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

In this work, starting from 4-hydroxycoumarin, three series of 22 coumarin derivatives, among which 8 have not been reported in the literature, were synthesized and their in vitro anti-inflammatory activities and mechanisms of action were preliminarily investigated using mouse macrophage model. The results showed that most of the derivatives could significantly inhibit the production of pro-inflammatory factor NO, with compounds 2e, 2f, 2g, 2h, 2i, 2j, 4e, and 4f showing better anti-inflammatory activity than the positive control drug dexamethasone. Further experiments showed that compounds 2h and 4f significantly inhibited the production of pro-inflammatory factors IL-6, TNF-α and IL-1β in RAW264.7 macrophages, and could, therefore, be used as lead compounds for further studies.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Objective To investigate the correlation between WT1,BCR-ABL genes and interleukin-6(IL-6),vascular endothelial growth factor(VEGF),plasma protein C(PC),plasma protein S(PS)in patients with myeloproliferative neoplasms(MPN).Methods A total of 54 MPN patients treated in this hospital from January 2021 to January 2024 were selected as the MPN group,and 54 healthy subjects undergoing physical examination during the same period were selected as the control group.The gene relative expression levels of WT1,BCR-ABL and levels of IL-6,VEGF,PC,and PS were detected and compared between the two groups.The correlations between WT1,BCR-ABL gene relative expression levels and IL-6,VEGF,PC,PS levels were analyzed,and the diagnostic efficacy of WT1 and BCR-ABL genes for MPN was evaluated by receiver operat-ing characteristic(ROC)curve.Results Compared with the control group,the gene relative expression levels of WT1,BCR-ABL and the levels of IL-6 and VEGF in the MPN group were higher,while the levels of PC and PS were lower,with statistically significant differences(P<0.05).Pearson correlation analysis showed that WT1 and BCR-ABL gene relative expression levels were positively correlated with IL-6 and VEGF levels,and negatively correlated with PC and PS levels(P<0.05).The combined use of WT1 and BCR-ABL genes has higher diagnostic efficacy for MPN than single indicators,with an area under the curve(AUC)of 0.833 and a sensitivity of 88.69%.Conclusion The relative expression levels of WT1 and BCR-ABL genes are correlated with IL-6,VEGF,PC,and PS levels in MPN patients.The combination of WT1 and BCR-ABL genes can effec-tively diagnose MPN.

Objective To explore the influence of 3D printed individualized tissue compensators on the dose of the radiotherapy target area and the radiotherapy accuracy in intensity-modulated radiotherapy for vul-var carcinoma.Methods Twenty patients with vulvar cancer who visited this hospital from December 2022 to December 2024 were selected as the research subjects and divided into the control group and 3D group accord-ing to the random number table method,10 cases in each group.The control group used the conventional tis-sue compensators,while the 3D group used the 3D printed individualized tissue compensators.The dosimetric results of the target area and normal tissues were compared between the two groups.Results Compared with the control group,the maximum dose[(5 501.00+22.12)cGy vs.(5 659.60+84.59)cGy],average dose[(5 203.60+52.45)cGy vs.(5 258.70+42.95)cGy]and dose of 2％target volume[(5 360.30+63.70)cGy vs.(5 408.90+91.90)cGy]in the 3D group were lower,and the homogeneity index(0.12+0.01 vs.0.13+0.02)and conformity index(1.16+0.05 vs.1.23+0.04)were better,and the differences were statistically significant(P＜0.05).There was no statistically significant difference in dose of 30％clinical target volume of the bladder and rectum between the two groups(P＞0.05).During and after radiotherapy,among 20 cases,4 cases presented with grade 3 skin reactions,which were wet peeling,with 2 cases in each of the two groups.The remaining 16 cases had the grade 1 to 2 skin reactions.Conclusion In intensity-modulated radiotherapy for vulvar carcinoma,the dose distribution of 3D-printed personalized tissue compensators is superior to that of conventional organizational compensators.

The morbidity of gout is increasing year by year,and it has become a common and frequent disease.Once induced,the pain will reach its peak within 24 hours,which leading unsufferable pain to the patients.Buccal needling is a new micro-needling therapy created by Professor WANG Yongzhou's team,which was discovered and summarized in clinical practice of acupuncture after years of research.Buccal needling exerts certain efficacy in the treatment of acute gout.The progress of gout is related to the three levels of"body,qi and spirit".This paper discusses buccal needling in the treatment of acute gouty arthritis from the view of biological holographic theory,generalized triple energizer theory,and the theory of the integration of spirit and body,thus to provide certain reference for the further development of buccal needling in the treatment of pain-related diseases.

