Objective: To explore the relationship between non suicidal self injury (NSSI) behavior and serum lipid levels as well as thyroid function among college students with depression. Methods: A total of 169 college students with depression in the psychiatry departments of tertiary hospitals (grade 3A and 3B) in Ningbo from December 2023 to April 2025 were selected. The Adolescent Self injury Scale (ASIS) was used to assess the presence of NSSI, and participants were accordingly divided into a NSSI group ( n =51) and a non NSSI group ( n =118). General demographic data (including gender, age, and family situation) were collected from both groups. Blood tests were performed to measure lipid profiles [triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C)] and thyroid hormones [triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH)]. Multivariate Logistic regression was employed to analyze risk factors for NSSI, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of serum lipid and thyroid hormone levels for NSSI occurrence in college students with depression. Results: The levels of TC, LDL-C, and TSH in the NSSI group were (4.02±0.73) mmol/L, (2.32±0.36) mmol/L, and (6.57±1.95) mU/L , which were significantly higher than those in the non NSSI group [(3.41±0.56) mmol/L, (2.00±0.27) mmol/L, and ( 4.48± 1.09) mU/L, respectively] ( t =5.32, 5.60, 7.20, all P <0.05). Logistic regression analysis revealed that college students from single parent/reconstituted families, those who had experienced school bullying, and those with higher levels of TC, LDL-C, and TSH had a significantly increased risk of engaging in NSSI ( OR =5.22, 6.12, 5.90, 83.64, 3.64, all P <0.05). ROC curve analysis demonstrated that the combined detection of TC, LDL-C, and TSH had high diagnostic efficacy for predicting NSSI in college students with depression, with a sensitivity of 86.3% and a specificity of 94.9%. Conclusions NSSI behavior in college students with depression is associated with serum lipid levels and thyroid function. These biomarkers may serve as useful reference indicators for assessing the conditions of these patients.

Objective To investigate the relationship between serum cystatin C(CysC)level and the risk of Parkinson's disease(PD)in middle-aged and elderly people in China.Methods Based on the baseline survey data from the China Health and Retirement Longitudinal Study(CHARLS)in 2011,participants who were not diagnosed with PD at the time of the baseline survey were recruited.The onset of PD was tracked and followed up until 2020,and the participants were divided into PD group and non-PD group according to whether they were newly diagnosed with PD in 2020.Multivariable Logistic regression analysis was performed to assess the association between serum CysC level and the risk of PD.Subgroup and interaction analyses were performed to assess effect modifications by age,gender and depression.Additionally,restricted cubic spline(RCS)was used to explore the linear or non-linear relationship between serum CysC level and the risk of PD in different subgroups.Results We included a total of 3 339 subjects in this study,who consisted of 1 495 males(44.77％)and 1 844 females(55.23％).While baseline participants were followed until 2020,32 subjects had a new PD,and the incidence of PD was 0.96％.The median age of PD group was 63.00 years.Multivariable Logistic regression analysis found that CysC was an independent risk factor for the risk of PD,and CysC was positive significantly associated with the risk of PD(OR=2.34,95％ CI:1.14-4.82,P=0.021).Subgroup analysis showed that CysC was positively associated with PD in females(OR=2.70,95％ CI:1.30-5.58,P=0.007)and subjects aged 60 years or older(OR=5.29,95％ CI:1.69-16.53,P=0.004).RCS model indicated a linear relationship between serum CysC level and the risk of PD in females(Ptotal=0.018,Pnon-linear=0.062)and subjects aged 60 years or older(Ptotal=0.024,Pnon-linear=0.379).Conclusion High level of CysC may increase the risk of PD in middle-aged and elderly people,especially in females and those aged 60 years or older.

Objective To investigate the relationship between inflammation index and the severity of cere-bral small vessel disease.Methods A total of 168 patients with cerebral small vessel disease who were admit-ted to the Eighth People's Hospital of Hebei from August 2019 to October 2022 were selected as the study ob-jects.The study subjects were divided into cerebral small vessel disease with light burden(light burden group)and cerebral small vessel disease with medium-heavy burden(medium-heavy burden group)according to the total imaging burden score of cerebral small vessel disease.The basic data and systemic immune-inflam-matory index(SII),neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),and monocyte to lymphocyte ratio(MLR)were compared between the two groups.Spearman correlation analysis was used to evaluate the correlation between SII,NLR,PLR and MLR and the total imaging burden score of cerebral small vessel disease,and the influence of SII,NLR,PLR and MLR on the medium-heavy burden of cerebral small vessel disease was further analyzed by multivariate Logistic regression.Receiver operating characteristic(ROC)curves were plotted to analyze the predictive value of SII,NLR,PLR and MLR in the severity of cere-bral small vessel disease.Results The age,smoking history,hypertension history,neutrophil,platelet,SII,NLR,PLR and MLR in medium-heavy burden group were significantly higher than those in light burden group,and lymphocyte was significantly lower than that in light burden group,with statistical significance(P<0.05).Spearman correlation analysis showed that SII(r=0.377),NLR(r=0.516),PLR(r=0.486)and MLR(r=0.391)were positively correlated with the total imaging burden score of cerebral small vessel disease(P<0.001).Multivariate Logistic regression analysis showed that age,neutrophil,platelet,SII,NLR,PLR and MLR were independent risk factors for medium-heavy burden in cerebral small vessel disease,and lymphocyte was independent protective factor for medium-heavy burden in cerebral small vessel disease(P<0.05).ROC curve analysis results showed that the area under the curve of SII,NLR,PLR and MLR separately detected were 0.720(95%CI:0.646-0.787),0.802(95%CI:0.733-0.859),0.784(95%CI:0.714-0.843)and 0.728(95%CI:0.654-0.794),respectively.The area under the curve of the combined detection of the four indexes was higher than that of the single detection of each index(P<0.05).Conclusion The combined detection of SII,NLR,PLR and MLR has high predictive value for the severity of cerebral small vessel dis-ease,and is worthy of clinical promotion.

