Objective: To explore the association between negative life events and smartphone addiction among middle school students, so as to provide theoretical support and practical guidance for prevention and intervention of smartphone addiction among middle school students. Methods: Using cluster sampling, 8 890 students were selected to survey from 27 junior high schools and 3 senior high schools in a district of Shenzhen in 2022 (baseline) and 2023 (followup). Data were collected through selfresigned questionnaires on basic information, the Smartphone Addiction Scale-Short Version, and the Adolescent Selfrating Life Events Checklist. Mixedeffects models were employed to analyze the association. Results: Compared to 2022, the punishment scores of middle school students in 2023 [1.00 (0.00, 6.00) and 1.00 (0.00, 6.00)] decreased (Z=4.27), while the scores of interpersonal stress, learning stress and adaptation [4.00(0.00, 8.00), 4.00(0.00, 8.00); 4.00(1.00, 8.00), 5.00(2.00, 9.00); 2.00 (0.00, 6.00), 3.00 (0.00, 7.00)] increased (Z=-3.04, -8.36, -6.80) (P<0.01). Mixedeffects models revealed a positive doseresponse relationship between negative life events and smartphone addiction (OR=1.08-1.17, P<0.01). Stepwise regression showed independent positive effects of interpersonal stress (OR=1.05), academic stress (OR=1.03), and adaptation stress (OR=1.11) on smartphone addiction (P<0.01). Subgroup analysis of nonaddicted students in 2022 confirmed persistent associations for academic stress (OR=1.03) and adaptation (OR=1.07) (P<0.01). Conclusion Negative life events exhibit a positive doseresponse relationship with smartphone addiction, particularly interpersonal stress, academic stress, and adaptationrelated events.

Objective: To explore the potential causal association between adolescent compulsive behaviour and smartphone addiction based on longitudinal data, so as to provide reference for the establishment of adolescent smartphone addiction interventions. Methods: A preliminary survey and follow-up were conducted on 8 907 middle and high school students in a district of Shenzhen in 2022 and 2023, respectively. Compulsive behaviours were measured by using the Mental Health Inventory for Middle School Students-60 Items (MMHI-60), smartphone addiction was assessed by using the Smartphone Addiction Scale-Short Version ( SAS- SV), and the associations between compulsive behaviours and smartphone addiction were analysed by using multilevel mixed-effects models and subgroup analyses. Results: Smartphone addiction detection rates among middle school students were significantly associated with genders, father s education level, mother s education level, study load subgroups, and whether or not they were single-parent families, and there were statistical differences ( χ 2=17.21-175.34, P <0.05). Students with compulsive behaviours were 2.98 times more likely to develop smartphone addiction than those without compulsive behaviours ( OR=2.98, 95%CI=2.77-3.22, P <0.05). Subgroup analysis of middle school students without smartphone addiction in the first year found that compulsive behaviours significantly predicted smartphone addiction ( OR= 1.76 , 95%CI=1.54-2.01, P <0.05). Conclusion There is a potential causal association between obsessive-compulsive behaviours and smartphone addiction in middle school students, and obsessive-compulsive behaviours in middle school students could significantly predicted the occurrence of smartphone addiction.

