Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective The purpose of writing the"expert consensus on humanistic care for patients in hospice care"(hereinafter referred to as the"consensus")aims to standardize the practice of humanistic care in the field of hospice care,ensuring that humanistic care is integrated throughout the entire service process for hospice care patients and their families.Methods A systematic search was conducted in domestic and foreign databases for literature related to hospice care and humanistic care,including guidelines,expert consensuses,systematic reviews or Meta-analyses,and evidence summaries.High-quality evidence was evaluated,extracted,and summarized to form the initial draft of the"consensus".From June to October 2024,20 experts from the fields of hospice care,nursing humanities,and evidence-based nursing were invited to participate in 1 round of expert consultation.Among them,13 experts were selected for 2 rounds of expert demonstration meetings.After collating and analyzing the experts' opinions,the initial draft was revised and refined,ultimately resulting in the final version of the"consensus".Results The effective response rate of the consultation questionnaire was 100％,with expert authority coefficient of 0.880,judgment coefficient of 0.935,and familiarity level of 0.825.The Kendall harmony coefficient of the expert consultation was 0.134(P＜0.05).The"consensus"consisted of 13 aspects,including the targets and objectives,principles,institutional guarantees,environmental requirements,etc.Conclusion This"consensus"possesses strong scientific rigor and practicality,which can provide guidance and references for the practice of humanistic care in the field of hospice care,promoting the standardization and humanization of hospice care services.

Objective To analyze the serum 25-hydroxy vitamin D[25(OH)D]levels and vitamin D nutri-tional status of 0-14 years old children in Hangzhou,and to provide scientific basis for the prevention of vita-min D deficiency.Methods A total of 26 225 healthy children aged 0 to 14 who were tested in Hangzhou Dian Medical Diagnosis Center from January 1,2021 to December 31,2023 were selected as the study objects.The 25(OH)D levels were detected by direct chemiluminescence method,and the 25(OH)D levels and vitamin D nutritional status of children with different genders,ages and seasons were analyzed and compared.Results The level of 25(OH)D in girls was slightly higher than that in boys,and the difference was statisti-cally significant(P＜0.05).With the increase of age,the level of 25(OH)D continued to decline,and the pro-portion of vitamin D deficiency and vitamin D insufficiency gradually increased.The level of 25(OH)D was the highest in children＜3 years old and the lowest in children 10-14 years old.There was statistical significance in the proportion of vitamin D nutritional status between boys and girls aged 10 to 14(P＜0.05).In the four seasons,children's 25(OH)D level is the highest in spring and the lowest in summer.The difference of 25(OH)D level and vitamin D nutritional status in different seasons was statistically significant(P＜0.05).The proportion of vitamin D deficiency and vitamin D insufficiency in winter was higher than that in other seasons,and the difference was statistically significant(P＜0.05).Conclusion The nutritional status of vitamin D in 0-14 year old children in Hangzhou is good,but the importance of vitamin D supplementation for children should not be ignored,and active publicity and education should be carried out to prevent vitamin D deficiency.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective:To explore the distribution characteristics and drug resistance of pathogenic bacteria in neonatal infectious diseases in Meizhou city from 2019 to 2023, and to guide the use of clinical antibacterial drugs.Methods:A retrospective analysis was conducted on the bacterial culture and drug sensitivity results of neonates with bacterial infectious diseases diagnosed and treated in Meizhou People's Hospital from January 2019 to December 2023. The distribution characteristics of pathogenic bacteria were observed, and the resistance of common pathogenic bacteria to antibacterial drugs was analyzed.Results:A total of 660 strains of pathogenic bacteria were collected, of which 434 isonates (65.76%) came from sputum, 111 isonates (16.82%) came from blood and 73 isonates (11.06%)came from umbilical secretions or other secretions.Gram-negative bacteria accounted for 55.45%(366/660), mainly Escherichia coli and Klebsiella pneumoniae. Gram-positive bacteria accounted for 42.42%(280/660), mainly Staphylococcus aureus and Streptococcus agalactiae. A total of 216 strains of multidrug-resistant bacteria were found, and the top three were extended spectrum beta-lactamases (ESBLs)-producing Escherichia coli, methicillin-resistant Staphylococcus aureus and ESBLs-producing Klebsiella pneumoniae.The resistance rates of Escherichia coli and Klebsiella pneumoniae to cefuroxime and cefotaxime were higher, and the resistance rates to ceftazidime, piperacillin-tazobactam and carbapenems were lower. The resistance rate of Staphylococcus aureus to penicillin was 91.61%. Streptococcus agalactiae was sensitive to penicillin, and both of them were sensitive to linezolid and vancomycin. Conclusions:The main pathogens of neonatal bacterial infection are Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Streptococcus agalactiae. The proportion of multidrug-resistant bacteria is high, mainly producing ESBLs bacteria. Antibiotics should be rationally selected according to the distribution and drug resistance of pathogens.

