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Bekaii-Saab T, Cho SK, Hocum B, Grossman J, Appukkuttan S, Babajanyan S, Marian M, Lee W, Barzi A, Yang M. Cost-effectiveness analysis of regorafenib dose optimization for refractory metastatic colorectal cancer. J Med Econ 2025; 28:655-663. [PMID: 40265856 DOI: 10.1080/13696998.2025.2496068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2025] [Revised: 04/16/2025] [Accepted: 04/17/2025] [Indexed: 04/24/2025]
Abstract
BACKGROUND New regimens have emerged as third-line or later therapies for metastatic colorectal cancer (mCRC), including regorafenib dose optimization (ReDO), trifluridine/tipiracil and bevacizumab (TAS-BEV) combination therapy, and fruquintinib. We evaluated relative cost-effectiveness of these therapies in patients with mCRC from a US payer's perspective. MATERIALS AND METHODS A partitioned survival model (PSM) was constructed to estimate total costs and quality-adjusted life years (QALYs). Clinical parameters were obtained from pivotal trials of the respective therapies and incremental cost-effectiveness ratios (ICERs) were estimated to assess relative cost-effectiveness of these treatments. Model robustness was assessed using deterministic (DSA) and probabilistic sensitivity analysis (PSA). Three scenario analyses were conducted: (1) assuming equal efficacy across treatments, (2) with prior exposure to anti-vascular endothelial growth factor (VEGF) therapy, and (3) alternative clinical inputs for fruquintinib from a different clinical trial. RESULTS Under the conventional willingness-to-pay (WTP) threshold in US ($150,000 per QALY gained), ReDO was cost-effective when compared with TAS-BEV and was dominant over fruquintinib. TAS-BEV was associated with an incremental QALY of 0.197 over ReDO, resulting in an ICER at $554,567 per QALY gained. The base case results were robust in DSA and PSA. Most influential parameters were treatment cost and effectiveness. In patients with prior anti-VEGF therapy, ReDO remained cost-effective compared to TAS-BEV and fruquintinib under the conventional WTP threshold. LIMITATION Differences in trial populations may affect the comparability of the outcomes. Sensitivity and scenario analyses were conducted to address these limitations. CONCLUSION ReDO was cost-effective compared with TAS-BEV from the US payer's perspective despite a higher QALY gain associated with TAS-BEV. ReDO was dominant over fruquintinib, consistently having a higher QALY gain and lower cost.
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Affiliation(s)
| | | | - Brian Hocum
- Bayer Healthcare Pharmaceuticals, Whippany, NJ, USA
| | | | | | | | | | | | - Afsaneh Barzi
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
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Xu K, Yu M, Sun Q, Zhang L, Qian X, Su D, Gong J, Shang J, Lin Y, Li X. Cost-effectiveness of PD-1 inhibitors combined with chemotherapy for first-line treatment of oesophageal squamous cell carcinoma in China: a comprehensive analysis. Ann Med 2025; 57:2482019. [PMID: 40131366 PMCID: PMC11938309 DOI: 10.1080/07853890.2025.2482019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2024] [Revised: 02/20/2025] [Accepted: 03/06/2025] [Indexed: 03/27/2025] Open
Abstract
BACKGROUND Programmed death-1 (PD-1) inhibitors combined with chemotherapy have become a standard first-line treatment for advanced oesophageal squamous cell carcinoma (ESCC). Given the high costs associated with immunotherapy, evaluating the cost-effectiveness of different PD-1 inhibitors in the Chinese healthcare setting is essential for guiding treatment decisions and policy development. METHODS A cost-effectiveness analysis was conducted comparing six PD-1 inhibitors-sintilimab, toripalimab, tislelizumab, camrelizumab, serplulimab, and pembrolizumab-combined with chemotherapy for first-line treatment of advanced ESCC. A partitioned survival model was used to calculate incremental cost-effectiveness ratios (ICERs) from healthcare system perspective, with a willingness-to-pay (WTP) threshold set at $36,598.19 per quality-adjusted life year (QALY). Sensitivity analyses were performed to evaluate the robustness of the results. RESULTS The ICERs for toripalimab, camrelizumab, pembrolizumab, serplulimab, sintilimab, and tislelizumab were $32,356.79/QALY, $48,410.64/QALY, $312,743.54/QALY, $121,200.84/QALY, $29,663.42/QALY, and $35,304.33/QALY, respectively. Sintilimab, toripalimab, and tislelizumab were below the WTP threshold. Among all regimens, the top three in life years (LYs) gained were toripalimab, serplulimab, and tislelizumab. Sensitivity analysis showed that utility values and drug prices were key factors influencing ICERs. Probabilistic analysis indicated that toripalimab, sintilimab, and tislelizumab had the highest probabilities of being cost-effective, at 83.1%, 81.4%, and 70.0%, respectively. CONCLUSION Sintilimab, toripalimab, and tislelizumab are the most cost-effective PD-1 inhibitors when combined with chemotherapy for the first-line treatment of advanced ESCC in China, with ICERs below the WTP threshold. While all six PD-1 inhibitors demonstrated clinical benefits, pembrolizumab and serplulimab were less favourable from a cost-effectiveness standpoint. Sensitivity analysis confirmed that drug prices and utility values are significant determinants of cost-effectiveness.
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Affiliation(s)
- Kai Xu
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
- Department of Pharmaceutical Regulatory Science and Pharmacoeconomics, School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Man Yu
- Department of Pharmaceutical Regulatory Science and Pharmacoeconomics, School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Qingli Sun
- Department of Pharmacy, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong Province, China
| | - Lingli Zhang
- School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu Province, China
| | - Xiaodan Qian
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
| | - Dan Su
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
| | - Jinhong Gong
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
| | - Jingjing Shang
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
| | - Yingtao Lin
- Department of Pharmaceutical Regulatory Science and Pharmacoeconomics, School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu Province, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- Clinical Medical Research Center, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Xin Li
- Department of Pharmacy, The Second People’s Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
- Department of Pharmaceutical Regulatory Science and Pharmacoeconomics, School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu Province, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- Department of Health Policy, School of Health Policy and Management, Nanjing Medical University, Nanjing, Jiangsu Province, China
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Chen Y, Zhou C, Zhang X, Chen M, Wang M, Zhang L, Chen Y, Huang L, Sun J, Wang D, Chen Y. Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer. Ann Med 2025; 57:2447930. [PMID: 39797413 PMCID: PMC11727174 DOI: 10.1080/07853890.2024.2447930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Revised: 11/26/2024] [Accepted: 12/12/2024] [Indexed: 01/13/2025] Open
Abstract
BACKGROUND Non-small cell lung cancer (NSCLC) is a fatal disease, and radioresistance is an important factor leading to treatment failure and disease progression. The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC. METHODS The weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) regression and random survival forest (RSF) were used to screen for prognostically relevant RRRGs. Multivariate Cox regression was used to construct a risk score model. Then, Immune landscape and drug sensitivity were evaluated. The biological functions exerted by the key gene LBH were verified by in vitro experiments. RESULTS Ninety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2 and TSPAN2) risk score model was established and demonstrated to be an independent prognostic factor in NSCLC on the basis of Cox regression analysis. The immune landscape and sensitivity to anti-tumour drugs showed significant disparities between patients categorized into different risk score subgroups. In vitro experiments indicated that overexpression of LBH enhanced the radiosensitivity of A549 cells, and knockdown LBH reversed the cytotoxicity induced by X-rays. CONCLUSION Our study developed an eight-gene risk score model with potential clinical value that can be adopted for choice of drug treatment and prognostic prediction. Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets.
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Affiliation(s)
- Yanliang Chen
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Chan Zhou
- Department of Geriatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Xiaoqiao Zhang
- Department of Geriatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Min Chen
- Department of Geriatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Meifang Wang
- Department of Pulmonary and Critical Care Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Lisha Zhang
- Department of Obstetrics, Tangshan Caofeidian District Hospital, Tangshan, Hebei, China
| | - Yanhui Chen
- Department of Neuroscience and Endocrinology, Tangshan Caofeidian District Hospital, Tangshan, Hebei, China
| | - Litao Huang
- Department of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Junjun Sun
- Department of Emergency Surgery, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, , China
| | - Dandan Wang
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Yong Chen
- Department of Radio-Chemotherapy, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China
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Yang X, Yue R, Zhao L, Wang Q. Integration of transcriptome and Mendelian randomization analyses in exploring the extracellular vesicle-related biomarkers of diabetic kidney disease. Ren Fail 2025; 47:2458767. [PMID: 39957315 PMCID: PMC11834810 DOI: 10.1080/0886022x.2025.2458767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 01/20/2025] [Accepted: 01/22/2025] [Indexed: 02/18/2025] Open
Abstract
BACKGROUND Diabetic Kidney Disease (DKD) is a common complication in patients with diabetes, and its pathogenesis remains incompletely understood. Recent studies have suggested that extracellular vesicles (EVs) may play a significant role in the initiation and progression of DKD. This study aimed to identify biomarkers associated with EVs in DKD through bioinformatics and Mendelian randomization (MR) analysis. METHODS This study utilized two DKD-related datasets, GSE96804 and GSE30528, alongside 121 exosome-related genes (ERGs) and 200 inflammation-related genes (IRGs). Differential analysis, co-expression network construction, and MR analysis were conducted to identify candidate genes. Machine learning techniques and expression validation were then employed to determine biomarkers. Finally, the potential mechanisms of action of these biomarkers were explored through Immunohistochemistry (IHC) staining, enrichment analysis, immune infiltration analysis, and regulatory network construction. RESULTS A total of 22 candidate genes were identified as causally linked to DKD. CMAS and RGS10 were identified as biomarkers, with both showing reduced expression in DKD. IHC confirmed low RGS10 expression, providing new insights into DKD management. CMAS was involved primarily in mitochondria-related pathways, while RGS10 was enriched in the extracellular matrix and associated pathways. Significant differences were observed in neutrophils and M2 macrophages between DKD and normal groups, correlating strongly with the biomarkers. CONCLUSION This study identified two EV-associated biomarkers, CMAS and RGS10, linked to DKD and elucidated their potential roles in disease progression. These results offer valuable insights for further exploration of DKD pathogenesis and the development of new therapeutic targets.
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Affiliation(s)
- Xu Yang
- Second Department of Nephrology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Rensong Yue
- Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Liangbin Zhao
- Second Department of Nephrology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Qiyue Wang
- Department of Pediatrics, Chengdu Jinniu Hospital of TCM, Chengdu, China
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Jiang W, Li L, Xia Y, Farooq S, Li G, Li S, Xu J, He S, Wu X, Huang S, Yuan J, Kong D. Neural dynamics of deception: insights from fMRI studies of brain states. Cogn Neurodyn 2025; 19:42. [PMID: 39991015 PMCID: PMC11842687 DOI: 10.1007/s11571-025-10222-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 01/14/2025] [Accepted: 01/16/2025] [Indexed: 02/25/2025] Open
Abstract
Deception is a complex behavior that requires greater cognitive effort than truth-telling, with brain states dynamically adapting to external stimuli and cognitive demands. Investigating these brain states provides valuable insights into the brain's temporal and spatial dynamics. In this study, we designed an experiment paradigm to efficiently simulate lying and constructed a temporal network of brain states. We applied the Louvain community clustering algorithm to identify characteristic brain states associated with lie-telling, inverse-telling, and truth-telling. Our analysis revealed six representative brain states with unique spatial characteristics. Notably, two distinct states-termed truth-preferred and lie-preferred-exhibited significant differences in fractional occupancy and average dwelling time. The truth-preferred state showed higher occupancy and dwelling time during truth-telling, while the lie-preferred state demonstrated these characteristics during lie-telling. Using the average z-score BOLD signals of these two states, we applied generalized linear models with elastic net regularization, achieving a classification accuracy of 88.46%, with a sensitivity of 92.31% and a specificity of 84.62% in distinguishing deception from truth-telling. These findings revealed representative brain states for lie-telling, inverse-telling, and truth-telling, highlighting two states specifically associated with truthful and deceptive behaviors. The spatial characteristics and dynamic attributes of these brain states indicate their potential as biomarkers of cognitive engagement in deception. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-025-10222-4.
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Affiliation(s)
- Weixiong Jiang
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
- Nanbei Lake Institute for Artificial Intelligence in Medicine, Haiyan, Zhejiang China
| | - Lin Li
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Yulong Xia
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Sajid Farooq
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Gang Li
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Shuaiqi Li
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Jinhua Xu
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Sailing He
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Xiangyu Wu
- The Research Center for Children’s Literature, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Shoujun Huang
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Jing Yuan
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
| | - Dexing Kong
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang China
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Xie J, He L, Qin S. Integrated bioinformatics analysis identifies neutrophils and villous cytotrophoblasts infiltration characterized by BLC6 upregulation as associated with the co-occurrence of gestational diabetes mellitus and pre-eclampsia. Hypertens Pregnancy 2025; 44:2475814. [PMID: 40122115 DOI: 10.1080/10641955.2025.2475814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 02/24/2025] [Indexed: 03/25/2025]
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) patients are one of the important high-risk groups for the development of pre-eclampsia (PE). The pathogenesis of PE in GDM patients is not fully understood. This study aims to identify hub genes and pathways associated with the co-occurrence of GDM and PE. METHODS The matrix files of GDM and PE datasets were downloaded from GEO to identify differentially expressed genes (DEGs). The common DEGs were predicted for functional analysis through GO and KEGG analysis. A protein-protein interaction (PPI) network was constructed to determine the common hub genes for GDM and PE. Diagnostic hub genes were obtained through regression modeling and ROC analysis, and validated in publicly available datasets. The differences in immune infiltration between GDM and PE were analyzed. The expression and role of common hub genes in the co-occurrence of GDM and PE were explored through analysis of single-cell sequencing data. RESULTS A total of 104 DEGs were identified between GDM and PE. These common DEGs were found to be involved in mucosal immune response and the JAK-STAT signaling pathway. A total of 27 common hub genes were identified for both GDM and PE. BCL6, DNAH9, and SCG2 were identified as potential diagnostic biomarkers for PE. BCL6 showed high expression in neutrophils and villous cytotrophoblasts (VCTs) in both PE and GDM. CONCLUSION This study identified BCL6, DNAH9, and SCG2 as common hub genes in GDM and PE. BCL6 is expected to be a new target for the diagnosis and treatment of GDM concurrent with PE.
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Affiliation(s)
- Jingjing Xie
- Department of Obstetrics and Gynecology, Guangzhou iBorn Women's & Children's Hospital, Guangzhou, Guangdong, China
| | - Le He
- Department of Obstetrics and Gynecology, Guangzhou iBorn Women's & Children's Hospital, Guangzhou, Guangdong, China
| | - Shuang Qin
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China
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Aboulalazm FA, Kazen AB, deLeon O, Müller S, Saravia FL, Lozada-Fernandez V, Hadiono MA, Keyes RF, Smith BC, Kellogg SL, Grobe JL, Kindel TL, Kirby JR. Reutericyclin, a specialized metabolite of Limosilactobacillus reuteri, mitigates risperidone-induced weight gain in mice. Gut Microbes 2025; 17:2477819. [PMID: 40190120 PMCID: PMC11980487 DOI: 10.1080/19490976.2025.2477819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 01/14/2025] [Accepted: 03/05/2025] [Indexed: 04/11/2025] Open
Abstract
The role of xenobiotic disruption of microbiota, corresponding dysbiosis, and potential links to host metabolic diseases are of critical importance. In this study, we used a widely prescribed antipsychotic drug, risperidone, known to influence weight gain in humans, to induce weight gain in C57BL/6J female mice. We hypothesized that microbes essential for maintaining gut homeostasis and energy balance would be depleted following treatment with risperidone, leading to enhanced weight gain relative to controls. Thus, we performed metagenomic analyses on stool samples to identify microbes that were excluded in risperidone-treated animals but remained present in controls. We identified multiple taxa including Limosilactobacillus reuteri as a candidate for further study. Oral supplementation with L. reuteri protected against risperidone-induced weight gain (RIWG) and was dependent on cellular production of a specialized metabolite, reutericyclin. Further, synthetic reutericyclin was sufficient to mitigate RIWG. Both synthetic reutericyclin and L. reuteri restored energy balance in the presence of risperidone to mitigate excess weight gain and induce shifts in the microbiome associated with leanness. In total, our results identify reutericyclin production by L. reuteri as a potential probiotic to restore energy balance induced by risperidone and to promote leanness.
