Objective:To systematically evaluate the incidence and influencing factors of postoperative stroke in patients with acute type A aortic dissection (ATAAD).Methods:Nine Chinese and English databases, including PubMed, Embase, CINAHL, JAMA, The Cochrane Library, CNKI, Wanfang, Vip and Chinese Biomedicine, were searched by computer to include literatures evaluating the incidence of postoperative stroke and its influencing factors in ATAAD patients. The search period was from the establishment of the database to September 2024. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias in the included studies. Stata 14.0 software was used to combine the prevalence rate, and descriptive analysis of influencing factors was performed.Results:A total of 22 articles were included, including 16 734 ATAAD patients, published from 2018 to 2024. Meta-analysis results showed that the incidence of postoperative stroke in ATAAD patients was 16% (14%-18%). Subgroup analyses showed a higher incidence of postoperative stroke in patients with ATAAD in Europe (19%, 95% CI: 15%-23%), with a sample size of 1 to 300 patients (18%, 95% CI: 14%-22%), and in 2024 (20%, 95% CI: 14%-28%). Descriptive analysis shows that the factors influencing the occurrence of postoperative stroke in ATAAD patients include preoperative history (preoperative hypotension, preoperative history of stroke, history of carotid artery disease, history of cardiac arrest), intraoperative measures (total arch replacement, femoral artery intubation, anterograde cerebral perfusion, intraoperative oxygen satiation), and various types of time (cryopreservation time, extracorporeal circulation time, operation time). Conclusion:The incidence of postoperative stroke is higher in ATAAD patients. Preoperative hypotension, history of stroke before surgery, history of carotid artery disease, history of cardiac arrest, total arch replacement, femoral artery intubation, anterograde cerebral perfusion, decrease of cerebral oxygen saturation during operation, and longer hypothermia stop time, cardiopulmonary bypass time and operation time may increase the risk of postoperative stroke in ATAAD patients.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

Objective To predict the potential distribution area of Halenia elliptica under current and future climate conditions;To provide a foundation for the sustainable utilization and cultivation of H.elliptica resources.Methods Based on 116 occurrence records and 36 environmental variables,this study employed correlation analysis and contribution rates to identify 10 key environmental factors of H.elliptica.The MaxEnt model,combined with Geographic Information Systems(GIS),was used to predict the potential suitable areas for H.elliptica under current and different future climate scenarios,and centroid shift analysis was performed using SDM_toolbox.Results The MaxEnt model predicted accurately,with an area under the receiver operating characteristic(ROC)curve of 0.968.Altitude,annual precipitation and mean temperature of the coldest season were identified as the primary influencing factors.The current suitable area for H.elliptica was approximately 176.04×104 km2.In the future climate conditions,the suitable habitat of H.elliptica will be moderately adjusted,especially in Sichuan and Xizang.Conclusion In the future,the suitable potential distribution areas for H.elliptica in China will increase,and there will be slight differences in the increment of different suitable potential distribution areas.This study can provide a basis for resource conservation and sustainable utilization,and highlight the importance of dynamic ecological monitoring in the context of global warming.

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

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.

To verify whether the two B-cell epitopes Pep1 and Pep4 in the FAdV-4 WZ fiber can be used as candidate epitopes for multivalent epitope vaccines,epitopes Pep1 and Pep4 were tandemly linked with the chicken infectious bronchitis virus strain M41 S1 protein gene in different patterns,and a recombinant fusion plasmid was constructed and expressed in E.coli BL21(DE3).It was confirmed by Western blot and ELISA tests that all four expressed fusion proteins reacted specific-ally with anti-M41 whole virus serum and WZ strain anti-Fiber 2-knob protein serum.After purifi-cation and immunization of BALB/c mice,specific antibodies against the peptide epitopes were de-tected in mouse sera.The results showed that the Pep4 epitope induced a stronger immune re-sponse than the Pep1 epitope.When Pep1 was connected with the amino and carboxyl termini of the fusion protein,respectively,both resulted in the production of the same level of anti-Pep1 anti-bodies in the immunized animals,whereas when Pep4 was connected with the carboxyl terminus of the fusion protein,the immunized animals produced a higher level of anti-Pep4-specific antibodies.This research indicates that the B cell epitopes Pep1 and Pep4 of the reactive WZ strain Fiber 2,when conjugated with proteins to form fusion proteins,can enhance the immunogenicity of Pep1 and Pep4 without affecting the antigenicity of the carrier protein.This study provides technical support and serves as a reference for the design and development of a multivalent epitope vaccine for FAdV-4.

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 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