Transcriptomic profiling of Dip2a in the neural differentiation of mouse embryonic stem cells

Introduction

The disconnected-interacting protein 2 homolog A (DIP2A), a member of disconnected-interacting 2 protein family, has been shown to be involved in human nervous system-related mental illness. This protein is highly expressed in the nervous system of mouse. Mutation of mouse DIP2A causes defects in spine morphology and synaptic transmission, autism-like behaviors, and defective social novelty [5], [27], indicating that DIP2A is critical to the maintenance of neural development. However, the role of DIP2A in neural differentiation has yet to be investigated.

Objective

To determine the role of DIP2A in neural differentiation, a neural differentiation model was established using mouse embryonic stem cells (mESCs) and studied by using gene-knockout technology and RNA-sequencing-based transcriptome analysis.

Results

We found that DIP2A is not required for mESCs pluripotency maintenance, but loss of DIP2A causes the neural differentiation abnormalities in both N2B27 and KSR medium. Functional knockout of Dip2a gene also decreased proliferation of mESCs by perturbation of the cell cycle and profoundly inhibited the expression of a large number of neural development-associated genes which mainly enriched in spinal cord development and postsynapse assembly.

Conclusions

The results of this report demonstrate that DIP2A plays an essential role in regulating differentiation of mESCs towards the neural fate.

Quercetin improves diabetic kidney disease by inhibiting ferroptosis and regulating the Nrf2 in streptozotocin-induced diabetic rats

Diabetic kidney disease (DKD) is a leading factor in end-stage renal disease. The complexity of its pathogenesis, combined with the limited treatment efficacy, necessitates deeper insights into potential causes. Studies suggest that ferroptosis-driven renal tubular damage contributes to DKD's progression, making its counteraction a potential therapeutic strategy. Quercetin, a flavonoid found in numerous fruits and vegetables, has demonstrated DKD mitigation in mouse models, though its protective mechanism remains ambiguous. In this study, we delved into quercetin's potential anti-ferroptotic properties, employing a DKD rat model and high glucose (HG)-treated renal tubular epithelial cell models. Our findings revealed that HG prompted unusual ferroptosis activation in renal tubular epithelial cells. However, quercetin counteracted this by inhibiting ferroptosis and activating NFE2-related factor 2 (Nrf2) expression in both DKD rats and HG-treated HK-2 cells, indicating its renal protective role. Further experiments, both in vivo and in vitro, validated that quercetin stimulates Nrf2. Thus, our research underscores quercetin's potential in DKD treatment by modulating the ferroptosis process via activating Nrf2 in a distinct DKD rat model, offering a fresh perspective on quercetin's protective mechanisms.

Galectin-1 overexpression induces normal fibroblasts translate into cancer-associated fibroblasts and attenuates the sensitivity of anlotinib in lung cancer

We aimed to investigate galectin-1 overexpression induces normal fibroblasts (NFs) translates into cancer-associated fibroblasts (CAFs). Galectin-1 overexpression was conducted in Human embryonic lung fibroblasts (HFL1) cell. The motilities of H1299 and A549 cells were measured. Human umbilical vein endothelial cell (HUVEC) proliferation and tube formation ability were assessed. Tumor volume and tumor weight was recorded. Cells motilities were increased, while apoptosis rates were decreased after CMs co-cultured. B-cell lymphoma-2 (Bcl-2) expression level was increased, while Bcl2-associatedX (Bax) and cleaved-caspase3 decreased. CMs treatment enhanced HUVEC proliferation and tube formation. Tumor volume and weight in CMs treated mice were increased, and the sensitivity of anlotinib in co-cultured cells was decreased. Our results revealed that galectin-1 overexpression induced NFs translated into CAFs.

Escherichia coli and HPV16 coinfection may contribute to the development of cervical cancer

Persistent human papillomavirus HPV infection is a necessary but insufficient condition for cervical cancer. Microorganisms are crucial environmental factors in cancers susceptibility and progression, recently attracting considerable attention. This study aimed to determine the infection status and relationship between high-risk HPV (HR-HPV) and lower genital tract infectious pathogens in cervical cancer and its precursors. From a retrospective and a prospective cohort analysis, Escherichia coli (E. coli) dominated the pathogens isolated from cervical discharges, and an isolation rate uptrend has been shown recently. HPV16 and E. coli's coinfection rate gradually increased with the severity of cervical intraepithelial neoplasia. The adhesion and invasion abilities of the isolated E. coli to HPV16-positive SiHa cells were evaluated in vitro. The TCGA database and cervical tissues samples analysis showed that IL-10 was upregulated in cervical cancer. IL-10 expression levels increased in tissue samples with the severity of cervical cancer and its precursors with HPV16 and E. coli coinfection. Although no significant changes in IL-10 production were observed in the co-culture supernatant, we hypothesized that Treg immune cells in the tumour microenvironment might be responsible for the local IL-10 upregulation, according to our data showing Foxp3 upregulation and an upward trend with the cervical intraepithelial neoplasia grading to cancer and tumours with E. coli and HPV16 coinfection. Our data provide insights into the possible role of E. coli in cervical cancer progression and suggest that the application of HPV and E. coli screening programs may be an effective strategy to relieve the burden of cervical cancer and its precursor lesions.

