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*

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.

Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnor-malities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms under-lying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Uti-lizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expres-sion QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4 110,NControls=13 569),we imple-mented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Associa-tion Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD patho-genesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate＜0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were asso-ciated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were asso-ciated with CJD at the transcriptional level.

Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnor-malities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms under-lying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Uti-lizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expres-sion QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4 110,NControls=13 569),we imple-mented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Associa-tion Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD patho-genesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate＜0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were asso-ciated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were asso-ciated with CJD at the transcriptional level.

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 investigate the clinical characteristics of female migraine patients with patent foramen ovale(PFO)and design a risk prediction model for PFO in female migraine patients(migraineur patients PFO risk prediction model,MPRPM).Methods Female migraine patients who visited Zhongshan Hospital,Fudan University from Jun 1,2019 to Dec 31,2022 were included.Preoperative information and follow-up results after discontinuation of medication were collected.Patients were divided into PFO-positive and PFO-negative groups based on transesophageal echocardiography results.A multivariate Logistic regression model and a random forest model were constructed,and the random forest model was validated multidimensionally.Key features were selected based on the mean decrease accuracy(MDA)to construct MPRPM.Results A total of 305 female patients were included in the study,with 204 patients in the PFO-positive group and 101 patients in the PFO-negative group.Multivariate Logistic regression analysis showed that age at migraine onset,attack frequency,severe impact on life during attacks,exercise-related headaches,menstruation-induced headaches,aura migraines,and a history of cryptogenic stroke were predictive factors for PFO positivity.The random forest model effectively predicted the incidence of PFO in female migraine patients,with an AUC of 0.895(95%CI:0.847-0.943).MPRPM demonstrated a sensitivity of 71.6%and specificity of 91.1%(AUC:0.862,95%CI:0.818-0.906,P<0.001).The optimal cut-off value was 2.5 points.Patients correctly classified by the model showed a higher rate of symptom improvement compared to incorrectly classified patients(94.3%vs.82.0%,P=0.023).Conclusion We identified predictive factors for PFO in migraine patients.MPRPM can provide guidance in the diagnostic process and therapeutic decision-making for female migraine patients,assist in patient triage,and reduce the healthcare burden.

Immunotherapy is an important breakthrough in canc-er treatment.Unfortunately,low drug concentration in tumor sites almost ineffectively initiates immune responses and thereby severely limits immune therapy applications in clinics.Nanoma-terials are well-recognized drug delivery system in cancer thera-py.Nanographene oxide(NGO)have shown immense perti-nence for anti-cancer drug delivery owing to their ultra-high sur-face area,chemical stability,good biocompatibility and excel-lent photosensitivity.In addition,functionalized modifications on the surface of NGO increase tumor targeting and minimize cy-totoxicity.This study focuses on reviewing the literature and up-dates on NGO in drug delivery and discussing the possibilities and challenges of NGO in cancer synergetic therapy.

Background: Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures. Methods: The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were “calibration,” “mass spectrometry,” and “regression.” Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results. Results: The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling. Conclusions This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.

Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.
Humans ; Female ; Blood Platelets/pathology* ; Biomarkers, Tumor/genetics* ; Ovarian Neoplasms/pathology* ; China

Abstract: Objective　To analyze the influencing factors of mother-to-child transmission of hepatitis B virus after combined immunological blockade, and to evaluate the effect of mother-to-child blockade, and to provide a basis for health policies and health interventions for preventing mother-to-child blockade of hepatitis B virus. Methods A total of 11 363 pairs of HBsAg positive pregnant women and their infants aged 7-12 months in Hainan Province from 2015 to 2020 were included in the study. The general situation, the situation of health care and delivery in this pregnancy and perinatal period, the detection of hepatitis B markers, the situation of antiviral therapy, the general situation of mother and infant during delivery and the implementation of blockade measures for mother-to-child transmission of hepatitis B were collected and analyzed. Results Among the 11 363 pairs of HBsAg positive pregnant women and their infants delivered in hospitals in Hainan province from 2015 to 2020, the positive rate of HBsAg in children at 7-12 months after birth was 1.47 %, and the difference in HBsAg positive rate of infants born in different years was not statistically significant (P>0.05). There were no significant differences in the positive rate of HBsAg among children born to pregnant women with different nationalities, educational levels, occupations, delivery modes, delivery places, obstetric operations and perineal laceration, abnormal perinatal period, children with different genders and premature delivery and perinatal (all P<0.05). There was significant difference in HBsAg positive rate among infants born to pregnant women of different ages, the positive rate of HBsAg of infants born to young pregnant women was higher than that of older pregnant women (P<0.05). The rate of antiviral therapy was low in HBeAg positive pregnant women, and the positive rate of HBsAg in their infants was 2.54%, which was higher than 0.83% in HBeAg negative pregnant women (P<0.05). Conclusions Combined immunological blockade with hepatitis B vaccine and hepatitis B immunoglobulin can effectively prevent the mother-to-child transmission of HBV. HBsAg-positive women can give birth at the right age, and HBeAg-positive pregnant women can be treated with antiviral therapy to block mother-to-child transmission, providing the important basis for the formulation of hepatitis B prevention and control strategies and measures.