Functional constipation （FC） is a clinically common functional bowel disorder characterized by a protracted course and associations with various chronic disorders and psychological abnormalities. Although not life-threatening， FC significantly impairs patients' quality of life. FC subtypes include slow-transit constipation （STC）， defecatory disorder （DD）， and normal-transit constipation （NTC）. The pathological mechanisms underlying FC have not been fully elucidated， and overall clinical efficacy remains unsatisfactory. Animal models of FC serve as essential tools for the study of disease mechanisms and the development of novel therapeutics. This article systematically reviews the current state of research on the animal models of FC and identifies that rodents， particularly rats and mice， are the most commonly used species. Dogs and pigs are also employed in complex intervention studies due to their physiological similarities to humans， though their use is limited by housing challenges and ethical considerations. Induction methods vary across different FC subtypes. STC models are primarily established with chemical agents such as loperamide or compound diphenoxylate. DD modeling often involves low-fiber diets combined with methylene blue injection or rectal narrowing. NTC modeling mainly relies on low-fiber dietary interventions. In addition， disease-syndrome combination models based on traditional Chinese medicine （TCM） theory have been developed， encompassing excess patterns such as heat accumulation， cold accumulation， and Qi stagnation， as well as deficiency patterns including Qi deficiency， blood deficiency， Yin deficiency， and Yang deficiency. These are achieved through an approach of disease model + syndrome induction， enabling the integration of mechanisms from both Western and TCM perspectives. Models are evaluated from two aspects： disease and syndrome manifestations （e.g.， colonic transit， secretory function， and TCM syndrome indicators such as mental state and body weight） and disease mechanisms （e.g.， enteric nervous system， interstitial cells of Cajal， smooth muscle cells， gut microbiota， and metabolites）. However， current research still faces challenges such as poor consistency in some models， non-specific interference in mechanism interpretation， insufficient studies on NTC， and lack of TCM tongue and pulse diagnosis in evaluation. Future efforts should focus on optimizing model stability and specificity to provide a more reliable experimental basis for investigating the pathological mechanisms of FC and developing therapeutic agents.

Triclosan (TCS) and triclocarban (TCC) are widely used synthetic broad-spectrum antibacterial agents that can enter the human body through the skin, gastrointestinal tract, and other pathways. More and more studies have found that exposure to TCS and TCC can affect human health, but currently, review reports on the health effects of human exposure to TCS and TCC are limited. Therefore, this study reviewed population studies on the relationship between TCS and TCC exposure and health effects by searching the PubMed database, summarized the associated health outcomes, and elucidated the biological mechanisms. A total of 56 studies were retrieved, among which cross-sectional studies (25 studies, 44.64%) and cohort studies (25 studies, 44.64%) accounted for a relatively large proportion, while case-control studies (6 studies, 10.72%) were relatively few. Studies on TCS exposure (48 studies, 85.71%) were far more prevalent than those on TCC exposure (2 studies, 3.57%). The remaining 6 studies involved both TCS and TCC exposure. The research results revealed that TCS exposure was associated with male and female abnormal reproductive functions, fetal growth restriction, abnormal behavior development in children, obesity, gestational diabetes mellitus (GDM), and immune-related diseases. Although the results of different studies show significant differences, they have indicated that exposure to TCS is a potential risk factor for these health problems. Due to the limited number of studies, the evidence for the relationship between TCC exposure and most of the aforementioned health effects is insufficient. Population studies and in vitro and in vivo studies have shown that exposure to TCS and TCC can interfere with the microbial homeostasis, the endocrine system, oxidative stress and immune function of the body, which are potential mechanisms causing adverse health effects. In the future, large-scale prospective cohort studies, as well as in vivo and in vitro studies, are still needed to further clarify the associations between TCS and TCC exposure and health effects, and to deeply explore its mechanism of action. These efforts will provide references for clarifying the human health hazards of TCS and TCC exposure and formulating targeted prevention and control strategies.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

