Recently, male reproductive health has attracted extensive attention, with the adverse effects of circadian disruption on male fertility gradually gaining recognition. However, the mechanism by which circadian disruption leads to damage to male reproductive system remains unclear. In this review, we first summarized the dual regulatory roles of circadian clock genes on the male reproductive system: (1) circadian regulation of testosterone synthesis via the hypothalamic-pituitary-testicular (HPT) and hypothalamic-pituitary-adrenal (HPA) axes; (2) non-circadian regulation of spermatogenesis. Next, we further listed the possible mechanisms by which circadian disruption impairs male fertility, including interference with the oscillatory function of the reproductive system, i.e., synchronization of the HPT axis, crosstalk between the HPT axis and the HPA axis, as well as direct damage to germ cells by disturbing the non-oscillatory function of the reproductive system. Future research using spatiotemporal omics, epigenomic assays, and neural circuit mapping in studying the male reproductive system may provide new clues to systematically unravel the mechanisms by which circadian disruption affects male reproductive system through circadian clock genes.
Male ; Humans ; Animals ; Circadian Clocks/physiology* ; Hypothalamo-Hypophyseal System/physiology* ; Circadian Rhythm/genetics* ; Spermatogenesis/physiology* ; Pituitary-Adrenal System/physiology* ; Testis/physiology* ; Testosterone/biosynthesis* ; CLOCK Proteins ; Infertility, Male/physiopathology*

A 7-year-old girl was admitted to the hospital with rapidly progressive vision loss. Since 1 year of age, she had exhibited developmental delay accompanied by visual impairment and neutropenia. Combined with genetic testing and molecular pathogenicity analysis, she was diagnosed with Cohen syndrome (CS) caused by compound heterozygous variants in VPS13B (c.6940+1G>T and c.2911C>T). The c.6940+1G>T variant resulted in exon 38 skipping, leading to a frameshift and premature termination. Reverse transcription quantitative polymerase chain reaction revealed significantly reduced VPS13B gene expression (P<0.05). Bioinformatic analysis suggested that both variants likely produce truncated proteins. This case highlights that integrating clinical features with molecular pathogenicity assessment (DNA, RNA, and protein analysis) can improve early diagnostic accuracy for CS.
Humans ; Female ; Child ; Vesicular Transport Proteins/genetics* ; Developmental Disabilities/etiology* ; Muscle Hypotonia/etiology* ; Myopia/etiology* ; Heterozygote ; Intellectual Disability/etiology* ; Microcephaly/etiology* ; Obesity/genetics* ; Growth Disorders/etiology* ; Retinal Degeneration/genetics* ; Psychomotor Disorders/genetics* ; Fingers/abnormalities*

OBJECTIVE: To investigate possible associations between physical function assessment scales, such as Short Physical Performance Battery (SPPB) and Berg Balance Scale (BBS), with all-cause mortality in acute decompensated heart failure (ADHF) patients. METHODS: A total of 108 ADHF patients were analyzed from October 2020 to October 2022, and followed up to May 2023. The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis, while for SPPB and BBS, univariate Cox regression analysis was followed by receiver operating characteristic curves, in which the area under the curve represented their predictive accuracy for all-cause mortality. Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores. Optimal cut-off value for BBS was then identified using restricted cubic spline plots, and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test. The clinical utility of BBS was measured using decision curve analysis. RESULTS: For baseline characteristics, age, female, blood urea nitrogen, as well as statins, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, or angiotensin receptor-neprilysin inhibitors, were predictive for all-cause mortality for ADHF patients. With respect to SPPB and BBS, higher scores were associated with lower all-cause mortality rates for both assessments; similar area under the curves were measured for both (0.774 for SPPB and 0.776 for BBS). Furthermore, BBS ≤ 36.5 was associated with significantly higher mortality, which was still applicable even adjusting for confounding factors; BBS was also found to have great clinical utility under decision curve analysis. CONCLUSIONS BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients, as well as prognosticate on all-cause mortality. Moreover, prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.

