Background Co-exposure to noise and microwave radiation occurs frequently. The central nervous system has been identified as a sensitive target organ for both noise and microwave exposure individually, and the underlying mechanisms remain poorly understood. The specific biological effects resulting from co-exposure to these two factors have yet to be fully elucidated. Objective To clarify the effects of co-exposure to noise and microwave on neurobehavior and hippocampal tissue structure, and to explore the underlying mechanism through the assessment of serum cytokines. Methods C57BL/6N mice were selected and randomly assigned to a blank control group, a noise group, a microwave group, and a combined noise & microwave exposure group. To establish the exposure models, the noise group was subjected to broadband noise at 100 dB for 2 h, while the microwave group received radiation at a central frequency of 9.375 GHz with an average power density of 12 mW·cm⁻² and a specific absorption rate of 2.58 W·kg⁻¹ for 15 min. Open field and tail suspension tests assessed anxiety-like emotional behaviour; novel object recognition and Y-maze tests evaluated cognitive function. Histological changes in hippocampal tissue were examined using haematoxylin and eosin (HE) staining, and Nissl staining under light microscopy. Serum cytokine levels were measured using radioimmunoassay and enzyme-linked immunosorbent assay (ELISA). Results After 3 d of exposure, the noise, microwave, and combined exposure groups showed significant reductions in exploration frequency, duration, and distance within the central zone of the open field test compared to the control group (P < 0.01); the combined exposure group exhibited increased ratios of peripheral-to-central exploration time and distance (P < 0.05). After 7 d of exposure, compared with the control group, the noise group maintained a decrease in central zone exploration time (P < 0.01), while the combined exposure group showed persistent decline across all central zone metrics (P < 0.05) and elevated peripheral-to-central ratios (P < 0.05); compared to the microwave group, the combined exposure group showed significant less time in the central zone (P < 0.05) and higher peripheral-to-central ratios (P < 0.05). Regarding behaviour and cognition, compared with the control group, the combined exposure group showed increased immobility time in the tail suspension test after 3 d of exposure (P < 0.01). At this interval, all exposure groups demonstrated reduced frequency and duration of novel object recognition (P < 0.05), with the combined exposure group showing a marked decrease in novel arm exploration time (P < 0.01). After 7 d of exposure, compared with the control group, the noise group showed reduced novel object recognition frequency (P < 0.05), and both the noise and microwave groups exhibited decreased novel arm exploration time (P < 0.05). Pathological alterations including an increased number of hyperchromatic nuclei and depleted Nissl bodies were observed in the CA3 and DG regions across all exposure groups with the most severe lesions observed in the combined exposure group. Serum levels of central nervous system-specific protein β (S-100β), glial fibrillary acidic protein (GFAP), and corticosterone (CORT) were significantly elevated in all exposure groups compared with the control group (P < 0.05). Aquaporin-4 (AQP4) levels increased in the combined exposure group (P < 0.05), while CXC chemokine ligand 10 (CXCL10) levels rose in both the noise and combined groups compared with the control group (P < 0.05). Specifically, S-100β and CXCL10 levels in the combined exposure group were higher than those in the microwave group (P < 0.05); moreover, levels of S-100β, GFAP, CORT, AQP4, and CXCL10 in the combined exposure group were significantly higher than those in the noise group (P < 0.05). Conclusion Combined exposure to noise and microwave radiation induces pathological changes in the hippocampus of mice, increases levels of serum stress hormones and neuro-specific biomarkers. These impairments are more severe than those observed following single-factor exposure. The underlaying mechanism may be related to systemic stress response, neuronal damage, astrocyte activation, and changes in blood-brain barrier permeability, leading to emotional behavioral abnormalities and cognitive decline.

