AIM To investigate the effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy(CSM).METHODS The CSM rat models were established and randomly assigned to the model group,the Fer-1 group(2 g/kg Ferrostatin-1 via intraperitoneal injection),the low-dose(9.7 g/kg,intragastrically),medium-dose(19.4 g/kg,intragastrically)and high-dose(38.8 g/kg,intragastrically)Jisuishang Formula groups,and the sham operation group,with 6 rats in each group.Following 4 weeks of treatment administration,BBB locomotor scores and oblique plate test result were recorded to assess their neurological function in rats.Histopathological evaluation utilized HE staining for spinal cord tissue pathology,Nissl staining for Nissl body visualization,and Prussian blue staining for iron ion deposition analysis.Protein expressions of Nrf2,SLC7A11,GPX4,HO-1,TFRC and Cox2 in spinal cord tissues was detected by immunofluorescence and Western blot,while mRNA expressions were quantified using RT-qPCR.RESULTS Compared to the sham group,the CSM model group exhibited significantly reduced BBB locomotor scores and inclined plane test performance at 1,2 and 4 weeks post-operation(P＜0.05);obvious tissue cavitation,cellular edema and Prussian blue positive iron deposition in spinal cord tissues;downregulated protein and mRNA expressions of Nrf2,SLC7A11,GPX4,HO-1(P＜0.05);and upregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).Compared to the model group,the Jisuishang Formula and Fer-1 intervention groups showed significantly improved BBB scores and inclined plane test result at 1,2 and 4 weeks post-operation(P＜0.05);reduced tissue cavitation,attenuated cellular edema and decreased Prussian blue positive iron deposition in spinal cord tissues;upregulated protein and mRNA expression of Nrf2,SLC7A11,GPX4 and HO-1 in spinal cord tissues(P＜0.05);and downregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).CONCLUSION Targeting the Nrf2/SLC7A11/GPX4 signaling pathway,Jisuishang Formula potentially suppresses ferroptosis and alleviates iron accumulation in spinal cord neurons,thereby improving neurological recovery in CSM rats.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the continuous development of imaging techniques such as magnetic resonance imaging,the detection rate of brain metastases is increasing.Although the incidence rate of cystic brain metastasis is far lower than that of solid brain metastasis,patients with cystic brain metastasis are in urgent condition and have obvious space occupying effect,which is an urgent clinical problem.Previous literature has reported that cystic brain metastasis is more common in breast cancer and lung adenocarcinoma,especially in lung cancer patients with positive driver gene.This article reports a case of small cell lung cancer with cystic brain metastasis,which started with neurological symptoms,and was clinically cured under a multidisciplinary diagnosis and treatment model.Through dynamic imaging evaluation and molecular residual lesion detection,the patient can avoid overtreatment and achieved a relatively higher quality of life on the basis of prolonging survival.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective:To investigate the feasibility and optimal expansion width of replacing the left anterior descending coronary artery (LADCA) with the region of heart sparing (RHS) to reduce cardiac radiation dose during breast cancer radiotherapy.Methods:Retrospective analysis was conducted on data from 88 patients with left-sided breast cancer who underwent radiotherapy at 2 centers: Nanfang Hospital of Southern Medical University (50 cases for the training set, 15 cases for the internal test set) and Ganzhou Hospital of Nanfang Hospital (23 cases for the external test set) from March 2022 to January 2024. All patients had left-sided invasive ductal carcinoma with axillary lymph node metastasis, and had undergone modified radical mastectomy and chemotherapy. Based on simulation CT images, 2 radiation oncologists delineated the LADCA and 8 RHSs. The RHSs were delineated by expanding the LADCA contour by 0.5 cm increments, totaling 8 expansions. The RHS widths were defined as 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 cm. The nnU-Net model was trained for 3D automatic segmentation of the LADCA and RHSs. Model performance was evaluated using the Dice similarity coefficient (DSC), relative volume error (RVE), sensitivity, specificity, and 95% Hausdorff distance (HD95). Additionally, the minimum, maximum, and average relative dose variations (RDV) as well as V5% and V20% indicators were calculated for the LADCA and each RHS. Correlation analysis was performed using the least squares regression, with the slope and coefficient of determination ( R2) employed to evaluate the accuracy of the model fitting, the relationship between the LADCA and RHS, and the degree of their correlation, thereby assessing the substitutive effect of the RHS for the LADCA. Results:The DSC for the LADCA was 0.415, while the DSCs for RHS widths of 0.5 cm and 4.0 cm were 0.718 and 0.835, respectively. Overall, the automatic segmentation performance improved with increasing RHS width. The DSC, RVE, sensitivity, specificity, and HD95 for the external test set were largely consistent with those of the internal test set, demonstrating the model's good robustness across different datasets. All RDVmin values were negative, while RDVmax and RDVmean showed a positive correlation with RHS width. RDVmean increased from 39.01% to 75.89% as the RHS width increased. In the correlation analysis, the slopes for RHS widths of 1.5 cm and 2.0 cm were 0.95 and 1.05, respectively, with R2 values and coefficients of variation of 0.79 and 0.73, and 21.11% and 24.03%, respectively. Conclusions:The automatic segmentation model trained on nnU-Net can accurately segment RHSs. Based on geometric and dosimetric indicators, a 1.5 cm-wide RHS is the most suitable substitute for the LADCA, effectively limiting the radiation dose to the LADCA without compromising target dose coverage.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

