Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

ObjectiveTo investigate the effects of zinc finger E-box binding homeobox 1 （ZEB1） on the proliferation， migration， and invasion of lung adenocarcinoma H322 cells， as well as its underlying molecular mechanisms. MethodsThe gene expression characteristics of the transcription factor ZEB1 in lung adenocarcinoma were analyzed using data from the GEO and TCGA public databases. RT-qPCR and Western blot were employed to measure mRNA and protein expression levels of ZEB1 in lung adenocarcinoma cell lines （H322， A549， 95-D） and normal human bronchial epithelial cells （BEAS-2B）. Lentiviral transduction was utilized to establish stable ZEB1-overexpressing （Oe-ZEB1） and vector control （Oe-NC） H322 cell lines. Cell proliferation was assessed using CCK-8， colony formation， and EdU assays， while apoptosis was evaluated by Hoechst33258/PI double staining. Wound healing and Transwell assays were performed to examine cell migration and invasion capabilities. Cell cycle distribution was determined by flow cytometry， and Western blot was used to analyze protein expression changes in relevant signaling pathways. ResultsThe findings from GEO and TCGA indicated that ZEB1 expression in lung adenocarcinoma varied with tumor malignancy grade. RT-qPCR and Western blot analyses revealed significantly higher ZEB1 expression in lung adenocarcinoma cell lines compared to BEAS-2B cells （P0.05）. Results from the CCK-8， colony formation， EdU， wound healing， and Transwell assays demonstrated that， compared with the un-transfected control （Control） group， Oe-ZEB1 H322 cells exhibited enhanced proliferation， migration， and invasion capabilities （P0.05）. Hoechst33258/PI double staining and flow cytometry analyses showed that， relative to the Control group， apoptosis was reduced in Oe-ZEB1 H322 cells （P0.05）. Additionally， a decreased proportion of cells in the G₁ phase and an increased proportion in the S phase were observed in Oe-ZEB1 cells， indicating accelerated cell cycle progression. Western blot analysis further revealed that， compared with the Control group， Oe-ZEB1 H322 cells exhibited upregulated expression of N-cadherin， mutant p53 （mutp53）， and Cyclin D1 （P0.05）， while expression levels of E-cadherin， murine double minute 2 （MDM2）， and p21 were downregulated （P0.05）. ConclusionOverexpression of ZEB1 promotes the proliferation， migration， and invasion of lung adenocarcinoma H322 cells and may facilitate cell cycle progression by modulating the MDM2/mutp53/p21 signaling pathway， thereby promoting the transition of cells from the G₀/G₁ phase to the S phase.

ObjectiveTo investigate the mechanism by which Jianpi Xiao'ai prescription （JPXAP） inhibits colorectal cancer progression by regulating the inducible nitric oxide synthase-arginase 1 （iNOS-ARG1） metabolic axis and inducing mitochondrial reactive oxygen species （mito-ROS）-mediated mitochondrial structural and functional impairment. MethodsAn arginine metabolism disorder model of human colorectal cancer HCT116 cells was established by combined treatment with recombinant human interferon-γ （IFN-γ， 10 μg·L^-1） and N（ω）-hydroxy-L-arginine （Nor-NOHA， 200 μmol·L^-1） for 24 h， followed by intervention with 5%， 10%， or 20% JPXAP-containing serum. Cell proliferation was assessed using cell counting kit-8 （CCK-8）， 5-ethynyl-2′-deoxyuridine （EdU） staining， and colony formation assays. Cell invasion and migration were evaluated using Transwell chamber and wound healing assays. Mitochondrial membrane potential （MMP） and ROS levels were assessed by JC-1 and MitoSOX staining， respectively. Mitochondrial ultrastructure was observed by transmission electron microscopy （TEM）. The expression of iNOS， ARG1， and mitochondrial dynamics-related proteins， including mitofusin 2 （MFN2） and dynamin-related protein 1 （DRP1）， was analyzed by Western blot and immunofluorescence. The levels of L-arginine， citrulline， and urea were determined by colorimetric methods and enzyme-linked immunosorbent assay （ELISA）. ResultsCompared with the blank group， the model group exhibited significantly upregulated iNOS expression， downregulated ARG1 expression， a decreased ARG1/iNOS ratio， reduced L-arginine and urea levels， and increased citrulline levels （P<0.05）. Meanwhile， mito-ROS accumulation was significantly increased， the JC-1 red/green fluorescence ratio was decreased， and mitochondria showed swelling and cristae disruption， indicating that metabolic disorder induced mitochondrial injury. Compared with the model group， all JPXAP-treated groups further decreased the ARG1/iNOS ratio， enhanced nitric oxide （NO） and reactive nitrogen species accumulation， further reduced L-arginine and urea levels， and increased citrulline levels （P<0.01）. EdU-positive rate， colony formation rate， wound healing rate， and Transwell invasion number all decreased significantly with increasing serum concentration （P<0.01）. Mito-ROS levels were further elevated， and the JC-1 red/green ratio further decreased. TEM revealed aggravated mitochondrial swelling and vacuolization. MFN2 expression was downregulated and DRP1 expression was upregulated （P<0.01），in a dose-dependent manner. ConclusionJPXAP further activates NO-mediated oxidative/nitrosative stress under arginine metabolism imbalance， inducing mito-ROS accumulation， MMP collapse， and mitochondrial dynamics imbalance， thereby inhibiting colorectal cancer cell proliferation and migration. These findings reveal an antitumor mechanism of JPXAP based on coordinated targeting of the "metabolism-mitochondria" axis.

