An fusaric acid-based CRISPR library screen identifies MDH2 as a broad-spectrum regulator of Fusarium toxin-induced cell death.

Fusarium mycotoxins are of great concern because they are the most common food-borne mycotoxins and environmental contaminants worldwide. Fusaric acid (FA), Deoxynivalenol (DON), Zearalenone (ZEA), T-2 toxin (T-2), and Fumonisin B1 (FB1) are important Fusarium toxins contaminating feeds and food and can cause serious health problems. FA can synergize with some other Fusarium toxins to enhance overall toxicity. However, the underlying molecular mechanism remains poorly understood. In this study, our CRISPR screening revealed Malate dehydrogenase 2 (MDH2) and Pyruvate dehydrogenase E1 subunit beta (PDHB) are the key genes for FA-induced cell death. Pathways associated with mitochondrial function, notably the TCA cycle, play a significant role in FA cytotoxicity. We found that MDH2 and PDHB depletion reduced FA-induced cell death, ROS accumulation, and the expression of caspase-3 and HIF-1α. The cell viability assays and flow cytometry demonstrated that MDH2 knockout but not PDHB decreased DON, ZEA, T-2, and FB1-induced cytotoxicity, apoptosis, and ROS accumulation. MDH2 inhibitor LW6 also decreased DON, ZEA, T-2, and FB1-induced toxicity. This suggested that MDH2, but not PDHB, is a common regulator of broad-spectrum Fusarium toxin (FA, DON, ZEA, T-2, and FB1)-induced cell death. Our work provides new avenues for the treatment of Fusarium toxin toxicity.

Assessment of LINC-PINT genetic polymorphisms and esophageal squamous cell carcinoma risk in the Hainan Han population.

OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high incidence and mortality rates worldwide. This study aimed to investigate the correlation between LINC-PINT polymorphisms and ESCC risk in the Hainan Han population. METHODS: A total of 391 patients with ESCC and 452 healthy controls were enrolled to evaluate the effect of LINC-PINT SNPs (single nucleotide polymorphisms) on ESCC susceptibility. Associations were evaluated by calculating odds ratios (OR) and 95% confidence intervals (CIs). Multifactor dimensionality reduction analysis was performed to explore the association between SNP-SNP interactions and ESCC susceptibility. We further determined the correlation between clinical indicators and SNP in patients with ESCC. RESULTS: Our study showed that rs157916 (OR 0.63, p = 0.011) and rs157928 (OR 0.80, p = 0.021) were associated with a decreased risk of ESCC. Stratified analysis indicated that rs157916 could decrease the risk of ESCC in people aged >64 years, in males, and non-drinkers (OR 0.58, p = 0.042; OR 0.58, p = 0.010; OR 0.62, p = 0.025, respectively). Rs16873842 was related to a decreased risk of ESCC in males (OR 0.70, p = 0.015). Rs7801029 was associated with ESCC risk in females (OR 0.39, p = 0.033) and non-drinkers (OR 0.68, p = 0.040). Rs7781295 decreased the ESCC risk in smokers (OR 0.58, p = 0.046) and drinkers (OR 0.58, p = 0.046). In addition, rs157928 played a protective role in ESCC risk in females (OR 0.39, p = 0.033) and non-smokers (OR 0.32, p = 0.006). Additionally, the best predictive model for ESCC was a combination of rs157916, rs16873842, rs7801029, rs7781295, rs28662387, and rs157928. CONCLUSION: Our study revealed that LINC-PINT polymorphisms were associated with ESCC risk.

A viscoelastic-stochastic model of cell adhesion considering matrix morphology and medium viscoelasticity.

