A novel ESIPT fluorescent probe for early detection and assessment of ferroptosis-mediated acute kidney injury via peroxynitrite fluctuation

BACKGROUND

Acute kidney injury (AKI) poses a severe risk to public health, mostly manifested by damage and death of renal tubular epithelial cells. However, routine blood examination, a conventional approach for clinical detection of AKI, is not available for identifying early-stage AKI. Plenty of reported methods were lack of early biomarkers and real time evaluation tools, which resulted in a vital challenge for early diagnosis of AKI. Therefore, developing novel probes for early detection and assessment of AKI is exceedingly crucial.

RESULTS

Based on ESIPT mechanism, a new fluorescent probe (MEO-NO) with 2-(2'-hydroxyphenyl) benzothiazole (HBT) derivatives as fluorophore has been synthesized for dynamic imaging peroxynitrite (ONOO-) levels in ferroptosis-mediated AKI. Upon the addition of ONOO-, MEO-NO exhibited obvious fluorescence changes, a significant Stokes shift (130 nm) and rapid response (approximately 45 s), and featured exceptional sensitivity (LOD = 7.28 nM) as well as high selectivity from the competitive species at physiological pH. In addition, MEO-NO was conducive to the biological depth imaging ONOO- in cells, zebrafish, and mice. Importantly, MEO-NO could monitor ONOO- levels during sorafenib-induced ferroptosis and CP-induced AKI. With the assistance of MEO-NO, we successfully visualized and tracked ONOO- variations for early detection and assessment of ferroptosis-mediated AKI in cells, zebrafish and mice models.

SIGNIFICANCE AND NOVELTY

Benefiting from the superior performance of MEO-NO, experimental results further demonstrated that the levels of ONOO- was overexpressed during ferroptosis-mediated AKI in cells, zebrafish, and mice models. The developed novel probe MEO-NO provided a strong visualization tool for imagining ONOO-, which might be a potential method for the prevention, diagnosis, and treatment of ferroptosis-mediated AKI.

The non-stationary and spatially varying associations between hand, foot and mouth disease and multiple environmental factors: A Bayesian spatiotemporal mapping model study

The transmission and prevalence of Hand, Foot and Mouth Disease (HFMD) are affected by a variety of natural and socio-economic environmental factors. This study aims to quantitatively investigate the non-stationary and spatially varying associations between various environmental factors and HFMD risk. We collected HFMD surveillance cases and a series of relevant environmental data from 2013 to 2021 in Xi'an, Northwest China. By controlling the spatial and temporal mixture effects of HFMD, we constructed a Bayesian spatiotemporal mapping model and characterized the impacts of different driving factors into global linear, non-stationary and spatially varying effects. The results showed that the impact of meteorological conditions on HFMD risk varies in both type and magnitude above certain thresholds (temperature: 30 °C, precipitation: 70 mm, solar radiation: 13000 kJ/m2, pressure: 945 hPa, humidity: 69%). Air pollutants (PM2.5, PM10, NO2) showed an inverted U-shaped relationship with the risk of HFMD, while other air pollutants (O3, SO2) showed nonlinear fluctuations. Moreover, the driving effect of increasing temperature on HFMD was significant in the 3-year period, while the inhibitory effect of increasing precipitation appeared evident in the 5-year period. In addition, the proportion of urban/suburban/rural area had a strong influence on HFMD, indicating that the incidence of HFMD firstly increased and then decreased during the rapid urbanization process. The influence of population density on HFMD was not only limited by spatial location, but also varied between high and low intervals. Higher road density inhibited the risk of HFMD, but higher night light index promoted the occurrence of HFMD. Our findings further demonstrated that both ecological and socioeconomic environmental factors can pose multiple driving effects on increasing the spatiotemporal risk of HFMD, which is of great significance for effectively responding to the changes in HFMD epidemic outbreaks.

Federated Learning With Only Positive Labels by Exploring Label Correlations

Federated learning (FL) aims to collaboratively learn a model by using the data from multiple users under privacy constraints. In this article, we study the multilabel classification (MLC) problem under the FL setting, where trivial solution and extremely poor performance may be obtained, especially when only positive data with respect to a single class label is provided for each client. This issue can be addressed by adding a specially designed regularizer on the server side. Although effective sometimes, the label correlations are simply ignored and thus suboptimal performance may be obtained. Besides, it is expensive and unsafe to exchange user's private embeddings between server and clients frequently, especially when training model in the contrastive way. To remedy these drawbacks, we propose a novel and generic method termed federated averaging (FedAvg) by exploring label correlations (FedALCs). Specifically, FedALC estimates the label correlations in the class embedding learning for different label pairs and utilizes it to improve the model training. To further improve the safety and also reduce the communication overhead, we propose a variant to learn fixed class embedding for each client, so that the server and clients only need to exchange class embeddings once. Extensive experiments on multiple popular datasets demonstrate that our FedALC can significantly outperform the existing counterparts.

Mineralocorticoid Receptor Antagonists in Patients With Heart Failure and Impaired Renal Function

BACKGROUND

Kidney dysfunction often leads to reluctance to start or continue life-saving heart failure (HF) therapy.

OBJECTIVES

This study sought to examine the efficacy and safety of mineralocorticoid receptor antagonists (MRAs) in patients with HF with reduced ejection fraction experiencing significant kidney dysfunction.

METHODS

We pooled individual patient data from the RALES (Randomized Aldactone Evaluation Study) and EMPHASIS-HF (Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure) trials. The association between MRA treatment and outcomes was assessed according to whether the estimated glomerular filtration rate (eGFR) declined to <30 mL/min/1.73 m2 or not. The primary outcome was cardiovascular death or HF hospitalization.

RESULTS

Among 4,355 patients included, 295 (6.8%) experienced a deterioration of eGFR after randomization to <30 mL/min/1.73 m2. These patients had more impaired baseline cardiac and kidney function (eGFR 47.3 ± 13.4 mL/min/1.73 m2 vs 70.5 ± 21.8 mL/min/1.73 m2) and had a higher risk of the primary outcome than patients without eGFR deterioration (HR: 2.49; 95% CI: 2.01-3.08; P < 0.001). However, the risk reduction in the primary outcome with MRA therapy was similar in those who experienced a decrease in eGFR to <30 mL/min/1.73 m2 (HR: 0.65; 95% CI: 0.43-0.99) compared with those who did not (HR: 0.63; 95% CI: 0.56-0.71) (Pinteraction = 0.87). In patients with a decrease in eGFR to <30 mL/min/1.73 m2, 21 fewer individuals (per 100 person-years) experienced the primary outcome with MRA treatment, vs placebo, compared with an excess of 3 more patients with severe hyperkalemia (>6.0 mmol/L).

CONCLUSIONS

Because patients experiencing a decrease in eGFR to <30 mL/min/1.73 m2 are at very high risk, the absolute risk reduction with an MRA in these patients is large and this decline in eGFR should not automatically lead to treatment discontinuation.

DaGAN++: Depth-Aware Generative Adversarial Network for Talking Head Video Generation

Predominant techniques on talking head generation largely depend on 2D information, including facial appearances and motions from input face images. Nevertheless, dense 3D facial geometry, such as pixel-wise depth, plays a critical role in constructing accurate 3D facial structures and suppressing complex background noises for generation. However, dense 3D annotations for facial videos is prohibitively costly to obtain. In this paper, first, we present a novel self-supervised method for learning dense 3D facial geometry (i.e., depth) from face videos, without requiring camera parameters and 3D geometry annotations in training. We further propose a strategy to learn pixel-level uncertainties to perceive more reliable rigid-motion pixels for geometry learning. Second, we design an effective geometry-guided facial keypoint estimation module, providing accurate keypoints for generating motion fields. Lastly, we develop a 3D-aware cross-modal (i.e., appearance and depth) attention mechanism, which can be applied to each generation layer, to capture facial geometries in a coarse-to-fine manner. Extensive experiments are conducted on three challenging benchmarks (i.e., VoxCeleb1, VoxCeleb2, and HDTF). The results demonstrate that our proposed framework can generate highly realistic-looking reenacted talking videos, with new state-of-the-art performances established on these benchmarks.

Spatial-temporal trends in leprosy burden and its associations with socioeconomic and physical geographic factors: results from the Global Burden of Disease Study 2019

OBJECTIVES

The purpose of our study was to assess the multiscalar changes in leprosy burden and its associated risk factors over the last three decades.

