A 11-year old female patient with severe thalassemia, receipt a lentivirus-based cell and gene therapy (CGT) therapy in Shenzhen Children′s Hosptial on July 27th, 2021. At the two follow-up visits after discharge, patient were continuously tested positive for HIV screening through HIV Ag/Ab Combo assay (chemiluminescence Immunoassay), and the viral load results of HIV-1 nucleic acid testing (NAT) were both>5 000 copies/ml. The patient can be diagnosed with HIV infection according to the National Guideline for Detection of HIV/AIDS(2020 Revised Edition). The thorough investigation findings and supplementary experiment results indicated that the false-positive HIV-1 NAT results was caused by cross-reactivity between the target sites detected by conventional HIV-1 NAT reagents and the lentiviral vectors fragments integrated into the genome of patient′s hematopoietic stem/progenitor cells. In conclusion, it is important for laboratories to select appropriate HIV-1 NAT testing platforms which won′t cause cross-reactivity for the testing of samples from patients who have been treated with HIV-derived vectors. It is also recommended to design and develop NAT testing platforms with multiple target regions labeled by different fluorescents for HIV NAT supplementation experiment to reduce the risk of false-positive diagnoses of HIV infection.

From the perspectives of traditional Chinese medicine （TCM） information knowledge base and assisted decision-making knowledge base， the construction status， quality evaluation status and existing problems of current TCM knowledge bases have been sorted out. And based on the quality evaluation strategies and dimensions of know-ledge bases in other disciplines， the evaluation indexes for TCM knowledge base is discussed， and the evaluation framework is initially formed， providing ideas for the improvement of the TCM knowledge base evaluation system. In terms of the evaluation indexes， there are basic evaluation dimensions which include data sources， data collection， and data application. The specific evaluation dimension of the information-based knowledge base is data quality， while that of the assisted decision-making knowledge base is data matching. Except for the data application dimension which counts the valid data items in the database for calculation， other indexes are scored based on the qualitative evaluation of "yes"， "no" or "unknown". The basic evaluation score and the specific evaluation score are added to obtain the total score. The knowledge base is graded according to the score， and the results are presented in the form of grade plus number.

BACKGROUND:Traditional scoliosis orthosis has some disadvantages,such as complex manufacturing process,long processing cycle,poor fit and so on.Three-dimensional printed scoliosis orthosis has the advantages of high manufacturing precision and personalization. OBJECTIVE:To evaluate the efficacy of three-dimensional printed scoliosis orthosis for scoliosis based on multi-criteria decision model. METHODS:Clinical data of 72 patients with scoliosis admitted to Chen Xinghai Hospital of Integrated Traditional Chinese and Western Medicine from January 2019 to October 2022 were retrospectively collected and divided into two groups according to the treatment of orthosis.Study group(n=23)received three-dimensional printed scoliosis orthosis.Traditional group(n=49)received the traditional polypropylene spine brace treatment.The clinical efficacy and complications were compared between the two groups.A multi-criteria decision model for the treatment of scoliosis with three-dimensional printed scoliosis orthosis was established,and the stability of the benefit value,risk value and decision model of the two groups were evaluated. RESULTS AND CONCLUSION:(1)Compared with the traditional group,there were significant differences in the top vertebral offset distance,Cobb angle,top vertebral rotation,Functional Movement Screen score,visual analog scale score and total effective rate in the study group at 6 months after surgery(P<0.05).(2)Among the benefit indexes,Cobb angle had the greatest impact on the condition of patients,while the risk indexes had the greatest impact on dyspnea.(3)The benefit values of the study group and the traditional group for scoliosis were 79 and 64,and the risk values were 74 and 57,respectively.The combined benefit and risk values found that the benefit-risk value of the study group was 16 higher than that of the traditional group.(4)In the range of 0-100%relative risk weight,the benefit-risk value of the study group was always higher than that of the traditional group,which proved that the multi-criteria decision-making model had good stability.(5)It is indicated that three-dimensional printed scoliosis orthosis can better restore the physiological curvature of scoliosis and improve the efficiency of treatment.

Following the reform of the professional title system for"Breaking Four One-sided Evaluation Criteria"—focu-sing on more than just papers,titles,academic qualifications,and awards-establishing a scientific,systematic,and comprehen-sive medical performance evaluation index system has become essential for developing medical talent teams and conducting profes-sional title assessments fundamentally.This study establishes a medical performance evaluation index system tailored for clinicians in various departments of a cancer hospital who are competing for senior professional titles.This system comprises six primary in-dicators and 18 secondary indicators,with results presented in a ranked format of medical performance.Additionally,we have al-so analyzed the corr-elation between clinicians'medical performance rankings and their professional title evaluation outcomes through practical application.The results indicate that clinicians with higher performance rankings have significantly higher suc-cess rates in evaluations(P＜0.05).This index system underscores clinical practice,enhances classification-based evaluations,and supports advanced information management and precision in hospital administration,thereby providing a solid foundation for strengthening the hospital's core competitiveness.

