Objective To analyze the unexamined items and situations in occupational health examinations of radiation workers, and provide a reference for the revision of occupational health examination standards for radiation workers. Methods A total of 29 630 radiation workers who underwent occupational health examinations at The Third People’s Hospital of Henan Province in 2023 were selected, and the non-examination rates were statistically analyzed according to occupation, gender, and age. Results The overall non-examination rate of non-medical radiation workers was significantly lower than that of the medical radiation workers (P<0.05). The non-examination rate of chest X-rays among medical radiation workers was significantly higher than that of non-medical radiation workers (P<0.05), while no significant differences were found in other items (P>0.05). Gender-stratified analysis showed that the non-examination rate of routine urine tests was higher in females than in males in both medical and non-medical radiation workers (P<0.05). Age-stratified analysis revealed no significant differences in non-examination rates among different age groups in non-medical radiation workers (P>0.05), whereas the chest X-ray non-examination rate was relatively high in medical radiation workers under 30 years old (P<0.05). Conclusion Significant differences were observed in the non-examination rates of occupational health examinations among radiation workers based on occupation, gender, and age. The overall non-examination rate was relatively low in non-medical radiation workers.

Background: The tight junction protein claudin18.2 (CLDN18.2) has been implicated in poor prognosis and suboptimal immunotherapy response in gastric cancer (GC). This study investigates the clinicopathological relevance of CLDN18.2 expression and its association with molecular subtypes in GC patients from a high-incidence region, combining transcriptomic and proteomic approaches to explore how CLDN18.2 contributes to progression and metastasis. Methods: A retrospective cohort of 494 GC patients (2019–2024) underwent immunohistochemical analysis for CLDN18.2, Epstein-Barr virus (Epstein–Barr virus–encoded RNA), p53, human epidermal growth factor receptor 2 (HER2), and mismatch repair proteins (MLH1, MSH2, PMS2, and MSH6). CLDN18.2 positivity was defined as moderate to strong (2+/3+) membranous staining in ≥75% of tumor cells. Clinicopathological correlations, biomarker associations, and survival outcomes were evaluated. Transcriptomic and proteomic sequencing was performed to explore molecular mechanisms. Results: CLDN18.2 positivity was observed in 26.9% (133/494) of gastric adenocarcinomas. CLDN18.2-positive tumors correlated with TNM stage (p = .003) and shorter overall survival (p = .018). No associations were identified with age, sex, HER2 status, microsatellite instability, or Epstein-Barr virus infection. Transcriptomic profiling revealed CLDN18.2-high tumors enriched in pathways involving cell junction disruption, signaling regulation, and immune modulation. Proteomic profiling showed that tumors with high CLDN18.2 were enriched in multiple mechanism-related pathways such as integrated metabolic reprogramming, cytoskeletal recombination, immune microenvironment dysregulation, and pro-survival signaling. These mechanisms may collectively contribute to tumor progression and metastasis. Conclusions CLDN18.2 overexpression is associated with poor prognosis in GC patients. Transcriptomic and proteomic analyses demonstrate that CLDN18.2 promotes tumor progression and metastasis, underscoring its potential as an independent prognostic factor in regions with a high incidence of GC.

