ObjectiveTo investigate the correlation between neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， systemic immune-inflammation index （SII） and the severity of intrauterine adhesions （IUA）. MethodsThe retrospective study included 380 patients who underwent transcervical resection of adhesions （TCRA） from December 2019 to March 2025. Based on the American Fertility Society （AFS） classification， patients were divided into mild （n=61）， moderate （n=225）， and severe （n=94） groups. NLR， PLR， and SII were calculated from preoperative blood tests. Statistical analyses included Kruskal-Wallis test and ordinal Logistic regression. ResultsNLR， PLR， and SII were significantly higher in the severe IUA group compared to the mild group （P<0.05）， with SII showing the strongest predictive ability （OR=1.004， P=0.001）. The number of intrauterine procedures was an independent risk factor （OR=1.27/level， P=0.016）. The predictive model ［Logit（P）=-0.676+0.241×operation times+0.004×SII］ effectively identified severe IUA cases. ConclusionInflammatory markers （particularly SII） are correlated with IUA severity and may serve as non-invasive tools for clinical assessment.

ObjectiveTo investigate the regulatory effect of overexpressed protein tyrosine phosphatase non-receptor type 2 （Ptpn2） on the inflammatory response of mouse alveolar macrophages （MH-S） induced by SiO₂. MethodsCells with overexpressed Ptpn2 were constructed and induced by SiO₂. The experimental groups were divided into four groups： the negative control group with an empty vector （NC）， the overexpressed Ptpn2 group （P）， the negative control group with an empty vector + SiO₂ induction （NS）， and the overexpressed Ptpn2 + SiO₂ induction group （PS）. Isobaric tags for relative and absolute quantification （iTRAQ） combined with liquid chromatography-tandem mass spectrometry （LC-MS/MS） were used to screen differential proteins， followed by Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） database analyses. Immunofluorescence staining was used to detect the expressions of Tumor necrosis factor （TNF） α， Gasdermin D （GSDMD）， and Transforming growth factor （TGF）-β1. Western blot was used to detect the protein expression levels of PTPN2， Toll-like receptor 4 （TLR4）， tumor necrosis factor-α （TNF-α）， nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3）， and proteins related to the TGF-β1 signaling pathway in the cells of each group. ResultsiTRAQ results identified 144 differential proteins among the four groups. GO analysis showed that in biological processes （BP）， these differential proteins were mainly enriched in IκB kinase/nuclear factor-κB （NF-κB） signaling， cell activation and signal transduction involved in immune responses， and regulation of receptor signaling pathways by signal transducer and activator of transcription （STAT）， etc. KEGG analysis revealed that the differential proteins were mainly enriched in Toll-like receptor signaling pathway， NF-κB signaling pathway， NOD-like receptor signaling pathway， TGF-β signaling pathway， and TNF signaling pathway. The results of immunofluorescence staining showed that compared with the NC group， the expressions of TNF α， GSDMD， and TGF-β1 in the cells of the NS group increased （P < 0.05）； compared to the NS group， the expression of the aforementioned proteins in the PS group decreased in cellular proteins（P < 0.05）. The results of Western blot showed that compared with the NC group， the protein expression levels of PTPN2， p-NF-κB，MyD88，TLR4，NLRP3，GSDMD，Caspase-1，IL-1β， TGF-βR1， TGF-βR，p-Smad2/3 in the NS group were significantly upregulated （P < 0.05）； compared with the NS group， the expression levels of the aforementioned proteins in the PS group were significantly downregulated （P < 0.05）. ConclusionOverexpression of Ptpn2 can inhibit the protein expressions of TLR4-TNF-α signaling， NLRP3 signaling， and TGF-β1 signaling closely related to inflammatory response in SiO₂-mediated MH-S macrophages.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

The blood-brain barrier （BBB） is a physical and biochemical barrier that precisely regulates brain homeostasis and plays a central role in controlling the transport of endogenous and exogenous drugs and related metabolites across the blood-brain interface. These functions of the BBB are mediated by its major components， including brain microvascular endothelial cells （BMECs）， tight junction protein complexes， and influx and efflux transporter proteins. One of the pathological features of ischemic stroke （IS） is BBB disruption， which plays an important role in the development of post-stroke brain injury and subsequent neurological dysfunction. Therefore， given the increasing incidence of IS， there is an urgent need to develop new therapeutic strategies to prevent BBB dysfunction and thereby protect injured brain tissue after IS. This study describes the pathological mechanisms by which BMEC injury after IS leads to BBB dysfunction and elucidates the association between BMECs and IS， including the regulation of apoptosis， autophagy， inflammatory responses， oxidative stress， neurotoxic effects， and cerebral edema. In addition， this article summarizes Chinese herbal medicines that may prevent and treat IS by targeting BMECs. These include monomeric compounds and single herbs such as flavonoids， glycosides， phenols， phthalides， terpenoids， and Styrax. Traditional Chinese medicine （TCM） compound formulas and preparations include oral formulations such as Buyang Huanwu decoction， Sailuotong， Naoxintong capsules， Dandeng Tongnao capsules， and Shexiang Tongxin dropping pills， as well as injectable preparations such as Tongluo Jiunao injection， Xingnaojing injection， Danshen polyphenolic acid for injection， Yiqi Fumai injection， and Shuxuetong injection. This study aims to explore the protective effects of TCM against IS through targeted regulation of BMEC function， providing new insights into the mechanisms of IS and endovascular therapeutic strategies.

