Objective: To investigate the prevalence and correlates of five somatic symptoms among junior and senior high school students, so as to provide a reference for the prevention of these symptoms in the population. Methods: From September to November 2024, a stratified cluster random sampling method was used to select 163 802 junior and senior high school students from 158 counties/districts in Henan Province. A questionnaire survey was conducted using the Student Health Status and Influencing Factors Survey (Secondary School Version) and the Special Survey on Influencing Factors of Key Common Diseases. Logistic regression was used to analyze the factors associated with each of the five somatic symptoms. Results: The reported prevalence of fever, cough, sore throat, diarrhea, and vomiting were 7.93%, 23.56%, 13.67%, 18.03%, and 3.17%, respectively. Girls reported (8.20%, 25.26%, 16.54%, 19.14%, 3.68%) higher rates than boys (7.67%, 21.97%, 11.00%, 16.99%, 2.69%) ( χ 2= 16.01, 245.78, 1 063.22, 128.89, 129.48, all P <0.01). Boarding students (8.95%, 25.79%, 15.77%, 20.77%, 3.45%) also had higher rates than nonboarding students (6.63%, 20.75%, 11.02%, 14.56%, 2.80%)( χ 2=298.37, 569.43, 772.23, 1 055.42 , 55.82, all P <0.01). Students from nonintact families reported higher rates (8.87%, 24.89%, 14.57%, 19.20%, 3.60% ) than those from intact families (7.58%, 23.07%, 13.34%, 17.60%, 3.01%) ( χ 2=72.48, 58.98, 41.61, 55.40, 36.00, all P <0.01). After adjusting for sociodemographic variables, multivariate Logistic regression showed that unhealthy dietary habits, daily homework or tutoring duration≥2 hours, daily screen time ≥2 hours, lack of parental encouragement for exercise, exposure to tobacco/alcohol, and substance abuse were associated with increased risk of reporting the five somatic symptoms ( OR =1.27- 1.63 , 1.21-1.27, 1.28-1.40, 1.07-1.13, 1.77-2.08, 1.76-2.17, all P <0.05). Conversely, handwashing habits, twice daily tooth brushing, daily breakfast consumption, engaging in at least 60 minutes of moderate to vigorous physical activity per day, spending outdoor time during breaks, and adequate sleep were associated with lower risk ( OR =0.82-0.90, 0.85 -0.92, 0.44- 0.76 , 0.83-0.93, 0.69-0.75, 0.65-0.78, all P <0.05). Conclusions Disparities exist in the prevalence of fever, cough, sore throat, diarrhea, and vomiting among secondary school students in Henan Province. The risk of experiencing these five somatic symptoms is closely linked to daily health behaviors. Comprehensive intervention strategies and scientific measures should be implemented to prevent somatic symptoms in junior and senior high school students.

Objective:To understand the species of mosquitoes and the status of important mosquito-borne viruses in the Ningxia surveyed regions, to identify the dominant mosquito species and virus types, and to analyze their genetic characteristics, providing a scientific basis for predicting and controlling mosquito-borne infectious diseases.Methods:Mosquitoes were collected using light traps in Yinchuan and Wuzhong cities of the Ningxia Hui Autonomous Region, and the collected mosquitoes were classified and identified. Real-time polymerase chain reaction (PCR) was used to detect the Japanese encephalitis virus (JEV), West Nile virus (WNV), Chikungunya virus (CHIKV), Sindbis virus (SINV) carried by mosquitoes. The positive sample was subjected to sequencing the whole genome, and the phylogenetic tree of virus strains was constructed using bioinformatics methods.Results:From June to August 2023, a total of 8 561 mosquitoes of 3 genera and 6 species were collected in Yinchuan and Wuzhong cities, Ningxia, among which Culex pipiens pallens was the dominant species with 3 050 individuals, accounting for 35.63%; Anopheles sinensis with 2 379 individuals, accounting for 27.79%; Culex tritaeniorhynchus with 1 489 individuals, accounting for 17.39%; Caspian Aedes with 1 468 individuals, accounting for 27.79%; Aedes vexans with 152 individuals, accounting for 1.78%; and Culex modestus with 23 individuals, accounting for 0.27%. JEV GIb type was detected in the specimens of Culex tritaeniorhynchus collected in Qingtongxia city. Conclusions:The dominant mosquito species in the surveyed areas of Ningxia are primarily Culex pipiens pallens, and JEV GIb virus was detected in Culex tritaeniorhynchus in Qingtongxia city. This study provides basic data for understanding the current status of mosquitoes and mosquito-borne viruses in the Ningxia region and offers scientific guidance for further public health prevention and control measures.

