Detrimental Role of CXCR3 in α-Naphthylisothiocyanate- and Triptolide-Induced Cholestatic Liver Injury.

The chemokine receptor CXCR3 is functionally pleiotropic, not only recruiting immune cells to the inflamed liver but also mediating the pathological process of cholestatic liver injury (CLI). However, the mechanism of its involvement in the CLI remains unclear. Both alpha-naphthylisothiocyanate (ANIT) and triptolide are hepatotoxicants that induce CLI by bile acid (BA) dysregulation, inflammation, and endoplasmic reticulum (ER)/oxidative stress. Through molecular docking, CXCR3 is a potential target of ANIT and triptolide. Therefore, this study aimed to investigate the role of CXCR3 in ANIT- and triptolide-induced CLI and to explore the underlying mechanisms. Wild-type mice and CXCR3-deficient mice were administered with ANIT or triptolide to compare CLI, BA profile, hepatic recruitment of IFN-γ/IL-4/IL-17+CD4+T cells, IFN-γ/IL-4/IL-17+iNKT cells and IFN-γ/IL-4+NK cells, and the expression of ER/oxidative stress pathway. The results showed that CXCR3 deficiency ameliorated ANIT- and triptolide-induced CLI. CXCR3 deficiency alleviated ANIT-induced dysregulated BA metabolism, which decreased the recruitment of IFN-γ+NK cells and IL-4+NK cells to the liver and inhibited ER stress. After triptolide administration, CXCR3 deficiency ameliorated dysregulation of BA metabolism, which reduced the migration of IL-4+iNKT cells and IL-17+iNKT cells and reduced oxidative stress through inhibition of Egr1 expression and AKT phosphorylation. Our findings suggest a detrimental role of CXCR3 in ANIT- and triptolide-induced CLI, providing a promising therapeutic target and introducing novel mechanisms for understanding cholestatic liver diseases.

Application of Entity-BERT model based on neuroscience and brain-like cognition in electronic medical record entity recognition.

Introduction: In the medical field, electronic medical records contain a large amount of textual information, and the unstructured nature of this information makes data extraction and analysis challenging. Therefore, automatic extraction of entity information from electronic medical records has become a significant issue in the healthcare domain. Methods: To address this problem, this paper proposes a deep learning-based entity information extraction model called Entity-BERT. The model aims to leverage the powerful feature extraction capabilities of deep learning and the pre-training language representation learning of BERT(Bidirectional Encoder Representations from Transformers), enabling it to automatically learn and recognize various entity types in medical electronic records, including medical terminologies, disease names, drug information, and more, providing more effective support for medical research and clinical practices. The Entity-BERT model utilizes a multi-layer neural network and cross-attention mechanism to process and fuse information at different levels and types, resembling the hierarchical and distributed processing of the human brain. Additionally, the model employs pre-trained language and sequence models to process and learn textual data, sharing similarities with the language processing and semantic understanding of the human brain. Furthermore, the Entity-BERT model can capture contextual information and long-term dependencies, combining the cross-attention mechanism to handle the complex and diverse language expressions in electronic medical records, resembling the information processing method of the human brain in many aspects. Additionally, exploring how to utilize competitive learning, adaptive regulation, and synaptic plasticity to optimize the model's prediction results, automatically adjust its parameters, and achieve adaptive learning and dynamic adjustments from the perspective of neuroscience and brain-like cognition is of interest. Results and discussion: Experimental results demonstrate that the Entity-BERT model achieves outstanding performance in entity recognition tasks within electronic medical records, surpassing other existing entity recognition models. This research not only provides more efficient and accurate natural language processing technology for the medical and health field but also introduces new ideas and directions for the design and optimization of deep learning models.

Dual-Atom Catalysts Derived from a Preorganized Covalent Organic Framework for Enhanced Electrochemical Oxygen Reduction.

