BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

OBJECTIVE To understand the development status and existing problems of traditional Chinese medicine（TCM） pharmacists in public TCM hospitals in China， aiming to provide suggestions for the competent departments to formulate management policies for TCM pharmacists and promote the healthy development of TCM. METHODS The data on the number and professional titles of TCM pharmacists in public TCM hospitals in China from 2019 to 2023 were collected. Descriptive analysis was employed to analyze the number， distribution and professional titles of TCM pharmacists in public TCM hospitals across the country， and to measure the quantity shortfalls of the number of TCM pharmacists in these hospitals. RESULTS From 2019 to 2023， the number of TCM pharmacists in public TCM hospitals in China grew slowly， with an average annual growth rate of 2.56%. However， the proportion of TCM pharmacists to the total number of pharmacists in public TCM hospitals gradually decreased， with an average annual growth rate of －0.65%. In terms of hospital grades， the number of TCM pharmacists in tertiary public TCM hospitals showed positive growth， while those in secondary and primary public TCM hospitals showed negative growth. In terms of hospital types， the average annual growth rate of TCM pharmacists in TCM hospitals was 2.22%， in integrated Chinese and Western medicine hospitals it was 7.97%， and in ethnic minority medicine hospitals it was 2.74%. The development of TCM pharmacists in different provinces was uneven. The annual growth rate of TCM pharmacists in Guizhou exceeded 10%， while the growth rate in Hunan and Heilongjiang was negative. In 2023， the number of TCM pharmacists per thousand population in public TCM hospitals was 0.03， indicating a relatively low staffing level. The professional titles of TCM pharmacists in public TCM hospitals were mainly primary and E-mail：601907549@qq.com intermediate， with a total of 67.33%. According to the calculation that the proportion of TCM pharmacists to pharmacists was not less than 60%， public TCM hospitals and hospitals of integrated TCM and Western medicine should be reconfigured with TCM pharmacists 6 212 and 1 288 people， respectively. CONCLUSIONS The number of TCM pharmacists in public TCM hospitals is growing slowly， with insufficient staffing levels， relatively low professional titles， and uneven distribution and development across provinces. It is suggested that relevant competent departments strengthen policy guidance， increase the attention given by the state level to TCM pharmacists， strengthen the construction of the talent team for TCM pharmacists， improve the quality and optimize the allocation of TCM pharmacist talents in order to promote the high-quality development of TCM services.

ObjectiveTo investigate the effects of different concentrations of Shaoyaotang-containing serum on lipopolysaccharide （LPS）-induced inflammation of human colorectal adenocarcinoma （Caco-2） cells by inhibiting apoptosis via activating the tumor necrosis factor （TNF） receptor superfamily member 6 （Fas）/Fas ligand （FasL） pathway. MethodsCaco-2 cells were allocated into blank， model （LPS， 10 mg·L^-1）， Shaoyaotang-containing serum （5%， 10%， 15%， 20%）， and Fas inhibitor （KR-33493， 20 mmol·L^-1） groups. Except the blank group， the other groups were stimulated with 10 mg·L^-1 LPS for 24 h for the modeling of inflammation. After successful modeling， the blank， Fas inhibitor， and model groups were treated with blank serum， and the Shaoyaotang-containing serum groups were treated with the serum samples at corresponding concentrations for 24 h. The Fas inhibitor group was subjected to KR-33493 pretreatment for 1 h. Cell proliferation and viability were examined by the cell-counting kit-8 （CCK-8） method. The levels of interleukin （IL）-6， IL-1β， and TNF-α were measured by enzyme-linked immunosorbent assay. Apoptosis was detected by flow cytometry. The protein and mRNA levels of Fas， FasL， cysteinyl aspartate-specific proteinase （Caspase）-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsCompared with the blank group， the model group presented a decrease in cell survival rate （P<0.01）. Compared with that in the model group， the cell survival rate showed no significant change in the 5% Shaoyaotang-containing serum group but increased in the 10%， 15%， and 20% Shaoyaotang-containing serum groups （P<0.01）. Since there was no statistical difference between the 5% Shaoyaotang-containing serum group and the model group， 10%， 15%， and 20% Shaoyaotang-containing sera were selected for the follow-up study. Compared with the blank group， the model group showed risen levels of IL-6， IL-1β， and TNF-α （P<0.01）， an increased apoptosis rate （P<0.01）， up-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.01）， and down-regulated protein and mRNA levels of Bcl-2 （P<0.01）. Compared with the model group， the Fas inhibitor group and the 10%， 15%， and 20% Shaoyaotang-containing serum groups showed declined levels of IL-6， IL-1β， and TNF-α （P<0.01）， decreased apoptosis rates （P<0.01）， down-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of Bcl-2 （P<0.05， P<0.01）. In addition， the 15% and 20% Shaoyaotang-containing serum groups had lower levels of IL-6， IL-1β， and TNF-α （P<0.05， P<0.01）， lower apoptosis rates （P<0.05， P<0.01）， lower protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and higher protein and mRNA levels of Bcl-2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can reduce the content of inflammatory factors in Caco-2 cells， down-regulate the protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax， and up-regulate the protein and mRNA levels of Bcl-2 under the intervention of LPS by regulating the Fas/FasL pathway and inhibiting the apoptosis of intestinal epithelial cells in ulcerative colitis.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

