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The incidence of endometrial cancer (EC) increases annually and tends to occur in younger women. A particularly important relationship exists between EC and metabolic disorders. As one of the most important components of lipid metabolism, phospholipids play an indispensable role in metabolic balance. LPCAT1 is a key enzyme regulating phospholipid metabolism. In this study, we perform further investigations to seek mechanistic insight of LPCAT1 in EC. Our results demonstrate that silencing of LPCAT1 inhibits the growth of endometrial cancer, while overexpression of LPCAT1 results in enhanced stemness and metastasis in endometrial cancer cell lines. Meanwhile, the contents of various phospholipids including phosphatidylethanolamine (PE), phosphatidylcholine (PC), and triglyceride (TG) change significantly after overexpression of LPCAT1. In addition, through RNA-sequencing and western blot analysis, we observe that the TGF-β/Smad2/3 signaling pathway is of great importance in the tumor-promoting function of LPCAT1. LPCAT1 promotes the expressions of stem cell-related transcription factors and epithelial-mesenchymal transition (EMT) related proteins through the TGF-β/Smad2/3 signaling pathway. Moreover, we find that TSI-01, which can inhibit the activity of LPCAT1, is able to restrain the proliferation of EC cell lines and promote cell apoptosis. Collectively, we demonstrate that LPCAT1 enhances the stemness and metastasis of EC by activating the TGF-β/Smad2/3 signaling pathway and that TSI-01 may have potential use for the treatment of EC.

Background and aim: The prevalence and adverse outcomes of metabolic dysfunction associated with steatotic liver disease (MAFLD) are increasing. The changes in the gut microbiota and metabolites associated with metabolic dysfunction-associated steatohepatitis (MASH) are regarded as an essential part of the progression of MAFLD. This study aimed to identify the gut microbiota and metabolites involved in the development of MAFLD in patients. Method: This study enrolled 90 patients (healthy controls, HC: n = 30; MASH: n = 30; MASH-related cirrhosis, MC: n = 30), and their fecal samples were collected for 16S rRNA sequencing and non-targeted LC–MS/MS metabolomics analysis. Data preprocessing and statistical analyses were performed using QIIME2 software, Pynast, QIIME2 package, Progenesis QI, and R program. Results: The abundance of Prevotellaceae at the family level and Prevotella at the genus level was lower in the MASH and NC samples than in the HC samples. Both Prevotellaceae and Prevotella showed the strongest correlation with MASH progression via random forest analysis. Untargeted metabolomics was used to quantitatively screen for discrepant metabolites in the stool samples from the three groups. Linolenic acid (LA)-related metabolite levels were significantly lower in MASH and NC samples. Associations between Prevotella- or LA-related metabolites and liver function were discovered. A high abundance of Prevotella was associated with LA-related metabolites and MASH. Conclusion: This study identified that gut microbiota and metabolites are associated with MASH-related metabolic dysfunction. LA and Prevotella are depleted during MASH progression, and additional supplementation with Prevotella may be a potential strategy for the future treatment of MAFLD. [ABSTRACT FROM AUTHOR]

Objective was to estimate the 5-year cumulative risk of HCC in patients with HBC by utilizing an artificial neural network (ANN). Methods: We conducted this study with 1589 patients hospitalized at Beijing Ditan Hospital of Capital Medical University and People's Liberation Army Fifth Medical Center. The training cohort consisted of 913 subjects from Beijing Ditan Hospital of Capital Medical University, while the validation cohort comprised 676 subjects from People's Liberation Army Fifth Medical Center. Through univariate analysis, we identified factors that independently influenced the occurrence of HCC, which were then used to develop the ANN model. To evaluate the ANN model, we assessed its predictive accuracy, discriminative ability, and clinical net benefit using metrics such as the area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curves. Results: In total, we included nine independent risk factors in the development of the ANN model. Remarkably, the AUC of the ANN model was 0.880, significantly outperforming the AUC values of other existing models including mPAGE-B (0.719) (95% CI 0.670– 0.768), PAGE-B (0. 710) (95% CI 0.660– 0.759), FIB-4 (0.693) (95% CI 0.640– 0.745), and Toronto hepatoma risk index (THRI) (0.705) (95% CI 0.654– 0.756) (p< 0.001 for all). The ANN model effectively stratified patients into low, medium, and high-risk groups based on their 5-year In the training cohort, the positive predictive value (PPV) for low-risk patients was 26.2% (95% CI 25.0– 27.4), and the negative predictive value (NPV) was 98.7% (95% CI 95.2– 99.7). For high-risk patients, the PPV was 54.7% (95% CI 48.6– 60.7), and the NPV was 91.6% (95% CI 89.4– 93.4). These findings were validated in the independent validation cohort. Conclusion: The ANNs model has good individualized prediction performance and may be helpful to evaluate the probability of the 5-year risk of HCC in patients with HBC. [ABSTRACT FROM AUTHOR]

