Objective:To investigate the risk factors and their predictive efficacy for early postoperative complications in elderly patients with hip fracture.Methods:A retrospective cohort study was conducted on the clinical data of 203 elderly patients with hip fracture admitted to the 908th Hospital of the Joint Logistics Support Force of the PLA and the First Affiliated Hospital of Nanchang University from January 2022 to December 2023, including 54 males and 149 females, aged 65-100 years [(80.5±7.7)years]. There were 96 patients with femoral neck fracture and 107 patients with intertrochanteric fracture. According to the AO/OTA classification, the fracture was classified as type 31A in 107 patients and type 31B in 96. Among them, 81 patients were treated with proximal femoral nail antirotation (PFNA), 65 with semi-hip arthroplasty, 52 with total hip arthroplasty (THA), and 5 with closed reduction and cannulated nail internal fixation. The patients were divided into complication group ( n=65) and non-complication group ( n=138) according to whether complications (mainly including delirium, lung infection, stress ulcer, and deep vein thrombosis of the lower limbs) occurred within 15 days after surgery. The gender, age, age stage, educational level, cause of injury, associated underlying diseases before surgery, AO/OTA classification, American Society of Anesthesiologists (ASA) classification, 5-factor modified frailty index (mFI-5) score, prognostic nutritional index (PNI), anesthesia method, operation method, operation time, intraoperative blood loss, length of hospital stay, etc., were recorded in the two groups. Univariate analysis and multivariate binary logistic regression analysis were used to evaluate the correlation between the above indexes and the occurrence of early postoperative complications in elderly patients with hip fracture and to determine their independent risk factors. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of each risk factor for the occurrence of early postoperative complications in elderly patients with hip fracture. Results:Univariate analysis showed a certain correlation between age, age stage, associated underlying diseases before surgery, AO/OTA classification, ASA classification, mFI-5 score, PNI, operation method, and length of hospital stay and the occurrence of early postoperative complications in elderly patients with hip fracture ( P<0.05), while gender, educational level, cause of injury, anesthesia method, operation time, and intraoperative blood loss were not correlated with the occurrence of early postoperative complications in elderly patients with hip fracture ( P>0.05). The results of multivariate binary logistic regression analysis showed that the associated underlying diseases before surgery ( OR=5.46, 95% CI 1.33, 22.39, P<0.05), mFI-5 score ( OR=15.90, 95% CI 5.36, 47.15, P<0.01), and PNI ( OR=0.70, 95% CI 0.60, 0.81, P<0.01) were significantly correlated with the occurrence of early postoperative complications in elderly patients with hip fracture. The results of ROC curve analysis showed that mFI-5 score (AUC=0.85, 95% CI 0.80, 0.91) and PNI (AUC=0.87, 95% CI 0.82, 0.93) had moderate predictive efficacy, while the early warning efficacy of associated underlying diseases was low (AUC=0.54, 95% CI 0.45, 0.62). The combination of the above risk factors was more effective in predicting early postoperative complications in elderly patients with hip fracture (AUC=0.95, 95% CI 0.92, 0.98). Conclusions:The mFI-5 score, PNI, and associated underlying diseases before surgery are independent risk factors for early postoperative complications in elderly patients with hip fracture. The mFI-5 score and PNI have a higher predictive efficacy than associated diseases before surgery on the occurrence of early postoperative complications in elderly patients with hip fracture, while the combination of the above risk factors provides a significantly better predictive performance.

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding

Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.
Hypertension/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional ; Drug Prescriptions ; Latent Class Analysis

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

This study assessed the role and mechanism of the recombinant Bacillus Calmette-Gue?rin vaccine(rBCG)with c-di-AMP adjuvant in regulating metabolism and immunity in epididymal white adipose(eWAT)in mice.Male C57BL/6 mice were intravenously immunized with BCG and rBCG,and their body weights were monitored.eWAT was isolated from the mice,and the stromal vascular fractions(SVFs)cell number was counted with a hemocytometer.Sections of mouse adipose tissue were prepared,and the size,number,and morphology of eWAT adipocytes and crown-like structure(CLS)formation were compared under a microscope after HE staining.The transcription levels of lipid metabolism-associated factors,cytokines and aging-associated genes in each group were determined with qRT-PCR.The body weights of mice gradually increased after immunization with BCG and rBCG.The proportions of eWAT increased,and the SVFs cell number decreased,in rBCG immunized mice.HE staining indicated that BCG immunization promoted hyperplasia,whereas rBCG immunization promoted hypertrophy of eWAT adipocytes;moreover,both BCG and rBCG immunization induced CLS formation in eWAT.The qRT-PCR results indicated that rBCG immunization inhibited the expression of genes associated with lipolysis and energy expenditure in eWAT.BCG immunization had little effect on cytokine transcription,whereas rBCG significantly induced the transcription of IFN-γ and IL-1Ra,and inhibited that of IL-15 and IL-2,but did not induce the expression of aging-associated genes.Thus,rBCG immunization induced eWAT adipocyte hypertrophy,which was associated with the inhibition of eWAT lipolysis and the regulation of cytokine expression.

