Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Stroke is the leading cause of death and disability among adults in China， and its common complications include digestive system abnormalities， cognitive impairment， depression， stroke-associated pneumonia， and hemiplegia. The combination of traditional Chinese and Western medicine has great potential in treating post-stroke complications. Xinglou Chengqitang （XLCQT） is a representative prescription of alleviating the disease in the upper part by treating the lower part. It has definite therapeutic effect and high safety. Clinically， XLCQT is often used to treat stroke and its complications. However， the quantity and quality of clinical trials of XLCQT in treating post-stroke complications need to be improved. Additionally， since the basic research is weak， the material basis and multi-target mechanism for the efficacy of this prescription are unknown. This article reviews XLCQT in terms of the pharmacodynamic basis， medicinal properties， safety evaluation， and progress in clinical research and mechanisms in treating post-stroke complications. This article summarizes 22 key active ingredients of XLCQT in treating acute stroke complicated with syndrome of phlegm heat and fu-organ excess. Among these key active ingredients， resveratrol， kaempferol， luteolin， chrysoeriol， apigenin， （+）-catechin， and adenosine have good pharmacokinetic properties and high bioavailability. The mechanisms of XLCQT in treating post-stroke complications are complex， including inflammatory response， brain-gut axis， hypothalamic-pituitary-adrenal （HPA） axis， intestinal flora， neurotrophic factors， autophagy， oxidative stress， and free radical damage. This review helps to deeply understand the pharmacodynamic basis and mechanisms of XLCQT in treating post-stroke complications and provides a theoretical basis for the clinical application of XLCQT against post-stroke complications and the development of drugs.

Objective: Patients with atherosclerotic cardiovascular disease (ASCVD) following percutaneous coronary intervention (PCI) are classified as very-high-risk individuals in cardiovascular disease (CVD) risk stratification. The distribution pattern of traditional Chinese medicine (TCM) syndromes in this patient population, as well as its association with blood lipid profiles and clinical prognosis, remains unclear. The present prospective cohort study aims to investigate these correlations, thereby providing insights to enrich the research fields. Methods: We enrolled consecutive patients with ASCVD who underwent PCI at the Integrated Cardiology Unit of China-Japan Friendship Hospital between September 1, 2020 and December 31, 2022. Demographics and clinical characteristics, signs and symptoms defining each TCM syndrome, and fasting venous blood samples were collected at baseline and follow up or upon major adverse cardiovascular events (MACEs). We analyzed the correlation between TCM syndromes, blood lipid profiles, and MACEs, and developed a new joint prognostic model incorporating both TCM syndromes and blood lipids using logistic regression. The analyses were based on detailed baseline and one-year follow-up data. Results: A per-protocol analysis was performed on 586 patients with complete data ultimately. During the one-year follow-up, 174 patients (29.69%) experienced a MACE. We performed statistical analyses on comorbidities, medication, and biochemical indicators across groups defined by TCM syndrome differentiation. When comparing different TCM syndromes, no significant differences were found in age, body mass index (BMI), history of revascularization, comorbidities, family history of CVD, smoking or drinking, or statin intensity (P > 0.05). Patients with intertwined phlegm and blood stasis syndrome exhibited significantly higher levels of total cholesterol (TC, 5.27 ± 1.18 mmol/L, P < 0.001), triglyceride (TG, 1.96 ± 1.33 mmol/L, P = 0.008), low-density lipoprotein cholesterol (LDL-C, 3.35 ± 0.79 mmol/L, P < 0.001), and high-density lipoprotein cholesterol (HDL-C, 1.24 ± 0.81 mmol/L, P < 0.001) compared with those with other TCM syndromes combined. A multivariable logistic regression model was constructed to predict MACEs. The model included TCM syndrome type [with intertwined phlegm and blood stasis as a predictor, adjusted odds ratio (OR) = 1.413, 95% confidence interval (CI): 0.517 – 3.864, P = 0.501], age (adjusted OR = 0.97, 95% CI: 0.955 – 1.001, P = 0.057), male gender (adjusted OR = 0.698, 95% CI: 0.416 – 1.170, P = 0.173), TC (adjusted OR = 1.004, 95% CI: 0.513 – 1.965, P = 0.990), and LDL-C (adjusted OR = 5.825, 95% CI: 2.214 – 15.326, P < 0.001). This model demonstrated good discriminatory ability for MACEs in post-PCI ASCVD patients [the area under the receiver operating characteristic (ROC) curve (AUC) = 0.865, 95% CI: 0.816 – 0.914]. Conclusion The intertwined phlegm and blood stasis TCM syndrome is associated with a distinct atherogenic lipid profile characterized by elevated levels of TC and LDL-C. The prognostic model that incorporates this TCM syndrome type along with conventional lipid parameters (TC and LDL-C) shows good discriminatory ability for predicting MACEs in ASCVD patients after PCI, underscoring the potential clinical utility of integrating TCM syndrome differentiation into CVD risk assessment.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