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Affiliation(s)
- Fatima A. Aboulalazm
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Alexis B. Kazen
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Orlando deLeon
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Susanne Müller
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Fatima L. Saravia
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Matthew A. Hadiono
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Robert F. Keyes
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
- Program in Chemical Biology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian C. Smith
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
- Program in Chemical Biology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Stephanie L. Kellogg
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Justin L. Grobe
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, USA
- Comprehensive Rodent Metabolic Phenotyping Core, Medical College of Wisconsin, Milwaukee, WI, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Tammy L. Kindel
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, WI, USA
- Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - John R. Kirby
- Department of Microbiology & Immunology, Medical College of Wisconsin, Milwaukee, WI, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, WI, USA
- Center for Microbiome Research, Medical College of Wisconsin, Milwaukee, WI, USA
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Zhang T, Chen Y, Xiang Z. Machine learning-based integration develops a disulfidptosis-related lncRNA signature for improving outcomes in gastric cancer. ARTIFICIAL CELLS, NANOMEDICINE, AND BIOTECHNOLOGY 2025; 53:1-13. [PMID: 39701937 DOI: 10.1080/21691401.2024.2440415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 11/05/2024] [Accepted: 11/25/2024] [Indexed: 12/21/2024]
Abstract
Gastric cancer remains one of the deadliest cancers globally due to delayed detection and limited treatment options, underscoring the critical need for innovative prognostic methods. Disulfidptosis, a recently discovered programmed cell death triggered by disulphide stress, presents a fresh avenue for therapeutic exploration. This research examines disulfidptosis-related long noncoding RNAs (DRLs) in gastric cancer, with the goal of leveraging these lncRNAs as potential markers to enhance patient outcomes and treatment approaches. Comprehensive genomic and clinical data from stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA). Employing least absolute shrinkage and selection operator (LASSO) regression analysis, a prognostic model was devised incorporating five key DRLs to forecast survival rates. The effectiveness of this model was validated using Kaplan-Meier survival plots, receiver operating characteristic (ROC) curves, and extensive functional enrichment studies. The importance of select lncRNAs and the expression variability of genes tied to disulfidptosis were validated via quantitative real-time PCR (qRT-PCR) and Western blot tests, establishing a solid foundation for their prognostic utility. Analyses of functional enrichment and tumour mutation burden highlighted the biological importance of these DRLs, connecting them to critical cancer pathways and immune responses. These discoveries broaden our comprehension of the molecular framework of gastric cancer and bolster the development of tailored treatment plans, highlighting the substantial role of DRLs in clinical prognosis and therapeutic intervention.
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Affiliation(s)
- Tianze Zhang
- Department of Gastrointestinal Surgery, The Second Hospital of Shandong University, Jinan, China
| | - Yuqing Chen
- Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, China
| | - Zhiping Xiang
- Head and Neck Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Thienpont A, Cho E, Williams A, Meier MJ, Yauk CL, Beal MA, Van Goethem F, Rogiers V, Vanhaecke T, Mertens B. In vitro to in vivo extrapolation modeling to facilitate the integration of transcriptomics data into genotoxicity assessment. Toxicology 2025; 515:154165. [PMID: 40288562 DOI: 10.1016/j.tox.2025.154165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2025] [Revised: 04/18/2025] [Accepted: 04/23/2025] [Indexed: 04/29/2025]
Abstract
In vitro transcriptomics holds promise for high-throughput, human-relevant data but is not yet integrated into regulatory decision-making due to the lack of standardized approaches. For genotoxicity assessment, transcriptomic biomarkers such as GENOMARK and TGx-DDI facilitate qualitative and quantitative analysis of complex in vitro transcriptomic datasets. However, advancing their use in quantitative testing requires standardized methods for deriving transcriptomic Points of Departure (tPoDs) and linking them to in vivo responses. Herein, we investigated different approaches to calculate tPoDs and applied in vitro to in vivo extrapolation to obtain administered equivalent doses (AEDs). Human HepaRG cells were exposed for 72 h to 10 known in vivo genotoxicants (glycidol, methyl methanesulfonate, nitrosodimethylamine, 4-nitroquinoline-N-oxide, aflatoxin B1, colchicine, cyclophosphamide, mitomycin C, ethyl methanesulfonate, and N-Nitroso-N-ethylurea) from the highest concentration that induces up to 50 % cytotoxicity through a range of lower concentrations. Gene expression data was generated using a customized version of the TempO-Seq® human S1500 + gene panel. The GENOMARK and TGx-DDI biomarkers produced genotoxic calls for all of these reference genotoxicants. Next, we performed benchmark concentration (BMC) modeling to generate both genotoxicity-specific biomarker (tPoDbiomarkers) and generic tPoDs (tPoD S1500+). High-throughput toxicokinetic models estimated the human AEDs for these tPoDs, which were compared with (a) previously reported genotoxicity-specific AEDs from other New Approach Methodologies, and (b) in vivo PoDs from animal studies. We found that the generic AEDs were more conservative than genotoxicity-specific biomarker AEDs. For six of the nine genotoxicants, transcriptomic AEDs were lower than the in vivo PoDs; refined kinetic models may improve predictions. Overall, in vitro transcriptomic data in HepaRG cells provide protective estimates of in vivo genotoxic concentrations, consistent with other in vitro genotoxicity testing systems.
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Affiliation(s)
- Anouck Thienpont
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), Brussels 1090, Belgium; Department of Chemical and Physical Health Risks, Sciensano, Brussels 1050, Belgium.
| | - Eunnara Cho
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Matthew J Meier
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Marc A Beal
- Bureau of Chemical Safety, Health Products and Food Branch, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Freddy Van Goethem
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), Brussels 1090, Belgium
| | - Vera Rogiers
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), Brussels 1090, Belgium
| | - Tamara Vanhaecke
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), Brussels 1090, Belgium
| | - Birgit Mertens
- Department of Chemical and Physical Health Risks, Sciensano, Brussels 1050, Belgium.
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10
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Skowronek MF, Pietroroia S, Silvera D, Ford M, Cassina A, Lecumberry F, Sapiro R. Morphometric analysis of the sperm midpiece during capacitation. Tissue Cell 2025; 95:102866. [PMID: 40157222 DOI: 10.1016/j.tice.2025.102866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 03/14/2025] [Accepted: 03/15/2025] [Indexed: 04/01/2025]
Abstract
In mammalian sperm, mitochondria are very densely packed and form a helical sheath in the midpiece of the flagellum. Mitochondria from somatic cells can rapidly change shape to adapt to environmental conditions. During capacitation, mammalian spermatozoa undergo morphological and physiological changes to acquire fertilization ability, evidenced by changes in sperm motility patterns (hyperactivation) and the ability to perform the acrosome reaction. Whether there are changes in sperm mitochondrial morphology during capacitation is unknown. This work aimed to quantify morphometric changes in the sperm midpiece during capacitation. Using mitochondrial fluorescent probes and a combination of freely available software, we quantified the dimensions and fluorescence intensity of the midpiece. After capacitation, the area occupied by the mitochondria decreased due to a reduction in the width but not the length of the midpiece. The decrease in the area of the midpiece occurred in spermatozoa that underwent the acrosome reaction, suggesting a reorganization of the mitochondria during capacitation. Ultrastructural analysis supported these results. The application of image processing to fluorescence microscopy images may help to identify morphological changes during capacitation.
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Affiliation(s)
- M F Skowronek
- UnidadAcadémica Departamento de Histología y Embriología, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - S Pietroroia
- UnidadAcadémica Departamento de Histología y Embriología, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - D Silvera
- Departamento de Procesamiento de Señales, Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay
| | - M Ford
- UnidadAcadémica Departamento de Histología y Embriología, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - A Cassina
- Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - F Lecumberry
- Departamento de Procesamiento de Señales, Facultad de Ingeniería, Universidad de la República, Montevideo, Uruguay
| | - R Sapiro
- UnidadAcadémica Departamento de Histología y Embriología, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay.
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11
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Truong KT, Wambaugh JF, Kapraun DF, Davidson-Fritz SE, Eytcheson S, Judson RS, Paul Friedman K. Interpretation of thyroid-relevant bioactivity data for comparison to in vivo exposures: A prioritization approach for putative chemical inhibitors of in vitro deiodinase activity. Toxicology 2025; 515:154157. [PMID: 40262668 DOI: 10.1016/j.tox.2025.154157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2025] [Revised: 04/16/2025] [Accepted: 04/17/2025] [Indexed: 04/24/2025]
Abstract
Many ToxCast assay endpoints can be mapped to molecular initiating events (MIEs) within the thyroid adverse outcome pathway (AOP) network. Herein, we provide a framework for interpretation of thyroid-relevant bioactivity data across MIEs. As a proof-of-concept, we used ToxCast data on the inhibition of deiodinase (DIO) enzymes, which convert thyroid hormones between active and inactive forms, and identified substances most likely to inhibit DIO enzymes. Data from 4 relevant cell-free in vitro assays are available for > 2000 chemicals in single concentration screening and 327 chemicals in multi-concentration screening. We filtered to identify chemicals that demonstrated inhibition for each DIO enzyme less likely to be confounded by assay interference, refining the list of putatively active chemicals from 523 to 135. In vitro bioactivity data were then used to estimate administered equivalent doses (AEDs) using a novel high-throughput toxicokinetic (HTTK) model for in vitro to in vivo extrapolation (IVIVE) of dose. To consider potential thyroid-disrupting activity in an appropriate life-stage and dose context, we extended an existing human maternal-fetal HTTK model to allow for simulations involving the first trimester of pregnancy. For many chemicals, using modeled fetal tissue concentrations produced lower AED estimates than using modeled maternal plasma concentrations alone, at least partially due to conservative assumptions in our HTTK model of complete gestation. This extensible approach for MIE groups of thyroid-related bioactivity data from ToxCast may inform further screening or analyses for potential adverse outcomes during pregnancy and development.
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Affiliation(s)
- K T Truong
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, USA
| | - J F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA
| | - D F Kapraun
- Center for Public Health and Environmental AssessmentUS EPA, Research Triangle Park, NC 27711, USA
| | - S E Davidson-Fritz
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA
| | - S Eytcheson
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, USA
| | - R S Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA
| | - K Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, US. Environmental Protection Agency (multiple locations), Washington, DC, USA.
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12
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Huang S, Ma Z, Fan F. Unraveling the core symptoms across distinct trajectories of problematic Internet use among 27,577 adolescents: Cross-lagged panel network analyses. Addict Behav 2025; 167:108356. [PMID: 40203462 DOI: 10.1016/j.addbeh.2025.108356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2024] [Revised: 02/24/2025] [Accepted: 04/03/2025] [Indexed: 04/11/2025]
Abstract
Problematic Internet Use (PIU) often begins in adolescence and develops along diverse trajectories. Understanding the interaction between PIU symptoms and identifying the core PIU symptoms that drive distinct trajectories among adolescents are crucial. We employed cross-lagged panel network analyses to examine temporal relationships of PIU symptoms among Chinese adolescents across four developmental trajectories over two time points. A total of 27,577 adolescents (Mean age = 13.8, SD = 1.5) participated in this study. Demographic variables and PIU symptoms were collected from December 17 to 26, 2021 (T1) and from May 17 to June 5, 2022 (T2). The symptom "Reluctant to stop" in the resilient group and "Uncontrollable checking" in the alleviating group at T1 were most predictive of remission of other symptoms at T2, while "Empty life" in the deteriorating group and "Feeling of missing" in the persistent dysfunction group were most strongly associated with worsening of other PIU symptoms. Improving self-control is likely to promote healthy and beneficial Internet use among adolescents, while enhancing social connection and fostering exercise habits may help mitigate negative emotions and reduce the emergence of additional PIU symptoms among adolescents who have developed PIU.
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Affiliation(s)
- Shuiqing Huang
- Department of Pedagogy and Educational Science, Faculty of Behavioural and Social Sciences, University of Groningen, Netherlands
| | - Zijuan Ma
- School of Psychology, South China Normal University, Guangzhou, China
| | - Fang Fan
- School of Psychology, South China Normal University, Guangzhou, China.
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13
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Kucukakcali Z, Akbulut S, Colak C. Prediction of genomic biomarkers for endometriosis using the transcriptomic dataset. World J Clin Cases 2025; 13:104556. [DOI: 10.12998/wjcc.v13.i20.104556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2024] [Revised: 03/03/2025] [Accepted: 03/13/2025] [Indexed: 04/09/2025] Open
Abstract
BACKGROUND Endometriosis is a clinical condition characterized by the presence of endometrial glands outside the uterine cavity. While its incidence remains mostly uncertain, endometriosis impacts around 180 million women worldwide. Despite the presentation of several epidemiological and clinical explanations, the precise mechanism underlying the disease remains ambiguous. In recent years, researchers have examined the hereditary dimension of the disease. Genetic research has aimed to discover the gene or genes responsible for the disease through association or linkage studies involving candidate genes or DNA mapping techniques.
AIM To identify genetic biomarkers linked to endometriosis by the application of machine learning (ML) approaches.
METHODS This case-control study accounted for the open-access transcriptomic data set of endometriosis and the control group. We included data from 22 controls and 16 endometriosis patients for this purpose. We used AdaBoost, XGBoost, Stochasting Gradient Boosting, Bagged Classification and Regression Trees (CART) for classification using five-fold cross validation. We evaluated the performance of the models using the performance measures of accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value and F1 score.
RESULTS Bagged CART gave the best classification metrics. The metrics obtained from this model are 85.7%, 85.7%, 100%, 75%, 75%, 100% and 85.7% for accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value and F1 score, respectively. Based on the variable importance of modeling, we can use the genes CUX2, CLMP, CEP131, EHD4, CDH24, ILRUN, LINC01709, HOTAIR, SLC30A2 and NKG7 and other transcripts with inaccessible gene names as potential biomarkers for endometriosis.
CONCLUSION This study determined possible genomic biomarkers for endometriosis using transcriptomic data from patients with/without endometriosis. The applied ML model successfully classified endometriosis and created a highly accurate diagnostic prediction model. Future genomic studies could explain the underlying pathology of endometriosis, and a non-invasive diagnostic method could replace the invasive ones.