STUDY DESIGN

We conducted an in-depth examination of leprosy's spatial-temporal trends at multiple geographical scale (global, regional, and national), utilizing information from Global Burden of Disease, Injuries, and Risk Factors Study (GBD 2019).

METHODS

Incidence and the estimated annual percentage change (EAPC) in age-standardized incidence rate (ASIR) of leprosy were determined, with countries categorized based on leprosy incidence changes. We examined socioeconomic and physical geography influences on leprosy incidence via Spearman correlation analysis, using ternary phase diagrams to reveal the synergetic effects on leprosy occurrence.

RESULTS

Globally, incident cases of leprosy decreased by 27.86% from 1990 to 2019, with a reduction in ASIR (EAPC = -2.53), yet trends were not homogeneous across regions. ASIR and EAPC correlated positively with sociodemographic index (SDI), and an ASIR growth appeared in high SDI region (EAPC = 3.07). Leprosy burden was chiefly distributed in Tropical Latin America, Oceania, Central Sub-Saharan Africa, and South Asia. Negative correlations were detected between the incidence of leprosy and factors of SDI, GDP per capita, urban population to total population, and precipitation, whereas the number of refugee population, temperature, and elevation showed opposite positive results.

CONCLUSIONS

Despite a global decline in leprosy over the past three decades, the disparities of disease occurrence at regional and national scales still persisted. Socioeconomic and physical geographic factors posed an obvious influence on the transmission risk of leprosy. The persistence and regional fluctuations of leprosy incidence necessitate the ongoing dynamic and multilayered control strategies worldwide in combating this ancient disease.

Multiplexed Serum Biomarkers to Discriminate Nonviable and Ectopic Pregnancy

OBJECTIVE

The use of multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies. In this study we assessed 24 markers with multiple machine learning-based methodologies to evaluate combinations of top candidates to develop a multiplexed prediction model for identification of 1) viability and 2) location of an early pregnancy.

DESIGN

A nested case-control design evaluating the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location SUBJECTS: 218 individuals with a symptomatic (pain and/or bleeding) early pregnancy: 75 with an ongoing intrauterine gestation, 68 ectopic pregnancies, and 75 miscarriages.

INTERVENTIONS

Serum values of 24 biomarkers were assessed in the same patients. Multiple machine learning-based methodologies to evaluate combinations of these top candidates to develop a multiplexed prediction model for identification of 1) a nonviable pregnancy (ongoing intrauterine pregnancy vs miscarriage or ectopic pregnancy) and 2) an ectopic pregnancy (ectopic pregnancy vs ongoing intrauterine pregnancy or miscarriage).

MAIN OUTCOME MEASURES

The predicted classification by each model was compared to actual diagnosis and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), conclusive classification, and accuracy were calculated.

RESULTS

Models using classification regression tree analysis using three markers (PSG3, CG-Alpha and PAPPA) were able to predict a maximum sensitivity 93.3%, a maximum specificity 98.6%. The model with the highest accuracy was 97.4% (with 70.2% receiving classification). Models using an overlapping group of three markers (sFLT, PSG3 and TFP12) achieved a maximum sensitivity of 98.5%. and a maximum specificity of 95.3%. The model with the highest accuracy was 94.4% (with 65.6% receiving classification). When the models were used simultaneously the conclusive classification increased to 72.7% with an accuracy 95.9%. The predictive ability of the biomarkers random forest produced similar test characteristics when using 11 predictive markers.

CONCLUSION

We have demonstrated a pool of biomarkers from divergent biological pathways that can be used to classify individuals with potential early pregnancy loss. The biomarkers CG-Alpha, PAPPA and PSG3 can be used to predict viability and sFLT, TPFI2 and PSG3 can be used to predict pregnancy location.

Acetyl-CoA metabolic accumulation promotes hepatocellular carcinoma metastasis via enhancing CXCL1-dependent infiltration of tumor-associated neutrophils

High levels of acetyl-CoA are considered a key metabolic feature of metastatic cancers. However, the impacts of acetyl-CoA metabolic accumulation on cancer microenvironment remodeling are poorly understood. In this study, using human hepatocellular carcinoma (HCC) tissues and orthotopic xenograft models, we found a close association between high acetyl-CoA levels in HCCs, increased infiltration of tumor-associated neutrophils (TANs) in the cancer microenvironment and HCC metastasis. Cytokine microarray and enzyme-linked immunosorbent assays (ELISA) revealed the crucial role of the chemokine (C-X-C motif) ligand 1(CXCL1). Mechanistically, acetyl-CoA accumulation induces H3 acetylation-dependent upregulation of CXCL1 gene expression. CXCL1 recruits TANs, leads to neutrophil extracellular traps (NETs) formation and promotes HCC metastasis. Collectively, our work linked the accumulation of acetyl-CoA in HCC cells and TANs infiltration, and revealed that the CXCL1-CXC receptor 2 (CXCR2)-TANs-NETs axis is a potential target for HCCs with high acetyl-CoA levels.

The oncogenic role and regulatory mechanism of ACAA2 in human ovarian cancer

Acetyl-CoAacyltransferase2 (ACAA2) is a key enzyme in the fatty acid oxidation pathway that catalyzes the final step of mitochondrial β oxidation, which plays an important role in fatty acid metabolism. The expression of ACAA2 is closely related to the occurrence and malignant progression of tumors. However, the function of ACAA2 in ovarian cancer is unclear. The expression level and prognostic value of ACAA2 were analyzed by databases. Gain and loss of function were carried out to explore the function of ACAA2 in ovarian cancer. RNA-seq and bioinformatics methods were applied to illustrate the regulatory mechanism of ACAA2. ACAA2 overexpression promoted the growth, proliferation, migration, and invasion of ovarian cancer, and ACAA2 knockdown inhibited the malignant progression of ovarian cancer as well as the ability of subcutaneous tumor formation in nude mice. At the same time, we found that OGT can induce glycosylation modification of ACAA2 and regulate the karyoplasmic distribution of ACAA2. OGT plays a vital role in ovarian cancer as a function of oncogenes. In addition, through RNA-seq sequencing, we found that ACAA2 regulates the expression of DIXDC1. ACAA2 regulated the malignant progression of ovarian cancer through the WNT/β-Catenin signaling pathway probably. ACAA2 is an oncogene in ovarian cancer and has the potential to be a target for ovarian cancer therapy.

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.

Targeting deubiquitinase OTUB1 protects vascular smooth muscle cells in atherosclerosis by modulating PDGFRβ

Atherosclerosis is a chronic artery disease that causes various types of cardiovascular dysfunction. Vascular smooth muscle cells (VSMCs), the main components of atherosclerotic plaque, switch from contractile to synthetic phenotypes during atherogenesis. Ubiquitylation is crucial in regulating VSMC phenotypes in atherosclerosis, and it can be reversely regulated by deubiquitinases. However, the specific effects of deubiquitinases on atherosclerosis have not been thoroughly elucidated. In this study, RNAi screening in human aortic smooth muscle cells was performed to explore the effects of OTU family deubiquitinases, which revealed that silencing OTUB1 inhibited PDGF-BB-stimulated VSMC phenotype switch. Further in vivo studies using Apoe-/- mice revealed that knockdown of OTUB1 in VSMCs alleviated atherosclerosis plaque burden in the advanced stage and led to a stable plaque phenotype. Moreover, VSMC proliferation and migration upon PDGF-BB stimulation could be inhibited by silencing OTUB1 in vitro. Unbiased RNA-sequencing data indicated that knocking down OTUB1 influenced VSMC differentiation, adhesion, and proliferation. Mass spectrometry of ubiquitinated protein confirmed that proteins related to cell growth and migration were differentially ubiquitylated. Mechanistically, we found that OTUB1 recognized the K707 residue ubiquitylation of PDGFRβ with its catalytic triad, thereby reducing the K48-linked ubiquitylation of PDGFRβ. Inhibiting OTUB1 in VSMCs could promote PDGFRβ degradation via the ubiquitin-proteasome pathway, so it was beneficial in preventing VSMCs' phenotype switch. These findings revealed that knocking down OTUB1 ameliorated VSMCs' phenotype switch and atherosclerosis progression, indicating that OTUB1 could be a valuable translational therapeutic target in the future.

[Upregulating KLF11 ameliorates intestinal inflammation in mice with 2, 4, 6-trinitrobenesulfonic acid-induced colitis by inhibiting the JAK2/STAT3 signaling pathway]

OBJECTIVE

To investigate the expression level of Kruppel-like transcription factor family member KLF11 in intestinal mucosal tissues of Crohn's disease (CD) and its regulatory effect on intestinal inflammation in CD-like colitis.