Dual-atom catalysts (DAC) are deemed as promising electrocatalysts due to the abundant active sites and adjustable electronic structure, but the fabrication of well-defined DAC is still full of challenges. Herein, bonded Fe dual-atom catalysts (Fe2 DAC) with Fe2 N6 C8 O2 configuration were developed through one-step carbonization of a preorganized covalent organic framework with bimetallic Fe chelation sites (Fe2 COF). The transition from Fe2 COF to Fe2 DAC involved the dissociation of the nanoparticles and the capture of atoms by carbon defects. Benefitting from the optimized d-band center and enhanced adsorption of OOH* intermediates, Fe2 DAC exhibited outstanding oxygen reduction activity with a half-wave potential of 0.898 V vs. RHE. This work will guide more fabrication of dual-atom and even cluster catalysts from preorganized COF in the future.

An affordable approach to classifying type 2 diabetes based on fasting plasma glucose, TyG index and BMI: a retrospective cohort study of NHANES Data from 1988 to 2014.

BACKGROUND: The ß-cell function and insulin resistance required by existing methods of classifying type 2 diabetes are not routinely adopted in most medical institutions of developing countries and regions. This study aims to propose a novel, affordable classification approach and evaluate its predictive ability for several health and mortality outcomes, including cardiovascular health (CVH), retinopathy, chronic kidney disease (CKD), nonalcoholic fatty liver disease (NAFLD), advanced liver fibrosis, and mortality caused by all-cause, cardiovascular disease (CVD), cancer. METHODS: Based on 4060 participants with diabetes (aged ≥ 30 at the time of diagnosis) selected from the National Health and Nutrition Examination Survey III & 1999-2014, we proposed a novel, but simple classification approach based on the threshold of fasting plasma glucose (FPG), triglyceride-glucose (TyG) index and body mass index (BMI). We used logistic regression model to assess its predictability for diabetes complications, and Cox regression model to estimate the mortality risks. RESULTS: By utilizing this approach, we characterized the subjects into four subgroups: subgroup A (obesity-related), which accounts for 37% of the total, subgroup B (age-related), 38%, subgroup C (insulin resistance), 20%, and subgroup D (severe insulin deficiency), 5%. Subjects in subgroup D had a higher risk of retinopathy, in subgroup B had a lower risk of poor cardiovascular health, nonalcoholic fatty liver disease, and advanced liver fibrosis, in subgroup C had a higher risk of all-cause mortality. CONCLUSIONS: This study proposes an affordable and practical method for classifying patients with type 2 diabetes into different subgroups, with a view to yield a high predictability of patient outcomes and to assist clinicians in providing better treatment.

Validation of type 2 diabetes subgroups by simple clinical parameters: a retrospective cohort study of NHANES data from 1999 to 2014.

OBJECTIVES: To verify whether a simplified method based on age, body mass index (BMI) and glycated haemoglobin (HbA1c) is feasible in classifying patients with type 2 diabetes (T2D), and evaluate the predictive ability of subgroups in several health and mortality outcomes. DESIGN: Retrospective cohort study. SETTING: The National Health and Nutrition Examination Survey 1999-2014 cycle. PARTICIPANTS: A total of 1960 participants with diabetes and the age at diagnosis greater than 30. PRIMARY AND SECONDARY OUTCOME MEASURES: Participants with T2D were assigned to previously defined (by Ahlqvist) subgroups based on five variables: age, BMI, HbA1c, homoeostasis model assessment (HOMA) 2 estimates of ß-cell function (HOMA2-B), and insulin resistance (HOMA2-IR), and on three variables: age, BMI and HbA1c. The classification performances of the three variables were evaluated based on 10-fold cross validation, with accuracy, precision and recall as evaluation criteria. Outcomes were assessed using logistic regression and Cox regression analysis. RESULTS: Without HOMA measurements, it is difficult to identify severe insulin-resistant diabetes, but other subgroups can be ideally identified. There is no significant difference between the five variables and the three variables in the ability to predict the prevalence of poor cardiovascular health (CVH), chronic kidney disease, non-alcoholic fatty liver disease and advanced liver fibrosis, and the risk of all-cause, cardiovascular disease and cancer-related mortality (p>0.05), except the prevalence of poor CVH in mild age-related diabetes (p<0.05). CONCLUSIONS: A simple classification based on age, BMI and HbA1c could be used to identify T2D with several health and mortality risks, which is accessible in most individuals with T2D. Due to its simplicity and practicality, more patients with T2D can benefit from subgroup specific treatment paradigms.