Background Thyroid hormones are crucial for development and proper functioning of human physiological systems. Current research on the thyroid mainly focuses on the impacts of lifestyle factors on thyroid dysfunction, while less attention is paid to the factors affecting thyroid hormone levels, especially occupational hazards, which warrants further investigation. Objective To investigate the associations between occupational hazard exposure and thyroid-stimulating hormone (TSH) and thyroid hormone levels in male coal mine workers. Methods A cross-sectional study design was adopted. A total of 12564 workers who participated in the occupational health check-ups at the Xishan Coal Electricity (Group) Corporation Occupational Disease Prevention and Control Institute in 2023 and met the inclusion and exclusion criteria were selected as research subjects. A self-designed electronic questionnaire was used to collect basic information, occupational history, and lifestyle habits of all study subjects. Height, weight, thyroid function test results, and occupational hazard exposure of the study subjects were obtained through occupational health examinations and routine workplace occupational hazard detection records. Generalized linear regression was used to analyze the associations between occupational hazard exposure and the levels of TSH and thyroid hormones. Results The median (P₂₅, P₇₅) levels of triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), and TSH in the included 12564 male coal mine workers were 1.16 (1.03, 1.29) ng·mL⁻¹, 7.70 (6.70, 8.90) μg·dL⁻¹, 3.63 (3.40, 3.84) pg·mL⁻¹, 1.19 (1.08, 1.30) ng·dL⁻¹, and 1.93 (1.36, 2.78) μIU·mL⁻¹, respectively. The overall abnormality rate of thyroid hormones was 2.83%, with the highest rate for subclinical hypothyroidism (1.83%), followed by hyperthyroidism (0.37%), hypothyroidism (0.32%), and subclinical hyperthyroidism (0.31%). After adjustment for confounding factors, the generalized linear regression model showed that long working hours were associated with higher levels of T3 and FT3, with β (95%CI) values of 0.011 (0.003, 0.019) and 0.038 (0.019, 0.057) respectively. Night shift work was linked to increased TSH levels and decreased FT4 levels, with β (95%CI) values of 0.171 (0.016, 0.326) and −0.012 (−0.019, −0.006) respectively. Coal dust exposure was associated with decreased levels of T3 and T4, with β (95%CI) values of −0.022 (−0.037, −0.008) and −0.320 (−0.434, −0.207) respectively. Noise exposure was related to decreased levels of T4 and FT4, with β (95%CI) values of −0.102 (−0.166, −0.038) and −0.020 (−0.027, −0.013) respectively. Conclusion The TSH and thyroid hormone levels of coal miners are mostly within the normal reference ranges, with a low abnormality rate. Long work hours, night shift work, coal dust, and noise are associated with the levels of TSH and thyroid hormone levels in the male miners. Coal companies should reasonably arrange working hours, optimize the night shift scheduling system, and enhance protection against coal dust and noise to promote occupational health and safeguard the physical health of miners.

Objective: To evaluate the intervention effectiveness of co-occurrence and prevention for myopia and obesity among primary and secondary school students, so as to provide a scientific basis for the development of comprehensive intervention measures in myopia and obesity. Methods: From September 2022 to September 2023, a cluster random sampling method was used to select 6 primary schools and 6 junior high schools from Tongzhou District, Beijing. Participants were randomly assigned to an intervention group (914 before intervention and 754 after intervention) and a control group (868 before intervention and 652 after intervention), with an expected duration of one academic year. Based on the RE-AIM framework, integrate resources from families, schools, communities, and medical institutions to develop a school-based intervention technology packagefor the co-occurrence and prevention of myopia and obesity in children. The intervention group received intervention according to the comprehensive intervention technology package, while the control group did not receive any intervention measures. Relevant health indicators during the baseline period and after intervention were measured and collected, and groups were compared by Chi quest test, t-test and Wilcoxon rank sum test. Results: After intervention, the uncorrected visual acuity of primary and secondary school students in the intervention group (4.79±0.30) and the control group (4.77±0.33) both decreased compared to those before intervention (4.80±0.30, 4.90±0.32) ( t =-7.00,-5.24); the decrease in uncorrected visual acuity in the intervention group was smaller than that in the control group( t =5.33)( P <0.01). After intervention, body mass index, waist circumference, hip circumference, and body fat percentage of primary and secondary school students in the intervention group decreased compared to those before intervention. However, the changes in these indicators were not statistically significant ( t/Z =-0.03, - 0.36，- 0.30，- 0.01, P >0.05); the above indicators in the control group increased compared to those before intervention, but only hip circumference and body fat percentage showed statistically significant changes ( t/Z =2.17, 2.62, P <0.05). After intervention, both the intervention group and the control group showed increases in systolic and diastolic blood pressure compared to those before intervention(intervention group: t =2.16,5.29; control group: t =6.84,5.07); the intervention group had lower systolic and diastolic blood pressure than the control group( t = -5.27 , -2.08)( P <0.05). After intervention, the intervention and the control groups had statistically significant differences in cognitive accuracy(92.48%, 69.33%) in terms of "outdoor exercise can prevent myopia" and "having 5 servings of adult fist sized vegetables and fruits every day" ( χ 2=6.30, 7.86, P <0.05). There was a statistically significant difference in the proportion of primary and secondary school students in the intervention group (40.98%) and the control group (35.43%) for "who did not drink sugary drinks for every day in the past 7 days" ( χ 2=4.32, P <0.05). After intervention, the intervention group and the control group showed increases in "school outdoor activity duration on school days" and "outdoor activity duration on rest days" compared to those before intervention ( t/Z =-13.32,-9.71;- 2.59，-2.69）；the behavior rate of "visual acuity measurement frequency at least once every 3 months" in the intervention group (46.68%) and the control group (52.76%) increased compared to those before intervention (36.43%, 44.01%), and the increases in the intervention group were greater than that in the control group ( χ 2=17.52,11.08) ( P <0.05). Conclusions Comprehensive intervention measures have significant intervention effects on controlling the occurrence and development of comorbidity of myopia and obesity in children. It could actively promote collaboration and cooperation among families, schools, communities and medical institutions to reduce the occurrence of myopia and obesity among primary and secondary school students.

