Roles of serum uric acid on the association between arsenic exposure and incident metabolic syndrome in an older Chinese population.

Growing evidences showed that heavy metals exposure may be associated with metabolic diseases. Nevertheless, the mechanism underlying arsenic (As) exposure and metabolic syndrome (MetS) risk has not been fully elucidated. So we aimed to prospectively investigate the role of serum uric acid (SUA) on the association between blood As exposure and incident MetS. A sample of 1045 older participants in a community in China was analyzed. We determined As at baseline and SUA concentration at follow-up in the Yiwu Elderly Cohort. MetS events were defined according to the criteria of the International Diabetes Federation (IDF). Generalized linear model with log-binominal regression model was applied to estimate the association of As with incident MetS. To investigate the role of SUA in the association between As and MetS, a mediation analysis was conducted. In the fully adjusted log-binominal model, per interquartile range increment of As, the risk of MetS increased 1.25-fold. Compared with the lowest quartile of As, the adjusted relative risk (RR) of MetS in the highest quartile was 1.42 (95% confidence interval, CI: 1.03, 2.00). Additionally, blood As was positively associated with SUA, while SUA had significant association with MetS risk. Further mediation analysis demonstrated that the association of As and MetS risk was mediated by SUA, with the proportion of 15.7%. Our study found higher As was remarkably associated with the elevated risk of MetS in the Chinese older adults population. Mediation analysis indicated that SUA might be a mediator in the association between As exposure and MetS.

A maternal brain hormone that builds bone.

In lactating mothers, the high calcium (Ca2+) demand for milk production triggers significant bone loss1. Although oestrogen normally counteracts excessive bone resorption by promoting bone formation, this sex steroid drops precipitously during this postpartum period. Here we report that brain-derived cellular communication network factor 3 (CCN3) secreted from KISS1 neurons of the arcuate nucleus (ARCKISS1) fills this void and functions as a potent osteoanabolic factor to build bone in lactating females. We began by showing that our previously reported female-specific, dense bone phenotype2 originates from a humoral factor that promotes bone mass and acts on skeletal stem cells to increase their frequency and osteochondrogenic potential. This circulatory factor was then identified as CCN3, a brain-derived hormone from ARCKISS1 neurons that is able to stimulate mouse and human skeletal stem cell activity, increase bone remodelling and accelerate fracture repair in young and old mice of both sexes. The role of CCN3 in normal female physiology was revealed after detecting a burst of CCN3 expression in ARCKISS1 neurons coincident with lactation. After reducing CCN3 in ARCKISS1 neurons, lactating mothers lost bone and failed to sustain their progeny when challenged with a low-calcium diet. Our findings establish CCN3 as a potentially new therapeutic osteoanabolic hormone for both sexes and define a new maternal brain hormone for ensuring species survival in mammals.

Abatacept retention and clinical effectiveness in patients with rheumatoid arthritis in a real-world setting in Taiwan.

AIM: To evaluate real-world abatacept retention and clinical outcomes in patients with rheumatoid arthritis in Taiwan. METHODS: This prospective, observational study enrolled patients with rheumatoid arthritis aged ≥20 years who received abatacept in real-world practice. The primary endpoint was the abatacept retention rate at 24 months. Patients were categorized into subgroups based on abatacept treatment status and previous biological disease-modifying antirheumatic drug (bDMARD) therapy. Risk factors affecting abatacept retention were determined by regression analysis. RESULTS: A total of 212 patients were enrolled. The overall abatacept retention rate at 24 months among all patients was 59.9% (95% confidence interval 53.0%-66.6%). Patients who were ongoing users of abatacept and bDMARD-naïve had the highest retention rate (76.3%); of these, 31.6% achieved low disease activity or remission after 2 years. Previous treatment with bDMARDs was associated with an increased risk of abatacept discontinuation (hazard ratio 1.99; p = .002). The most common reasons for abatacept discontinuation were drug switch (11.3%) and loss to follow-up (6.1%). Abatacept was well-tolerated with no new safety signals. CONCLUSION: The 24-month retention rate of abatacept was 59.9%; abatacept was associated with improved clinical outcomes and was well-tolerated in the real-world setting in Taiwan.

