Objective: To explore the interaction between school bullying and insomnia in relation to depression-anxiety-stress emotions among primary and secondary school students,so as to provide a basis for preventing negative emotional states in adolescents. Methods: In October 2024, a stratified cluster sampling method was used to select 3 058 students in grade 5-6 of primary, junior and senior high school in Sheyang County of Jiangsu Province. The Delaware Bullying Victimization Scale, Insomnia Severity Index, Depression-Anxiety-Stress Scale-21, and Study Condition Questionnaire were employed to investigate school bullying, insomnia, depression-anxiety-stress emotions, and academic performance. The χ 2 test and Logistic regression were used to analyze the association between school bullying and insomnia interactions and depression-anxiety-stress emotions among primary and secondary school students, multiplicative interaction analysis was conducted, and additive interaction analysis was performed using R software. Results: The detection rates of depression-anxiety-stress emotions among primary and secondary school students were 21.6%, 28.4% and 10.8%, respectively. The detection rates of physical bullying, relationship bullying, verbal bullying and cyberbullying in school bullying were 10.6%, 14.0%, 22.3%, and 6.2%, respectively. The detection rate for insomnia was 23.1%. Results from Logistic regression analysis showed that, after adjusting for relevant factors, physical, relational, verbal, and cyberbullying and insomnia were positively correlated with the detection rates of depression ( OR = 5.72- 10.93), anxiety ( OR =6.35-12.17), and stress emotions ( OR =5.97-14.52) among primary and secondary school students (all P <0.01). The multiplicative interaction between physical, relational, verbal, and cyberbullying and insomnia was positively correlated with the detection rates of depression ( OR =8.00-18.01), anxiety ( OR =11.35-17.76), and stress emotions ( OR =7.64-9.12) in primary and secondary school students (all P <0.01). Additive interactions were observed between physical, relational, verbal, and cyberbullying and insomnia in relation to the detection rates of depression, anxiety, and stress emotions among primary and secondary school students (both RERI and AP >0 and the credible interval excluded 0, SI >1 and the credible interval excluded 1). Conclusion School bullying and insomnia are associated with depression, anxiety, and stress emotions among primary and secondary school students, and they exhibit both multiplicative and additive interactions.

OBJECTIVE: To evaluate the clinical effect of "Tongdu Yisui" (unblocking the governor vessel and benefiting marrow) acupuncture and moxibustion on Meige syndrome. METHODS: Fifteen patients with Meige syndrome were treated with "Tongdu Yisui" acupuncture and moxibustion. Acupuncture was applied to Baihui (GV20), Dazhui (GV14), Shenzhu (GV12), Zhiyang (GV9), Jinsuo (GV8), bilateral Taixi (KI3), Zhaohai (KI6) and etc. Moxibustion was delivered at Jinsuo (GV8). After acupuncture and moxibustion at these body points, Jiao's scalp acupuncture was operated at bilateral chorea-tremor control area, and the patients were asked to walk for 20 min during needle retaining. Acupuncture and moxibustion were administered 20 min each time, once every two days, 3 times weekly and for 8 consecutive weeks. Assessments were conducted before treatment, after treatment, and follow-up at three months after treatment completion using the Burke-Fahn-Marsden dystonia rating scale (BFMDRS-M), abnormal involuntary movement scale (AIMS), and blepharospasm disability index (BSDI); and the clinical effect was evaluated after treatment. RESULTS: Compared before treatment, the scores of the sub-items of BFMDRS-M for eyes, mouth, speech and swallowing, and neck, as well as the total score of the scale, AIMS score and BSDI score decreased after treatment and during follow-up (P<0.05); the scores of the above indexes were not different statistically in comparison between the follow-up and after treatment (P>0.05). After treatment, 13 cases were effective, 2 cases were failed and the total effective rate was 86.7% (13/15). CONCLUSION "Tongdu Yisui" acupuncture and moxibustion can effectively alleviate motor symptoms and dysfunction of Meige syndrome and presents the sustained therapeutic effect.
Humans ; Moxibustion ; Male ; Female ; Acupuncture Therapy ; Adult ; Middle Aged ; Meige Syndrome/therapy* ; Acupuncture Points ; Young Adult ; Treatment Outcome ; Aged ; Adolescent