Objective To explore the role of X chromosome encoded epigenetic regulator UTX in NK cell-mediated anti-tumor activity.Methods Male Ncr1-iCre mice were crossed with female UTXfl/fl mice to generate F1 Ncr1-iCre+UTXfl/-male mice,which were further crossed with female UTXfl/fl mice to obtain male Ncr1-iCre-UTX fl/-control mice(M-Con)and NK-specific deletion of UTX male mice Ncr1-iCre+UTXfl/-(M-KO),as well as female Ncr1-iCre-UTXfl/fl control mice(F-Con)and UTX-deficient female mice Ncr1-iCre+UTXfl/fl(F-KO).UTX-deficient mice were injected with melanoma cell line B16F10 via tail vein to observe pulmonary metastatic tumor nodules.Moreover,flow cytometry was applied to detect the proportion and quantity of pulmonary NK cells(CD3-CD19-NK1.1+),maturation makers KLRG1 and CD11b,activation receptors NKG2D and CD69,and effector molecules,including perforin,granzyme B,CD107a,and IFN-γ.Then pulmonary NK cells were sorted and co-cultured with B16F10 cells,and the apoptosis of the melanoma cells was measured with flow cytometry.Results Compared with the M-Con mice,the M-KO mice presented less number of pulmonary tumor nodules(P<0.05),increased proportion and quantity of NK cells in the tumor microenvironment(P<0.01),though no obvious changes in the ratio of NK maturation makers KLRG1 to CD11b,enhanced expression level of cytotoxic molecule perforin(P<0.01),but no changes in the expression of effector molecule granzyme B,degranulation marker CD107a and cytokine IFN-γ in NK cells.Co-culture of NK cells and B16F10 cells promoted the apoptosis of tumor cells(P<0.05).Compared with the F-Con mice,the F-KO mice had no statistical difference in the number of pulmonary tumor nodules,but larger proportion and number of NK cells(P<0.05),decreased ratio of KLRG1 to CD11b(P<0.01),elevated level of perforin but decreased levels of granzyme B,CD107a and IFN-γ in NK cells(P<0.01).The co-culture of NK cells and B16F10 cells reduced the apoptosis of tumor cells in F-KO female mice(P<0.05).Conclusion NK-specific deletion of UTX regulates pulmonary metastasis of melanoma in a sex-dependent manner.

Objective: To investigate the inhibitory effect of Elesclomol (ES) + Cu2 + on the proliferation of human hepatoma cell lines PLC/PRF/5 and Huh-7 and its potential to induce Cuproptosis. Methods: Human hepatoma cell lines PLC/PRF/5 and Huh_7 cells were Cultured in vitro. ES solution , Cu2 + solution and copper chelating agent ammonium tetrathiomolybdate VI (ATTM) solution was treated separately or in combination. The effect of ES + Cu2 + on the survival rate of human hepatoma cell lines PLC/PRF/5 and Huh_7 cells and the effect of ES + Cu2 + on the survival rate after pretreatment with copper chelating agent ATTM were evaluated using CCK_8 kit. The cell death induced by ES + Cu2 + was detected by flow cytometry and the changes of ES + Cu2 + after pretreatment with copper chelating agent ATTM. The expression of Cuproptosis related proteins ATPase copper transporting beta (ATP7B) ,ferredoxin 1 (FDX1) , dihydrolipoamide s_acetyltransferase(DLAT) and superoxide dismutase 1 (SOD1) were detected by Western blot. The effect of ES + Cu2 + on cell proliferation and the reverse effect after ATTM pretreatment was detected by cell scratch assay. Results: The toxicity of ES + Cu2 + to human hepatocellular carcinoma cell lines PLC/PRF/5 and Huh_7 was significantly dose_dependent (P < 0. 05) . Compared with the control group , the combined application of ES and Cu2 + had a more significant inhibitory effect on hepatocellular carcinoma cells than ES or Cu2 + alone (P < 0. 05) , and copper chelating agent ATTM could reverse the inhibitory effect of ES + Cu2 + on hepatocellular carcinoma cells (P < 0. 05) . Flow cytometry results showed that compared with the control group , the proportion of cell death in PLC/PRF/5 and Huh_7 cells treated with ES + Cu2 + increased , while the proportion of cell death decreased after ATTM intervention (P < 0. 05) . The results of cell scratch test showed that the migration ability of PLC/PRF/5 and Huh_7 cells was decreased after ES + Cu2 + treatment , however, the addition of ATTM reversed the inhibitory effect of ES + Cu2 + on cell migration (P < 0. 05) . Compared with the control group , the expression levels of copper death related proteins ATP7B , FDX1 , DLAT and SOD1 decreased after ES + Cu2 + treatment , but the addition of ATTM reversed the expression trend of these proteins (P < 0. 05) . Conclusion The combination of ES and Cu2 + can effectively inhibit the proliferation and migration of PLC/PRF/5 and Huh_7 of hepatocellular carcinoma cells , and induce Cuproptosis , which provides a new strategy for the treatment of hepatocellular carcinoma.