Quantitative investigation of the adhesive behavior between cells and the extracellular matrix (ECM) through molecular bonds is essential for cell culture and bio-medical engineering in vitro. Cell adhesion is a complex multi-scale behavior that includes temporal and spatial scales. However, the influence of the cell and matrix creep effect and the complex spatial morphology characteristics of the matrix on the cell adhesion mechanism is unclear. In the present study, an idealized theoretical model has been considered, where the adhesion of cells and the matrix is simplified into a planar strain problem of homogeneous viscoelastic half-spaces. Furthermore, a new viscoelastic-stochastic model that considers the morphological characteristics of the matrix, the viscoelasticity of the cell and the viscoelasticity of the substrate was developed under the action of a constant external force. The model characterizes the matrix topographical features by fractal dimension (FD), interprets the effects of FD and medium viscoelasticity on the molecular bond force and the receptor-ligand bond re-association rate and reveals a new mechanism for the stable adhesion of molecular bond clusters by Monte Carlo simulation. Based on this model, it was identified that the temporal and spatial distribution of molecular bond force was affected by the matrix FD and the lifetime and stability of the molecular bond cluster could be significantly improved by tuning the FD. At the same time, the viscoelastic creep effect of the cell and matrix increased the re-association rate of open bonds and could expand the window of stable adhesion more flexibly.

Network Medicine Approach Unravels Endophenotype Signature in Alzheimer's Disease through Large-Scale Comparative Proteomics Analysis: Vascular Dysfunction as a Prime Example.

Alzheimer's disease (AD) is the most common neurodegenerative disease burdening public health. We proposed a network-based infrastructure to identify protein signatures for five AD pathological endophenotypes: amyloidosis, tauopathy, vascular dysfunction, lysosomal dysfunction, and neuroinflammation. We analyzed 23 proteomic data sets from AD patients and transgenic mouse models, using network proximity to measure associations between endophenotype modules and differentially expressed proteins (DEPs) in the integrated AD proteome. We focused on the vascular dysfunction signature with 21 DEPs by integrating RNA-seq, single-cell transcriptomics, GWAS, and literature. Experiments on APP/PS1 and MCAO models highlighted three proteins (SEPT5, SNAP25, STXBP1) as novel AD biomarker candidates. This study demonstrates a network medicine framework for deciphering endophenotype signatures in AD.

Light-Activated In Situ Vaccine with Enhanced Cytotoxic T Lymphocyte Infiltration and Function for Potent Cancer Immunotherapy.

In situ cancer vaccination is an attractive strategy that stimulates protective antitumor immunity. Cytotoxic T lymphocytes (CTLs) are major mediators of the adaptive immune defenses, with critical roles in antitumor immune response and establishing immune memory, and are consequently extremely important for in situ vaccines to generate systemic and lasting antitumor efficacy. However, the dense extracellular matrix and hypoxia in solid tumors severely impede the infiltration and function of CTLs, ultimately compromising the efficacy of in situ cancer vaccines. To address this issue, a robust in situ cancer vaccine, Au@MnO2 nanoparticles (AMOPs), based on a gold nanoparticle core coated with a manganese dioxide shell is developed. The AMOPs modulated the unfavorable tumor microenvironment (TME) to restore CTLs infiltration and function and efficiently induced immunogenic cell death. The Mn2+-mediated stimulator of the interferon genes pathway can be activated to further augment the therapeutic efficacy of the AMOPs. Thus, the AMOPs vaccine successfully elicited long-lasting antitumor immunity to considerably inhibit primary, recurrent, and metastatic tumors. This study not only highlights the importance of revitalizing CTLs efficacy against solid tumors but also makes progress toward overcoming TME barriers for sustained antitumor immunity.

The Association Between Triglyceride-Glucose Index and Its Combination with Obesity Indicators and Lower Extremity Peripheral Artery Disease in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