Parkinson's disease(PD),the second most prevalent neurodegenerative disease,has shown an increasing incidence in recent years,significantly impacting the quality of life of elderly individuals and their families.The onset of cognitive impairment and Parkinson's disease dementia(PDD)are critical milestones in the progression of PD.Imaging examinations,serving as essential detection and evaluation tools for neurodegenerative diseases,have been increasingly applied to PD-related research.Different imaging techniques demonstrate distinct advantages and features in screening cognitive dysfunction in PD.Choosing a reliable imaging method not only maximizes the advantages of the examination,enhancing the sensitivity and specificity in identifying PD patients at risk of cognitive impairment,but also reduces the frequency of examinations and the radiation dose received by patients.This review summarizes the existing findings on imaging markers of cognitive impairment in PD from three aspects,structural imaging,functional imaging,and multimodal techniques.Furthermore,it explores future research directions,aiming to provide powerful imaging support for the clinical diagnosis and treatment of PD.

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Parkinson's disease(PD),the second most prevalent neurodegenerative disease,has shown an increasing incidence in recent years,significantly impacting the quality of life of elderly individuals and their families.The onset of cognitive impairment and Parkinson's disease dementia(PDD)are critical milestones in the progression of PD.Imaging examinations,serving as essential detection and evaluation tools for neurodegenerative diseases,have been increasingly applied to PD-related research.Different imaging techniques demonstrate distinct advantages and features in screening cognitive dysfunction in PD.Choosing a reliable imaging method not only maximizes the advantages of the examination,enhancing the sensitivity and specificity in identifying PD patients at risk of cognitive impairment,but also reduces the frequency of examinations and the radiation dose received by patients.This review summarizes the existing findings on imaging markers of cognitive impairment in PD from three aspects,structural imaging,functional imaging,and multimodal techniques.Furthermore,it explores future research directions,aiming to provide powerful imaging support for the clinical diagnosis and treatment of PD.

Objective: To explore the association between the joint association of screen time on weekdays and weekends with self rated sleep quality among adolescents, providing scientific basis for improving adolescent sleep health. Methods: Using data from "Huantai Children s Cardiovascular Health Follow up Cohort" survey conducted during November to December 2023, a total of 1 197 adolescents aged 12-17 years with complete demographic characteristics, physical measurements, and questionnaire data were included. The dose response relationship between screen time and sleep quality was evaluated by restrictive cubic splines (RCS). Based on screen time on weekdays and weekends (normal: < 2 h/d; excessive: ≥ 2 h/d), adolescents were categorized into 4 groups. Multivariate Logistic regression models were used to analyze the association between the combined effect of screen time on weekdays and weekends and sleep quality. Results: The RCS analysis results showed that there was a linear dose response relationship between average daily screen time and poor sleep quality in adolescents (non linear P >0.05). The results of multiple Logistic regression analysis showed that adjusting for potential covariates,compared with adolescents having normal screen time on both weekdays and weekends, those with excessive screen time on both weekdays and weekends had increased risk of poor sleep quality ( OR=2.51, 95%CI=1.33-4.62, P <0.01). Sex stratified analysis revealed that girls with excessive screen time on both weekdays and weekends had increased odds of poor sleep quality ( OR=3.03, 95%CI=1.23-7.14, P =0.01), compared to girls who had normal screen time on both weekdays and weekends. Conclusions A linear dose response relationship exists between daily screen time and poor sleep quality in adolescents. Excessive screen time on both weekdays and weekends is positively associated with poor sleep quality, particularly more pronounced among female adolescents.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To understand the species of mosquitoes and the status of important mosquito-borne viruses in the Ningxia surveyed regions, to identify the dominant mosquito species and virus types, and to analyze their genetic characteristics, providing a scientific basis for predicting and controlling mosquito-borne infectious diseases.Methods:Mosquitoes were collected using light traps in Yinchuan and Wuzhong cities of the Ningxia Hui Autonomous Region, and the collected mosquitoes were classified and identified. Real-time polymerase chain reaction (PCR) was used to detect the Japanese encephalitis virus (JEV), West Nile virus (WNV), Chikungunya virus (CHIKV), Sindbis virus (SINV) carried by mosquitoes. The positive sample was subjected to sequencing the whole genome, and the phylogenetic tree of virus strains was constructed using bioinformatics methods.Results:From June to August 2023, a total of 8 561 mosquitoes of 3 genera and 6 species were collected in Yinchuan and Wuzhong cities, Ningxia, among which Culex pipiens pallens was the dominant species with 3 050 individuals, accounting for 35.63%; Anopheles sinensis with 2 379 individuals, accounting for 27.79%; Culex tritaeniorhynchus with 1 489 individuals, accounting for 17.39%; Caspian Aedes with 1 468 individuals, accounting for 27.79%; Aedes vexans with 152 individuals, accounting for 1.78%; and Culex modestus with 23 individuals, accounting for 0.27%. JEV GIb type was detected in the specimens of Culex tritaeniorhynchus collected in Qingtongxia city. Conclusions:The dominant mosquito species in the surveyed areas of Ningxia are primarily Culex pipiens pallens, and JEV GIb virus was detected in Culex tritaeniorhynchus in Qingtongxia city. This study provides basic data for understanding the current status of mosquitoes and mosquito-borne viruses in the Ningxia region and offers scientific guidance for further public health prevention and control measures.

