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.

Objective: To translate the common metrics for donation attitude, subjective norm, perceived behavioral control, and intention for the blood donation context (BD-ASPI) into Chinese, and to test its reliability and validity among college students. Methods: A research team was established. Following Beaton's cross-cultural adaptation guidelines, the BD-ASPI was translated, culturally adapted, and pre-tested to develop the Chinese version. Using convenience sampling, 620 students from four universities in Wuhan were surveyed form August to November 2024 to test the scale's reliability and validity. Results: The Chinese version of the scale consisted of 21 items across four dimensions: attitude towards blood donation, subjective norm, perceived behavioral control, and intention. The item-level content validity index ranged from 0.89 to 1.00, and the average scale-level content validity index was 0.984. Confirmatory factor analysis indicated a good fit for the second-order factor model. The Criterion validity was 0.509 (P<0.001). The overall Cronbach's α coefficient was 0.965, with the coefficients for each dimension ranging from 0.891 to 0.974. The test-retest reliability was 0.894. Conclusion: The Chinese version of the BD-ASPI demonstrates good reliability and validity, and can serve as an effective tool for assessing the behavioral intention of voluntary blood donation among college students in China.

Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

Tissue repair requires the reconstruction of functional vascular networks to restore oxygen and nutrient delivery, eliminate metabolic waste, and maintain tissue homeostasis. Although biochemical factors such as growth factors and cytokines have been extensively studied in vascular regeneration, increasing evidence indicates that mechanical signals from the extracellular matrix (ECM) are equally important regulators of angiogenesis. Matrix stiffness, as a major biomechanical property of the tissue microenvironment, provides critical information that influences endothelial cell (EC) behavior and vascular remodeling through mechanotransduction. However, the biological effects of matrix stiffness are not universally defined as either pro- or anti-angiogenic, but are highly dependent on tissue context, cellular composition, disease progression, and the dynamic changes occurring during tissue repair. Therefore, understanding how matrix stiffness regulates vascular regeneration is essential for developing more precise strategies for tissue engineering and regenerative medicine. In this review, we summarize recent advances in the regulation of angiogenesis by matrix stiffness during tissue repair from multiple perspectives. First, we discuss the direct effects of matrix stiffness on EC behaviors, including differentiation, morphological remodeling, migration, proliferation, barrier maintenance, and vascular network formation. ECs sense mechanical alterations in the surrounding matrix through various mechanosensitive structures, including integrins, focal adhesion complexes, and mechanosensitive ion channels such as Piezo1 and TRPV proteins. These mechanical signals are subsequently transmitted through intracellular pathways involving FAK, RhoA/ROCK, MAPK, and Hippo-YAP/TAZ signaling, leading to cytoskeletal reorganization and transcriptional regulation. Through these mechanisms, matrix stiffness regulates endothelial functional states and determines the balance between regenerative vascular formation and pathological vascular remodeling. Beyond the direct regulation of ECs, we further highlight the importance of stiffness-mediated intercellular communication within the regenerative microenvironment. Matrix stiffness can regulate the behavior and secretory profiles of vascular-associated cells, including mesenchymal stem cells and macrophages, thereby indirectly affecting endothelial function through paracrine mechanisms. Changes in matrix mechanics influence the secretion of angiogenic factors, inflammatory cytokines, and extracellular vesicles from these cells, creating a mechanical regulation network that coordinates vascular regeneration. This perspective extends the traditional concept of matrix stiffness from a physical support structure to an active regulatory signal that integrates multiple cellular responses during tissue repair. Furthermore, we discuss the tissue-specific effects of matrix stiffness in vascular regeneration across different organs, including the aorta, lung, liver, and heart. Although excessive matrix stiffening is frequently associated with fibrosis and vascular dysfunction, the consequences of mechanical changes vary considerably among tissues. Moderate stiffness alterations may support endothelial activation and vascular stabilization in certain regenerative contexts, whereas persistent pathological stiffening can promote inflammation, endothelial dysfunction, and impaired vascular repair. These findings emphasize that the biological meaning of “soft” and “stiff” microenvironments should be interpreted according to specific tissue and experimental conditions rather than as universal mechanical classifications. Finally, we summarize current challenges and future perspectives in this field. A major limitation is the lack of standardized mechanical characterization among different studies, as stiffness measurements are influenced by material properties, testing methods, and experimental conditions, limiting direct comparison across research systems. Moreover, most existing models fail to fully reproduce the dynamic and viscoelastic properties of native ECM during tissue regeneration. Future studies should combine advanced biomaterials with standardized mechanical analysis, organoid models, and multi-omics approaches to establish more accurate mechanical regulatory maps. Overall, this review proposes that matrix stiffness is not merely a structural feature of tissues, but an active biological signal that regulates vascular regeneration through coordinated mechanotransduction and multicellular interactions. A deeper understanding of stiffness-mediated vascular regulation will provide new theoretical insights and therapeutic opportunities for improving tissue repair outcomes.