Background: Lower extremity peripheral artery disease (LEAD) is a significant chronic complication of type 2 diabetes mellitus (T2DM) that significantly contributes to disability and mortality. The subtle presentation of LEAD symptoms often leads to underrecognition and misdiagnosis. Therefore, identifying simple and effective evaluation indicators is essential for the early detection and management of LEAD. Insulin resistance is closely associated with diabetes and its complications. However, the specific relationship between insulin resistance-measured by the triglyceride-glucose (TyG) index-and obesity indicators in relation to LEAD remains unclear. Objective: This study aims to investigate the association between the TyG index and its combination with obesity indicators in participants with T2DM and LEAD. Methods: We performed a univariate analysis on 3176 T2DM patients to identify risk factors for LEAD. Patients were then divided into quartiles based on the TyG index combined with various obesity indicators. The chi-square test was used to compare the prevalence of LEAD across these groups. Logistic regression analysis was conducted to examine the association between the TyG index, in combination with different obesity indicators, and the occurrence of LEAD. Finally, we assessed the predictive ability of the TyG index combined with obesity indicators for LEAD by comparing the area under the ROC curve (AUC). Results: The study included 3176 T2DM patients (1691 males and 1485 females) with a mean age of 56.16±10.60 years. Among them, 106 individuals had LEAD. The prevalence of LEAD varied significantly across quartiles of the TyG index, TyG-WC, and TyG-WHR (Q4 > Q3 > Q2 > Q1; P < 0.05). Multiple logistic regression analysis showed that the TyG index, TyG-WC, and TyG-WHR were positively associated with the risk of LEAD in T2DM patients. ROC curve analysis identified the best cutoff values for predicting LEAD: 9.8059 for the TyG index (sensitivity: 49.1%, specificity: 67.9%, AUC: 0.583), 808.8397 for TyG-WC (sensitivity: 70.8%, specificity: 47.8%, AUC: 0.603), and 8.8543 for TyG-WHR (sensitivity: 75.5%, specificity: 44.6%, AUC: 0.607). Conclusion: In T2DM patients, the TyG index, TyG-WHR, and TyG-WC are positively associated with the occurrence of LEAD. TyG-WHR and TyG-WC exhibit a stronger correlation with LEAD compared to the TyG index alone, indicating their superior diagnostic value.

Integrative Analysis of the Microbiome and Metabolome of Broiler Intestine: Insights into the Mechanisms of Probiotic Action as an Antibiotic Substitute.

Antibiotic substitutes have become a research focus due to restrictions on antibiotic usage. Among the antibiotic substitutes on the market, probiotics have been extensively researched and used. However, the mechanism by which probiotics replace antibiotics remains unclear. In this study, we aimed to investigate this mechanism by comparing the effects of probiotics and antibiotics on broiler growth performance and intestinal microbiota composition. Results shown that both probiotics and antibiotics increased daily weight gain and reduced feed conversion rate in broilers. Analysis of ileum and cecum microorganisms via 16S rRNA gene sequencing revealed that both interventions decreased intestinal microbial diversity. Moreover, the abundance of Bacteroides increased in the mature ileum, while that of Erysipelatoclostridium decreased in the cecum in response to both probiotics and antibiotics. The main metabolites of probiotics and antibiotics in the intestine were found to be organic acids, amino acids, and sugars, which might play comparable roles in growth performance. Furthermore, disaccharides and trisaccharides may be essential components in the ileum that enable probiotics to replace antibiotics. These findings provide important insights into the mechanisms underlying the use of probiotics as antibiotic substitutes in broiler breeding.

Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sepsis in the pediatric intensive care unit (PICU). STUDY DESIGN: This retrospective observational study was conducted in the PICUs of the First Affiliated Hospital of Sun Yat-sen University from December 2016 to June 2019 and Shenzhen Children's Hospital from January 2019 to July 2020. The children were divided into a death group and a survival group. Different machine language (ML) models were used to predict the risk of death in children with sepsis. RESULTS: A total of 671 children with sepsis were enrolled. The accuracy (ACC) of the artificial neural network model was better than that of support vector machine, logical regression analysis, Bayesian, K nearest neighbor method and decision tree models, with a training set ACC of 0.99 and a test set ACC of 0.96. CONCLUSIONS: The AI model can be used to predict the risk of death due to sepsis in children in the PICU, and the artificial neural network model is better than other AI models in predicting mortality risk.

A taurine-based hydrogel with the neuroprotective effect and the ability to promote neural stem cell proliferation.