METHODS

We examined KLF11 expression levels in diseased and normal colon mucosal tissues from 12 CD patients and 12 patients with colorectal cancer using immunofluorescence staining. KLF11 expression was also detected in the colon mucosal tissues of a mouse model of 2, 4, 6-trinitrobenesulfonic acid (TNBS)-induced colitis. A recombinant adenoviral vector was used to upregulate KLF11 expression in the mouse models and the changes in intestinal inflammation was observed. A Caco-2 cell model with stable KLF11 overexpression was constructed by lentiviral infection. The effect of KLF11 overexpression on expressions of JAK2/STAT3 signaling pathway proteins was investigated using immunoblotting in both the mouse and cell models. The mouse models were treated with coumermycin A1, a JAK2/STAT3 signaling pathway agonist, and the changes in intestinal inflammatory responses were observed.

RESULTS

The expression level of KLF11 was significantly lowered in both the clinical specimens of diseased colon mucosal tissues and the colon tissues of mice with TNBS-induced colitis (P < 0.05). Adenovirus-mediated upregulation of KLF11 significantly improved intestinal inflammation and reduced the expression levels of inflammatory factors in the intestinal mucosa of the colitis mouse models (P < 0.05). Overexpression of KLF11 significantly inhibited the expression levels of p-JAK2 and p-STAT3 in intestinal mucosal tissues of the mouse models and in Caco-2 cells (P < 0.05). Treatment with coumermycin A1 obviously inhibited the effect of KLF11 upregulation for improving colitis and significantly increased the expression levels of inflammatory factors in the intestinal mucosa of the mouse models (P < 0.05).

CONCLUSION

KLF11 is downregulated in the intestinal mucosa in CD, and upregulation of KLF11 can improve intestinal inflammation and reduce the production of inflammatory factors probably by inhibiting the JAK2/STAT3 signaling pathway.

Circuit-wide gene network analysis reveals sex-specific roles for phosphodiesterase 1b in cocaine addiction

Cocaine use disorder is a significant public health issue without an effective pharmacological treatment. Successful treatments are hindered in part by an incomplete understanding of the molecular mechanisms that underlie long-lasting maladaptive plasticity and addiction-like behaviors. Here, we leverage a large RNA-sequencing dataset to generate gene co-expression networks across 6 interconnected regions of the brain's reward circuitry from mice that underwent saline or cocaine self-administration. We identify phosphodiesterase 1b (Pde1b), a Ca2+/calmodulin-dependent enzyme that increases cAMP and cGMP hydrolysis, as a central hub gene within a nucleus accumbens (NAc) gene module that was bioinformatically associated with addiction-like behavior. Chronic cocaine exposure increases Pde1b expression in NAc D2 medium spiny neurons (MSNs) in male but not female mice. Viral-mediated Pde1b overexpression in NAc reduces cocaine self-administration in female rats, but increases seeking in both sexes. In female mice, overexpressing Pde1b in D1 MSNs attenuates the locomotor response to cocaine, with the opposite effect in D2 MSNs. Overexpressing Pde1b in D1/D2 MSNs had no effect on the locomotor response to cocaine in male mice. At the electrophysiological level, Pde1b overexpression reduces sEPSC frequency in D1 MSNs, while increasing excitability of D2 MSNs. Lastly, Pde1b overexpression significantly reduced the number of differentially expressed genes (DEGs) in NAc following chronic cocaine, with discordant effects on gene transcription between sexes. Together, we identify novel gene modules across the brain's reward circuitry associated with addiction-like behavior and explore the role of Pde1b in regulating the molecular, cellular, and behavioral responses to cocaine.Significance Statement Cocaine use disorder is a major public health challenge without an effective pharmacological treatment. Here, we leverage a combination of genome-wide RNA sequencing, gene co-expression network analysis, and bioinformatic analyses of cocaine self-administration behavior to identify a role for phosphodiesterase 1b (Pde1b) in regulating maladaptive, addiction-like behavior. Our studies reveal cell-type- and sex-specific roles for Pde1b in regulating the molecular, cellular, and behavioral responses to cocaine, yielding insight into the molecular mechanisms by which cocaine induces maladaptive plasticity in the brain's reward circuity to drive addiction-like behavior. These discoveries guide directions for future research investigating the molecular basis of cocaine action and provide a pathway for therapeutic development for cocaine use disorder.

The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

BACKGROUND

As global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease's etiology and response to drugs.

OBJECTIVE

We designed the Alzheimer's Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics.

METHODS

We designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base.

RESULTS

AlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones.

CONCLUSIONS

AlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

Identifying Progression-Specific Alzheimer's Subtypes Using Multimodal Transformer

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet its current treatments are limited to stopping disease progression. Moreover, the effectiveness of these treatments remains uncertain due to the heterogeneity of the disease. Therefore, it is essential to identify disease subtypes at a very early stage. Current data-driven approaches can be used to classify subtypes during later stages of AD or related disorders, but making predictions in the asymptomatic or prodromal stage is challenging. Furthermore, the classifications of most existing models lack explainability, and these models rely solely on a single modality for assessment, limiting the scope of their analysis. Thus, we propose a multimodal framework that utilizes early-stage indicators, including imaging, genetics, and clinical assessments, to classify AD patients into progression-specific subtypes at an early stage. In our framework, we introduce a tri-modal co-attention mechanism (Tri-COAT) to explicitly capture cross-modal feature associations. Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (slow progressing = 177, intermediate = 302, and fast = 15) were used to train and evaluate Tri-COAT using a 10-fold stratified cross-testing approach. Our proposed model outperforms baseline models and sheds light on essential associations across multimodal features supported by known biological mechanisms. The multimodal design behind Tri-COAT allows it to achieve the highest classification area under the receiver operating characteristic curve while simultaneously providing interpretability to the model predictions through the co-attention mechanism.

Suppression of AGRN enhances CD8+ T cell recruitment and inhibits breast cancer progression

Breast cancer (BC) stands as a prominent contributor to global cancer-related mortality, with an increasing incidence annually. This study aims to investigate AGRN gene expression in BC, as well as explore its influence on the tumor immune microenvironment. AGRN displayed a pronounced upregulation in BC tissues relative to paracancerous tissues. Single-cell RNA analysis highlighted AGRN-specific elevation within cancer cell clusters and also showed expression expressed in stromal as well as immune cell clusters. AGRN upregulation was positively correlated with clinicopathological stage and negatively correlated with BC prognosis. As revealed by the in vitro experiment, AGRN knockdown effectively hinders BC cells in terms of proliferation, invasion as well as migration. AGRN protein, which may interact with EXT1, LRP4, RAPSN, etc., was primarily distributed in the cell cytoplasm. Notably, immune factors might interact with AGRN in BC, evidenced by its discernible associations with immunofactors like IL10, CD274, and PVRL2. Mass spectrometry and immunohistochemistry revealed that the reduction of AGRN led to an increase in CD8+ T cells with triple-negative breast cancer (TNBC). Mechanistically, the connection between TRIM7 and PD-L1 is improved by AGRN, acting as a scaffold, thereby facilitating the accelerated degradation of PD-L1 by TRIM7. Downregulation of AGRN inhibits BC progression and increases CD8+ T cell recruitment. Targeting AGRN may contribute to BC treatment. The biomarker AGRN, serving as a therapeutic target for BC, emerges as a prospective avenue for enhancing both diagnosis and prognosis in BC cases.

TFE3-Splicing Factor Fusions Represent Functional Drivers and Druggable Targets in Translocation Renal Cell Carcinoma

TFE3 is a member of the basic helix-loop-helix leucine zipper MiT transcription factor family, and its chimeric proteins are associated with translocation renal cell carcinoma (tRCC). Despite the variety of gene fusions, most TFE3 fusion partner genes are related to spliceosome machinery. Dissecting the function of TFE3 fused to spliceosome machinery factors (TFE3-SF) could direct the development of effective therapies for this lethal disease, which is refractory to standard treatments for kidney cancer. Here, by using a combination of in silico structure prediction, transcriptome profiling, molecular characterization, and high-throughput high-content screening (HTHCS), we interrogated a number of oncogenic mechanisms of TFE3-SF fusions. TFE3-SF fusions drove the transformation of kidney cells and promoted distinct oncogenic phenotypes in a fusion partner-dependent manner, differentially altering the transcriptome and RNA splicing landscape and activating different oncogenic pathways. Inhibiting TFE3-SF dimerization reversed its oncogenic activity and represented a potential target for therapeutic intervention. Screening the FDA-approved drugs library LOPAC and a small-molecule library (Microsource) using HTHCS combined with FRET technology identified compounds that inhibit TFE3-SF dimerization. Hit compounds were validated in 2D and 3D patient-derived xenograft models expressing TFE3-SF. The antihistamine terfenadine decreased cell proliferation and reduced in vivo tumor growth of tRCC. Overall, these results unmask therapeutic strategies to target TFE3-SF dimerization for treating patients with tRCC.

