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.

Objective:Mendelian randomization analysis (MR) was used to investigate the causal association between nine cathepsins and cholelithiasis.Methods:Single nucleotide polymorphism (SNP) sites closely associated and mutually independent with nine cathepsins and cholelithiasis were screened out from the Genome-Wide Association Study database and the FinnGen Biobank database, respectively. SNP corresponding to exposure factors were selected as instrumental variables. Two-sample bidirectional MR analysis was conducted with methods of inverse variance weighted (IVW), weighted median and MR-Egger regression. Additionally, multivariable Mendelian randomization (MVMR) was conducted to estimate the direct effect of cathepsins on cholelithiasis. Cochran's Q test, MR-PRESSO method and MR Egger regression were used to evaluate the levels of heterogeneity and pleiotropy. And the leave-one-out method was performed for the sensitivity analysis. Results:The univariable Mendelian randomization analysis results indicated that elevated cathepsin B levels increased the overall risk of cholelithiasis (IVW: OR=1.054, 95% CI: 1.025-1.083, P<0.001). The reverse MR analyses did not support a causal effect of cholelithiasis on cathepsin B (IVW: OR=0.998, 95% CI: 0.920-1.083, P=0.969). A multivariable analysis showed that elevated cathepsin B levels were still strongly associated with an increased risk of cholelithiasis (IVW: OR=1.038, 95% CI: 1.003-1.073, P=0.031). None evidence of significant pleiotropy and heterogeneity was observed, which was verified by sensitivity analysis. Conclusion:Cathepsin B may serve as a marker for cholelithiasis, and has important guiding significance in cholelithiasis treatment.

Objective:Mendelian randomization analysis (MR) was used to investigate the causal association between nine cathepsins and cholelithiasis.Methods:Single nucleotide polymorphism (SNP) sites closely associated and mutually independent with nine cathepsins and cholelithiasis were screened out from the Genome-Wide Association Study database and the FinnGen Biobank database, respectively. SNP corresponding to exposure factors were selected as instrumental variables. Two-sample bidirectional MR analysis was conducted with methods of inverse variance weighted (IVW), weighted median and MR-Egger regression. Additionally, multivariable Mendelian randomization (MVMR) was conducted to estimate the direct effect of cathepsins on cholelithiasis. Cochran's Q test, MR-PRESSO method and MR Egger regression were used to evaluate the levels of heterogeneity and pleiotropy. And the leave-one-out method was performed for the sensitivity analysis. Results:The univariable Mendelian randomization analysis results indicated that elevated cathepsin B levels increased the overall risk of cholelithiasis (IVW: OR=1.054, 95% CI: 1.025-1.083, P<0.001). The reverse MR analyses did not support a causal effect of cholelithiasis on cathepsin B (IVW: OR=0.998, 95% CI: 0.920-1.083, P=0.969). A multivariable analysis showed that elevated cathepsin B levels were still strongly associated with an increased risk of cholelithiasis (IVW: OR=1.038, 95% CI: 1.003-1.073, P=0.031). None evidence of significant pleiotropy and heterogeneity was observed, which was verified by sensitivity analysis. Conclusion:Cathepsin B may serve as a marker for cholelithiasis, and has important guiding significance in cholelithiasis treatment.

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.

Objective To evaluate the application of three deep learning algorithms in automatic segmentation of clinical target volumes (CTVs) in high-dose-rate brachytherapy after surgery for endometrial carcinoma. Methods A dataset comprising computed tomography scans from 306 post-surgery patients with endometrial carcinoma was divided into three subsets: 246 cases for training, 30 cases for validation, and 30 cases for testing. Three deep convolutional neural network models, 3D U-Net, 3D Res U-Net, and V-Net, were compared for CTV segmentation. Several commonly used quantitative metrics were employed, i.e., Dice similarity coefficient, Hausdorff distance, 95th percentile of Hausdorff distance, and Intersection over Union. Results During the testing phase, CTV segmentation with 3D U-Net, 3D Res U-Net, and V-Net showed a mean Dice similarity coefficient of 0.90 ± 0.07, 0.95 ± 0.06, and 0.95 ± 0.06, a mean Hausdorff distance of 2.51 ± 1.70, 0.96 ± 1.01, and 0.98 ± 0.95 mm, a mean 95th percentile of Hausdorff distance of 1.33 ± 1.02, 0.65 ± 0.91, and 0.40 ± 0.72 mm, and a mean Intersection over Union of 0.85 ± 0.11, 0.91 ± 0.09, and 0.92 ± 0.09, respectively. Segmentation based on V-Net was similarly to that performed by experienced radiation oncologists. The CTV segmentation time was < 3.2 s, which could save the work time of clinicians. Conclusion V-Net is better than other models in CTV segmentation as indicated by quantitative metrics and clinician assessment. Additionally, the method is highly consistent with the ground truth, reducing inter-doctor variability and treatment time.