The advancement of microbiome technologies has facilitated a growing interest in the interactions between urinary microbiota and urinary stone formation. This article systematically reviews the technological evolution, and the reciprocal mechanism of microbiota involvement in lithogenesis and its clinical significance. It specifically highlights the changes within the urinary microbiota of calcium oxalate stone patients, notably a depletion of Lactobacillus populations and an enrichment of pathogenic taxa such as Enterobacteriaceae. Furthermore, it delineates the mechanisms whereby microbes participate in stone formation through metabolic regulation, physical adhesion, and inflammatory processes. The article also explores the influence exerted by distinct stone types on the structural composition and functional dynamics of the urinary microbiota. Integrated multi-omics analyses offer novel perspectives for unraveling the intricate microbiome-host interaction network. This approach is anticipated to facilitate significant advances in developing precision-focused prophylactic and therapeutic strategies for urinary stones from a microecological standpoint.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

ObjectiveTo investigate the intervention effect of Tengli Kangliu prescription （TKP） on the carcinogenesis of colorectal adenoma （CRA） induced by azoxymethane （AOM）/dextran sulphate sodium salt （DSS） in C57BL/6 mice and decipher the potential mechanism through regulating the signal transducer and activator of transcription 3 （STAT3） pathway to target M2-type macrophages. MethodsA total of 55 male C57BL/6 mice were randomized into a blank group （n=10）， a model group （n=15）， a celecoxib （0.02 g·kg^-1·d^-1） group （n=15）， a TKP （42.43 g·kg^-1·d^-1） group （n=15）. The mice in the model， TKP， and celecoxib groups were modeled for CRA lesions through the AOM/DSS three-cycle protocol. The intervention in each group began one week after free access to DSS and lasted for 12 weeks， and the blank group received 20 mL·kg^-1·d^-1 normal saline through gavage. Throughout the study period， changes in body mass and survival rate were recorded， alongside measurements of colorectal length and spleen mass. Histological changes of the colonic tissue were observed by HE staining. Immunohistochemical （IHC） staining was performed to detect the positive expression of CD68 and CD11c in the colorectal tissue. Western blot was employed to assess the protein levels of STAT3， phosphorylated （p）-STAT3， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） in the intestinal tissue. Real-time quantitative PCR was employed to analyze the mRNA levels of arginase 1 （Arg1）， CD206， and vascular endothelial growth factor （VEGF）. Enzyme-linked Immunosorbent assay（ELISA） was employed to measure the serum concentrations of Th2-type cytokines interleukin （IL）-4， IL-6， and IL-13 in mice. ResultsCompared with the blank group， the model group exhibited symptoms including diarrhea， hematochezia， and body mass loss， accompanied by shortened colon length， mucosal damage， and multiple tumors. In addition， the model group showcased up-regulated protein levels of STAT3， p-STAT3， and Bcl-2， down-regulated protein level of Bax， increased positive expression of CD68 and CD11c， and up-regulated mRNA levels of Arg1， CD206， and VEGF in the colon tissue， together with elevated serum levels of IL-4， IL-13， and IL-6 （P<0.05）. Compared with the model group， the above-mentioned indicators were partially reversed in both TKP group and celecoxib group， with superior effects observed in the TKP group （P<0.05）. ConclusionTKP significantly improves the survival quality of the mouse model of AOM/DSS-induced CRA by reducing intestinal inflammation and decreasing colorectal tumor number and size. It may delay the progression of AOM/DSS-induced colorectal tumor-like lesions by inhibiting activation of the STAT3/p-STAT3 signaling pathway in the intestinal tissue， targeting regulation of M2-type macrophages， and improving the tumor microenvironment， thereby suppressing CRA carcinogenesis.