SIGNIFICANCE

TFE3-splicing factor fusions possess both transcription and splicing factor functions that remodel the transcriptome and spliceosome and can be targeted with dimerization inhibitors to suppress the growth of translocation renal cell carcinoma.

Robust Offloading for Edge Computing-Assisted Sensing and Communication Systems: A Deep Reinforcement Learning Approach

In this paper, we consider an integrated sensing, communication, and computation (ISCC) system to alleviate the spectrum congestion and computation burden problem. Specifically, while serving communication users, a base station (BS) actively engages in sensing targets and collaborates seamlessly with the edge server to concurrently process the acquired sensing data for efficient target recognition. A significant challenge in edge computing systems arises from the inherent uncertainty in computations, mainly stemming from the unpredictable complexity of tasks. With this consideration, we address the computation uncertainty by formulating a robust communication and computing resource allocation problem in ISCC systems. The primary goal of the system is to minimize total energy consumption while adhering to perception and delay constraints. This is achieved through the optimization of transmit beamforming, offloading ratio, and computing resource allocation, effectively managing the trade-offs between local execution and edge computing. To overcome this challenge, we employ a Markov decision process (MDP) in conjunction with the proximal policy optimization (PPO) algorithm, establishing an adaptive learning strategy. The proposed algorithm stands out for its rapid training speed, ensuring compliance with latency requirements for perception and computation in applications. Simulation results highlight its robustness and effectiveness within ISCC systems compared to baseline approaches.

Expressions and Clinical Significance of Met and YAP in Gastric Cancer Tissue Microarray

Objective

This study is aimed at investigating the expression of Met and YAP in gastric cancer and their impact on clinical prognosis.

Methods

Tissue samples and clinical data were collected from 89 patients with gastric cancer. Immunohistochemistry was performed to quantify the expression of Met and YAP using tissue microarray. The correlation between the expressions of Met, YAP, and clinicopathological characteristics of patients was determined using a chi-square test. Survival analysis was conducted using the Kaplan-Meier method, while multivariate survival analysis was performed using the Cox proportional hazard model. Bioinformatics analysis was carried out by downloading chip data from TCGA.

Results

The expression levels of both Met and YAP were significantly higher in gastric cancer tissues compared to adjacent tissues (P < 0.001). Met expression showed a positive association with P53 and CD133, whereas YAP expression correlated positively with tumor grade and CD133 (P < 0.05). Pearson's analysis revealed a significant correlation between Met expression and VEGFR as well as CD133, while YAP expression correlated with Ki67 and VEGFR (P < 0.05). Patients with high levels of both Met and YAP exhibited decreased survival time (P < 0.01). Furthermore, Met expression, N stage, and VEGFR were identified as independent risk factors for gastric cancer prognosis (P < 0.05), whereas no such association was observed for YAP expression. Bioinformatics analysis demonstrated a significant correlation between the expressions of Met and YAP; both proteins were highly expressed in gastric cancer patients accompanied by markedly reduced survival time.

Conclusion

The expressions of Met and YAP are closely associated with the survival outcomes as well as clinicopathological features in patients with gastric cancer. Moreover, our findings highlight that Met serves as an independent prognostic factor for gastric cancer.

Effects of sacubitril/valsartan according to polypharmacy status in PARAGON-HF

AIMS

Patients with heart failure (HF) and preserved ejection fraction (HFpEF) have a particularly high prevalence of comorbidities, often necessitating treatment with many medications. The aim of this study was to evaluate the association between polypharmacy status and outcomes in PARAGON-HF.

METHODS AND RESULTS

In this post hoc analysis, baseline medication status was available in 4793 of 4796 patients included in the primary analysis of PARAGON-HF. The effects of sacubitril/valsartan, compared with valsartan, were assessed according to the number of medications at baseline: 683 non-polypharmacy (<5 medications); 2750 polypharmacy (5-9 medications), and 1360 hyper-polypharmacy (≥10 medications). The primary outcome was total HF hospitalizations and cardiovascular deaths. Patients with hyper-polypharmacy were older, had more severe limitations due to HF (worse New York Heart Association class and Kansas City Cardiomyopathy Questionnaire scores), and had greater comorbidity. The non-adjusted risk of the primary outcome was significantly higher in patients taking more medications, and similar trends were seen for HF hospitalization and cardiovascular and all-cause death. The effect of sacubitril/valsartan versus valsartan on the primary outcome from the lowest to highest polypharmacy category was (as a rate ratio): 1.19 (0.76-1.85), 0.94 (0.77-1.15), and 0.77 (0.61-0.96) (pinteraction = 0.16). Treatment-related adverse events were more common in patients in the higher polypharmacy categories but not more common with sacubitril/valsartan, versus valsartan, in any polypharmacy category.

CONCLUSIONS

Polypharmacy is very common in patients with HFpEF, and those with polypharmacy have worse clinical status and a higher rate of non-fatal and fatal outcomes. The benefit of sacubitril/valsartan was not diminished in patients taking a larger number of medications at baseline.

Oxidative Dissolution Process of Sphalerite in Fe2(SO4)3-O3 System: Implications for Heavy Metals Removal and Recovery

Metal sulfides in waste rocks and tailings are susceptible to serious soil and water contamination due to the generation of acid mine drainage (AMD) during stockpiling. The hydrometallurgical process is one of the most essential heavy metal remediation technologies through harmless disposal and resource utilization of the waste sulfides. However, atmospheric hydrometallurgy of sulfides still faces great challenges due to low leaching efficiency and high cost. In this work, we proposed a cooperative leaching system (Fe2(SO4)3-O3) and investigated the oxidative dissolution process of sphalerite (ZnS). Under the optimal conditions, the extracted zinc reached 97.8%. Reactive oxygen species (ROS) (·OH, 1O2 and ·O2-) were identified in the radical quenching experiments. The dissolution of sphalerite did not show passivation due to the ozone's capability to oxidize the sulfur in sphalerite to sulfate. In addition, stirring rate, O3 inlet concentration, and Fe2(SO4)3 concentration had a significant effect on the dissolution of sphalerite. Meanwhile, the apparent activation energy was 24.11 kJ/mol based on kinetic fitting, which indicated that the controlling step of the reaction was mainly a diffusion process. This work demonstrated the cooperative effect of sphalerite leaching in the O3-Fe2(SO4)3 system and provided a theoretical reference for efficient and atmospheric dissolution of sphalerite.

Progress on synthesis and structure-activity relationships of lamellarins over the past decade

Lamellarins are polyaromatic alkaloids isolated from marine organisms, including mollusks, tunicates, and sponges. Currently, over 60 structurally distinct natural lamellarins have been reported, and most of them exhibit promising biological activities, such as topoisomerase inhibition, mitochondrial function inhibition, multidrug resistance reversing, and anti-HIV activity. There has also been a significant progress on the synthetic study of lamellarins which has been regularly updated by numerous medicinal chemists as well. This review provides a detailed summary of the synthesis, pharmacology, and structural modification of lamellarins over the past decades.

Serotonin Transporter-dependent Histone Serotonylation in Placenta Contributes to the Neurodevelopmental Transcriptome

Brain development requires appropriate regulation of serotonin (5-HT) signaling from distinct tissue sources across embryogenesis. At the maternal-fetal interface, the placenta is thought to be an important contributor of offspring brain 5-HT and is critical to overall fetal health. Yet, how placental 5-HT is acquired, and the mechanisms through which 5-HT influences placental functions, are not well understood. Recently, our group identified a novel epigenetic role for 5-HT, in which 5-HT can be added to histone proteins to regulate transcription, a process called H3 serotonylation. Here, we show that H3 serotonylation undergoes dynamic regulation during placental development, corresponding to gene expression changes that are known to influence key metabolic processes. Using transgenic mice, we demonstrate that placental H3 serotonylation is dependent on 5-HT uptake by the serotonin transporter (SERT/SLC6A4). SERT deletion robustly reduces enrichment of H3 serotonylation across the placental genome, and disrupts neurodevelopmental gene networks in early embryonic brain tissues. Thus, these findings suggest a novel role for H3 serotonylation in coordinating placental transcription at the intersection of maternal physiology and offspring brain development.