Objective To investigate the environmental contamination related to first patient with carbapenem-re-sistant Acinetobacter baumannii(CRAB)infection and the infection status of relevant patients in a newly established intensive care unit(ICU)of a hospital in Tibetan area,and analyze the transmission risk.Methods From the ad-mission in ICU of a patients who was first detected CRAB on November 15,2021 to the 60th day of hospitalization,all patients who stayed in ICU for＞48 hours were performed active screening on CRAB.On the 30th day and 60th day of the admission to the ICU of the first CRAB-infected patient,environment specimens were taken respectively 2 hours after high-frequency diagnostic and therapeutic activities but before disinfection,and after disinfection but before medical activities.CRAB was cultured with chromogenic culture medium.Results Among the 13 patients who were actively screened,1 case was CRAB positive,he was transferred from the ICU of a tertiary hospital to the ICU of this hospital on November 19th.On the 40th day of admission to the ICU,he had fever,increased frequency for sputum suction,and CRAB was detected.The drug sensitivity spectrum was similar to that of the first case,and he also stayed in the adjacent bed of the first case.64 environmental specimens were taken,and 9 were positive for CRAB,with a positive rate of 14.06％,8 sampling points such as the washbasin,door handle and bed rail were positive for CRAB after high-frequency diagnostic and therapeutic activities.After routine disinfection,CRAB was detected from the sink of the washbasin.Conclusion For the prevention and control of CRAB in the basic-level ICU in ethnic areas,it is feasible to conduct risk assessment on admitted patients and adopt bundled prevention and con-trol measures for high-risk patients upon admission.Attention should be paid to the contaminated areas(such as washbasin,door handle,and bed rail)as well as the effectiveness of disinfection of sink of washbasin.

Objectives: This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach. Methods: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches. Results: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment. Conclusions This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.

A 3-year-old boy presented with bluish patch and scattered blue spots on the left side of his face. After several sessions of laser treatment, the azury patch in the periorbital area became even darker. Histopathology showed many bipolar, pigment-laden dendritic cells scattered in the papillary and upper reticular dermis. Immunohistochemically, these cells were positive for S100, SOX-10, melan-A, P16, and HMB-45. The positive rate of Ki-67 was less than 5%. Finally, the lesion was diagnosed with nevus of Ota concurrent with common blue nevus. Therefore, for cases of the nevus of Ota with poor response to laser treatment, the possible coexisting diseases should be suspected.
Male ; Humans ; Child, Preschool ; Nevus, Blue/pathology* ; Nevus of Ota/therapy* ; Skin/pathology* ; Face ; Skin Neoplasms/pathology*

Objective: To construct and verify a light-weighted convolutional neural network (CNN), and explore its application value for screening the early stage (subcategory 0/1 and stage Ⅰ of pneumoconiosis) of coal workers' pneumoconiosis (CWP) from digital chest radiography (DR) . Methods: A total of 1225 DR images of coal workers who were examined at an Occupational Disease Prevention and Control Institute in Anhui Province from October 2018 to March 2021 were retrospectively collected. All DR images were collectively diagnosed by 3 radiologists with diagnostic qualifications and gave diagnostic results. There were 692 DR images with small opacity profusion 0/- or 0/0 and 533 DR images with small opacity profusion 0/1 to stage Ⅲ of pneumoconiosis. The original chest radiographs were preprocessed differently to generate four datasets, namely 16-bit grayscale original image set (Origin16), 8-bit grayscale original image set (Origin 8), 16-bit grayscale histogram equalized image set (HE16) and 8-bit grayscale histogram equalized image set (HE8). The light-weighted CNN, ShuffleNet, was applied to train the generated prediction model on the four datasets separately. The performance of the four models for pneumoconiosis prediction was evaluated on a test set containing 130 DR images using measures such as the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, and Youden index. The Kappa consistency test was used to compare the agreement between the model predictions and the physician diagnosed pneumoconiosis results. Results: Origin16 model achieved the highest ROC area under the curve (AUC=0.958), accuracy (92.3%), specificity (92.9%), and Youden index (0.8452) for predicting pneumoconiosis, with a sensitivity of 91.7%. And the highest consistency between identification and physician diagnosis was observed for Origin16 model (Kappa value was 0.845, 95%CI: 0.753-0.937, P<0.001). HE16 model had the highest sensitivity (98.3%) . Conclusion: The light-weighted CNN ShuffleNet model can efficiently identify the early stages of CWP, and its application in the early screening of CWP can effectively improve physicians' work efficiency.
Humans ; Retrospective Studies ; Anthracosis/diagnostic imaging* ; Pneumoconiosis/diagnostic imaging* ; Coal Mining ; Neural Networks, Computer ; Coal