ObjectiveTo investigate the potential mechanism of Yiqi Yangyin Huoxue Formula （益气养阴活血方， YYHF） in the treatment of membranous nephropathy （MN） based on the NOX4-mediated stromal cell-derived factor-1α（SDF-1α）/CXC chemokine receptor 4 （CXCR4） signaling pathway. MethodsA total of 42 male SD rats were randomly divided into blank group （n=6） and modeling group （n=36）. The modeling rats were given a single injection of sheep antirat Fx1A （6 ml/kg） serum into the tail vein to establish MN model. Thirty-six rats with successful modeling were further divided into model group （normal saline， 10 ml/kg）， benazepril group （10 mg·kg^-1·d^-1）， the medium-dose YYHF group （11.0 g·kg^-1·d^-1） and high-dose YYHF group （22.0 g·kg^-1·d^-1）， with 9 rats in each group. All groups received daily intragastric administration for 6 consecutive weeks. During the experimental period， the general condition of rats in each group was observed. After gavage administration finished， a fully automated biochemical analyzer was used to measure the 24-hour urine total protein （24 h-UTP） and serum biochemical parameters， including albumin （ALB）， aspartate aminotransferase （AST）， blood urea nitrogen （BUN）， serum creatinine （SCr）， total cholesterol （TC）， and triglyceride （TG）. Hematoxylin-eosin （HE） staining and periodic acid-silver metheramine （PASM） staining were used to observe the histopathological changes of renal tissues in each group of rats. The levels of superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were detected by ELISA. The protein expression levels of NOX4， SDF-1α， CXCR4， Nrf2， nuclear factor kappa B subunit p65 （NF-κB p65） and podocyte slit diaphragm protein nephrin in rat renal tissues were detected by Western Blotting. The mRNA expressions of NOX4， SDF-1α， CXCR4， Nrf2， NF-κB p65 and Nephrin in renal tissues were detected by real-time fluorescence quantitative polymerase chain reaction （RT-PCR）. ResultsCompared to the blank group， rats in the model group exhibited typical features of MN， including lethargy， reduced activity， dull and coarse fur， marked edema， and massive proteinuria. Compared to the model group， these abnormal conditions were improved to varying degrees in all treatment groups. The high-dose YYHF group showed a level of improvement comparable to that of the benazepril group， with overall recovery superior to that of the medium-dose YYHF group. Compared to the blank group， the model group showed increased levels of 24 h-UTP， BUN， SCr， TC and TG， decreased level of ALB， increased levels of MDA and protein and mRNA expressions of NOX4， SDF-1α， CXCR4 and NF-κB p65 in renal tissue， along with decreased levels of SOD and protein and mRNA expressions of Nrf2， Nephrin （P＜0.01）， accompanied by severe renal pathological damage. Compared to the model group， the benazepril and the medium- and high-dose YYHF groups showed significant improvements in the above indicators （P＜0.01）， along with alleviation of renal pathological injury. The 24 h-UTP level in the high-dose YYHF group was lower than that in the medium-dose group （P＜0.01）， while no statistically significant difference was observed among the other treatment groups （P＞0.01）. ConclusionYYHF may alleviate oxidative stress and inflammatory responses by down-regulating the expression of NOX4 and inhibiting the SDF-1α/CXCR4-Nrf2 signaling pathway， thereby improving podocyte damage and protecting renal function.