Multiomics analysis reveals the potential of LPCAT1-PC axis as a therapeutic target for human intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a highly prevalent musculoskeletal disorder that is associated with considerable morbidity. However, there is currently no drug available that has a definitive therapeutic effect on IDD. In this study, we aimed to identify the molecular features and potential therapeutic targets of IDD through a comprehensive multiomics profiling approach. By integrating transcriptomics, proteomics, and ultrastructural analyses, we discovered dysfunctions in various organelles, including mitochondria, the endoplasmic reticulum, the Golgi apparatus, and lysosomes. Metabolomics analysis revealed a reduction in total phosphatidylcholine (PC) content in IDD. Through integration of multiple omics techniques with disease phenotypes, a pivotal pathway regulated by the lysophosphatidylcholine acyltransferase 1 (LPCAT1)-PC axis was identified. LPCAT1 exhibited low expression levels and exhibited a positive correlation with PC content in IDD. Suppression of LPCAT1 resulted in inhibition of PC synthesis in nucleus pulposus cells, leading to a notable increase in nucleus pulposus cell senescence and damage to cellular organelles. Consequently, PC exhibits potential as a therapeutic agent, as it facilitates the repair of the biomembrane system and alleviates senescence in nucleus pulposus cells via reversal of downregulation of the LPCAT1-PC axis.

Deletion of GPR81 activates CREB/Smad7 pathway and alleviates liver fibrosis in mice.

BACKGROUND: Enhanced glycolysis is a crucial metabolic event that drives the development of liver fibrosis, but the molecular mechanisms have not been fully understood. Lactate is the endproduct of glycolysis, which has recently been identified as a bioactive metabolite binding to G-protein-coupled receptor 81 (GPR81). We then questioned whether GPR81 is implicated in the development of liver fibrosis. METHODS: The level of GPR81 was determined in mice with carbon tetrachloride (CCl4)-induced liver fibrosis and in transforming growth factor beta 1 (TGF-ß1)-activated hepatic stellate cells (HSCs) LX-2. To investigate the significance of GPR81 in liver fibrosis, wild-type (WT) and GPR81 knockout (KO) mice were exposed to CCl4, and then the degree of liver fibrosis was determined. In addition, the GPR81 agonist 3,5-dihydroxybenzoic acid (DHBA) was supplemented in CCl4-challenged mice and TGF-ß1-activated LX-2 cells to further investigate the pathological roles of GPR81 on HSCs activation. RESULTS: CCl4 exposure or TGF-ß1 stimulation significantly upregulated the expression of GPR81, while deletion of GPR81 alleviated CCl4-induced elevation of aminotransferase, production of pro-inflammatory cytokines, and deposition of collagen. Consistently, the production of TGF-ß1, the expression of alpha-smooth muscle actin (α-SMA) and collagen I (COL1A1), as well as the elevation of hydroxyproline were suppressed in GPR81 deficient mice. Supplementation with DHBA enhanced CCl4-induced liver fibrogenesis in WT mice but not in GPR81 KO mice. DHBA also promoted TGF-ß1-induced LX-2 activation. Mechanistically, GPR81 suppressed cAMP/CREB and then inhibited the expression of Smad7, a negative regulator of Smad3, which resulted in increased phosphorylation of Smad3 and enhanced activation of HSCs. CONCLUSION: GPR81 might be a detrimental factor that promotes the development of liver fibrosis by regulating CREB/Smad7 pathway.

A novel variant c.902C>A (p. A301D) in KCNQ4 associated with non-syndromic deafness 2A in a Chinese family.