Ischemic stroke, a cerebrovascular disease caused by arterial occlusion in the brain, can lead to brain impairment and even death. Stem cell therapies have shown positive advantages to treat ischemic stroke because of their extended time window, but the cell viability is poor when transplanted into the brain directly. Therefore, a new hydrogel GelMA-T was developed by introducing taurine on GelMA to transplant neural stem cells. The GelMA-T displayed the desired photocuring ability, micropore structure, and cytocompatibility. Its compressive modulus was more similar to neural tissue compared to that of GelMA. The GelMA-T could protect SH-SY5Y cells from injury induced by OGD/R. Furthermore, the NE-4C cells showed better proliferation performance in GelMA-T than that in GelMA during both 2D and 3D cultures. All results demonstrate that GelMA-T possesses a neuroprotective effect for ischemia/reperfusion injury against ischemic stroke and plays a positive role in promoting NSC proliferation. The novel hydrogel is anticipated to function as cell vehicles for the transplantation of neural stem cells into the stroke cavity, aiming to treat ischemic stroke.

Bushenhuoluo Decoction improves polycystic ovary syndrome by regulating exosomal miR-30a-5p/ SOCS3/mTOR/NLRP3 signaling-mediated autophagy and pyroptosis.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a frequent and complicated endocrine disease that remains a major reason for infertility. Bushenhuoluo Decotion (BSHLD) has been validated to exhibit curative effects on PCOS. This study was aimed to explore the potential mechanism underlying the therapeutic action of BSHLD. METHODS: PCOS rat model was induced by dehydroepiandrosterone (DHEA). Serum hormone and cytokines levels and ovarian pathological alterations were measured to assess ovarian function. Exosomes (Exos) were identified by Transmission electron microscopy and Nanoparticle Tracking Analysis. RT-qPCR, Western blotting, immunohistochemical staining, and immunofluorescence staining were performed to detect molecule expressions. Proliferation and pyroptosis of granulosa cells (GCs) were evaluated by CCK-8 and flow cytometry, respectively. The binding relationship between miR-30a-5p and suppressor of cytokine signaling 3 (SOCS3) was verified by dual luciferase reporter and RIP assays. RESULTS: BSHLD treatment improved serum hormone abnormality, insulin sensitivity, and ovarian morphologic changes of PCOS rats. Moreover, BSHLD treatment restrained the excessive autophagy and pyroptosis in ovarian tissues of PCOS rats. Moreover, BSHLD reduced the expression of miR-30a-5p in serum, serum-derived Exos, and ovarian tissues, thus inhibiting autophagy and NLRP3-mediated pyroptosis in GCs. Mechanistically, SOCS3 was proved as a target of miR-30a-5p and could activate mTOR/P70S6K pathway to repress autophagy. The inhibitory effect of miR-30a-5p deficiency on autophagy and pyroptosis of GCs was attenuated by rapamycin. CONCLUSION: Collectively, BSHLD suppressed autophagy and pyroptosis to improve POCS by regulating exosomal miR-30a-5p/SOCS3/mTOR signaling.

YTHDF2-mediated circYAP1 drives immune escape and cancer progression through activating YAP1/TCF4-PD-L1 axis.

Immune escape is identified as one of the reasons for the poor prognosis of colorectal cancer (CRC) patients. Circular RNAs are considered to promote tumor progression by mediating tumor immune escape. We discovered that higher expression of circYAP1 was associated with a worse prognosis of CRC patients. Functional experiments in vitro and in vivo showed that circYAP1 upregulation inhibited the cytotoxicity of CD8+ T cells by upregulating programmed death ligand-1 (PD-L1). Mechanistically, we found that circYAP1 directly binds to the YAP1 protein to prevent its phosphorylation, enhancing proportion of YAP1 protein in the nucleus, and that YAP1 interacts with TCF4 to target the PD-L1 promoter and initiate PD-L1 transcription in CRC cells. Taken together, circYAP1 promotes CRC immune escape and tumor progression by activating the YAP1/TCF4-PD-L1 axis and may provide a new strategy for combination immunotherapy of CRC patients.

MPDZ is associated with immune infiltration and regulates migration and invasion by switching YAP1 phosphorylation in colorectal cancer.