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Affiliation(s)
- Zeynep Kucukakcali
- Department of Biostatistics and Medical Informatics, Inonu University Faculty of Medicine, Malatya 44280, Türkiye
| | - Sami Akbulut
- Department of Biostatistics and Medical Informatics, Inonu University Faculty of Medicine, Malatya 44280, Türkiye
- Surgery and Liver Transplant Institute, Inonu University Faculty of Medicine, Malatya 44280, Türkiye
| | - Cemil Colak
- Department of Biostatistics and Medical Informatics, Inonu University Faculty of Medicine, Malatya 44280, Türkiye
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14
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Zhang Z, Robinson L, Whelan R, Jollans L, Wang Z, Nees F, Chu C, Bobou M, Du D, Cristea I, Banaschewski T, Barker GJ, Bokde ALW, Grigis A, Garavan H, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Orfanos DP, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Winterer J, Broulidakis MJ, van Noort BM, Stringaris A, Penttilä J, Grimmer Y, Insensee C, Becker A, Zhang Y, King S, Sinclair J, Schumann G, Schmidt U, Desrivières S. Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder. J Affect Disord 2025; 379:889-899. [PMID: 39701465 PMCID: PMC7617286 DOI: 10.1016/j.jad.2024.12.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 11/28/2024] [Accepted: 12/14/2024] [Indexed: 12/21/2024]
Abstract
BACKGROUND Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD). METHODS Case-control samples (aged 18-25 years), including participants with Anorexia Nervosa (AN), Bulimia Nervosa (BN), MDD, AUD, and matched controls, were used for diagnostic classification. For risk prediction, we used a longitudinal population-based sample (IMAGEN study), assessing adolescents at ages 14, 16 and 19. Regularized logistic regression models incorporated broad data domains spanning psychopathology, personality, cognition, substance use, and environment. RESULTS The classification of EDs was highly accurate, even when excluding body mass index from the analysis. The area under the receiver operating characteristic curves (AUC-ROC [95 % CI]) reached 0.92 [0.86-0.97] for AN and 0.91 [0.85-0.96] for BN. The classification accuracies for MDD (0.91 [0.88-0.94]) and AUD (0.80 [0.74-0.85]) were also high. The models demonstrated high transdiagnostic potential, as those trained for EDs were also accurate in classifying AUD and MDD from healthy controls, and vice versa (AUC-ROCs, 0.75-0.93). Shared predictors, such as neuroticism, hopelessness, and symptoms of attention-deficit/hyperactivity disorder, were identified as reliable classifiers. In the longitudinal population sample, the models exhibited moderate performance in predicting the development of future ED symptoms (0.71 [0.67-0.75]), depressive symptoms (0.64 [0.60-0.68]), and harmful drinking (0.67 [0.64-0.70]). CONCLUSIONS Our findings demonstrate the potential of combining multi-domain data for precise diagnostic and risk prediction applications in psychiatry.
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Affiliation(s)
- Zuo Zhang
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK; School of Psychology, Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Lauren Robinson
- Department of Psychological Medicine, Centre for Research in Eating and Weight Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK; Oxford Institute of Clinical Psychology Training and Research, Oxford University, Oxford, UK
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Lee Jollans
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Zijian Wang
- School of Computer Science and Technology, Donghua University, Shanghai, China
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany; Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany; Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | - Congying Chu
- University of Chinese Academy of Sciences, 100190 Beijing, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China
| | - Marina Bobou
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK; Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Dongping Du
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA
| | - Ilinca Cristea
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, VT, USA
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, France; AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Developmental trajectories & psychiatry", Université Paris-Saclay, Université Paris Cité, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli UMR9010, Gif-sur-Yvette, France; Psychiatry Department, EPS Barthélemy Durand, Etampes, France
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Jeanne Winterer
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany; Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - M John Broulidakis
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Psychology, College of Science, Northeastern University, Boston, MA, USA
| | - Betteke Maria van Noort
- Department of Psychology, MSB Medical School Berlin, Rüdesheimer Str. 50, 14197 Berlin, Germany
| | - Argyris Stringaris
- Division of Psychiatry and Department of Clinical, Educational & Health Psychology, University College London, UK
| | - Jani Penttilä
- Department of Social and Health Care, Psychosocial Services Adolescent Outpatient Clinic Kauppakatu 14, Lahti, Finland
| | - Yvonne Grimmer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Corinna Insensee
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Andreas Becker
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Yuning Zhang
- Psychology Department, B44 University Rd, University of Southampton, Southampton SO17 1PS, UK
| | - Sinead King
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK; School of Medicine, Centre for Neuroimaging, Cognition and Genomics, National University of Ireland (NUI), Galway, Ireland; Beaumont Hospital, Royal College of Surgeons, Ireland
| | - Julia Sinclair
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany; Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Ulrike Schmidt
- Department of Psychological Medicine, Centre for Research in Eating and Weight Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; South London and Maudsley NHS Foundation Trust, London, UK
| | - Sylvane Desrivières
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK.
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15
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Lynn SG, Schultz IR, Matten SR, Patel PR, Watson SL, Yueh YL, Black SR, Wetmore BA. Cross-species comparisons of plasma binding and considerations for data evaluation. Toxicol In Vitro 2025; 106:106036. [PMID: 40023338 DOI: 10.1016/j.tiv.2025.106036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Revised: 02/12/2025] [Accepted: 02/22/2025] [Indexed: 03/04/2025]
Abstract
The US Environmental Protection Agency is increasingly employing new approach methods (NAMs), including in vitro plasma binding and hepatocyte clearance experiments to collect chemical-species specific data. This paper presents data from plasma binding experiments using rapid equilibrium dialysis (RED) devices and plasma from humans, rats, and rainbow trout with a 4-h incubation time. A total of 54 chemicals, utilizing two concentrations, were tested across the three species resulting in 238 chemical-species specific datasets. Mass balance controls for chemical plasma stability and dialysis system recovery were used to evaluate the datasets and almost 40 % of the datasets (92/238 datasets) produced quantitative measurements. Cross-species comparisons and evaluations of the impact of physicochemical properties on chemical-assay performance were also evaluated. Comparisons of human-rat plasma binding revealed rat plasma generally demonstrated higher fup values for chemicals than human. While fup values in trout plasma were frequently lower than rat or human plasma. A comparison with literature data was performed and correlations between plasma binding, expressed as fraction unbound in plasma (fup), and log Kow across all three species indicate that the strongest relationship occurs at log Kow values between 1.5 and 4. The obtained datasets exhibited a wide range of behaviors, emphasizing the need for a robust approach to data quality assessment. The broader analysis of fup values indicates that chemicals with log Kow > 4.5 will be highly bound (fup ≤ 0.0001), difficult to measure, and have low reproducibility across laboratories, suggesting that use of different methods may be needed across different physicochemical properties.
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Affiliation(s)
- Scott G Lynn
- US Environmental Protection Agency, Office of Pesticide Programs, William Jefferson Clinton Building, 1200 Pennsylvania Avenue NW, Washington, DC 20460, USA.
| | - Irvin R Schultz
- Environmental and Fisheries Sciences Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA.
| | - Sharlene R Matten
- US Environmental Protection Agency, Office of Program Support, William Jefferson Clinton Building, 1200 Pennsylvania Avenue NW, Washington, DC 20460, USA.
| | - Purvi R Patel
- RTI International, Discovery Sciences, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA.
| | - Scott L Watson
- RTI International, Discovery Sciences, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA.
| | - Yun Lan Yueh
- RTI International, Discovery Sciences, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA.
| | - Sherry R Black
- RTI International, Discovery Sciences, 3040 East Cornwallis Road, Research Triangle Park, NC 27709, USA.
| | - Barbara A Wetmore
- US Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA.
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16
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Ji X, Feng N, Zhao T, Cui L. Protective and risk factors in problematic mobile phone use among adolescents: A three-wave longitude study. Addict Behav 2025; 165:108299. [PMID: 39970598 DOI: 10.1016/j.addbeh.2025.108299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 02/12/2025] [Accepted: 02/14/2025] [Indexed: 02/21/2025]
Abstract
Adolescents' problematic mobile phone use (PMPU) has become increasingly severe. This study examined the changes in relationships between dimensions of PMPU, protective (positive psychological capital, i.e., optimism, hope, resilience, core self-evaluation) and risk (psychological distress, i.e., anxiety, depression, loneliness, and stress) factors within the network, aiming to identify the most influential factors over time and find the longitudinal predictive relationships between the factors and PMPU. A total of 1,170 Chinese adolescents participated over three waves (T1: January 2023, T2: August 2023, T3: February 2024). Cross-section network analysis showed that "core self-evaluation", "depression", "hope", "loss of control", and "stress_P" were the central nodes. "Stress_N" (sense of losing control and negative affective reactions) in risk factors and "affect control" (ability to regulate emotions) in protective factors were the bridge symptoms in the network across three timepoints. As shown in network comparison, the global strength of the network remained stable from T1 to T2 but increased from T2 to T3. The edge strength between "family support", "anxiety" and the nodes of PMPU weakened across the time. While, correlations between "loneliness", "goal planning", "positive thinking", "affect control" and PMPU nodes strengthened. The relationship between "Stress_N" and PMPU initially increasing before decreasing. Longitudinal cross-lagged network analysis revealed that "negative life consequence" and "craving" in PMPU strongly predicted protective/risk factors, while "hope," "affect control," and "core self-evaluation" were most susceptible to prediction. The findings highlight the significant role of "core self-evaluation" and "stress_N" in the development of adolescents' PMPU and the negative results of PMPU. Additionally, the changes in the network over time suggest that the factors influencing PMPU evolve, with various protective/risk factors gaining or losing significance at different stages. The results of CLPN emphasize the negative outcome of PMPU. Therefore, targeting interventions on the internalized symptoms may help alleviate the severity of PMPU among adolescents.
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Affiliation(s)
- Xiaoqing Ji
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Ningning Feng
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Shanghai Centre for Brain Science and Brain-Inspired Technology, Shanghai 200062, China
| | - Tong Zhao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
| | - Lijuan Cui
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Shanghai Centre for Brain Science and Brain-Inspired Technology, Shanghai 200062, China.
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17
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Pistone D, Bortolussi S, Fatemi S, Marcaccio B, Bagnale L, Pezzi C, Paganelli M, Ramos RL, Formicola E, Sica R, Buompane R, Porzio G, Manti L, Gialanella L, Vercesi V, Postuma I. A GATE Monte Carlo study on ICRP110 phantoms for BNCT dosimetry evaluation. Appl Radiat Isot 2025; 220:111724. [PMID: 40010065 DOI: 10.1016/j.apradiso.2025.111724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 01/05/2025] [Accepted: 02/11/2025] [Indexed: 02/28/2025]
Abstract
Boron Neutron Capture Therapy (BNCT) is attracting renewed attention due to advancements in compact proton accelerators for the production of neutron beams, and new BNCT facilities are being planned all around the world. A key aspect in BNCT treatments will be patient dosimetry, particularly given the complex radiation field created by neutron interactions with biological tissues. This study aimed at developing a prototype of BNCT dosimetry workflow based on Monte Carlo (MC) simulations for the GATE toolkit. Investigating the feasibility of performing voxel-level dosimetry through full MC transport in terms of simulation time and statistical uncertainties, the ICRP110 male and female adult voxelized phantoms were used to model the human body, adding the possibility to set in their organs user-defined concentrations of 10B. Irradiation simulations of the head district with two monoenergetic neutron beams and with a realistic clinical neutron spectrum were carried out. The absorbed dose matrices for each simulation, assuming both no 10B and then a systemic distribution of 15 ppm, were scored separating the contributions from 7Li, alpha particles, protons and photons. Results showed the expected increase, in presence of 10B distribution, of the 7Li and alpha average dose components in organs of interest of the head, such as brain, reaching in it about 1.3 and 2.3 fGy/evt, respectively, in presence of 15 ppm of 10B. The present prototype of dosimetric workflow, whose macros and files are freely shared for interested users and developers, will serve as a basis for future studies aiming at simulating similar BNCT scenarios with larger statistics, for example by exploiting high computing resources, to verify the obtained results with lower statistical uncertainties and possibly optimize the workflow to reduce simulation times while ensuring suitable dosimetric accuracy.
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Affiliation(s)
- Daniele Pistone
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy.
| | - Silva Bortolussi
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy; Università di Pavia, Dipartimento di Fisica, Pavia, Italy
| | - Setareh Fatemi
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy
| | - Barbara Marcaccio
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy; Università di Pavia, Dipartimento di Fisica, Pavia, Italy; National University of San Martín (UNSAM), Buenos Aires, Argentina
| | - Laura Bagnale
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy
| | - Cristina Pezzi
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy; Università di Pavia, Dipartimento di Fisica, Pavia, Italy
| | | | - Ricardo Luis Ramos
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy
| | - Emilia Formicola
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy
| | - Rosa Sica
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy
| | - Raffaele Buompane
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy
| | - Giuseppe Porzio
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy
| | - Lorenzo Manti
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy; Dipartimento di Fisica "Ettore Pancini", Università degli Studi di Napoli "Federico II", Napoli, Italy
| | - Lucio Gialanella
- Università degli Studi della Campania "Luigi Vanvitelli", Dipartimento di Matematica e Fisica, Caserta, Italy; Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, Napoli, Italy
| | - Valerio Vercesi
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy
| | - Ian Postuma
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Pavia, Pavia, Italy
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18
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Ion A, Georgescu A, Iliescu D, Nye CD, Miu A. Events-Affect-Personality: A Daily Diary Investigation of the Mediating Effects of Affect on the Events-Personality Relationship. Psychol Rep 2025; 128:1861-1886. [PMID: 37148303 DOI: 10.1177/00332941231175363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Our 10-day diary investigation anchored in dynamic personality theories, such as Whole Trait Theory examined (a) whether within-person variability in two broad personality traits Extraversion and Neuroticism is consistently predicted by daily events, (b) whether positive and negative affect, respectively partly mediate this relationship and (c) the lagged relationships between events, and next day variations in affect and personality. Results revealed that personality exhibited significant within-person variability, that positive and negative affect partly mediate the relationship between events and personality, affect accounting for up to 60% of the effects of events on personality. Additionally, we identified that event-affect congruency was accountable for larger effects compared to event-affect non-congruency.
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Affiliation(s)
- Andrei Ion
- University of Bucharest, Bucharest, Romania
| | | | | | - Christopher D Nye
- Department of Psychology, Michigan State University, 316 Physics Rd., East Lansing, MI 48824, USA
| | - Andrei Miu
- Babeș-Bolyai University, Cluj-Napoca, Romania
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19
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Kim IE, Oduor C, Stamp J, Luftig MA, Moormann AM, Crawford L, Bailey JA. Incorporation of Epstein-Barr viral variation implicates significance of Latent Membrane Protein 1 in survival prediction and prognostic subgrouping in Burkitt lymphoma. Int J Cancer 2025; 156:2188-2199. [PMID: 40047459 PMCID: PMC11971018 DOI: 10.1002/ijc.35384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 02/06/2025] [Accepted: 02/10/2025] [Indexed: 04/05/2025]
Abstract
Although Epstein-Barr virus (EBV) plays a role in Burkitt lymphoma (BL) tumorigenesis, it is unclear if EBV genetic variation impacts clinical outcomes. From 130 publicly available whole-genome tumor sequences of EBV-positive BL patients, we used least absolute shrinkage and selection operator (LASSO) regression and Bayesian variable selection models within a Cox proportional hazards framework to select the top EBV variants, putative driver genes, and clinical features associated with patient survival time. These features were incorporated into survival prediction and prognostic subgrouping models. Our model yielded 22 EBV variants, including seven in latent membrane protein 1 (LMP1), as most associated with patient survival time. Using the top EBV variants, driver genes, and clinical features, we defined three prognostic subgroups that demonstrated differential survival rates, laying the foundation for incorporating EBV variants such as those in LMP1 as predictive biomarker candidates in future studies.