BACKGROUND: Deafness autosomal dominant 2A (DFNA2A) is related to non-syndromic genetic hearing impairment. The KCNQ4 (Potassium Voltage-Gated Channel Subfamily Q Member 4) can lead to DFNA2A. In this study, we report a case of autosomal dominant non-syndromic hearing loss with six family members as caused by a novel variant in the KCNQ4 gene. METHODS: The whole-exome sequencing (WES) and pure tone audiometry were performed on the proband of the family. Sanger sequencing was conducted on family members to determine if the novel variant in the KCNQ4 gene was present. Evolutionary conservation analysis and computational tertiary structure protein prediction of the wild-type KCNQ4 protein and its variant were then performed. In addition, voltage-gated channel activity of the wild-type KCNQ4 protein and its variant were tested using whole-cell patch clamp. RESULTS: It was observed that the proband had inherited autosomal dominant, non-syndromic sensorineural hearing loss as a trait. A novel co-segregating heterozygous missense variant (c.902C>A, p.Ala301Asp) of the KCNQ4 gene was identified in the proband and other five affected family members. This variant was predicted to cause an alanine-to-aspartic acid substitution at position 301 in the KCNQ4 protein. The alanine at position 301 is well conserved across different species. Whole-cell patch clamp showed that there was a significant difference between the WT protein currents and the mutant protein currents in the voltage-gated channel activity. CONCLUSION: In the present study, performing WES in conjunction with Sanger sequencing enhanced the detection of a novel, potentially causative variant (c301 A>G; p.Ala301Asp) in exon 6 of the KCNQ4 gene. Therefore, our findings contributed to the mutation spectrum of the KCNQ4 gene and may be useful in the diagnosis and gene therapy of deafness autosomal dominant 2A.

Logistic regression modeling of cytokines for cerebrospinal fluid evaluation in primary central nervous system lymphoma.

BACKGROUND: The diagnostic utility of cerebrospinal fluid (CSF) cytology encounters impediments stemming from variability in cell collection techniques and pathologists' morphological acumen, resulting in wide-ranging CSF positivity rates for primary central nervous system lymphomas (PCNSL). Such disparity impacts patient evaluation, treatment stratagem, and prognostication. Thus, this study endeavors to explore liquid biomarkers complementary to CSF cytology or immunophenotype analysis in the diagnosis of CSF involvement. METHODS: 398 newly diagnosed PCNSL patients were categorized into CSF involvement and non-involvement groups based on CSF cytology and immunophenotype analysis. Binary logistic regression analysis was performed on 338 patients to investigate factors predicting CSF involvement and to develop a joint prediction model. An additional cohort of 60 PCNSL patients was recruited for model validation. Statistical analyses included the Mann-Whitney U test for comparing various CSF parameters between two groups. ROC curve analyses were performed for each biomarker to identify PCNSL CSF involvement. RESULTS: The cytokine IL-10 level in CSF has emerged as the most promising biomarker for CSF evaluation, boasting an ROC AUC of 0.922. C-TNFα and soluble C-IL2R demonstrate efficacy in quantifying tumor burden within the CSF. Logistic regression identified C-IL10lg (OR = 30.103, P < 0.001), C-TNC (OR = 1.126, P < 0.001), C-IL2Rlg (OR = 3.743, P = 0.029) as independent predictors for CSF involvement, contributing to a joint predictive model with an AUC of 0.935, sensitivity of 74.1 %, and specificity of 93.0 %. Validation of the model in an independent cohort confirmed its effectiveness, achieving an AUC of 0.9713. CONCLUSIONS: The identification of these feasible biomarkers and the development of an accurate prediction model may facilitate the precise evaluation of CSF status in PCNSL, offering significant advancements in patient management.

TDRD1 phase separation drives intermitochondrial cement assembly to promote piRNA biogenesis and fertility.

