ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Background Workers in the cable manufacturing industry are exposed to high-speed machinery and equipment for a long time, coupled with heavy workload, which poses significant risks to their physical health. However, the issue of occupational injuries in this industry has not received enough attention yet. Objective To understand the incidence of occupational injury of workers in cable manufacturing industry and to analyze the influencing factors. Method A basic information questionnaire and an occupational injury questionnaire were developed to investigate the occupational injuries of 1 343 workers in a cable manufacturing enterprise in the past year, and a total of 1 225 valid questionnaires were recovered, with an effective rate of 91.2%. Descriptive statistics were used to characterize the causes, injury locations, injury types, and other characteristics of employees’ occupational injuries. Chi-square test was used to analyze the occupational injury status of groups with different demographic characteristics, occupational characteristics, lifestyles, and interpersonal relationships. Logistic regression was used to analyze the influencing factors of occupational injuries. Result The incidence of occupational injuries among workers in a cable manufacturing enterprise in the past year was 8.6%, which mainly happened in male workers (80.0%) and occurred from May to July in summer (45.7%). The main causes were mechanical injuries (32.4%) and object blows (27.6%). The main sources of damage were machinery and equipment (36.2%) as well as raw materials and products (15.2%). The main injuries were located in upper limbs (53.3%) and lower limbs (22.9%). The main types of injuries were fractures (33.3%) and abrasions/contusions/puncture wounds (19.0%). The results of univariate analysis showed that there were statistically significant variations in the incidence of occupational injuries by gender, overtime, pre-job training, years of service in current position, alcohol consumption, physical exercise per week, and co-worker relationship (P<0.05). The logistic regression model showed that workers who exercised less than twice a week, did not participate in pre-job training, worked overtime, and had fair/poor/very poor colleague relationship had a higher risk of occupational injury, while women had a lower risk of occupational injury. Conclusion The distribution of occupational injury population is mainly male, and the time distribution is mainly from May to July. Gender, physical exercise, pre-job training, overtime, and colleague relationship are the influencing factors of occupational injuries. We should strengthen pre-job training, arrange work hours reasonably, and create a good working atmosphere to reduce the occurrence of occupational injuries.

Background Social psychological factors have emerged as a key area of research in occupational injury prevention. Occupational stress, a significant component of social psychology, has garnered widespread attention due to its potential impact on occupational injury. Objective To analyze the factors influencing occupational stress among cable manufacturing workers and explore the relationship between occupational stress and occupational injury, and to provide scientific evidence for reducing occupational stress and injury. Methods A questionnaire on basic demographics, occupational injury, and occupational stress (Effort-Reward Imbalance, ERI) was used to investigate 1343 workers in a cable enterprise. Chi-square test was employed to analyze the distribution of occupational stress across different worker characteristics. Logistic regression was used to identify factors influencing occupational stress, and a decision tree model was applied to assess the impact of occupational stress on injury risk. Results A total of 1225 valid questionnaires were collected, yielding a response rate of 91.2%. The positive rate of occupational stress was 28.7%, while the incidence of occupational injury in the past year was 8.6%. The results of univariate analysis revealed that workers who had experienced occupational injuries had a higher positive rate of occupational stress compared to those without injuries (P<0.05), and there were significant differences in the distribution of occupational stress by genders, overtime work, shift work, daily working hours, fatigue levels, sleep duration, family relationships, and colleague relationships (P<0.05). The logistic regression results showed that individuals who worked shifts, had fair/poor/very colleague relationships, and frequently worked overtime had a higher risk of occupational stress (P<0.05). The final decision tree model confirmed that occupational stress was a risk factor for occupational injury. Additional factors influencing occupational injury included physical exercise, colleague relationships, pre-job training participation, and gender. Workers who exercised less than twice per week and experienced occupational stress had a significantly higher risk of injury (23.6%) compared to those without occupational stress (10.9%). Conclusion Shift work, colleague relationships, and overtime work are correlated with the positive rate of occupational stress among cable manufacturing workers. Implementing a reasonable work schedule and fostering a positive work environment are recommended. Reducing occupational stress may help lower the risk of occupational injuries in this industry.

ObjectiveTo characterize the seasonal patterns of influenza in Kunming City, Yunnan Province before, during, and after the COVID-19 pandemic, and provide scientific evidence for optimizing influenza prevention and control strategies. MethodsInfluenza-like illness (ILI) and etiological surveillance data for influenza from the 14^th week of 2010 to the 13^th week of 2024 in Kunming City of Yunnan Province were collected. Harmonic regression models were constructed to analyze the epidemic characteristics and seasonal patterns of influenza before (2010/2011‒2019/2020 influenza seasons), during (2020/2021‒2022/2023 influenza seasons), and after (2023/2024 influenza season) the COVID-19 pandemic. ResultsBefore the COVID-19 pandemic, influenza in Kunming City mainly exhibited an annual cyclic pattern without a significant semi-annual periodicity, peaking from December to February of the next year, with an epidemic duration of 20‒30 weeks. During the pandemic, influenza seasonality shifted, with an increase in semi-annual periodicity and an approximate one month delay in annual peaks. However, after the pandemic, the annual amplitude of influenza increased compared with that before the pandemic, and the epidemic duration extended by about one month. Although the annual peak largely reverted to the pre-pandemic levels, the annual peaks for different influenza subtypes/lineages had not fully recovered. ConclusionInfluenza seasonality in Kunming City underwent substantial alterations following the COVID-19 pandemic and has not yet fully reverted to pre-pandemic levels. Continuous surveillance on different subtypes/lineages of influenza viruses remains essential, and prevention and control strategies should be adjusted and optimized in a timely manner based on current epidemic trends.