Objective:To investigate the differences in brain age and brain age gap (BAG) between patients with prolonged disorders of consciousness (pDoC) and healthy controls (HC).Methods:A retrospective cross-sectional study was performed; 43 patients with pDoC admitted to Rehabilitation Medicine Center, Zhujiang Hospital, Southern Medical University from January 2020 to October 2022 were enrolled; 26 healthy volunteers recruited at the same time and 187 healthy subjects from the publicly available healthy control dataset Nathan Kline Institute-Rockland Sample (NKI-RS) were chosen as HC group. The clinical and imaging data of these subjects were collected. A brain age estimation model was constructed based on amplitude of low-frequency fluctuation (ALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) for healthy individuals, and the pDoC group was used as the test set. A two-sample t-test was used to compare the brain age and BAG differences between the pDoC group and HC group. Pearson correlation analysis was used to explore the correlation between BAG and coma recovery scale-revised (CRS-R) in the pDoC group. Results:The chronological age and estimated brain age in the HC group were (41.54±9.61) and (42.32±10.65) years, respectively, without significant difference ( t=-0.254, P=0.801). The chronological age and estimated brain age in the pDoC group were (49.91±12.03) and (62.79±15.00) years, respectively, with significant difference ( t=-4.341, P<0.001). The BAG in the HC and pDoC groups were (0.78±4.59) and (12.88±7.17) years, respectively, with significant difference ( t=-7.822, P<0.001). Correlation analysis results showed that in the pDoC patients, no correlation was noted between BAG and CRS-R score on the day of imaging scan or 6 months after the day of imaging scan ( r=0.090, P=0.738; r=0.205, P=0.674); no correlation was noted between BAG and difference in CRS-R score (difference value of CRS-R score 6 months after the day of imaging scan-CRS-R score on the day of imaging scan, r=0.246, P=0.687). Conclusion:Compared with the HC subjects, patients with pDoC exhibit an abnormal increase in brain age, suggesting that pDoC caused by severe brain injury may lead to accelerated brain aging.

Objective To analyze the differences in structural integrity of cerebral white matter fiber bundles in vegetative state(VS)patients with different prognoses,and to construct an early-stage prognostic prediction model for 1-year post-stabilization prognosis.Methods A retrospective analysis was conducted on 52 VS patients admitted to the Department of Rehabilitation Medicine at Zhujiang Hospital of Southern Medical University.Patients were stratified into good prognosis(n=22)and poor prognosis(n=30)at 1-year follow-up based on Coma Recovery Scale-Revised(CRS-R)scores.The fractional anisotropy values of cerebral white matter fiber bundles were derived from diffusion tensor imaging,and for the first time,the scores of the visual subscales of CRS-R were combined with FA values as input features for the prognostic model.To optimize model construction,the least absolute shrinkage and selection operator regression was employed for feature screening,and synthetic minority over-sampling technique for data balancing.The prognostic prediction model was subsequently developed using a support vector machine algorithm and validated via leave-one-out cross-validation.Model performance was evaluated using area under receiver operating characteristic curve,along with accuracy,sensitivity,specificity,and F1 score metrics.Results Following LASSO regression feature screening,the pontine crossing tract,medial lemniscus,tapetum,splenium of corpus callosum,and visual subscale scores were identified as key predictors.A multimodal SVM-based prediction model constructed with the above features could effectively predict the 1-year prognosis of VS patients,achieving a high predictive performance(AUC=0.894).Conclusion The SVM-based model integrating FA values of specific white matter fiber bundles and visual subscale scores demonstrates excellent predictive performance in predicting the 1-year prognosis of VS patients.

Objective To analyze the differences in structural integrity of cerebral white matter fiber bundles in vegetative state(VS)patients with different prognoses,and to construct an early-stage prognostic prediction model for 1-year post-stabilization prognosis.Methods A retrospective analysis was conducted on 52 VS patients admitted to the Department of Rehabilitation Medicine at Zhujiang Hospital of Southern Medical University.Patients were stratified into good prognosis(n=22)and poor prognosis(n=30)at 1-year follow-up based on Coma Recovery Scale-Revised(CRS-R)scores.The fractional anisotropy values of cerebral white matter fiber bundles were derived from diffusion tensor imaging,and for the first time,the scores of the visual subscales of CRS-R were combined with FA values as input features for the prognostic model.To optimize model construction,the least absolute shrinkage and selection operator regression was employed for feature screening,and synthetic minority over-sampling technique for data balancing.The prognostic prediction model was subsequently developed using a support vector machine algorithm and validated via leave-one-out cross-validation.Model performance was evaluated using area under receiver operating characteristic curve,along with accuracy,sensitivity,specificity,and F1 score metrics.Results Following LASSO regression feature screening,the pontine crossing tract,medial lemniscus,tapetum,splenium of corpus callosum,and visual subscale scores were identified as key predictors.A multimodal SVM-based prediction model constructed with the above features could effectively predict the 1-year prognosis of VS patients,achieving a high predictive performance(AUC=0.894).Conclusion The SVM-based model integrating FA values of specific white matter fiber bundles and visual subscale scores demonstrates excellent predictive performance in predicting the 1-year prognosis of VS patients.

