OBJECTIVE To investigate the clinical characteristics and risk factors for batroxobin-related severe hypofibrinogenemia （HFIB） and construct a risk prediction model. METHODS A retrospective analysis was conducted on inpatients treated with batroxobin in the First Medical Center of a tertiary hospital from January 1， 2020， to December 31， 2024. Patients were categorized into non-severe HFIB group and severe HFIB group based on the severity of HFIB. Univariate and multivariate Logistic regression analyses were performed to identify the independent influencing factors for batroxobin-related severe HFIB. A nomogram was developed using the “rms” package in R 4.5 software. The predictive performance of the model was evaluated using the receiver operating characteristic curve. Calibration was assessed via the Bootstrap resampling method， and goodness-of-fit was evaluated with the Hosmer-Lemeshow test. RESULTS A total of 1 472 patients were included in this study. Of these， 1 445 developed HFIB， yi elding an incidence of 98.17%. Furthermore， 895 were classified as severe HFIB， accounting for 60.80% of the cohort. Multivariate Logistic regression analysis showed that increased age， high initial dose per 10 kg body weight， use of maintenance dose， and concomitant glucocorticoid use were independent risk factors for batroxobin-related severe HFIB， while high baseline fibrinogen （FIB） level was identified as a protective factor. The model demonstrated an area under the curve of 0.760 （95% CI： 0.735-0.785）. The mean absolute error of the calibration curve was 0.006. The P value of the Hosmer-Lemeshow test was 0.609. CONCLUSIONS Batroxobin can rapidly and significantly reduce FIB levels and carries a risk of inducing severe HFIB. Patients with advanced age， high initial dose per 10 kg body weight， use of maintenance dose and concomitant glucocorticoid use had a higher risk of batroxobin-related severe HFIB， while high baseline FIB level had a lower risk of batroxobin-related severe HFIB. The risk prediction model developed based on these factors can be used to predict the likelihood of batroxobin-related severe HFIB.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Foot-and-mouth disease (FMD) is one of the major animal infectious diseases in the world. All cloven-hoofed animals are susceptible to FMD. Vaccination is still the first choice for the prevention and control of FMD. mRNA vaccines can be rapidly designed, synthesized, and produced on a large scale in vitro, and they can induce effective protective immune responses, demonstrating the advantages of rapid development, easy preparation, and low biosafety risks. The design of untranslated regions is a key to enhancing the expression and efficacy of mRNA vaccines. In order to generate an efficient FMD mRNA vaccine, we designed three FMD P12A3C expression vectors with different untranslated regions and synthesized corresponding mRNAs. By comparing expression efficiency of these vectors and their mRNAs at different time points and in different cell lines, we found that the mRNA P12A3C-UTR3 had the best expression and universality. This study laid a foundation for the development of mRNA vaccines against FMD and provided a theoretical basis for the optimal sequence design of efficient mRNA.
Foot-and-Mouth Disease Virus/genetics* ; Animals ; RNA, Messenger/biosynthesis* ; Foot-and-Mouth Disease/immunology* ; Antigens, Viral/biosynthesis* ; Viral Vaccines/biosynthesis* ; Genetic Vectors/genetics* ; Cell Line ; Vaccines, DNA/immunology*

Autophagy is a fundamental biological metabolic process involved in immune defense, material metabolism, and homeostasis and closely linked to immune regulation. Systemic lupus erythematosus (SLE) is a widespread connective tissue disorder primarily resulting from immune system imbalance. Due to the immune system's failure to recognize its own substances, it generates autoantibodies that can affect various tissues and organs, leading to diverse clinical manifestations. The pathogenesis and treatment of SLE are currently under extensive investigation. In normal metabolic processes, autophagy engages in both innate and adaptive immunity, regulates the immune response, and is crucial for maintaining normal immune function and the body's internal homeostasis. Research has indicated that SLE patients exhibit immune dysfunction and altered autophagy levels. Modulating autophagy expression can influence immune system functionality and alleviate SLE symptoms. Additionally, autophagy aids in the innate immune response and adaptive immunity by clearing metabolites and regulating the life cycle of immune cells. Studies suggest that drugs targeting autophagy can positively influence the progression of SLE. This article reviews advancements in research regarding the impact of autophagy on the pathogenesis of SLE through the regulation of immune system functions.
Lupus Erythematosus, Systemic/pathology* ; Autophagy/immunology* ; Humans ; Animals ; Immunity, Innate ; Adaptive Immunity ; Disease Progression ; Immune System/immunology*

