ObjectiveTo investigate the regulatory effect and potential mechanisms of isocitrate dehydrogenase 3A （IDH3A） on cardiomyocyte hypertrophy. MethodsThe expression of IDH3A in the myocardium of healthy volunteers （n=10） and patients with heart failure （HF） （n=10）， and in the myocardium of mice subjected to transverse aortic constriction （TAC） surgery and sham operation， as well as in phenylephrine （PE）-induced neonatal rat ventricular cardiomyocytes （NRVCs）， was assessed by real-time quantitative polymerase chain reaction （RT-qPCR） and Western blot assay. The effect of adenovirus-mediated overexpression of IDH3A on the expression of hypertrophy-related genes in PE-induced NRVCs was also evaluated. The effect of IDH3A on NRVCs area was examined by phalloidin staining assay. A mutant of IDH3A with abolished enzymatic activity， IDH3A_D208A， was generated through site-directed mutagenesis. The impact of this IDH3A mutant on the hypertrophic phenotype， ATP and ROS levels in NRVCs was evaluated to investigate whether the regulatory role of IDH3A in cardiomyocyte hypertrophy was dependent on its enzymatic activity. The effect of exogenous α-ketoglutaric acid （AKG） on cardiomyocyte hypertrophy was also detected by Western blot and phalloidin staining assay， respectively. ResultsIDH3A was significantly decreased in the myocardium of HF patients， in the myocardium of TAC-operated mice， and in PE-induced NRVCs （P = 0.005 2，P = 0.026 6，P = 0.041 3 and P = 0.006 6， respectively）. Overexpression of IDH3A markedly suppressed the expression of hypertrophy-related genes and the increase of cell size of PE-induced NRVCs （P < 0.000 1， P = 0.000 1 and P = 0.000 2， respectively）. The ATP and ROS analysis indicated that IDH3A inhibited the increases of ATP and ROS levels in PE-induced NRVCs （P = 0.001 2 and P<0.000 1， respectively）， whereas the enzymatically inactive IDH3A mutant lacked this effect. Exogenous AKG provision could， but overexpression of IDH3A mutant failed to suppress PE-induced NRVCs hypertrophy. ConclusionIDH3A inhibits cardiomyocyte hypertrophy via elevating AKG level， providing scientific evidence for study on IDH3A-based treatment of cardiac hypertrophy.

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

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

OBJECTIVE: To explore the immunophenotypic characteristics of bone marrow granulocytes (G) and their clinical significance in patients with multiple myeloma (MM). METHODS: The granulocyte immunophenotypes of bone marrow in 70 MM patients (MM group) and 40 anemia patients (control group) were detected by flow cytometry, and its correlation with clinical characteristics was further analyzed. Univariate and multivariate regression analysis were used to screen factors that affected prognosis. RESULTS: The CD56⁺G%, CD13⁺G%, CD22⁺G% and CD117⁺G% in MM group were higher than those in the control group (all P <0.05). CD56⁺G% and CD117⁺G% in CR⁺VGPR group were significantly lower than those in PR+MR+PD group (both P <0.05). The CD10⁺G% in RISS Ⅲ stage and Ca²⁺ ≥2.65 mmol/L groups were increased (both P <0.05). The CD56⁺G% in elevated lactate dehydrogenase, β₂-microglobulin≥5.5 mg/L and hemoglobin <85 g/L groups were increased (all P <0.05), while the CD117⁺G% in high-risk cytogenetic positive group was decreased (P <0.05). The expression rate of CD molecules on granulocytes was divided into low (L) and high (H) groups according to the median value. The overall survival (OS) of the LCD56⁺G%, LCD13⁺G% and LCD22⁺G% groups was significantly prolonged (all P <0.05). CD13⁺G% and CD22⁺G% were independent risk factors for OS in MM patients (HR=0.443, 0.410, both P <0.05). CONCLUSION The CD56⁺G%, CD10⁺G% and CD117⁺G% are closely correlated with clinical features in MM patients, while CD13⁺G% and CD22⁺G% are closely correlated with prognosis. Detection of CD molecules expression on granulocytes may be used to evaluate prognosis and guide treatment.
Humans ; Multiple Myeloma/immunology* ; Granulocytes/immunology* ; Prognosis ; Immunophenotyping ; Male ; Bone Marrow ; Female ; Flow Cytometry ; Middle Aged ; Aged ; Clinical Relevance