2D Salphen-based heteropore covalent organic frameworks for highly efficient electrocatalytic water oxidation.

The construction of heteroporous covalent organic frameworks (COFs) is still a challenge. Herein, a series of 2D COFs with hexagonal and quadrilateral pores were constructed via in situ salphen or metal salphen formation. Metallized salphen-based COFs can be used as electrocatalysts towards water oxidation with an overpotential of 266 mV at 10 mA cm-2.

Overview of systematic evaluation of efficacy of Tongxie Yaofang in treating diarrhea-predominant irritable bowel syndrome.

BACKGROUND: Tongxie Yaofang is commonly used in the treatment of IBS-D. Many systematic reviews have confirmed its efficacy and safety, but the methodology and quality of evidence need to be further evaluated. METHODS: The databases of Chinese National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature (CBM), Wanfang, VIP, Web of Science (SCI), PubMed, Cochrane Library, and Embase were searched to gather systematic evaluations of TXYF in treating IBS-D. The search time was from inception to January 2021. The search was performed independently by 2 researchers who screened the literature and extracted data. Methodological quality of the studies included in the systematic evaluation was evaluated by the A MeaSurement Tool to Assess systematic Reviews-2 (AMSTAR-2) scale. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) system was used to categorize the evidence quality of outcome indicators, and the curative effect evaluation was summarized. RESLUTS: A total of 10 systematic evaluations were included, and the results of AMSTAR-2 evaluation showed that 6 reports were relatively complete, 4 reports were poor, and the overall quality was not high. DISCUSSION: It was revealed that TXYF can improve the total clinical effective rate and symptoms of patients with IBS-D, but the GRADE evaluation results showed that the quality of evidence was low to extremely low. It is suggested that further high-quality clinical research should be conducted to provide more reliable evidence-based medical evidence for the application of TXYF in the treatment of irritable bowel syndrome.

RP11-323N12.5 promotes the malignancy and immunosuppression of human gastric cancer by increasing YAP1 transcription.

BACKGROUND: YAP1 is a core protein of the Hippo signaling pathway and is associated with malignancy and immunosuppression. In the present study, we discovered a novel lncRNA, RP11-323N12.5, with tumor promotion and immunosuppression activities through enhancing transcription of YAP1. METHODS: RP11-323N12.5 was identified using GEPIA. Its expression levels and their relationship with clinical features were investigated using clinical samples. The regulation of YAP1 transcription by RP11-323N12.5 was investigated in both GC and T cells, the tumor and immunosuppression promotion roles of RP11-323N12.5 were explored in vitro and in vivo. RESULTS: RP11-323N12.5 was the most up-regulated lncRNA in human GC, based on data from the TCGA database. Its transcription was significantly positively correlated with YAP1 transcription, YAP1 downstream gene expression which contribute to tumor growth and immunosuppression. RP11-323N12.5 promoted YAP1 transcription by binding to c-MYC in the YAP1 promoter region. Meanwhile, transcription of RP11-323N12.5 was also regulated by YAP1/TAZ/TEADs activation in GC cells. RP11-323N12.5 had tumor- and immnosuppression-promoting effects by enhancing YAP1 downstream genes in GC cells. Excessive RP11-323N12.5 was also observed in tumor-infiltrating leukocytes (TILs), which may be exosome-derived and also be related to enhanced Treg differentiation as a result YAP1 up-regulation. Moreover, RP11-323N12.5 promoted tumor growth and immunosuppression via YAP1 up-regulation in vivo. CONCLUSIONS: RP11-323N12.5 was the most up-regulated lncRNA in human GC and it promoted YAP1 transcription by binding to c-MYC within the YAP1 promoter in both GC and T cells. RP11-323N12.5 is an ideal therapeutic target in human GC due to its tumor-promoting and immunosuppression characteristics.