External Evaluation of Population Pharmacokinetic Models for High-Dose Methotrexate in Adult Patients with Hematological Tumors

Currently, numerous population pharmacokinetic (popPK) models for methotrexate (MTX) have been published for estimating PK parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high-dose MTX (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The software package NONMEM was used to perform an external evaluation for each model, including prediction-based diagnosis, simulation-based diagnosis, and Bayesian forecasting. The simulation-based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, 7 candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. The published popPK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our data set. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.

Establishment of iPS cell line (SDQLCHi061-A) from a patient with carbamoylphosphate synthetase I deficiency due to CPS1 mutation

The induced pluripotent stem cells (iPSCs) line was generated using peripheral blood mononuclear cells (PBMCs) from a patient with compound heterozygous mutation of c.2374A > G/p.M792V and c.3949C > T/p.R1317W in the CPS1 gene by non-integrating vectors. The expression of pluripotency markers, potential for in vitro trilineage differentiation and exhibiting normal karyotype were demonstrated in the SDQLCHi061-A cell line. This cell line could provide a useful CPS1D model in vitro for further study.

Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting

This paper delves into the problem of correlated time-series forecasting in practical applications, an area of growing interest in a multitude of fields such as stock price prediction and traffic demand analysis. Current methodologies primarily represent data using conventional graph structures, yet these fail to capture intricate structures with non-pairwise relationships. To address this challenge, we adopt dynamic hypergraphs in this study to better illustrate complex interactions, and introduce a novel hypergraph neural network model named CHNN for correlated time series forecasting. In more detail, CHNN leverages both semantic and topological similarities via an interaction model and hypergraph diffusion process, thereby constructing comprehensive collaborative correlation scores that effectively guide spatial message propagation. In addition, it incorporates short-term temporal information to generate efficient spatio-temporal feature maps. Lastly, a long-term temporal module is proposed to generate future predictions utilizing both temporal attention and a gated recurrent network. Comprehensive experiments conducted on four real-world datasets, i.e., Tiingo, Stocktwits, NYC-Taxi, and Social Network demonstrate that the proposed CHNN markedly outperforms a range of benchmark methods.

Comparison of three VST orthokeratology lenses in axial length growth and average corneal reshaping in myopia children: A retrospective self-controlled study

Purpose

To determine the differences in myopia control efficiency and corneal reshaping between three different brands of orthokeratology (OK) lenses (Lucid, Euclid, and Alpha).

Method

We retrospectively reviewed subjects who started simultaneously using different brands of OK lenses. For each participant, every 6 months in the 19 months of following, the changes in axial length (AL), horizontal and vertical maximum distances of the treatment zone (HMDTZ and VMDTZ), width of the high convex zone (WHCZ), distance of decentration, and horizontal and vertical components of the decentration vector were measured. The average values of the above data, the average value of the decentration vector (ADV), and the average value of decentration calculated algebraically (ADA) were calculated.

Results

All the three pairs (Lucid (n = 46) vs. Euclid (n = 46): groups Lucid-versus-Euclid-Lucid (LE-L) and LE-E), Lucid (n = 50) vs. Alpha (n = 50): groups LA-L and LA-A), and Euclid (n = 17) vs. Alpha (n = 17): groups EA-E and EA-A) showed good comparability. Regarding the change in AL during 19 months, none of the pairs showed significant differences (LE-L:0.27 ± 0.24 mm, LE-E:0.31 ± 0.24 mm (p = 0.68); LA-L:0.36 ± 0.26 mm, LA-A:0.36 ± 0.27 mm (p = 0.85); EA-E:0.34 ± 0.27 mm, EA-A:0.41 ± 0.28 mm (p = 0.63)). Regarding treatment zone, Lucid showed the largest HMDTZ and VMDTZ (both p < 0.05). Regarding the WHCZ, none of the pairs showed significant differences. For the ADV and ADA, Lucid had more ADV and ADA than Euclid (ADV: LE-L:0.73 ± 0.44 mm, LE-E:0.55 ± 0.45 mm, p < 0.05; ADA: LE-L:0.80 ± 0.41 mm, LE-E:0.63 ± 0.44 mm, p < 0.05), and the remaining pairs showed no significant difference. For the overall cohort with 113 eyes, the change in AL was weakly correlated with both ADV and ADA (both p < 0.05). Regarding the ADV/ADA, all pairs showed no significant differences, indicating equal lens position stability.

Conclusion

After OK, there were no significant differences between the different pairs of the three brands in AL growth, WHCZ, or lens position stability, although Lucid had a larger treatment zone than Euclid and Alpha, and Lucid had more decentration than Euclid. A larger lens decentration were weakly related to less AL growth.

Phthalate exposure and blood pressure in U.S. children aged 8-17 years (NHANES 2013-2018)

BACKGROUND

Current evidence from epidemiologic studies suggested that phthalate metabolites might be associated with blood pressure (BP) changes. However, the special relationship between phthalate metabolites and BP changes in children has not been clearly elucidated in existing researches.

OBJECTIVES

We investigated the links between phthalate metabolites and various BP parameters, including systolic/diastolic BP, mean arterial pressure (MAP), and the presence of hypertension.

METHODS

The population sample consisted of 1036 children aged 8 to 17 years from the 2013-2018 NHANES in the United States. High performance liquid chromatography-electrospray ionization-tandem mass spectrometry was used to measure urinary concentrations of 19 phthalate metabolites. Systolic/diastolic BP were derived from the average of three valid measurements, and MAP was calculated as (systolic BP + 2 × diastolic BP)/3. Hypertension was defined as mean systolic BP and/or diastolic BP that was ≥ 95th percentile for gender, age, and height reference. Linear regression, logistic regression, and weighted quantile sum (WQS) regression models were employed to assess the associations between phthalate exposure and systolic/diastolic BP, MAP, and hypertension.

RESULTS

Ten of 19 phthalate metabolites including MCNP, MCOP, MECPP, MBP, MCPP, MEP, MEHHP, MiBP, MEOHP, and MBzP had detection frequencies > 85% with samples more than 1000. MCNP, MCOP, MECPP, MBP, MCPP, MEHHP, MiBP, MEOHP, and MBzP were generally negatively associated with systolic/diastolic BP and MAP, but not protective factors for hypertension. These associations were not modified by age (8-12 and 13-17 years) or sex (boys and girls). The above-mentioned associations were further confirmed by the application of the WQS analysis, and MCOP was identified as the chemical with the highest weight.

CONCLUSION

Phthalate metabolites were associated with modest reductions in systolic/diastolic BP, and MAP in children, while appeared not protective factors for hypertension. Given the inconsistent results among existing studies, our findings should be confirmed by other cohort studies.

Low-loss tantalum pentoxide photonics with a CMOS-compatible process

We report a Ta2O5 photonic platform with a propagation loss of 0.49 dB/cm at 1550 nm, of 0.86 dB/cm at 780 nm, and of 3.76 dB/cm at 2000 nm. The thermal bistability measurement is conducted in the entire C-band for the first time to reveal the absorption loss of Ta2O5 waveguides, offering guidelines for further reduction of the waveguide loss. We also characterize the Ta2O5 waveguide temperature response, which shows favorable thermal stability. The fabrication process temperature is below 350°C, which is friendly to integration with active optoelectronic components.

The genetic architecture of multimodal human brain age

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .

Chromatin accessibility and H3K9me3 landscapes reveal long-term epigenetic effects of fetal-neonatal iron deficiency in rat hippocampus

BACKGROUND

Iron deficiency (ID) during the fetal-neonatal period results in long-term neurodevelopmental impairments associated with pervasive hippocampal gene dysregulation. Prenatal choline supplementation partially normalizes these effects, suggesting an interaction between iron and choline in hippocampal transcriptome regulation. To understand the regulatory mechanisms, we investigated epigenetic marks of genes with altered chromatin accessibility (ATAC-seq) or poised to be repressed (H3K9me3 ChIP-seq) in iron-repleted adult rats having experienced fetal-neonatal ID exposure with or without prenatal choline supplementation.