The intermitochondrial cement (IMC) is a prominent germ granule that locates among clustered mitochondria in mammalian germ cells. Serving as a key platform for Piwi-interacting RNA (piRNA) biogenesis; however, how the IMC assembles among mitochondria remains elusive. Here, we identify that Tudor domain-containing 1 (TDRD1) triggers IMC assembly via phase separation. TDRD1 phase separation is driven by the cooperation of its tetramerized coiled-coil domain and dimethylarginine-binding Tudor domains but is independent of its intrinsically disordered region. TDRD1 is recruited to mitochondria by MILI and sequentially enhances mitochondrial clustering and triggers IMC assembly via phase separation to promote piRNA processing. TDRD1 phase separation deficiency in mice disrupts IMC assembly and piRNA biogenesis, leading to transposon de-repression and spermatogenic arrest. Moreover, TDRD1 phase separation is conserved in vertebrates but not in invertebrates. Collectively, our findings demonstrate a role of phase separation in germ granule formation and establish a link between membrane-bound organelles and membrane-less organelles.

Associations of overweight/obesity with patient-reported outcome measures after oblique lumbar interbody fusion.

Background: Oblique lateral interbody fusion (OLIF) combined with transpedicular screw fixation has been practiced for degenerative spinal diseases of elderly patients for years. However, overweight patients have been shown to have longer operative times and more complications from surgery. The effect on clinical outcome is still uncertified. The objective of this study was to determine is overweight a risk factor to clinical outcome of OLIF combined with transpedicular screw fixation technique. Material and methods: A retrospective study in patients submitted to OLIF combined with transpedicular screw fixation from January 2018 to August 2019 was conducted. VAS score, ODI score and EQ5D were measured before the operation and one year after the operation. Results: A total of 111 patients were included with 48 patients in the non-obese group and 55 patients in the overweight/obese group. There was no significant difference between the two groups in gender, age, smoking history, hypertension, chronic kidney disease and diabetes mellitus. Overweight/obese group has higher BMI (28.4 vs. 22.7, p < 0.001) than non-obese group. There was no difference between the two groups in pre-operative VAS score, ODI score and EQ5D score. However, the healthy weight group improved much more than the overweight score in VAS score, ODI score and EQ5D score. Conclusion: The overweight/obese patient group had clinical outcomes worse than the non-obese group in terms of pain relief and life functions.

A Blood Hepatocellular Carcinoma Signature Recognizes Very Small Tumor Nodules with Metastatic Traits.

Background and Aims: Hepatocellular carcinoma (HCC) cases with small nodules are commonly treated with radiofrequency ablation (RFA), but the recurrence rate remains high. This study aimed to establish a blood signature for identifying HCC with metastatic traits pre-RFA. Methods: Data from HCC patients treated between 2010 and 2017 were retrospectively collected. A blood signature for metastatic HCC was established based on blood levels of alpha-fetoprotein and des-γ-carboxy-prothrombin, cell-free DNA (cfDNA) mutations, and methylation changes in target genes in frozen-stored plasma samples that were collected before RFA performance. The HCC blood signature was validated in patients prospectively enrolled in 2021. Results: Of 251 HCC patients in the retrospective study, 33.9% experienced recurrence within 1 year post-RFA. The HCC blood signature identified from these patients included des-γ-carboxy-prothrombin ≥40 mAU/mL with cfDNA mutation score, where cfDNA mutations occurred in the genes of TP53, CTNNB1, and TERT promoter. This signature effectively predicted 1-year post-RFA recurrence of HCC with 92% specificity and 91% sensitivity in the retrospective dataset, and with 87% specificity and 76% sensitivity in the prospective dataset (n=32 patients). Among 14 cases in the prospective study with biopsy tissues available, positivity for the HCC blood signature was associated with a higher HCC tissue score and shorter distance between HCC cells and microvasculature. Conclusions: This study established an HCC blood signature in pre-RFA blood that potentially reflects HCC with metastatic traits and may be valuable for predicting the disease's early recurrence post-RFA.

Exploring machine learning applications in Meningioma Research (2004-2023).