STAT3 activation regulated circ-STAT3.46 promote expression of IGF1R by sponging of miR-139-5p in human colon cancer.

BACKGROUND: Recently the roles of circRNAs were extensively studied within human malignancies. Now we explored a potential regulatory axis consisted of circ-STAT3.46-miR-139-5p-IGF1R in human colon cancer. METHODS: The expression of circ-STAT3.46-miR-139-5p-IGF1R were determined by using real-time PCR in human colon cancer (n=56) and adjacent normal tissues. The relationship between clinical characters and tissue or serum exosome circ-STAT3.46 were studied. The detailed regulation within circ-STAT3.46-miR-139-5p-IGF1R was verified by in vitro studies. RESULTS: Aberrant expression of circ-STAT3.46, miR-139-5p, and IGF1R were spotted between colon cancer tissues and control. A significantly negative correlation between circ-STAT3.46 and miR-139-5p were verified within human colon cancer tissues. Expression of circ-STAT3.46 in colon cancer tissue and serum exosome were associated with TMN stage and bad prognosis of post-surgery colon cancer patients. IGF1R was positively correlated to circ-STAT3.46 in human colon cancer tissues. Moreover, the transcription of circ-STAT3.46 was regulated by IGF1/IGF1R/STAT3 signaling. Overexpression of circ-STAT3.46 can decrease miR-139-5p in colon cancer cells, meanwhile, increased miR-139-5p were found in circ-STAT3.46 knockdown cells. RNA pull-down assay revealed that circ-STAT3.46 could sponge miR-139-5p, and luciferase reporter assay indicated that miR-139-5p could further downregulate IGF1R transcription by binding to its 3'UTR in human colon cancer cells. CONCLUSIONS: circ-STAT3.46 was regulated by IGF/IGF1R/STAT3 activation, and overexpression of circ-STAT3.46 can up-regulate IGF1R by sponging of miR-139-5p within human colon cancer.

SNP rs3202538 in 3'UTR region of ErbB3 regulated by miR-204 and miR-211 promote gastric cancer development in Chinese population.

BACKGROUND/AIMS: ErbB3 is an oncogene which has proliferation and metastasis promotion effects by several signaling pathways. However, the individual expression difference regulated by miRNA was almost still unknown. We focused on the miRNAs associated SNPs in the 3'-UTR of ErbB3 to investigate the further relationship of the SNPs with miRNAs among Chinese gastric cancer (GC) patients. METHODS: We performed case-control study including 851 GC patients and 799 cancer-free controls. Genotyping, real-time PCR assay, cell transfection, the dual luciferase reporter assay, western-blot, cell proliferation and trans-well based cell invasion assay were used to investigate the effects of the SNP on ErbB3 expression. Moreover, a 5-years-overall survival and relapse free survival were investigated between different genotypes. RESULTS: We found that patients suffering from Helicobacter pylori (Hp.) infection indicated to be the susceptible population by comparing with controls. Besides, SNP rs3202538 (G/T) in ErbB3 3'-UTR was involved in the occurrence of GC by acting as tumor risk factors. SNP rs3202538 (G/T) could be regulated by both miR-204 and miR-211 which caused an upregulation of ErbB3 in patients. Furthermore, the carriers of T genotype was related to the significantly high expression of ErbB3, and to big tumor size, poor differentiation as well as the high probability of metastasis. Both miR-211 and miR-204 can significantly decrease cell proliferation, metastasis as well as downstream AKT activation through G but not T allele of ErbB3 3'UTR. Moreover, the SNP of G/T was associated with shorter survival of post-surgery GC patients with 5 years of follow up study. CONCLUSION: In conclusion, our findings have shown that the SNP rs3202538 (G/T) in ErbB3 3'-UTR acted as promotion factors in the GC development through disrupting the regulatory role of miR-204 and miR-211 in ErbB3 expression.