BACKGROUND: Multiple PDZ Domain Crumbs Cell Polarity Complex Component (MPDZ) is involved in a few human cancers. However, the features and potential mechanisms of MPDZ in progression of colorectal cancer (CRC) remains unknown. METHODS: The prognostic role of MPDZ in CRC was determined by Kaplan-Meier and univariate regression analysis. Enrichment analysis was performed to characterize crucial pathways of MPDZ. Immune infiltration and immunotherapeutic outcome were further evaluated. CCK8, EDU, transwell, and wound healing assay were used to assess the influence of MPDZ on pernicious performance of CRC cells. CD8+ T cells and CRC cells were co-cultured to explore the effect of MPDZ on the tumor microenvironment. qRT-PCR, western blot, immunoprecipitation (IP), and methylated RNA immunoprecipitation (me-RIP) were implemented in seeking for the potential mechanisms of MPDZ in CRC. RESULTS: CRC patients with elevated MPDZ expression suffered from significantly worse prognosis. Enrichment analysis revealed that MPDZ involved in pathways related to metastasis and cell cycle in CRC. In addition, MPDZ expression were related to several immunoinhibitors and had the ability to predict immunotherapy response. Finally, in vitro assays demonstrated that MPDZ knockdown inhibited migration, invasion and immune evasion of CRC cells. Mechanistically, MPDZ knockdown enhanced YAP1 phosphorylation by increased LATS1 expression. Moreover, m6A-MPDZ mRNA may be recognized and degraded by m6A recognition protein YTHDF2. CONCLUSIONS: MPDZ was critical for CRC development and could be a promising candidate for the treatment of CRC patients.

PTPN13 rs989902 and CHEK2 rs738722 are associated with esophageal cancer.

PURPOSE: Individual genetic background can play an essential role in determining the development of esophageal squamous cell carcinoma (ESCC). PTPN13 and CHEK2 play important roles in the pathogenesis of ESCC. This case-control study aimed to analyze the association between gene polymorphisms and ESCC susceptibility. METHODS: DNA was extracted from the peripheral blood of patients. The Agena MassARRAY platform was used for the genotyping. Statistical analysis was conducted using the chi-squared test or Fisher's exact test, logistic regression analysis, and stratification analysis. RESULTS: The 'G' allele of rs989902 (PTPN13) and the 'T' allele of rs738722 (CHEK2) were both associated with an increased risk of ESCC (rs989902: OR = 1.23, 95% CI = 1.02-1.47, p = 0.028; rs738722: OR = 1.28, 95% CI = 1.06-1.55, p = 0.011). Stratification analysis showed that SNPs (rs989902 and rs738722) were notably correlated with an increased risk of ESCC after stratification for age, sex, smoking, and drinking status. In addition, rs738722 might be associated with lower stage, while rs989902 had a lower risk of metastasis. CONCLUSION: Our findings display that PTPN13 rs989902 and CHEK2 rs738722 are associated with an increased risk of ESCC in the Chinese Han population.

Meta-Analysis of Functional Electrical Stimulation Combined with Occupational Therapy on Post-Stroke Limb Functional Recovery and Quality of Life.

OBJECTIVE: This study aimed to investigate whether Functional Electrical Stimulation (FES) and Transcranial Direct Current Stimulation (tDCS) enhanced the effect of Occupational Therapy (OT) on post-stroke limb functional recovery and quality of life, using direct and network meta-analysis. METHODS: A computerized search was conducted in databases such as Medline, Web of Science, Embase, CNKI (China National Knowledge Infrastructure), Wanfang Data, and VIP Information for prospective randomized controlled trials on OT, FES, and tDCS for improving post-stroke limb motor function and quality of life, with the search cutoff date of July 1, 2023. RESULTS: Following the screening process, a total of 8 research articles were incorporated, encompassing 358 participants. Among these, 177 individuals underwent OT exclusively, while 181 individuals underwent a combined regimen of OT alongside electromagnetic therapy. In terms of the intervention methods, the control group received OT treatment only, while the experimental group employed tDCS in 5 studies and FES in 3 studies. Within these investigations, Fugl-Meyer Assessment (FMA) scores were reported in 8 studies. The aggregated mean difference (MD) for FMA scores was 5.08 (95% CI: 2.46, 7.71), with a specific MD of 2.77 (95% CI: 1.46, 4.09) for the tDCS subgroup and 9.04 (95% CI: 5.34, 12.73) for the FES subgroup. Notably, FES combined with OT exhibited significant advantages in enhancing FMA scores when compared to the combination of tDCS and OT. Furthermore, four studies provided data on modified Barthel Index (MBI) scores, yielding a collective MD of 7.20 (95% CI: 4.44, 9.95). CONCLUSION: In patients with stroke, both FES combined with OT and tDCS combined with OT exhibit substantial enhancements in limb function and quality of life compared to OT alone. Notably, FES combined with OT yields superior clinical benefits when compared to the amalgamation of tDCS and OT.

