PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

Glioma represents the most prevalent malignant tumor of the central nervous system, with chemotherapy serving as an essential adjunctive treatment. However, most chemotherapeutic agents exhibit limited ability to penetrate the blood-brain barrier (BBB). This study introduced a novel dual-targeting strategy for glioma therapy by modulating the formation of nanobody-driven protein coronas to enhance the brain and tumor-targeting efficiency of hydrophobic cisplatin prodrug-loaded lipid nanoparticles (C8Pt-Ls). Specifically, nanobodies (Nbs) with fibrinogen-binding capabilities were conjugated to the surface of C8Pt-Ls, resulting in the generation of Nb-C8Pt-Ls. Within the bloodstream, Nb-C8Pt-Ls could bound more fibrinogen, forming the protein corona that specifically interacted with LRP-1, a receptor highly expressed on the BBB. This interaction enabled a "Hitchhiking Effect" mechanism, facilitating efficient trans-BBB transport and promoting effective brain targeting. Additionally, the protein corona interacted with LRP-1, which is also overexpressed in glioma cells, achieving precise tumor targeting. Computational simulations and SPR detection clarified the molecular interaction mechanism of the Nb-fibrinogen-(LRP-1) complex, confirming its binding specificity and stability. Our results demonstrated that this strategy significantly enhanced C8Pt accumulation in brain tissues and tumors, induced apoptosis in glioma cells, and improved therapeutic efficacy. This study provides a novel framework for glioma therapy and underscores the potential of protein corona modulation-based dual-targeting strategies in advancing treatments for brain tumors.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

Objective Genotypes(G)1,3,and 5 of the Japanese encephalitis virus(JEV)have been isolated in China,but the dominant genotype circulating in Chinese coastal areas remains unknown.We searched for G5 JEV-infected cases and attempted to elucidate which JEV genotype was most closely related to human Japanese encephalitis(JE)in the coastal provinces of China. Methods In this study,we collected serum specimens from patients with JE in three coastal provinces of China(Guangdong,Zhejiang,and Shandong)from 2018 to 2020 and conducted JEV cross-neutralization tests against G1,G3,and G5. Results Acute serum specimens from clinically reported JE cases were obtained for laboratory confirmation from hospitals in Shandong(92 patients),Zhejiang(192 patients),and Guangdong(77 patients),China,from 2018 to 2020.Seventy of the 361 serum specimens were laboratory-confirmed to be infected with JEV.Two cases were confirmed to be infected with G1 JEV,32 with G3 JEV,and two with G5 JEV. Conclusion G3 was the primary infection genotype among JE cases with a definite infection genotype,and the infection caused by G5 JEV was confirmed serologically in China.

Objective To investigate the risk factors for delayed union of extra-articular fractures of the middle and lower third of the tibia treated by locking plate.Methods Total of 135 patients of extra-articular fractures of the middle and lower third of the tibia from January 2013 to December 2018 were retrospectively analyzed,including 85 males and 50 females,ranged from 19 to 80 years old.All cases were treated with locking plates.The patients were divided into union group and delayed union group ac-cording to the condition of fracture union.The risk factors of delayed healing were determined by univariate analysis of 14 factors that might affect fracture healing first,then the factors with significance were analyzed by binary Logistic regression.Results There were 13 patients of delayed union,and the rate of delayed union was 9.63％.Univariate analysis showed that delayed union was associated with age,smoking,reduction method,anemia and time of preoperative preparation.Regression analysis showed thatage[OR=0.849,95％CI(0.755,0.954),P=0.006],smoking[OR=0.020,95％CI(0.002,0.193),P=0.001],reduction method[OR=23.924,95％CI(2.210,258.943),P=0.009],anemia[OR=0.016,95％CI(0.001,0.289),P=0.005]were the con-tributory factors for delayed union.Conclusion Young age,smoking,closed reduction and anemia are the risk factors for de-layed union of extra-articular fractures of the middle and lower third of the tibia treated by locking plate.