Objective: This study aims to examine the trends in machine learning application to meningiomas between 2004 and 2023. Methods: Publication data were extracted from the Science Citation Index Expanded (SCI-E) within the Web of Science Core Collection (WOSCC). Using CiteSpace 6.2.R6, a comprehensive analysis of publications, authors, cited authors, countries, institutions, cited journals, references, and keywords was conducted on December 1, 2023. Results: The analysis included a total of 342 articles. Prior to 2007, no publications existed in this field, and the number remained modest until 2017. A significant increase occurred in publications from 2018 onwards. The majority of the top 10 authors hailed from Germany and China, with the USA also exerting substantial international influence, particularly in academic institutions. Journals from the IEEE series contributed significantly to the publications. "Deep learning," "brain tumor," and "classification" emerged as the primary keywords of focus among researchers. The developmental pattern in this field primarily involved a combination of interdisciplinary integration and the refinement of major disciplinary branches. Conclusion: Machine learning has demonstrated significant value in predicting early meningiomas and tailoring treatment plans. Key research focuses involve optimizing detection indicators and selecting superior machine learning algorithms. Future efforts should aim to develop high-performance algorithms to drive further innovation in this field.

Application of adaptive chaotic dung beetle optimization algorithm to near-infrared spectral model transfer.

A new transfer approach was proposed to share calibration models of the hexamethylenetetramine-acetic acid solution for studying hexamethylenetetramine concentration values across different near-infrared (NIR) spectrometers. This approach combines Savitzky-Golay first derivative (S_G_1) and orthogonal signal correction (OSC) preprocessing, along with feature variable optimization using an adaptive chaotic dung beetle optimization (ACDBO) algorithm. The ACDBO algorithm employs tent chaotic mapping and a nonlinear decreasing strategy, enhancing the balance between global and local search capabilities and increasing population diversity to address limitations observed in traditional dung beetle optimization (DBO). Validated using the CEC-2017 benchmark functions, the ACDBO algorithm demonstrated superior convergence speed, accuracy, and stability. In the context of a partial least squares (PLS) regression model for transferring hexamethylenetetramine-acetic acid solutions using NIR spectroscopy, the ACDBO algorithm excelled over alternative methods such as uninformative variable elimination, competitive adaptive reweighted sampling, cuckoo search, grey wolf optimizer, differential evolution, and DBO in efficiency, accuracy of feature variable selection, and enhancement of model predictive performance. The algorithm attained outstanding metrics, including a determination coefficient for the calibration set (Rc2) of 0.99999, a root mean square error for the calibration set (RMSEC) of 0.00195%, a determination coefficient for the validation set (Rv2) of 0.99643, a root mean squared error for the validation set (RMSEV) of 0.03818%, residual predictive deviation (RPD) of 16.72574. Compared to existing OSC, slope and bias correction (S/B), direct standardization (DS), and piecewise direct standardization (PDS) model transfer methods, the novel strategy enhances the accuracy and robustness of model predictions. It eliminates irrelevant background information about the hexamethylenetetramine concentration, thereby minimizing the spectral discrepancies across different instruments. As a result, this approach yields a determination coefficient for the prediction set (Rp2) of 0.96228, a root mean squared error for the prediction set (RMSEP) of 0.12462%, and a relative error rate (RER) of 17.62331, respectively. These figures closely follow those obtained using DS and PDS, which recorded Rp2, RMSEP, and RER values of 0.97505, 0.10135%, 21.67030, and 0.98311, 0.08339%, 26.33552, respectively. Unlike conventional methods such as OSC, S/B, DS, and PDS, this novel approach does not require the analysis of identical samples across different instruments. This characteristic significantly broadens its applicability for model transfer, which is particularly beneficial for transferring specific measurement samples.

A non-invasive osteopontin-targeted phase changeable fluorescent nanoprobe for molecular imaging of myocardial fibrosis.

