Objective To systematically analyze the literature characteristics of Journal of Organ Transplantation since its inception. Methods Using the China National Knowledge Infrastructure (CNKI) academic journal full-text database as the data source, all articles published in the Journal of Organ Transplantation from January 2010 to August 2025 were retrieved. After excluding non-academic papers, a total of 1 568 research papers were included. R language 4.3.0, Bibliometrix package 3.2.1, and Citespace software were used to analyze the number of publications, publishing institutions, authors, keywords and other aspects. Results The number of publications in Journal of Organ Transplantation increased from an average of 82 articles per year in the early years after its inception to 113 articles per year in recent years, a growth of 37.8%. The geographical distribution of publishing institutions covers 32 provinces, cities and autonomous regions nationwide, mainly concentrated in the South China, East China and North China regions, and has now basically covered the central and western regions in recent years. The author collaboration network includes 45 authors distributed across 7 major collaboration clusters, forming a stable multi-level national research system centered on key university-affiliated hospitals. The high-frequency keywords are dominated by "liver transplantation" (425 times) and "kidney transplantation" (396 times). The theme evolution shows a clear three-stage characteristic: initially focusing on clinical technology application, deepening to immune mechanism exploration in the middle stage, and recently (since 2022) focusing on cutting-edge research areas such as xenotransplantation. Conclusions Journal of Organ Transplantation has witnessed the rapid development of China's organ transplantation cause, fully reflecting the research status and trends in China's organ transplantation field, and has provided an important platform for the future development and international cooperation in China's organ transplantation field.

Objective: To understand the current status of neglect among rural preschool children in Xi an under the multi child policy and the association with family characteristics, so as to provide a reference for preventing and reducing the occurrence of child neglect. Methods: A total of 7 052 parents of preschool children were selected using stratified cluster sampling across 9 suburban counties/districts in Xi an from March to April 2025. A questionnaire survey was administered using the Chinese Norm Scale for Neglect Assessment of Rural(Preschool) Children Aged 3-6. The t-test, Chi-quare test, and analysis of variance (ANOVA) were used for inter group comparisons. Results: The overall prevalence rate and mean score of neglect among rural preschool aged children in Xi an were 32.4% and 38.27±6.70, respectively. Statistically significant differences were detected in neglect rates and neglect degrees among preschool children of different genders and grade levels ( χ 2=30.41, 15.15, t/F =4.92,7.03, all P <0.05). Statistically significant differences were also detected in neglect rates and neglect degrees among preschool children from whether only one child, different family structures, numbers of children in a family and families with different annual incomes ( χ 2=29.22, 10.41 , 31.99, 186.47, t/F =-9.96, 5.50, 33.57, 68.63, all P <0.05). In multi child families, there was a statistically significant difference in neglect degree among children with different birth orders ( F =4.25, P <0.05), but there was no statistically significant difference in neglect rate ( χ 2=5.73, P >0.05). Among all subgroups, the highest neglect rates and neglect degrees were observed in children from multi child families(35.0%,39.00±6.71), other family types(50.0%，42.38±12.34) and families with three children(39.9%，39.50±7.43). Lower annual family income was associated with higher neglect rates and neglect degrees among preschool children( χ 2 trend =186.47， F =270.68，both P <0.05). Conclusions Under the multiple child policy, the neglect of preschool children in rural areas of Xi an is quite severe, particularly in families with multiple children and low income households. Targeted interventions should be implemented for high risk groups.

Objective To explore the factors affecting the quality of psychological assistance hotline connections in Shaanxi Province, and to provide a basis for optimizing services. Methods A total of 149 calls with suicidal tendencies were included from January to March 2022, and data were collected by 31 trained assessors through standardized questionnaires (general information, suicide risk, emotional intensity, and wiring characteristics). Results The results showed that 56.38% of the callers were female, with age groups concentrated between ≤ 18 years old (29.53%) and 19-34 years old (43.62%). The call duration was mainly between 31 and 45 minutes (50.34%). Operators conducted a suicide risk assessment on the callers, with 38.9% having a comprehensive assessment, 38.9% having an incomplete assessment, and 22.1% having no assessment. The main mental disorders of the callers were depression (48.32%), anxiety (15.44%), and bipolar disorder (14.77%), with 25.50% having comorbidities of ≥ 2 disorders. Emotional scores were as follows: depression (4.11 ± 0.76), sadness (3.97 ± 1.03), and despair (3.78 ± 1.05). There were significant differences in depression, anger, despair, and sadness among the callers with different levels of danger (t=4.79, 3.35, 15.79, 4.24, all P<0.05). Women had higher levels of fear than men (t=3.10, P<0.01). The longer the call duration, the higher the level of despair (t=5.66, P<0.01). Multiple regression analysis showed that incomplete suicide risk assessment by operators (B=-2.36), general procedures for operators' connections (B=5.44), and technical factors (B=2.01) significantly affected the quality of psychological assistance hotlines (all P<0.05). Conclusion Callers with suicidal tendencies generally have serious mental and psychological problems and prominent negative emotions. Strengthening the suicide risk assessment ability of operators and standardizing processes and service attitudes are key to improving the quality of psychological assistance hotlines.