ObjectiveTo investigate the effects of different concentrations of Shaoyaotang-containing serum on lipopolysaccharide （LPS）-induced inflammation of human colorectal adenocarcinoma （Caco-2） cells by inhibiting apoptosis via activating the tumor necrosis factor （TNF） receptor superfamily member 6 （Fas）/Fas ligand （FasL） pathway. MethodsCaco-2 cells were allocated into blank， model （LPS， 10 mg·L^-1）， Shaoyaotang-containing serum （5%， 10%， 15%， 20%）， and Fas inhibitor （KR-33493， 20 mmol·L^-1） groups. Except the blank group， the other groups were stimulated with 10 mg·L^-1 LPS for 24 h for the modeling of inflammation. After successful modeling， the blank， Fas inhibitor， and model groups were treated with blank serum， and the Shaoyaotang-containing serum groups were treated with the serum samples at corresponding concentrations for 24 h. The Fas inhibitor group was subjected to KR-33493 pretreatment for 1 h. Cell proliferation and viability were examined by the cell-counting kit-8 （CCK-8） method. The levels of interleukin （IL）-6， IL-1β， and TNF-α were measured by enzyme-linked immunosorbent assay. Apoptosis was detected by flow cytometry. The protein and mRNA levels of Fas， FasL， cysteinyl aspartate-specific proteinase （Caspase）-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsCompared with the blank group， the model group presented a decrease in cell survival rate （P<0.01）. Compared with that in the model group， the cell survival rate showed no significant change in the 5% Shaoyaotang-containing serum group but increased in the 10%， 15%， and 20% Shaoyaotang-containing serum groups （P<0.01）. Since there was no statistical difference between the 5% Shaoyaotang-containing serum group and the model group， 10%， 15%， and 20% Shaoyaotang-containing sera were selected for the follow-up study. Compared with the blank group， the model group showed risen levels of IL-6， IL-1β， and TNF-α （P<0.01）， an increased apoptosis rate （P<0.01）， up-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.01）， and down-regulated protein and mRNA levels of Bcl-2 （P<0.01）. Compared with the model group， the Fas inhibitor group and the 10%， 15%， and 20% Shaoyaotang-containing serum groups showed declined levels of IL-6， IL-1β， and TNF-α （P<0.01）， decreased apoptosis rates （P<0.01）， down-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of Bcl-2 （P<0.05， P<0.01）. In addition， the 15% and 20% Shaoyaotang-containing serum groups had lower levels of IL-6， IL-1β， and TNF-α （P<0.05， P<0.01）， lower apoptosis rates （P<0.05， P<0.01）， lower protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and higher protein and mRNA levels of Bcl-2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can reduce the content of inflammatory factors in Caco-2 cells， down-regulate the protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax， and up-regulate the protein and mRNA levels of Bcl-2 under the intervention of LPS by regulating the Fas/FasL pathway and inhibiting the apoptosis of intestinal epithelial cells in ulcerative colitis.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.