ObjectiveTo observe the effects of Yangjing Zhongyutang （YJZYT） on mitochondrial biogenesis and oxidative stress damage mediated by the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor gamma coactivator-1alpha （PGC-1α） signaling pathway in cyclophosphamide （CTX）-induced rats with diminished ovarian reserve （DOR）， and to explore its mechanism in improving ovarian reserve function and follicular development. MethodsForty-two 8-week-old female SD rats with normal estrous cycles were randomly divided into a blank control group （n=7） and a model group （n=35）. Rats in the model group received a single intraperitoneal injection of CTX （90 mg·kg^-1） to establish the DOR model. After modeling， estrous cycles were monitored for 7 consecutive days， and model success was confirmed based on criteria for estrous cycle disruption. After successful modeling， rats were divided into groups for intervention： estradiol valerate group （0.09 mg·kg^-1）， and YJZYT high-， medium-， and low-dose groups （19.98， 9.99， 5.00 g·kg^-1）. The blank control group and model group were given an equal volume of distilled water by gavage. All groups received daily gavage once for 4 consecutive weeks. The general state， body weight， and ovarian wet weight of rats were observed and recorded， and the ovarian organ index was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， anti-Müllerian hormone （AMH）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px）. Hematoxylin-eosin （HE） staining was performed to observe ovarian histomorphological changes and follicular development status. Immunofluorescence was used to detect reactive oxygen species （ROS） expression levels. Colorimetric assays were employed to measure adenosine triphosphate （ATP） and malondialdehyde （MDA） content in ovarian tissues. Quantitative Real-time polymerase chain reaction （Real-time PCR） was used to detect mitochondrial DNA （mtDNA） copy number and the mRNA expression levels of key genes including SIRT1， PGC-1α， nuclear respiratory factor 1 （NRF1）， and mitochondrial transcription factor A （TFAM）. Western blot was performed to detect the protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM. ResultsCompared with the blank group， rats in the model group exhibited disrupted estrous cycles， obviously reduced body weight， and decreased ovarian index （P<0.05）. Ovarian histopathology revealed cortical thinning， loose structure， and a significant reduction in both primordial and growing follicles （P<0.01）. Serum FSH and LH levels were significantly elevated （P<0.01）， while E₂ and AMH levels were obviously reduced （P<0.05， P<0.01）. ATP content and mtDNA copy number decreased in ovarian tissue （P<0.01）， ROS expression increased， MDA levels rose， while SOD and GSH-Px activities obviously decreased （P<0.05， P<0.01）， mRNA and protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM were obviously downregulated （P<0.05， P<0.01）. After treatment， compared with the model group， body weight and ovarian index obviously recovered in rats administered various doses of YJZYT （P<0.05）， serum E₂ and AMH levels increased， while FSH and LH levels obviously decreased （P<0.05， P<0.01）， ovarian tissue ATP content and mtDNA copy number were up-regulated， ROS and MDA levels decreased， and antioxidant enzymes SOD and GSH-Px activity obviously increased （P<0.05， P<0.01）， Gene and protein expression levels related to the SIRT1/PGC-1α /NRF1/TFAM signaling pathway were obviously up-regulated compared to the model group （P<0.05， P<0.01）， HE staining revealed that ovarian structure gradually recovered to integrity in all treatment groups， with a obviously increase in the number of primordial and growing follicles （P<0.05， P<0.01）. Granulosa cells were neatly arranged， indicating marked improvement in ovarian function. ConclusionYJZYT may improve ovarian function and follicular development in rats with diminished ovarian reserve by activating the SIRT1/PGC-1α signaling pathway， promoting mitochondrial biogenesis， enhancing mitochondrial function， and alleviating oxidative stress damage.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

Aim To investigate the promotive effects and mechanisms of the combined use of brucine(Bru)and lumbrokinase(LK),active ingredient derived from Longma formula,in promoting chondrocyte proliferation via the Wnt/β-catenin signaling pathway.Methods The extracted primary rat chondrocytes were divided in-to the following groups:Control group,Bru,LK alone group,and Bro+LK combination group.The optimal drug concentration and intervention time were deter-mined using CCK-8 assay,followed by cell proliferation validation through EdU and phalloidin staining.The expression levels of collagen Ⅱ,aggrecan and SRY-re-lated high-mobility group box gene 9(SOX9)in chon-drocytes following intervention with the combination of Bru and LK were detected by Western blotting.Addi-tionally,the regulatory effects of these proteins on the Wnt/β-catenin signaling pathway were also investiga-ted.Results The optimal combination concentration of Longma formula active ingredients(Bru 0.025 mg·L-1+LK 5 mg·L-1)significantly enhanced chondro-cyte viability compared to control,Bru,or LK alone at 48 h.This combination increased the S-phase ratio,promoted the aggregation of intracellular actin fila-ments,and upregulated the expression of collagen Ⅱ and aggrecan.Furthermore,it activated the Wnt/β-catenin pathway,leading to increased SOX9 expres-sion.Conclusions The optimal combination of Bru and LK(Bru 0.025 mg·L-1+LK 5 mg·L-1)de-rived from Longma formula significantly maintains chondrocyte phenotype and promotes cellular prolifera-tion through the activation of the Wnt/β-catenin signa-ling pathway,which subsequently upregulates the downstream target SOX9.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.
Big Data ; Humans ; Virus Diseases/virology* ; Artificial Intelligence