scPML: pathway-based multi-view learning for cell type annotation from single-cell RNA-seq data.

Recent developments in single-cell technology have enabled the exploration of cellular heterogeneity at an unprecedented level, providing invaluable insights into various fields, including medicine and disease research. Cell type annotation is an essential step in its omics research. The mainstream approach is to utilize well-annotated single-cell data to supervised learning for cell type annotation of new singlecell data. However, existing methods lack good generalization and robustness in cell annotation tasks, partially due to difficulties in dealing with technical differences between datasets, as well as not considering the heterogeneous associations of genes in regulatory mechanism levels. Here, we propose the scPML model, which utilizes various gene signaling pathway data to partition the genetic features of cells, thus characterizing different interaction maps between cells. Extensive experiments demonstrate that scPML performs better in cell type annotation and detection of unknown cell types from different species, platforms, and tissues.

Association study for the role of MMP8 gene polymorphisms in Colorectal cancer susceptibility.

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignant tumors, influenced by several genetic loci in its clinical phenotypes. The aim of this study was to determine the relationship between the MMP8 gene polymorphism and CRC risk in the Chinese Han population. METHOD: This study recruited 688 CRC patients and 690 healthy controls. The relationship between MMP8 polymorphism and CRC susceptibility was assessed by calculating the odds ratio (OR) and 95% confidence interval (CI) after stratifying by age, gender, body mass index (BMI), smoking, and alcohol consumption under a multi-genetic model. RESULTS: MMP8 rs3740938 was associated with increased CRC predisposition (p = 0.016, OR = 1.24, 95% CI: 1.04-1.48), and this association was detected particularly in subjects aged > 60 years, females, people with BMI > 24 kg/m2, smokers, and drinkers. Moreover, rs3740938 was found to be associated with the pathological type of rectal cancer. CONCLUSIONS: Our results first displayed that rs3740938 in MMP8 was a risk factor for CRC predisposition. This finding may provide a new biological perspective for understanding the role of the MMP8 gene in CRC pathogenesis.

The STING-IRF3 Signaling Pathway, Mediated by Endoplasmic Reticulum Stress, Contributes to Impaired Myocardial Autophagic Flux After Ischemia/Reperfusion.

ABSTRACT: This study aimed to determine whether endoplasmic reticulum (ER) stress is involved in impaired autophagy after myocardial ischemia/reperfusion (M-I/R) and elucidate the underlying mechanisms. The expression levels of stimulator of interferon gene (STING) and interferon regulatory transcription factor 3 (IRF3) phosphorylation increased in M-I/R heart tissues and hypoxia-treated/reoxygenation-treated H9c2 cells. The ER stress inhibitor 4-phenylbutyric acid (4-PBA) significantly suppressed the stimulation of STING-IRF3 transcription and alleviated cardiac dysfunction caused by M-I/R injury. In addition, 4-PBA reversed ischemia-induced/reperfusion-induced autophagic flux dysfunction, as demonstrated by a decrease in p 62 and LC3 levels. Similarly, the protective effect of STING deficiency on myocardial cell damage was achieved by the recovery of autophagic flux. Conversely, the protective effect of 4-PBA against hypoxia/reoxygenation injury in cardiomyocytes was offset by STING overexpression, wherein the activated STING-IRF3 pathway promoted the expression of Rubicon (a negatively-regulated autophagic molecule) by binding to the Rubicon promoter. Rubicon ablation effectively counteracts the adverse effects of STING overexpression in cardiomyocytes. The data showed that STING-IRF3 signaling of ER stress receptors is particularly important in the progression of physiological M-I/R caused by the inhibition of autophagic flow in vivo and in vitro.