RESULTS

Fetal-neonatal ID was induced by limiting maternal iron intake from gestational day (G) 2 through postnatal day (P) 7. Half of the pregnant dams were given supplemental choline (5.0 g/kg) from G11-18. This resulted in 4 groups at P65 (Iron-sufficient [IS], Formerly Iron-deficient [FID], IS with choline [ISch], and FID with choline [FIDch]). Hippocampi were collected from P65 iron-repleted male offspring and analyzed for chromatin accessibility and H3K9me3 enrichment. 22% and 24% of differentially transcribed genes in FID- and FIDch-groups, respectively, exhibited significant differences in chromatin accessibility, whereas 1.7% and 13% exhibited significant differences in H3K9me3 enrichment. These changes mapped onto gene networks regulating synaptic plasticity, neuroinflammation, and reward circuits. Motif analysis of differentially modified genomic sites revealed significantly stronger choline effects than early-life ID and identified multiple epigenetically modified transcription factor binding sites.

CONCLUSIONS

This study reveals genome-wide, stable epigenetic changes and epigenetically modifiable gene networks associated with specific chromatin marks in the hippocampus, and lays a foundation to further elucidate iron-dependent epigenetic mechanisms that underlie the long-term effects of fetal-neonatal ID, choline, and their interactions.

FABEL: Forecasting Animal Behavioral Events with Deep Learning-Based Computer Vision

Behavioral neuroscience aims to provide a connection between neural phenomena and emergent organism-level behaviors. This requires perturbing the nervous system and observing behavioral outcomes, and comparing observed post-perturbation behavior with predicted counterfactual behavior and therefore accurate behavioral forecasts. In this study we present FABEL, a deep learning method for forecasting future animal behaviors and locomotion trajectories from historical locomotion alone. We train an offline pose estimation network to predict animal body-part locations in behavioral video; then sequences of pose vectors are input to deep learning time-series forecasting models. Specifically, we train an LSTM network that predicts a future food interaction event in a specified time window, and a Temporal Fusion Transformer that predicts future trajectories of animal body-parts, which are then converted into probabilistic label forecasts. Importantly, accurate prediction of food interaction provides a basis for neurobehavioral intervention in the context of compulsive eating. We show promising results on forecasting tasks between 100 milliseconds and 5 seconds timescales. Because the model takes only behavioral video as input, it can be adapted to any behavioral task and does not require specific physiological readouts. Simultaneously, these deep learning models may serve as extensible modules that can accommodate diverse signals, such as in-vivo fluorescence imaging and electrophysiology, which may improve behavior forecasts and elucidate invervention targets for desired behavioral change.

Physiological regulation of microalgae under cadmium stress and response mechanisms of time-series analysis using metabolomics

The investigation of heavy metal wastewater treatment utilizing microalgae adsorption has been extensively demonstrated. However, the response mechanism based on metabolomics to analyze the time-series changes of microalgae under Cd stress has not been described in detail. In this study, SEM/TEM demonstrated that Cd accumulated on the cell surface of microalgae and was bioconcentrated in the cytoplasm, vesicles, and chloroplasts. Carbonyl/quinone/ketone/carboxyl groups (OCO), membrane polysaccharides (OH), and phospholipids (PO) were involved in the interaction of Cd ions, and the chlorophyll content underwent a process of decreasing in the early stage (1.62 mg/g at 48 h) and recovering to the normal level in the late stage, and the contents of MDA, GSH, and SOD were all increased (29.7 nmol/g, 0.23 mg/g, and 30.01 u/106 cells) and then gradually returned to the steady state. The results of EPS content and fluorescent labeling showed that Cd induced the overexpression and synthesis of extracellular polysaccharides and proteins, which is one of the defense mechanisms participating in the reduction of cellular damage by complexed Cd. Metabolomics results indicated that the malate synthesis pathway was activated after Cd-20 h, and the microalgal cells began to shift the metabolic pathway to storage lipid or polysaccharide biosynthesis. In the Calvin cycle, the expression of D-Sedoheptulose 7-phosphate in Cd-20 h_vs_ck and Cd-72 h_vs_Cd-20 h firstly declined and then increased, and the photosynthesis system was suppressed at the beginning, and then gradually returned to normal to maintain the successful development of the dark reaction. The results of time series analysis revealed that the response of microalgae to Cd was categorized into fast response and slow response to regulate cell adsorption and growth metabolism.

Distance-weighted Sinkhorn loss for Alzheimer's disease classification

Traditional loss functions such as cross-entropy loss often quantify the penalty for each mis-classified training sample without adequately considering its distance from the ground truth class distribution in the feature space. Intuitively, the larger this distance is, the higher the penalty should be. With this observation, we propose a penalty called distance-weighted Sinkhorn (DWS) loss. For each mis-classified training sample (with predicted label A and true label B), its contribution to the DWS loss positively correlates to the distance the training sample needs to travel to reach the ground truth distribution of all the A samples. We apply the DWS framework with a neural network to classify different stages of Alzheimer's disease. Our empirical results demonstrate that the DWS framework outperforms the traditional neural network loss functions and is comparable or better to traditional machine learning methods, highlighting its potential in biomedical informatics and data science.

RGS4 Actions in Mouse Prefrontal Cortex Modulate Behavioral and Transcriptomic Responses to Chronic Stress and Ketamine

The signal transduction protein, regulator of G protein signaling 4 (RGS4), plays a prominent role in physiologic and pharmacological responses by controlling multiple intracellular pathways. Our earlier work identified the dynamic but distinct roles of RGS4 in the efficacy of monoamine-targeting versus fast-acting antidepressants. Using a modified chronic variable stress (CVS) paradigm in mice, we demonstrate that stress-induced behavioral abnormalities are associated with the downregulation of RGS4 in the medial prefrontal cortex (mPFC). Knockout of RGS4 (RGS4KO) increases susceptibility to CVS, as mutant mice develop behavioral abnormalities as early as 2 weeks after CVS resting-state functional magnetic resonance imaging I (rs-fMRI) experiments indicate that stress susceptibility in RGS4KO mice is associated with changes in connectivity between the mediodorsal thalamus (MD-THL) and the mPFC. Notably, RGS4KO also paradoxically enhances the antidepressant efficacy of ketamine in the CVS paradigm. RNA-sequencing analysis of naive and CVS samples obtained from mPFC reveals that RGS4KO triggers unique gene expression signatures and affects several intracellular pathways associated with human major depressive disorder. Our analysis suggests that ketamine treatment in the RGS4KO group triggers changes in pathways implicated in synaptic activity and responses to stress, including pathways associated with axonal guidance and myelination. Overall, we show that reducing RGS4 activity triggers unique gene expression adaptations that contribute to chronic stress disorders and that RGS4 is a negative modulator of ketamine actions. SIGNIFICANCE STATEMENT: Chronic stress promotes robust maladaptation in the brain, but the exact intracellular pathways contributing to stress vulnerability and mood disorders have not been thoroughly investigated. In this study, the authors used murine models of chronic stress and multiple methodologies to demonstrate the critical role of the signal transduction modulator regulator of G protein signaling 4 in the medial prefrontal cortex in vulnerability to chronic stress and the efficacy of the fast-acting antidepressant ketamine.

Transcriptional characterization of cocaine withdrawal versus extinction within nucleus accumbens

Substance use disorder is characterized by a maladaptive imbalance wherein drug seeking persists despite negative consequences or drug unavailability. This imbalance correlates with neurobiological alterations some of which are amplified during forced abstinence, thereby compromising the capacity of extinction-based approaches to prevent relapse. Cocaine use disorder (CUD) exemplifies this phenomenon in which neurobiological modifications hijack brain reward regions such as the nucleus accumbens (NAc) to manifest craving and withdrawal-like symptoms. While increasing evidence links transcriptional changes in the NAc to specific phases of addiction, genome-wide changes in gene expression during withdrawal vs. extinction (WD/Ext) have not been examined in a context- and NAc-subregion-specific manner. Here, we used cocaine self-administration (SA) in rats combined with RNA-sequencing (RNA-seq) of NAc subregions (core and shell) to transcriptionally profile the impact of experiencing withdrawal in the home cage or in the previous drug context or experiencing extinction training. As expected, home-cage withdrawal maintained drug seeking in the previous drug context, whereas extinction training reduced it. By contrast, withdrawal involving repetitive exposure to the previous drug context increased drug-seeking behavior. Bioinformatic analyses of RNA-seq data revealed gene expression patterns, networks, motifs, and biological functions specific to these behavioral conditions and NAc subregions. Comparing transcriptomic analysis of the NAc of patients with CUD highlighted conserved gene signatures, especially with rats that were repetitively exposed to the previous drug context. Collectively, these behavioral and transcriptional correlates of several withdrawal-extinction settings reveal fundamental and translational information about potential molecular mechanisms to attenuate drug-associated memories.