Due to the elevated fatality rate of cardiovascular diseases, myocardial fibrosis emerges as a prominent pathological alteration in the majority of heart ailments and their associated pathologies, thereby augmenting the likelihood of sudden cardiac death. Consequently, the prompt and obligatory identification of myocardial fibrosis assumes paramount importance in averting malignant incidents among patients afflicted with cardiac disorders. Herein, with higher expression osteopontin (OPN) found in cardiac fibrosis tissue, we have developed a dual-modality imaging probe, namely OPN targeted nanoparticles (OPN@PFP-DiR NPs), which loaded perfluoropentane (PFP) for ultrasound (US) and 1,1-dioctadecyl-3,3,3,3-tetramethylindotricarbocyanine iodide (DiR) for near-infrared fluorescence (NIR) of molecular imaging, to investigate the molecular features of cardiac fibrosis using US and NIR imaging. Subsequently, the OPN@PFP-DiR NPs were administered intravenously to a mouse model of myocardial infarction (MI). The US and NIR molecular imaging techniques were employed to visualize the accumulation of the nanoparticles in the fibrotic myocardium. Hence, this research presents a valuable noninvasive, cost-effective, and real-time imaging method for evaluating cardiac fibrosis, with promising clinical applications.

Autophagy Deficiency Induced by SAT1 Potentiates Tumor Progression in Triple-Negative Breast Cancer.

Aggressive triple-negative breast cancer (TNBC) still lacks approved targeted therapies, requiring more exploration of its underlying mechanisms. Previous studies have suggested a potential role of SAT1 (Spermidine/Spermine N1-acetyltransferase 1) in cancer, which needs to be further elucidated in breast cancer. In this study, highly expressed SAT1 in TNBC signified worse patient prognoses. And SAT1 knockdown effectively inhibited the proliferation and migration abilities of TNBC cells in vitro and in vivo. In terms of mechanism, the transcription factor JUN enhanced SAT1 transcriptional activity by binding to its promoter region. Then, SAT1 protein in the cytoplasm engaged in directly binding with YBX1 for sustaining YBX1 protein stability via deubiquitylation mediated by the E3 ligase HERC5. Further, SAT1 was found to suppress autophagy remarkably via stabilization of mTOR mRNA with the accumulation of YBX1-mediated methyl-5-cytosine (m5C) modification. These findings proved that SAT1 drives TNBC progression through the SAT1/YBX1/mTOR axis, which may provide a potential candidate for targeted therapy in advanced TNBC.

Molecular Cloning and Functional Identification of a Pericarp- and Testa-Abundant Gene's (AhN8DT-2) Promoter from Arachis hypogaea.

Cultivated peanut (Arachis hypogaea L.) is a key oil- and protein-providing legume crop of the world. It is full of nutrients, and its nutrient profile is comparable to that of other nuts. Peanut is a unique plant as it showcases a pegging phenomenon, producing flowers above ground, and after fertilization, the developing peg enters the soil and produces seeds underground. This geocarpic nature of peanut exposes its seeds to soil pathogens. Peanut seeds are protected by an inedible pericarp and testa. The pericarp- and testa-specific promoters can be effectively used to improve the seed defense. We identified a pericarp- and testa-abundant expression gene (AhN8DT-2) from available transcriptome expression data, whose tissue-specific expression was further confirmed by the qRT-PCR. The 1827bp promoter sequence was used to construct the expression vector using the pMDC164 vector for further analysis. Quantitative expression of the GUS gene in transgenic Arabidopsis plants showed its high expression in the pericarp. GUS staining showed a deep blue color in the pericarp and testa. Cryostat sectioning of stained Arabidopsis seeds showed that expression is only limited to seed coat (testa), and staining was not present in cotyledons and embryos. GUS staining was not detected in any other tissues, including seedlings, leaves, stems, and roots, except for some staining in flowers. Under different phytohormones, this promoter did not show an increase in expression level. These results indicated that the AhN8DT-2 promoter drives GUS gene expression in a pericarp- and testa-specific manner. The identified promoter can be utilized to drive disease resistance genes, specifically in the pericarp and testa, enhancing peanut seed defense against soil-borne pathogens. This approach has broader implications for improving the resilience of peanut crops and other legumes, contributing to sustainable agricultural practices and food security.

Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records.

