HELQ suppresses migration and proliferation of non-small cell lung cancer cells by repairing DNA damage and inducing necrosis.

HELQ plays a key role in DNA damage response and cell-cycle checkpoint regulation. It has been implicated in ovarian and pituitary tumors and may play a role in germ cell maintenance. This study investigated the role of HELQ in lung cancer. The expression of HELQ in patients with non-small-cell lung cancer (NSCLC) was downregulated compared with normal human lungs. Clinical prognostic analysis of Kaplan-Meier plots revealed that patients with NSCLC with low HELQ levels had a reduced overall survival. Further, we found that HELQ depletion enhanced lung cancer cell malignancy. Furthermore, overexpression of HELQ in lung cancer cells reduced cell migration in vitro, while DNA damage repair was inhibited. Both in vitro and in vivo studies have shown that HELQ induces cell death. Mechanistically, we found that cells overexpressing HELQ showed a tendency to induce necrosis. After analyzing the database of HELQ interactors. we found that RIPK3 may interact with it and proved this conclusion by immunoprecipitation. Our findings identified the tumor suppressive role of HELQ in malignant human lung cancer and unraveled a potential therapeutic strategy for cancer treatment through HELQ activation. Moreover, HELQ may also be a predictive biomarker for the clinical predisposition, progression, and prognosis of lung cancer.

Machine learning for the prediction of postoperative nosocomial pulmonary infection in patients with spinal cord injury.

PURPOSE: The purpose of this study was to establish the best prediction model for postoperative nosocomial pulmonary infection through machine learning (ML) and assist physicians to make accurate diagnosis and treatment decisions. METHODS: Patients with spinal cord injury (SCI) who admitted to a general hospital between July 2014 and April 2022 were included in this study. The data were segmented according to the ratio of seven to three, 70% were randomly selected to train the model, and the other 30% were used for testing. We used LASSO regression to screen the variables, and the selected variables were used in the construction of six different ML models. Shapley additive explanations and permutation importance were used to explain the output of the ML models. Finally, sensitivity, specificity, accuracy and area under receiver operating characteristic curve (AUC) were used as the evaluation index of the model. RESULTS: A total of 870 patients were enrolled in this study, of whom 98 (11.26%) developed pulmonary infection. Seven variables were used for ML model construction and multivariate logistic regression analysis. Among these variables, age, ASIA scale and tracheotomy were found to be the independent risk factors for postoperative nosocomial pulmonary infection in SCI patients. Meanwhile, the prediction model based on RF algorithm performed best in the training and test sets. (AUC = 0.721, accuracy = 0.664, sensitivity = 0.694, specificity = 0.656). CONCLUSION: Age, ASIA scale and tracheotomy were the independent risk factors of postoperative nosocomial pulmonary infection in SCI. The prediction model based on RF algorithm had the best performance.

The role of routine laboratory tests after unilateral total knee arthroplasty.

BACKGROUND: Recent studies suggest that routine laboratory tests are not required within 1 day after partial knee arthroplasty. In this study, we evaluated the utility of routine postoperative laboratory tests after initial unilateral total knee arthroplasty (TKA) in an Asian population. In addition, we explored risk factors associated with abnormal test results. METHODS: Clinical data of patients who underwent original unilateral TKA between 2015 and 2020 were retrospectively analyzed. Patient characteristics and laboratory test results were recorded. Multivariate binary logistic regression analysis was performed to identify risk factors associated with 3 abnormal laboratory results. RESULTS: A total of 713 patients, who underwent relevant laboratory tests within 3 days of TKA surgery, were enrolled. Among them, 8.1%, 9.9%, and 3.4% patients with anemia, hypoalbuminemia, and abnormal serum potassium levels required clinical intervention after surgery. Binary logistic regression analysis revealed that preoperative hemoglobin levels, estimated blood loss, and age were independent risk factors of postoperative blood transfusion in TKA patients. On the other hand, preoperative albumin levels, intraoperative blood loss, and operation time were risk factors associated with postoperative albumin supplementation. In addition, lower body mass index (BMI) and preoperative hypokalemia were potential risk factors of postoperative potassium supplementation. CONCLUSION: Considering that more than 90% of abnormal postoperative laboratory tests do not require clinical intervention, we believe that routine laboratory tests after surgery have little significance in patients with primary unilateral TKA. However, postoperative laboratory testing is necessary for patients with established risk factors.

Risk Factors and Nomogram for Postoperative Pulmonary Infection in Patients with Cervical Spinal Cord Injury.

