Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

Objective:To evaluate the efficacy of combined cricopharyngeal myotomy (CPM) and autologous fat injection laryngoplasty (AFIL) in the management of dysphagia secondary to glossopharyngeal and vagal nerve injury.Methods:This retrospective cohort study collected the clinical data of 18 patients with persistent dysphagia due to glossopharyngeal and vagus nerve injuries, who underwent concurrent cricopharyngeal myotomy (CPM) and autologous fat injection laryngoplasty (AFIL) at the Department of Otolaryngology, Peking Union Medical College Hospital, from January 2017 to December 2024. Pre-and postoperative assessments included electronic flexible laryngoscope, the Chinese version of Swallow Quality-of-Life Questionnaire (CSWAL-QOL), videofluoroscopic swallowing study (VFSS), body weight changes, and nasogastric tube (NGT) removal status with routine follow-up. The comparison of swallowing function before and after surgery was conducted using paired samples t-test and χ2 test. Results:The study cohort comprised 10 male and 8 female patients, with ages ranging from 33 to 70 years (mean±SD: 53.8±10.5). All surgical procedures were completed successfully without complications. During the 6-to 24-month follow-up period, 10 of the 13 patients who were initially nasogastric tube-dependent achieved successful decannulation. Compared with preoperative values, postoperative measurements demonstrated statistically significant improvements across all parameters: mean body weight increased from (56.95±9.14) kg to (59.22±8.72) kg ( t=3.689 , P<0.01), CSWAL-QOL scores improved from 91.89±17.81 to 130.83±25.42 ( t=6.921 , P<0.01), while, both VFSS scales showed marked reductions (VFSS-SWAL: 6.78±1.40 to 3.39±1.61, t=-8.001, P<0.01; PAS: 6.56±1.15 to 2.94±1.26, t=-10.114, P<0.01). Conclusions:Combined CPM and AFIL represents an effective surgical approach for dysphagia following glossopharyngeal and vagal nerve injury, thereby demonstrating significant improvements in both swallowing function and quality of life.

Objective To explore the impact of ondansetron's use within 24 h before delirium assess-ment in ICU patients on the risk of delirium occurrence.Methods All data were derived from the Critical Care Medical Information Database(MIMIC)-Ⅲ,MIMIC-Ⅳ and the eICU Collaborative Research Database.The research subjects were the patients who were admitted to ICU for treatment for the first time and had re-cords of delirium assessment.The research variable was whether ondansetron was used within 24 h before de-lirium assessment.The main observation indicator was whether delirium occurred after the patient entering to ICU,and whether the patient died during hospitalization or was discharged and returned home was taken as the secondary observation indicator.The propensity score matching eliminated confounding factors,and the stepwise logistic regression and nearest neighbor matching were used to analyze the influencing factors.Results A total of 78 364 patients had the delirium assessment records,among them 22 158 patients had the positive assessment results.A total of 294 patients who used ondansetron within 24 h before delirium assess-ment were taken as the ondansetron group,and 78 070 patients who did not use ondansetron were taken as the control group.Propensity score matching corrected most of the covariates between the two groups.The results of multivariate logistic regression analysis showed that the use of ondansetron was a protective factor for the delirium occurrence(OR=0.72,95％CI:0.53-0.96),and the results of nearest neighbor matching analysis also supported this association(OR=0.48,95％CI:0.31-0.76).However,the use of ondansetron had no effect on the outcome of in-hospital death or discharge home for critically ill patients(P＞0.05).Conclusion Ondansetron may be an effective drug for the prevention or treatment of delirium in critically ill patients.

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

Objective:To evaluate the efficacy of combined cricopharyngeal myotomy (CPM) and autologous fat injection laryngoplasty (AFIL) in the management of dysphagia secondary to glossopharyngeal and vagal nerve injury.Methods:This retrospective cohort study collected the clinical data of 18 patients with persistent dysphagia due to glossopharyngeal and vagus nerve injuries, who underwent concurrent cricopharyngeal myotomy (CPM) and autologous fat injection laryngoplasty (AFIL) at the Department of Otolaryngology, Peking Union Medical College Hospital, from January 2017 to December 2024. Pre-and postoperative assessments included electronic flexible laryngoscope, the Chinese version of Swallow Quality-of-Life Questionnaire (CSWAL-QOL), videofluoroscopic swallowing study (VFSS), body weight changes, and nasogastric tube (NGT) removal status with routine follow-up. The comparison of swallowing function before and after surgery was conducted using paired samples t-test and χ2 test. Results:The study cohort comprised 10 male and 8 female patients, with ages ranging from 33 to 70 years (mean±SD: 53.8±10.5). All surgical procedures were completed successfully without complications. During the 6-to 24-month follow-up period, 10 of the 13 patients who were initially nasogastric tube-dependent achieved successful decannulation. Compared with preoperative values, postoperative measurements demonstrated statistically significant improvements across all parameters: mean body weight increased from (56.95±9.14) kg to (59.22±8.72) kg ( t=3.689 , P<0.01), CSWAL-QOL scores improved from 91.89±17.81 to 130.83±25.42 ( t=6.921 , P<0.01), while, both VFSS scales showed marked reductions (VFSS-SWAL: 6.78±1.40 to 3.39±1.61, t=-8.001, P<0.01; PAS: 6.56±1.15 to 2.94±1.26, t=-10.114, P<0.01). Conclusions:Combined CPM and AFIL represents an effective surgical approach for dysphagia following glossopharyngeal and vagal nerve injury, thereby demonstrating significant improvements in both swallowing function and quality of life.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Objective To propose a cell phone fingertip video-based heart rate extraction algorithm to relieve the influences of environmental factors.Methods Firstly,the fingertip video was captured and extracted at a frame rate of 30 frames/s,and the images were separated into three channels:R,G,and B.The brightness changes of the three channels were compared,the G channel,which was the most sensitive to the fingertip blood flow signal,was selected as the signal source,and the brightness change information was extracted to generate a volumetric pulse waveform with a duration of 10 s.Secondly,the waveform underwent signal processing such as digital filtering,removal of baseline drift and Fourier transform,then the heart rate was predicted based on the position information of the maximum spectral peak.Finally,the heart rate prediction efficacy by the proposed algorithm was validated on Brno University of Technology Smartphone PPG Database(BUT PPG dataset).Results The predicted heart rate by the algorithm and the actual value had the mean square deviation,root mean square deviation and mean absolute error being 3.71,1.92 and 1.2 beats/min,respectively.Condusion The algorithm proposed has high accuracy for heart rate prediction,and can be invovled in cell phones for daily heart rate monitoring.[Chinese Medical Equipment Journal,2024,45(8):16-20]

The plants of Rutaceae, with wide distribution in China, have a long history of medicinal use. They contain a wide variety of alkaloids, which include isoquinolines, quinolines, acridones, carbazoles, and indoles. Pharmacological studies have shown that most of these alkaloids have antitumor, anti-inflammatory, antiviral, antidiabetic and other activities. This article summarized 378 alkaloids isolated from plants of Rutaceae and their pharmacological effects, aiming to lay a basis for future drug development and sustainable utilization of plant resources.
Alkaloids/chemistry* ; Humans ; Rutaceae/chemistry* ; Animals ; Drugs, Chinese Herbal/chemistry* ; Anti-Inflammatory Agents/chemistry*