Effects of selenium-enriched yeast dietary supplementation on egg quality, gut morphology and caecal microflora of laying hens

Selenium (Se) is an essential micronutrient for humans and animals and is a powerful antioxidant that can promote reproductive and immune functions. The purpose of this study was to evaluate the effects of supplemental dietary selenium-enriched yeast (SeY) on egg quality, gut morphology and microflora in laying hens. In total, 100 HY-Line Brown laying hens (45-week old) were randomly allocated to two groups with 10 replicates and fed either a basal diet (without Se supplementation) or a basal diet containing 0.2 mg/kg Se in the form of SeY for 8 weeks. The Se supplementation did not have a significant effect on egg quality and intestinal morphology of laying hens. Based on the 16S rRNA sequencing, SeY dietary supplementation effectively modulated the cecal microbiota structure. An alpha diversity analysis demonstrated that birds fed 100 mg/kg SeY had a higher cecal bacterial diversity. SeY dietary addition elevated Erysipelotrichia (class), Lachnospiraceae (family), Erysipelotrichaceae (family) and Ruminococcus_torques_group (genus; p < .05). Analysis of microbial community-level phenotypes revealed that SeY supplementation decreased the microorganism abundance of facultatively anaerobic and potentially pathogenic phenotypes. Overall, SeY supplementation cannot significantly improve intestinal morphology; however, it modulated the composition of cecal microbiota toward a healthier gut.

Deep insight into regulation mechanism of band distribution in phase junction CdS for enhanced photocatalytic H2 production

An in-depth understanding of structure-activity relationship between the phase constitution and solar-to-hydrogen (STH) conversion efficiency is conducive to guiding the optimization route of targeted photocatalyst candidates, further establishing advanced photocatalytic systems. Herein, based on the concept of phase engineering, we encompassed the crystalline phase of CdS and achieved precise regulation of phase proportion as well as phase boundary width in the phase junction for the first time. The above cooperative effect not only modifies energy band distribution for sufficient redox potentials, but also guarantees the reverse migration orientation of photogenerated carriers in phase junction, thereby endowing photocarriers with a prolonged lifetime. Compared to pure cubic or hexagonal phase (72.6 or 101.1 μmol h-1 g-1), this CdS system with optimized phase junction demonstrates an improved photocatalytic hydrogen evolution activity of 1.04 mmol h-1 g-1 and favorable stability without cocatalyst assistance, which mainly stems from an efficient protons reduction process interacting with long-lived photogenerated electrons. This research explores the mechanism behind phase regulation and its relationship with junction capability, providing a powerful strategy to manipulate crystal phase distribution and paving a feasible avenue for other phase-dependent photocatalysts towards rational design of heterostructures based on different phases in solar energy conversion field.

The functions of exosomes targeting astrocytes and astrocyte-derived exosomes targeting other cell types

Astrocytes are the most abundant glial cells in the central nervous system; they participate in crucial biological processes, maintain brain structure, and regulate nervous system function. Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins, peptides, nucleotides, and lipids secreted from their cellular sources. Increasing evidence shows that exosomes participate in a communication network in the nervous system, in which astrocyte-derived exosomes play important roles. In this review, we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system. We also discuss the potential research directions of the exosome-based communication network in the nervous system. The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain. New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.

Superelastic carbon aerogels with anisotropic and hierarchically-enhanced cellular structure for wearable piezoresistive sensors

Elastic carbon aerogels have promising applications in the field of wearable sensors. Herein, a new strategy for preparing carbon aerogels with excellent compressive strength and strain, shape recovery, and fatigue resistance was proposed based on the structure design and carbonization optimization of nanocellulose-based precursor aerogels. By the combination of directional freezing and zinc ion cross-linking, bacterial cellulose (BC)/alginate (SA) composite aerogels with high elasticity and compressive strength were first achieved. The existance of zinc ions also significantly improved the carbon retention rate and inhibited structural shrinkage, thus making the carbon aerogels retain ultra-high elasticity and fatigue resistance after compression. Moreover, the carbon aerogel possessed excellent piezoresistive pressure sensing performance with a wide detection range of 0-7.8 kPa, high sensitivity of 11.04 kpa-1, low detection limit (2 % strain), fast response (112 ms), and good durability (over 1,000 cycles). Based on these excellent properties, the carbon aerogel pressure sensors were further successfully used for human motion monitoring, from joint motion to and speech recognition.

Hypoxia-induced TRPM7 promotes glycolytic metabolism and progression in hepatocellular carcinoma

BACKGROUND

Hypoxia disrupts glucose metabolism in hepatocellular carcinoma (HCC). Transient receptor potential cation channel, subfamily M, member 7 (TRPM7) plays an ontogenetic role. Thus, we aimed to explore the regulation of TRPM7 by hypoxia-induced factor (HIF) and its underlying mechanisms in HCC.