OBJECTIVE: To identify the risk factors for developing postoperative pulmonary infection in patients with acute cervical spinal cord injury (CSCI), and to develop a nomogram prediction model. METHODS: Patients with CSCI who were admitted to 3 different medical centers between July 2011 and July 2021 were included in this study. All patients underwent cervical spine surgery. Data for patients admitted to the first 2 centers were included in a training set to establish the nomogram prediction model, and data for patients admitted to the third center were included in a validation set to externally verify the efficacy of the prediction model. For the training set, patients were divided into an infected group and a noninfected group (control group). Independent risk factors for postoperative pulmonary infection in patients with CSCI were identified by univariate and multivariate logistic regression analyses. Additionally, a nomogram prediction model was developed and validated based on the risk factors. RESULTS: A total of 689 patients were enrolled, including 574 for the training set and 115 for the validation set. Of the patients included for the training set, 144 developed pulmonary infection, with an incidence of 25.09%; 40 patients included for the validation set developed pulmonary infection (34.78%). Multivariate logistic regression analysis showed that age, American Spinal Injury Association grade, steroid pulse, high-level injury, smoking, multistage surgery, and operation duration were risk factors for the development of postoperative pulmonary infection in patients with CSCI. The area under the curve of the receiver operating characteristic curve of the model built by the training set was 0.905, and that of the receiver operating characteristic curve of the verification set was 0.917. The decision curve indicated that the model was in the range 1%-100%, and the predicted net benefit value of the model was high. CONCLUSIONS: Age, American Spinal Injury Association grade, steroid pulse, CSCI site, smoking history, number of surgical levels, and surgical duration are correlated with the development of postoperative pulmonary infection in patients with CSCI. The risk prediction model of postoperative pulmonary infection has a good prediction efficiency and accuracy.

A Bibliometric Analysis of Publications on Spinal Cord Injury Treatment With Glucocorticoids Using VOSviewer.

Background: Spinal cord injury (SCI) has devastating physical and social consequences for patients. Systemic administration of methylprednisolone (MP) at a higher dosage though can reduce neurological deficits following acute SCI. Still, this treatment regimen is controversial, owing to the apparent dose-related side effects and relatively minor improvement in neurological function. Therefore, this study aimed at the bibliometric analysis of published literature related to SCI treatment, which may lead to future research trends. Methods: The literature published relating to SCI and using glucocorticoids for its treatment between 1982 and 2022 was collected and scanned in the Web of Science collection database using the keywords glucocorticoid, dexamethasone, MP, corticosteroids, and SCI, followed by using VOSviewer for bibliometric analysis of these articles. Results: A total of 1,848 published articles and 7,448 authors on SCI and glucocorticoid usage were identified. The SCI total link strength accounts for 1,341, and MP for 762 has a strong link to neuroprotection and inflammation. The mean citation count for the top 20 most-cited articles was 682 (range: 358-1,828), where most of these were descriptive studies having focused on clinical features. The Journal of Neurotrauma was the highest-ranked journal with 6,010 citations. A total of 69 articles were published by Michael G Fehlings from the University of Toronto with 6,092 citations. The University of Toronto has published 90-related manuscripts with 7,632 citations. In contrast, 800 articles were published in the United States, with 39,633 citations and total link strength of 5,714. The second-ranked country was China, with 241 published articles and 3,403 citations. Conclusions: The research published on applying MP in treating SCI has increased with time. Although the United States has made a significant global contribution to this important field of research, it requires rigorous clinical trials designed to verify the therapeutic role of MP in SCI and its appropriate dosage to find solutions for neurological recovery.

Effect of screw tunnels on proximal femur strength after screw removal: A finite element analysis.

BACKGROUND: The presence of screw tunnels in the femoral neck is a problem for patients with proximal femoral fractures after removal of internal fixation. The question of how much does the existence of the screw tunnels affect the strength of the femur and whether the patient needs to be protected with an adjunctive device has been controversial. The objective of this finite element analysis was to determine (1) whether the screw tunnels affects normal weight bearing after removal of internal fixation of a proximal femur fracture, (2) which screw tunnels parameters affect the weight bearing capacity of the entire femur. HYPOTHESIS: The presence of the screw tunnels reduces the load-bearing capacity of the femur, and the arrangement, diameter and wall thickness of the screw tunnels affect the load-bearing capacity of the femur. MATERIALS AND METHODS: Twenty patients who underwent surgical treatment for proximal femur fracture at our hospital were included in the study. Computed tomography (CT) values of the screw tunnel wall in the femur after removal of internal fixations were analysed. Mimics v16.0 and Hypermesh v13.0 software programs were used to generate 3-dimensional (3D) tetrahedral finite element models of the proximal femur with different screw tunnel numbers, diameters, thicknesses, and arrangements. An acetabulum exerting a vertical pressure load of 600N on the femoral head was simulated and the force on various parts of the femur in each model was calculated. RESULTS: There was no difference in the Hounsfield Units of the tunnel walls and cortical bone of the proximal femur (893.48±61.28 vs. 926.34±58.43; p=0.091). In each of the 3D models, the cancellous bone was the first structure to reach maximal stress. The compressive strength of the femur decreased with increasing thickness of the screw tunnel wall and decreased with increasing tunnel diameter. The femoral neck model with the inverted triangle screw tunnel arrangement had the highest compressive strength. DISCUSSION: The femoral neck with screw tunnels can withstand day-to-day stress without special intervention. For femoral neck fractures fixed with cannulated screws, inverted triangle screws are recommended; For a single screw tunnel in the femoral neck, the larger the diameter of the femoral neck internal screw channel, the weaker the load-bearing capacity of the femur. LEVEL OF EVIDENCE: III; well-designed computational non-experimental study.