Objective:To analyze the current status of anesthesiology research in the world and China in 2023 and to identify the anesthesiology research hotspots using bibliometrics.Methods:The literature related to anesthesiology published in PubMed in 2023 was searched, and the country and author of the literature, as well as the key words of the literature were visually analyzed by using the software CiteSpace6.2. R4.Results:A total of 22 473 articles were included, the country with the largest number of publications was the United States, and China ranked second. The author with the highest number of publications in the field of anesthesiology in the worldwide in 2023 was Kaye Alan D from the United States. Chronic pain, general anesthesia and pain management were the research hotspots in the field of anesthesiology worldwide in 2023. The research hotspots in the field of anesthesiology in China focused on general anesthesia, oxidative stress and neuropathic pain.Conclusions:The United States is the leader in the research in the field of anesthesiology, with China following behind. The keywords of the literature in the field of anesthesiology between China and the world are roughly the same, reflecting the convergence of Chinese scientific research with global scientific research. Domestic anaesthesia practitioners can refer to or learn from the research hotspots of related countries and strengthen communication and cooperation between teams while conducting academic research.

Objective:To explore the mediating roles of rumination and avoidance coping between information anxiety and suicidal ideation.Methods:In March 2022, a total of 896 college students were surveyed by the information anxiety scale(IAS), ruminative responses scale(RRS), coping style questionnaire(CSQ)and self-rating idea of suicidal ideation scale(SIOSS). The ANOVA analysis, Pearson correlation analysis and mediating effect analysis were performed by the SPSS 22.0 software.Results:The detection rate of suicidal ideation among college students was 9.15%(82/896). The information anxiety score was(73.84±17.29), the rumination score was(47.73±12.16), the avoidance coping score was(3.76±2.52), and the suicidal ideation score was(5.41±4.09). Information anxiety was significantly positively correlated with rumination, avoidance coping and suicidal ideation( r=0.49, 0.36, 0.37, all P<0.05). Rumination was significantly positively correlated with avoidance coping and suicidal ideation( r=0.42, 0.59, both P<0.05). There was a significantly positive correlation between avoidance coping and suicidal ideation( r=0.45, P<0.05). Information anxiety affected suicidal ideation of college students through four paths.The direct effect value of information anxiety on suicidal ideation was 0.06, accounting for 16.67% of the total effect. The effect values of the separate mediating effect of rumination and avoid coping were 0.22 and 0.04, and accounting for 61.11% and 11.11% of the total effect respectively. The chain mediating effect value of rumination and avoid coping was 0.04, accounting for 11.11% of the total effect. Conclusion:Information anxiety can directly affect suicidal ideation of college students and indirectly affect suicidal ideation through rumination and avoidance coping.

Objective:To explore the mediating effect of experiential avoidance and emotional eating between intolerable uncertainty and life satisfaction of college students.Methods:From October to December 2021, a total of 890 college students in the Beijing-Tianjin-Hebei region were tested by the intolerable uncertainty scale (simplified version), the acceptance action scale second edition, the Dutch eating behavior questionnaire and the life satisfaction scale. All data processing and analysis were preformed by SPSS 22.0 software, and the mediating effect was tested by Pearson correlation analysis and Bootstrap analysis.Results:The intolerable uncertainty score was (26.43±7.64), the experiential avoidance score was (22.63±9.67), the emotional eating score was (26.43 ±11.83), and the life satisfaction score was (16.74±6.03). Intolerable uncertainty was significantly and negatively correlated with life satisfaction( r=-0.76, P<0.01), and was significantly and positively correlated with experience avoidance and emotional eating( r=0.66, 0.78, both P<0.01). Experience avoidance was significantly and positively correlated with emotional eating( r=0.70, P<0.01), and was significantly and negatively correlated with life satisfaction( r=-0.62, P<0.01). Emotional eating was significantly and negatively correlated with life satisfaction( r=-0.68, P<0.01). Intolerable uncertainty affects life satisfaction through four paths.The direct effect value of intolerable uncertainty on life satisfaction was -0.53, accounting for 70.23% of the total effect. The separate mediating effect value of experience avoidance was -0.11, accounting for 50.00% of the total indirect effect.The separate mediating effect value of emotional eating was -0.08, accounting for 36.36% of the total indirect effect, and the chain mediating effect value of experience avoidance and emotional eating was -0.03, accounting for 13.64% of the total indirect effect. Conclusion:Intolerable uncertainty can directly affect life satisfaction of college students and indirectly through experiencing avoidance and emotional eating.

