ObjectiveTo explore the role of cuproptosis and identify cuproptosis-related genes in Wilson disease （WD） through bioinformatics analysis and clinical validation，providing implications and directions for the diagnosis and treatment of WD. Methods（1） Screening of target genes： The differentially expressed genes （DEGs） between WD and healthy control were obtained from GeneCards，and the cuproptosis-related genes were obtained from Gene Expression Omnibus （GEO） and published literature.The cuproptosis-related genes in WD were obtained by intersection.Through gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses，the specific biological process，functions or metabolic pathways of cuproptosis-related genes in WD were predicted.Molecular docking and PyMOL visualization were then performed to analyze and verify the potential regulatory mechanism of Gandou Fumu Decoction for cuproptosis.（2）Validation of target genes： The blood samples of 15 WD patients treated in the department of encephalopathy and 15 healthy volunteers undergoing physical examinations in the health management center were randomly collected from the First Affiliated Hospital of Anhui University of Chinese Medicine.The expression levels of target genes were determined by Western blot and real-time PCR. Results（1） A total of 3 607 DEGs in WD were obtained from GSE107323 in GEO，and 68 cuproptosis-related genes were obtained from GeneCards and published literature.Twelve common target genes were obtained by intersection，including three up-related genes（SQSTM1，MIF1，and TAX1BP1） and nine down-regulated genes（CP，SERPINE1，AOC3，GPX4，SLC27A5，VEGF-A，PDHB，PDK1，and ATP7B）.The common target genes were mainly enriched in monocarboxylic acid metabolism，oxidoreductase activity，negative regulation of molecular functions，which mainly involved HIF-1，ferroptosis and other signaling pathways.Molecular docking and PyMOL visualization results showed Gandou Fumu Decoction had good binding ability with the cuproptosis-related genes PDK1，SERPINE1，VEGFA，and AOC3 in WD.（2）A total of 30 blood samples were collected，including 15 WD patients and 15 health volunteers.Western blot results showed that expression levels of target genes were consistent with the results obtained by bioinformatics analysis.RT-qPCR results showed that compared with healthy volunteers，WD patients had down-regulated mRNA levels of SERPINE1，GPX4，SLC27A5，and VEGF-A and up-regulated mRNA levels of SQSTM1 and MIF1（P<0.05）. ConclusionThe expression levels of cuproptosis-related genes in WD patients are consistent with the results predicted by bioinformatics analysis.The characteristic preparation Gandou Fumu Decoction of Xin'an Medicine showed good binding abilities with the cuproptosis-related genes in WD.Cuproptosis may play a key role in the pathophysiological mechanism of WD，which can provide a new target for the diagnosis and treatment of WD.

OBJECTIVE: To observe the efficacy and safety of Tiaowei Jiannao acupuncture (acupuncture for regulating defensive qi and nourishing brain) for post-ischemic stroke insomnia (PISI). METHODS: A total of 96 patients with PISI were randomized into an acupuncture group (32 cases, 1 case was excluded), a medication group (32 cases, 1 case dropped out, 1 case was excluded) and a sham-acupuncture group (32 cases, 1 case dropped out, 1 case was excluded). In the acupuncture group, Tiaowei Jiannao acupuncture was applied at bilateral Shenmai (BL62), Zhaohai (KI6), Hegu (LI4), Taichong (LR3), and Baihui (GV20), Sishencong (EX-HN1), Yintang (GV24⁺), Shenting (GV24), once a day, 1-day interval was taken after 6-day treatment, for 