The aqueous micro batteries (AMBs) are expected to be one of the most promising micro energy storage devices for its safe operation and cost‐effectiveness. However, the performance of the AMBs is not satisfactory, which is attributed to strong interaction between metal ions and the electrode materials. Here, the first AMBs are developed with NH4+ as charge carrier. More importantly, to solve the low conductivity and the dissolution during the NH4+ intercalation/extraction problem of perylene material represented by perylene‐3,4,9,10‐tetracarboxylic dianhydride (PTCDA), the Ti3C2Tx MXene with high conductivity and polar surface terminals is introduced as a conductive skeleton (PTCDA/Ti3C2Tx MXene). Benefitting from this, the PTCDA/Ti3C2Tx MXene electrodes exhibit ultra‐high cycle life and rate capability (74.31% after 10 000 galvanostatic chargedischarge (GCD) cycles, and 91.67 mAh g−1 at 15.0 A g−1, i.e., capacity retention of 45.2% for a 30‐fold increase in current density). More significantly, the AMBs with NH4+ as charge carrier and PTCDA/Ti3C2Tx MXene anode provide excellent energy density and power density, cycle life, and flexibility. This work will provide strategy for the development of NH4+ storage materials and the design of AMBs. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) have a profound effect on biological processes in various malignancies. However, few studies have investigated their functions and specific mechanisms in endometrial cancer. In this study, we focused on the role and mechanism of lncRNA‐ZXF1 in endometrial cancer. Bioinformatics and in vitro and in vivo experiments were used to explore the expression and function of lncRNA‐ZXF1. We found that lncRNA‐ZXF1 altered the migration and invasion of endometrioid endometrial cancer (EEC) cells. Furthermore, our results suggest that lncRNA‐ZXF1 regulates EEC cell proliferation. This regulation may be achieved by the lncRNA‐ZXF1‐mediated alteration in the expression of P21 through two mechanisms. One is that lncRNA‐ZXF1 functions as a molecular sponge of miR‐378a‐3p to regulate PCDHA3 expression and then modulate the expression of P21. The other is that lncRNA‐ZXF1 inhibits CDC20‐mediated degradation of ubiquitination by directly binding to P21. To the best of our knowledge, this study is the first to explore lncRNA‐ZXF1 functioning as a tumor‐suppressing lncRNA in EEC. LncRNA‐ZXF1 may become therapeutic, diagnostic, and prognostic indicator in the future. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) is a pandemic that has caused a high number of deaths worldwide. Inflammatory factors may play important roles in COVID-19 progression. Yindan Jiedu granules (YDJDG) can inhibit the progression of COVID-19, but the associated mechanism is unclear.Purpose: To evaluate the therapeutic effects of YDJDG on COVID-19 and explore its underlying mechanism.Methods: We recruited 262 participants and randomly assigned 97 patients each to the YDJDG and control groups using one-to-one propensity score matching (PSM). Clinical effects were observed and serum inflammatory and immune indicators were measured. The target network model of YDJDG was established by predicting and determining the targets of identified compounds. The main constituents of the YDJDG extracts were identified and evaluated using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and molecular docking. Besides, the anti-inflammatory effects of YDJDG and its specific biological mechanism of action were studied.Results: After PSM, the results showed that compared with the control group, the YDJDG group had a shorter time of dissipation of acute pulmonary exudative lesions (p < 0.0001), shorter time to negative conversion of viral nucleic acid (p < 0.01), more rapid decrease in serum amyloid A level and erythrocyte sedimentation rate (p < 0.0001), and a higher rate of increase in CD4+T cell count (p = 0.0155). By overlapping the genes of YDJDG and COVID-19, 213 co-targeted genes were identified. Metascape enrichment analysis showed that 25 genes were significantly enriched in the NF-κB pathway, which were mainly targets of luteolin, quercetin, and kaempferol as confirmed by MS analysis. Molecular docking revealed that the ligands of three compounds had strong interaction with NF-κB p65 and IκBα. In vivo, YDJDG significantly protected animals from lipopolysaccharide (LPS)-induced acute lung injury (ALI), decreasing the lung wet/dry weight ratio, ALI score, and lung histological damage. In LPS-treated RAW264.7 cells, YDJDG suppressed nuclear translocation of NF-κB p65. In vivo and in vitro, YDJDG exerted anti-inflammatory effects by inhibiting the production of inflammatory cytokines (IL-6, IL-1β, and TNF-α). These effects were accompanied by the inhibition of NF-ĸB activation and IκBα phosphorylation.Conclusion: YDJDG may shorten the COVID-19 course and delay its progression by suppressing inflammation via targeting the NF-κB pathway. [ABSTRACT FROM AUTHOR]