This paper reports a case of peritonitis caused by Campylobacter fetus in a continuous ambulatory peritoneal dialysis (CAPD) patient. The patient was a middle-aged man, with chronic kidney disease stage 5 secondary to chronic glomerulonephritis, and had been on CAPD for 6 years. He was admitted to our department with a 7 day history of abdominal pain and cloudy effluent. Peritoneal effluent culture was negative and metagenomic next-generation sequencing suggested Campylobacter fetus. Intraperitoneal treatment with amikacin was failed. Peritoneal dialysis catheter was removed and hemodialysis treatment was performed. After treatment of erythromycin oral for 4 weeks, the patient's symptoms was improved and discharged.

In the diagnosis of cardiovascular diseases, the analysis of electrocardiogram (ECG) signals has always played a crucial role. At present, how to effectively identify abnormal heart beats by algorithms is still a difficult task in the field of ECG signal analysis. Based on this, a classification model that automatically identifies abnormal heartbeats based on deep residual network (ResNet) and self-attention mechanism was proposed. Firstly, this paper designed an 18-layer convolutional neural network (CNN) based on the residual structure, which helped model fully extract the local features. Then, the bi-directional gated recurrent unit (BiGRU) was used to explore the temporal correlation for further obtaining the temporal features. Finally, the self-attention mechanism was built to weight important information and enhance model's ability to extract important features, which helped model achieve higher classification accuracy. In addition, in order to mitigate the interference on classification performance due to data imbalance, the study utilized multiple approaches for data augmentation. The experimental data in this study came from the arrhythmia database constructed by MIT and Beth Israel Hospital (MIT-BIH), and the final results showed that the proposed model achieved an overall accuracy of 98.33% on the original dataset and 99.12% on the optimized dataset, which demonstrated that the proposed model can achieve good performance in ECG signal classification, and possessed potential value for application to portable ECG detection devices.
Humans ; Electrocardiography ; Algorithms ; Cardiovascular Diseases ; Databases, Factual ; Neural Networks, Computer

Objective:To establish a differential diagnosis model for IgA nephropathy and non-IgA nephropathy based on machine learning algorithms.Methods:Retrospective study adopted,from 2019 to 2020,260 patients were referred to the Department of Nephrology at the First Affiliated Hospital of Kunming Medical University, the First People′s Hospital in Yunnan province, and Yan′an Hospital of Kunming city. All patients were diagnosed by renal pathology, 130 cases of primary IgA nephropathy, the 130 cases of non-IgA nephropathy. Collection of materials, including gender and age, 28 clinical data, and routine laboratory test results,the sex ratio of IgA nephropathy group and non-IgA nephropathy group were 59∶71 and 64∶66 respectively, the ages were 37.20 (21.89, 53.78) and 43.30 (27.77, 59.18) years, respectively. 260 patients were divided into a training set (70%, 182 cases) and a test set (30%, 78 cases). Using the decision tree, random forests, support vector machine, extreme gradient boosting to establish a differential diagnosis model for IgA nephropathy and non-IgA nephropathy. Based on the true positive rate, true negative rate, false-positive rate, false-negative rate, accuracy, subjects features work area under the curve(AUC), the precision ratio, recall ratio, and F1 score, comprehensively evaluate the performance of each model, finally, the best performance of the model was chosen. Using SPSS 25.0 to analyze the data, P<0.05 was considered to be statistically significant. Results:The accuracy of the decision tree, support vector machine, random forests and extreme gradient boosting establish differential diagnosis model was 67.95%, 70.51%, 80.77% and 83.33%, respectively; AUC values was 0.74, 0.76, 0.80 and 0.83; Judgment for primary IgA nephropathy F1 score was 0.73, 0.72, 0.80 and 0.83, respectively. The efficiency of the extreme gradient boosting model based on the above evaluation indicators is the highest, its diagnosis of IgA nephropathy of the sensitivity and specificity respectively 89% and 79%. The variable importance from high to low was blood albumin, IgA/C3, serum creatinine, age, urine protein, urine albumin, high-density lipoprotein cholesterol, urea.Conclusion:The differential diagnosis model for IgA nephropathy was established successfully and non-IgA nephropathy and the efficiency performance of the extreme gradient boosting algorithm was the best.