OBJECTIVE:The main clinical manifestations of knee osteoarthritis are pain,swelling,stiffness,and limited activity,which have a serious impact on the life of patients.Exercise therapy can effectively improve the related symptoms of patients with knee osteoarthritis.This paper uses the method of network meta-analysis to compare the efficacy of different exercise types in the treatment of knee osteoarthritis. METHODS:CNKI,WanFang,PubMed,Embase,Cochrane Library,Web of Science,Scopus,Ebsco,SinoMed,and UpToDate were searched with Chinese search terms"knee osteoarthritis,exercise therapy"and English search terms"knee osteoarthritis,exercise".Randomized controlled trials on the application of different exercise types in patients with knee osteoarthritis from October 2013 to October 2023 were collected.The outcome measures included visual analog scale,Western Ontario and McMaster Universities Osteoarthritis Index score,Timed Up and Go test,and 36-item short form health survey.Literature quality analysis was performed using the Cochrane Manual recommended tool for risk assessment of bias in randomized controlled trials.Two researchers independently completed the data collection,collation,extraction and analysis.RevMan 5.4 and Stata 18.0 software were used to analyze and plot the obtained data. RESULTS:A total of 29 articles with acceptable quality were included,involving 1 633 patients with knee osteoarthritis.The studies involved four types of exercise:aerobic training,strength training,flexibility/skill training,and mindfulness relaxation training.(1)The results of network meta-analysis showed that compared with routine care/health education,aerobic training could significantly improve pain symptoms(SMD=-3.26,95%CI:-6.33 to-0.19,P<0.05);strength training(SMD=-0.79,95%CI:-1.34 to-0.23,P<0.05)and mindfulness relaxation training(SMD=-0.79,95%CI:-1.23 to-0.34,P<0.05)could significantly improve the function of patients.Aerobic training(SMD=-1.37,95%CI:-2.24 to-0.51,P<0.05)and mindfulness relaxation training(SMD=-0.41,95%CI:-0.80 to-0.02,P<0.05)could significantly improve the functional mobility of patients.Mindfulness relaxation training(SMD=0.70,95%CI:0.21-1.18,P<0.05)and strength training(SMD=0.42,95%CI:0.03-0.81,P<0.05)could significantly improve the quality of life of patients.(2)The cumulative probability ranking results were as follows:pain:aerobic training(86.6%)>flexibility/skill training(60.1%)>strength training(56.8%)>mindfulness relaxation training(34.7%)>routine care/health education(11.7%);Knee function:strength training(73.7%)>mindfulness relaxation training(73.1%)>flexibility/skill training(56.1%)>aerobic training(39.9%)>usual care/health education(7.6%);Functional mobility:aerobic training(94.7%)>mindfulness relaxation training(65.5%)>strength training(45.1%)>flexibility/skill training(41.6%)>routine care/health education(3.2%);Quality of life:mindfulness relaxation training(91.3%)>strength training(68.0%)>flexibility/skill training(44.3%)>aerobic training(34.0%)>usual care/health education(12.3%). CONCLUSION:(1)Exercise therapy is effective in the treatment of knee osteoarthritis,among which aerobic training has the best effect on relieving pain and improving functional mobility.Strength training and mindfulness relaxation training has the best effect on improving patients'function.Mindfulness relaxation training has the best effect on improving the quality of life of patients.(2)Limited by the quality and quantity of the included literature,more high-quality studies are needed to verify it.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.