METHODS

hypoxia was induced in multiple HCC cells using 1% O2 or CoCl2 treatment, and subsequently blocked using siRNAs targeting HIF-1α or HIF-2α as well as a HIF-1α protein synthesis inhibitor. The levels of HIF-1α and TRPM7 were assessed using quantitative PCR (qPCR) and Western blot analysis. Chromatin immunoprecipitation (ChIP) and luciferase assays were performed to observe the regulation of TRPM7 promoter regions by HIF-1α. A PCR array was utilized to screen glucose metabolism-related enzymes in HEK293 cells overexpressing TRPM7 induced by tetracycline, and then verified in TRPM7-overexpressed huh7 cells. Finally, CCK-8, transwell, scratch and tumor formation experiments in nude mice were conducted to examine the effect of TRPM7 on proliferation and metastasis in HCC.

RESULTS

Exposure to hypoxia led to increase the levels of TRPM7 and HIF-1α in HCC cells, which were inhibited by HIF-1α siRNA or enhanced by HIF-1α overexpression. HIF-1α directly bound to two hypoxia response elements (HREs) in the TRPM7 promoter. Several glycolytic metabolism-related enzymes, were simultaneously upregulated in HEK293 and huh7 cells overexpressing TRPM7 during hypoxia. In vitro and in vivo experiments demonstrated that TRPM7 promoted the proliferation and metastasis of HCC cells.

CONCLUSIONS

TRPM7 was directly transcriptionally regulated by HIF-1α, leading to glycolytic metabolic reprogramming and the promotion of HCC proliferation and metastasis in vitro and in vivo. Our findings suggest that TRPM7 might be a potential diagnostic indicator and therapeutic target for HCC.

The orientation of CpG conjugation on aluminum oxyhydroxide nanoparticles determines the immunostimulatory effects of combination adjuvants

In subunit vaccines, aluminum salts (Alum) are commonly used as adjuvants, but with limited cellular immune responses. To overcome this limitation, CpG oligodeoxynucleotides (ODNs) have been used in combination with Alum. However, current combined usage of Alum and CpG is limited to linear mixtures, and the underlying interaction mechanism between CpG and Alum is not well understood. Thus, we propose to chemically conjugate Alum nanoparticles and CpG (with 5' or 3' end exposed) to design combination adjuvants. Our study demonstrates that compared to the 3'-end exposure, the 5'-end exposure of CpG in combination adjuvants (Al-CpG-5') enhances the activation of bone-marrow derived dendritic cells (BMDCs) and promotes Th1 and Th2 cytokine secretion. We used the SARS-CoV-2 receptor binding domain (RBD) and hepatitis B surface antigen (HBsAg) as model antigens to demonstrate that Al-CpG-5' enhanced antigen-specific antibody production and upregulated cytotoxic T lymphocyte markers. Additionally, Al-CpG-5' allows for coordinated adaptive immune responses even at lower doses of both CpG ODNs and HBsAg antigens, and enhances lymph node transport of antigens and activation of dendritic cells, promoting Tfh cell differentiation and B cell activation. Our novel Alum-CPG strategy points the way towards broadening the use of nanoadjuvants for both prophylactic and therapeutic vaccines.

Branched-chain amino acid supplementation drives dynamic changes in gut microbiota without impairing glucose and lipid homeostasis at the different stages of insulin resistance in mice on a high-fat diet

OBJECTIVE

The potential role of dietary branched-chain amino acids on circulating branched-chain amino acid levels and their relationship with metabolic health are complex, and the literature is inconsistent. We aimed to explore the dynamic effects of branched-chain amino acid supplementation on glucose and lipid homeostasis at different stages of insulin resistance in high-fat diet-fed mice.

METHODS

Male C57BL/6J mice were fed with a normal chow diet, high-fat diet, or high-fat diet supplemented with 100% branched-chain amino acids for 12 or 24 wk. Metabolic parameters and gut microbiota profiling were performed at these two time points.

RESULTS

High-fat diet feeding caused varying degrees of branched-chain amino acid metabolic disorders in two different stages of insulin resistance. Supplementing with branched-chain amino acids further exacerbated branched-chain amino acid accumulation in the early stage of insulin resistance (12 wk), while adding branched-chain amino acids did not further elevate branched-chain amino acid levels in the hyperglycemia and hyperinsulinemia stage (24 wk). Compared with the high-fat diet group, branched-chain amino acid supplementation did not affect body weight; liver total cholesterol and triacylglycerol levels; and serum glucose, insulin, total cholesterol, triacylglycerol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol levels as well as glucose tolerance at these two time points but triggered dynamic changes in the gut bacterial diversity and gut microbiota composition and abundance, especially in the genus associated with obesity and related metabolic disorders.