OBJECTIVE: This study aimed to identify high-risk areas for type 2 diabetes mellitus (T2DM) mortality to provide relevant evidence for interventions in emerging economies. METHODS: Empirical Bayesian Kriging and a discrete Poisson space-time scan statistic were applied to identify the spatiotemporal clusters of T2DM mortality. The relationships between economic factors, air pollutants, and the mortality risk of T2DM were assessed using regression analysis and the Poisson Log-linear Model. RESULTS: A coastal district in East Guangdong, China, had the highest risk (Relative Risk [RR] = 4.58, P < 0.01), followed by the 10 coastal districts/counties in West Guangdong, China (RR = 2.88, P < 0.01). The coastal county in the Pearl River Delta, China (RR = 2.24, P < 0.01), had the third-highest risk. The remaining risk areas were two coastal counties in East Guangdong, 16 districts/counties in the Pearl River Delta, and two counties in North Guangdong, China. Mortality due to T2DM was associated with gross domestic product per capita (GDP per capita). In pilot assessments, T2DM mortality was significantly associated with carbon monoxide. CONCLUSION High mortality from T2DM occurred in the coastal areas of East and West Guangdong, especially where the economy was progressing towards the upper middle-income level.
Diabetes Mellitus, Type 2/epidemiology* ; China/epidemiology* ; Humans ; Risk Factors ; Spatio-Temporal Analysis ; Air Pollutants/analysis* ; Socioeconomic Factors ; Bayes Theorem ; Female ; Male ; Middle Aged

Objective To observe the value of transesophageal echocardiography(TEE)for guiding left atrial appendage closure(LAAC)with LAmbre occluder.Methods Data of 40 non-valvular atrial fibrillation(NVAF)patients who underwent LA AC with LAmbre occluder were retrospectively analyzed.CT angiography(CTA)before treatment,TEE and digital subtraction angiography(DSA)findings during LAAC were comparatively observed,and the correlations of the anchor area diameter and left atrial appendage opening diameter measured with the above three as well as occluder size were analyzed,and TEE and DSA for evaluating peri-device leak(PDL)were compared.Results LAAC were successfully performed with LAmbre occlude in all 40 cases.The diameter of the fixed umbrella was positively correlated with anchor area diameter measured with CTA,TEE and DSA(r=0.79,0.82,0.91,all P＜0.01),of occlusion umbrella was positively correlated with left atrial appendage opening diameter measured with CTA,TEE and DSA(r=0.56,0.89,0.86,all P＜0.01).Immediately after the release of occluder in LAAC,PDL occurred in 16 cases and were detected with both TEE and DSA,while in the rest 24 cases no PDL was found with neither TEE nor DSA.Conclusion TEE had comparable value to DSA for guiding LAAC using LAmbre occluder.