AIM To investigate the effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy(CSM).METHODS The CSM rat models were established and randomly assigned to the model group,the Fer-1 group(2 g/kg Ferrostatin-1 via intraperitoneal injection),the low-dose(9.7 g/kg,intragastrically),medium-dose(19.4 g/kg,intragastrically)and high-dose(38.8 g/kg,intragastrically)Jisuishang Formula groups,and the sham operation group,with 6 rats in each group.Following 4 weeks of treatment administration,BBB locomotor scores and oblique plate test result were recorded to assess their neurological function in rats.Histopathological evaluation utilized HE staining for spinal cord tissue pathology,Nissl staining for Nissl body visualization,and Prussian blue staining for iron ion deposition analysis.Protein expressions of Nrf2,SLC7A11,GPX4,HO-1,TFRC and Cox2 in spinal cord tissues was detected by immunofluorescence and Western blot,while mRNA expressions were quantified using RT-qPCR.RESULTS Compared to the sham group,the CSM model group exhibited significantly reduced BBB locomotor scores and inclined plane test performance at 1,2 and 4 weeks post-operation(P＜0.05);obvious tissue cavitation,cellular edema and Prussian blue positive iron deposition in spinal cord tissues;downregulated protein and mRNA expressions of Nrf2,SLC7A11,GPX4,HO-1(P＜0.05);and upregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).Compared to the model group,the Jisuishang Formula and Fer-1 intervention groups showed significantly improved BBB scores and inclined plane test result at 1,2 and 4 weeks post-operation(P＜0.05);reduced tissue cavitation,attenuated cellular edema and decreased Prussian blue positive iron deposition in spinal cord tissues;upregulated protein and mRNA expression of Nrf2,SLC7A11,GPX4 and HO-1 in spinal cord tissues(P＜0.05);and downregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).CONCLUSION Targeting the Nrf2/SLC7A11/GPX4 signaling pathway,Jisuishang Formula potentially suppresses ferroptosis and alleviates iron accumulation in spinal cord neurons,thereby improving neurological recovery in CSM rats.

Objective To explore the risk factors associated with the development of acute respir-atory distress syndrome(ARDS)in patients with severe traumatic brain injury(sTBI)and to construct and validate a risk prediction model for ARDS in these patients.Methods Clinical data from 371 sTBI patients admitted to Yangzhou Affiliated Hospital of Yangzhou University between January 2017 and December 2023 were retrospectively collected.Patients were randomly divided into modeling group(n=259)and validation group(n=112)at a 7-to-3 ratio.A nomogram model was constructed after screening for risk factors using the Least Absolute Shrinkage and Selection Operator(LASSO)and multivariate Logistic regression analysis.Model performance was evaluated using the receiver operating characteristic(ROC)curve,area under the curve(AUC),Hosmer-Lemeshow test,calibration curve,and deci-sion curve analysis(DCA).Results Statistically significant differences were observed in heart rate,respiratory rate,pupil size,percutaneous oxygen saturation(SpO2),Glasgow Coma Scale(GCS)score,Acute Physiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ)score,head Ab-breviated Injury Scale(AIS)score,chest AIS score,emergency intubation,pulmonary infection,associated chest trauma,midline shift,blood transfusion within 12 hours of admission,fluid intake within 24 hours of admission,shock,mechanical ventilation,hemoglobin level,hematocrit,white blood cell count,prothrombin time,international normalized ratio,total protein,albumin,serum calcium,oxygenation index,and base excess between the two groups(P＜0.05).Multivariate Lo-gistic regression analysis revealed that SpO2,pulmonary infection,and fluid intake within 24 hours of admission were predictors of ARDS in sTBI patients.The Hosmer-Lemeshow test results for the modeling and validation groups showed good fit(x2=10.373,P=0.240;x2=13.21,P=0.105).DCA results for both groups indicated net benefit at threshold probabilities ranging from 0％to 72％and 0％to 50％,respectively.Conclusion SpO2,pulmonary infection,and fluid in-take within 24 hours of admission are risk factors for ARDS in sTBI patients.The model constructed using these factors demonstrates good performance and provides a reliable tool for clinical screening of high-risk ARDS populations among sTBI patients.

Thoracolumbar spine fracture often leads to severe pain, functional impairments, and neurological deficits, for which open reduction and internal fixation can effectively restore the spinal structural stability. Open decompression and reduction with internal fixation can help relieve spinal cord compression and improve spinal function in cases of concomitant cord injury. Although spinal stability can be restored through surgery, patients often face chronic pain and functional impairments postoperatively. A postoperative rehabilitation program is critical in optimizing therapeutic outcomes, reducing complications, and minimizing the risk of secondary injuries. However, current rehabilitation methods, such as physical therapy, functional training, and pain management, are confronted with problems in clinical practice, including significant variation in efficacy, poor patient adherence, and prolonged rehabilitation period. There is an urgent need for a unified rehabilitation strategy to address these problems. To this end, the Spinal Trauma Group of the Orthopedic Physicians Branch of the Chinese Medical Association and the Spine Health Professional Committee of the Chinese Human Health Technology Promotion Association organized experts from relevant fields to formulate Evidence-based guidelines for rehabilitation treatment after internal fixation of thoracolumbar spine fracture in adults ( version 2025) by integrating evidences from clinical researches and advanced rehabilitation concepts at home and abroad. A total number of 14 recommendations concerning the rehabilitation treatment with multimodal analgesia, psychological intervention, deep vein thrombosis prevention, core muscle and extremity exercise, appropriate use of braces, early weight-bearing, device-aided rehabilitation exercise, neuroregulatory therapy, rehabilitation team were put forward, aiming to standardize the post-operative rehabilitation process following internal fixation, promote the functional recovery, and enhance patients′ quality of life.