Dry eye disease(DED)and depression(DEP), though anatomically and clinically distinct, show significant epidemiological, pathophysiological, and prognostic interplay. Their co-occurrence has risen sharply in recent years, yet the mechanisms driving this comorbidity remain under-investigated. This review systematically synthesizes current evidence, highlighting that pro-inflammatory cytokines, neuro-regulatory imbalance, mitochondrial dysfunction, and gut-microbiota dysbiosis constitute a shared molecular network, while sleep deprivation and antidepressant use further amplify the vicious cycle. By identifying limitations in existing studies, this review proposes future research directions to offer new theoretical and clinical insights for managing DED-DEP comorbidity.

AIM: To explore the factors associated with significant corneal astigmatism during the perioperative period in patients with pterygium. METHODS: Patients with primary pterygium presenting at Shanxi Eye Hospital between February and June 2025 were enrolled. All patients underwent medical history collection. Pre- and postoperative data were obtained using Pentacam, anterior segment photography, Image J software, and anterior segment optical coherence tomography(AS-OCT). All patients underwent pterygium excision combined with autologous bulbar conjunctival flap transplantation under local infiltration anesthesia. RESULTS: A total of 76 patients(76 eyes)with pterygium were finally enrolled(30 males, 46 females)with a mean age of 62.2±8.2 y. The mean length of corneal invasion by pterygium was 3.61±0.89 mm, the mean depth of invasion into the anterior corneal surface was 0.15±0.09 mm, and the median area of corneal invasion was 10.25(6.90, 18.75)mm2. The median preoperative corneal astigmatism was 1.50(0.70, 5.45)D. Median astigmatism was 0.8(0.40, 1.28)D at 2 wk postoperatively and 0.60(0.30, 1.15)D at 1 mo postoperatively. Patient age showed a positive correlation with preoperative astigmatism, and with residual astigmatism at 2 wk and 1 mo postoperatively(all P<0.05). The length of corneal invasion was positively correlated with preoperative astigmatism and residual astigmatism at both postoperative timepoints(P<0.01). The depth of invasion showed no significant linear correlation with astigmatism at any stage(P=0.250, 0.761, 0.686). The area of corneal invasion was positively correlated with astigmatism at all stages(P<0.01). Patients were grouped based on significant astigmatism(≥1.0 D)and non-significant astigmatism(<1.0 D), after adjusting for other variables, age(P=0.031)and the area of corneal invasion(P=0.004)were identified as risk factors for significant astigmatism. Pterygium invasion length was not significant factors(P>0.05). Receiver operating characteristic(ROC)analysis showed the highest area under the curve(AUC)for the invasion area(AUC=0.915). CONCLUSION: Significant preoperative corneal astigmatism in pterygium patients is correlated with patient age, the length of corneal invasion, and the area of invasion. The area of pterygium invasion into the cornea is the strongest predictor of significant preoperative corneal astigmatism.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

Objective To investigate the expression of carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) in esophageal squamous cell carcinoma (ESCC) and analyze its correlation with immune cell infiltration and patient prognosis. Methods Three ESCC datasets (GSE161533, GSE26886, and GSE23400) from the GEO database were analyzed to identify differentially expressed genes. CEACAM6 was identified as a key gene through survival analysis. Its expression, prognostic value, and relationship with immune cell infiltration were further explored using databases, such as TIMER. Tissue samples were collected from 162 patients with ESCC. Immunohistochemistry was performed to detect the expression of CEACAM6, immune cell markers (CD4, CD8, CD20, and CD56), and immune checkpoint molecules (HHLA2 and CD40LG). Correlations between CEACAM6 expression and clinicopathological features, immune cell infiltration, and immune checkpoints were analyzed. Results Bioinformatic analysis and clinical sample validation confirmed that CEACAM6 expression was significantly upregulated in ESCC tissues compared with adjacent nontumor tissues (P<0.05). High CEACAM6 expression was closely associated with advanced clinical stage (AJCC Ⅲ-Ⅳ), high T stage (T3-T4), lymph node metastasis, nonulcerative type, and poor prognosis. Furthermore, CEACAM6 expression levels were positively correlated with the infiltration density of CD8⁺ T cells, CD4⁺ T cells, and CD20⁺ B cells within the tumor microenvironment and with the expression of the immune checkpoint molecules HHLA2 and CD40LG (all P<0.05). Conclusion CEACAM6 serves as an independent poor prognostic factor for ESCC. Its high expression is implicated in the modulation of the tumor immune microenvironment by correlating with specific immune cell infiltration and immune checkpoint molecules, suggesting its potential as a novel prognostic biomarker and immunotherapeutic target for ESCC.