Current experimental and computational methods have limitations in accurately and efficiently classi-fying ion channels within vast protein spaces.Here we have developed a deep learning algorithm,GPT2 Ion Channel Classifier(GPT2-ICC),which effectively distinguishing ion channels from a test set con-taining approximately 239 times more non-ion-channel proteins.GPT2-ICC integrates representation learning with a large language model(LLM)-based classifier,enabling highly accurate identification of potential ion channels.Several potential ion channels were predicated from the unannotated human proteome,further demonstrating GPT2-ICC's generalization ability.This study marks a significant advancement in artificial-intelligence-driven ion channel research,highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data.Moreover,it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels. Several potential ion channels were predicated from the unannotated human proteome, further demonstrating GPT2-ICC's generalization ability. This study marks a significant advancement in artificial-intelligence-driven ion channel research, highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data. Moreover, it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Objective To investigate the role of Toll-like receptor 4(TLR4)in the regulation of homocys-teine(Hcy)-induced ferroptosis in macrophages.Methods Mouse macrophage cells RAW264.7 were cultured and divided into control group,Hcy intervention group(Hcy group),and Hcy plus ferroptosis inhibitor group(Hcy+Fer-1 group).After transfection with interference fragments,macrophages were treated with Hcy,and then divided into control group,Hcy intervention group(Hcy group),TLR4 interference negative control plus Hcy intervention group(si-NC+Hcy group),and TLR4 interference plus Hcy intervention group(si-TLR4+Hcy group).Macrophages were transfected with overexpression lentivirus and treated with Hcy,then were divided into control group,Hcy intervention group(Hcy group),a TLR4 overexpression negative control plus Hcy intervention group(OE-NC+Hcy group),and a TLR4 overexpression plus Hcy intervention group(OE-TLR4+Hcy group).After 48 hours of intervention,real-time fluorescent quantitative PCR and western blot were used to detect the expression levels of TLR4 in macrophages treated with Hcy;western blot was used to detect the expression levels of ferroptosis-related proteins ACSL4,GPX4,and FTH1 in macrophages,and ferrous ion assay kit to detect the concentration of Fe2+in macrophages;reactive oxygen species(ROS)assay kit and laser confocal microscopy were used to detect the content of intracellular reactive oxygen species.Results Compared with those in the control group,the expression level of the pro-ferroptosis protein ACSL4 was increased in the Hcy group(P<0.05),while the expression levels of anti-ferroptosis proteins GPX4 and FTH1 were decreased(P<0.05);the concentration of Fe2+was increased(P<0.05),and the content of ROS was increased.Meanwhile,the protein and mRNA expres-sion levels of TLR4 were both increased in the Hcy group(P<0.05).After macrophages were transfected with TLR4 interference fragments,compared with those in the si-NC+Hcy group,the expression levels of GPX4 and FTH1 were increased(P<0.05);the expression level of ACSL4 was decreased(P<0.05);the concentration of Fe2+was decreased(P<0.05),and the content of ROS was reduced in the si-TLR4+Hcy group.After macro-phages were transfected with TLR4 overexpression lentivirus,compared with those in the OE-NC+Hcy group,the expression levels of GPX4 and FTH1 were decreased(P<0.05),and the expression level of ACSL4 was increased(P<0.05)in the OE-TLR4+Hcy group.Conclusion Hcy induces the occurrence of ferroptosis in macrophages,and Toll-like receptor 4 has a positive feedback regulatory effect on ferroptosis in macrophages.