OBJECTIVE: To screen anti-tumor drugs that improve antigen processing and presentation in acute myeloid leukemia (AML) cells. METHODS: A TCR-like or TCR mimic antibody that can specifically recognize HLA-A*0201:WT1_126-134 ( RMFPNAPYL) complex (hereafter referred to as HLA-A2:WT1) was synthesized to evaluate the function of antigen processing and presentation machinery (APM) in AML cells. AML cell line THP1 was incubated with increasing concentrations of IFN-γ, hypomethylating agents (HMA), immunomodulatory drugs (IMiD), proteasome inhibitors (PI) and γ-secretase inhibitors (GSI), followed by measuring of HLA-ABC, HLA-A2 and HLA-A2:WT1 levels by flow cytometry at consecutive time points. RESULTS: The TCR-like antibody we generated only binds to HLA-A*0201⁺WT1⁺ cells, indicating the specificity of the antibody. HLA-A2:WT1 level of THP-1 cells detected with the TCR-like antibody was increased significantly after co-incubation with IFN-γ, showing that the HLA-A2:WT1 TCR like antibody could evaluate the function of APM. Among the anti-tumor agents screened in this study, GSI (LY-411575) and HMA (decitabine and azacitidine) could significantly increase the HLA-A2:WT1 level. The IMiD lenalidomide and pomalidomide could aslo upregulate the expression of HLA-A2:WT1 complex under certain concentrations of the drugs and incubation time. As proteasome inhibitors, carfilzomib could significantly decreased the expression of HLA-A2:WT1, while bortezomib had no significant effect on HLA-A2:WT1 expression. CONCLUSION HLA-A2:WT1 TCR-like antibody can effectively reflect the APM function. Some of the anti-tumor drugs can affect the APM function and immunogenicity of tumor cells.
Humans ; Leukemia, Myeloid, Acute/immunology* ; Antineoplastic Agents/pharmacology* ; Antigen Presentation/drug effects* ; HLA-A2 Antigen/immunology* ; Receptors, Antigen, T-Cell/immunology* ; Cell Line, Tumor ; Interferon-gamma

OBJECTIVE: To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data, by utilizing a dynamic graph-based registration network model (maxillofacial dynamic graph registration network, MDGR-Net), and to provide a valuable reference for digital design and analysis in clinical dental applications. METHODS: Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022. Through data augmentation, a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm. These were divided into a training set (1 400 cases), a validation set (200 cases), and an internal test set (200 cases). The MDGR-Net model constructed feature vectors for key points in both original and mirror point clouds (X, Y), established correspondences between key points in the X and Y point clouds based on these feature vectors, and calculated rotation and translation matrices using singular value decomposition (SVD). Utilizing the MDGR-Net model, intelligent registration of the original and mirror point clouds were achieved, resulting in a combined point cloud. The principal component analysis (PCA) algorithm was applied to this combined point cloud to obtain the symmetry reference plane associated with the MDGR-Net methodology. Model evaluation for the translation and rotation matrices on the test set was performed using the coefficient of determination (R²). Angle error evaluations for the three-dimensional maxillofacial symmetry reference planes were constructed using the MDGR-Net-associated method and the "ground truth" iterative closest point (ICP)-associated method were conducted on 200 cases in the internal test set and 40 cases in an external test set. RESULTS: Based on testing with the three-dimensional maxillofacial data from the 200-case internal test set, the MDGR-Net model achieved an R² value of 0.91 for the rotation matrix and 0.98 for the translation matrix. The average angle error on the internal and external test sets were 0.84°±0.55° and 0.58°±0.43°, respectively. The construction of the three-dimensional maxillofacial symmetry reference plane for 40 clinical cases took only 3 seconds, with the model performing optimally in the patients with skeletal Class Ⅲ malocclusion, high angle cases, and Angle Class Ⅲ orthodontic patients. CONCLUSION This study proposed the MDGR-Net association method based on intelligent point cloud registration as a novel solution for constructing three-dimensional maxillofacial symmetry reference planes in clinical dental applications, which can significantly enhance diagnostic and therapeutic efficiency and outcomes, while reduce expert dependence.
Humans ; Deep Learning ; Algorithms ; Imaging, Three-Dimensional/methods* ; Male ; Female ; Maxilla/diagnostic imaging* ; Adult