ObjectiveTo investigate the effects and potential mechanisms of morning and evening fasting on postprandial lipid responses, a post hoc analysis based on a crossover randomized controlled trial was conducted to assess the effects of different fasting strategies on postprandial lipid metabolism in community residents in Shanghai. MethodsA total of 23 participants took part in a randomized crossover trial involving two intervention days: morning fasting and evening fasting, with a washout period of 6 days between intervention days. Two-way analysis of variance was used to test the differences in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the relative expression of circadian clock genes before and after the next meal under fasting. Wilcoxon rank sum tests were used to analyze the different metabolites between the two groups. Principal component analysis and Orthogonal partial least squares-discriminant analysis were conducted to evaluate the ability of metabolites to differentiate between morning fasting and evening fasting and identify the important differential metabolites. After adjusting for age, sex, and BMI, a partial correlation analysis was performed to identify metabolites associated with plasma lipids. In addition, important metabolites associated with plasma lipids were computed by pathway enrichment analysis. ResultsAfter evening fasting intervention, fasting TG level [(0.37±0.29) vs (0.27±0.18)] mmol·L^-1, fasting and postprandial change values in TC [(2.74±0.47) vs (2.51±0.27)] mmol·L^-1 and LDL-C [(1.32±0.38) vs (0.99±0.27)] mmol·L^-1 were significantly lower than those after morning fasting (P<0.05). While, change values of fasting LDL-C [(0.89±0.37) vs (1.14±0.37)] mmol·L^-1 and TG [(1.14±0.19) vs (1.28±0.17)] mmol·L^-1 were significantly higher than those after morning fasting intervention (P<0.05). After fasting intervention, the relative expression of AMPK, CRY1, CLOCK, MTNR1B, AANAT, and ASMT was correlated with the amount of plasma lipid changes (P<0.05). Specifically, CLOCK and AANAT were upregulated following evening fasting and downregulated after morning fasting. Among the 217 important differential metabolites, 111 were correlated with plasma lipids, and which were primarily enriched in the cysteine and methionine metabolism pathways (P<0.05). ConclusionCompared to morning fasting, evening fasting was more effective in improving postprandial lipid responses, indicating that an evening fasting window during intermittent fasting could be conducive to cardiovascular disease prevention in adults. Meanwhile, it is suggested that morning and evening fasting may affect lipid responses through circadian rhythm oscillations and the cysteine and methionine metabolism pathways.

Background Protein tyrosine phosphatase non-receptor type II (PTPN2) is essential for the regulation of inflammation and immunity, but the specific mechanism of action of Ptpn2 in silicosis is unknown. Objective To investigate the regulatory role of overexpression of Ptpn2 in SiO₂-mediated inflammatory response in alveolar type II epithelial cells based on transcriptome sequencing. Methods This study was an in vitro study. A negative control group (vector transferred) and an overexpression of Ptpn2 group of mouse lung epithelial cell line MLE-12 cells were firstly constructed. Transcriptome sequencing was performed to detect differentially expressed genes (DEGs), differentially expressed mRNAs, and differentially expressed ncRNAs in the two groups of MLE-12 cells, and then the DEGs were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Constructed MLE-12 cells and A549 cells were stimulated using SiO₂ suspension, and divided into a negative control group (vector transferred), an overexpression of Ptpn2 group, a negative control + SiO₂ group, and an overexpression of Ptpn2 + SiO₂ group, respectively. Protein expressions of tumor necrosis factor-α (TNF-α) and interleukin (IL)-17A, IL-2, IL-1β were detected by Western blot. Positive TNF-α expression was detected by immunofluorescence staining. Results The results of Western blot showed that the protein expression level of PTPN2 was up-regulated in the overexpressed Ptpn2 group compared with the negative control group (P < 0.05). The volcano plot and clustering heat map showed that there were 1122 DEGs, 3681 differentially expressed mRNAs, and 474 differentially expressed ncRNAs in the overexpressed Ptpn2 group compared with the negative control group. The results of GO enrichment showed that, in terms of the biological process, the DEGs were mainly related to the regulation of metal ion transport, extracellular matrix organization, and extracellular structural organization; in terms of cellular composition, the DEGs were mainly related to collagen-containing extracellular matrix, receptor complexes, and basement membranes; in terms of molecular function, the DEGs were mainly related to the extracellular matrix structural constituents, glycosaminoglycan binding, and semaphorin receptor binding. The results of KEGG enrichment showed that the DEGs were closely related to cytokin-cytokine receptor interaction, IL-17 signaling pathway, TNF signaling pathway, and chemokine signaling pathway. In MLE-12 and A549 cells, the results of Western blot showed that the protein expression levels of TNF-α , IL-17A, IL-2, and IL-1β were up-regulated in the negative control + SiO₂ group compared with the negative control group (P < 0.05), and the protein expression levels of TNF-α, IL-17A, IL-2, and IL-1β were down-regulated in the overexpression of Ptpn2 + SiO₂ group compared with the negative control + SiO₂ group (P < 0.05). The immunofluorescence staining showed that the expression of TNF-α was increased in the negative control + SiO₂ group compared with the negative control group, and decreased in the overexpression of Ptpn2 + SiO₂ group compared with the negative control + SiO₂ group. Conclusion Overexpression of Ptpn2 inhibits SiO₂-mediated inflammatory response in MLE-12 cells and A549 cells.

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.