Objective:To analyze the changes in the phylogenetic and antigenic characteristics of the hemagglutinin (HA) gene of influenza virus A(H3N2) [A(H3N2)] during the 2022-2024 influenza seasons in Beijing.Methods:The data of influenza-like cases and A(H3N2) strains from 17 network laboratories and their corresponding sentinel hospitals were collected during the 2022-2024 influenza seasons. The HA genes were amplified and sequenced after extracting nucleic acids of the chosen virus strains. BioEdit, the nucleotide and amino acid sequence identity were conducted, and the maximum likelihood method in MEGA 5.0 software was used to construct the phylogenetic tree of HA genes. Web Logo displayed the amino acid mutation, and the N-glycosylation sites of HA online were analyzed using the NetNGlyc1.0 Server online. The Datamonkey platform was utilized to analyze the positive selection pressure sites of the HA protein.Results:The 2022-2024 influenza season includes 2022-2023 and 2023-2024. During the influenza seasons of 2022-2024, the positive rates of A(H3N2) nucleic acid were 10.35% (2 127/20 543) and 10.47% (4 386/41 876), respectively. In the 2022-2023 influenza season, there were two peaks in the A(H3N2). The comparison of HA genes between all A(H3N2) strains studied with the 2022-2024 vaccine strain (A/Darwin/9/2021) revealed that all of the strains studied have the two amino acid mutations involving 186 and 225 receptor binding sites. There were 31 amino acid substitutions in the 2022-2023 influenza season, of which 18 variant sites involved antigenic determinants. There were 35 amino acid mutations during the 2023-2024 influenza season, of which 14 were related to antigenic determinants. There were changes in the genetic evolutionary subclades of A(H3N2) strains in two influenza seasons: from 2022 to 2023, three evolutionary subclades were co-prevalent together, with the 3C.2a1b.2a.2a.3a.1 accounting for 76.67% (23/30), the 3C.2a1b.2a.1a accounting for 20.00% (6/30), the 3C.2a1b.2a.2a.1 accounting for 3.33% (1/30); from 2023 to 2024, two subclades were prevalent, with 3C.2a1b.2a.2a.3a.1 accounting for 95.12% (39/41) and 3C.2a1b.2a.2a.1 accounting for 4.88% (2/41). The glycosylation site changes of the HA protein of A(H3N2) have been enhanced from 2023 to 2024. The 145 amino acid position of the HA protein of the A(H3N2) was the positive selection site for stress selection site analysis.Conclusions:The evolutionary subclades of the HA gene of A(H3N2) in Beijing showed changes from 2022 to 2024, and the glycosylation site polymorphism of the HA protein of A(H3N2) significantly increased from 2023 to 2024. Continuous monitoring of HA mutations in the A(H3N2) is crucial, providing a basis for developing influenza prevention and control strategies, as well as new strategic support for screening influenza vaccine components, vaccine design, and discovery of drug targets.