Machine Learning models trained from real-world data have demonstrated promise in predicting suicide attempts in adolescents. However, their transportability, namely the performance of a model trained on one dataset and applied to different data, is largely unknown, hindering the clinical adoption of these models. Here we developed different machine learning-based suicide prediction models based on real-world data collected in different contexts (inpatient, outpatient, and all encounters) with varying purposes (administrative claims and electronic health records), and compared their cross-data performance. The three datasets used were the All-Payer Claims Database in Connecticut, the Hospital Inpatient Discharge Database in Connecticut, and the Electronic Health Records data provided by the Kansas Health Information Network. We included 285,320 patients among whom we identified 3389 (1.2%) suicide attempters and 66% of the suicide attempters were female. Different machine learning models were evaluated on source datasets where models were trained and then applied to target datasets. More complex models, particularly deep long short-term memory neural network models, did not outperform simpler regularized logistic regression models in terms of both local and transported performance. Transported models exhibited varying performance, showing drops or even improvements compared to their source performance. While they can achieve satisfactory transported performance, they are usually upper-bounded by the best performance of locally developed models, and they can identify additional new cases in target data. Our study uncovers complex transportability patterns and could facilitate the development of suicide prediction models with better performance and generalizability.

Meta-analysis identifies common gut microbiota associated with multiple sclerosis.

BACKGROUND: Previous studies have identified a diverse group of microbial taxa that differ between patients with multiple sclerosis (MS) and the healthy population. However, interpreting findings on MS-associated microbiota is challenging, as there is no true consensus. It is unclear whether there is gut microbiota commonly altered in MS across studies. METHODS: To answer this, we performed a meta-analysis based on the 16S rRNA gene sequencing data from seven geographically and technically diverse studies comprising a total of 524 adult subjects (257 MS and 267 healthy controls). Analysis was conducted for each individual study after reprocessing the data and also by combining all data together. The blocked Wilcoxon rank-sum test and linear mixed-effects regression were used to identify differences in microbial composition and diversity between MS and healthy controls. Network analysis was conducted to identify bacterial correlations. A leave-one-out sensitivity analysis was performed to ensure the robustness of the findings. RESULTS: The microbiome community structure was significantly different between studies. Re-analysis of data from individual studies revealed a lower relative abundance of Prevotella in MS across studies, compared to controls. Meta-analysis found that although alpha and beta diversity did not differ between MS and controls, a higher abundance of Actinomyces and a lower abundance of Faecalibacterium were reproducibly associated with MS. Additionally, network analysis revealed that the recognized negative Bacteroides-Prevotella correlation in controls was disrupted in patients with MS. CONCLUSIONS: Our meta-analysis identified common gut microbiota associated with MS across geographically and technically diverse studies.

Gut microbial diversity and functional characterization in people with alcohol use disorder: A case-control study.

Individuals with Alcohol Use Disorder (AUD) typically have comorbid chronic health conditions, including anxiety and depression disorders, increased sleep disruption, and poor nutrition status, along with gut microbial dysbiosis. To better understand the effects of gut dysbiosis previously shown in individuals with AUD, gut microbiome and metabolome were investigated between three cohorts. Two groups of individuals with AUD included treatment-seeking newly abstinent for at least six weeks (AB: N = 10) and non-treatment-seeking currently drinking (CD: N = 9) individuals. The third group was age, gender, and BMI-matched healthy controls (HC: N = 12). Deep phenotyping during two weeks of outpatient National Institutes of Health Clinical Center visits was performed, including clinical, psychological, medical, metabolic, dietary, and experimental assessments. Alpha and beta diversity and differential microbial taxa and metabolite abundance of the gut microbiome were examined across the three groups. Metabolites derived from the lipid super-pathway were identified to be more abundant in the AB group compared to CD and HC groups. The AB individuals appeared to be most clinically different from CD and HC individuals with respect to their gut microbiome and metabolome. These findings highlight the potential long-term effects of chronic alcohol use in individuals with AUD, even during short-term abstinence.

The association between parental warmth and children's prosocial behaviour: A moderated mediation analysis.

