Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion. METHODS: The proposed model consists of the Input, Backbone Network and Classification Head modules. The Input module carries out data augmentation to improve the sample quality and generalization ability of the model. The Backbone Network was responsible for feature extraction based on Yolov8 combined with CBAM, ECA, PSA attention mechanism and AIFI feature interaction module. The Classification Head consists of a convolutional layer and a softmax function to output the final probability value of each class. The images of the key structures (the eyes, face, head, thalamus, and spine) were annotated with frames by physicians for model training to improve the classification accuracy of the anterior occipital, posterior occipital, and transverse occipital orientations. RESULTS: The experimental results showed that the proposed model had excellent performance in the tire orientation classification task with the classification accuracy reaching 0.984, an area under the PR curve (average accuracy) of 0.993, and area under the ROC curve of 0.984, and a kappa consistency test score of 0.974. The prediction results by the deep learning model were highly consistent with the actual classification results. CONCLUSIONS The multi-feature fusion model proposed in this study can efficiently and accurately classify fetal orientation in intrapartum ultrasound videos.
Humans ; Female ; Ultrasonography, Prenatal/methods* ; Pregnancy ; Fetus/diagnostic imaging* ; Neural Networks, Computer ; Video Recording

Objective:To assess the real-world triage performance of a dual-marker strategy (DMS) combining copeptin and high-sensitivity cardiac troponin T (hs-cTnT) in patients presenting with chest pain and suspected non-ST-segment elevation myocardial infarction (NSTEMI).Methods:It was conducted a prospective study of 277 consecutive chest pain patients admitted to the Emergency Department of Zhongshan Hospital, Fudan University, between July and August 2023. Admission levels of copeptin and hs-cTnT were measured. The safety, efficacy, and triage efficiency of the DMS (defined as copeptin <10 pmol/L and hs-cTnT <0.014 ng/mL) for excluding NSTEMI were evaluated based on final diagnoses and clinical outcomes.Results:Among 277 patients, 141 (50.9%) had cardiogenic diseases (51 NSTEMI, 37 unstable angina pectoris [UAP], 11 myocardial bridges, and 42 non-coronary artery disease), 29 (10.5%) had non-cardiac conditions, and 107 (38.6%) had low-risk chest pain of unknown etiology. A total of 103 patients (37.2%) were DMS-negative (copeptin and hs-cTnT both below cutoff), including 0 NSTEMI cases, 2 UAP cases, 1 myocardial bridge, 6 non-coronary artery diseases, 4 non-cardiac conditions, and 90 low-risk cases. The DMS demonstrated a negative predictive value (NPV) of 100% for excluding NSTEMI, with no major adverse cardiac events (MACE) observed in DMS-negative patients during 30-day follow-up. Real-world data revealed that only 42.2% of suspected NSTEMI patients received a second troponin test (timing: 1 hour—5.9%, 2 hours—23.9%, ≥3 hours—70.1%). The DMS enabled safe and efficient triage of 37.2% of chest pain patients at 0-hour, outperforming other strategies in applicability and feasibility ( P < 0.05). Conclusions:In real-world clinical practice, the DMS (copeptin combined with hs-cTnT) optimally complements guideline-recommended hs-cTnT algorithms. It provides a simple, rapid, and safe approach to managing acute chest pain, demonstrating superior applicability for improving emergency triage efficiency.

Objective To screen long non-coding RNA(lncRNA)associated with disulfidptosis and investigate the immune landscape between lncRNA and pancreatic cancer,for effective guidance in clinical practice.Methods The normal and pancreatic cancer tissue samples were obtained from The Cancer Genome Atlas database,and the lncRNA associated with disulfidptosis was identified based on the Cox and LASSO regression analyses.A risk prognosis model was constructed,and its predictive performance was verified using comprehensive methods.An accurate nomogram was construted to predict the prognosis of patients with pancreatic cancer.The biological differences were analyzed via Gene Ontology,Gene Set Enrichment Analysis,and an immunoassay.The immunotherapy response was estimated using the tumor mutational burden(TMB)score.Results A total of 251 disulfidptosis-related lncRNAs were successfully identified,and three groups of lncRNAs were selected as the reference for the risk model.Pathway analysis showed that immune-related pathways were associated with disulfidptosis-related lncRNA risk models.The risk score was significantly correlated with immune cell infiltration and the ESTIMATE score.Patients with higher risk scores had elevated TMB,indicating that high-risk patients exhibited a better immune checkpoint blockade response.Conclusion The findings of this study contribute to a deeper understanding of disulfidpto-sis-related lncRNA and provide a potential therapeutic strategy for pancreatic cancer.

Objective To explore the role of an artificial intelligence(AI)model based on real-time object detection network in fetal facial ultrasound examination.Methods With the normal fetal facial ultrasound standard plane(FFUSP)at 20-24 weeks of gestation as the research object,a FFUSP recognition model based on real-time object detection network was constructed.The recognition accuracy of the model for FFUSP and the anatomical structures were analyzed,and the clinical value was evaluated by analyzing its performance in identifying FFUSP in 119 cases of fetal ultrasound images.Results The overall precision,recall rate,mAP@.5 and mAP@.5:.95 of the AI model were 97.8%,98.5%,98.1%and 61.0%,respectively.The clinical validation showed that the AI model had a sensitivity,specificity,positive predictive value,negative predictive value and accuracy of 100.0%,98.5%,87.4%,100.0%and 98.7%for facial anatomy recognition,and the results were highly consistent with the classification of fetal ultrasound experts(k=0.925,P<0.001).The recognition accuracy of the model for 3 types of standard planes reached 100%;and the average speed of dynamic video detection was 33.93 frames per second.Conclusion The FFUSP recognition model based on real-time object detection network exhibits excellent performance,and it can be applied to real-time ultrasound diagnosis,teaching and intelligent quality evaluation.