Objective To establish a scoring model for predicting the prognosis and drug sensitivity of colorectal cancer(CRC)based on the expression of disulfidptosis-related genes by bioinformatics analyses combined with the validation with CRC patient-derived organoids(CRC-PDOs).Methods NMF(non-negative Matrix Factorization)algorithm,Cox and LASSO regression analyses were used to identify disulfidptosis-related genes with predictive value for CRC prognosis,and disulfidptosis-related risk scoring formula was constructed.The differential genes and enrichment pathways among different clusters were analyzed by GO(Gene Ontology)and KEGG(Kyoto Encyclopedia of Genes and Genomes).The sensitivity of the high/low-risk clusters of CRC patients to chemotherapy drugs was predicted using the GDSC database and validated using CRC-PDOs.Results The results of NMF algorithm showed that CRC patients could be grouped into two clusters based on the disulfidptosis-related genes.COX regression analysis demonstrated that LRPPRC and SLC7A11 were the only two genes with significance to predict the prognosis of CRC patients(P=0.047,0.033).Low expression of SLC7A11 or high expression of LRPPRC in tumors of CRC patients was significantly correlated with overall survival(OS)(P=0.004,0.003).Based on LASSO regression analysis,the mortality risk scoring formula for disulfidptosis was as follows:Risk score=LRPPRC×(-0.670 5)+SLC7A11×0.311 2,and the GSE161158 dataset could be re-grouped into high-risk and low-risk clusters accordingly.There were 125 differentially expressed genes(DEGs)between the two clusters.According to the GO and KEGG results,the up-regulated genes in high-risk cluster were mainly enriched in immune regulation,such as leukocyte chemotaxis,granulocyte migration and toll-like receptor binding.Low-risk cluster was characterized by pathways associated with sulfide metabolism,such as sulfur compound transmembrane transporter activity.Based on the GDSC database,the expression level of SLC7A11 and LRPPRC could predict chemotherapy drug sensitivity.As a representative,the efficacy of chemotherapy drug(irinotecan)on inhibiting the growth of CRC-PDOs was shown to be linearly correlated with the relative gene expression levels of SLC7A11 and LRPPRC in CRC tissues of patients(P=0.007,0.040).Conclusion According to the results based on the bioinformatics analyses and drug sensitivity testing on CRC-PDOs,disulfidptosis risk score could predict the prognosis and drug sensitivity of CRC patients,with potential clinical application prospect.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Atherosclerosis caused by disorders of lipid metabolism is the main pathological basis of atherosclerotic cardiovascular disease.Statins are the cornerstone of lipid-modulating therapy for this type of disease,but in practice there are still some patients with suboptimal lipid management.Proprotein convertase subtilisin/kexin type 9(PCSK9)inhibitors have been gradually applied as a new class of lipid-modulating drugs for the treatment in patients with this type of disease,and recent studies have shown that in addition to regulating lipid metabolism,PCSK9 inhibitors also have potential anti-inflammatory and anti-platelet activation effects.This article sorts out the multiple pharmacological mechanisms of action of PCSK9 inhibitors and the current status of clinical research of PCSK9 inhibitors.Besides,it discusses the factors that may affect the efficacy of PCSK9 inhibitors,in order to provide a reference for the safe and rational medication of PCSK9 inhibitors.

Objective To elucidate the clinical significance of high expression levels of endonuclease meiosis 1(EME1)in the prognosis of hepatocellular carcinoma(HCC).Methods The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases were used to screen and analyze differential gene expression between HCC and non-tumor tissues.A retrospective collection of liver tissue samples from 80 HCC patients who underwent hepatectomy in the Fifth Medical Center of Chinese PLA General Hospital between January 2010 and December 2014 was performed.Immunohistochemistry analysis was employed to detect the EME1 expression levels.Survival analysis was then conducted to assess the impact of EME1 expression on 5-year postoperative survival rate of HCC patients.Additionally,gene enrichment analysis was applied to predict the function of EME1 in HCC.Results A total of 371 HCC tissue samples and 50 non-tumor liver tissue samples from TCGA database were analyzed,revealing significantly higher EME1 expression in HCC tissues.Microarray analysis of 107 samples within the GEO database(70 HCC tissues and 37 non-tumor tissues)confirmed that EME1 mRNA expression was markedly elevated in HCC tissues compared with non-tumor tissues(P<0.05).The 5-year overall survival(OS)rate was notably lower in high EME1 expression group than that in low expression group(44.1%vs.53.0%,P<0.05).Semi-quantitative immunohistochemistry analysis demonstrated that patients with high EME1 expression had a significantly lower OS rate than those with low EME1 expression(32.8%vs.45.0%,P<0.05).Multivariate COX regression analysis identified that high EME1 expression(HR=2.234,95%CI 1.073-4.649,P=0.032)and advanced China liver caner(CNLC)staging(HR=4.317,95%CI 1.799-10.359,P=0.001)were independent risk factors for the 5-year OS of post-operation patients with HCC.Conclusion Elevated EME1 expression in HCC tissues correlates with an adverse prognosis of HCC and suggests that EME1 could serve as a potential therapeutic target for HCC.