Echocardiographic abnormalities and joint hypermobility in Chinese patients with Osteogenesis imperfecta

BACKGROUND

Very little is known about the characteristics of echocardiographic abnormalities and joint hypermobility in Chinese patients with osteogenesis imperfecta (OI). The aim of our study was to investigate the characteristics, prevalence and correlation of echocardiographic abnormalities and joint hypermobility in Chinese patients with OI.

METHODS

A cross-sectional comparative study was conducted in pediatric and adult OI patients who were matched in age and sex with healthy controls. Transthoracic echocardiography was performed in all patients and controls, and parameters were indexed for body surface area (BSA). The Beighton score was used to evaluate the degree of joint hypermobility.

RESULTS

A total of 48 patients with OI (25 juveniles and 23 adults) and 129 age- and sex-matched healthy controls (79 juveniles and 50 adults) were studied. Four genes (COL1A1, COL1A2, IFITM5, and WNT1) and 39 different mutation loci were identified in our study. Mild valvular regurgitation was the most common cardiac abnormality: mild mitral and tricuspid regurgitation was found in 12% and 36% of pediatric OI patients, respectively; among 23 OI adults, 13% and 17% of patients had mild mitral and tricuspid regurgitation, respectively, and 4% had mild aortic regurgitation. In multiple regression analysis, OI was the key predictor of left atrium diameter (LAD) (β=-3.670, P < 0.001) and fractional shortening (FS) (β = 3.005, P = 0.037) in juveniles, whereas for adults, OI was a significant predictor of LAD (β=-3.621, P < 0.001) and left ventricular mass (LVM) (β = 58.928, P < 0.001). The percentages of generalized joint hypermobility in OI juveniles and adults were 56% and 20%, respectively. Additionally, only in the OI juvenile group did the results of the Mann‒Whitney U test show that the degree of joint hypermobility was significantly different between the echocardiographic normal and abnormal groups (P = 0.004).

CONCLUSIONS

Mild valvular regurgitation was the most common cardiac abnormality in both OI juveniles and adults. Compared with OI adults, OI juveniles had more prevalent and wider joint hypermobility. Echocardiographic abnormalities may imply that the impairment of type I collagen is more serious in OI. Baseline echocardiography should be performed in OI patients as early as possible.

The chromatin remodeling factor Arid1a cooperates with Jun/Fos to promote osteoclastogenesis by epigenetically upregulating Siglec15 expression

Osteoporosis is characterized by an imbalance between osteoclast-mediated bone resorption and osteoblast-related bone formation, particularly increased osteoclastogenesis. However, the mechanisms by which epigenetic factors regulate osteoclast precursor differentiation during osteoclastogenesis remain poorly understood. Here, we show that the specific knockout of the chromatin remodeling factor Arid1a in bone marrow-derived macrophages (BMDMs) results in increased bone mass. The loss of Arid1a in BMDM inhibits cell-cell fusion and maturation of osteoclast precursors, thereby suppressing osteoclast differentiation. Mechanistically, Arid1a increases the chromatin access in the gene promoter region of sialic acid-binding Ig-like lectin 15 (Siglec15) by transcription factor Jun/Fos, which results in the upregulation of Siglec15 and promotion of osteoclast differentiation. However, the loss of Arid1a reprograms the chromatin structure to restrict Siglec15 expression in osteoclast precursors, thereby inhibiting BMDM differentiation into mature osteoclasts. Deleting Arid1a after ovariectomy (a model for postmenopausal bone loss) alleviated bone loss and maintained bone mass. In summary, epigenetic reprogramming mediated by Arid1a loss suppresses osteoclast differentiation and may serve as a promising therapeutic strategy for treating bone loss diseases.

A novel intracoronary hypothermia device reduces myocardial reperfusion injury in pigs

BACKGROUND

Hypothermia therapy has been suggested to attenuate myocardial necrosis; however, the clinical implementation as a valid therapeutic strategy has failed, and new approaches are needed to translate into clinical applications. This study aimed to assess the feasibility, safety, and efficacy of a novel selective intracoronary hypothermia (SICH) device in mitigating myocardial reperfusion injury.

METHODS

This study comprised two phases. The first phase of the SICH was performed in a normal porcine model for 30 minutes ( n = 5) to evaluate its feasibility. The second phase was conducted in a porcine myocardial infarction (MI) model of myocardial ischemia/reperfusion was performed by balloon occlusion of the left anterior descending coronary artery for 60 minutes and maintained for 42 days. Pigs in the hypothermia group ( n = 8) received hypothermia intervention onset reperfusion for 30 minutes and controls ( n = 8) received no intervention. All animals were followed for 42 days. Cardiac magnetic resonance analysis (5 and 42 days post-MI) and a series of biomarkers/histological studies were performed.

RESULTS

The average time to lower temperatures to a steady state was 4.8 ± 0.8 s. SICH had no impact on blood pressure or heart rate and was safely performed without complications by using a 3.9 F catheter. Interleukin-6 (IL-6), tumor necrosis factor-α, C-reactive protein (CRP), and brain natriuretic peptide (BNP) were lower at 60 min post perfusion in pigs that underwent SICH as compared with the control group. On day 5 post MI/R, edema, intramyocardial hemorrhage, and microvascular obstruction were reduced in the hypothermia group. On day 42 post MI/R, the infarct size, IL-6, CRP, BNP, and matrix metalloproteinase-9 were reduced, and the ejection fraction was improved in pigs that underwent SICH.

CONCLUSIONS

The SICH device safely and effectively reduced the infarct size and improved heart function in a pig model of MI/R. These beneficial effects indicate the clinical potential of SICH for treatment of myocardial reperfusion injury.

IRF3 activates RB to authorize cGAS-STING-induced senescence and mitigate liver fibrosis

Cytosolic double-stranded DNA surveillance by cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) signaling triggers cellular senescence, autophagy, biased mRNA translation, and interferon-mediated immune responses. However, detailed mechanisms and physiological relevance of STING-induced senescence are not fully understood. Here, we unexpectedly found that interferon regulatory factor 3 (IRF3), activated during innate DNA sensing, forms substantial endogenous complexes in the nucleus with retinoblastoma (RB), a key cell cycle regulator. The IRF3-RB interaction attenuates cyclin-dependent kinase 4/6 (CDK4/6)-mediated RB hyperphosphorylation that mobilizes RB to deactivate E2 family (E2F) transcription factors, thereby driving cells into senescence. STING-IRF3-RB signaling plays a notable role in hepatic stellate cells (HSCs) within various murine models, pushing activated HSCs toward senescence. Accordingly, IRF3 global knockout or conditional deletion in HSCs aggravated liver fibrosis, a process mitigated by the CDK4/6 inhibitor. These findings underscore a straightforward yet vital mechanism of cGAS-STING signaling in inducing cellular senescence and unveil its unexpected biology in limiting liver fibrosis.

Resistant starch intake facilitates weight loss in humans by reshaping the gut microbiota

Emerging evidence suggests that modulation of gut microbiota by dietary fibre may offer solutions for metabolic disorders. In a randomized placebo-controlled crossover design trial (ChiCTR-TTRCC-13003333) in 37 participants with overweight or obesity, we test whether resistant starch (RS) as a dietary supplement influences obesity-related outcomes. Here, we show that RS supplementation for 8 weeks can help to achieve weight loss (mean -2.8 kg) and improve insulin resistance in individuals with excess body weight. The benefits of RS are associated with changes in gut microbiota composition. Supplementation with Bifidobacterium adolescentis, a species that is markedly associated with the alleviation of obesity in the study participants, protects male mice from diet-induced obesity. Mechanistically, the RS-induced changes in the gut microbiota alter the bile acid profile, reduce inflammation by restoring the intestinal barrier and inhibit lipid absorption. We demonstrate that RS can facilitate weight loss at least partially through B. adolescentis and that the gut microbiota is essential for the action of RS.

Benefits of 12-month peer support for diabetes self management sustained at 18 months

AIMS

To evaluate sustainability of peer support (PS) benefits in diabetes management.