OBJECTIVES: This study aimed to evaluate the repeatability and reliability of a self-developed domestic wireless surface electromyography (sEMG) system (Oralmetry) in assessing the activity of the temporalis and masseter muscles to provide theoretical support for its clinical application. METHODS: Twenty-two volunteers were recruited. Through multiple repeated measurements, the sEMG signals of bilateral anterior temporalis and masseter muscles during maximum voluntary clenching were collected using the self-developed sEMG device, Oralmetry, and two commercial sEMG devices (Zebris and Teethan), filtered, screened, and standardized. Seven sEMG indicators for assessing masticatory muscle function were calculated. The intraclass correlation coefficient (ICC) was used to evaluate the repeatability of the measurements from the three sEMG devices, and statistical analysis was conducted to compare the consistency of the seven sEMG indicators obtained from the devices. RESULTS: Among the 22 participants, the ICC values of the repeated measurements from the three sEMG devices ranged from 0.88 to 0.99. The measurements of three sEMG indicators (antero-posterior coeffificient, percentage overlapping coeffificient_MM, and percentage overlapping coeffificient_TA) obtained by Zebris were significantly different from those obtained by Oralmetry and Teethan (P<0.05). No significant differences in the measurements of the seven sEMG indicators were found between Oralmetry and Teethan. CONCLUSIONS Oralmetry and the two commercial sEMG devices demonstrated good repeatability in capturing sEMG indicators for evaluating masticatory muscle function. In particular, Oralmetry showed the highest ICC values. All three devices also exhibited good consistency in measuring sEMG indicators, and a high agreement was observed between the two wireless sEMG devices (Oralmetry and Teethan). These findings provide theoretical support for the clinical application of Oralmetry.
Humans ; Electromyography/methods* ; Masseter Muscle/physiology* ; Masticatory Muscles/physiology* ; Wireless Technology ; Reproducibility of Results ; Temporal Muscle/physiology* ; Male ; Adult ; Female ; Young Adult

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective:To explore the method of obtaining the key parameters of the average value articulator in healthy people based on mandibular movement trajectory data, with a view to providing a reference for the clinical application of the average value articulator.Methods:One hundred healthy volunteers (42 males and 58 females) with individual normal occlusion, aged 18-55 years old, who met the inclusion criteria were recruited from Beijing, and their mandibular movement trajectory data were collected. The left and right sagittal condylar inclination(SCI) and transversal condylar inclination(TCI) were obtained from the values of the articulator parameters which were generated in the mandibular movement analysis system.The SCI and TCI were grouped by gender and calculated separately for the two groups and the overall sample; the gender differences in the two parameters and the differences between the mean values of the two parameters and the average value articulator empirical values (35° for SCI and 15° for TCI) for the overall sample were compared.Results:The differences between SCI (35.8°±7.4°) and TCI [11.2° (11.3°)] in males and the corresponding parameters [35.6°±8.3° and 10.8° (9.5°), respectively] in females were not statistically significant ( t=0.10, P=0.922; Z=-0.60, P=0.552); the overall sample SCI (35.7°±7.9°) did not differ statistically from the average value articulator empirical value ( t=1.23, P=0.221), and the overall sample TCI [10.9° (10.3°)] was significantly smaller than the average value articulator empirical value ( W=5 825.00, P<0.001). Conclusions:The mandibular movement trajectory data of 100 adults with individual normal occlusion in this study shows that the gender factor does not affect the setting of the key parameters of the average value articulator, the SCI of the average value articulator empirical values is appropriate, and the TCI has the possibility of being on the large side. In the clinical use of the articulator to assist in the design of restorations, the parameter values should be rationally adjusted according to the actual situation of the patient′s dentition and mandibular movement.