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Affiliation(s)
- Isaac E. Kim
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- The Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Cliff Oduor
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
| | - Julian Stamp
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
| | - Micah A. Luftig
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, North Carolina, USA
- Center for Virology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Ann M. Moormann
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Lorin Crawford
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- Microsoft Research, Cambridge, MA, USA
| | - Jeffrey A. Bailey
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- The Warren Alpert Medical School, Brown University, Providence, RI, USA
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
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20
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Couldrick JM, Woodward AP, Lynch JT, Brown NAT, Barton CJ, Scarvell JM. The relationship between radiological OA severity or body weight and outcomes following a structured education and exercise therapy program (GLA:D®) for people with knee osteoarthritis. Musculoskelet Sci Pract 2025; 77:103307. [PMID: 40101458 DOI: 10.1016/j.msksp.2025.103307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Revised: 02/25/2025] [Accepted: 03/04/2025] [Indexed: 03/20/2025]
Abstract
BACKGROUND Clinicians may presume people with higher bodyweight or greater OA severity do not respond to exercise therapy for knee osteoarthritis (OA), but few studies have examined this. OBJECTIVE To examine the relationship between radiographical OA severity or bodyweight and pain and functional outcomes following a structured education and exercise therapy program (Good Life with OsteoArthritis from Denmark: GLA:D®). METHODS 33 participants with knee OA were assessed at baseline and week 8 following GLA:D®. Outcomes were pain (Visual analogue scale (VAS) 0-100), Knee Injury and Osteoarthritis Outcome Score-12 (KOOS-12 total), 40 m-fast-paced walk and 30-s chair stand. Multilevel models were used to define the severity of OA in medial, lateral and patellofemoral compartments using the Kellgren-Lawrence (KL) system and to examine the relationship between compartment severity, bodyweight and outcomes. RESULTS No meaningful relationships between bodyweight and response to GLA:D® were found for any outcome measures. Greater medial OA compartment severity was related to less improvement in pain, KOOS-12 and chair stand repetitions. However, all levels of lateral compartment severity had similar improvements, and greater patellofemoral compartment severity was related to more improvement for KOOS-12 and pain. CONCLUSION Bodyweight may have little influence on a person's response to a structured education and exercise therapy program. While people with greater medial compartment severity were less likely to improve following the program, OA severity in the PF and lateral compartments was not a barrier to improvement.
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Affiliation(s)
| | | | - Joseph T Lynch
- Faculty of Health, University of Canberra, Canberra, Australia; College of Medicine and Health Sciences, Australian National University, Canberra, Australia; Trauma Orthopaedic Research Unit, Canberra Hospital (TORU), Canberra, Australia
| | - Nicholas A T Brown
- Faculty of Health, Queensland University of Technology, Brisbane, Australia
| | | | - Jennie M Scarvell
- Faculty of Health, University of Canberra, Canberra, Australia; Trauma Orthopaedic Research Unit, Canberra Hospital (TORU), Canberra, Australia
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21
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Chen D, Ye H, Bu L, Wang D, Fan F. Which should be targeted first? The comorbidity of sleep disturbances and anxiety symptoms among adolescents: Cross-sectional and longitudinal network analyses. J Affect Disord 2025; 378:329-339. [PMID: 40049530 DOI: 10.1016/j.jad.2025.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2024] [Revised: 02/28/2025] [Accepted: 03/02/2025] [Indexed: 03/09/2025]
Abstract
BACKGROUND The comorbidity of sleep disturbances and anxiety is well-established, but which symptoms to prioritize for intervention remains unclear. Academic stress, a key factor worsening both, is common among adolescents facing growing academic demands. Understanding how it affects both comorbidities from a symptomatology perspective is crucial for developing targeted interventions. METHODS The longitudinal survey of 34,494 adolescents was conducted twice (Mage = 12.89 [1.76] years). Adolescents were categorized into three groups based on academic stress scores' mean ± 1 standard deviation. Then, we examined the moderating effect of academic stress on the relationship between sleep disturbances and anxiety symptoms longitudinally by comparing groups' network structures, where nodes represent symptoms, and edge thickness reflects the associations' strength. RESULTS In the cross-sectional network, at both time points, the key bridge symptom is "sleep quality" (bridge Expected Influence (bEI) at T1 = 0.21; bEI at T2 = 0.20). In the longitudinal network, "irritability" (bEI = 0.21) and "sleep quality" (bEI = 0.21) are key bridge symptoms in the whole sample, with "sleep quality" (bEI = 0.36) most prominent in the high stress group. In the low stress group, it's "difficulty initiating sleep" (bEI = 0.14). Additionally, compared to the low group, adolescents with high academic stress possess more tightly connected relationships (edge weights ≥0.05) not only within single disorder symptom networks but also between two disorder symptom networks (number of edges: 2 vs 34). CONCLUSION These findings highlight the moderating role of academic stress, offering insights for targeted interventions to improve adolescent mental health.
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Affiliation(s)
- Dan Chen
- School of Psychology, Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, Ministry of Education Key Laboratory of Brain Cognition and Educational Science, Guangdong Emergency Response Technology Research Center for Psychological Assistance in Emergencies, South China Normal University, Guangzhou, China; School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Haoxian Ye
- School of Psychology, Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, Ministry of Education Key Laboratory of Brain Cognition and Educational Science, Guangdong Emergency Response Technology Research Center for Psychological Assistance in Emergencies, South China Normal University, Guangzhou, China
| | - Luowei Bu
- School of Psychology, Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, Ministry of Education Key Laboratory of Brain Cognition and Educational Science, Guangdong Emergency Response Technology Research Center for Psychological Assistance in Emergencies, South China Normal University, Guangzhou, China
| | - Dongfang Wang
- School of Psychology, Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, Ministry of Education Key Laboratory of Brain Cognition and Educational Science, Guangdong Emergency Response Technology Research Center for Psychological Assistance in Emergencies, South China Normal University, Guangzhou, China.
| | - Fang Fan
- School of Psychology, Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, Ministry of Education Key Laboratory of Brain Cognition and Educational Science, Guangdong Emergency Response Technology Research Center for Psychological Assistance in Emergencies, South China Normal University, Guangzhou, China
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22
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Kain MP, Epstein JH, Ross N. Rethinking statistical approaches for serological data analysis for viral surveillance. J Virol Methods 2025; 335:115149. [PMID: 40122214 DOI: 10.1016/j.jviromet.2025.115149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2024] [Revised: 03/08/2025] [Accepted: 03/09/2025] [Indexed: 03/25/2025]
Abstract
A robust serological surveillance system for zoonotic pathogens is imperative for both early detection and advancing knowledge of emerging diseases. A statistical analysis plan that is aligned to research and epidemiological goals requires a purposeful choice among alternative methods for differentiating seronegative from seropositive samples, estimating seroprevalence, and estimating risk factors associated with seropositivity. The common standard deviation-based cutoff (e.g., 3sd) approach is simple to implement and understand, but fails to appropriately propagate uncertainty in serostatus assignments to any risk factor analysis. Methods such as Gaussian mixture models, which jointly estimate serostatus, risk factors, and their uncertainty, can alleviate the dichotomy created by the cutoff approach. Yet, because of a lack of empirical guidance of method performance, it remains difficult to choose a robust analysis method for a given serological dataset. Here we examine the performance of both cutoff and clustering approaches using simulated datasets that represent the epidemiological, biological, and immunological data generation process. We focus on understudied pathogens for which validated serological assays do not exist, as is common in emerging viruses in wildlife. We quantify coverage (the proportion of time 95 % confidence intervals contain the true value) and bias (systematic differences between true values and model point estimates) of model estimates for individual serostatus assignments, population seroprevalence, and regression coefficients for serostatus risk factors. In nearly all scenarios, Bayesian mixture models provide the highest coverage and lowest bias. Only with very low seroprevalence (∼ < 3 %) and large differences in signal between seronegative and seropositive individuals will a cutoff provide low bias and near-nominal coverage. Given poor coverage of risk factor regression coefficients, we advise against using a cutoff approach for quantifying determinants of seropositivity.
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Affiliation(s)
| | - Jonathan H Epstein
- EcoHealth Alliance, New York, NY, USA; One Health Science, Mt. Kisco, NY, USA
| | - Noam Ross
- EcoHealth Alliance, New York, NY, USA; rOpenSci, P.O. Box 90596, Austin, TX 78709, USA
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23
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Castiblanco MR, Kingston S, Zhao Y, Céspedes A, Powell JS, Bruzzese JM. The Association of Mental Health, Asthma Control and Acute Care Visits Among Rural Adolescents with Poorly Controlled Asthma. J Sch Nurs 2025; 41:383-389. [PMID: 35300544 PMCID: PMC9827738 DOI: 10.1177/10598405221085675] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Anxiety and depressive symptoms are associated with asthma-related acute care utilization. Few studies include rural adolescents. Asthma control may be the mechanism by which mental health affects acute care. This study explored associations between generalized anxiety, asthma-related anxiety, depressive symptoms, and acute care visits, and tested if asthma control mediates these associations among 197 rural adolescents with asthma. Data analysis included descriptive statistics and regression. Controlling for age, sex and race/ethnicity, asthma-related anxiety was associated with higher odds of acute care visits (OR = 2.09, 95% CI [1.42, 3.07]). Asthma control mediated this relationship: one unit increase in anxiety, on average, increased the odds of having any acute care visit by 5%. Generalized anxiety and depressive symptoms were not associated with acute care visits. Helping adolescents reduce their concerns regarding asthma while improving their self-management skill may potentially to reduce acute care among rural adolescents.
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Affiliation(s)
| | | | - Yihong Zhao
- Columbia University School of Nursing, New York, NY, USA
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24
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Jansson‐Fröjmark M, Sunnhed R. Smartphone application-delivered cognitive behavioural therapy for insomnia with telephone support for insomnia disorder compared to a waitlist control: a randomised clinical trial. J Sleep Res 2025; 34:e14363. [PMID: 39377371 PMCID: PMC12069742 DOI: 10.1111/jsr.14363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 10/09/2024]
Abstract
Although there have been promising findings for smartphone application (app)-delivered cognitive behavioural therapy for insomnia (CBT-I), previous trials have not screened participants rigorously for insomnia disorder and used therapist support. Based on the above, we aimed to examine the effects of smartphone app-delivered CBT-I with telephone support against a waitlist (WL) in a sample with insomnia disorder. A total of 64 participants with insomnia disorder were randomised to smartphone app-delivered CBT-I (n = 32) or a WL (n = 32). Smartphone app-delivered CBT-I consisted of six weekly smartphone app modules with 15 min of telephone support per week. At pre- and post-treatment, and the 3-month follow-up, we assessed insomnia symptoms and associated correlates and consequences. At post-treatment, we also assessed measures related to adherence (therapist support, exercise/module completion), self-rated perception of treatment content, activity, and adverse events. CBT-I significantly outperformed the WL with large effects on the primary outcome (d = 2.26) and was significantly different on most of the secondary outcomes with medium to large effects. CBT-I also resulted in a significantly larger proportion of treatment remitters (CBT-I: 64.5-77.4%, WL: 6.5-6.9%) and responders (CBT-I: 77.4-90.3%, WL: 19.4-24.1%) at post-treatment and follow-up, compared to the WL. Treatment was associated with high satisfaction, high adherence, low attrition, and few treatment-impeding adverse events. Based on the medium to large effects of smartphone app-delivered CBT-I with telephone support, this trial highlights the potential of delivering CBT-I exclusively through an app with therapist telephone support for high efficacy, satisfaction, and adherence.
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Affiliation(s)
- Markus Jansson‐Fröjmark
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet, and Stockholm Health Care ServicesStockholmSweden
| | - Rikard Sunnhed
- Centre for Psychiatry Research, Department of Clinical NeuroscienceKarolinska Institutet, and Stockholm Health Care ServicesStockholmSweden
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25
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Huang HK, Kuo J, Zhang Y, Aborahama Y, Cui M, Sastry K, Park S, Villa U, Wang LV, Anastasio MA. Fast aberration correction in 3D transcranial photoacoustic computed tomography via a learning-based image reconstruction method. PHOTOACOUSTICS 2025; 43:100698. [PMID: 40115737 PMCID: PMC11923815 DOI: 10.1016/j.pacs.2025.100698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2024] [Revised: 02/08/2025] [Accepted: 02/09/2025] [Indexed: 03/23/2025]
Abstract
Transcranial photoacoustic computed tomography (PACT) holds significant potential as a neuroimaging modality. However, compensating for skull-induced aberrations in reconstructed images remains a challenge. Although optimization-based image reconstruction methods (OBRMs) can account for the relevant wave physics, they are computationally demanding and generally require accurate estimates of the skull's viscoelastic parameters. To circumvent these issues, a learning-based image reconstruction method was investigated for three-dimensional (3D) transcranial PACT. The method was systematically assessed in virtual imaging studies that involved stochastic 3D numerical head phantoms and applied to experimental data acquired by use of a physical head phantom that involved a human skull. The results demonstrated that the learning-based method yielded accurate images and exhibited robustness to errors in the assumed skull properties, while substantially reducing computational times compared to an OBRM. To the best of our knowledge, this is the first demonstration of a learned image reconstruction method for 3D transcranial PACT.
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Affiliation(s)
- Hsuan-Kai Huang
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
| | - Joseph Kuo
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
| | - Yang Zhang
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, 91125, CA, United States
| | - Yousuf Aborahama
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, 91125, CA, United States
| | - Manxiu Cui
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, 91125, CA, United States
| | - Karteekeya Sastry
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, 91125, CA, United States
| | - Seonyeong Park
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
| | - Umberto Villa
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, 78712, TX, United States
| | - Lihong V Wang
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, 91125, CA, United States
| | - Mark A Anastasio
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, 61801, IL, United States
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26
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Duerr GD, Hamiko M, Beer J, Nattermann J, Schafhaus M, Held SAE, Schewe JC, Wittmann M, Kurts C, Zimmer S, Velten M, Heine A. The interplay between COVID-19 and heart disease: Unravelling a complex connection. Life Sci 2025; 370:123524. [PMID: 40044033 DOI: 10.1016/j.lfs.2025.123524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Revised: 02/23/2025] [Accepted: 03/01/2025] [Indexed: 03/20/2025]
Abstract
The intersection of coronavirus (COVID-19) and heart disease has emerged as a critical nexus in the landscape of global health. Individuals with heart disease face elevated risks when infected with Severe Acute Respiratory-Syndrome Coronavirus-type-2 (SARS-CoV-2) leading to COVID-19. The virus can directly affect the heart, resulting in myocarditis, arrhythmias, and heart failure, even in individuals without prior medical cardiac history. Therefore, tools identifying patients with cardiac infestation and predicting disease severity are of utmost importance. This study's unbiased stratification of clinical and immunological parameters of 134 SARS-CoV-2 positive patients revealed clusters of course-severity within the established WHO ordinal severity-scale leading to its summary (SWOSS) into three categories, A-C. PE and SWOSS-C were significantly associated with reduced survival of COVID-19 patients. The previously introduced CD8/Treg/monocyte-ratio which hints at a dysfunctional antiviral immunity associated with poor prognosis could be verified in this larger study population. However, the number of circulating CD14 + HLA-DR+ monocytes represented the most significant predictor for myocardial damage indicated by PE. We used all available data for an unbiased examination of associations and predictions by machine learning algorithms: Predictive markers for PE can be obtained in clinic and may serve as prognostic features. Among numerous parameters, C-reactive protein (CRP) was the most important in determining the presence of PE and SWOSS-category. Prediction of survival was most relevantly influenced by SWOSS-category underlining the benefit of this condensed classification for clinical practice. All AI-revealed prognostic features serve as promising starting-point to gain further understanding of the interplay between COVID-19 and heart disease.