Objective To investigate the epidemiological characteristics and changing trend of typhus in Shaanxi Province from 2005 to 2023 to provide a scientific basis for its prevention and control. Methods Excel 2007, SPSS 25.0, Joinpoint 4.9.1.0, and Geoda 1.6 were used for data collection and statistical analysis. Super Map was used for data visualization to describe the changing characteristics of the disease. Results A total of 394 typhus cases were reported in Shaanxi Province from 2005 to 2023. The average annual incidence of typhus was 0.054/100 000, showing a dynamic fluctuation trend(AAPC=-3.3, t=-0.3, P>0.05). The cases were mainly concentrated in Baoji, Hanzhong and Xi′an, accounting for 78.68%. The incidence peak was from May to October, accounting for 64.21% of annual incidence. The epidemic season was from May to October and December. The incidence of the disease was concentrated in the 40-69 age group, accounting for 58.88%, and the sex was 1.07:1. The main occupation was farmers, accounting for 72.08%. The median time from onset to diagnosis was 7 days. Global spatial autocorrelation analysis showed that there were significant spatial autocorrelations in 11 years from 2005 to 2023(P<0.05). Local spatial autocorrelation analysis detected a total of 43“high-high”clustering areas, mainly concentrated in Baoji City. Conclusions The overall incidence of typhus in Shaanxi Province showed a dynamic fluctuation trend, with notable seasonal and regional aggregation. The incidence of typhus was higher in middle-aged and elderly people in rural areas. Surveillance should be strengthened in typhus endemic areas in summer and autumn, and health education should be conducted for key population to form good health habits and reduce the incidence of typhus.

Objective To explore the epidemiological characteristics of gouty arthritis in Northwest China from 2023 to 2025, and to formulate preventive intervention measures. Methods By retrospectively analyzing the case data of medical institutions in Northwest China from January 2023 to June 2025 (a total of 8 139 cases), the incidence trend and population distribution characteristics of gouty arthritis in this area were analyzed. Multivariate logistic regression analysis was performed to identify risk factors. Results From 2023 to 2025, the prevalence rate of gouty arthritis in adult residents in Northwest China was 3.74% (304/8 139). Among the sites affected by gouty arthritis, the metatarsophalangeal joint accounted for the highest proportion (P<0.05). From the perspective of age distribution, the prevalence rate was the highest in 40-59 years old group (5.90%), followed by 66-80 years old group (4.21%) and >80 years old group (2.75%). The incidence rate in 40-65 years old group was higher than that in the other age groups (P<0.05). High blood uric acid and creatinine, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome were risk factors affecting gouty arthritis in Northwest China (P<0.05). Conclusion High blood uric acid level, high creatinine level, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome are risk factors influencing gouty arthritis in Northwest China. Based on the above factors, this study proposes comprehensive prevention strategies from the individual, community and public health levels to provide a scientific basis for reducing the incidence rate of gouty arthritis.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

With the rapid development of artificial intelligence(AI)technology,it shows great po-tential in the field of cancer early diagnosis and treatment and also faces risks and challenges.This paper systematically and comprehensively analyzed the multidimensional issues of AI in the management of cancer early diagnosis and treatment programs based on the SWOT(strengths,weaknesses,opportunities,threats)analysis framework.By identifying and evaluating the inherent advantages and disadvantages of AI technology,as well as the opportunities and potential threats brought by the external environment,targeted management optimization strategies are further pro-posed,in order to provide reference for AI technology to more efficiently and safely serve cancer early diagnosis and treatment programs.

Cancer screening and early diagnosis and treatment programs involve complex institu-tional and personnel,long cycles,large funding requirements,and uneven quality levels,posing challenges to scientific management.This paper focuses on the high-quality development of cancer screening and early diagnosis and treatment work,and optimizes the project management system for cancer screening and early diagnosis and treatment based on the PDCA cycle.By introducing the PD-CA cycle to cancer screening and early diagnosis and treatment project in Beijing,the application of the PDCA cycle in cancer screening and early diagnosis and treatment was further explored.

Objective:Invasive pulmonary mucormycosis(PM)is a rare but highly lethal opportunistic infection.COVID-19 associated mucormycosis(CAM)is difficult to diagnose,often leading to misdiagnosis or missed diagnosis,and has poor treatment outcomes.This study reports a case of successfully treated CAM and explores optimized diagnostic and therapeutic strategies.Methods:A retrospective analysis of the diagnosis and treatment process in a 50-year-old female patient with COVID-19 associated with diabetic ketoacidosis(DKA)and invasive pulmonary mucormycosis was conducted.Combined with a literature review,the therapeutic efficacy of local bronchoscopic instillation in conjunction with systemic treatment using liposomal Amphotericin B(L-AmB)was specifically evaluated.Results:The patient was rapidly diagnosed with Rhizopus microsporus infection through metagenomic next-generation sequencing(mNGS).She subsequently received antifungal treatment with intravenous L-AmB combined with local bronchoscopic instillation.After treatment,the patient was significantly improved,with imaging studies showing gradual absorption of the lesions.Follow-up at six months revealed no recurrence.A literature review suggests that early diagnosis and multimodal therapy are key to improving survival rates in patients with CAM.Conclusion:mNGS can significantly improve the early diagnosis rate of CAM.The combination of local and systemic treatment with L-AmB is valuable in improving prognosis.Early diagnosis,multimodal antifungal therapy,and individualized management are key to increasing the survival rate of patients with CAM.

Cancer screening and early diagnosis and treatment programs involve complex institu-tional and personnel,long cycles,large funding requirements,and uneven quality levels,posing challenges to scientific management.This paper focuses on the high-quality development of cancer screening and early diagnosis and treatment work,and optimizes the project management system for cancer screening and early diagnosis and treatment based on the PDCA cycle.By introducing the PD-CA cycle to cancer screening and early diagnosis and treatment project in Beijing,the application of the PDCA cycle in cancer screening and early diagnosis and treatment was further explored.