ObjectiveTo explore the mechanism of modified Xiehuangsan in treating tic disorders （TD） based on microglial polarization and the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor （NF）-κB pathway. MethodsSeventy-two Sprague-Dawley （SD） rats were randomly assigned into six groups： control， model， tiapride （0.025 g·kg^-1）， and low-， medium-， and high-dose （12， 24， 48 g·kg^-1， respectively） modified Xiehuangsan， with 12 rats in each group. Except the control group， the other groups received intraperitoneal injection of 3，3'-iminodipropionitrile （IDPN） for 7 consecutive days for the modeling of TD. After successful modeling， the control and model groups were given normal saline via gavage， and the other groups were administrated with corresponding drugs by gavage. After 28 days of continuous intervention， rat behaviors were observed， and the modified Xiehuangsan group showing the best anti-TD effect was selected for deciphering the treatment mechanism. Hematoxylin and eosin staining was conducted to observe morphological changes in the rat striatum. Immunohistochemistry was employed to detect the expression of CD16 and CD206 in the striatum. Real-time PCR was employed to measure the mRNA levels of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， IL-4， TLR4， MyD88， and NF-κB p65 in the striatum. Western blot was employed to determine the protein levels of ionized calcium-binding adapter molecule 1 （Iba1）， Fc receptor family for immunoglobulin （Ig）G type Ⅲ （CD16）， mannose receptor （CD206）， TLR4， MyD88， and NF-κB p65 in the striatum. ResultsCompared with the control group， the model group showed increased stereotyped behaviors， locomotor activity， total movement distance， and movement speed， shortened resting time （P<0.01）， and noticeable pathological changes in the striatum. Compared with the model group， the tiapride group and modified Xiehuangsan groups exhibited reduced stereotyped behavior， locomotor activity， total movement distance， and movement speed， prolonged resting time （P<0.05， P<0.01）， and alleviated pathological changes in the striatum. Among the modified Xiehuangsan groups， the high-dose group had the best intervention effect and the mildest pathological changes. Therefore， the high-dose group was selected for further research. Compared with the control group， the modeling of TD increased Iba1 and CD16 expression （P<0.05， P<0.01）， up-regulated the mRNA levels of IL-1β and TNF-α （P<0.05， P<0.01）， down-regulated the mRNA level of IL-4 （P<0.05）， up-regulated the mRNA and protein levels of TLR4 and MyD88 （P<0.05， P<0.01）， and up-regulated the protein level of NF-κB p65 （P<0.01）. Compared with the model group， modified Xiehuangsan reduced Iba1 and CD16 expression （P<0.05， P<0.01）， up-regulated the protein level of CD206 （P<0.05， P<0.01）， down-regulated the mRNA levels of IL-1β and TNF-α （P<0.05）， up-regulated the mRNA level of IL-4 （P<0.01）， and down-regulated the mRNA and protein levels of TLR4， MyD88， and NF-κB p65 （P<0.05， P<0.01）. ConclusionModified Xiehuangsan demonstrated a definite therapeutic effect on TD in rats. It may reduce neuroinflammation in TD rats by regulating the polarization of microglia in the striatum via the TLR4/MyD88/NF-κB signaling pathway.

High mobility group box 1 (HMGB1), when released extracellularly, plays a pivotal role in the development of spinal cord synapses and exacerbates autoimmune diseases within the central nervous system. In experimental autoimmune encephalomyelitis (EAE), a condition that models multiple sclerosis, the levels of extracellular HMGB1 and interleukin-33 (IL-33) have been found to be inversely correlated. However, the mechanism by which IL-33 deficiency enhances HMGB1 release during EAE remains elusive. Our study elucidates a potential signaling pathway whereby the absence of IL-33 leads to increased binding of P300/CBP-associated factor with HMGB1 in the nuclei of astrocytes, upregulating HMGB1 acetylation and promoting its release from astrocyte nuclei in the spinal cord of EAE mice. Conversely, the addition of IL-33 counteracts the TNF-α-induced increase in HMGB1 and acetylated HMGB1 levels in primary astrocytes. These findings underscore the potential of IL-33-associated signaling pathways as a therapeutic target for EAE treatment.
Animals ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Astrocytes/metabolism* ; Interleukin-33/metabolism* ; HMGB1 Protein/metabolism* ; Acetylation ; Mice, Knockout ; Mice, Inbred C57BL ; p300-CBP Transcription Factors/metabolism* ; Mice ; Spinal Cord/metabolism* ; Cells, Cultured ; Female ; Signal Transduction

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.