Objective: To investigate the changing trends for associations of anxiety and depressive symptoms with smartphone addiction among middle school students, so as to provide a scientific basis for preventing smartphone addiction in middle school students. Methods: From 2022 to 2023, a method of combining convenient sampling with cluster sampling was used to select 8 923 middle school students from 27 junior high schools and 3 senior high schools in a district of Shenzhen City between September 2022 (baseline, T1) and September 2023 (follow up, T2). The Smartphone Addiction Scale-Short Version (SAS-SV), Patients Health Questionnaire-9 Item (PHQ-9), and Generalized Anxiety Disorder 7-item Scale (GAD-7) were administered to assess smartphone addiction, anxiety and depressive symptoms. Mixed effects models were used to analyze the association of anxiety and depressive symptoms with smartphone addiction among middle school students. Results: From September 2022 to September 2023, the reported prevalence of smartphone addiction increased from 24.22% to 25.25% ( χ 2=45.71); and smartphone addiction scores [ 24.00 (16.00, 32.00),25.00(16.00, 33.00)], anxiety symptom scores [2.00(0.00, 7.00),3.00(0.00, 7.00)] and depressive symptom scores[3.00(0.00, 8.00),5.00(0.00, 9.00)] all significantly increased ( Z =-17.43, -42.38, -41.57) (all P <0.05). There were statistically significant difference in the distribution of anxiety and depression symptom levels among middle school students in 2022 and 2023 ( χ 2=85.15, 106.85, both P <0.05). After adjusting for covariates such as age, gender and family background, mixed effects models revealed dose response associations of anxiety and depressive symptoms with smartphone addiction among middle school students:mild anxiety symptom( OR =3.22), moderate to severe anxiety symptom ( OR =5.36), mild depressive symptom ( OR =3.32) and moderate to severe depressive symptom ( OR =6.13) were significantly associated with higher risks of smartphone addiction (all P <0.05). Interaction effect analysis found that co existing anxiety and depressive symptoms synergistically increased addiction risk by 5.60 times ( OR =5.60) compared to the asymptomatic group, with 32% of the combined risk attributable to their interaction ( S=1.64, AP =0.32)(both P < 0.05 ). Conclusions Anxiety and depressive symptoms are significantly associated with smartphone addiction, exhibiting a synergistic effect. Attention should be paid to emotional issues and smartphone addiction among middle school students.

The aim of this study is to investigate the protective effect of idebenone (IDE) combined with borneol (BO) against Parkinson's disease (PD). In this study, wild-type AB zebrafish and transgenic Tg ( vmat2: GFP) zebrafish with green fluorescence labeled dopamine neurons were used to establish the PD model with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride (MPTP). Following drug treatment, the behavioral performance and dopamine neuron morphology of zebrafish were evaluated, and regulation of dopamine signaling pathway-related genes was determined using RT-qPCR. The results showed that IDE combined with BO improved the behavioral disorders of zebrafish such as bradykinesia and shortening movement distance, also effectively reversed the damage of MPTP-induced dopaminergic neurons. At the same time, the expression of dopamine synthesis and transportation-related genes was up-regulated, and the normal function of the signal transduction pathway was restored. The combination showed a better therapeutic effect compared to the IDE monotherapy group. This study reveals the protective mechanism of IDE combined with BO on the central nervous system for the first time, which provides an important experimental basis and theoretical reference for clinical combination strategy in PD treatment.
Animals ; Zebrafish ; Signal Transduction/drug effects* ; Animals, Genetically Modified ; Dopamine/metabolism* ; Neuroprotective Agents/pharmacology* ; Disease Models, Animal ; Camphanes/pharmacology* ; Ubiquinone/pharmacology* ; Parkinson Disease/drug therapy* ; Dopaminergic Neurons/metabolism*

In the YY 0989.3-2023 standard, clause 27.106 specifies the protection test against electromagnetic interference, but it only briefly describes the test level for electromagnetic exposure, and does not detail the parameters of the torso. This study aims to explore the internal field distribution for different torso parameters under electromagnetic exposure, and explore the patterns of field distribution through modeling and simulation. The results indicate that the parameters of the torso significantly affect the internal field distribution. The findings of this study provide a basis and reference for the electromagnetic compatibility test for implantable neurostimulator products.
Electromagnetic Fields ; Implantable Neurostimulators ; Computer Simulation

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Over the past 30 years,nano-drug delivery systems(NDDS)have become a promising field of drug research.However,a poor knowledge of the in vivo process of NDDS,the limited methods of pharmacokinetic correlation,and the inability to effectively provide strong support for the construction of upstream drug as well as the evaluation of downstream pharmacology and toxicology have become the technical bottleneck for their clinical transformation.Lipid nanodrug(LND)is the most successful NDDS for industrial transformation with great biocompatibility.Taking LND as an example,this paper reviewed the delivery process and influencing factors in vivo,and summarized the regulatory mecha-nism of biological environments on drug release in vivo.Based on advanced spectroscopy and mass spectrometry techniques,the spatial and temporal distribution of the dynamic carrier particle/depolymer-ized molecule ratio and dynamic free/encapsulated drug ratio of LND in biological matrix were ana-lyzed.Finally,the existing problems and future developments in this field were summarized to provide references for the analysis of NDDS in vivo,and stimulate readers'interest in nanomedical research and development.