Objective:To investigate the differences in brain age and brain age gap (BAG) between patients with prolonged disorders of consciousness (pDoC) and healthy controls (HC).Methods:A retrospective cross-sectional study was performed; 43 patients with pDoC admitted to Rehabilitation Medicine Center, Zhujiang Hospital, Southern Medical University from January 2020 to October 2022 were enrolled; 26 healthy volunteers recruited at the same time and 187 healthy subjects from the publicly available healthy control dataset Nathan Kline Institute-Rockland Sample (NKI-RS) were chosen as HC group. The clinical and imaging data of these subjects were collected. A brain age estimation model was constructed based on amplitude of low-frequency fluctuation (ALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) for healthy individuals, and the pDoC group was used as the test set. A two-sample t-test was used to compare the brain age and BAG differences between the pDoC group and HC group. Pearson correlation analysis was used to explore the correlation between BAG and coma recovery scale-revised (CRS-R) in the pDoC group. Results:The chronological age and estimated brain age in the HC group were (41.54±9.61) and (42.32±10.65) years, respectively, without significant difference ( t=-0.254, P=0.801). The chronological age and estimated brain age in the pDoC group were (49.91±12.03) and (62.79±15.00) years, respectively, with significant difference ( t=-4.341, P<0.001). The BAG in the HC and pDoC groups were (0.78±4.59) and (12.88±7.17) years, respectively, with significant difference ( t=-7.822, P<0.001). Correlation analysis results showed that in the pDoC patients, no correlation was noted between BAG and CRS-R score on the day of imaging scan or 6 months after the day of imaging scan ( r=0.090, P=0.738; r=0.205, P=0.674); no correlation was noted between BAG and difference in CRS-R score (difference value of CRS-R score 6 months after the day of imaging scan-CRS-R score on the day of imaging scan, r=0.246, P=0.687). Conclusion:Compared with the HC subjects, patients with pDoC exhibit an abnormal increase in brain age, suggesting that pDoC caused by severe brain injury may lead to accelerated brain aging.

Objective: Based on observational, longitudinal and intervention study of common diseases among students in Jiangsu Province, this paper presents the current progress of two year follow up of myopia cohort regarding the association between growth parameters with progression of myopia among children and adolescents in areas with rapid economic growth. Methods: This survey adopted the stratified cluster sampling method for school selection. The full automatic computer optometry (TOPCON RM800) was used to track myopia related parameters for all participants from 2019 to 2020 under the condition of mydriasis (compound topicamide eye drops). Relationship between growth parameters of children and adolescents and the incidence and progression of myopia was analyzed by using Cox regression multiple statistical model. Results: The myopia rates of students from grade 1 to grade 3 in 2019 were 5.4%, 21.5% and 37.3% respectively. After one year, the myopia rates of all school stages increased to 25.3%, 43.3% and 58.1% respectively( χ 2=53.59, 49.63, 32.52, P <0.01). The mean diopter of right eye and left eye after mydriasis were ( 0.30± 1.24/0.39±1.26)D in 2019 and (-0.33±1.54/-0.19±1.55)D in 2020, respectively based on Cox multiple regression results, age ( HR =1.21, 95% CI =1.09-1.34), naked eye vision ( HR =0.08, 95% CI =0.07-0.11), height ( HR =0.98, 95% CI =0.97-0.99) showed a strong correlation with the incidence and progression of myopia( P <0.05). Conclusion Myopia is growing rapidly in the central region of Jiangsu Province. It is suggested that diopter, axial length, naked eye vision, age, height and other indicators should be included in the refractive archives of children and adolescents in the region.

