Objectives The aim of this review was to assess the risk of cardiovascular disease (CVD) events associated with shift work and determine if there is a dose–response relationship in this association. Method Electronic databases (PubMed, Scopus, and Web of Science) were searched for cohort or case–control control study designs in any population, reporting exposure to shift work as the main contributing factor to estimate CVD risk. For each study, adjusted relative risk (RR) ratios and 95% confidence intervals (CI) were extracted, and used to calculate the pooled RR using random-effect models. Meta-regression analysis was conducted to explore potential heterogeneity sources. Potential non-linear dose–response relationships were examined using fractional polynomial models. Results We included 21 studies with a total of 173 010 unique participants. The majority of the studies were ranked low-to-moderate risk of bias. The risk of any CVD event was 17% higher among shift workers than day workers. The risk of coronary heart disease (CHD) morbidity was 26% higher (1.26, 95% CI 1.10–1.43, I 2 = 48.0%). Sub-group analysis showed an almost 20% higher risk of CVD and CHD mortality among shift workers than those who did not work shifts (1.22, 95% CI 1.09–1.37, I 2 = 0% and 1.18, 95% CI 1.06–1.32 I 2 =0%; respectively). After the first five years of shift work, there was a 7.1% increase in risk of CVD events for every additional five years of exposure (95% CI 1.05–1.10). Heterogeneity of the pooled effect size (ES) estimates was high (I 2 =67%), and meta-regression analysis showed that sample size explained 7.7% of this. Conclusions The association between shift work and CVD risk is non-linear and seems to appear only after the first five years of exposure. As shift work remains crucial for meeting production and service demands across many industries, policies and initiatives are needed to reduce shift workers’ CVD risk.

Background. Shift work is characterized by employees working outside the standard hours of 7:00 am to 6:00 pm. Because shift work includes night work, the normal sleep–wake cycle (circadian rhythm) is disrupted, with potential consequences for shift workers’ physical and mental health. Objectives. To assess the pooled effects of shift work on mental health and to evaluate whether these differ in men and women. Search Methods. We searched PubMed, Scopus, and Web of Science databases for peer-reviewed or government reports published up to August 2018 Selection Criteria. To be included, studies had to be longitudinal or case–control studies of shift work exposure associated with adverse mental health outcomes. For subanalyses, we grouped these outcomes as anxiety symptoms, depressive symptoms, or general poor mental health symptoms. Data Collection and Analysis. We followed the Meta-Analysis of Observational Studies in Epidemiology Group guidelines. We extracted adjusted risk estimates for each study to calculate pooled effect sizes (ESs) using random effect models and metaregression analysis to explore sources of heterogeneity. Main Results. We included 7 longitudinal studies, with 28 431 unique participants. Shift work was associated with increased overall risk of adverse mental health outcomes combined (ES = 1.28; 95% confidence interval [CI] = 1.02, 1.62; I² = 70.6%) and specifically for depressive symptoms (ES = 1.33; 95% CI = 1.02, 1.74; I² = 31.5%). Gender differences explained more than 90% of heterogeneity, with female shift workers more likely to experience depressive symptoms than female non–shift workers (odds ratio = 1.73; 95% CI = 1.39, 2.14). Authors’ Conclusions. To our knowledge, this is the first meta-analysis to investigate the pooled effects of shift work on the risk of poor mental health, including subanalyses by type of poor mental health and gender. Shift workers, particularly women, are at increased risk for poor mental health, particularly depressive symptoms. Public Health Implications. Depression accounts for 4.3% of the global burden of disease and incidence, with mental disorders worldwide predicted to cost US $16.3 million by 2030. With 1 in 5 people in the United States and Europe doing shift work, and the increased risk of poor mental health among shift workers, shift work industries are a priority context for reducing this burden. Workplace health promotion programs and policies are needed to minimize shift workers’ risk of poor mental health.