CONCLUSION

Dietary branched-chain amino acid supplementation drives dynamic changes in circulating branched-chain amino acid levels and gut microbiome without subsequent effects on glucose and lipid homeostasis in high-fat diet-induced obese mice within the parameters of our study.

Added value of spectral computed tomography quantitative parameters for differentiating tuberculosis-associated fibrosing mediastinitis from endobronchial lung cancer: initial results

OBJECTIVE

The objective of this study was to explore the added value of spectral computed tomography (CT) parameters to conventional CT features for differentiating tuberculosis-associated fibrosing mediastinitis (TB-associated FM) from endobronchial lung cancer (EBLC).

METHODS

Chest spectral CT enhancement images from 109 patients with atelectasis were analyzed retrospectively. These patients were divided into two distinct categories: the TB-associated FM group (n = 77) and the EBLC group (n = 32), based on bronchoscopy and/or pathological findings. The selection of spectrum parameters was optimized with the least absolute shrinkage and selection operator regression analysis. The relationship between the spectrum parameters and conventional parameters was explored using Pearson's correlation. Multivariate logistic regression analysis was used to build spectrum model. The spectrum parameters in the spectrum model were replaced with their corresponding conventional parameters to build the conventional model. Diagnostic performances were evaluated using receiver operating characteristic curve analyses.

RESULTS

There was a moderate correlation between the parameters ㏒(L-AEFNIC) - ㏒(L-AEFC) (r= 0.419; p< 0.0001), ㏒(O-AEF40KeV) - ㏒(O-AEFC) (r= 0.475; p< 0.0001), [L-A-hydroxyapatite {HAP}(I)] - (L-U-CT) (r= 0.604; p< 0.0001), {arterial enhancement fraction (AEF) derived from normalized iodine concentration (NIC) of lymph node (L-AEFNIC), AEF derived from CT40KeV of bronchial obstruction (O-AEF40KeV), arterial-phase Hydroxyapatite (Iodine) concentration of lymph node [L-A-HAP(I)], AEF derived from conventional CT (AEFC), unenhanced CT value (U-CT)}. Spectrum model could improve diagnostic performances compared to conventional model (area under curve: 0.965 vs 0.916, p= 0.038).

CONCLUSION

There was a moderate correlation between spectrum parameters and conventional parameters. Integrating conventional CT features with spectrum parameters could further improve the ability in differentiating TB-associated FM from EBLC.

Renal protective effects and mechanisms of Astragalus membranaceus for diabetic kidney disease in animal models: An updated systematic review and meta-analysis

BACKGROUND

Astragalus membranaceus (AM) shows potential therapeutic benefits for managing diabetic kidney disease (DKD), a leading cause of kidney failure with no cure. However, its comprehensive effects on renal outcomes and plausible mechanisms remain unclear.

PURPOSE

This systematic review and meta-analysis aimed to synthesize the effects and mechanisms of AM on renal outcomes in DKD animal models.

METHODS

Seven electronic databases were searched for animal studies until September 2023. Risk of bias was assessed based on SYRCLE's Risk of Bias tool. Standardized mean difference (SMD) or mean difference (MD) were estimated for the effects of AM on serum creatinine (SCr), blood urea nitrogen (BUN), albuminuria, histological changes, oxidative stress, inflammation, fibrosis and glucolipids. Effects were pooled using random-effects models. Heterogeneity was presented as I2. Subgroup analysis investigated treatment- and animal-related factors for renal outcomes. Publication bias was assessed using funnel plots and Egger's test. Sensitivity analysis was performed to assess the results' robustness. RevMan 5.3 and Stata MP 15 software were used for statistical analysis.

RESULTS

Forty studies involving 1543 animals were identified for analysis. AM treatment significantly decreased SCr (MD = -19.12 μmol/l, 95 % CI: -25.02 to -13.23), BUN (MD = -6.72 mmol/l, 95 % CI: -9.32 to -4.12), urinary albumin excretion rate (SMD = -2.74, 95 % CI: -3.57, -1.90), histological changes (SMD = -2.25, 95 % CI: -3.19 to -1.32). AM treatment significantly improved anti-oxidative stress expression (SMD = 1.69, 95 % CI: 0.97 to 2.41), and decreased inflammation biomarkers (SMD = -3.58, 95 % CI: -5.21 to -1.95). AM treatment also decreased fibrosis markers (i.e. TGF-β1, CTGF, collagen IV, Wnt4 and β-catenin) and increased anti-fibrosis marker BMP-7. Blood glucose, lipids and kidney size were also improved compared with the DM control group.

CONCLUSION

AM could improve renal outcomes and alleviate injury through multiple signaling pathways. This indicates AM may be an option to consider for the development of future DKD therapeutics.

Development and validation of a risk prediction model and prediction tools for post-thrombotic syndrome in patients with lower limb deep vein thrombosis

PURPOSE

Our research aims to compare the predictive performance of decision tree algorithms (DT) and logistic regression analysis (LR) in constructing models, and develop a Post-Thrombotic Syndrome (PTS) risk stratification tool.