Objective To analyze the correlation between cardiac function and degree of coronary artery lesion in elderly patients with coronary heart disease. Methods A total of 110 elderly patients with coronary heart disease and 30 elderly people without coronary heart disease (non-coronary heart disease group) in the Third People's Hospital of Chengdu were selected for the study. Based on Gensini score, the patients with coronary heart disease were classified into mild, moderate and severe lesion groups. The echocardiographic indicators and myocardial injury indicators [cardiac troponin I (cTnI), creatine kinase (CK), creatine kinase isoenzyme (CK-MB)] were compared among the groups. The correlation between cardiac function indicators and degree of coronary artery lesion and the evaluation value of various indicators on severe coronary artery lesion were analyzed. Results The left ventricular ejection fraction (LVEF) was represented as severe lesion groupmoderate lesion group>mild lesion group> non-coronary heart disease group (P<0.05). LVEF showed a negative correlation with degree of coronary artery lesion (P<0.05), while LVEDD, LVESD, cTnI, CK and CK-MB all exhibited positive correlations with degree of coronary artery lesion (P<0.05). The combined detection of the above indicators demonstrated superior evaluation efficiency on severe coronary artery lesion compared to any single indicator (P<0.05). Conclusion There is a significant correlation between cardiac function and degree of coronary artery lesion in elderly patients with coronary heart disease. Comprehensive evaluation of these indicators is conducive to clinical disease risk stratification and individualized treatment.

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

During habitation on low-Earth-orbit (LEO) space stations, astronauts are exposed to a combination of orbital microgravity, space radiation, an enclosed and artificially controlled cabin environment, altered sleep-wake rhythms, and sustained operational and psychosocial demands. These factors can modify sensorimotor inputs, body-fluid distribution, arousal state, and task-related neural processing, thereby affecting brain function and behavior. Because evidence from real spaceflight remains limited by small samples, heterogeneous mission durations, and different measurement time points, this review integrates findings from real human spaceflight with relevant ground-based analog studies while treating real orbital studies as the primary source of evidence. We focus on electroencephalography (EEG) and event-related potentials (ERPs), structural and functional neuroimaging, and sensorimotor and cognitive outcomes, with particular attention to the direction, anatomical distribution, temporal course, and possible physiological significance of the reported changes. EEG studies indicate that long-duration spaceflight is associated with increased resting-state beta activity, particularly in sensorimotor and frontotemporal regions, together with state-dependent alterations in beta-band functional connectivity. In contrast, alpha source power and functional connectivity associated with the default mode network are reduced during long-duration missions, and some of these effects may persist into the early postflight period. Task-related electrophysiological findings further suggest that sustained mental workload can weaken frontocentral theta-temporoparietal gamma phase-amplitude coupling, whereas in-flight decision-making is accompanied by reduced P300 amplitude and reorganization of feedback-related potentials. Short-duration missions, however, have shown relative preservation of posterior dominant rhythms and some ERP measures, indicating that mission duration, recording state, and task demands substantially influence the observed electrophysiological phenotype. Neuroimaging provides complementary evidence at structural and network levels. Long-duration spaceflight has been associated with upward brain displacement, ventricular and cerebrospinal fluid expansion, regional gray- and white-matter remodeling, and alterations in white-matter structural connectivity. Functional magnetic resonance imaging (fMRI) studies further indicate reorganization of vestibular-sensorimotor, visual, and default mode networks. Some network changes recover after return to Earth, whereas others may remain detectable for months. Importantly, most MRI measurements are obtained after landing rather than in orbit; therefore, postflight findings may reflect a mixture of in-flight adaptation, the rapid transition back to 1 g, and subsequent readaptation rather than a single spaceflight effect. Behavioral evidence is most consistent for sensorimotor function. Early after return, astronauts frequently show impaired postural control, gait, spatial orientation, and coordination, consistent with reweighting among vestibular, visual, and proprioceptive information. By comparison, simple cognition and some critical operational tasks are often preserved. More subtle or high-load processes-including sustained attention, feedback evaluation, temporal processing, error monitoring, and metacognitive calibration may be more sensitive than global cognitive performance. This dissociation between neural change and preserved behavior suggests that altered brain activity should not automatically be interpreted as functional deterioration. Integrating the available modalities, we propose that LEO space-station habitation is better characterized by system-specific and stage-dependent neural adaptation than by a generalized increase or decline in brain function. The most coherent cross-modal pattern involves sensorimotor reorganization: reduced gravitational reference and weight-bearing feedback under microgravity may drive reweighting of vestibular, visual, and proprioceptive inputs, accompanied by changes in beta activity and vestibular-sensorimotor networks and followed by transient postflight sensorimotor deficits. A second major process involves fluid-related structural remodeling, in which cephalad fluid shifts and altered hydrostatic gradients may contribute to changes in cerebrospinal fluid spaces, ventricular volume, and brain tissue configuration. Resting-state and cognitive electrophysiological changes likely represent additional adjustments in network regulation and resource allocation, but their functional interpretation remains more dependent on sleep, workload, recording conditions, and individual differences. Future studies should move beyond isolated pre-post comparisons and group averages toward standardized longitudinal designs spanning preflight, multiple in-flight time points, and postflight recovery. Synchronized assessment of brain function, behavior, sleep, and key environmental parameters should be used to characterize individual adaptation trajectories and determine which neural changes reflect successful compensation, which predict delayed recovery, and which have genuine value for brain-health risk prediction and individualized countermeasures.

