An implantable cardiac monitor(ICM)is a subcutaneous electronic device for recording and remotely transmitting electrocardiographic events.New-generation ICM,like the Reveal LINQ,have extended arrhythmia monitoring duration and improved diagnostic yield through miniaturization,large storage capacity,and easy implantation.They provide comprehensive monitoring data for cardiovascular disease diagnosis and treatment,optimize individualized treatment plans,and enhance patient prognosis.In recent years,research on ICM in cardiovascular fields has deepened,and their clinical application scope has expanded.They show significant advantages and unique value and are widely used in early cardiovascular disease diagnosis and prognostic management.In the future,ICM are expected to play a bigger role in boosting diagnostic and prognostic capabilities for cardiovascular disease patients,offering stronger support for early disease detection,accurate diagnosis,and effective management.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

An implantable cardiac monitor(ICM)is a subcutaneous electronic device for recording and remotely transmitting electrocardiographic events.New-generation ICM,like the Reveal LINQ,have extended arrhythmia monitoring duration and improved diagnostic yield through miniaturization,large storage capacity,and easy implantation.They provide comprehensive monitoring data for cardiovascular disease diagnosis and treatment,optimize individualized treatment plans,and enhance patient prognosis.In recent years,research on ICM in cardiovascular fields has deepened,and their clinical application scope has expanded.They show significant advantages and unique value and are widely used in early cardiovascular disease diagnosis and prognostic management.In the future,ICM are expected to play a bigger role in boosting diagnostic and prognostic capabilities for cardiovascular disease patients,offering stronger support for early disease detection,accurate diagnosis,and effective management.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Aim To investigate the effects of rosavin on hepatocellular steatosis and its mechanism of action.Methods AML-12 and HepG2 cells were induced to undergo hepatocellular steatosis by free fatty acids(FFA),and the optimal inducing concentration was determined by oil red O staining and CCK-8 assay.The cell activity was detected by CCK-8 assay after ro-savin treatment,and the lipid droplet accumulation was observed by oil red O staining.The levels of triglycer-ide(TG),total cholesterol(TC),glutamic oxalacetic transaminase(AST),glutamic pyruvic transaminase(ALT),superoxide dismutase(SOD),glutathione per-oxidase(GSH-Px),and malondialdehyde(MDA)were detected by kits.The potential targets of rosavin in non-alcoholic fatty liver disease(NAFLD)were ana-lyzedby network pharmacology and molecular docking,and the expression of core candidate targets before and after the rosavin intervention was detected by real-time fluorescence quantitative PCR.Results Hepatocyte steatosis was induced by FFA,and the intervention of rosavin(25,50 μmol·L-1)reduced the number of intracellular lipid droplets in hepatocytes in a dose-de-pendent manner,also lowered the cellular levels of TG,TC,AST,ALT,elevated the levels of SOD and GSH-Px,and reduced the levels of MDA.Network pharma-cological analysis and molecular docking yielded five core candidate targets:NOS3,MAPK14,PPARG,TNF-α,and IGF-1,and real-time fluorescence quantitative PCR showed that the action of loxavir significantly re-duced the gene expression of TNF-α and PPARG in hepatocytes after FFA induction.Conclusions Rosa-vin can attenuate the inflammatory response,oxidative stress level,and lipid accumulation in hepatocytes by modulating TNF-α and PPARG,thereby ameliorating FFA-induced hepatocellular steatosis.

OBJECTIVE: Resveratrol (Res) is a promising anticancer drug against hepatocellular carcinoma (HCC), but whether its anti-HCC effects implicate mitophagy remains unclear. Therefore, we aimed to explore the specific role of Res in mitophagy and the related mechanisms during the treatment of HCC. METHODS: HepG2 cells and tumor-grafted nude mice were used to investigate the effects of low-, middle- and high-dose of Res on HCC progression and mitophagy in vitro and in vivo, respectively. A series of approaches including cell counting kit-8, flow cytometry, wound healing and transwell assays were used to evaluate tumor cell functions. Transmission electron microscopy, immunofluorescence and Western blotting were used to assess mitophagy. Mitochondrial oxygen consumption rate, reactive oxygen species and membrane potential were used to reflect mitochondrial function. After disrupting the expression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), miR-143-3p, and ribonucleoside reductase M2 (RRM2), the effects of the MALAT1/miR-143-3p/RRM2 axis on cell function and mitophagy under Res treatment were explored in vitro. Additionally, dual-luciferase reporter and chromatin immunoprecipitation were used to confirm interactions between target genes. RESULTS: Res significantly inhibited the proliferation and promoted apoptosis of HCC cells in vitro, while significantly suppressing tumor growth in a dose-dependent manner and inducing mitophagy and mitochondrial dysfunction in vivo. Interestingly, MALAT1 was highly expressed in HCC cells and its knockdown upregulated miR-143-3p expression in HCC cells, which subsequently inhibited RRM2 expression. Furthermore, in nude mice grafted with HCC tumors and treated with Res, the expression of MALAT1, miR-143-3p and RRM2 were altered significantly. In vitro data further supported the targeted binding relationships between MALAT1 and miR-143-3p and between miR-143-3p and RRM2. Therefore, a series of cell-based experiments were carried out to study the mechanism of the MALAT1/miR-143-3p/RRM2 axis involved in mitophagy and HCC; these experiments revealed that MALAT1 knockdown, miR-143-3p mimic and RRM silencing potentiated the antitumor effects of Res and its activation of mitophagy. CONCLUSION Res facilitated mitophagy in HCC and exerted anti-cancer effects by targeting the MALAT1/miR-143-3p/RRM2 axis. Please cite this article as: Feng CY, Cai CS, Shi XQ, Zhang ZJ, Su D, Qiu YQ. Resveratrol promotes mitophagy via the MALAT1/miR-143-3p/RRM2 axis and suppresses cancer progression in hepatocellular carcinoma. J Integr Med. 2025; 23(1): 79-91.
Humans ; MicroRNAs/genetics* ; Liver Neoplasms/metabolism* ; Carcinoma, Hepatocellular/metabolism* ; Mitophagy/drug effects* ; Resveratrol/pharmacology* ; Animals ; Mice, Nude ; RNA, Long Noncoding/genetics* ; Hep G2 Cells ; Mice ; Disease Progression ; Mice, Inbred BALB C

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

The development of novel point-to-point drugs targeting resistance mechanisms is a critical and popular research field; nevertheless, success remains challenging. Therefore, given the short survival time and heightened expectations of patients with advanced NSCLC, the design of various combination therapy strategies––integrating preclinical, clinical, and real-world evidence (such as radiotherapy, chemotherapy, targeted therapy, antibody–drug conjugates, oncolytic viruses, and cell therapy)––may be a wise and practical choice to address the disease. Resistance to immunotherapy involves almost all cell types in the body, primarily cancer cells and T cells involved in immune surveillance. As a result of space limitations, this article focuses on the progress and challenges of various combined strategies for directly eliminating cancer cells. We also emphasize the realignment of treatment goals, shifting from primarily focusing on eliminating cancer cells (via chemotherapy and radiotherapy) to fully utilizing immune regulation to overcome resistance to immune checkpoint inhibitors.