ObjectiveTo perform metabolic associated fatty liver disease （MAFLD） screening among individuals attending community health institutions， to identify the patients at a low， moderate or high risk of advanced liver fibrosis based on fibrosis-4 index （FIB-4） and liver stiffness measurement （LSM） measured by liver transient elastography， and to implement stratified management. MethodsA cross-sectional study was conducted among 630 individuals attending Beijing Baizhifang Community Health Service Center from January to July 2024， and they were divided into MAFLD group and non-MAFLD group. According to body mass index （BMI）， the MAFLD group was further divided into lean MAFLD group （BMI<23 kg/m²） and non-lean MAFLD group （BMI≥23 kg/m²）. The above groups were compared in terms of demographic features， laboratory markers， hepatic steatosis， and LSM. Fibrosis risk stratification was performed for MAFLD patients based on FIB-4 and LSM， and a closed-loop management system involving referral to tertiary hospitals and follow-up at community health institutions was implemented. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsThere were 445 individuals （70.6%） in the MAFLD group and 185 individuals （29.4%） in the non-MAFLD group. Compared with the non-MAFLD group， the MAFLD group had a significantly lower proportion of male individuals （χ²=4.299， P<0.05）， a significant reduction in the level of high-density lipoprotein cholesterol （Z=3.484， P<0.05）， and significant increases in body weight （Z=-7.366， P<0.05）， BMI （Z=-9.740， P<0.05）， waist circumference （Z=-6.397， P<0.05）， hip circumference （Z=-6.935， P<0.05）， alanine aminotransferase （ALT） （Z=-2.765， P<0.05）， fasting blood glucose （Z=-3.646， P<0.05）， triglyceride （TG） （Z=-6.569， P<0.05）， total cholesterol （Z=-2.033， P<0.05）， low-density lipoprotein cholesterol （Z=-2.935， P<0.05）， controlled attenuation parameter （CAP） （Z=-19.784， P<0.05）， and LSM （Z=-5.703， P<0.05）. Within the MAFLD group， there were 124 individuals （27.9%） in the lean MAFLD group and 321 individuals （72.1%） in the non-lean MAFLD group. Compared with the non-lean MAFLD group， the lean MAFLD group had significantly lower body weight （Z=-12.414， P<0.05）， BMI （Z=-16.363， P<0.05）， waist circumference （Z=-7.733， P<0.05）， hip circumference （Z=-8.595， P<0.05）， ALT （Z=-2.835， P<0.05）， aspartate aminotransferase （Z=-1.972， P<0.05）， TG （Z=-2.407， P<0.05）， CAP （Z=-4.429， P<0.05）， degree of steatosis （χ²=16.588， P<0.05）， and LSM （Z=-3.908， P<0.05）. Based on the results of FIB-4 and LSM， 76 patients at a moderate or high risk of liver fibrosis should be referred to a higher-level hospital for further management. ConclusionThe detection rate of MAFLD reaches 70.6% among the individuals attending community health institutions， among whom 76 （17.1%） should be referred to a higher-level hospital. Establishing a liver fibrosis risk stratification and management system based on FIB-4 and LSM among MAFLD individuals in communities provides a practical pathway for chronic disease management and referral system construction in community health institutions.

China is a high-incidence region for gastric cancer globally. The disease is characterized by a high morbidity rate, low early diagnostic rate, and poor long-term outcomes, imposing a significant burden on both patients and society. Therefore, exploring the pathogenesis of gastric cancer, developing novel therapeutic strategies, and identifying new drug targets is of great importance. Telomerase expression is broadly associated with cancer cell targeting, and its up-regulation is one of the key factors driving the initiation and progression of gastric cancer. Additionally, telomerase is intricately involved in the regulation of autophagy and autophagy-associated cell death. While autophagy can induce chemoresistance, excessive autophagy may lead to cell death, which also constitutes one of the mechanisms of chemotherapy. Telomerase not only directly contributes to gastric cancer pathogenesis but also indirectly influences its development and treatment by modulating autophagy and autophagic cell death. Therefore, telomerase holds promise as a novel therapeutic target in gastric cancer.
Humans ; Stomach Neoplasms/genetics* ; Telomerase/genetics* ; Autophagy/physiology*