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Affiliation(s)
- G D Duerr
- Department of Cardiovascular Surgery, University Medical Center, Johannes-Gutenberg University, Mainz, Germany.
| | - M Hamiko
- Department of Cardiac Surgery, University Hospital Bonn, Bonn, Germany
| | - J Beer
- Department of Cardiovascular Surgery, University Medical Center, Johannes-Gutenberg University, Mainz, Germany
| | - J Nattermann
- Department of Internal Medicine I, University Hospital Bonn, Bonn, Germany
| | - M Schafhaus
- Department of Cardiac Surgery, University Hospital Bonn, Bonn, Germany
| | - S A E Held
- Department of Internal Medicine III for Hematology, Oncology, Rheumatology and Immune-Oncology, University Hospital Bonn, Bonn, Germany
| | - J C Schewe
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Medical Center Rostock, Rostock, Germany
| | - M Wittmann
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Bonn, Germany
| | - C Kurts
- Institute for Experimental Immunology, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - S Zimmer
- Department of Internal Medicine II - Cardiology, University Hospital Bonn, Bonn, Germany
| | - M Velten
- Department of Anesthesiology and Pain Management, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - A Heine
- Department of Internal Medicine III for Hematology, Oncology, Rheumatology and Immune-Oncology, University Hospital Bonn, Bonn, Germany
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27
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Kiso T, Okada Y, Kawata S, Shichiji K, Okumura E, Hatsumi N, Matsuura R, Kaminaga M, Kuwano H, Okumura E. Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value. Eur J Radiol Open 2025; 14:100649. [PMID: 40236979 PMCID: PMC11999524 DOI: 10.1016/j.ejro.2025.100649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 03/21/2025] [Accepted: 03/26/2025] [Indexed: 04/17/2025] Open
Abstract
Purpose To evaluate the usefulness of radiomics features extracted from ultrasonographic images in diagnosing and predicting the severity of knee osteoarthritis (OA). Methods In this single-center, prospective, observational study, radiomics features were extracted from standing radiographs and ultrasonographic images of knees of patients aged 40-85 years with primary medial OA and without OA. Analysis was conducted using LIFEx software (version 7.2.n), ANOVA, and LASSO regression. The diagnostic accuracy of three different models, including a statistical model incorporating background factors and machine learning models, was evaluated. Results Among 491 limbs analyzed, 318 were OA and 173 were non-OA cases. The mean age was 72.7 (±8.7) and 62.6 (±11.3) years in the OA and non-OA groups, respectively. The OA group included 81 (25.5 %) men and 237 (74.5 %) women, whereas the non-OA group included 73 men (42.2 %) and 100 (57.8 %) women. A statistical model using the cutoff value of MORPHOLOGICAL_SurfaceToVolumeRatio (IBSI:2PR5) achieved a specificity of 0.98 and sensitivity of 0.47. Machine learning diagnostic models (Model 2) demonstrated areas under the curve (AUCs) of 0.88 (discriminant analysis) and 0.87 (logistic regression), with sensitivities of 0.80 and 0.81 and specificities of 0.82 and 0.80, respectively. For severity prediction, the statistical model using MORPHOLOGICAL_SurfaceToVolumeRatio (IBSI:2PR5) showed sensitivity and specificity values of 0.78 and 0.86, respectively, whereas machine learning models achieved an AUC of 0.92, sensitivity of 0.81, and specificity of 0.85 for severity prediction. Conclusion The use of radiomics features in diagnosing knee OA shows potential as a supportive tool for enhancing clinicians' decision-making.
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Affiliation(s)
- Takeharu Kiso
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
- Graduate School of Medical Sciences, Suzuka University, 1001-1, Kishioka-cho, Suzuka-shi, Mie 510-0293, Japan
| | - Yukinori Okada
- Graduate School of Medical Sciences, Suzuka University, 1001-1, Kishioka-cho, Suzuka-shi, Mie 510-0293, Japan
- Tokyo Medical University Hospital, Department of Clinical Medicine, Division of Radiation Oncology, 6-7-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo 160-0023, Japan
| | - Satoru Kawata
- Department of Radiology, Faculty of Medical and Health Sciences, Tsukuba International University, 6-20-1 Manabe, Tsuchiura-shi, Ibaraki 300-0051, Japan
- Postdoctoral Program, Graduate School of Health Sciences, Kyorin University, 5-4-1 Shimorenjaku, Mitaka-shi, Tokyo 181-8612, Japan
| | - Kouta Shichiji
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
| | - Eiichiro Okumura
- Department of Radiology, Faculty of Medical and Health Sciences, Tsukuba International University, 6-20-1 Manabe, Tsuchiura-shi, Ibaraki 300-0051, Japan
| | - Noritaka Hatsumi
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
| | - Ryohei Matsuura
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
| | - Masaki Kaminaga
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
| | - Hikaru Kuwano
- Department of Radiology, Medical Corporation Seireikai Tachikawa Memorial Hospital, 2-12-14 Yakumo, Kasama, Ibaraki 309-1611, Japan
| | - Erika Okumura
- Graduate School of Medical Sciences, Suzuka University, 1001-1, Kishioka-cho, Suzuka-shi, Mie 510-0293, Japan
- Department of Radiology, Tsukuba Medical Center Hospital, 1-3-1 Amakubo, Tsukuba City, Ibaraki Prefecture 305-8558, Japan
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Li YM, Li CX, Jureti R, Awuti G. Identification and Validation of Ferritinophagy-Related Biomarkers in Periodontitis. Int Dent J 2025; 75:1781-1797. [PMID: 40233623 PMCID: PMC12043013 DOI: 10.1016/j.identj.2025.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2025] [Revised: 02/19/2025] [Accepted: 03/01/2025] [Indexed: 04/17/2025] Open
Abstract
OBJECTIVE While ferritinophagy is believed to play a significant role in the development of periodontitis, the exact mechanisms remain unclear. This study aimed to investigate the biomarkers associated with ferritinophagy in periodontitis using transcriptomic data. METHODS Two periodontitis-related datasets from Gene Expression Omnibus, GSE10334, and GSE16134, served as the training and validation cohorts, respectively. Additionally, 36 ferritinophagy-related genes (FRGs) were obtained from the GeneCards database. We compared the expression differences of FRGs between the periodontitis and control groups, identifying the different FRGs as candidates. Weighted gene coexpression network analysis (WGCNA) was applied to capture the key modules and modular genes related to periodontitis, utilizing the candidate FRG scores as trait. Then we intersected these with key module genes to identify differentially expressed FRGs. Hub genes were filtered using a protein-protein interaction network. Ultimately, biomarkers were acquired through machine learning, receiver operating characteristic curves, and expression levels. In addition, biomarker-associated immune cells and functional pathways were analysed to predict the upstream regulatory molecules. RESULTS In total, 18 candidate FRGs showed significant differences between the periodontitis and control groups, and from the protein-protein interaction network, eight hub genes were identified among the 175 differentially expressed FRGs by analysing 1096 differentially expressed genes and 4479 key modular genes. Eventually, ALDH2, diazepam binding inhibitor, HMGCR, OXCT1, and ACAT2 were identified as potential biomarkers through machine learning algorithms, receiver operating characteristic curve analysis, and gene expression assessments. In addition, resting dendritic cells, mast cells, and follicular helper T cells were positively correlated with the five biomarkers (Cor > 0.3 and P < .05). All five biomarkers are involved in the translation initiation pathway, including transcription factors like KLF5 and microRNAs such as hsa-miR-495-3p and hsa-miR-27a-3p. Reverse transcription-quantitative polymerase chain reaction analysis showed that all biomarkers were expressed at low levels in the periodontitis group. However, the differences in expression levels for OXCT1 and ACAT2 between groups were not statistically significant. CONCLUSIONS A total of five ferritinophagy-related biomarkers - ALDH2, diazepam binding inhibitor, HMGCR, OXCT1, and ACAT2 - were screened to explore new treatment options for periodontitis.
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Affiliation(s)
- Yi-Ming Li
- Department of Periodontology, School/Hospital of Stomatology, The First Affiliated Hospital of Xinjiang Medical University, National Clinical Medical Research Institute, Urumqi, China
| | - Chen-Xi Li
- Department of Oral and Maxillofacial Oncology & Surgery, School/Hospital of Stomatology, The First Affiliated Hospital of Xinjiang Medical University, National Clinical Medical Research Institute, Urumqi, China; Dental Medicine Institute of Xinjiang Uygur Autonomous Region, Urumqi, China.
| | - Reyila Jureti
- Department of Periodontology, School/Hospital of Stomatology, The First Affiliated Hospital of Xinjiang Medical University, National Clinical Medical Research Institute, Urumqi, China
| | - Gulinuer Awuti
- Department of Periodontology, School/Hospital of Stomatology, The First Affiliated Hospital of Xinjiang Medical University, National Clinical Medical Research Institute, Urumqi, China
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Geynisman DM, Chepynoga K, Yates G, Tate A, Kurt M, Patel MY, Teitsson S, Mitra S, Mamtani R. Estimating the Impact of Adjuvant Treatment With Nivolumab on Long-Term Survivorship Rates Compared With Surveillance in Muscle Invasive Urothelial Carcinoma: Mixture Cure Modeling Analyses of Disease-Free Survival From the Phase 3 CheckMate 274 Trial. Clin Genitourin Cancer 2025; 23:102335. [PMID: 40204616 DOI: 10.1016/j.clgc.2025.102335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2025] [Revised: 03/04/2025] [Accepted: 03/12/2025] [Indexed: 04/11/2025]
Abstract
BACKGROUND Curative potential of adjuvant nivolumab was compared with radical resection only among patients at high risk of recurrence following radical surgery of muscle-invasive urothelial carcinoma (MIUC). METHODS Using patient-level disease-free survival (DFS) data from CheckMate 274 (n = 709, minimum follow-up, 31.6 months), we applied mixture cure models (MCMs) to the adjuvant nivolumab (NIVO) and placebo (PBO) arms of the intention-to-treat (ITT) population and tumor PD-L1 expression ≥1% subpopulation. DFS was derived for hypothetical "cured" and "uncured" subgroups. DFS for the cured subgroup was estimated using WHO background mortality rates matched to trial demographic characteristics. Uncured DFS was modeled using parametric distributions and characterized with cure fractions by maximum-likelihood methods. Model selection considered clinical plausibility, visual comparisons of model fit, and goodness-of-fit statistics. RESULTS MCM analysis demonstrated that almost all uncured patients experience recurrence or death within 5 years. Clinically plausible models estimated higher cure fractions in tumor PD-L1 ≥1% subgroup for patients treated with NIVO (PD-L1 ≥1%: 59.1%-61.0% vs ITT: 43.1%-45.1%), and highly similar cure fractions for patients receiving PBO irrespective of their PD-L1 expression (PD-L1 ≥1%: 35.9%-36.4% vs ITT: 36.4%-37.0%). Projected 10-year mean DFS was 4.38 to 4.47 years for NIVO and 3.61 to 3.64 years for PBO in the ITT population, and 5.54 to 5.65 years for NIVO and 3.54 to 3.57 years for PBO in the PD-L1 ≥1% subpopulation. CONCLUSIONS Adjuvant NIVO for high-risk MIUC was associated with a higher cure fraction than PBO in the ITT and PD-L1 ≥1% populations. Results align with reported survival from the trial and highlight clinical outcomes of interest. CheckMate 274 ClinicalTrials.gov identifier, NCT02632409.
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Affiliation(s)
- Daniel M Geynisman
- Fox Chase Cancer Center-Temple University Health System, Philadelphia, PA.
| | | | - Georgia Yates
- Parexel International, Access Consulting - Analytics, London, UK
| | - Ashley Tate
- Parexel International, Access Consulting - Analytics, Amsterdam, the Netherlands
| | | | | | | | | | - Ronac Mamtani
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
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Azrag AA, Niassy S, Bloukounon-Goubalan AY, Abdel-Rahman EM, Tonnang HE, Mohamed SA. Cotton production areas are at high risk of invasion by Amrasca biguttula (Ishida) (Cicadellidae: Hemiptera): potential distribution under climate change. PEST MANAGEMENT SCIENCE 2025; 81:2910-2921. [PMID: 39835365 DOI: 10.1002/ps.8659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Revised: 11/29/2024] [Accepted: 01/04/2025] [Indexed: 01/22/2025]
Abstract
BACKGROUND The cotton jassid, Amrasca biguttula, a dangerous and polyphagous pest, has recently invaded the Middle East, Africa and South America, raising concerns about the future of cotton and other food crops including okra, eggplant and potato. However, its potential distribution remains largely unknown, posing a challenge in developing effective phytosanitary strategies. We used an ensemble model of six machine-learning algorithms including random forest, maxent, support vector machines, classification and regression tree, generalized linear model and boosted regression trees to forecast the potential distribution of A. biguttula in the present and future using presence records of the pest and bioclimatic predictors. The accuracy of these algorithms was assessed based on the area under the curve (AUC), correlation (COR), deviance and true skill statistic (TSS). RESULTS All algorithms showed good performance in forecasting the distribution of A. biguttula (AUC ≥ 0.91, COR ≥ 0.72, TSS ≥ 0.77 and deviance ≤ 0.65). Mean temperature of wettest quarter, mean temperature of driest quarter and precipitation of the wettest month were the key variables that contributed to predicting A. biguttula occurrence. Projection of the model showed that cotton production areas in Asia, sub-Saharan Africa, and South America are at threat of invasion by A. biguttula under the current climatic scenario. Additionally, range expansion for A. biguttula is projected in the future in sub-Saharan Africa, South America and China, indicating a suitable ecological niche for A. biguttula to thrive. CONCLUSION Our results provide early warning and decision-making information that can guide efforts to prevent this pest's further spread and invasion into new areas. © 2025 Society of Chemical Industry.
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Affiliation(s)
| | - Saliou Niassy
- African Union Inter-African Phytosanitary Council (AU-IAPSC), Yaoundé, Cameroon
| | | | | | - Henri Ez Tonnang
- International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya
- University of KwaZulu-Natal, School of Agricultural, Earth, and Environmental Sciences, Pietermaritzburg, South Africa
| | - Samira A Mohamed
- International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya
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Mokaram Doust Delkhah A. Integrated transcriptomics of multiple sclerosis peripheral blood mononuclear cells explored potential biomarkers for the disease. Biochem Biophys Rep 2025; 42:102022. [PMID: 40290807 PMCID: PMC12033924 DOI: 10.1016/j.bbrep.2025.102022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2025] [Revised: 04/08/2025] [Accepted: 04/16/2025] [Indexed: 04/30/2025] Open
Abstract
Background Despite their importance, blood RNAs have not been comprehensively studied as potential diagnostic markers for multiple sclerosis (MS). Herein, by the integration of GSE21942 and GSE203241 microarray profiles of peripheral blood mononuclear cells, this study explored potential biomarkers for the disease. Methods After identification of differentially expressed genes (DEGs), functional enrichment analyses were performed, and PPI and miRNA-mRNA regulatory networks were constructed. After implementing weighted gene co-expression network analysis (WGCNA) and discovering MS-specific modules, the converging results of differential expression analysis and WGCNA were subjected to machine learning methods. Lastly, the diagnostic performance of the prominent genes was evaluated by receiver operating characteristic (ROC) analysis. Results COPG1, RPN1, and KDM3B were initially highlighted as potential biomarkers based on their acceptable diagnostic efficacy in the integrated data, as well as in both GSE141804 and GSE146383 datasets as external validation sets. However, given that they were downregulated in the integrated data while they were upregulated in the validation sets, they could not be considered as potential biomarkers for the disease. In addition to this inconsistency, evaluating their diagnostic performance in other external datasets (GSE247181, GSE59085, and GSE17393) did not reveal their diagnostic efficacy. Conclusions This study could not unveil promising blood biomarkers for MS, possibly due to a small sample size and unaccounted confounding factors. Considering PBMCs and blood specimens as valuable sources for the identification of biomarkers, further transcriptomic analyses are needed to discover potential biomarkers for the disease.