3 weeks totally. In the medication group, eszopiclone tablet was given orally, 1-3 mg a time, once a day for 3 weeks. In the sham-acupuncture group, non-invasive sham acupuncture was applied, the acupoint selection, frequency and course of treatment were the same as the acupuncture group. Before treatment, after 2,3 weeks of treatment, the scores of Pittsburgh sleep quality index (PSQI), self-rating sleep scale (SRSS), National Institutes of Health Stroke scale (NIHSS), Hamilton depression scale-17 (HAMD-17) were observed; before and after treatment, the sleep parameters were recorded using polysomnography (PSG); and the efficacy and safety were evaluated after treatment in the 3 groups. RESULTS: After 2,3 weeks of treatment, the scores of PSQI, HAMD-17 and SRSS in the acupuncture group and the medication group, as well as the SRSS scores in the sham-acupuncture group were decreased compared with those before treatment (P<0.05); after 2 weeks of treatment, the NIHSS score in the acupuncture group was decreased compared with that before treatment (P<0.05); after 3 weeks of treatment, the NIHSS scores in the acupuncture group, the medication group and the sham-acupuncture group were decreased compared with those before treatment (P<0.05). After 3 weeks of treatment, the scores of PSQI, SRSS, HAMD-17 and NIHSS in the acupuncture group and the medication group, as well as the NIHSS score in the sham-acupuncture group were decreased compared with those after 2 weeks of treatment (P<0.05). After 2,3 weeks of treatment, the scores of PSQI, SRSS and HAMD-17 in the acupuncture group and the medication group were lower than those in the sham-acupuncture group (P<0.05), the NIHSS scores in the acupuncture group were lower than those in the medication group and the sham-acupuncture group (P<0.05); after 3 weeks of treatment, HAMD-17 score in the acupuncture group was lower than that in the medication group (P<0.05), the NIHSS score in the medication group was lower than that in the sham-acupuncture group (P<0.05). Compared before treatment, after treatment, the total sleep time was prolonged (P<0.05), the wake after sleep onset, sleep latency, and non-rapid eye movement (NREM) sleep latency were shortened (P<0.05), the sleep efficiency was improved (P<0.05), the number of awakenings was reduced (P<0.05), the percentage of rapid eye movement (REM%) and the percentage of NREM stage 1 (N1%) were decreased (P<0.05), the percentage of NREM stage 2 (N2%) and the percentage of NREM stage 3 (N3%) were increased (P<0.05) in the acupuncture group and the medication group; the sleep latency was shortened in the sham-acupuncture group (P<0.05). After treatment, the PSG indexes in the acupuncture group and the medication group were superior to those in the sham-acupuncture group (P<0.05); in the acupuncture group, the number of awakenings was less than that in the medication group (P<0.05), the REM% and N1% were lower than those in the medication group (P<0.05), the N2% and N3% were higher than those in the medication group (P<0.05). The total effective rate were 93.5% (29/31) and 90.0% (27/30) in the acupuncture group and the medication group respectively, which were higher than 10.0% (3/30) in the sham-acupuncture group (P<0.05). There was no serious adverse events in any of the 3 groups. CONCLUSION Tiaowei Jiannao acupuncture improves the insomnia symptoms in patients with ischemic stroke, improves the quality of sleep, increases the deep sleep, promotes the recovery of neurological function, and relieves the depression. It is effective and safe for the treatment of PISI.