Objective:To explore the factors influencing diarrhea after nasal feeding in patients with severe neurological illness, construct a nomogram model and verify its predictive performance.Methods:A retrospective study was conducted to select 797 nasal feeding patients admitted to the Neurological Intensive Care Unit of the Tianjin First Central Hospital from May 2020 to November 2023 as study subjects. Patients were divided into a modeling set ( n=558) and a validation set ( n=239) in a 7∶3 ratio. Influencing factors were screened based on univariate analysis, correlations between variables were detected by multicollinearity diagnostics, and then risk factors were identified using binomial Logistic regression, and a nomogram model was created. The predictive capacity of the model was assessed using the area under the receiver operating characteristic curve ( AUC), the degree of fit of the model was evaluated using the Hosmer-Lemeshow test and calibration curves were plotted, and the practical application value of the model in clinical practice was appraised by means of clinical decision curve analysis. Results:Binomial Logistic regression analysis showed that Glasgow Coma Scale score ( OR=0.891), Acute Physiology and Chronic Health Evaluation Ⅱ score ( OR=1.063), sedative-analgesic ( OR=0.326), albumin level ( OR=0.856), days of antibiotic use ( OR=3.338), and acid suppressants ( OR=3.260 ) were the factors influencing diarrhea after nasal feeding in patients with severe neurological illness ( P<0.05). In the validation set, the AUC for the nomogram model of the risk of diarrhea after nasal feeding in patients with severe neurological illness was 0.82 [95% CI (0.77, 0.87) ], with a sensitivity of 0.72 and a specificity of 0.72. Clinical decision curve showed nomogram model had high application value. Conclusions:The constructed nomogram model has good predictive performance and can help healthcare professionals in neurocritical care specialties to identify patients at high risk of diarrhea at an early stage, thus informing the development of individualized prevention strategies in clinical practice.

Objective:To explore the effect of combining transcranial magnetic stimulation (rTMS) with acupuncture in the treatment of patients with vascular cognitive impairment (VCI).Methods:A total of 40 VCI patients were randomly assigned to either the control group or the experimental group ( n=20 per group) using a random number table. Both groups received routine treatment and rTMS, while the experimental group was additionally provided with acupuncture for four weeks. The rTMS was at 10Hz at 90% of the motor threshold. Before and after the treatment, both groups′ cognition was evaluated using the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). Ability in the activities of daily living (ADL) was quantified using the modified Barthel Index (MBI). Serum levels of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were measured using enzyme-linked immunosorbent assays. Results:Significant improvement was observed in both groups′ average MoCA, MMSE, and MBI scores, along with reductions in peripheral serum IL-6 and TNF-α levels. The experimental group exhibited significantly higher MoCA subdomain scores in the visuospatial and executive function, attention, and delayed recall subdomains, as well as a higher total MoCA score compared to the control group. The average MMSE and MBI scores were significantly higher in the experimental group than the control group, and that group′s serum IL-6 and TNF-α levels were significantly lower, on average. Pearson correlation analysis demonstrated a positive correlation between the improvements in MoCA and MMSE scores and the reductions in IL-6 and TNF-α levels in both groups.Conclusions:rTMS combined with acupuncture effectively improves cognition and ADL ability among VCI patients. The underlying mechanism may be associated with the reduction of neuroinflammatory factors IL-6 and TNF-α.

Objective This study aimed to explore the ability of ultrasonographic radiomics in predicting the occurrence of in-stent restenosis(ISR)after carotid artery stenting(CAS)by analyzing the correlation between radiomic features of responsible plaques in carotid artery stenosis and the incidence of ISR.Methods A retrospective collection was conducted on 206 cases that underwent CAS treatment at our hospital.The enrolled patients were randomly split into a training set(144 cases)and a test set(62 cases)at a 7∶3 ratio.We utilized the Darwin Intelligent Research Platform to extract radiomic features from each region of interest,and then screened 1125 ultrasonographic radiomic features.Different machine learning algorithms were employed to construct diagnostic models,and the best-performing classifier was selected.Various prediction models were established,including a clinical-ultrasonographic feature model,a radiomic model,and a combined clinical-ultrasonographic-radiomic model.Results Multivariate logistic regression analysis in the training set revealed that hypertension,hyperuricemia,triglycerides,and plaque location were independent risk factors for ISR after CAS.For the clinical-ultrasonographic model,the area under the curve(AUC)values for the training and validation sets were 0.896 and 0.644,respectively.The corresponding AUC values for the radiomic model were 0.961 and 0.715,while those for the combined model were 0.947 and 0.727.Conclusion The radiomic model demonstrates superior performance in predicting ISR compared to the traditional clinical-ultrasonographic model.The combined model exhibited an enhanced ability to predict ISR occurrence,thereby improving the diagnostic performance of traditional assessments.