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Engelhard M, Wojdyla D, Wang H, Pencina M, Henao R. Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. Artif Intell Med 2025; 164:103130. [PMID: 40253926 DOI: 10.1016/j.artmed.2025.103130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 04/06/2025] [Accepted: 04/09/2025] [Indexed: 04/22/2025]
Abstract
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical literature to correct such disparities by removing race as a predictor (i.e., race-free models). Alternatively, a variety of machine learning methods have been proposed to constrain differences in model predictions between racial groups. In this work, we compare these approaches for equitable stroke risk prediction. We begin by proposing a discrete-time, neural network-based time-to-event model that incorporates a parity constraint designed to make predictions more similar between groups. Using harmonized data from Framingham Offspring, MESA, and ARIC studies, we develop both parity-constrained and unconstrained stroke risk prediction models, then compare their performance with race-free models in a held-out test set and a secondary validation set (REGARDS). Our evaluation includes both intra-group and inter-group performance metrics for right-censored time to event outcomes. Results illustrate a fundamental trade-off in which parity-constrained models must sacrifice intra-group calibration to improve inter-group discrimination performance, while the race-free models strike a balance between the two. Consequently, the choice of model must depend on the potential benefits and harms associated with the intended clinical use. All models as well as code implementing our approach are available in a public repository. More broadly, these results provide a roadmap for development of equitable clinical risk prediction models and illustrate both merits and limitations of a race-free approach.
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Affiliation(s)
- Matthew Engelhard
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, United States of America; Duke AI Health, United States of America.
| | - Daniel Wojdyla
- Duke Clinical Research Institute, United States of America
| | - Haoyuan Wang
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, United States of America
| | - Michael Pencina
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, United States of America; Duke AI Health, United States of America; Duke Clinical Research Institute, United States of America
| | - Ricardo Henao
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, United States of America; Duke AI Health, United States of America; Duke Clinical Research Institute, United States of America
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Veerman LKM, Willemen AM, Derks SDM, Brouwer-van Dijken AAJ, Sterkenburg PS. Supporting young siblings of children with intellectual disabilities and/or visual impairments with the serious game 'Broodles': A mixed methods randomized controlled trial. RESEARCH IN DEVELOPMENTAL DISABILITIES 2025; 161:104996. [PMID: 40147420 DOI: 10.1016/j.ridd.2025.104996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Revised: 03/17/2025] [Accepted: 03/18/2025] [Indexed: 03/29/2025]
Abstract
BACKGROUND Siblings of children with neurodevelopmental conditions experience conflicting emotions and have an increased risk of mental health problems. Several sibling interventions have been developed, but few are readily available, leaving many siblings unsupported. Therefore, the free, online, self-administered sibling serious game 'Broodles' was developed. This study assessed its social validity and effectiveness in promoting quality of life, and inter- and intrapersonal factors in siblings (6-9 years) of children with intellectual disabilities and/or visual impairments. METHODS A mixed methods, waitlist control group, randomized controlled trial was conducted. In total, 107 Dutch or Belgian parent-child dyads completed questionnaires at three timepoints (baseline, one-month post-test, two-month follow-up). The intervention group also completed post-test interviews. Effects were assessed using multilevel modelling, and thematic analysis was applied to the evaluations. RESULTS Significant, weak interaction effects (R² = .03-.06) were found on sibling negative adjustment, but only in those who completed ≥ 75 % of the game and followed the study timeline. Regardless of group, (very) small, significant improvements over time were found on several outcomes (R² = .01-.06). 'Broodles' was experienced as fun (80 %) and helpful (79 %). Perceived learning outcomes included the themes: 'sibling awareness and validation', 'emotions and needs', 'coping with emotions and situations' and 'family interactions'. CONCLUSION Although quantitative data showed small effects, qualitative data revealed a variety of learning outcomes which can contribute to siblings' resilience, and prevention of mental health problems. To unlock its full potential, future studies should examine if additional family-targeted components can enhance the intervention's impact.
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Affiliation(s)
- Linda K M Veerman
- Department of Clinical Child and Family Studies; Amsterdam Public Health; LEARN!; Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, the Netherlands.
| | - Agnes M Willemen
- Department of Clinical Child and Family Studies; Amsterdam Public Health; LEARN!; Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, the Netherlands.
| | - Suzanne D M Derks
- Department of Clinical Child and Family Studies; Amsterdam Public Health; LEARN!; Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, the Netherlands.
| | | | - Paula S Sterkenburg
- Department of Clinical Child and Family Studies; Amsterdam Public Health; LEARN!; Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, the Netherlands; Bartiméus, Oude Arnhemse Bovenweg 3, Doorn 3941 XM, the Netherlands.
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Zheng Z, Chen J, Xu J, Jiang B, Li L, Li Y, Dai Y, Wang B. Peripheral blood RNA biomarkers can predict lesion severity in degenerative cervical myelopathy. Neural Regen Res 2025; 20:1764-1775. [PMID: 39104114 PMCID: PMC11688566 DOI: 10.4103/nrr.nrr-d-23-01069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 10/10/2023] [Accepted: 11/23/2023] [Indexed: 08/07/2024] Open
Abstract
JOURNAL/nrgr/04.03/01300535-202506000-00027/figure1/v/2024-08-05T133530Z/r/image-tiff Degenerative cervical myelopathy is a common cause of spinal cord injury, with longer symptom duration and higher myelopathy severity indicating a worse prognosis. While numerous studies have investigated serological biomarkers for acute spinal cord injury, few studies have explored such biomarkers for diagnosing degenerative cervical myelopathy. This study involved 30 patients with degenerative cervical myelopathy (51.3 ± 7.3 years old, 12 women and 18 men), seven healthy controls (25.7 ± 1.7 years old, one woman and six men), and nine patients with cervical spondylotic radiculopathy (51.9 ± 8.6 years old, three women and six men). Analysis of blood samples from the three groups showed clear differences in transcriptomic characteristics. Enrichment analysis identified 128 differentially expressed genes that were enriched in patients with neurological disabilities. Using least absolute shrinkage and selection operator analysis, we constructed a five-gene model (TBCD, TPM2, PNKD, EIF4G2, and AP5Z1) to diagnose degenerative cervical myelopathy with an accuracy of 93.5%. One-gene models (TCAP and SDHA) identified mild and severe degenerative cervical myelopathy with accuracies of 83.3% and 76.7%, respectively. Signatures of two immune cell types (memory B cells and memory-activated CD4+ T cells) predicted levels of lesions in degenerative cervical myelopathy with 80% accuracy. Our results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.
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Affiliation(s)
- Zhenzhong Zheng
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Jialin Chen
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Jinghong Xu
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Bin Jiang
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Lei Li
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Yawei Li
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Yuliang Dai
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
| | - Bing Wang
- Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan Province, China
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Lee G, Jung W, Sakaie K, Oh S. An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net. NMR IN BIOMEDICINE 2025; 38:e70057. [PMID: 40331503 PMCID: PMC12056887 DOI: 10.1002/nbm.70057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2024] [Revised: 04/10/2025] [Accepted: 04/28/2025] [Indexed: 05/08/2025]
Abstract
Quantitative susceptibility mapping (QSM) provides the spatial distribution of magnetic susceptibility within tissues through sequential steps: phase unwrapping and echo combination, mask generation, background field removal, and dipole inversion. Accurate mask generation is crucial, as masks excluding regions outside the brain and without holes are necessary to minimize errors and streaking artifacts during QSM reconstruction. Variations in susceptibility values can arise from different mask generation methods, highlighting the importance of optimizing mask creation. In this study, we propose QSMmask-net, a deep neural network-based method for generating precise QSM masks. QSMmask-net achieved the highest Dice score compared to other mask generation methods. Mean susceptibility values using QSMmask-net masks showed the lowest differences from manual masks (ground truth) in simulations and healthy controls (no significant difference, p > 0.05). Linear regression analysis confirmed a strong correlation with manual masks for hemorrhagic lesions (slope = 0.9814 ± 0.007, intercept = 0.0031 ± 0.001, R2 = 0.9992, p < 0.05). We have demonstrated that mask generation methods can affect the susceptibility value estimations. QSMmask-net reduces the labor required for mask generation while providing mask quality comparable to manual methods. The proposed method enables users without specialized expertise to create optimized masks, potentially broadening QSM applicability efficiently.
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Affiliation(s)
- Gawon Lee
- Department of Biomedical EngineeringHankuk University of Foreign StudiesYonginRepublic of Korea
| | | | - Ken E. Sakaie
- Department of Diagnostic Radiology, Diagnostics InstituteThe Cleveland ClinicClevelandOhioUSA
| | - Se‐Hong Oh
- Department of Biomedical EngineeringHankuk University of Foreign StudiesYonginRepublic of Korea
- Department of Diagnostic Radiology, Diagnostics InstituteThe Cleveland ClinicClevelandOhioUSA
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Bergner-Koether R, Peschka L, Pastukhov A, Carbon CC, Steins-Loeber S, Hajak G, Rettenberger M. The Relevance of Hypersexuality and Impulsivity in Different Groups of Treatment-Seekers With and Without (Exclusive) Pedophilia. SEXUAL ABUSE : A JOURNAL OF RESEARCH AND TREATMENT 2025; 37:371-398. [PMID: 39104158 PMCID: PMC11997290 DOI: 10.1177/10790632241271204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/07/2024]
Abstract
Hypersexuality and impulsivity are regarded as risk factors for sexual offending against children. Studies exploring these factors in undetected men who offended or are at risk of offending are rare. This study aims to investigate hypersexuality and impulsivity in treatment-seeking men with and without a diagnosis of (exclusive) pedophilia who committed child sexual abuse (CSA), consumed child sexual abuse images (CSAI), or feel at risk of offending sexually. Data were obtained from three child abuse prevention projects in Bamberg, Germany. We employed self-report (BIS-11, HBI), objective measures (TSO), and risk assessment tools (STABLE-2007). We computed Bayesian ordinal logit and binomial generalized linear models to explore differences between groups and to predict lifetime CSA and CSAI. Hypersexuality scores were particularly pronounced in patients with exclusive and non-exclusive pedophilia. Patients without pedophilia scored similarly to nonclinical samples. Impulsivity measures did not consistently differ between groups. We could not predict lifetime CSA and CSAI using impulsivity and hypersexuality measures. Sexual rather than general impulsivity seems to be an issue in men with pedophilia. The motivation to offend in patients without pedophilia is discussed.
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Affiliation(s)
- Ralf Bergner-Koether
- Department for Sexual Medicine, Sozialstiftung Bamberg, Bamberg, Germany
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Bamberg, Germany
| | - Lasse Peschka
- Department for Sexual Medicine, Sozialstiftung Bamberg, Bamberg, Germany
- Department of General Psychology and Methodology, University of Bamberg, Bamberg, Germany
| | - Alexander Pastukhov
- Department of General Psychology and Methodology, University of Bamberg, Bamberg, Germany
| | - Claus-Christian Carbon
- Department of General Psychology and Methodology, University of Bamberg, Bamberg, Germany
| | - Sabine Steins-Loeber
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Bamberg, Germany
| | - Göran Hajak
- Department for Sexual Medicine, Sozialstiftung Bamberg, Bamberg, Germany
| | - Martin Rettenberger
- Centre for Criminology (Kriminologische Zentralstelle, – KrimZ), Wiesbaden, Germany
- Department of Psychology at the Johannes Gutenberg University Mainz (JGU), Germany
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Du J, Liu Y, Luo Z, Wang M, Liu Y. Identification of Periodontal Disease Diagnostic Markers Via Data Cross-Validation. Int Dent J 2025; 75:1936-1950. [PMID: 39904707 DOI: 10.1016/j.identj.2025.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 12/28/2024] [Accepted: 01/16/2025] [Indexed: 02/06/2025] Open
Abstract
INTRODUCTION AND AIMS Periodontitis is a globally prevalent disease that is clinically diagnosed when the periodontal tissues are pathologically affected. Therefore, it is vital to identify novel periodontitis-associated biomarkers that will aid in diagnosing or treating potential patients with periodontitis. METHODS The GSE16134 and GSE10334 datasets were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes between periodontitis and healthy samples. Single-sample gene set enrichment analysis was performed to identify significantly involved signalling pathways. Weighted gene correlation network analysis was used to identify key molecular modules. Hub genes were screened using key genes to construct a diagnosis and prediction model of periodontitis. Microenvironment cell population-counter was used to analyse immune cell infiltration patterns in periodontal diseases. RESULTS Single-sample gene set enrichment analysis revealed that periodontitis involves the PI3K/AKT/mTOR signalling pathway and associated module genes (667 genes). Kyoto Encyclopedia of Genes and Genomes enrichment analysis of the module genes revealed that periodontitis involves the type I interferon, rhythmic process, and response to type I interferon signalling pathways. GSEA identified 21 core genes associated with periodontitis and classified them into two clusters, A and B. Genomics of Drug Sensitivity in Cancer analysis revealed that AKT.inhibitor.VIII had high drug sensitivity in the cluster A subtype. Monocytes and myeloid dendritic cell infiltration were enriched in the cluster A subtype, whereas natural killer T cell infiltration was enriched in the cluster B subtype. CONCLUSION The pathway and gene modules identified in this study may help comprehensively diagnose periodontitis and provide a novel method for evaluating new treatments. CLINICAL RELEVANCE Our results are beneficial for classifying periodontitis subtypes and treatment using targeted medicine.
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Affiliation(s)
- Juan Du
- Laboratory of Tissue Regeneration and Immunology and Department of Periodontics, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Beijing, China
| | - Yi Liu
- Laboratory of Tissue Regeneration and Immunology and Department of Periodontics, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Beijing, China
| | - Zhenhua Luo
- Laboratory of Tissue Regeneration and Immunology and Department of Periodontics, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Beijing, China
| | - Minfeng Wang
- Laboratory of Tissue Regeneration and Immunology and Department of Periodontics, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Beijing, China
| | - Yitong Liu
- Laboratory of Tissue Regeneration and Immunology and Department of Periodontics, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Beijing, China.
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Souza Bulhões RD, Pimentel JS, Rodrigues PC. Bayesian spatio-temporal modeling of severe acute respiratory syndrome in Brazil: A comparative analysis across pre-, during, and post-COVID-19 eras. Infect Dis Model 2025; 10:466-476. [PMID: 39834649 PMCID: PMC11743096 DOI: 10.1016/j.idm.2024.12.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 11/09/2024] [Accepted: 12/13/2024] [Indexed: 01/22/2025] Open
Abstract
This paper presents an investigation into the spatio-temporal dynamics of Severe Acute Respiratory Syndrome (SARS) across the diverse health regions of Brazil from 2016 to 2024. Leveraging extensive datasets that include SARS cases, climate data, hospitalization records, and COVID-19 vaccination information, our study employs a Bayesian spatio-temporal generalized linear model to capture the intricate dependencies inherent in the dataset. The analysis reveals significant variations in the incidence of SARS cases over time, particularly during and between the distinct eras of pre-COVID-19, during, and post-COVID-19. Our modeling approach accommodates explanatory variables such as humidity, temperature, and COVID-19 vaccine doses, providing a comprehensive understanding of the factors influencing SARS dynamics. Our modeling revealed unique temporal trends in SARS cases for each region, resembling neighborhood patterns. Low temperature and high humidity were linked to decreased cases, while in the COVID-19 era, temperature and vaccination coverage played significant roles. The findings contribute valuable insights into the spatial and temporal patterns of SARS in Brazil, offering a foundation for targeted public health interventions and preparedness strategies.