Objective:To analyze the exercise rehabilitation preference of stroke patients, and provide reference for clinical medical staff to formulate personalized exercise rehabilitation scheme, construct precise rehabilitation decision support system, and develop exercise rehabilitation intelligent service platform.Methods:A convenience sampling approach was employed to select the stroke patients in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from June to December 2024, a face to face cross-sectional survey was conducted using the questionnaire on exercise rehabilitation preferences of stroke patients based on the method of discrete choice experiments. The obtained data were analyzed using conditional Logit model.Results:Finally, 242 stroke patients were included, including 152 males and 90 females, aged 64 (56, 69) years. The six attributes included in this study: rehabilitation goal, rehabilitation setting, exercise intensity, exercise duration, exercise supervision method, and payment method. The relative importance of each attribute was ranked as follows: payment method (37.1%), exercise duration (15.5%), supervision method (14.3%), rehabilitation setting (14.1%), exercise intensity (11.4%), and rehabilitation goal (7.6%). The most preferred combination was identified as a rehabilitation goal of ≥70% recovery, professional institution/hospital as the setting, supervision by wearable device combined with professional guidance, low-intensity exercise, a duration of 30-60 minutes per session, and a self-payment rate of <30%. Under this combination, the probability of patients choosing the rehabilitation program was 75.4%.Conclusions:Stroke patients' preferences for exercise rehabilitation are influenced by multiple factors, with substantial heterogeneity observed across individuals. Rehabilitation programs should be tailored according to patients' preferences regarding goals, settings, duration, and other key attributes to enhance adherence and optimize rehabilitation outcomes.

Objective The purpose of writing the"expert consensus on humanistic care for patients in hospice care"(hereinafter referred to as the"consensus")aims to standardize the practice of humanistic care in the field of hospice care,ensuring that humanistic care is integrated throughout the entire service process for hospice care patients and their families.Methods A systematic search was conducted in domestic and foreign databases for literature related to hospice care and humanistic care,including guidelines,expert consensuses,systematic reviews or Meta-analyses,and evidence summaries.High-quality evidence was evaluated,extracted,and summarized to form the initial draft of the"consensus".From June to October 2024,20 experts from the fields of hospice care,nursing humanities,and evidence-based nursing were invited to participate in 1 round of expert consultation.Among them,13 experts were selected for 2 rounds of expert demonstration meetings.After collating and analyzing the experts' opinions,the initial draft was revised and refined,ultimately resulting in the final version of the"consensus".Results The effective response rate of the consultation questionnaire was 100％,with expert authority coefficient of 0.880,judgment coefficient of 0.935,and familiarity level of 0.825.The Kendall harmony coefficient of the expert consultation was 0.134(P＜0.05).The"consensus"consisted of 13 aspects,including the targets and objectives,principles,institutional guarantees,environmental requirements,etc.Conclusion This"consensus"possesses strong scientific rigor and practicality,which can provide guidance and references for the practice of humanistic care in the field of hospice care,promoting the standardization and humanization of hospice care services.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective:To explore the distribution characteristics and drug resistance of pathogenic bacteria in neonatal infectious diseases in Meizhou city from 2019 to 2023, and to guide the use of clinical antibacterial drugs.Methods:A retrospective analysis was conducted on the bacterial culture and drug sensitivity results of neonates with bacterial infectious diseases diagnosed and treated in Meizhou People's Hospital from January 2019 to December 2023. The distribution characteristics of pathogenic bacteria were observed, and the resistance of common pathogenic bacteria to antibacterial drugs was analyzed.Results:A total of 660 strains of pathogenic bacteria were collected, of which 434 isonates (65.76%) came from sputum, 111 isonates (16.82%) came from blood and 73 isonates (11.06%)came from umbilical secretions or other secretions.Gram-negative bacteria accounted for 55.45%(366/660), mainly Escherichia coli and Klebsiella pneumoniae. Gram-positive bacteria accounted for 42.42%(280/660), mainly Staphylococcus aureus and Streptococcus agalactiae. A total of 216 strains of multidrug-resistant bacteria were found, and the top three were extended spectrum beta-lactamases (ESBLs)-producing Escherichia coli, methicillin-resistant Staphylococcus aureus and ESBLs-producing Klebsiella pneumoniae.The resistance rates of Escherichia coli and Klebsiella pneumoniae to cefuroxime and cefotaxime were higher, and the resistance rates to ceftazidime, piperacillin-tazobactam and carbapenems were lower. The resistance rate of Staphylococcus aureus to penicillin was 91.61%. Streptococcus agalactiae was sensitive to penicillin, and both of them were sensitive to linezolid and vancomycin. Conclusions:The main pathogens of neonatal bacterial infection are Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Streptococcus agalactiae. The proportion of multidrug-resistant bacteria is high, mainly producing ESBLs bacteria. Antibiotics should be rationally selected according to the distribution and drug resistance of pathogens.

Objective:To analyze the exercise rehabilitation preference of stroke patients, and provide reference for clinical medical staff to formulate personalized exercise rehabilitation scheme, construct precise rehabilitation decision support system, and develop exercise rehabilitation intelligent service platform.Methods:A convenience sampling approach was employed to select the stroke patients in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from June to December 2024, a face to face cross-sectional survey was conducted using the questionnaire on exercise rehabilitation preferences of stroke patients based on the method of discrete choice experiments. The obtained data were analyzed using conditional Logit model.Results:Finally, 242 stroke patients were included, including 152 males and 90 females, aged 64 (56, 69) years. The six attributes included in this study: rehabilitation goal, rehabilitation setting, exercise intensity, exercise duration, exercise supervision method, and payment method. The relative importance of each attribute was ranked as follows: payment method (37.1%), exercise duration (15.5%), supervision method (14.3%), rehabilitation setting (14.1%), exercise intensity (11.4%), and rehabilitation goal (7.6%). The most preferred combination was identified as a rehabilitation goal of ≥70% recovery, professional institution/hospital as the setting, supervision by wearable device combined with professional guidance, low-intensity exercise, a duration of 30-60 minutes per session, and a self-payment rate of <30%. Under this combination, the probability of patients choosing the rehabilitation program was 75.4%.Conclusions:Stroke patients' preferences for exercise rehabilitation are influenced by multiple factors, with substantial heterogeneity observed across individuals. Rehabilitation programs should be tailored according to patients' preferences regarding goals, settings, duration, and other key attributes to enhance adherence and optimize rehabilitation outcomes.