Humans ; Acupuncture Therapy ; Male ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Female ; Middle Aged ; Aged ; Acupuncture Points ; Treatment Outcome ; Adult ; Ischemic Stroke/complications* ; Stroke/complications* ; Sleep

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: To identify early potential risk factors for hospital-acquired pneumonia (HAP) in patients with mild traumatic brain injury (mTBI), construct a risk prediction model, and evaluate its predictive efficacy. METHODS: A case-control study was conducted using clinical data from mTBI patients admitted to the neurosurgery department of Changzhou Second People's Hospital from September 2021 to September 2023. The patients were divided into two groups based on whether they developed HAP. Clinical data within 48 hours of admission were statistically analyzed to identify factors influencing HAP occurrence through univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection to identify the most influential variables. The dataset was divided into training and validation sets in a 7:3 ratio. A multivariate Logistic regression analysis was then performed using the training set to construct the prediction model, exploring the risk factors for HAP in mTBI patients and conducting internal validation in the validation set. Receiver operator characteristic curve (ROC curve), decision curve analysis (DCA), and calibration curve were utilized to assess the sensitivity, specificity, decision value, and predictive accuracy of the prediction model. RESULTS: A total of 677 mTBI patients were included, with 257 in the HAP group and 420 in the non-HAP group. The significant differences were found between the two groups in terms of age, maximum body temperature (MaxT), maximum heart rate (MaxHR), maximum systolic blood pressure (MaxSBP), minimum systolic blood pressure (MinSBP), maximum respiratory rate (MaxRR), cause of injury, and laboratory indicators [C-reactive protein (CRP), procalcitonin (PCT), neutrophil count (NEUT), erythrocyte sedimentation rate (ESR), fibrinogen (FBG), fibrinogen equivalent units (FEU), prothrombin time (PT), activated partial thromboplastin time (APTT), total cholesterol (TC), lactate dehydrogenase (LDH), prealbumin (PAB), albumin (Alb), blood urea nitrogen (BUN), serum creatinine (SCr), hematocrit (HCT), hemoglobin (Hb), platelet count (PLT), glucose (Glu), K⁺, Na⁺], suggesting they could be potential risk factors for HAP in mTBI patients. After LASSO regression analysis, the key risk factors were enrolled in the multivariate Logistic regression analysis. The results revealed that the cause of injury being a traffic accident [odds ratio (OR) = 2.199, 95% confidence interval (95%CI) was 1.124-4.398, P = 0.023], NEUT (OR = 1.330, 95%CI was 1.214-1.469, P < 0.001), ESR (OR = 1.053, 95%CI was 1.019-1.090, P = 0.003), FBG (OR = 0.272, 95%CI was 0.158-0.445, P < 0.001), PT (OR = 0.253, 95%CI was 0.144-0.422, P < 0.001), APTT (OR = 0.689, 95%CI was 0.578-0.811, P < 0.001), Alb (OR = 0.734, 95%CI was 0.654-0.815, P < 0.001), BUN (OR = 0.720, 95%CI was 0.547-0.934, P = 0.016), and Na⁺ (OR = 0.756, 95%CI was 0.670-0.843, P < 0.001) could serve as main risk factors for constructing the prediction model. Calibration curves demonstrated good calibration of the prediction model in both training and validation sets with no evident over fitting. ROC curve analysis showed that the area under the ROC curve (AUC) of the prediction model in the training set was 0.943 (95%CI was 0.921-0.965, P < 0.001), with a sensitivity of 83.6% and a specificity of 91.5%. In the validation set, the AUC was 0.917 (95%CI was 0.878-0.957, P < 0.001), with a sensitivity of 90.1% and a specificity of 85.0%. DCA indicated that the prediction model had a high net benefit, suggesting practical clinical applicability. CONCLUSIONS The cause of injury being a traffic accident, NEUT, ESR, FBG, PT, APTT, Alb, BUN, and Na⁺ are identified as major risk factors influencing the occurrence of HAP in mTBI patients. The prediction model constructed using these parameters effectively assesses the likelihood of HAP in mTBI patients.
Humans ; Risk Factors ; Case-Control Studies ; Logistic Models ; Healthcare-Associated Pneumonia/epidemiology* ; Brain Injuries, Traumatic/complications* ; Male ; Female ; ROC Curve ; Pneumonia/etiology* ; Middle Aged ; Adult

As a classic work of Japanese Chinese medicine, Huang Han Yi Xue, with its ancient prescription school theories and Western medical principles, influenced the formation of Hu Xishu's academic thinking on cold-induced disease. This article combined Huang Han Yi Xue with the recordings and manuscripts of Hu's existing lectures to show another perspective on the flow of Hu's academic thought on cold-induced disease. It is considered that the influence of Huang Han Yi Xue made Hu different from the traditional typhoid scholars. Hu abandoned the annotations of Huang Di Nei Jing, emphasized the relativity of prescriptions and syndrome, focused on the state of Mingxuan reaction, paid attention to food, water and blood stasis, explained the essence of disease with physiological and anatomical knowledge, innovated the cognition of the six meridians and the eight compendiums, and formed a new theoretical system.