Background: The equilibrium between gut microbiota (GM) and the host plays a pivotal role in maintaining overall health, influencing various physiological and metabolic functions. Emerging research suggests that exercise modulates the abundance and functionality of gut bacteria, yet the comprehensive effects on GM diversity remain to be synthesized. Objectives and Design: The study aims to quantitatively examine the effect of exercise on the diversity of gut microbiota of adults using a systemic review and meta-analysis approach. Methods: PubMed, Ebsco, Embase, Web of Science, Cochrane Central Register of Controlled Trials, the China National Knowledge Infrastructure, and Wanfang Data were searched from their inception to September 2023. Exercise intervention studies with a control group that describe and compare the composition of GM in adults, using 16S rRNA gene sequencing, were included in this meta-analysis. Results: A total of 25 studies were included in this meta-analysis with a total of 1044 participants. Based on a fixed-effects model [Chi² = 29.40, df = 20 (p = 0.08); I² = 32%], the pooled analysis showed that compared with the control group, exercise intervention can significantly increase the alpha diversity of adult GM, using the Shannon index as an example [WMD = 0.05, 95% CI (0.00, 0.09); Z = 1.99 (p = 0.05)]. In addition, exercise interventions were found to significantly alter GM, notably decreasing Bacteroidetes and increasing Firmicutes, indicating a shift in the Firmicutes/Bacteroidetes ratio. The subgroup analysis indicates that females and older adults appear to exhibit more significant changes in the Shannon Index and observed OTUs. Conclusions: Exercise may be a promising way to improve GM in adults. In particular, the Shannon index was significantly increased after exercise. Distinct responses in GM diversity to exercise interventions based on gender and age implicated that more research was needed.

Exercise is positively associated with higher microbial diversity, but there is limited information on exercise intensity's effect on gut microbiome composition and function in clinical populations. This study examines whether different intensities of exercise exert differential effects on gut microbiome composition and function in low active people with type 2 diabetes. This is a sub‐study of the Exercise for Type 2 Diabetes Study, a single centre, prospective, randomised controlled trial. Participants (n = 12) completed 8‐weeks of combined aerobic and resistance moderate intensity continuous training (C‐MICT) or combined aerobic and resistance high‐intensity interval training (C‐HIIT). Faecal samples were collected before and after intervention to measure gut microbiome composition and metabolic pathways (metagenome shotgun sequencing) and short‐chain fatty acids. Post‐exercise α‐diversity was different between groups as was the relative abundance of specific taxa was (p < .05). Post‐exercise relative abundance of Bifidobacterium, A. municiphila, and butyrate‐producers Lachnospira eligens, Enterococcus spp., and Clostridium Cluster IV were higher at lower exercise intensity. Other butyrate‐producers (from Eryspelothrichales and Oscillospirales), and methane producer Methanobrevibacter smithii were higher at higher exercise intensity. Pyruvate metabolism (ko00620),COG “Cell wall membrane envelope biogenesis” and “Unknown function” pathways were significantly different between groups and higher in C‐MICT post‐exercise. Differential abundance analysis on KO showed higher expression of Two‐component system in C‐HIIT. Transcription factors and “unknown metabolism” related pathways decreased in both groups. There were no significant between group changes in faecal short chain fatty acids. Exercise intensity had a distinct effect on gut microbiome abundance and metabolic function, without impacting short‐chain fatty acid output.Highlights Evidence of exercise effect on gut microbiome outcomes is limited to healthy and athletic populations In low active people with type 2 diabetes, different exercise intensities increased specific health promoting and butyrate producers species, and showed differentially abundant gut microbiome metabolic pathways. Further investigation is warranted, and if this supports the present findings, then specific exercise intensities may be promoted to target specific species and optimise gut health.

Background: The co-stimulatory B7 family members are cell-surface protein ligands, binding to receptors on lymphocytes to regulate immune responses. One of them is the inducible co-stimulatory molecule ligand (ICOS-L). This protein is expressed on professional antigen-presenting cells (APCs), including B cells, macrophages, and dendritic cells (DCs), but it can also be expressed by endothelial cells, lung epithelium and in tumour microenvironment cells. ICOS-L is important for memory and effector T cells during the specific humoral immune responses, but its role in cancer is not yet understood. Objective: To discuss the role of ICOS/ICOS-L in cancer, given importance of identifying selective targets for cancer treatment, and knowing the mechanism of immune evasion by tumour. Main findings: ICOS/ICOS-L signal has opposite effects on the T-cell response. ICOS-L is activated in several types of cancers to maintain immunosuppressive CD4+ T cell subsets, such as regulatory T cells (Tregs). ICOS-L over-expression is associated with tumour progression and poor overall survival. In colon cancer, activation of this co-stimulatory signal is associated with improved survival suggesting a dualistic effect of the ICOS/ICOs-L signal pathway. Interestingly, following anti-cancer vaccine or anti-CTLA-4 treatment, ICOS+ T cells increased significantly in both the CD4+ and CD8+ population and the ratio Teff/Treg increased in tumour microenvironment. This suggests a potential role of ICOS/ICOS-L in improving effectiveness of cancer therapy. Conclusion: ICOS/ICOS-L signal pathway has the potential to improve cancer treatment. However, studies in other models are needed to understand whether inhibition of ICOS expression or the blockage of its co-stimulation could be a potential therapeutic target or adjuvant treatment for immunotherapy.