Objective To analyze the clinical features of chronic obstructive pulmonary disease (COPD) patients with heart failure (HF) in Nanjing and explore the influencing factors. Methods A total of 773 COPD inpatients were selected from January 2021 to January 2024 in Nanjing Combined Hospital of Traditional Chinese and Western Medicine, Nanjing Qixia District Hospital, Nanjing Lishui District People's Hospital, Nanjing Pukou District Hospital of Traditional Chinese Medicine and Nanjing First Hospital., and were divided into 2 groups according to the presence or absence of combined HF. The general data and medical records of the two groups were compared, the clinical characteristics of COPD patients with HF were summarized, and the influencing factors of COPD patients with HF were analyzed by multivariate logistic regression. Results Among the 242 patients (31.31%) with COPD had HF, chronic paroxysmal dyspnea was the most common first symptom, 169 patients (69.83%) had left heart failure, 63 patients (30.17%) were diagnosed as right heart failure or global heart failure , 17 patients (7.02%) had myocardial infarction. Multivariate logistic regression analysis showed that the risk of HF was 1.678 times and 1.691times higher in COPD groups ≥ 50 years old and male COPD groups than in < 50 years old and female groups, respectively; the risk of HF was 1.491 times higher in COPD groups engaged in physical work than in physical work groups; the risk of HF was 1.447 times and 1.580 times higher in COPD groups with hypertension and coronary heart disease than in COPD groups without hypertension and coronary heart disease, respectively; the risk of HF was 1.859 times higher in COPD groups smoking>400 vial/year than in COPD groups≤400 vial/ year; the risk of HF was 1.757 times higher in COPD groups with acute exacerbation frequency≥2 times/year than in COPD groups<2 times/year; the above differences were statistically significant (P<0.05). Conclusion Attention should be paid to elderly, male and heavy physical work group of COPD patients. Active treatment of hypertension and coronary heart disease, effective tobacco control and reduction of the frequency of acute exacerbation are effective ways to reduce the risk of HF in COPD patients in Nanjing.

BackgroundSchizophrenia is a highly heterogeneous disease with different clinical subtypes. Artificial intelligence technology represented by deep learning models has provided considerable benefits for the electroencephalogram （EEG）-based schizophrenia diagnosis， treatment and research， however， to date little research has been conducted regarding any of these benefits among Chinese schizophrenic patients. ObjectiveTo investigate the application of deep learning techniques utilizing EEG parameters for the diagnosis of first-episode schizophrenia and grading of EEG abnormalities in patients， with the aim of contributing to improved clinical diagnosis and treatment strategies for the disorder. MethodsFrom January 2020 to January 2023， a total of 130 patients with first-episode schizophrenia who met the diagnostic criteria of International Classification of Diseases， tenth edition （ICD-10）， and attended at the Third People's Hospital of Fuyang， along with 150 health checkup examinees， were enrolled. All of them underwent EEG examination. An optimized long short-term memory （LSTM） deep learning model was developed utilizing EEG signals. Ten-fold cross-validation method was employed to evaluate the model's performance. The dataset was then split into two components： a training set （90%） for LSTM model development and a test set （10%） for validation. The accuracy， recall rate， precision， F1-score， schizophrenia diagnosis and EEG abnormality grading were used as evaluation indicators， and the results of the proposed model were compared to the assessments made by experienced psychiatrists. ResultsFor schizophrenia diagnosis， the modeling group achieved the following performance metrics： precision （94.40±3.03）%， recall rate （94.30±3.23）%， accuracy （94.60±2.22）%， and F1-score （94.20±2.20）%. In the validation group， the corresponding metrics were precision （90.90±2.85）%， recall rate （92.20±1.14）%， accuracy （92.20±1.69）%， and F1-score （91.50±1.78）%. Statistical analysis revealed no significant differences between the LSTM diagnostic model and the experienced psychiatrists in terms of precision， recall rate， accuracy， and F1-score for schizophrenia diagnosis （χ²=1.500， 0.750， 2.722， 1.056， P>0.05）. The modeling group demonstrated an accuracy rate of （91.71±1.73）% in grading EEG abnormalities. For Grade 1 abnormalities， the modeling group reported a precision of （96.40±2.39）%， a recall rate of （94.77±1.40）%， and an F1-score of （95.55±1.14）%. In the case of Grade 2 abnormalities， the precision was （85.89±2.04）%， the recall rate was （88.10±6.18）%， and the F1-score was （87.06±3.12）%. For the more severe Grade 3 abnormalities， the modeling group's precision was （79.61±7.33）%， the recall rate was （81.79±9.87）%， and the F1-score was （80.41±6.79）%. Additionally， the validation group exhibited an accuracy rate of （85.61±6.16）%. The precision， recall rate， and F1-score for Grade 1 abnormalities were （91.43±6.25）%， （92.64±9.65）% and （91.56±4.83）%， respectively. For Grade 2 abnormalities， these metrics were （71.17±19.02）%， （77.64±17.24）% and （71.88±11.33）%. In the case of Grade 3 abnormalities， the precision was （90.00±21.08）%， the recall rate was （80.00±25.82）%， and the F1-score was （81.67±19.95）%. There was no significant difference in the accuracy， recall， accuracy and F1 value between LSTM model and senior doctors in evaluating the abnormal degree of EEG in schizophrenia （χ²=0.098， 0.036， 0.020， 0.336， P>0.05）. The LSTM model takes less time to diagnose schizophrenia and EEG abnormalities than senior doctors， and the differences were statistically significant （t=57.147， 43.104， P<0.01）. ConclusionThe study utilizes an EEG-based LSTM deep learning model for diagnosing first-episode schizophrenia and grading EEG abnormalities， and the model not only matches the performance of experienced psychiatrists but also significantly reduces the time required for diagnosis.