Bayesian statistics is an approach for learning from evidences as it accumulates, combining prior distribution with current information on a quantity of interest, in which posterior distribution and inferences are being updated each time new data become available using Bayes' Theorem. Though frequentist approach has dominated medical studies, Bayesian approach has been more and more widely recognized by its flexibility and efficiency. Research and development (R&D) on anti-cancer new drugs have been so hot globally in recent years in spite of relatively high failure rate. It is the common demand of pharmaceutical enterprises and researchers to identify the optimal dose, regime and right population in the early-phase R&D stage more accurately and efficiently, especially when the following three major changes have been observed. The R&D on anticancer drugs have transformed from chemical drugs to biological products, from monotherapy to combination therapy, and the study design has also gradually changed from traditional way to innovative and adaptive mode. This also raises a number of subsequent challenges on decision-making of early R&D, such as inability to determine MTD, flexibility to deal with delayed toxicity, delayed response and dose-response changing relationships. It is because of the above emerging changes and challenges that the Bayesian approach is getting more and more attention from the industry. At least, Bayesian approach has more information for decision-making, which could potentially help enterprises achieve higher efficiency, shorter period and lower investment. This study also expounds the application of Bayesian statistics in the early R&D on anticancer new drugs, and compares and analyzes its idea and application scenarios with frequentist statistics, aiming to provide macroscopic and systematic reference for all related stakeholders.
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Humans ; Bayes Theorem ; Lung Neoplasms/drug therapy* ; Research Design ; Antineoplastic Agents/therapeutic use* ; Biological Products ; Pharmaceutical Preparations

Objective:To study the clinical features of children with Prader-Willi syndrome(PWS).Methods:Eighteen cases of PWS were collected from July 2016 to November 2018 in Shenzhen Maternal and Child Healthcare Hospital, Southern Medical University.The clinical data of children with PWS were analyzed retrospectively.Results:There were 12 males and 6 females in 18 cases with PWS.The diagnosis age ranged from 25 days to 9.5 years old [(3.09±3.02) years old]. Among them, 11 cases were in infancy (≤3 years old) and 7 cases after infancy (>3 years old). The main clinical features of infants with PWS were 11 cases of gonadal dysplasia (100.0%), 11 cases of psychomotor retardation (100.0%), 10 cases of hypotonia (90.1%), 6 cases of feeding difficulty and weak cry (54.5%). After infancy the main clinical features included 7 cases of psychomotor retardation (100.0%), 5 cases of hyperphagia(71.4%), 5 cases of obesity (71.4%), 5 cases of abnormal behavior problems (71.4%) and 4 cases of visual problems (57.1%). The clinical features of all patients throughout the developmental stage were as follows: decreased fetal movement, hypoplasia, neonatal hypotonia, weak cry, feeding difficulty, psychomotor delay, hyperphagia, obesity, abnormal behavior problems, and so on.Conclusions:The clinical features of PWS vary with age.The main clinical features in the infancy are hypotonia, weak cry, difficulty feeding and gonadal dysplasia.After infancy, there are hyperphagia, obesity, behavior and visual problems.And psychomotor retardation is present in the whole developmental stage of children with PWS.Early diagnosis and treatment are important for improving the prognosis of PWS.

Objective:The antigenic and genetic characteristics of influenza A(H1N1)pdm09 virus isolated from the mainland of China during the 2018-2019 influenza surveillance year were analyzed.Methods:Two thousand nine hundred and fifty-eight influenza A(H1N1)pdm09 virus strains in the 2018-2019 influenza surveillance year were analyzed by hemagglutination inhibition test. The hemagglutinin(HA) gene of 279 influenza A(H1N1)pdm09 virus strains was sequenced and analyzed. The representative strains of the dominant clades were performed for antigenic characteristics using post-vaccination human antisera.Results:Two thousand eight hundred and sixty-one (97%, 2 861/2 958) viruses characterized were antigenically similar to A/Michigan/45/2015. All HA gene of the sequenced viruses belonged to 6B.1 clade, and 269(96%, 269/279) viruses belonged to 6B.1A subclade. Compared with the vaccine virus, it had the common amino acid substitutions of S74R, S164T and I295V in the HA protein. There were several small groups with common amino acid substitutions in the 6B.1A subclade, and 51% sequenced viruses had S183P amino acid substitution in this subclade. The result of antigenic analysis using post-vaccination human antiserums showed that most of the representative strains were well inhibited by the sera.Conclusions:The antigenicity of influenza A(H1N1)pdm09 viruses in the mainland of China in 2018-2019 influenza surveillance year matched well with the corresponding vaccine strain, but the HA gene had genetically diverse characteristic.