Objective: To genotype 50 RhD variant samples from Guangzhou, China, using our previously established genotyping strategy, thereby providing guidance for transfusion management and antenatal monitoring in RhD-variant individuals. Methods: Between June and August 2024, fifty samples identified as RhD variants during RhD-negative confirmation testing at Guangzhou Blood Center were collected. Serological testing for the D antigen was performed with two different anti-D reagents, and the epitope profiles of the D antigen were determined using a commercial panel of monoclonal anti-D reagents containing nine kinds of monoclonal anti-D. Genomic DNA was extracted, and high-resolution melting (HRM) analysis was applied to detect the Asian-type DEL (RHD 1227A). Subsequently, RHD genotyping was carried out using Multiplex Ligation-dependent Probe Amplification (MLPA) and Sanger sequencing. Results: Among the 50 D variant samples, 17 (34.0%) Asian type DEL samples were detected by HRM, including 13 cases with RHD DEL1/01N.01 genotype and 4 cases with RHD DEL1/DEL1 genotype. Eleven (11/50, 22.0%) samples were typed as DVI by the epitope profiles of D antigen. The epitope profiles of D antigen combined with Sanger sequencing of exon 6 identified 5 (5/50, 10.0%) cases of RHD weak partial 15/01N.01. MLPA combined with Sanger sequencing identified two cases of RHD DVI.3/DEL1, representing 4.0% (2/50) of the samples. Additionally, the following RHD genotypes were each detected in one case: RHD weak D type 18/01N.04, RHD weak D type 72/01N.01, RHD weak D type 95/DEL1, RHD weak D type 114/DEL1, RHD weak D type 136/DEL1, RHD weak D type 147/01N.01, RHD 496G/496G, RHD 536C/01N.01, RHD 689A/689A, RHD 689A/DEL1, RHD DEL32/DEL1, RHD DV.1/01N.01, RHD DV.5/01N.01, RHD 01.01/01N.01, and RHD 01/01N.01. Conclusion: Fifty D variant individuals were typed using our previously established serological and molecular approach. These findings provide guidance for precision transfusion therapy in RhD variant patients and inform evidence-based decisions regarding anti-D immunoglobulin prophylaxis for RhD variant pregnant women.

Malnutrition significantly impacts patient outcomes and prognosis.Enteral nutrition(EN)serves as a critical nutritional support strategy for hospitalized patients,particularly those who are critically ill,by effectively addressing malnutrition.However,nutritional requirements vary substantially based on disease state and individual characteristics.Artificial intelligence(AI)enables precision EN management through its advanced data processing and predictive analytics capabilities.This review examines current applications of AI in precision EN delivery,identifies existing challenges,and proposes solutions.We aim to inform future research directions and facilitate AI integration into clinical EN practice,ultimately optimizing patient-centered nutritional care.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.