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Affiliation(s)
- Rodrigo de Souza Bulhões
- Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil
- Department of Statistical Methods, IM, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | | | - Paulo Canas Rodrigues
- Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil
- Econometrics and Business Statistics, Monash University, Australia
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Schneider I, Wallrafen-Sam K, Kennedy S, Akiyama MJ, Spaulding AC, Jenness SM. Interventions for SARS-CoV-2 prevention among Jailed adults: A network-based modeling analysis. Infect Dis Model 2025; 10:628-638. [PMID: 40027595 PMCID: PMC11869379 DOI: 10.1016/j.idm.2025.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 10/30/2024] [Accepted: 02/03/2025] [Indexed: 03/05/2025] Open
Abstract
Background Airborne pathogens present challenges in settings like jails or prisons with a high density of contacts. The state of Georgia has the highest percentage of its citizens under correctional supervision in the United States. Yet, it had slow COVID vaccine uptake among jail residents, requiring prevention also using non-pharmaceutical interventions. Using a network-based SARS-CoV-2 transmission model parameterized with data from the Fulton County Jail, this study investigates the impact of three SARS-CoV-2 prevention strategies: vaccination, contact tracing and quarantining, and jail release to reduce jail population density. Methods Social contact networks were simulated at two different overlapping network layers: cell and block. Cell-level contacts represented shared confined sleeping space, whereas block-level contacts represented shared socialization space. Contact tracing and quarantining were simulated at the cell-level or both cell- and block-levels, hereafter referred to as all-level. A reference scenario and nine intervention scenarios were simulated three hundred times to estimate the median and interquartile range (IQR) of the outcome measures. Each scenario simulated a 185-day period to measure the prolonged effects of the interventions amid a potential COVID outbreak in the jail. The cumulative incidence, number of infections averted (NIA), and percentage of infections averted (PIA) were calculated comparing interventions against a base scenario without them. For the seven scenarios involving contact tracing and quarantining, total quarantines over the simulation and the number of quarantines per day were calculated to determine the quarantine requirements. Sensitivity analyses compared the impact of jointly varying vaccination rates and contact tracing rates. Results Cell-level contact tracing alone was an ineffective intervention (3.2% PIA), but its impact increased in combination with other interventions (i.e., vaccination or increased jail release rate). The other intervention strategies each produced a PIA over 10%, with the jail release scenario producing a PIA of nearly 20% despite only resulting in a 13% reduction in the jail population. The all-level contact tracing only scenario was effective at both 50% and 100% of contacts traced, but feasibility would be limited without a reduction in the jail population. Conclusions Implementing a combination intervention approach could substantially reduce the morbidity from COVID-19 and future respiratory viruses in this jail setting while providing secondary protection to the community.
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Affiliation(s)
- Isaac Schneider
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Karina Wallrafen-Sam
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Shanika Kennedy
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Matthew J. Akiyama
- Divisions of General Internal Medicine & Infectious Diseases, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Anne C. Spaulding
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Samuel M. Jenness
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
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Karamcheti ST, Brightwell G, Bremer P, Schofield MR. Hierarchical Bayesian linear mixed model to estimate variability in the thermal inactivation parameters for Listeria species. Food Microbiol 2025; 128:104731. [PMID: 39952750 DOI: 10.1016/j.fm.2025.104731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Revised: 01/08/2025] [Accepted: 01/09/2025] [Indexed: 02/17/2025]
Abstract
A total of 476 D-values associated with 76 strains of Listeria spp. in liquid media were obtained from 27 scientific articles. Meta-analysis was carried out using hierarchical Bayesian models to assess variability, predict the D-, and estimate the zT-, and zpH-values for Listeria spp. across a range of temperatures (55-70 °C) and pH values (3-8 units). Different hypotheses regarding variability between strains or studies in each model correspond to different hierarchical assumptions about the inactivation parameters. The models produced were compared based on their predictive ability, Bayes-R2 and widely applicable information criterion (WAIC) values. A hierarchical model that considered random effects due to both strain and study effects on the thermal inactivation parameters was determined to be the "best" model and was subsequently used to estimate the posterior distributions for the D-, zT-, and zpH-values. The variability introduced in the parameters due to differences between studies was higher than that of variability between strains. The parameters estimated using the model for different strains of Listeria species may be applicable for processing aqueous foods such as milk and liquid products such as sauces and gravies across a temperature range of 55-70 °C and pH values of 3-8 units.
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Affiliation(s)
- Soundarya T Karamcheti
- Department of Food Science, University of Otago, PO Box 56, Dunedin, 9054, New Zealand; Food System Integrity, AgResearch Ltd., Hopkirk Research Institute, Cnr University Ave and Library Road, Massey University, Palmerston North, 4442, New Zealand
| | - Gale Brightwell
- Food System Integrity, AgResearch Ltd., Hopkirk Research Institute, Cnr University Ave and Library Road, Massey University, Palmerston North, 4442, New Zealand; New Zealand Food Safety Science and Research Centre, Massey University, Palmerston North, 4410, New Zealand
| | - Phil Bremer
- Department of Food Science, University of Otago, PO Box 56, Dunedin, 9054, New Zealand; New Zealand Food Safety Science and Research Centre, Massey University, Palmerston North, 4410, New Zealand
| | - Matthew R Schofield
- Department of Mathematics and Statistics, University of Otago, PO Box 56, Dunedin, 9054, New Zealand.
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Keleman AA, Bollinger RM, Rodakowski J, Chang CH, Kehrer-Dunlap AL, Ances BM, Stark SL. Exploring the Remote Administration of a Performance-Based Functional Assessment. J Appl Gerontol 2025; 44:981-993. [PMID: 39449317 PMCID: PMC12018588 DOI: 10.1177/07334648241292968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2024] Open
Abstract
Performance-based assessments of instrumental activities of daily living (IADL) can detect subtle functional impairments better than self-reported questionnaires. While most performance-based IADL assessments were developed for in-person administration, remote administration could increase access to vulnerable older adults. This study compared in-person and remote administration of IADL tasks from the Performance Assessment of Self-Care Skills. Community-dwelling older adults completed tasks (shopping, checkbook balancing, and medication management) at baseline (in-person) and follow-up (either in-person or remote, with modifications) two years later. Scores between the two follow-up groups, change in scores from baseline to follow-up, and differential item functioning (DIF) between the two administration methods at follow-up were examined. There were no differences in scores between methods of administration, but remote tasks took longer, and one item had significant DIF (ps < .01). Clinicians found remote administration acceptable and feasible. With minor adaptations, remote administration of the three tasks was supported. Further validation research is needed.
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Affiliation(s)
- Audrey A. Keleman
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA
| | - Rebecca M. Bollinger
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA
| | - Juleen Rodakowski
- Department of Occupational Therapy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chih-Hung Chang
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA
- Institute for Informatics, Washington University School of Medicine, St Louis, MO, USA
- Department of Orthopaedic Surgery, Washington University School of Medicine, St Louis, MO, USA
| | | | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Susan L. Stark
- Program in Occupational Therapy, Washington University School of Medicine, St Louis, MO, USA
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Horváth G, Herczeg D, Kovács B, Péntek Á, Kaczur B, Herczeg G. Microplastic uptake with food increases risk-taking of a wide-spread decomposer, the common pill bug Armadillidium vulgare. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2025; 374:126220. [PMID: 40210158 DOI: 10.1016/j.envpol.2025.126220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2025] [Revised: 03/20/2025] [Accepted: 04/07/2025] [Indexed: 04/12/2025]
Abstract
Exposure to microplastics (MPs) i.e., plastic fragments between 1 μm and 1 mm in diameter causing growing concern for wildlife and humanity. It is now evident that MPs can accumulate in soil, freshwater, seawater and the atmosphere; thus, living organisms are directly or indirectly exposed to these significant ecological stressors globally. Studies on the physiological effects of MPs in wildlife are emerging, yet, to date, only a handful of studies with a special focus on how MPs affect animal behaviour are available, and there is even less research on how different components of among- and within-individual behavioural variation are affected by MPs. The main goal of this study was to investigate how prolonged exposure (6 weeks) to 10 μm spherical polystyrene microplastics in food (24.85 particles/mg) influences individual variation in risk-taking behaviour in a widespread decomposer, the common pill bug Armadillidium vulgare. Our results indicate a strong MP effect on different levels of behavioural variation: (i) individual mean risk-taking increased, while (ii) a correlation between mean risk-taking and residual within-individual risk-taking variation emerged (risk-takers became less predictable) in the MP treated group. These findings underscore the intricate effects of MPs on individual behavioural variation, with potentially far-reaching ecological and evolutionary consequences given their pervasive presence in both terrestrial and aquatic ecosystems. The negative impacts of these changes are widespread; in our study, MP exposure may increase the susceptibility of A. vulgare to predation, potentially contributing to population decline.
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Affiliation(s)
- Gergely Horváth
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary; HUN-REN-ELTE-MTM Integrative Ecology Research Group, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary.
| | - Dávid Herczeg
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary; HUN-REN-ELTE-MTM Integrative Ecology Research Group, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary
| | - Boglárka Kovács
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary
| | - Ágnes Péntek
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary
| | - Bettina Kaczur
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary
| | - Gábor Herczeg
- Department of Systematic Zoology and Ecology, Institute of Biology, ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary; HUN-REN-ELTE-MTM Integrative Ecology Research Group, Pázmány Péter Sétány 1/c, Budapest, H-1117, Hungary
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Kini SU, My Thi Vy H, Subramanian M, Krishnamoorthy PM, Duong SQ, Rocheleau G, Narula J, Do R, Nadkarni GN. Associations between pathophysiological traits and symptom development in retrospective analysis of V30M and V122I transthyretin amyloidosis. IJC HEART & VASCULATURE 2025; 58:101663. [PMID: 40276302 PMCID: PMC12019459 DOI: 10.1016/j.ijcha.2025.101663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2025] [Revised: 03/19/2025] [Accepted: 03/20/2025] [Indexed: 04/26/2025]
Abstract
Background The Val30Met (V30M) and Val122Ile (V122I) transthyretin (TTR) mutations often beget hereditary amyloid transthyretin amyloidosis (hATTR). Since symptoms are progressively debilitating and potentially fatal if untreated, low survival rates result from late diagnoses of hATTR patients. This retrospective analysis of microarray and biobank data helped establish clinical biomarkers for early hATTR detection. Methods In a Portuguese sample of V30M carriers (n = 183), gene profiling identified dysregulated immune markers. Among African Americans (AA) and Hispanic/Latinx Americans (HA) from the Mount Sinai BioMe Biobank (n = 28,718), a case-control style Phenome-Wide Association Study (PheWAS; odds ratio [95% confidence interval]) of V122I for phenotypic and echocardiogram traits (β coefficients [95 % CI]) determined gene pleiotropy. Results Among V30M profiles, 96 (52.4%) were symptomatic, expressing upregulated neutrophil activity (p < 10-16), IL-6/JAK/STAT3 signaling (p < 10-3), and downregulated CD4+T cell expression (p = 0.009), compared to their asymptomatic counterparts. In BioMe, 562 (2.0%) were V122I carriers, demonstrating associations with heart failure (1.71 [1.23-2.39]; p = 0.0014), amyloidosis (20.79 [8.42-51.31]; p = 4.67 × 10-11), secondary/extrinsic cardiomyopathies (17.73 [7.25-43.37]; p = 2.97 × 10-10), peripheral nerve disorders (4.14 [2.42-7.09]; p = 2.26 × 10-7), primary angle-closure glaucoma (8.03 [3.15-20.46]; p = 1.27 × 10-5), malignant neoplasm of the female breast (4.48 [2.23-9.00]; p = 2.48 × 10-5), fracture of tibia and fibula (8.42 [3.25-21.89]; p = 1.19 × 10-5), and Carpal tunnel syndrome (2.62 [1.68-4.11]; p = 2.44 × 10-5). Echocardiographic presentations included higher LVEDV (15.87 [9.63-22.10]; p = 6.04 × 10-7) and LA length (1.52 [0.69-2.35]; p = 3.31 × 10-4). Race-stratified associations identified that AA presented more severe cardiac abnormalities than HA. Conclusions This study identified inflammatory biomarkers upregulated in symptomatic V30M carriers and phenotypic/echocardiographic traits associated with V122I, representing comorbidities of hATTR pathology. Such markers can provide the basis for future improvements in diagnostic regimes to deliver early therapies.
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Affiliation(s)
- Sameer U. Kini
- Scarsdale High School, Scarsdale, NY, United States of America
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ha My Thi Vy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Bio Me Phenomics Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Madhav Subramanian
- Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, MO, United States of America
| | - Parasuram M. Krishnamoorthy
- Department of Medicine, Division of Cardiology, Mount Sinai Hospital, New York, NY, United States of America
| | - Son Q. Duong
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Division of Pediatric Cardiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ghislain Rocheleau
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Jagat Narula
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Bio Me Phenomics Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Bio Me Phenomics Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Division of Data Driven and Digital Medicine (D3M), Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
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Köse AM, Petzold P, Zocholl D, Kostoulas P, Rose M, Fischer F. Prevalence Estimation Using a Depression Screening Tool in the National Health and Nutrition Examination Survey: Comparison of Different Cutoffs. Int J Methods Psychiatr Res 2025; 34:e70019. [PMID: 40178057 PMCID: PMC11966556 DOI: 10.1002/mpr.70019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2024] [Revised: 02/25/2025] [Accepted: 03/12/2025] [Indexed: 04/05/2025] Open
Abstract
OBJECTIVES The National Health and Nutrition Examination Survey (NHANES) in the US relies on the depression screening tool PHQ-9 to assess depressive symptoms in the general population. For prevalence estimation, PHQ-9s imperfect diagnostic accuracy can be modeled with a Bayesian Latent Class Model. We investigate the impact of different cutoffs on prevalence estimation. METHODS We used data from the 16-th wave of the National Health and Nutrition Examination Survey (NHANES). We assessed the joint posterior distribution to asssess the prevalence of major depression as well as sensitivity and specificity of the PHQ-9 at cutoffs 5 to 15. We also assessed the impact of weakly and strongly informative prevalence priors. RESULTS Data from 9693 participants of the NHANES Wave 2019-2020 were analyzed. Under weakly informative prevalence priors, prevalence estimates ranged from 16.0% (95% CrI: 0.3%-87.8%) when using a cut-off of 5% to 3.9% (0.2%-12.7%) at 13. More informative prevalence priors led to narrower credible intervals, but the observed data was still in accordance with a wide range of possible MDD prevalence estimates. CONCLUSIONS Regardless of the cutoff and the prevalence prior chosen, prevalence estimation of major depressive disorders in the NHANES based on the PHQ-9 is imprecise.