Notum, a negative feedback regulator of the Wnt signaling, has emerged as a promising target for treating glucocorticoid-induced osteoporosis (GIOP). This study showcases an efficient strategy for discovering the anti-Notum constituents from herbal medicines (HMs) as novel anti-GIOP agents. Firstly, a rapid-responding near-infrared fluorogenic substrate for Notum was rationally engineered for high-throughput identifying the anti-Notum HMs. The results showed that Bu-Gu-Zhi (BGZ), a known anti-osteoporosis herb, potently inhibited Notum in a competitive-inhibition manner. To uncover the key anti-Notum constituents in BGZ, an efficient strategy was adapted via integrating biochemical, phytochemical, computational, and pharmacological assays. Among all identified BGZ constituents, three furanocoumarins were validated as strong Notum inhibitors, while 5-methoxypsoralen (5-MP) showed the most potent anti-Notum activity and favorable safety profiles. Mechanistically, 5-MP acted as a competitive inhibitor of Notum via creating strong hydrophobic interactions with Trp128 and Phe268 in the catalytic cavity of Notum. Cellular assays showed that 5-MP remarkably promoted osteoblast differentiation and activated Wnt signaling in dexamethasone (DXMS)-challenged MC3T3-E1 osteoblasts. In dexamethasone-induced osteoporotic mice, 5-MP strongly elevated bone mineral density (BMD) and improved cancellous and cortical bone thickness. Collectively, this study constructs a high-efficient platform for discovering key anti-Notum constituents from HMs, while 5-MP emerges as a promising anti-GIOP agent.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease lacking effective therapy. Metformin, an antidiabetic medication, has shown promising therapeutic properties in preclinical fibrosis models; however, its precise cellular targets and associated mechanisms in fibrosis resolution remain incompletely defined. Most research on metformin's effects has focused on mesenchymal and inflammatory responses with limited attention to epithelial cells. In this study, we utilized Sftpc lineage-traced and Fgfr2b conditional knockout mice, along with BMP2/PPARγ and AMPK inhibitors, to explore metformin's impact on alveolar epithelial cells in a bleomycin-induced pulmonary fibrosis model and cell culture. We found that metformin increased the proliferation and differentiation of alveolar type 2 (AT2) cells, particularly the recently identified injury-activated alveolar progenitors (IAAPs)-a subpopulation characterized by low SFTPC expression but enriched for PD-L1. Single-cell RNA sequencing revealed a reduction in apoptosis among mature AT2 cells. Interestingly, metformin's therapeutic effects were not significantly affected by BMP2 or PPARγ inhibition, which blocked the lipogenic differentiation of myofibroblasts. However, Fgfr2b deletion in Sftpc lineage cells significantly impaired metformin's ability to promote fibrosis resolution, a process linked to AMPK signaling. In conclusion, metformin alleviates fibrosis by directly activating AT2 cells, especially the IAAPs, through a mechanism that involves AMPK and FGFR2b signaling, but is largely independent of BMP2/PPARγ pathways.

Objectives:This study aims to evaluate the relationship between the triglyceride-glucose body mass index(TyG-BMI),the right pericoronary fat attenuation index(RCA-FAI),and prognosis in patients with coronary artery disease(CAD).Methods:This study included 513 CAD patients who underwent coronary computed tomography angiography(CCTA)and coronary angiography between April 2018 and June 2023.Data collection and parameter calculations were performed for all research variables.The patients were stratified into three groups based on TyG-BMI tertiles:T1 group(TyG-BMI≤207.02,n=171),T2 group(207.02