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*

OBJECTIVE: To investigate the effects of low-dose irradiated autologous peripheral blood reinfusion (LDIAPBR) on a rat model of radiation-induced leukopenia. METHODS: The rats were randomly divided into four groups. In the LDIAPBR group, LDIAPBR was performed 1 day before modeling (10% of the total circulating blood volume was withdrawn, irradiated with 100 mGy ex vivo, and completely reinfused). Meanwhile, the normal group and model group only underwent blood withdrawal and reinfusion of the same proportion without blood irradiation. Except for the normal group, all groups were subjected to 1 Gy X-ray whole-body irradiation to establish a radiation-induced leukopenia rat model. The positive drug group received subcutaneous injection of rhG-CSF after modeling. It was monitored that the general condition of the rats, peripheral blood cell counts, immune organ indices, bone marrow nucleated cell counts and viability, and the pathological analysis of bone marrow sections was conducted. RESULTS: The LDIAPBR group exhibited significant improvements in overall condition compared to the model group. Notably, compared with the model group, peripheral blood leukocyte and lymphocyte counts were markedly higher in the LDIAPBR group. Furthermore, there was a significant increase in both the number and viability of nucleated cells in the bone marrow. Pathological examination of bone marrow sections revealed increased nucleated cell density and reduced cavity area in the LDIAPBR group. CONCLUSION LDIAPBR can effectively improve hematological parameters and bone marrow hematopoietic function in a rat model of radiation-induced leukopenia, providing a new approach for the prevention and treatment of radiation-related injuries.
Animals ; Leukopenia/prevention & control* ; Rats ; Blood Transfusion, Autologous ; Whole-Body Irradiation ; Radiation Injuries, Experimental/therapy*

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Sodium ; Wastewater ; Potassium ; Diet ; Blood Pressure ; China ; Sodium, Dietary ; Sodium Chloride, Dietary

Cells not only contain membrane-bound organelles (MBOs), but also membraneless organelles (MLOs) formed by condensation of many biomacromolecules. Examples include RNA-protein granules such as nucleoli and PML nuclear bodies (PML-NBs) in the nucleus, as well as stress granules and P-bodies in the cytoplasm. Phase separation is the basic organizing principle of the form of the condensates or membraneless organelles (MLOs) of biomacromolecules including proteins and nucleic acids. In particular, liquid-liquid phase separation (LLPS) compartmentalises and concentrates biological macromolecules into liquid condensates. It has been found that phase separation of biomacromolecules requires some typical intrinsic characteristics, such as intrinsically disordered regions, modular domains and multivalent interactions. The phase separation of biomacromolecules plays a key role in many important cell activities. In recent years, the phase separation of biomacromolecules phase has become a focus of research in gene transcriptional regulation. Transcriptional regulatory elements such as RNA polymerases, transcription factors (TFs), and super enhancers (SEs) all play important roles through phase separation. Our group has previously reported for the first time that long-term inactivation or absence of assembly factors leads to the formation of condensates of RNA polymerase II (RNAPII) subunits in the cytoplasm, and this process is reversible, suggesting a novel regulatory model of eukaryotic transcription machinery. The phase separation of biomacromolecules provides a biophysical understanding for the rapid transmission of transcriptional signals by a large number of TFs. Moreover, phase separation during transcriptional regulation is closely related to the occurrence of cancer. For example, the activation of oncogenes is usually associated with the formation of phase separation condensates at the SEs. In this review, the intrinsic characteristics of the formation of biomacromolecules phase separation and the important role of phase separation in transcriptional regulation are reviewed, which will provide reference for understanding basic cell activities and gene regulation in cancer.

Objective Hypertriglyceridemic waist(HW),hypertriglyceridemic waist-to-height ratio(HWHtR),and waist-to-hip ratio(WHR)have been shown to be indicators of cardiometabolic risk factors.However,it is not clear which indicator is more suitable for children and adolescents.We aimed to investigate the relationship between HW,HWHtR,WHR,and cardiovascular risk factors clustering to determine the best screening tools for cardiometabolic risk in children and adolescents. Methods This was a national cross-sectional study.Anthropometric and biochemical variables were assessed in approximately 70,000 participants aged 6-18 years from seven provinces in China.Demographics,physical activity,dietary intake,and family history of chronic diseases were obtained through questionnaires.ANOVA,x2 and logistic regression analysis was conducted. Results A significant sex difference was observed for HWHtR and WHR,but not for HW phenotype.The risk of cardiometabolic health risk factor clustering with HW phenotype or the HWHtR phenotype was significantly higher than that with the non-HW or non-HWHtR phenotypes among children and adolescents(HW:OR = 12.22,95%CI:9.54-15.67;HWHtR:OR = 9.70,95%CI:6.93-13.58).Compared with the HW and HWHtR phenotypes,the association between risk of cardiometabolic health risk factors(CHRF)clustering and high WHR was much weaker and not significant(WHR:OR = 1.14,95%CI:0.97-1.34). Conclusion Compared with HWHtR and WHR,the HW phenotype is a more convenient indicator with higher applicability to screen children and adolescents for cardiovascular risk factors.

Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,and the results highly rely on the personal knowledge and experience.The goal of this work was to establish a software-aided approach,by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry(UHPLC/IM-QTOF-MS)and in-house high-definition MS2 library,to enhance the identification of prototypes and metabolites of the compound formulae in vivo,taking Sishen formula(SSF)as a template.Seven different MS2 acquisition methods were compared,which demonstrated the potency of a hybrid scan approach(namely high-definition data-independent/data-dependent acquisition(HDDIDDA))in the identification precision,MS1 coverage,and MS2 spectra quality.The HDDIDDA data for 55 reference compounds,four component drugs,and SSF,together with the rat bio-samples(e.g.,plasma,urine,feces,liver,and kidney),were acquired.Based on the UNIFI? platform(Waters),the efficient data processing workflows were estab-lished by combining mass defect filtering(MDF)-induced classification,diagnostic product ions(DPIs),and neutral loss filtering(NLF)-dominated structural confirmation.The high-definition MS2 spectral li-braries,dubbed in vitro-SSF and in vivo-SSF,were elaborated,enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples.Consequently,118 prototypes and 206 metabolites of SSF were identified,with the identification rate reaching 80.51％and 79.61％,respectively.The metabolic pathways mainly involved the oxidation,reduction,hydrolysis,sulfation,methylation,demethylation,acetylation,glucuronidation,and the combined reactions.Conclusively,the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.

Ferroptosis is a new type of programmed cell death different from apoptosis and necrosis.Its mechanism involves iron overload,lipid peroxidation,and reactive oxygen species(ROS)generation caused by disordered iron metabolism.Ferroptosis is associated with primary osteoporosis as well as the secondary osteoporosis such as steroid-induced osteoporosis,diabetic osteoporosis and postmenopausal osteoporosis.The Chinese medicines for the prevention and treatment of osteoporosis through the mechanism of ferroptosis mainly involve Chinese herbal compounds such as herbal pair of Eucommiae Cortex-Dipsaci Radix,Jintiange Capsules,and Bugu Shengsui Prescription,the single Chinese herbal medicine of Achyranthis Bidentatae Radix,and the active ingredients of herbal medicines such as icariin,gastrodin,quercetin,and artesunate.The prevention and treatment of osteoporosis by Chinese medicine monomer and Chinese herbal compound can inhibit ferroptosis through multiple targets and multiple pathways.At present,Chinese medicine has advantages in the prevention and treatment of postmenopausal osteoporosis.The prevention and treatment of osteoporosis by regulating the mechanism of ferroptosis can provide a direction for the future research on the prevention and treatment of osteoporosis by Chinese medicine.

Hepatotoxicity induced by bioactive constituents in traditional Chinese medicines or herbs,such as bavachin(BV)in Fructus Psoraleae,has a prolonged latency to overt drug-induced liver injury in the clinic.Several studies have described BV-induced liver damage and underlying toxicity mechanisms,but little attention has been paid to the deciphering of organisms or cellular responses to BV at no-observed-adverse-effect level,and the underlying molecular mechanisms and specific indicators are also lacking during the asymptomatic phase,making it much harder for early recognition of hepatotoxicity.Here,we treated mice with BV for 7 days and did not detect any abnormalities in biochemical tests,but found subtle steatosis in BV-treated hepatocytes.We then profiled the gene expression of hepatocytes and non-parenchymal cells at single-cell resolution and discovered three types of hepatocyte subsets in the BV-treated liver.Among these,the hepa3 subtype suffered from a vast alteration in lipid metabolism,which was characterized by enhanced expression of apolipoproteins,carboxylesterases,and stearoyl-CoA desaturase 1(Scd1).In particular,increased Scd1 promoted monounsaturated fatty acids(MUFAs)syn-thesis and was considered to be related to BV-induced steatosis and polyunsaturated fatty acids(PUFAs)generation,which participates in the initiation of ferroptosis.Additionally,we demonstrated that mul-tiple intrinsic transcription factors,including Srebf1 and Hnf4a,and extrinsic signals from niche cells may regulate the above-mentioned molecular events in BV-treated hepatocytes.Collectively,our study deciphered the features of hepatocytes in response to BV insult,decoded the underlying molecular mechanisms,and suggested that Scd1 could be a hub molecule for the prediction of hepatotoxicity at an early stage.