Background: The model for end-stage liver disease (MELD) score is widely used for the prognostication in end-stage liver disease but has limited performance in acute-on-chronic liver failure (ACLF). In this study, we identified additional predictive parameters and reformed the MELD score to predict ACLF more accurately., Methods: A meta-analysis was performed on relevant studies to identify the predictive factors of 28-day/90-day outcomes of ACLF, which were validated in two large prospective cohorts. A prognostic score was developed by incorporating predictive parameters into the MELD score. The model was evaluated with a focus on discrimination and calibration., Results: The meta-analysis incorporated 32 cohort studies with a total of 13 939 patients, of which 13 risk factors were identified, and 3 risk factors (age, neutrophil count and hepatic encephalopathy (HE) grade) besides MELD score were validated in 751 patients with ACLF derived from two prospective cohorts. A new model (Chinese Acute-on-Chronic Liver Failure Consortium (CATCH-LIFE)-MELD score) was developed as follows: 0.028×age+0.3×HE grade+0.039×neutrophil count+0.079×MELD score. CATCH-LIFE-MELD score achieved a concordance index of 0.791/0.788 for 28-day/90-day outcomes, which is superior to other traditional scores. Other discrimination indices, including net reclassification improvement, integrated discrimination improvement and probability density function, and calibration including Nagelkerke's R 2 and Brier scores confirmed its superiority. Moreover, the accuracy of CATCH-LIFE-MELD score remained stable. It was highest in patients with or without hepatitis B virus infection, cirrhosis, liver failure or under the Chinese Group on the Study of Severe Hepatitis B (COSSH) criteria or European Association for the Study of the Liver (EASL) criteria. All results were substantiated by an evaluation using an external cohort., Conclusions: CATCH-LIFE-MELD score, a modified MELD score exhibited improved accuracy in predicting the short-term prognosis of ACLF than other traditional scores., Competing Interests: The research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Soil microorganisms are the most active participants in terrestrial ecosystems, and have key roles in biogeochemical cycles and ecosystem functions. Despite the extensive research on soil pH as a key predictor of microbial community and composition, a limitation of these studies lies in determining whether bacterial and/or fungal communities are directly or indirectly influenced by pH. We conducted a controlled laboratory experiment to investigate the effects of soil pH amendment (+/- 1-2 units) with six levels on soil microbial communities in two contrasting Chinese agricultural soils (pH 8.43 in Dezhou, located in the North China Plain, Shandong vs pH 6.17 in Wuxi, located in the Taihu Lake region, Jiangsu, east China). Results showed that the fungal diversity and composition were related to soil pH, but the effects were much lower than the effects of soil pH on bacterial community in two soils. The diversity and composition of bacterial communities were more closely associated with soil pH in Wuxi soils compared to Dezhou soils. The alpha diversity of bacterial communities peaked near in situ pH levels in both soils, displaying a quadratic fitting pattern. Redundancy analysis and variation partition analysis indicated that soil pH affected bacterial community and composition by directly imposing a physiological constraint on soil bacteria and indirectly altering soil characteristics (e.g., nutrient availability). The study also examined complete curves of taxa relative abundances at the phylum and family levels in response to soil pH, with most relationships conforming to a quadratic fitting pattern, indicating soil pH is a reliable predictor. Furthermore, soil pH amendment affected the transformation of nitrogen and the abundances of functional genes involved in the nitrogen cycle, and methane production and consumption. Overall, results from this study would enhance our comprehension of how soil microorganisms in contrasting farmlands will respond to soil pH changes, and would contribute to more effective soil management and conservation strategies., Importance: This study delves into the impact of soil pH on microbial communities, investigating whether pH directly or indirectly influences bacterial and fungal communities. The research involved two contrasting soils subjected to a 1-2 pH unit amendment. Results indicate bacterial community composition was shaped by soil pH through physiological constraints and nutrient limitations. We found that most taxa relative abundances at the phylum and family levels responded to pH with a quadratic fitting pattern, indicating that soil pH is a reliable predictor. Additionally, soil pH was found to significantly influence the predicted abundance of functional genes involved in the nitrogen cycle as well as in methane production and consumption processes. These insights can contribute to develop more effective soil management and conservation strategies., Competing Interests: The authors declare no conflict of interest.