Objective To investigate the factors influencing the development of extra-pulmonary tuberculosis(EPTB)in patients with viral hepatitis complicated by pulmonary tuberculosis(PTB).Methods A retrospective analysis was conducted on 427 patients with Hepatitis B Virus(HBV)and Hepatitis C Virus(HCV)infections complicated by PTB admitted to the tuberculosis department of Kunming Third People's Hospital from January 2015 to December 2020.Patients were divided into the EPTB complication group(n=72)and the non-EPTB complication group(n=355)based on the presence of EPTB.Clinical treatment data of patients were collected.Univariate and multivariate Logistic regression analyse were used to screen independent risk factors for EPTB as predictive factors.A nomogram prediction model was established for Extrapulmonary Tuberculosis(EPTB)complications in patients with viral hepatitis and Pulmonary Tuberculosis(PTB),evaluated using the Hosmer-Lemeshow test and ROC curve analysis.Results Among the 427 patients,292(68.3%)were male and 135(31.7%)were female,with 72 cases of EPTB,resulting in an incidence rate of 16.86%.In the EPTB group,there were 34 males(47.2%)and 38 females(52.8%).The types of EPTB included tuberculous pleuritis(21 cases,29%),tuberculous peritonitis(16 cases,22%),lymph node tuberculosis(13 cases,18%),tuberculous encephalitis(5 cases,6%),intestinal tuberculosis(6 cases,8%),bone tuberculosis(5 cases,6%),pelvic tuberculosis(3 cases,4%),and genitourinary tuberculosis(3 cases,4%).Multivariate logistic regression analysis showed that gender(OR=0.425,95%CI:0.250-0.722,P=0.02),low triglyceride(TG)levels(OR=0.837,95%CI:0.717-0.978,P=0.025),the tuberculosis-specific antigen A(ESAT-6)(OR=1.007,95%CI:1.003～1.011 were independent influencing factors for EPTB in patients with PTB complicated by HBV and HCV infections.The optimal cutoff value for the nomogram model is 0.192,with a sensitivity of 0.611,specificity of 0.710,Youden index of 0.741,positive likelihood ratio of 2.103,and negative likelihood ratio of 0.548.The Hosmer-Lemeshow test yielded χ2=2.631,P=0.955.ROC curve analysis showed an AUC of 0.693,95%CI:0.629 1～0.7574.Conclusion The prediction model based on gender,low TG levels and ESAT-6 can well predict the occurrence of EPTB to some extent,providing a reference for clinical treatment.

Objective: To investigate the impact of tumor necrosis factor ligand superfamily member 13(TNFSF13) derived from M2 macrophages on temozolomide(TMZ) resistanceviaregulating interferon regulatory factor 8(IRF8) in glioblastoma(GBM) cells. Methods: Immunohistochemistry(IHC) was used to detect the expression of TNFSF13 in normal brain tissues and GBM tissues. ELISA was used to measure the expression of TNFSF13 in the conditioned media(CM) of M0-type macrophages and M2-type macrophages. M0-CM and M2-CM were used to culture U251 sensitive(U251/S) and resistant(U251/R) cells. The TMZ treatment group was also treated with 800 μmol/L TMZ. The U251/R cells were divided into the following groups: con group, M2vector-CM group, M2vector-CM+TMZ group, M2TNFSF13-CM group, M2TNFSF13-CM+TMZ group, si-IRF8 group, and si-IRF8+M2TNFSF13-CM group. CCK-8 assay was used to detect cell viability and calculate the IC50value. Transwell assay was used to detect cell invasion. Flow cytometry was used to detect apoptosis. Western blot was used to detect the expression of IRF8. Nude mouse xenograft models were constructed and the nude mice were divided into the following groups: U251+M2si-NCgroup, U251+M2si-TNFSF13group, U251+M2si-NC+TMZ group, U251+M2si-TNFSF13+TMZ group. The tumor volume and mass of each group were measured, and IHC was used to detect the expression of TNFSF13 and CD206 in tumor tissues of each group. Results: Compared with adjacent tissues and M0-CM, the expression of TNFSF13 was up-regulated in cancer tissues and M2-CM. Compared with the M0-CM group, the IC50value of TMZ and the number of cell invasions in U251/S and U251/R cells in the M2-CM group significantly increased(allP<0.05). Overexpression of TNFSF13 in M2 macrophages could promote the IC50value of TMZ in U251/R cells, promote cell invasion, and inhibit cell apoptosis(allP<0.05). Overexpression of TNFSF13 promoted the expression of IRF8, and knocking down IRF8 could attenuate the TMZ resistance of U251/R mediated by overexpression of TNFSF13.In vivostudies showed that knocking down TNFSF13 alone or combined with TMZ treatment significantly inhibited tumor growth and reduced the expression of TNFSF13 and CD206. Conclusion TNFSF13 derived from M2 macrophages promotes TMZ resistance in GBM cells by activating IRF8.