Objective To evaluate the patterns of sleep duration by integrating nocturnal and daytime sleep,and to explore their asso-ciations with activities of daily living(ADL)in middle-aged and older adults.Methods The data of sleep and ADL were obtained from 11 085 subjects aged 45 and older,which were collected from the China Health and Retirement Longitudinal Study(CHARLS).At enrollment in 2011,data on nocturnal and daytime sleep duration were collected through questionnaires.Firstly,subjects were divided into three groups based on the 33rd and 66th percentiles of nocturnal sleep duration,assigned scores of 1,2 and 3,respectively.Subsequently,subjects were divided into three groups based on the 33rd and 66th percentiles of daytime sleep du-ration,assigned scores of 3,2 and 1,respectively.Finally,the scores for nocturnal and daytime sleep were summed to create a total sleep score ranging from 2 to 6.A total sleep score of 6 was defined as sleep duration pattern 1,indicating a longer nocturnal sleep duration with no or shorter daytime sleep duration.Similarly,total sleep scores of 5,4,3 and 2 were defined as sleep duration patterns 2,3,4 and 5,respectively,with sleep duration pattern 5 indicating a shorter nocturnal sleep duration and a longer daytime sleep duration.The status of ADL was assessed using the Activities of Daily Living Scale(Katz edition)at baseline and during follow-up in 2013,2015 and 2018.The association between sleep duration patterns and the risk of ADL disability was evaluated us-ing a Cox proportional hazards model.Results A total of 63 015 person-years were followed,with 11 085 subjects,during which 3 239 individuals experienced ADL disability.The 33rd and 66th percentiles of the nocturnal sleep duration in the study population were 6.00 hours and 7.00 hours,respectively;while the 33rd and 66th percentiles of the daytime sleep duration were 0.00 hours and 1.00 hours,respectively.Of those,1 522 were classified into sleep duration pattern 1,2 196 into sleep duration pattern 2,4 299 into sleep duration pattern 3,2 304 into sleep duration pattern 4,and 764 into sleep dura-tion pattern 5.Compared to sleep duration pattern 1,the risk of ADL disability of patterns 3,4 and 5 were higher(P<0.05),with P-value for the trend less than 0.001,after adjusting for age,sex,body mass index,marital sta-tus,educational level,residence,smoking,drinking,history of chronic diseases,depression status and season.No interaction effect between gender,age and season,and sleep duration patterns was observed(P>0.05).Com-pared to subjects with nocturnal sleep duration≥9 hours and daytime sleep duration<2 hours,those with noctur-nal sleep duration<7 hours and daytime sleep duration≥2 hours had a higher risk of ADL disability(P<0.05).Conclusion Older adults who sleep less at night but take longer naps during the day are at a higher risk of experiencing limitations in their ADL.Sleep patterns may influence ADL among middle-aged and older populations,and man-aging their sleep duration patterns could help prevent the onset of ADL limitations.

Objective:To establish a genomic nucleic acid mass spectrometry detection platform for allelic risk associated with Alzheimer's disease.Methods:Whole blood samples of 61 patients diagnosed as Alzheimer's disease in the Affiliated Brain Hospital of Guangzhou Medical University from December 28th, 2023 to 31st, March 2024 were collected and deoxynucleic acid (DNA) was extracted, including 22 males and 39 females, aged (67.36 ± 8.18) years old. After screening out 17 risk gene loci in Chinese population, multiplex polymerase chain reaction primers, single-base extension primers and Sanger sequencing primers were designed. Ten samples were used for primer optimization and debugging through Sanger sequencing and time-of-flight mass spectrometry to establish a detection system. The remaining samples were genotyped using a time-of-flight mass spectrometer and verified by Sanger sequencing for accuracy evaluation. Five samples were selected for gradient dilution and then subjected to time-of-flight mass spectrometry detection to evaluate the detection limit. Three clinical samples, one case of Escherichia coli and one case of Staphylococcus aureus genomic DNA samples were selected for cross-reaction research. The anti-interference ability of the detection system was evaluated against hemolysis, chylous substances and conventional anticoagulants in the samples. Two samples, one wild and one homozygous mutation sample with representative peak shapes, were selected to evaluate the anti-interference ability. Four samples containing the common genotypes of all gene loci in the system were selected and repeated 10 times to evaluate the precision.Results:The minimum intensity of single-base extension primers on mass spectrometry is greater than half of the maximum intensity. All 17 risk gene loci screened were successfully typed. The time-of-flight mass spectrometry detection results of 1,037 loci from 61 samples showed that the genotyping detection rate was 100%. The genotypes of the 20 DNA samples were completely consistent with the results of Sanger sequencing, with an accuracy rate of 100%. The mass spectrometry detection results of five samples after gradient dilution indicated that the low detection limit was 5 ng of DNA. The reaction system has a strong anti-interference ability against hemolysis of samples, chylous substances, conventional anticoagulants and DNA cross-contamination. Homologous allele interference and no cross-reaction between the bacterial genome and 17 gene loci do not affect the risk genome detection results. The results of 10 repeated mass spectrometry tests on 4 samples showed that the precision was 100%.Conclusion:The genomic detection system of Alzheimer's disease risk has been successfully established to provide an auxiliary mean for disease diagnosis and risk assessment.