METHODS

We retrospectively collected and analyzed relevant case information of 618 patients diagnosed with DVT from January 2012 to December 2021 in three different tertiary hospitals in Jiangxi Province as the modeling group. Additionally, we used the case information of 212 patients diagnosed with DVT from January 2022 to January 2023 in two tertiary hospitals in Hubei Province and Guangdong Province as the validation group. We extracted electronic medical record information including general patient data, medical history, laboratory test indicators, and treatment data for analysis. We established DT and LR models and compared their predictive performance using receiver operating characteristic (ROC) curves and confusion matrices. Internal and external validations were conducted. Additionally, we utilized LR to generate nomogram charts, calibration curves, and decision curves analysis (DCA) to assess its predictive accuracy.

RESULTS

Both DT and LR models indicate that Year, Residence, Cancer, Varicose Vein Operation History, DM, and Chronic VTE are risk factors for PTS occurrence. In internal validation, DT outperforms LR (0.962 vs 0.925, z = 3.379, P < 0.001). However, in external validation, there is no significant difference in the area under the ROC curve between the two models (0.963 vs 0.949, z = 0.412, P = 0.680). The validation results of calibration curves and DCA demonstrate that LR exhibits good predictive accuracy and clinical effectiveness. A web-based calculator software of nomogram (https://sunxiaoxuan.shinyapps.io/dynnomapp/) was utilized to visualize the logistic regression model.

CONCLUSIONS

The combination of decision tree and logistic regression models, along with the web-based calculator software of nomogram, can assist healthcare professionals in accurately assessing the risk of PTS occurrence in individual patients with lower limb DVT.

Systematically amino acid analysis: Advancements in extinction coefficient determination for therapeutic proteins

Biologicals developers often face challenges in accurately determining the extinction coefficient (EC) measurement. We have successfully improved the precision and robustness of the widely recognized amino acid analysis method for EC determination, through a stepwise optimization process. Extensive analyses based on 114 observations, covering eight proteins over three years were performed, with a maximum relative standard deviation of 1.5% among multiple analysts, and a maximum deviation of 2.8% from the theoretical EC across the eight given proteins examined.

Box2Mask: Box-Supervised Instance Segmentation via Level-Set Evolution

In contrast to fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of simple box annotations, which has recently attracted increasing research attention. This paper presents a novel single-shot instance segmentation approach, namely Box2Mask, which integrates the classical level-set evolution model into deep neural network learning to achieve accurate mask prediction with only bounding box supervision. Specifically, both the input image and its deep features are employed to evolve the level-set curves implicitly, and a local consistency module based on a pixel affinity kernel is used to mine the local context and spatial relations. Two types of single-stage frameworks, i.e., CNN-based and transformer-based frameworks, are developed to empower the level-set evolution for box-supervised instance segmentation, and each framework consists of three essential components: instance-aware decoder, box-level matching assignment and level-set evolution. By minimizing the level-set energy function, the mask map of each instance can be iteratively optimized within its bounding box annotation. The experimental results on five challenging testbeds, covering general scenes, remote sensing, medical and scene text images, demonstrate the outstanding performance of our proposed Box2Mask approach for box-supervised instance segmentation. In particular, with the Swin-Transformer large backbone, our Box2Mask obtains 42.4% mask AP on COCO, which is on par with the recently developed fully mask-supervised methods.

Occurrence of rare earth elements in umbilical cord serum and association with thyroid hormones and birth outcomes in newborns

Rare earth elements (REEs) are emerging contaminants that are increasingly used in high technology products. However, limited information is available regarding exposure to REEs and associated health effects in neonates. This study aimed to investigate the association between REE concentrations and thyroid hormone levels, as well as birth outcomes in 109 newborns in Beijing, China. We measured the concentrations of 16 REEs and thyroid hormones in umbilical cord serum. To assess the impact of exposure to individual REEs and REE mixtures on thyroid hormone levels and birth outcomes, we employed univariate linear regression, least absolute shrinkage and selection operator (LASSO), and weighted quantile sum (WQS) models. We detected 14 REEs at high rates (92.6%-100%), with yttrium exhibiting the highest median (interquartile range) concentration [43.94 (0.33-172.55) ng/mL], followed by scandium [3.64 (0.46-11.15) ng/mL]. Univariate analyses showed that per logarithmic (ln)-unit change of neodymium (Nd) and samarium (Sm) was associated with 0.039 [95% confidence interval (CI): 0.001, 0.007] and 0.031 (95% CI: 0.003, 0.060) increases in free thyroxine (FT4) levels, respectively. Moreover, 14 REEs exhibited significant associations with triiodothyronine (T3) levels, resulting in increases ranging from 0.066 to 0.307. Elevated concentrations of terbium (Tb) [per ln-unit change: -0.021 (95% CI: -0.041, -0.01)] and lutetium (Lu) [-0.023 (95% CI: -0.043, -0.002)] were inversely correlated with birth length in newborns. A further multiple exposure analysis employing the LASSO model identified Sm, Nd, Y, Sc, and Lu as critical factors influencing FT4 and T3 levels. Additionally, WQS analyses showed positive associations between exposure to a mixture of 14 REEs and FT4 (P = 0.046), T3 (P < 0.001), and birth length (P = 0.049). These findings suggest that in utero exposure to REEs might disrupt thyroid hormone homeostasis and impact intrauterine growth. Further studies are warranted to validate these findings and elucidate the underlying mechanisms.