Background and Aims: Approximately 10% of patients with acute decompensated (AD) cirrhosis develop acute-on-chronic liver failure (ACLF) within 28 days. Such cases have high mortality and are difficult to predict. Therefore, we aimed to establish and validate an algorithm to identify these patients on hospitalization., Methods: Hospitalized patients with AD who developed ACLF within 28 days were considered pre-ACLF. Organ dysfunction was defined according to the chronic liver failure-sequential organ failure assessment (CLIF-SOFA) criteria, and proven bacterial infection was taken to indicate immune system dysfunction. A retrospective multicenter cohort and prospective one were used to derive and to validate the potential algorithm, respectively. A miss rate of <5% was acceptable for the calculating algorithm to rule out pre-ACLF., Results: In the derivation cohort ( n =673), 46 patients developed ACLF within 28 days. Serum total bilirubin, creatinine, international normalized ratio, and present proven bacterial infection at admission were associated with the development of ACLF. AD patients with ≥2 organ dysfunctions had a higher risk for pre-ACLF patients [odds ratio=16.581 95% confidence interval: (4.271-64.363), p <0.001]. In the derivation cohort, 67.5% of patients (454/673) had ≤1 organ dysfunction and two patients (0.4%) were pre-ACLF, with a miss rate of 4.3% (missed/total, 2/46). In the validation cohort, 65.9% of patients (914/1388) had ≤1 organ dysfunction, and four (0.3%) of them were pre-ACLF, with a miss rate of 3.4% (missed/total, 4/117)., Conclusions: AD patients with ≤1 organ dysfunction had a significantly lower risk of developing ACLF within 28 days of admission and could be safely ruled out with a pre-ACLF miss rate of <5%., Competing Interests: XZ, YG and YS have been editorial board members of Journal of Clinical and Translational Hepatology since 2021, 2019 and 2022 respectively. The other authors have no conflict of interest related to this publication., (© 2023 Authors.)

Background: Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) has significant morbidity and mortality and is associated with the induction of cytokines/chemokines, which might contribute to the pathogenesis of liver injury. This study aimed to explore the cytokine/chemokine profiles of patients with HBV-ACLF and develop a composite clinical prognostic model., Methods: We prospectively collected blood samples and the clinical data of 107 patients with HBV-ACLF admitted to the Beijing Ditan Hospital. The concentrations of 40-plex cytokines/chemokines were measured in 86 survivors and 21 non-survivors using the Luminex assay. Discrimination between the cytokine/chemokine profiles in different prognosis groups was analyzed using the multivariate statistical techniques of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). An immune-clinical prognostic model was obtained using multivariate logistic regression analysis., Results: The PCA and PLS-DA indicated that cytokine/chemokine profiling could clearly distinguish patients with different prognoses. A total of 14 cytokines, namely, IL-1β, IL-6, IL-8, IL-10, TNF-α, IFN-γ, CXCL1, CXCL2, CXCL9, CXCL13, CX3CL1, GM-SCF, CCL21, and CCL23, were significantly correlated with disease prognosis. Multivariate analysis identified CXCL2, IL-8, total bilirubin, and age as independent risk factors that constituted the immune-clinical prognostic model, which showed the strongest predictive value of 0.938 compared with those of the Chronic Liver Failure Consortium (CLIF-C) ACLF (0.785), Model for End-Stage Liver Disease (MELD) (0.669), and MELD-Na (0.723) scores ( p  < 0.05 for all)., Conclusion: The serum cytokine/chemokine profiles correlated with the 90-day prognosis of patients with HBV-ACLF. The proposed composite immune-clinical prognostic model resulted in more accurate prognostic estimates than those of the CLIF-C ACLF, MELD, and MELD-Na scores., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhu, Gao, Li, Shi, Hou, Chen, Zhang and Wang.)