Objective: To analyze the factors associated with readmission within three months of surgery for gastric cancer and the impact of readmission on patients' long-term nutritional status and quality of life. Methods: This was a prospective cohort study comprising patients who underwent radical gastrectomy in the Department of Pancreatic and Gastric Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences from October 2018 to August 2019. Patients who failed to complete postoperative follow-up, whose body mass index (BMI) could not be accurately estimated, or who were unable to complete a quality-of-life questionnaire were excluded. The patients were followed up for 12 months. Time to, cause(s) of, and outcomes of readmission were followed up 1, 2 and 3 months postoperatively. BMI was followed up 1, 3, 6 and 12 months postoperatively. Results of blood tests were collected and patients' nutritional status and quality of life were assessed 12 months postoperatively. Nutritional status was evaluated by BMI, hemoglobin, albumin, and total lymphocyte count. Quality of life was evaluated using the European Organization for Research in the Treatment of Cancer (EORTC) Quality of Life scale. The higher the scores for global health and functional domains, the better the quality of life, whereas the higher the score in the symptom domain, the worse the quality of life. Results: The study cohort comprised 259 patients with gastric cancer, all of whom were followed up for 3 months and 236 of whom were followed up for 12 months. Forty-four (17.0%) patients were readmitted within 3 months. The commonest reasons for readmission were gastrointestinal dysfunction (16 cases, 36.3%), intestinal obstruction (8 cases, 18.2%), and anastomotic stenosis (8 cases, 18.2%). Logistic regression analysis showed that preoperative Patient-Generated Subjective Global Assessment score ≥ 4 points (OR=1.481, 95% CI: 1.028‒2.132), postoperative complications (OR=3.298, 95%CI:1.416‒7.684) and resection range (OR=1.582, 95% CI:1.057‒2.369) were risk factors for readmission within 3 months of surgery. Compared with patients who had not been readmitted 12 months after surgery, patients who were readmitted within 3 months of surgery tended to have greater decreases in their BMI [-2.36 (-5.13,-0.42) kg/m² vs. -1.73 (-3.33,-0.33) kg/m², Z=1.850, P=0.065), significantly lower hemoglobin and albumin concentrations [(122.1±16.6) g/L vs. (129.8±18.4) g/L, t=2.400, P=0.017]; [(40.9±5.0) g/L vs. (43.4±3.3) g/L, t=3.950, P<0.001], and significantly decreased global health scores in the quality of life assessment [83 (67, 100) vs. 100 (83, 100), Z=2.890,P=0.004]. Conclusion: Preoperative nutritional risk, total or proximal radical gastrectomy, and complications during hospitalization are risk factors for readmission within 3 months of surgery for gastric cancer. Perioperative management and postoperative follow-up should be more rigorous. Readmission within 3 months after surgery may be associated with a decline in long-term nutritional status and quality of life. Achieving improvement in long-term nutritional status and quality of life requires tracking of nutritional status, timely evaluation, and appropriate interventions in patients who need readmission.
Humans ; Nutritional Status ; Quality of Life ; Patient Readmission ; Stomach Neoplasms/complications* ; Prospective Studies ; Postoperative Complications/etiology* ; Gastrectomy/adverse effects* ; Retrospective Studies

Humans ; Hearing Loss/etiology* ; Lupus Erythematosus, Systemic/complications* ; Prognosis

A long-held belief is that pituitary hormones bind to their cognate receptors in classical target glands to actuate their manifold functions. However, a number of studies have shown that multiple types of pituitary hormone receptors are widely expressed in non-classical target organs. Each pituitary gland-derived hormone exhibits a wide range of nonconventional biological effects in these non-classical target organs. Herein, the extra biological functions of pituitary hormones, thyroid-stimulating hormone, follicle-stimulating hormone, luteinizing hormone, adrenocorticotrophic hormone, and prolactin when they act on non-classical organs were summarized, defined by the novel concept of an "atypical pituitary hormone-target tissue axis." This novel proposal explains the pathomechanisms of abnormal glucose and lipid metabolism, obesity, hypertension, fatty liver, and atherosclerosis while offering a more comprehensive and systematic insights into the coordinated regulation of environmental factors, genetic factors, and neuroendocrine hormones on human biological functions. The continued exploration of the physiology of the "atypical pituitary hormone-target tissue axis" could enable the identification of novel therapeutic targets for metabolic diseases.
Humans ; Pituitary Hormones/metabolism* ; Luteinizing Hormone ; Follicle Stimulating Hormone ; Prolactin ; Pituitary Gland/metabolism*

Mining data from traditional Chinese medicine(TCM) prescriptions is one of the important methods for inheriting the experience of famous doctors and developing new drugs. However, current research work has problems such as to be optimized research plans and non-standard statistics. The main problems and corresponding solutions summarized by the research mainly include four aspects.(1)The research plan design needs to consider the efficacy and quality of individual cases.(2)The significance of the difference in confidence order of association rules needs to be further considered, and the lift should not be ignored.(3)The clustering analysis steps are complex. The selection of clustering variables should comprehensively consider factors such as the frequency of TCM, network topology parameters, and practical application significance. The selection of distance calculation and clustering methods should be improved based on the characteristics of TCM clinical data. Jaccard distance and its improvement plan should be given attention in the future. A single, unexplained clustering result should not be presented, but the final clustering plan should be selected based on a comprehensive consideration of TCM clinical characteristics and objective evaluation indicators for clustering.(4)When calculating correlation coefficients, algorithms that are only suitable for continuous variables should not be applied to binary variables. This article explained the connotations of the above problems based on the characteristics of TCM clinical research and statistical principles and proposed corresponding suggestions to provide important references for future data mining research work.
Humans ; Medicine, Chinese Traditional ; Prescriptions ; Data Mining ; Cluster Analysis ; Physicians ; Drugs, Chinese Herbal/therapeutic use*