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: Coronavirus disease 2019 (COVID-19) can result in fatigue and post-exertional malaise; however, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exacerbates lower urinary tract symptoms (LUTS) is unclear. This study investigated the association between prenatal SARS-CoV-2 infection and postpartum LUTS. METHODS: A multicenter, retrospective cohort study was conducted at two tertiary hospitals in China from November 1, 2022, to November 1, 2023. Participants were classified into infected and uninfected groups based on SARS-CoV-2 antigen results. LUTS prevalence and severity were assessed using self-reported symptoms and the Incontinence Impact Questionnaire-Short Form (IIQ-7). Pelvic floor muscle activity was measured using electromyography following the Glazer protocol. Group comparisons were performed to evaluate the association of SARS-CoV-2 infection with LUTS and electromyography parameters, with stratified analyses conducted using SPSS version 26.0. RESULTS: Among 3,652 participants (681 infected, 2,971 uninfected), no significant differences in LUTS prevalence or IIQ-7 scores were observed. However, SARS-CoV-2 infection was an independent factor influencing the electromyographic activity of the pelvic floor muscles (mean tonic contraction amplitudes), regardless of delivery mode ( P = 0.001). CONCLUSION Prenatal SARS-CoV-2 infection was not significantly associated with an increased risk of postpartum LUTS but independently altered pelvic floor muscle electromyographic activity, suggesting potential neuromuscular effects.
Humans ; Female ; COVID-19/epidemiology* ; Retrospective Studies ; Adult ; Pregnancy ; Lower Urinary Tract Symptoms/virology* ; Postpartum Period ; Pregnancy Complications, Infectious/virology* ; China/epidemiology* ; Electromyography ; SARS-CoV-2/physiology* ; Pelvic Floor/physiopathology* ; Prevalence

Objective:To detect the levels of sex hormones and insulin in follicular fluid(FF)and the expression level of phosphatase and tensin homolog deleted on chromosome ten(PTEN)in granulosa cells in the infertile patients with polycystic ovary syndrome(PCOS),and to preliminarily explain the correlations between the insulin level and the expression level of PTEN mRNA.Methods:Seventy infertile patients were selected as the subjects and divided into PCOS group and control group(tubal obstruction or infertility due to male factors)according to infertility factors.All patients received in vitro fertilization-embryo transfer(IVF-ET)treatment.FF and ovarian granulosa cells were collected on the day of ovulation.The expression levels of PTEN mRNA in ovarian granulosa cells of the patients in two groups were detected by real-time fluorescence quantitative PCR(RT-qPCR)method.The levels of sex hormone and insulin in FF were measured by electrochemiluminescence.The correlations of the PTEN mRNA expression level in ovarian granulosa cells and testosterone(T)in FF with the level of insulin in FF were analyzed by Spearman correlation analysis method.Results:There were no significant differences in age,infertility years,body mass index(BMI),basic sex hormone,total dose of gonadotropin(Gn)and days of ovulation induction in two groups(P＞0.05).Compared with control group,the anti-Mullerian hormone(AMH)and antral follicle counting(AFC)of the patients in PCOS group were significantly increased(P＜0.05).The RT-qPCR results showed that the PTEN mRNA expression level in ovarian granulosa cells of the patients in the PCOS group was higher than that in control group(P＜0.001).The electrochemiluminescence results showed that the levels of T and insulin in FF of the patients in PCOS group were higher than those in control group(P＜0.05),whereas the estrogen and progesterone levels were lower than those in control group(P＜0.05).The Spearman correlation analysis showed that that T level in FF was positively correlated with the insulin level of the patients in PCOS group(r=0.577,P＜0.001),and the PTEN mRNA expression level in ovarian granulosa cells was positively correlated with the insulin levels in FF(r=0.616,P＜0.001);in control group,there was no correlation between T level and insulin level in FF(r=0.266,P=0.123),and there was no correlation between the expression level of PTEN mRNA in granulosa cells and the insulin level in FF in control group(r=-0.214,P=0.216).Conclusion:The high expression of PTEN in granulosa cells of the infertile patients with PCOS may be related to the local hyperinsulin level in the ovary,and PTEN participates in the occurrence and development of PCOS.

Chest low-dose computed tomography (LDCT) is a widely utilized modality for lung cancer screening and follow-up in high-risk populations, owing to its low radiation dose. However, the diagnostic accuracy of LDCT is significantly constrained by inherent limitations, including elevated image noise and reduced contrast resolution. The potential for deep learning technologies to address these challenges through data-driven LDCT image denoising approaches has been demonstrated. In this review, the advantages and limitations of deep learning models were introduced, including supervised, unsupervised, and self-supervised learning. The potential and challenges of these models in clinical applications were analyzed, thereby providing a reference for subsequent research and clinical practice.