Abstract Postoperative urinary retention is a common complication after mixed hemorrhoid surgery, referring to the inability of urine in the bladder to be normally expelled, leading to urine retention. This condition not only prolongs the postoperative recovery time and increases medical costs, but may also cause problems such as urinary tract infections and bladder dysfunction. The pathogenesis of urinary retention after mixed hemorrhoid surgery is complex, involving multiple factors such as the type of surgery, anesthesia method, individual differences among patients, postoperative pain management and psychological stress. Although there are various clinical treatment methods, their efficacy varies among individuals. This article reviews relevant literature from 2018 to 2024, analyzing the etiology of urinary retention after mixed hemorrhoid surgery. It summarizes the intervention measures and mechanisms of non-pharmacological treatments, such as physical therapy and analgesic techniques, as well as pharmacological treatments, including anticholinesterase drugs, selective α-receptor blockers and analgesics drugs, so as to provide the reference for the prevention and treatment of urinary retention after mixed hemorrhoid surgery.

Objectives:To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development.Methods:Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error ( MAPE). The association between SDI and incidence rates was assessed through generalized linear models. Results:A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with MAPE of 4.71%, 7.66% and 10.30%, respectively. Conclusion:SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as "rapid antibody screening in key areas + vaccination boosters for high-risk populations" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.

Objective:To explore the association between the use of tetracyclines during pregnancy and congenital malformations, with the aim of providing evidence-based guidance for the rational use of antibiotics during pregnancy.Methods:Data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) and the Canada Vigilance Adverse Reaction (CVAR) database from January 2015 to September 2024 were collected. Five methods including Tree-based scan statistic (TreeScan), proportional reporting ratio (PRR), reporting odds ratio (ROR), the UK Medicines and Healthcare Products Regulatory Agency (MHRA) comprehensive standard, and the Bayesian confidence propagation neural network (BCPNN) were used to detect signals of risk for congenital malformations in offspring following maternal use of tetracyclines during pregnancy. A signal that met the threshold criteria of all above 5 methods was considered as a risk signal. Based on population-based cohort of the drug exposures and adverse pregnancy outcomes (DEEP) data from January 2013 to December 2021 in Xiamen City, propensity score matching (PSM)-based Poisson regression was applied to evaluate the association between the first-trimester tetracyclines exposure and congenital malformations in offspring. Adjusted relative risk (a RR) and its 95% confidence interval ( CI) were calculated. Sensitivity analysis was conducted to validate the reliability of the results. Results:A total of 304 098 reports of adverse events during pregnancy were obtained from the FAERS and CVAR databases. Among them, 5 028 reports were related to tetracyclines, including 1 026 reports of congenital malformations in offspring, involving congenital malformations of musculoskeletal system, other digestive system, and other congenital malformations. Signal detection results suggested that tetracyclines may be a risk signal for above congenital malformations in offspring. The DEEP data included 411 936 pregnant women. After PSM, 240 pregnant women exposed to tetracyclines were included. The results showed no significant association between the first-trimester tetracyclines exposure and congenital malformations in offspring (a RR=0.75, 95% CI: 0.26-2.17), sensitivity analysis also showed no correlation. Conclusions:Data mining from the FAERS and CVAR databases suggests a potential association between tetracyclines use during pregnancy and congenital malformations in offspring. However, the DEEP data study shows no significant correlation.

Sepsis constitutes a predominant cause of mortality in critically ill patients,and early determination of the type of infection is crucial for influencing patient management and forecasting outcomes.Currently,blood culture serves as the gold standard for diagnosing sepsis.Yet,its limitations,such as a lengthy culture period and low positivity rate,hinder its ability to provide a microbiological basis for early initiation of antimicrobial therapy in clinical practice.Serological markers have engendered significant interest due to their convenience and rapid detection in vitro,emerging as indispensable laboratory indices for early inference of infection.In recent years,with extensive research on sepsis across diverse academic domains,numerous novel serological markers exhibit promise in diagnosing sepsis.Therefore,this review explores the characteristics and applicatron value of new serological markers for early diagnosis of sepsis,and reviews them in combination with relevant predictive models,bringing new ideas for early clinical diagnosis of sepsis.

Somatostatin receptor 1 (SSTR1) is a crucial therapeutic target for various neuroendocrine and oncological disorders. Current SSTR1-targeted treatments, including the first-generation somatostatin analog lanreotide (Lan) and the second-generation analog pasireotide (Pas), show promise but encounter challenges related to selectivity and efficacy. This study presents high-resolution cryo-electron microscopy structures of SSTR1 complexed with Lan or Pas, revealing the distinct mechanisms of ligand-binding and activation. These structures illustrate unique conformational changes in the SSTR1 orthosteric pocket induced by each ligand, which are critical for receptor activation and ligand selectivity. Combined with the biochemical assays and molecular dynamics simulations, our results provide a comparative analysis of binding characteristics within the SSTR family, highlighting subtle differences in SSTR1 activation by Lan and Pas. These insights pave the way for designing next-generation therapies with enhanced efficacy and reduced side effects through improved receptor subtype selectivity.