Objective To understand the changing trend of dementia disease burden attributed to high BMI in China from 1990-2019, and to provide a basis for the development of dementia prevention and control strategies. Methods Using data from the Global Burden of Disease Study 2019(GBD2019)，the changes in disease burden were analyzed using indicators such as deaths, disability adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs) and their standardized rates. The differences between sexes and age groups were compared. Joinpoint regression model was used to analyze the trend of changes in the disease burden of dementia attributable to high BMI in China. Results From 1990 to 2019, the burden of dementia disease attributed to high BMI continued to increase, with 20,300 more deaths, 404,200 more DALYs, and more than a four-fold increase in both mortality and DALYs rates. The overall burden of disease was greater for women than for men, but the rate of increase in the burden of disease was higher for men than for women. The disease burden in the age group of 80 and over was significantly higher than in other age groups. Conclusion Attention should be paid to people with high BMI, especially for the prevention and control of dementia risk in older age groups with high BMI. Active countermeasures should be taken to control the occurrence of dementia.

Cationic liposomes,as non-viral vectors,are widely used in gene therapy and gene silencing.Although numerous cationic liposomes have various structures,they can all improve the per-formance of gene delivery.As gene therapy is increasingly studied,it may be foreseen that new cationic lipoplexes will be explored.In this review,we aim to discuss four constituent domains of cationic lipids(headgroup,hydrophobic domain,linker and helper lipids)in gene delivery.This article attempts to demonstrate that various lipid structures show different transfection efficiency and cytotoxicity by sum-marizing the similarities and differences between the four parts of cationic lipids.Furthermore,their major influencing factors are covered.Finally,three clinical cases of ionizable lipids are described to reveal their characteristics and differences from cationic lipids.This paper is intended to provide a conceptual framework for the design of cationic liposomes and for the selection of cationic lipids.

Objective To analyze the clinical manifestations and epidemiological characteristics of influenza in Hubei. Methods Pharyngeal swab specimens from 16,500 patients with suspected influenza infection admitted to our hospital from January 2020 to December 2022 were selected. Viral detection and serotyping were performed by fluorescence quantitative polymerase chain reaction. Furthermore, the epidemiological and clinical data of patients were collected to analyze the clinical features and epidemiological characteristics of influenza viruses. Results A total of 16 500 clinical specimens were tested in this study, with a positive detection rate of 16.27% (2 684/16 500). The positive detection rate was 5.10% (862/16 500) for influenza A virus, 10.13% (1 672/16 500) for influenza B virus and 0.91% (150/16 500) for mixed influenza. The positive detection rate of influenza viruses was on the rise from 2020 to 2022 , reaching 18.43% in 2022. Seasonal distribution analysis denoted that the highest positive detection rates were observed in spring (18.23%) and winter (19.72%), with statistical difference (P<0.05). In terms of age distribution, patients<12 years (19.14%) had the highest positive detection rate, followed by those >60 years (17.71%), with statistical difference (P<0.05). From 2020 to 2022, the positive detection rate of influenza virus was 16.89% in males, which was higher than 15.63% in females (P<0.05). The main clinical symptoms were fever (86.89%) and cough (80.27%) for influenza A virus infections, cough (92.52%) and fever (86.06%) for influenza B virus infections, and cough (94.00%), fever (88.00%) and runny nose (86.00%) for mixed infections. Conclusion The influenza B viruses are the leading cause of influenza in Hubei from 2020 to 2022, and the infection demonstrates an increasing annual trend, with a high prevalence in winter and spring. Furthermore, children and the elderly are high-risk populations, and clinical manifestions are mainly cough and fever.