Objective To explore the effects of different types of drinking water on the growth and fecal flora of mice.Methods Specific pathogen-free NIH mice were randomly divided into five groups,32 mice each group,with half males and half females in each group.The group were given either purified water(control group),acidified water,alkalized water,weakly acidic water or solid water.Diet and body weight were monitored continuously for 20 days.After the experiment,animal fecal samples were collected,and the V3-V4 region was amplified with bacterial 16S rDNA universal primers.An Illumina Miseq high-throughput sequencing platform was used for high-throughput sequencing,and microbial community,α diversity and β diversity were analyzed by bioinformatics method.Results The body weight of female mice given different pH values of weakly acidic water was higher,while the weight of the other groups was lower,than that of the control group(P＞0.05).The body weight of male mice in the acidified water group was higher,while that of other groups was lower,than that of control group,but there was no statistical difference between the groups(P＞0.05).The body weights of male and female mice in the solid water group were lower than those in the control group(P＜0.05).The food and water intake of the female animals in the alkaline water group and the water intake of female animals in the solid water group were lower than those of the other groups.OTU clustering analysis showed that the data volume of the sequencing was reasonable,and the fecal flora species of NIH mice were divided into five phyla,among which Bacteroides and Firmicutes were dominant.Unclassified Pseudopurpuromonas,Lactobacillus and Alistipes were the main genera.There were differences in fecal flora abundance and diversity among the mice given the five drinking water types.α analysis showed that the acidified water group had the highest flora abundance and diversity,while the solid water group had the lowest flora diversity.β analysis showed that the fecal flora composition in the solid water group was the closest to that of the control group,followed by the alkalized water group,acidified water group and weakly acidic water group.Conclusions Through an exploration of the effects of consuming different forms of water,this study revealed that solid water consumption had the greatest effects on body weight,feed intake,water consumption,and fecal flora of mice.The abundance and diversity of fecal flora in mice were affected by different pH values of drinking water,especially acidified water.

Objective:To describe demographic,clinical and physiological characteristics,treatment between first-episode major depressive disorder(MDD)and relapse MDD,and to explore characteristics of relapse MDD.Methods:Totally 858 patients who met the diagnostic criteria for depression of the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),were included by using the Mini International Neuropsychiatric Interview(MINI),Clinician-Rated Dimensions of Psychosis Symptom Severity,and Hamilton Depression Scale etc.Among them,529(58.6％)were first-episode depression and 329(36.0％)were relapsed.The differences of demographic characteristics,clinical and physiological characteristics,treatment were compared byx2test and Kruskal-Wallis rank sum test.Multivariate logistic regression was used to explore the characteristics of MDD recur-rence.Results:Compared to first-episode MDD,relapse MDD had more comorbidity(OR=2.11,95％CI:1.00-4.44),more days out of role(OR=1.26,95％CI:1.01-1.56),more history of using psychiatric drug more than one month(OR=1.41,95％CI:1.02-1.97)and electroconvulsive therapy(OR=3.23,95％CI:1.42-7.36),and higher waist-hip ratio(OR=33.88,95％CI:2.88-399.32).Conclusion:Relapse MDD has positive as-sociation with comorbidity of mental disorders,out of role,and higher waist-hip ratio.