[Retracted] Fe3O4‑solamargine induces apoptosis and inhibits metastasis of pancreatic cancer cells

Following the publication of the above article, a concerned reader drew to the Editor's attention that certain of the Transwell invasion assay data shown in Fig. 5B on p. 911 were strikingly similar to data that had appeared in a previously published paper written by different authors at a different research institute. In view of the fact that certain of the data in the above article had already appeared in a previously published paper, the Editor of International Journal of Oncology has decided that this paper should be retracted from the publication. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [International Journal of Oncology 54: 905‑915, 2019; DOI: 10.3892/ijo.2018.4637].

Adiposity indicators exhibit depot- and sex-specific associations with multimorbidity onset: A cohort study of the UK Biobank

AIM

This study investigated the depot- and sex-specific associations of adiposity indicators with incident multimorbidity and comorbidity pairs.

MATERIALS AND METHODS

We selected 382 678 adults without multimorbidity (≥2 chronic diseases) at baseline from the UK Biobank. General obesity, abdominal obesity and body fat percentage indices were measured.

RESULTS

Cox proportional hazard regression analyses of general obesity indices revealed that for every one-unit increase in body mass index, the risk of incident multimorbidity increased by 5.2% (95% confidence interval 5.0%-5.4%). A dose-response relationship was observed between general obesity degrees and incident multimorbidity. The analysis of abdominal obesity indices showed that for every 0.1 increment in waist-to-height ratio and waist-to-hip ratio, the risk of incident multimorbidity increased by 42.0% (37.9%-46.2%) and 27.9% (25.7%-30.0%), respectively. Central obesity, as defined by waist circumference, contributed to a 23.2% increased risk of incident multimorbidity. Hip circumference and hip-to-height ratio had protective effects on multimorbidity onset. Consistent findings were observed for males and females. Body fat percentage elevated 3% (0.2%-5.9%) and 5.3% (1.1%-9.7%) risks of incident multimorbidity in all adults and females, respectively. Arm fat percentages elevated 5.3% (0.8%-9.9%) and 19.4% (11.0%-28.5%) risks of incident multimorbidity in all adults and males, respectively. The general obesity indices, waist circumference, waist-to-height ratio, waist-to-hip ratio and central obesity increased the onset of comorbidity pairs, whereas hip circumference and hip-to-height ratio decreased the onset of comorbidity pairs. These adiposity indicators mainly affect diabetes mellitus-related comorbidity onset in males and hypertensive-related comorbidity onset in females.

CONCLUSIONS

Adiposity indicators are predictors of multimorbidity and comorbidity pairs and represent a promising approach for intervention.

TaoHe ChengQi decoction ameliorates sepsis-induced cardiac dysfunction through anti-ferroptosis via the Nrf2 pathway

BACKGROUND

Sepsis-induced cardiac dysfunction (SICD) is a serious complication of sepsis that is associated with increased mortality. Ferroptosis has been reported in the SICD. TaoHe ChengQi decoction (THCQD), a classical traditional Chinese medicinal formula, has multiple beneficial pharmacological effects. The potential effects of THCQD on the SICD remain unknown.

PURPOSE

To investigate the effect of THCQD on SICD and explore whether this effect is related to the regulation of myocardial ferroptosis through nuclear factor erythroid 2-related factor 2 (Nrf2) activation.

METHODS

We induced sepsis in a mouse model using cecal ligation and puncture (CLP) and administered THCQD (2 and 4 g/kg) and dexamethasone (40 mg/kg). Mice mortality was recorded and survival curves were plotted. Echocardiography, hematoxylin and eosin staining, and analysis of serum myocardial injury markers and inflammatory factors were used to evaluate cardiac pathology. Myocardial ferroptosis was detected by quantifying specific biomarker content and protein levels. Through HPLC-Q-Exactive-MS analysis, we identified the components of the THCQD. Network pharmacology analysis and Cellular Thermal Shift Assay (CETSA) were utilized to predict the targets of THCQD for treating SICD. We detected the expression of Nrf2 using Western blotting or immunofluorescence. An RSL3-induced ferroptosis model was established using neonatal rat cardiomyocytes (NRCMs) to further explore the pharmacological mechanism of THCQD. In addition to measuring cell viability, we observed changes in NRCM mitochondria using electron microscopy and JC-1 staining. NRF2 inhibitor ML385 and Nrf2 knockout mice were used to validate whether THCQD exerted protective effects against SICD through Nrf2-mediated ferroptosis signaling.