The Value of Applying Machine Learning in Predicting the Time of Symptom Onset in Stroke Patients: Systematic Review and Meta-Analysis.

BACKGROUND: Machine learning is a potentially effective method for identifying and predicting the time of the onset of stroke. However, the value of applying machine learning in this field remains controversial and debatable. OBJECTIVE: We aimed to assess the value of applying machine learning in predicting the time of stroke onset. METHODS: PubMed, Web of Science, Embase, and Cochrane were comprehensively searched. The C index and sensitivity with 95% CI were used as effect sizes. The risk of bias was evaluated using PROBAST (Prediction Model Risk of Bias Assessment Tool), and meta-analysis was conducted using R (version 4.2.0; R Core Team). RESULTS: Thirteen eligible studies were included in the meta-analysis involving 55 machine learning models with 41 models in the training set and 14 in the validation set. The overall C index was 0.800 (95% CI 0.773-0.826) in the training set and 0.781 (95% CI 0.709-0.852) in the validation set. The sensitivity and specificity were 0.76 (95% CI 0.73-0.80) and 0.79 (95% CI 0.74-0.82) in the training set and 0.81 (95% CI 0.68-0.90) and 0.83 (95% CI 0.73-0.89) in the validation set, respectively. Subgroup analysis revealed that the accuracy of machine learning in predicting the time of stroke onset within 4.5 hours was optimal (training: 0.80, 95% CI 0.77-0.83; validation: 0.79, 95% CI 0.71-0.86). CONCLUSIONS: Machine learning has ideal performance in identifying the time of stroke onset. More reasonable image segmentation and texture extraction methods in radiomics should be used to promote the value of applying machine learning in diverse ethnic backgrounds. TRIAL REGISTRATION: PROSPERO CRD42022358898; https://www.crd.york.ac.uk/Prospero/display_record.php?RecordID=358898.

The acetylation of pknH is linked to the ethambutol resistance of Mycobacterium tuberculosis.

EmbR, a substrate of pknH in Mycobacterium tuberculosis (Mtb), is related to the ethambutol (EMB) resistance. This study aimed to investigate the relationship between acetylation of pknH and the resistance of EMB mono-resistant Mtb. The EMB mono-resistant Mtb strain was constructed based on the MYCOTB and the Löwenstein-Jensen (LJ) proportion method. The growth kinetics was used to evaluate the bacterial growth. Escherichia coli, as the host of Mtb, was used for cloning and protein purification. Moreover, the immunoprecipitation was performed along with western blot to evaluate the EmbR phosphorylation and pknH acetylation. Each independent experiment was conducted in triplicate. EMB mono-resistant Mtb strain was successfully constructed according to the results of MIC values of 14 anti-Mtb drugs. The EMB resistant (ER) Mtb strain showed faster growth than the wild-type (WT) Mtb strain, and the difference was statistically significant. Moreover, pknH robustly phosphorylates EmbR, and pknH and acetylated pknH protein levels were downregulated in ER strain. The acetylation of pknH may reduce the phosphorylation of EmbR to inhibit the growth of Mtb strain. Enhancing the acetylation of pknH may be a promising method to inhibit the EMB resistance against Mtb.

Enhancing Offensive Language Detection with Data Augmentation and Knowledge Distillation.

Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms, as well as promoting the safe deployment of large language models. Training data is the basis for developing detectors; however, the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English resources. This significantly affects the accuracy of Chinese offensive language detectors in practical applications, especially when dealing with hard cases or out-of-domain samples. To alleviate the limitations posed by available datasets, we introduce AugCOLD (Augmented Chinese Offensive Language Dataset), a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model generation. Furthermore, we employ a multiteacher distillation framework to enhance detection performance with unsupervised data. That is, we build multiple teachers with publicly accessible datasets and use them to assign soft labels to AugCOLD. The soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network, i.e., the final offensive detector. We conduct experiments on multiple public test sets and our well-designed hard tests, demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.