AIM:To investigated the mechanism of action of Yiqi tongfu xiere prescription(YTX)in treating mice with lipopolysaccharide(LPS)-in-duced acute lung injury(ALI).METHODS:According to the random number table,24 C57BL/6 mice were divided into 4 groups:control group(Control),model group(LPS),low dose group(YTX-L)and high dose group(YTX-H).Except for the control group,the mice models of acute lung injury were established by intratracheal instillation of LPS solu-tion(5 mg/kg).The low and high dose treatment groups were given intragastric administration con-tinuously for 14 days.After 24 hours,the lung tis-sue,bronchoalveolar lavage fluid(BALF)and serum of the four groups were taken for follow-up detec-tion.The degree of pulmonary edema was evaluat-ed by wet weight coefficient(wet to dry ratio,W/D)of lung tissue.The degree of alveolar inflamma-tion and pulmonary fibrosis were evaluated by HE and Masson staining,and the contents of BALF and serum inflammatory cytokines IL-1β and IL-6 were detected by ELISA.The protein expressions of α-SMA,FN,Col-Ⅰ and Col-Ⅲ were measured by West-ern blot.Determination of α-SMA,FN,Col-Ⅰ,MAPK,NF-κB mRNA expression by RT-PCR method.RE-SULTS:Compared with LPS group,the contents of BALF,IL-1β and IL-6 in serum,Wmax D ratio,lung pathology,serum α-SMA,FN,Col-Ⅰ,Col-Ⅲ protein expression and α-SMA,FN,Col-Ⅰ,MAPK,NF-κB mRNA expression in treatment group were signifi-cantly lower than those in control group.CONCLU-SION:YTX can significantly reduce the levels of pul-monary fibrosis markers such as α-SMA,FN,Col-Ⅰand Col-Ⅲ by inhibiting the activation of MAPK/NF-κB signal pathway,and improve alveolar inflamma-tion and pulmonary fibrosis in mice with lung inju-ry,suggesting that YTX can treat acute lung injury and provide a theoretical basis for the clinical use of YTX.

Objective This study aimed to investigate the relationship between multiple inflammatory markers and poor outcome in patients with intracerebral hemorrhage,and to compare their predictive abilities.Methods We retrospectively analyzed the patients with intracerebral hemorrhage admitted to the Department of Neurology of the First Affiliated Hospital of Nanchang University from January 1,2015 to March 31,2023.According to the Modified Rankin Scale at 90 days after onset,the patients were divided into good outcome(mRS≤2 points)and poor outcome(mRS score≥3 points).Clinical information,laboratory examinations and follow-up data were compared between the two groups.Inflammatory markers include neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),monocyte to high-density lipoprotein ratio(MHR),systemic inflammatory response index(SIRI),systemic immune-inflammation index(SII),white blood cell count to mean platelet volume ratio(WMR),lymphocyte to monocyte ratio(LMR),and systemic coagulation-inflammation index(SCI).Univariate and multivariate logistic regression analysis were used to analyze the predictors of poor prognosis after intracerebral hemorrhage,and receiver operating characteristic curve(ROC)was constructed to compare their predictive ability.Results A total of 510 patients with intracerebral hemorrhage were included.Of those,297(58.2%)had good outcome,and 213(41.8%)had poor outcome.Comparison of baseline characteristics demonstrated that patients with poor prognosis had higher levels of white blood cells,neutrophils,high-density lipoprotein,fibrinogen,NLR,PLR,SIRI,SII,WMR at admission,larger baseline hematoma volume and baseline perihematomal edema volume,a higher proportion of lobar hemorrhage,older age,and lower levels of platelets,lymphocytes,LMR,and SCI(P<0.05).Multivariate regression analysis showed that NLR(OR:1.081,95%CI:1.032～1.1131,P=0.001),SIRI(OR:1.089,95%CI:1.014～1.169,P=0.019),SII(OR:1.000,95%CI:1.000～1.001,P=0.011),WMR(OR:2.627,95%CI:1.267～5.445,P=0.009)were independently associated with poor prognosis in patients with ICH.In ROC analysis,the area under the curve of NLR(0.729,95%CI:0.685～0.774)was higher than SIRI(0.692,95%CI:0.645～0.738),SII(0.688,95%CI:0.641～0.735)and WMR(0.65,95%CI:0.602～0.698)for predicting poor outcomes.Conclusion NLR,SIRI,SII and WMR at admission are independently associated with poor outcomes in patients with intracerebral hemorrhage,and NLR has the strongest predictive ability.