Prosocial behaviour is a bedrock of humane societies. Although previous studies have shown that parental style is an important contributing factor for children's prosocial behaviour, the psychological mechanism underlying this association in specific cultural background remains unclear. Based on the ecological systems theory, this study sought to explore the influence of parental warmth on children's prosocial behaviour, and the mediating effect of self-efficacy, as well as the moderating role of teachers' incentive evaluation in the link between self-efficacy and children's prosocial behaviour. This cross-sectional, survey-based study collected data from parents and teachers of 414 Chinese preschoolers (5-6 years old). Parents of these children finished questionnaires on the Chinese version of the short-form Egna minnen av. Barndoms uppfostran (s-EMBU-C), Child Behaviour Scale (CBS), and the revised General Self-efficacy Scale (GSES), while Incentive evaluation questionnaire was finished by their teachers. Results indicated that children who experience high parental warmth were more likely to act prosocially (b = 0.61, p < 0.001) and the association between parental warmth and prosocial behaviour was partially mediated by self-efficacy (indirect effect = 0.25, 95 % CI = [0.19, 0.32]). Besides, teachers' incentive evaluation moderated the link between self-efficacy and children's prosocial behaviour (b = 0.24, p < 0.001). Specifically, the effect of self-efficacy on prosocial behaviour was stronger for high teachers' incentive evaluation children than those with low teachers' incentive evaluation. These findings extend the existing understanding of the mechanism concerning the influence of parental warmth on prosocial behaviour in Chinese settings. The results revealed that interventions that could improve children's self-efficacy would be effective in accelerating their prosocial behaviour and schools played a crucial role in working with families to increase their self-efficacy at a young age. It should be noted that this study focused only on Chinese children of 5-6 years old, and the cross-sectional design means that the possibility of bidirectional effects could not be ruled out.

Impact of metformin on melanoma: a meta-analysis and systematic review.

Background: There is evidence of a modest reduction in skin cancer risk among metformin users. However, no studies have further examined the effects of metformin on melanoma survival and safety outcomes. This study aimed to quantitatively summarize any influence of metformin on the overall survival (OS) and immune-related adverse effects (irAEs) in melanoma patients. Methods: Selection criteria: The inclusion criteria were designed based on the PICOS principles. Information sources: PubMed, EMBASE, Cochrane Library, and Web of Science were searched for relevant literature published from the inception of these databases until November 2023 using 'Melanoma' and 'Metformin' as keywords. Survival outcomes were OS, progression-free survival (PFS), recurrence-free survival (RFS), and mortality; the safety outcome was irAEs. Risk of bias and data Synthesis: The Cochrane tool for assessing the risk of bias in randomized trial 2 (RoB2) and methodological index for non-randomized studies (MINORS) were selected to assess the risk of bias. The Cochrane Q and I 2 statistics based on Stata 15.1 SE were used to test the heterogeneity among all studies. Funnel plot, Egger regression, and Begg tests were used to evaluate publication bias. The leave-one-out method was selected as the sensitivity analysis tool. Results: A total of 12 studies were included, involving 111,036 melanoma patients. The pooled HR for OS was 0.64 (95% CI [0.42, 1.00], p = 0.004, I2 = 73.7%), HR for PFS was 0.89 (95% CI [0.70, 1.12], p = 0.163, I2 = 41.4%), HR for RFS was 0.62 (95% CI [0.26, 1.48], p = 0.085, I2 = 66.3%), and HR for mortality was 0.53 (95% CI [0.46, 0.63], p = 0.775, I2 = 0.0%). There was no significant difference in irAEs incidence (OR = 1.01; 95% CI [0.42, 2.41]; p = 0.642) between metformin and no metformin groups. Discussion: The improvement in overall survival of melanoma patients with metformin may indirectly result from its diverse biological targets and beneficial effects on multiple systemic diseases. While we could not demonstrate a specific improvement in the survival of melanoma patients, the combined benefits and safety of metformin for patients taking the drug are worthy of recognition. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024518182.