Objective To investigate the mutation spectrum of F7 gene and its clinical implications in patients with coagulation factorⅦ(FⅦ)deficiency in the southeastern Chinese population,and to analyze the correlations among genotype,FⅦ activity(FⅦ:C),and bleeding risk.Methods A retrospective analysis was conducted on 66 probands diagnosed with FⅦ deficiency between 2010 and 2024 at The First Affiliated Hospital of Wenzhou Medical University.The clinical data,bleeding scores according to ISTH(Internation-al Society on Thrombosis and Haemostasis),the results of coagulation function tests,and F7 gene sequencing data were collected and analyzed.Results Among the 66 probands,59 cases exhibited severe FⅦ deficiency,of whom 37 presented bleeding symptoms,pri-marily gingival bleeding,epistaxis,and menorrhagia.The most frequent mutation:sp.His408Gln,p.Cys10Profs * 16,and p.Cys389Gly,were clustered in exon 8.Prothrombin time(PT)showed a significant positive correlation with ISTH bleeding scores(P＜0.05),while FⅦ:C demonstrated weak predictive power for bleeding risk.Conclusion Exon 8 and the S1 peptide region of the F7 gene were identified as mutation hotspots,and PT was highlighted as an effective tool for evaluating bleeding risk.Although FⅦ:C levels exhibited only a limited correlation with bleeding risk,genetic mutation analysis provided crucial insights for the molecular diag-nosis and clinical management of FⅦ deficiency.

Objective:To gain a understanding of the occurrence of cognitive impairment among residents in drinking water-borne endemic fluorosis (drinking water-borne fluorosis) areas, and to study its influencing factors.Methods:In March 2023, a cluster sampling method was used to select local residents aged 18 and above from the drinking water-borne fluorosis areas in Jishan County, Shanxi Province as survey subjects. General demographic data were collected through face-to-face surveys, and a random urine sample was collected once to determine urinary fluoride level. Cognitive function was assessed using the mini-mental state examination (MMSE), and the survey subjects were divided into a cognitive impairment group ( < 27 points) and a control group (27 - 30 points) based on the MMSE scores. A multiple logistic regression model and a decision tree model based on chi-squared automatic interaction detector were constructed to analyze the factors affecting cognitive impairment, and the model fitting effect was evaluated using receiver operating characteristic (ROC) curve.Results:A total of 3 301 subjects were included in the survey, including 2 081 females and 1 220 males. There were 1 515 subjects < 60 years old and 1 786 subjects ≥60 years old, with urinary fluoride level [ M ( Q1, Q3)] of 2.92 (1.78, 4.54) mg/L. There were 1 939 cases in the cognitive impairment group and 1 362 cases in the control group, with a detection rate of 58.74% (1 939/3 301) for cognitive impairment; and the differences in gender, age, education level, marital status, annual household income, alcohol consumption, smoking distribution, and urinary fluoride level between the two groups were statistically significant ( P < 0.05). The results of multiple logistic regression analysis showed that female, ≥60 years, and urinary fluoride > 4.54 mg/L were risk factors for cognitive impairment [ OR (95% CI): 1.25 (1.01, 1.54), 2.66 (2.26, 3.14), 1.32 (1.06, 1.65), P < 0.05]. Education level of primary school or above, annual household income≥12 000 yuan, and mild alcohol consumption were protective factors for cognitive impairment [ OR (95% CI): 0.15 (0.09, 0.25), 0.58 (0.48, 0.68), 0.67 (0.51, 0.87), P < 0.05]. The analysis results of the decision tree model showed that age had the greatest impact on the occurrence of cognitive impairment, followed by annual household income, education level, and urinary fluoride. The areas under the ROC curves of the multiple logistic regression and decision tree model were 0.72 and 0.70 ( P < 0.001), respectively, indicating good model fitting performance. Conclusion:The detection rate of cognitive impairment in residents of drinking water-borne fluorosis areas is relatively high, and age, annual household income, education level, and urinary fluoride are all influencing factors for occurrence of cognitive impairment.