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.

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/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.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.

Objectives It was a preliminary exploration on rare disease management of comprehensive hospital based on the"Center-Multidisciplinary Team"structure.Methods By applying interrupted time series analysis,the characteristics and related medical service of rare disease patients discharged from sample hospitals from 2021 to 2023 were measured.Results The results showed that the hospital served 19 825 rare disease patients from 2021 to 2023.The proportion of patients whose main diagnosis were rare diseases was approximately 27％.The interrupted time series technique indicated that the expected proportion of rare disease patients increased instantly by 1.89 thousand points.The capability to diagnose has significantly improved,with a growing trend on volume of bioinformatics analysis services for rare diseases patients.Conclusion The rare disease management based on the"Center-Team"structure can increase the attention of medical staff to rare diseases,strengthen the diagnostic capacity of rare diseases,and make patient management more continuous and disciplinary co-operation more efficient without significantly increasing the input burden on hospitals.