OBJECTIVE To promote the application of drones in emergency rescue and related fields， expand “low-altitude+ medical” rescue services， and advance the standardization of “low-altitude+medical” distribution services. METHODS The Consensus on Low-altitude Transport and Delivery Services for Emergency Medicines via Drones （2025 Edition） （hereinafter referred to as the Consensus） was jointly initiated by the Division of Therapeutic Drug Monitoring， Chinese Pharmacological Society and the Expert Committee on Precision Medication of the Guangdong Pharmaceutical Association. Guangzhou Red Cross Hospital served as the leading unit， organizing 53 multidisciplinary experts nationwide to participate in drafting and reviewing. A nominal group technique was employed to discuss and finalize the consensus outline， resulting in a preliminary draft. Delphi method was employed， and 11 external review experts were invited to conduct the evaluation. After the experts’ opinions were analyzed and integrated， the Consensus was finalized. RESULTS & CONCLUSIONS The finalized Consensus includes its purpose， principles， and applicable scenarios， basic requirements， and operational procedures for low-altitude transport and delivery of emergency medications； distribution requirements and precautions for controlled substances， fragile medications， and temperature-sensitive medications； and recommendations for emergency medications supplies suitable for the low-altitude transportation and distribution. The release of this Consensus is expected to provide guidance and support for the standardization of “low-altitude+medical” distribution services and the application of low-altitude economy in the healthcare sector.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.

Objective:To explore the feasibility of the new auxiliary analysis software in chromosomal aberration analysis of radiation workers during occupational health examinations.Methods:Health examination data of 2 469 radiation workers in Henan province were collected. Manual analysis of chromosomal aberrations in peripheral blood lymphocytes was conducted using the new auxiliary software and the Ikaros software. Then, the chromosomal aberrations detected using both software tools were compared.Results:The new auxiliary software yielded a lower chromosomal aberration rate among radiation workers compared with the Ikaros software [(0.314 ± 0.014)% vs. (0.391 ± 0.022)%, χ2 = 9.24, P = 0.002]. Notably, the new auxiliary software yielded a significantly lower rate of acentric fragments (ace) [(0.136 ± 0.009)% vs. (0.209 ± 0.020)%, χ2= 17.76, P < 0.001]. However, no statistically significant differences were observed between the result of the two software tools in the rates of dicentrics plus rings (dic + r) and translocations ( P > 0.05). According to the GBZ/T 248-2014 standard, the differences in abnormality rates of chromosomal aberrations between the two groups had no statistically significance ( P > 0.05), with both groups showing an abnormality rate of 0 for ace. Furthermore, the new auxiliary software could double the detection efficiency. Among pre-service radiation workers of various occupations, the differences in the chromosomal aberrations detected using the two software tools exhibited statistical significance ( χ2 = 10.26, P = 0.001). In contrast, the differences in the chromosomal aberrations among in-service and post-service radiation workers had no statistically different significance ( P>0.05). The Poisson regression analysis result demonstrated that the rate of chromosomal aberrations excluding ace was affected by age ( z = 2.73, P = 0.006), while gender, analysis method, service status, and occupation had no impact. Conclusions:The two software tools yielded largely consistent result in detecting chromosomal aberrations induced by exposure to ionizing radiation. Notably, the new auxiliary software can significantly improve detection efficiency, indicating the feasibility of applying it to chromosomal aberration analysis among radiation workers.