RESULTS

THCQD reduced mortality in septic mice, protected against CLP-induced myocardial injury, decreased systemic inflammatory response, and prevented myocardial ferroptosis. Network pharmacology analysis and CETSA experiments predicted that THCQD may protect against SICD by activating the Nrf2 signaling pathway. Western blotting and immunofluorescence showed that THCQD activated Nrf2 in cardiac tissue. THCQDs consistently mitigated RSL3-induced ferroptosis in NRCM, which is related to Nrf2. Furthermore, the pharmacological inhibition of Nrf2 and genetic Nrf2 knockout partially reversed the protective effects of THCQD on SICD and ferroptosis.

CONCLUSION

The effect of THCQD on SICD was achieved by activating Nrf2 and its downstream pathways.

Integrated models of population pharmacokinetics and exposure response to optimize dosage regimen for anaprazole sodium in duodenal ulcer

Anaprazole sodium enteric-coated tablet is a novel proton pump inhibitor which has been approved for the treatment of duodenal ulcer. The aim of this study is to provide reliable information for the design of an optimal dosage regimen. Population pharmacokinetics and exposure-response models were integrated to evaluate the pharmacokinetic parameters and covariates of Anaprazole and its metabolite M21-1, and subsequently provided dosage suggestions based on clinical trials and simulation data. A pharmacokinetic model incorporating two-compartment for the parent drug and one-compartment for the metabolite, with both first-order and zero-order mixed absorption was used to describe the pharmacokinetics of Anaprazole and M21-1. Age emerged as a significant covariate affecting the elimination rate constant of M21-1, with clearance decreasing as age advances. No correlation was observed between the pharmacokinetics of Anaprazole or M21-1 and the adverse reactions under the current dosages. BMI might be the influence factor of the mild gastrointestinal adverse reactions. Meanwhile, Anaprazole had a good healing rate (94.0 %) in duodenal ulcer patients and the exposure-response analysis indicated that the cured results were not influenced by the exposure parameters of parent drug or metabolite. In conclusion, the drug is safe when dosing between 20 and 100 mg once a day.

Unsupervised Test-Time Adaptation Learning for Effective Hyperspectral Image Super-Resolution With Unknown Degeneration

Fusing a low-resolution hyperspectral image (HSI) with a high-resolution (HR) multi-spectral image has provided an effective way for HSI super-resolution (SR). The key lies on inferring the posteriori of the latent (i.e., HR) HSI using an appropriate image prior and the likelihood determined by the degeneration between the latent HSI and the observed images. However, in scenarios with complex imaging environments and various imaging scenes, the prior of HSIs can be prohibitively complicated and the degeneration is often unknown, which causes it difficult to accurately infer the posteriori of each latent HSI. To tackle this problem, we present an unsupervised test-time adaptation learning (UTAL) framework for HSI SR under unknown degeneration. Instead of directly modeling the complicated image prior, it first implicitly learns a content-agnostic prior shared across different images through supervisedly pre-training a mutual-guiding fusion module on extensive synthetic data. Then, it adapts the shared prior to those private characteristics in the latent HSI for posteriori inference through unsupervisedly learning a self-guiding adaptation module and a degeneration estimation network on two observed images in the test phase. Such a two-stage learning scheme models the complicated image prior in a divide-and-conquer manner, which eases the modeling difficulty and improves the prior accuracy. Moreover, the unknown degeneration can be estimated properly. Both of these two advantages empower us to accurately infer the posteriori of the latent HSI, thereby increasing the generalization performance in real applications. Additionally, in order to further mitigate the over-fitting in coping with more challenging cases (e.g., degenerations in both spectral and spatial domains are unknown) and speed up, we propose to meta-train UTAL on extensive synthetic SR tasks and solve it using an alternative optimization strategy such that UTAL learns to produce good generalization performance in real challenging cases with a small number of gradient descent steps. To verify the efficacy of UTAL, we evaluate it on HSI SR tasks with different unknown degenerations as well as some other HSI restoration tasks (e.g., compressive sensing), and report strong results superior to that of existing competitors.

