Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

OBJECTIVES: To study clinical manifestations and gene mutation features of neonates with centronuclear myopathy. METHODS: A retrospective analysis was conducted on the medical data of 5 neonates with centronuclear myopathy diagnosed in the Neonatal Intensive Care Unit of Children's Hospital, Zhejiang University School of Medicine from January 2020 to August 2024. The data included gender, gestational age, birth weight, Apgar score, clinical manifestations, creatine kinase level, electromyography, genetic testing results and the outcomes of the infants. RESULTS: All 5 male neonates had a history of postpartum asphyxia and resuscitation. They all presented with hypotonia, myasthenia, and respiratory failure; two neonates also had swallowing dysfunction. Of the five neonates, three had normal creatine kinase levels, while two had slightly elevated levels. Electromyography was performed for three neonates, among whom two had myogenic damage. MTM1 gene mutations were identified by genetic testing in all five neonates, including two nonsense mutations and three missense mutations, among which one variant had not been previously reported. Four mutations were inherited from the mother, and the other one was a de novo mutation. The five neonates showed no clinical improvement following treatment, failed weaning from mechanical ventilation, and ultimately died after withdrawal of life-sustaining therapy. CONCLUSIONS Centronuclear myopathy caused by MTM1 gene mutation often has a severe phenotype and a poor prognosis, and it should be considered for neonates with hypotonia and myasthenia after birth. Genetic testing should be performed as soon as possible.
Humans ; Myopathies, Structural, Congenital/genetics* ; Male ; Infant, Newborn ; Retrospective Studies ; Mutation ; Female ; Protein Tyrosine Phosphatases, Non-Receptor/genetics*

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 understand the incidence trend of brucellosis over time in Shandong Province from 2004 to 2023, and provide evidence for the prevention and control of brucellosis.Methods:The incidence data of brucellosis in Shandong from 2004 to 2023 were collected from China Disease Prevention and Control Information System. The annual change percentage (APC) and annual average change percentage (AAPC) of the incidence rate were calculated by using Joinpoint regression model. A age-period-cohort model was used to analyze changes in brucellosis incidence with age, period, and birth cohort.Results:The average annual incidence of brucellosis was 1.76/100 000 in Shandong from 2004 to 2023. The Joinpoint regression analysis results showed that the reported incidence of brucellosis increased by an average of 92.0% and 18.9% each year from 2004 to 2010 and from 2010 to 2014, respectively, and decreased by an average of 0.2% each year from 2014 to 2023. The results of APC model showed that the incidence of brucellosis increased first and then decreased with age ( χ2=176.92, P<0.001), and incidence of brucellosis showed slow increase and rapid increase first, then decrease ( χ2=2 921.03, P<0.001) over time. The risk for brucellosis reached peak in 2016 ( RR=5.29, 95% CI: 4.96-5.65) and became the lowest in 2006 ( RR=0.24, 95% CI: 0.21-0.28). The incidence increased in later birth cohort ( χ2=348.88, P<0.001), the AAPCs of all the age groups were between 15.0% and 40.0%, and the older the age, the greater the risk ( χ2=348.77, P<0.001). Conclusions:From 2004 to 2023, the reported incidence of brucellosis in Shandong showed a significant age-period-cohort effect, which increased first and then decreased, first increased and then decreased with age, increased slowly and rapidly first, then decreased over time, and increased in later birth cohort. It is necessary to conduct targeted prevention and control, health education to reduce the risk for brucellosis.

Objective To explore the effectiveness of drawing-based method in medical courses and their impact on students' learning habits,academic performance,and comprehensive competencies,in order to meet the demand for high-quality,interdisciplinary,and innovative talent,and provide theoretical support for integrating aesthetic education into medical training.Methods A questionnaire survey was conducted among medical students(n=310)at Dalian Medical University,covering the frequency of using drawing method and their effects on learning outcomes,innovation ability,and humanistic qualities.Data were analyzed using the Chi-square test and Fisher's exact test(P＜0.05).Results Totally 93.6％of students approved of using drawing method for learning medical courses,with 70.8％having developed a habit of drawing-based learning.Students with stronger drawing skills were more inclined to use drawing method and supported their application in teaching.The frequency of drawing-based learning was positively correlated with anatomy scores(P＜0.05).Students generally agreed that drawing method enhanced knowledge comprehension,learning interest,long-term memory,innovation ability,critical thinking,and humanistic qualities.However,students with weaker drawing skills perceived drawing method as potentially increasing learning burdens and being less efficient,but this perception significantly decreased with increased drawing frequency(P＜0.05).Conclusion Drawing methods are widely used in medical courses and effectively improve learning outcomes and comprehensive competencies.Drawing proficiency and frequency are key factors influencing students' acceptance and learning effectiveness.Future efforts should focus on promoting drawing method,strengthening students' drawing skills,and optimizing learning processes to deepen the integration of aesthetic education in medical training.