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Affiliation(s)
- Ali Mertcan Köse
- Department of Computer ProgrammingIstanbul Ticaret UniversityIstanbulTurkey
| | - Paul Petzold
- Charité – Universitätsmedizin BerlinCorporate Member of Freie Universität Berlin and Humboldt Universität zu BerlinMedizinische Klinik Mit Schwerpunkt für PsychosomatikCenter for Patient‐Centered Outcomes ResearchBerlinGermany
| | - Dario Zocholl
- Institute of Medical BiometryInformatics and EpidemiologyUniversity Hospital BonnBonnGermany
| | - Polychronis Kostoulas
- Laboratory of Epidemiology & Artificial IntelligenceFaculty of Public & One HealthUniversity of ThessalyKarditsaGreece
| | - Matthias Rose
- Charité – Universitätsmedizin BerlinCorporate Member of Freie Universität Berlin and Humboldt Universität zu BerlinMedizinische Klinik Mit Schwerpunkt für PsychosomatikCenter for Patient‐Centered Outcomes ResearchBerlinGermany
- German Center for Mental Health (DZPG)BerlinGermany
| | - Felix Fischer
- Charité – Universitätsmedizin BerlinCorporate Member of Freie Universität Berlin and Humboldt Universität zu BerlinMedizinische Klinik Mit Schwerpunkt für PsychosomatikCenter for Patient‐Centered Outcomes ResearchBerlinGermany
- German Center for Mental Health (DZPG)BerlinGermany
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Schipper N, Bodmer M, Dufour S, Hommels NMC, Nielen M, van den Borne BHP. Network meta-analysis based ranking of dry off interventions to cure or prevent intramammary infections in dairy cows. Prev Vet Med 2025; 239:106487. [PMID: 40073588 DOI: 10.1016/j.prevetmed.2025.106487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2024] [Revised: 02/14/2025] [Accepted: 02/19/2025] [Indexed: 03/14/2025]
Abstract
This study aimed to rank dry off interventions for the prevention of new intramammary infections (IMI) and the cure of existing IMI in quarters of dry cows using two network meta-analyses. Randomized controlled trials reported in 137 papers were assessed for inclusion eligibility. Network meta-analyses were performed separately for the incidence risk of IMI and cure risk of IMI. For cure of IMI, 29 trials with 10 dry off interventions were included. Both selective and blanket dry cow therapy, either in combination with an internal teat sealant or as a singular intervention, resulted in a better cure risk compared with the non-antimicrobial interventions. No differences were observed between the antimicrobial based interventions. For the incidence risk of IMI, 54 trials were included, representing 18 dry off interventions. The incidence risk of IMI was similar for the various selective dry cow treatments when antimicrobials were administered together with an internal teat sealant, either at quarter or cow level. Also, they did not differ from the evaluated blanket dry cow treatment interventions or when an internal teat sealant was applied alone. Selective dry cow therapy with internal teat sealant is therefore likely a suitable intervention option to simultaneously maintain a low incidence risk of IMI and a high cure risk of IMI, all the while lowering the antimicrobial use in dairy herds. Circumstances in the herd, including the distribution and prevalence of mastitis pathogens, should be evaluated before results are utilized in dairy practice given the heterogeneity of included studies.
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Affiliation(s)
- Nynke Schipper
- Infectious Disease Epidemiology, Wageningen University and Research, Wageningen 6700 AH, the Netherlands
| | - Michèle Bodmer
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bern 3012, Switzerland
| | - Simon Dufour
- Regroupement Op+lait, Saint-Hyacinthe, QC J2S 2M2, Canada; Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC J2S 2M2, Canada
| | - Nina M C Hommels
- Business Economics Group, Wageningen University and Research, Wageningen 6700 EW, the Netherlands
| | - Mirjam Nielen
- Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584 CL, the Netherlands
| | - Bart H P van den Borne
- Infectious Disease Epidemiology, Wageningen University and Research, Wageningen 6700 AH, the Netherlands; Business Economics Group, Wageningen University and Research, Wageningen 6700 EW, the Netherlands.
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Li S, Quan J, Li S, Li S, Chen C, Huang R. Identification and validation of m7G-related genes related to macrophage immunity in acute myocardial infarction through comprehensive bioinformatics analysis. Biochem Biophys Res Commun 2025; 760:151684. [PMID: 40174368 DOI: 10.1016/j.bbrc.2025.151684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2024] [Revised: 02/19/2025] [Accepted: 03/21/2025] [Indexed: 04/04/2025]
Abstract
BACKGROUND Acute myocardial infarction (AMI) is a fatal disease related to immune cell activation; however, the pathological molecular mechanisms associated with AMI and immunity remain unclear. This study aims to explore m7G-related hub genes associated with immune cell characteristics in AMI through the bioinformatics method. METHODS Transcriptome sequencing data downloaded from GSE59867 (GPL6244) were used to screen m7G-related differentially expressed genes (DEGs) between AMI and non-AMI controls. Abnormal immune cell characteristics was analyzed by single-sample gene set enrichment analysis (ssGSEA) algorithm. Hub genes were screened from m7G-related DEGs by the support vector machine recursive feature elimination (SVM-RFE) algorithm and random forest tree model. The association of hub genes with immune cell types was analyzed by GSEA and Spearman correlation analysis. A mouse AMI model and hypoxia-stimulated macrophage model were established to verified the function of CYFIP1 on macropahges. RESULTS We identified significant differences in 21 types of immune cells and 13 m7G-related DEGs between AMI and non-AMI controls. m7G-related DEGs were enriched in nucleoside nuclear catabolism, RNA modification and translation regulation, the HIF-1 signaling pathway, etc. 111 AMI samples were divided into three clusters based on the cluster analysis of m7G-related DEG expression profiles, and immune cell types were significantly different in the three clusters. Four hub genes including CYFIP1, EIF4E2, IFIT5, and NCBP3 were screened and positively or negatively correlated with AMI. ROC curve verified the efficiency of the 4 hub genes in the diagnosis prediction models of AMI. CYFIP1 had the best prediction efficiency of than other 3 hub genes. GESA enrichment and Spearman correlation analysis found that hub genes were associated with inflammation and immune, especially CYFIP1 had a strong statistical relationship with macrophages, Monocyte, etc. By experiments, we found that CYFIP1 was upregulated in AMI patients and animal models, and knockdown of CYFIP1 inhibited hypoxia-mediated macrophage inflammatory response. CONCLUSION m7G-related hub genes are associated with immune cell characteristics in AMI, among which CYFIP1 may play a key role in the regulatory network of macrophage immune response.
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Affiliation(s)
- Shanghai Li
- Affiliated Hospital of Guangdong Medical University, China
| | - Jinhai Quan
- Affiliated Hospital of Guangdong Medical University, China
| | - Shisen Li
- Affiliated Hospital of Guangdong Medical University, China
| | - Shihai Li
- Affiliated Hospital of Guangdong Medical University, China.
| | - Can Chen
- Affiliated Hospital of Guangdong Medical University, China.
| | - Ruina Huang
- Affiliated Hospital of Guangdong Medical University, China.
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van Vugt LK, Zwart TC, Bezstarosti S, Heidt S, Reinders MEJ, Hesselink DA, de Vries APJ, de Winter BCM, Moes DJAR. Alemtuzumab Exposure and T Lymphocyte Depletion: A Population Pharmacokinetic-Pharmacodynamic Model of Alemtuzumab Induction Therapy for Kidney Transplantation. Clin Pharmacol Ther 2025. [PMID: 40374867 DOI: 10.1002/cpt.3714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2025] [Accepted: 04/22/2025] [Indexed: 05/18/2025]
Abstract
Alemtuzumab is a T cell-depleting monoclonal antibody that is used for the prevention of kidney transplant rejection. The duration of lymphodepletion after the current standard induction therapy dose is likely longer than necessary, resulting in prolonged T cell lymphopenia with the associated risk of infections. Here, the interplay between alemtuzumab exposure and T cell dynamics was quantitatively evaluated, and the influence of different doses on T cell recovery was investigated. A population pharmacokinetic-pharmacodynamic model describing the interplay between 30 mg alemtuzumab induction therapy and T cell dynamics in kidney transplantation was developed using NONMEM, using pharmacodynamic data from the Triton study (NCT02057965). The developed model was used to perform an exposure-response analysis and investigate dose optimization with model-derived simulations. In total, 418 peripheral blood T cell measurements from 61 adult kidney transplant recipients were included for model development. A single-compartment turnover Emax model with a first-order T cell influx with feedback and a first-order T cell efflux with parallel alemtuzumab-stimulated T cell removal best described the data. Higher alemtuzumab exposure was associated with lower individual-predicted T cells 4 weeks after administration and longer T cell recovery (> 200 cells/μL). In the simulations, a fixed dose of 15 mg improved median recovery times by 19 days as compared to the standard 30 mg dose without influencing early T cell depletion. A population pharmacokinetic-pharmacodynamic model adequately described T cell dynamics after alemtuzumab induction therapy in kidney transplant recipients. This model can be used to inform future dose-optimization studies of alemtuzumab in different clinical settings.
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Affiliation(s)
- Lukas K van Vugt
- Erasmus MC Transplant Institute, Rotterdam, The Netherlands
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tom C Zwart
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Hospital Pharmacy, Haga Teaching Hospital, The Hague, The Netherlands
| | - Suzanne Bezstarosti
- Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sebastiaan Heidt
- Erasmus MC Transplant Institute, Rotterdam, The Netherlands
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marlies E J Reinders
- Erasmus MC Transplant Institute, Rotterdam, The Netherlands
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Leiden University Medical Center, Leiden, The Netherlands
| | - Dennis A Hesselink
- Erasmus MC Transplant Institute, Rotterdam, The Netherlands
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Aiko P J de Vries
- Leiden Transplant Center, Leiden University Medical Center, Leiden, The Netherlands
- Division of Nephrology, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Brenda C M de Winter
- Department of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Dirk Jan A R Moes
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
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Belov DI, Lüdtke O, Ulitzsch E. A supervised learning approach to estimating IRT models in small samples. THE BRITISH JOURNAL OF MATHEMATICAL AND STATISTICAL PSYCHOLOGY 2025. [PMID: 40371820 DOI: 10.1111/bmsp.12396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 04/30/2025] [Indexed: 05/16/2025]
Abstract
Existing estimators of parameters of item response theory (IRT) models exploit the likelihood function. In small samples, however, the IRT likelihood oftentimes contains little informative value, potentially resulting in biased and/or unstable parameter estimates and large standard errors. To facilitate small-sample IRT estimation, we introduce a novel approach that does not rely on the likelihood. Our estimation approach derives features from response data and then maps the features to item parameters using a neural network (NN). We describe and evaluate our approach for the three-parameter logistic model; however, it is applicable to any model with an item characteristic curve. Three types of NNs are developed, supporting the obtainment of both point estimates and confidence intervals for IRT model parameters. The results of a simulation study demonstrate that these NNs perform better than Bayesian estimation using Markov chain Monte Carlo methods in terms of the quality of the point estimates and confidence intervals while also being much faster. These properties facilitate (1) pretesting items in a real-time testing environment, (2) pretesting more items and (3) pretesting items only in a secured environment to eradicate possible compromise of new items in online testing.
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Affiliation(s)
- Dmitry I Belov
- Law School Admission Council, Newtown, Pennsylvania, USA
| | - Oliver Lüdtke
- IPN - Leibniz Institute for Science and Mathematics Education, Kiel, Germany
- Centre for International Student Assessment, Munich, Germany
| | - Esther Ulitzsch
- IPN - Leibniz Institute for Science and Mathematics Education, Kiel, Germany
- Centre for Educational Measurement, University of Oslo, Oslo, Norway
- Centre for Research on Equality in Education, University of Oslo, Oslo, Norway
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Zhang P, Sun C, Zhu Z, Miao J, Wang P, Zhang Q, Wang L, Qin Y, Wu T, Yao Z, Hu B, Wang Y, Xue W, Sun D. Depressive symptoms changes in the new-onset stroke patients: A cross-lagged panel network analysis. J Affect Disord 2025; 377:198-205. [PMID: 39983780 DOI: 10.1016/j.jad.2025.02.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 02/17/2025] [Accepted: 02/18/2025] [Indexed: 02/23/2025]
Abstract
BACKGROUND Each year, there are approximately 10.3 million new stroke cases worldwide, with 2 million occurring in China. Post-stroke depression (PSD) is a common complication that negatively affects rehabilitation outcomes and increases long-term mortality. OBJECTIVE This study used network analysis to investigate the cross-sectional and longitudinal networks between depressive symptoms in new-onset stroke patients with PSD, aiming to identify the key symptoms and predictive relationships among distinct symptoms during the acute phase and 6 months after the stroke. METHODS This longitudinal descriptive study collected data from October 2022 to December 2023, including eligible new-onset stroke patients. Depressive symptoms were assessed using the CES-D scale, and network analysis was used to analyze the interactions between symptoms. RESULTS 613 participants completed the data collection. The study found that D3 (Felt sadness) emerged as the central depressive symptom at both baseline and follow-up (EI value = 1.215 and 1.168, respectively). In the longitudinal network analysis, D7 (Sleep quality) displayed the strongest out-Expected Influence (value = 1.728), while D4 (Everything was an effort) showed the strongest in-Expected Influence (value = 1.322). LIMITATIONS The self-report measure is adopted for all depressive symptoms in the study, and there may be some deviation. CONCLUSION These symptom-level associations at cross-sectional and longitudinal networks extend our understanding of PSD symptoms in new-onset stroke patients by pointing to specific key depressive symptoms that may aggravate PSD. Recognizing these symptoms is imperative for the development of targeted interventions and treatments aimed at addressing PSD in new-onset stroke patients.
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Affiliation(s)
- Peijia Zhang
- Department of Nursing, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, Henan 450003, China.
| | - Changqing Sun
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhengqi Zhu
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Jixing Miao
- School of Chemical Engineering, Zhengzhou University, Zhengzhou, Henan, China
| | - Panpan Wang
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Qiang Zhang
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Lianke Wang
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Ying Qin
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Tiantian Wu
- Department of Nursing, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, Henan 450003, China
| | - Zihui Yao
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Bo Hu
- Department of Nursing, Haining Fourth People's Hospital, Haining, Zhejiang, China
| | - Yu Wang
- Department of Nursing, The First Affiliated Hospital of Xinxiang Medical College, Xinxiang University People's Hospital, Zhengzhou, Henan, China
| | - Wei Xue
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Dequan Sun
- School of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China
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Lou N, Dai L, Gao R, Yang J, Gui L, Yang S, Liu P, Shi Y, Han X. Single-cell sequencing and spatial transcriptomics reveal FAS+ T cell and autophagy-related signatures predicting chemoimmunotherapy response in diffuse large B-cell lymphoma patients. SCIENCE CHINA. LIFE SCIENCES 2025:10.1007/s11427-024-2849-2. [PMID: 40374987 DOI: 10.1007/s11427-024-2849-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Accepted: 03/12/2025] [Indexed: 05/18/2025]
Abstract
Current subtyping methods of diffuse large B-cell lymphoma (DLBCL) could not satisfy the clinical demands for risk assessment and prognostic prediction. We aimed to investigate the prognostic effect of autophagy-related genes (ARGs) in DLBCL. Transcriptomic data of 1,409 DLBCL patients, 531 healthy controls (HCs), and single-cell sequencing data of 4 DLBCL were included. Validation involved spatial transcriptomics from 10 DLBCL patients and 110 DLBCL proteomic data from a local cohort. We identified 153 differentially expressed ARGs between DLBCL patients (n=48) and HCs (n=531), classifying 414 DLBCL patients into two subtypes based on autophagy heterogeneity. Subtype I, characterized by upregulated T regulatory (Treg) cells (P<0.0001) and T follicular helper (Tfh) cells (P=0.0012), showed a superior prognosis (P=0.035). Eight prognostic ARGs were selected to construct an autophagy-related model, dividing patients into low- and high-risk groups. Kaplan-Meier survival analysis revealed significantly better outcomes for the low-risk group in both the discovery (P<0.0001) and validation cohorts (P=0.0041). High-risk patients exhibited elevated IDO1 (P=0.042) and LAG3 (P<0.001) levels. Among the eight signature proteins, higher FAS was further verified to indicate a better prognosis in the local cohort (n=110) using antibody array (P=0.0083). FAS was primarily expressed in T cells such as Treg and Tfh cells and was elevated in non-progressive disease patients. FAS-positive T cells showed increased interferon-gamma (normalized enrichment score (NES)=2.196, FDR<0.0001) and alpha (NES=1.836, FDR<0.01) response activities. We constructed an autophagy-related model and identified FAS as a prognostic biomarker. FAS+ Treg and Tfh cell-enriched TME indicated a favorable prognosis.
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Affiliation(s)
- Ning Lou
- Clinical Pharmacology Research Center, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Liyuan Dai
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Ruyun Gao
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Jianliang Yang
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Lin Gui
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Sheng Yang
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Peng Liu
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China
| | - Yuankai Shi
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100021, China.
| | - Xiaohong Han
- Clinical Pharmacology Research Center, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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