Objective:To investigate the value of 18F-FDG PET/CT imaging in the diagnosis of suspected autoimmune encephalitis (AE) in children with epilepsy and negative MRI. Methods:From May 2019 to August 2022, 94 suspected AE children (49 males, 45 females; age 1-15 years) with epilepsy and negative MRI who underwent brain 18F-FDG PET/CT imaging at Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine were retrospectively analyzed. All patients were divided into AE and non-AE groups based on clinical final diagnosis. The effectiveness of visual diagnosis was evaluated. The cortical lesion extent score (S), and SUV max, SUV mean and minimum of SUV (SUV min) of cortical lesions (L), basal ganglia (B) and thalamus (T) were measured and SUV ratios (SUVR) of L/B or L/T were obtained. Independent-sample t test or Mann-Whitney U test was used to analyze data. Binary logistic regression analysis was used to screen the diagnostic factors of AE, and a diagnostic model was established. The diagnostic efficiency was evaluated by ROC curve analysis and Delong test. Results:There were 53 cases in AE group and 41 cases in non-AE group. Based on visual analysis, the sensitivity, specificity and accuracy of 18F-FDG PET/CT for AE were 100%(53/53), 43.9%(18/41) and 75.5%(71/94), respectively. Differences of LSUV max, LSUV mean, LSUV min, L/BSUVR max, L/BSUVR mean, L/BSUVR min, L/TSUVR max, L/TSUVR mean, L/TSUVR min and S between AE and non-AE groups were statistically significant ( z=-6.74, t values: from -8.51 to -3.97, all P<0.001). ROC curve analysis showed that the AUC of L/BSUVR max was the highest (0.914) among visual analysis and semi-quantitative parameters. Logistic regression analysis showed that S (odds ratio ( OR)=11.40, 95% CI: 2.18-59.52, P=0.004), L/BSUVR max( OR=13.19, 95% CI: 2.11-82.51, P=0.006) and L/TSUVR max( OR=9.66, 95% CI: 1.57-59.55, P=0.015) were independent diagnostic factors for AE. Regression model was established: P=1/(1+ e - x), x=2.433×S+ 2.580×L/BSUVR max+ 2.267×L/TSUVR max-3.802. The AUC of this model was 0.948, with the sensitivity, specificity and accuracy of 98.1%(52/53), 90.2%(37/41) and 94.7%(89/94), respectively. The diagnostic efficacy of the optimized scoring system was consistent with the pre-optimization model, and were both superior to L/BSUVR max(both z=2.01, both P=0.040). Conclusion:The diagnostic model and scoring system based on the semi-quantitative analysis of 18F-FDG PET/CT have better diagnostic efficacy for AE and are superior to semi-quantitative parameters alone.