OBJECTIVE: Lipid oxidation is involved in the pathogenesis of atherosclerosis and may be contribute to the development of Ischemic stroke (IS). However, the lipid profiles associated with IS have been poorly studied. We conducted a pilot study to identify potential IS-related lipid molecules and pathways using lipidomic profiling. METHODS: Serum lipidomic profiling was performed using LC-MS in 20 patients with IS and 20 age- and sex-matched healthy controls. Univariate and multivariate analyses were simultaneously performed to identify the differential lipids. Multiple testing was controlled for using a false discovery rate (FDR) approach. Enrichment analysis was performed using MetaboAnalyst software. RESULTS: Based on the 294 lipids assayed, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were used to distinguish patients with IS from healthy controls. Fifty-six differential lipids were identified with an FDR-adjusted P less than 0.05 and variable influences in projection (VIP) greater than 1.0. These lipids were significantly enriched in glycerophospholipid metabolism (FDR-adjusted P = 0.009, impact score = 0.216). CONCLUSIONS Serum lipid profiles differed significantly between patients with IS and healthy controls. Thus, glycerophospholipid metabolism may be involved in the development of IS. These results provide initial evidence that lipid molecules and their related metabolites may serve as new biomarkers and potential therapeutic targets for IS.
Humans ; Pilot Projects ; Lipidomics ; Male ; Female ; Biomarkers/blood* ; Middle Aged ; Ischemic Stroke/blood* ; Aged ; China ; Lipids/blood* ; Adult ; Case-Control Studies ; East Asian People

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

OBJECTIVE: To explore clinical effect of autologous osteochondral transplantation (AOT) in the treatment of recurrent anterior dislocation of the shoulder joint with glenoid cartilage defect in rabbits by establishing a model of recurrent anterior dislocation of the shoulder joint with < 20% glenoid cartilage defect in rabbits. METHODS: Twenty-four male New Zealand white rabbits, aged 6-month-old, weighed (2.69±0.17) kg were selected. The labrum of shoulder joint of rabbits was artificially destroyed to establish a model of recurrent anterior dislocation of shoulder joint with cartilage defect. They were divided into AOT surgery group and simple suture group, with 12 rabbits in each group. AOT group were underwent AOT surgery, while simple suture group was treated with simple Bankart suture for recurrent shoulder joint dislocation. At 6 and 12 weeks after operation, 6 rabbits between two groups were sacrificed for sampling. The dietary conditions, activity conditions, mental states of rabbits and healing conditions of grafts in the specimens were observed and compared between two groups. HE staining was used to observe cell creep, cell morphology, inflammatory cell infiltration, fibrochondrocytes and their arrangement. Masson staining was used to observe the formation and arrangement of collagen fibers; Safrane-green staining was used to observe the regeneration of articular cartilage, subchondral bone and bone tissue. Bone mineral density (BMD), bone volume (BV) and trabecular thickness (Tb.Th) between two groups were measured by Micro-CT to evaluate the remodeling of shoulder glenoid bone defects by autologous osteochondral cartilage. RESULTS: After different surgical interventions were carried out in both groups of rabbits, at 6 weeks after the operation, the abduction, extension, internal rotation and external rotation of the shoulder joint on the operated side showed limited range of motion compared with the contralateral side, while adduction and forward flexion showed no obvious abnormalities compared with the contralateral side. At 12 weeks after operation, the range motion of tshoulder joints in both groups of rabbits had returned to the state before modeling. The effects of HE staining, Masson staining and safrane-green staining at 12 weeks after operation in both groups were stronger than the staining results at 6 weeks after operation. Moreover, the results of HE staining, Masson staining and safranin fixation green staining in AOT group at 6 and 12 weeks after operation were all higher than those in simple suture group. Micro-CT scan results at 6 and 12 weeks after operation showed that BMD (0.427±0.014), (0.466±0.032) g·cm-3, BV(116.171±3.527), (159.327±3.500) mm3, and Tb.Th (0.230±0.006), (0.285±0.009) mm in AOT group, which were higher than those of simple suture group in BMD(0.358±0.011), (0.384±0.096) g·cm-3, BV(72.657±3.903), (118.713±3.860) mm3, and Tb.Th(0.204±0.009), (0.243±0.007) mm;and the differences were statistically significant (P<0.05). CONCLUSION AOT procedure could effectively promote osteogenesis and fibrocartilage regeneration in the cartilage defect area of the shoulder glenoid <20%, which is conducive to reshaping the structure of the shoulder glenoid.
Animals ; Rabbits ; Male ; Transplantation, Autologous ; Cartilage, Articular/injuries* ; Shoulder Dislocation/physiopathology* ; Bone Transplantation ; Shoulder Joint/surgery*

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*