Reducing the contaminant dispersion and infection risks in the train cabins by adjusting the inlet turbulence intensity: A study based on turbulence simulation

Existing studies on ventilation in closed spaces mainly considered the average inlet velocity and ignored the influence of inlet turbulent fluctuation. However, the variation in inlet turbulence intensity (TI) is considerable and significantly affects the dispersion of contaminants. This study conducts numerical simulations verified by experiments to investigate the effect of the inlet TI on train contaminants dispersion and analyze infection probability variation. Firstly, the unsteady Reynolds-averaged Navier-Stokes (URANS) method and improved delayed detached eddy simulation (IDDES) method are compared in simulating the internal airflow characteristics based on the on-site measurement. The results indicate that the latter dominates in capturing airflow pulsations more than the former, although the mean airflow results obtained from both methods agree well with experimental results. Furthermore, the IDDES method is employed to investigate the effect of the inlet TI on contaminant dispersion, and the infection risks are also assessed using the improved probability model. The results show that, with the increase of TI from 5 % to 30 %, the contaminant removal grows considerably, with the removal index rising from 0.23 to 1.86. The increased TI leads to the overall and local infection risks of occupants descending significantly, wherein the former decreases from 1.53 % to 0.88 % with a reduction rate of 42 %, and the latter drops from 3.30 % to 2.16 % with a mitigation rate of 35 %. The findings can serve as solid guidelines for numerical method selection in accurately capturing the indoor dynamic airflow distribution and for the ventilation parameters design regarding TI inside trains to mitigate the airborne infection risk.

Engineering Pancreatic Islets to Transiently Codisplay on Their Surface Thrombomodulin and CD47 Immunomodulatory Proteins as a Means of Mitigating Instant Blood-Mediated Inflammatory Reaction following Intraportal Transplantation

Most pancreatic islets are destroyed immediately after intraportal transplantation by an instant blood-mediated inflammatory reaction (IBMIR) generated through activation of coagulation, complement, and proinflammatory pathways. Thus, effective mitigation of IBMIR may be contingent on the combined use of agents targeting these pathways for modulation. CD47 and thrombomodulin (TM) are two molecules with distinct functions in regulating coagulation and proinflammatory responses. We previously reported that the islet surface can be modified with biotin for transient display of novel forms of these two molecules chimeric with streptavidin (SA), that is, thrombomodulin chimeric with SA (SA-TM) and CD47 chimeric with SA (SA-CD47), as single agents with improved engraftment following intraportal transplantation. This study aimed to test whether islets can be coengineered with SA-TM and SA-CD47 molecules as a combinatorial approach to improve engraftment by inhibiting IBMIR. Mouse islets were effectively coengineered with both molecules without a detectable negative impact on their viability and metabolic function. Coengineered islets were refractory to destruction by IBMIR ex vivo and showed enhanced engraftment and sustained function in a marginal mass syngeneic intraportal transplantation model. Improved engraftment correlated with a reduction in intragraft innate immune infiltrates, particularly neutrophils and M1 macrophages. Moreover, transcripts for various intragraft procoagulatory and proinflammatory agents, including tissue factor, HMGB1 (high-mobility group box-1), IL-1β, IL-6, TNF-α, IFN-γ, and MIP-1α, were significantly reduced in coengineered islets. These data demonstrate that the transient codisplay of SA-TM and SA-CD47 proteins on the islet surface is a facile and effective platform to modulate procoagulatory and inflammatory responses with implications for both autologous and allogeneic islet transplantation.

Alterations in serum metabolic profiles of early-stage hepatocellular carcinoma patients after radiofrequency ablation therapy

OBJECTIVE

To investigate the alterations in serum metabolic profiles and early-stage hepatocellular carcinoma (HCC) patient characteristics after radiofrequency ablation (RFA) therapy. This evaluation aimed to assess treatment effectiveness and identify potential novel approaches and targets for HCC treatment and prognosis monitoring.

METHODS

Untargeted metabolomics technology was employed to analyze serum metabolic profiles in healthy volunteer controls (NCs) and early stage HCC patients before and after RFA therapy. Additionally, Human Metabolome Database and Kyoto Encyclopedia of Genes and Genomes database were used to identify the differential metabolites (DMs) and metabolic pathways. Cystoscape was utilized to construct DM gene networks. Amino acid analyses were performed to validate our findings.

RESULTS

We identified 11, 14, and six DMs between the NC and HCC groups, HCC patients before and after RFA therapy, and post-RFA HCC and NC groups, respectively. The expression levels of these DMs, particularly those of amino acids and lipids, significantly changed. Compared with the NC group, higher levels of L-tyrosine, aspartate, and 18-oxo-oleate were observed in HCC patients, which were significantly reduced in patients after RFA therapy. Meanwhile, HCC patients after RFA therapy had increased levels of L-arginine, phosphatidic acid (20:3), and lysophosphatidyl choline (LPC) (20:4) compared to those before therapy, while their levels before therapy were lower than those of NC. Moreover, most metabolites in the post-RFA and NC groups showed no significant changes in expression, except for L-tyrosine and LPC (16:0). These metabolites could potentially serve as characteristic factors of early-stage HCC patients after RFA therapy. Joint pathway analysis revealed striking changes, mainly in phenylalanine, tyrosine, and tryptophan biosynthesis; alanine, aspartate, and glutamate metabolism; and arginine and aminoacyl-tRNA biosynthesis. Bioinformatics analysis of publicly available data preliminarily identified 187 DM-related metabolic enzymes.

CONCLUSION

Our study proposed novel targets for early-stage HCC treatment, laying the groundwork for improving treatment efficacy and prognosis of early-stage HCC patients.