METHODS

Supporting a Peer Leader program through Community Health Centers (CHCs) included trainings and consultations from baseline to 12 months. Evaluation at baseline, 12-month, and 18-month follow-up included primary outcome, HbA1c, and other outcomes of SBP, DBP, LDLc, PHQ-8, diabetes distress, and EQ-5D.

RESULTS

1284 participants with type 2 diabetes mellitus were recruited from 9 CHCs. Mean (SD) for age = 68.00 (7.55) years, 43.07 % male, mean (SD) for diabetes duration = 11.79 (7.34) years. Across 18-months, linear mixed model analyses controlling for confounders found the least square mean (SE) of HbA1c improved significantly from 7.62 % (0.06 %) to 7.53 % (0.06 %) for all, and from 9.25 % (0.09 %) to 8.52 % (0.11 %) among those ≥8 % at baseline. Parallel improvements were found among all for SBP, DBP, PHQ-8, diabetes distress, and, among those elevated at baseline for all outcomes. EQ-5D showed significant but modest increase from baseline to 18 months. No significant reversals between 12 and 18 months were found except for LDLc. Supporting robustness of findings, patterns were similar across age, diabetes duration, and gender.

CONCLUSIONS

Relative to the fundamentally progressive nature of diabetes, it is striking that improvements associated with PS were generally sustained after program support ended.

Transcription Factor STAT3-Activated LDHB Promotes Tumor Properties of Endometrial Cancer Cells by Inducing MDH2 Expression

The pathogenesis of endometrial cancer (EC) involves the regulation of lactate dehydrogenases. However, the role and mechanism of lactate dehydrogenase-B (LDHB) in EC progression have not been studied. The mRNA levels of LDHB and malate dehydrogenase 2 (MDH2) were detected by quantitative real-time polymerase chain reaction. Protein expression was checked by western blotting and immunohistochemistry assays. Cell proliferation, apoptosis, and invasion were analyzed by 5-Ethynyl-2'-deoxyuridine, transwell, and flow cytometry assay, respectively. Glycolysis was investigated using Glucose Assay Kit, CheKine™ Micro Lactate Assay Kit, and ADP/ATP ratio assay kit. An in vivo tumor formation assay was conducted to disclose the effect of LDHB on tumor growth in vivo. The associations among signal transducer and activator of transcription 3 (STAT3), LDHB, and MDH2 were predicted through JASPAR or GeneMANIA online database and identified by chromatin immunoprecipitation assay, dual-luciferase reporter assay, and co-immunoprecipitation assay. LDHB expression was increased in EC tissues and cells in comparison with normal endometrial tissues and human endometrial stromal cells. LDHB had the potential as a biomarker to predict the prognosis of EC patients. In addition, LDHB knockdown inhibited the proliferation, invasion, and glycolysis and promoted apoptosis of RL95-2 and Ishikawa cells. LDHB knockdown inhibited tumor property of Ishikawa cells in vivo. STAT3 bound to the promoter region of LDHB, and STAT3 silencing-induced effects were relieved after LDHB upregulation. LDHB interacted with and regulated MDH2 expression. Moreover, MDH2 overexpression rescued LDHB knockdown-induced effects on EC cell phenotypes. STAT3-activated LDHB promoted endometrial cancer cell malignancy by inducing MDH2 production.

TEA domain transcription factor 1(TEAD1) induces cardiac fibroblasts cells remodeling through BRD4/Wnt4 pathway

Cardiac fibroblasts (CFs) are the primary cells tasked with depositing and remodeling collagen and significantly associated with heart failure (HF). TEAD1 has been shown to be essential for heart development and homeostasis. However, fibroblast endogenous TEAD1 in cardiac remodeling remains incompletely understood. Transcriptomic analyses revealed consistently upregulated cardiac TEAD1 expression in mice 4 weeks after transverse aortic constriction (TAC) and Ang-II infusion. Further investigation revealed that CFs were the primary cell type expressing elevated TEAD1 levels in response to pressure overload. Conditional TEAD1 knockout was achieved by crossing TEAD1-floxed mice with CFs- and myofibroblasts-specific Cre mice. Echocardiographic and histological analyses demonstrated that CFs- and myofibroblasts-specific TEAD1 deficiency and treatment with TEAD1 inhibitor, VT103, ameliorated TAC-induced cardiac remodeling. Mechanistically, RNA-seq and ChIP-seq analysis identified Wnt4 as a novel TEAD1 target. TEAD1 has been shown to promote the fibroblast-to-myofibroblast transition through the Wnt signalling pathway, and genetic Wnt4 knockdown inhibited the pro-transformation phenotype in CFs with TEAD1 overexpression. Furthermore, co-immunoprecipitation combined with mass spectrometry, chromatin immunoprecipitation, and luciferase assays demonstrated interaction between TEAD1 and BET protein BRD4, leading to the binding and activation of the Wnt4 promoter. In conclusion, TEAD1 is an essential regulator of the pro-fibrotic CFs phenotype associated with pathological cardiac remodeling via the BRD4/Wnt4 signalling pathway.

Targeted repression of topA by CRISPRi reveals a critical function for balanced DNA topoisomerase I activity in the Chlamydia trachomatis developmental cycle

Chlamydia trachomatis is an obligate intracellular bacterium that is responsible for the most prevalent bacterial sexually transmitted infection. Changes in DNA topology in this pathogen have been linked to its pathogenicity-associated developmental cycle. Here, evidence is provided that the balanced activity of DNA topoisomerases contributes to controlling Chlamydia developmental processes. Utilizing catalytically inactivated Cas12 (dCas12)-based clustered regularly interspaced short palindromic repeats interference (CRISPRi) technology, we demonstrate targeted knockdown of chromosomal topA transcription in C. trachomatis without detected toxicity of dCas12. Repression of topA impaired the developmental cycle of C. trachomatis mostly through disruption of its differentiation from a replicative form to an infectious form. Consistent with this, expression of late developmental genes of C. trachomatis was downregulated, while early genes maintained their expression. Importantly, the developmental defect associated with topA knockdown was rescued by overexpressing topA at an appropriate degree and time, directly linking the growth patterns to the levels of topA expression. Interestingly, topA knockdown had effects on DNA gyrase expression, indicating a potential compensatory mechanism for survival to offset TopA deficiency. C. trachomatis with topA knocked down displayed hypersensitivity to moxifloxacin that targets DNA gyrase in comparison with the wild type. These data underscore the requirement of integrated topoisomerase actions to support the essential developmental and transcriptional processes of C. trachomatis.IMPORTANCEWe used genetic and chemical tools to demonstrate the relationship of topoisomerase activities and their obligatory role for the chlamydial developmental cycle. Successfully targeting the essential gene topA with a CRISPRi approach, using dCas12, in C. trachomatis indicates that this method will facilitate the characterization of the essential genome. These findings have an important impact on our understanding of the mechanisms by which well-balanced topoisomerase functions in adaptation of C. trachomatis to unfavorable growth conditions imposed by antibiotics.

Cu2 WS4 -PEG Nanozyme as Multifunctional Sensitizers for Enhancing Immuno-Radiotherapy by Inducing Ferroptosis

Unavoidable damage to normal tissues and tumor microenvironment (TME) resistance make it challenging to eradicate breast carcinoma through radiotherapy. Therefore, it is urgent to develop radiotherapy sensitizers that can effectively reduce radiation doses and reverse the suppressive TME. Here, a novel biomimetic PEGylated Cu2 WS4 nanozyme (CWP) with multiple enzymatic activities is synthesized by the sacrificing template method to have physical radiosensitization and biocatalyzer-responsive effects on the TME. Experiment results show that CWP can improve the damage efficiency of radiotherapy on breast cancer cell 4T1 through its large X-ray attenuation coefficient of tungsten and nucleus-penetrating capacity. CWP also exhibit strong Fenton-like reactions that produced abundant ROS and GSH oxidase-like activity decreasing GSH. This destruction of redox balance further promotes the effectiveness of radiotherapy. Transcriptome sequencing reveals that CWP induced ferroptosis by regulating the KEAP1/NRF2/HMOX1/GPX4 molecules. Therefore, owing to its multiple enzymatic activities, high-atomic W elements, nucleus-penetrating, and ferroptosis-inducing capacities, CWP effectively improves the efficiency of radiotherapy for breast carcinoma in vitro and in vivo. Furthermore, CWP-mediated radiosensitization can trigger immunogenic cell death (ICD) to improve the anti-PD-L1 treatments to inhibit the growth of primary and distant tumors effectively. These results indicate that CWP is a multifunctional nano-sensitizers for radiotherapy and immunotherapy.