BACKGROUND: The effect of the interval between previous Helicobacter pylori (H. pylori) eradication and rescue treatment on therapeutic outcomes remains unknown. The aim of this study was to investigate the association between eradication rates and treatment interval durations in H. pylori infections. METHODS: This prospective observational study was conducted from December 2021 to February 2023 at six tertiary hospitals in Shandong, China. We recruited patients who were positive for H. pylori infection and required rescue treatment. Demographic information, previous times of eradication therapy, last eradication therapy date, and history of antibiotic use data were collected. The patients were divided into four groups based on the rescue treatment interval length: Group A, ≥4 weeks and ≤3 months; Group B, >3 and ≤6 months; Group C, >6 and ≤12 months; and Group D, >12 months. The primary outcome was the eradication rate of H. pylori . Drug compliance and adverse events (AEs) were also assessed. Pearson's χ2 test or Fisher's exact test was used to compare eradication rates between groups. RESULTS: A total of 670 patients were enrolled in this study. The intention-to-treat (ITT) eradication rates were 88.3% (158/179) in Group A, 89.6% (120/134) in Group B, 89.1% (123/138) in Group C, and 87.7% (192/219) in Group D. The per-protocol (PP) eradication rates were 92.9% (156/168) in Group A, 94.5% (120/127) in Group B, 94.5% (121/128) in Group C, and 93.6% (190/203) in Group D. There was no statistically significant difference in the eradication rates between groups in either the ITT ( P = 0.949) or PP analysis ( P = 0.921). No significant differences were observed in the incidence of AEs ( P = 0.934) or drug compliance ( P = 0.849) between groups. CONCLUSION: The interval duration of rescue treatment had no significant effect on H. pylori eradication rates or the incidence of AEs. REGISTRATION ClinicalTrials.gov , NCT05173493.
Humans ; Helicobacter Infections/drug therapy* ; Helicobacter pylori/pathogenicity* ; Male ; Female ; Prospective Studies ; Middle Aged ; Anti-Bacterial Agents/adverse effects* ; Adult ; Aged ; Treatment Outcome ; Proton Pump Inhibitors/therapeutic use*

OBJECTIVES: To investigate the effect of interferon-λ1 (IFN-λ1) on glucocorticoid (GC) resistance in human bronchial epithelial cells (HBECs) stimulated by respiratory syncytial virus (RSV). METHODS: HBECs were divided into five groups: control, dexamethasone, IFN-λ1, RSV, and RSV+IFN-λ1. CCK-8 assay was used to measure the effect of different concentrations of IFN-λ1 on the viability of HBECs, and the sensitivity of HBECs to dexamethasone was measured in each group. Quantitative real-time PCR was used to measure the mRNA expression levels of p38 mitogen-activated protein kinase (p38 MAPK), glucocorticoid receptor (GR), and MAPK phosphatase-1 (MKP-1). Western blot was used to measure the protein expression level of GR in cell nucleus and cytoplasm, and the nuclear/cytoplasmic ratio of GR was calculated. RESULTS: At 24 and 72 hours, the proliferation activity of HBECs increased with the increase in IFN-λ1 concentration in a dose- and time-dependent manner (P˂0.05). Compared with the RSV group, the RSV+IFN-λ1 group had significant reductions in the half-maximal inhibitory concentration of dexamethasone and the mRNA expression level of p38 MAPK (P<0.05), as well as significant increases in the mRNA expression levels of GR and MKP-1, the level of GR in cell nucleus and cytoplasm, and the nuclear/cytoplasmic GR ratio (P<0.05). CONCLUSIONS IFN-λ1 can inhibit the p38 MAPK pathway by upregulating MKP-1, promote the nuclear translocation of GR, and thus ameliorate GC resistance in HBECs.
Humans ; p38 Mitogen-Activated Protein Kinases/genetics* ; Glucocorticoids/pharmacology* ; Receptors, Glucocorticoid/analysis* ; Dual Specificity Phosphatase 1/physiology* ; Dexamethasone/pharmacology* ; Drug Resistance/drug effects* ; Respiratory Syncytial Viruses ; Interferons/pharmacology* ; MAP Kinase Signaling System/drug effects* ; Epithelial Cells/drug effects* ; Signal Transduction/drug effects* ; Cells, Cultured

A 14-year-old boy was admitted to the hospital due to a single episode of afebrile seizure and four hours of impaired consciousness. Three months prior to admission, he had a history of bilateral uveitis. Cerebrospinal fluid analysis revealed a mild elevation in white blood cell count. Cranial magnetic resonance imaging and contrast-enhanced scans showed multiple abnormal signals in both cerebral hemispheres, with punctate and nodular enhancement. Susceptibility-weighted imaging revealed multiple punctate hemorrhages within lesions in the bilateral frontal and left parietal lobes, suggestive of vasculitis. Brain biopsy demonstrated inflammatory granulomatous lesions. No secondary causes were identified, and the final diagnosis was granulomatous primary central nervous system vasculitis. The patient's condition improved after treatment with methylprednisolone sodium succinate and mycophenolate mofetil. This report describes a rare case of granulomatous central nervous system vasculitis in a child and provides valuable insights for the diagnosis and treatment of this disease.
Humans ; Male ; Vasculitis, Central Nervous System/diagnosis* ; Adolescent ; Magnetic Resonance Imaging ; Granuloma/diagnosis*