ObjectiveTo develop a standardized classification model for traditional Chinese medicine （TCM） syndrome patterns of mixed hemorrhoids using multi-center real-world data， and unveil their distribution patterns and core risk factors， thereby providing evidence-based support for standardizing TCM syndrome differentiation and implementing precision interventions. MethodsA multi-center cross-sectional study was conducted， enrolling 13 283 mixed hemorrhoid patients from eight hospitals in Jiangsu Province between September 1st， 2023 and December 31st， 2024. DeepSeek-R1-Distill-Qwen-7B and LLaMA-3.3 large language models （LLM） were integrated with latent class analysis （LCA） to perform unsupervised learning and latent class modeling of TCM symptomatology. Potential risk factors were screened via univariate analysis， followed by logistic regression to identify independent risk factors for each syndrome pattern. ResultsThe model's performance indicators were stable and reliable across different clinical data types，i.e. in the outpatient records， past medical history （F1=99.7%）， current medical history （F1=94.9%）， and specialist examination （F1=90.7%）； in inpatient records， past medical history （F1=98.2%）， current medical history （F1=91.2%）， specialist examination （F1=90.3%）， and discharge status （F1=90.6%）. Latent class mode-ling identified four core TCM syndrome patterns including spleen deficiency and qi sinking syndrome （915 cases， 6.89%）， damp-heat pouring downward syndrome （10 820 cases， 81.46%）， qi stagnation and blood stasis syndrome （1252 cases， 9.43%）， and wind injuring intestinal collaterals syndrome （296 cases， 2.22%）， with respective latent class probabilities of 0.069， 0.815， 0.094， and 0.022. Logistic regression demonstrated that gender， age， disease duration， hypertension， diabetes， hyperlipidemia， constipation， smoking history， and alcohol consumption were independent risk factors for pattern differentiation （P＜0.05）. The efficacy validation evaluation revealed that the cure rates for patients with spleen deficiency and qi sinking syndrome and qi stagnation and blood stasis syndrome were higher than those for patients with damp-heat pouring downward syndrome （adjusted P＜0.05）， with no statistically significant differences among other syndrome patterns. ConclusionDamp-heat pouring downward syndrome is the predominant syndrome in mixed hemorrhoids. Gender， age， disease duration， hypertension， diabetes， hyperlipi-demia， constipation， smoking history， and alcohol consumption are independent risk factors for the differentiation of syndrome types.

OBJECTIVE To form an expert consensus on the clinical application of parenteral direct thrombin inhibitors （DTIs） in patients during the perioperative period. METHODS Led by Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital （the Affiliated Hospital of UESTC）， a multidisciplinary working group was established. Through literature review and the Delphi method， clinical questions related to the rational perioperative use of parenteral DTIs were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” framework； systematic searches were conducted in CNKI， Medline， Embase and other databases. Relevant evidence from randomized controlled trials and cohort studies was included and synthesized. Evidence quality was assessed using the Grades of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through multiple rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven recommendations （each with an expert consensus rate exceeding 90%） on the use of parenteral DTIs in perioperative patients were developed. These recommendations specify drug selection， dosing ranges， key monitoring points， and safety management strategies for parenteral DTIs in various scenarios， including the perioperative period of ventricular assist device implantation， the perioperative period of cardiac surgery， perioperative patients with lower-extremity atherosclerotic disease， the perioperative period of percutaneous coronary intervention in patients with acute coronary syndrome， the perioperative period of carotid artery stenting in patients with carotid stenosis， the perioperative period of patients with right heart thrombosis， and patients who develop related thrombosis and dysfunction after a central venous catheter insertion. In addition， warning and management pathways for perioperative bleeding and thrombotic events were proposed. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in perioperative period.

Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

ObjectivePost-ischemic acute inflammation and the subsequent persistent dysregulation of the immune microenvironment represent major pathological drivers that aggravate neuronal injury and severely restrict functional recovery following ischemic stroke. Although current reperfusion therapies partially restore blood flow, they fail to effectively modulate the secondary inflammatory cascade and oxidative stress, which remain critical barriers to neurological restoration. To address this challenge, this study aimed to engineer and systematically evaluate a biomimetic nanosystem composed of transforming growth factor-β1 (TGF-β1)-loaded platelet membrane-camouflaged lipid nanoparticles (PLP). This nanosystem was designed to achieve dual lesion-targeted delivery and immune microenvironment remodeling. By verifying its spatiotemporal accumulation, anti-inflammatory activity, and neuroprotective efficacy, we sought to establish an integrated therapeutic strategy that simultaneously enables lesion targeting, immune regulation, and functional recovery after ischemic injury. MethodsThe physicochemical properties of PLP, including hydrodynamic particle size, zeta potential, structural stability, and morphology, were characterized using dynamic light scattering, zeta potential analysis, and transmission electron microscopy. The preservation of platelet membrane-derived adhesion and immunoregulatory proteins was confirmed by SDS-PAGE through comparative analysis of protein band profiles between PLP and native platelet membranes. The in vitro biological activities of PLP were evaluated using two complementary cellular models. LPS-induced M1-polarized RAW264.7 macrophages were employed to assess inflammatory modulation, while oxygen glucose deprivation/reperfusion (OGD/R)-induced BV2 microglial cells and SH-SY5Y neuronal cells were utilized to investigate neuroinflammatory regulation and neuronal protection. For in vivo validation, a transient middle cerebral artery occlusion (tMCAO) mouse model was established to mimic ischemia-reperfusion injury. The spatiotemporal biodistribution and lesion-targeting capability of the PLP were monitored through live fluorescence imaging. Therapeutic efficacy was comprehensively evaluated by triphenyltetrazolium chloride (TTC) staining, glial fibrillary acidic protein (GFAP) immunofluorescence analysis, body weight monitoring, and neurological severity score (NSS) assessment. ResultsPLP nanoparticles displayed a uniform spherical morphology, nanoscale particle size distribution, and stable negative surface charge, indicating favorable colloidal stability and circulation potential. SDS-PAGE results confirmed the effective retention of key platelet membrane proteins associated with endothelial adhesion, immune evasion, and inflammatory regulation, demonstrating the successful biomimetic construction. Optimal therapeutic concentrations were determined in OGD/R-induced BV2 cells, where PLP exhibited excellent cytocompatibility and anti-inflammatory activity.In vitro experiments demonstrated that PLP significantly inhibited the polarization of RAW264.7 macrophages toward the pro-inflammatory M1 phenotype and markedly reduced neuronal apoptosis under ischemia-reperfusion conditions. In vivo fluorescence imaging revealed that PLP rapidly accumulated in the ischemic brain hemisphere and maintained prolonged retention for up to 7 d, suggesting enhanced lesion-specific targeting and sustained drug release. Compared with control group, PLP treatment significantly reduced cerebral infarct volume, attenuated reactive astrogliosis, improved weight recovery, and accelerated neurological functional restoration, as reflected by significantly improved NSS scores. ConclusionThis study establishes a multifunctional biomimetic nanoplatform that integrates platelet membrane-mediated active targeting with the anti-inflammatory, antioxidative, and neuroprotective properties of TGF-β1. The PLP system enables rapid lesion homing and long-term retention while synergistically regulating the post-stroke inflammatory microenvironment by suppressing pro-inflammatory immune activation, reducing neuronal apoptosis, and limiting excessive astrocyte reactivity. Importantly, this study proposes a conceptually therapeutic paradigm that combines targeted delivery with immune microenvironment remodeling to achieve comprehensive neurovascular protection. These findings provide strong experimental evidence supporting the translational potential of biomimetic nanotherapeutics as next-generation precision interventions for ischemic stroke.

ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.