Objective:To study the characteristics of metabolites in lower resPiratory tract between coal workers' pneumoconiosis patients and dust exposure patients, and compare the differences of metabolites and their main metabolic pathways.Methods:From December 2020 to February 2021, through a prospective cross-sectional study, a total of 26 patients with coal workers' pneumoconiosis (metabolic group of coal workers' pneumoconiosis) were selected from the bronchoalveolar lavage treatment of coal workers' pneumoconiosis and dust exposure in the Respiratory and Critical Care Medicine Department of the 920th Hospital of the Joint Logistics Support Force during the same period. With 19 cases of dust exposure as the control group (dust exposure metabolic group), samples of alveolar lavage fluid were collected from 2 groups. Metabolites of the two groups were quantitatively analyzed by metabonomics technology, and the characteristics of metabolites and their metabolic pathways were compared. The metabolites with potential predictive value were screened by receiver operating characteristic curve (ROC curve) .Results:Through metabolomic analysis of alveolar lavage fluid in the coal workers' pneumoconiosis group and the dust contact group, a total of 28 different metabolites were screened, including trihydroxybutyric acid, alanine, ethanolamine, L-osan, proline (carboxyl), leucine, 2-hydroxyglutaric acid, proline, lactic acid, serine, valine and threonine in the coal workers' pneumoconiosis group. The levels of differential metabolites such as ornithine, isoleucine, threitol, glucose and lysine were higher ( P<0.05). The levels of different metabolites such as sarcoine, pelanoic acid, palmitic acid, heptadecanoic acid, n-butylamine, tetradecanoic acid, isobutylamine, aminoadipic acid, phosphate, uracil and cytosine were higher in the dust exposure group ( P<0.05). Two major metabolic pathways include glycine, serine and threonine metabolism, arginine and proline metabolism, biotin metabolism, and aminoacyl biosynthesis metabolism. Among the 17 metabolites increased in the coal workers' pneumoconiosis group, the AUC of threitol and lactic acid was greater than 0.8, and the specificity and sensitivity of the working characteristic curves of the two metabolites were 80% and 70%, respectively. Conclusion:There were significant differences in the metabolites of lower respiratory tract between patients with coal workers' pneumoconiosis and those exposed to dust, and the differences were related to multiple metabolic pathways. Threitol and lactic acid may have potential predictive value for pneumoconiosis.

Objective:To study the characteristics of metabolites in lower resPiratory tract between coal workers' pneumoconiosis patients and dust exposure patients, and compare the differences of metabolites and their main metabolic pathways.Methods:From December 2020 to February 2021, through a prospective cross-sectional study, a total of 26 patients with coal workers' pneumoconiosis (metabolic group of coal workers' pneumoconiosis) were selected from the bronchoalveolar lavage treatment of coal workers' pneumoconiosis and dust exposure in the Respiratory and Critical Care Medicine Department of the 920th Hospital of the Joint Logistics Support Force during the same period. With 19 cases of dust exposure as the control group (dust exposure metabolic group), samples of alveolar lavage fluid were collected from 2 groups. Metabolites of the two groups were quantitatively analyzed by metabonomics technology, and the characteristics of metabolites and their metabolic pathways were compared. The metabolites with potential predictive value were screened by receiver operating characteristic curve (ROC curve) .Results:Through metabolomic analysis of alveolar lavage fluid in the coal workers' pneumoconiosis group and the dust contact group, a total of 28 different metabolites were screened, including trihydroxybutyric acid, alanine, ethanolamine, L-osan, proline (carboxyl), leucine, 2-hydroxyglutaric acid, proline, lactic acid, serine, valine and threonine in the coal workers' pneumoconiosis group. The levels of differential metabolites such as ornithine, isoleucine, threitol, glucose and lysine were higher ( P<0.05). The levels of different metabolites such as sarcoine, pelanoic acid, palmitic acid, heptadecanoic acid, n-butylamine, tetradecanoic acid, isobutylamine, aminoadipic acid, phosphate, uracil and cytosine were higher in the dust exposure group ( P<0.05). Two major metabolic pathways include glycine, serine and threonine metabolism, arginine and proline metabolism, biotin metabolism, and aminoacyl biosynthesis metabolism. Among the 17 metabolites increased in the coal workers' pneumoconiosis group, the AUC of threitol and lactic acid was greater than 0.8, and the specificity and sensitivity of the working characteristic curves of the two metabolites were 80% and 70%, respectively. Conclusion:There were significant differences in the metabolites of lower respiratory tract between patients with coal workers' pneumoconiosis and those exposed to dust, and the differences were related to multiple metabolic pathways. Threitol and lactic acid may have potential predictive value for pneumoconiosis.

This paper reviews gamified mobile applications, summarizes their current application status in nurse training for pressure injury management, and analyzes the functions, uses, and limitations of pressure injury management mobile applications. The aim is to provide a reference for the development of gamified mobile applications for pressure injury management in China.

Objective To explore how to enhance the quality and efficiency of ethics committee operations based on an information management system.Methods This study analyzes the challenges in the ethical review of Investigator Initiated Trials(IIT)and compares existing ethics review systems in China.Using a tertiary hospital as an example,the paper details the practi-cal impact of an information management system for improving the management level of the ethics committee office and the effi-ciency of project reviews.Results The ethics review information management system evolved from basic usage and initial ethics review functions to include ethics tracking review and meeting review capabilities,offering comprehensive functionality.Conclu-sion The information management system enhances the efficiency of ethical review processes,but ongoing optimization is neces-sary to better align with the needs of clinical research in medical institutions.