Macroautophagy/autophagy, is widely recognized for its crucial role in enabling cell survival and maintaining cellular energy homeostasis during starvation or energy stress. Its regulation is intricately linked to cellular energy status. In this review, covering yeast, mammals, and plants, we aim to provide a comprehensive overview of the understanding of the roles and mechanisms of carbon- or glucose-deprivation related autophagy, showing how cells effectively respond to such challenges for survival. Further investigation is needed to determine the specific degraded substrates by autophagy during glucose or energy deprivation and the diverse roles and mechanisms during varying durations of energy starvation.Abbreviations: ADP: adenosine diphosphate; AMP: adenosine monophosphate; AMPK: AMP-activated protein kinase; ATG: autophagy related; ATP: adenosine triphosphate; ER: endoplasmic reticulum; ESCRT: endosomal sorting complex required for transport; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; GD: glucose deprivation; GFP: green fluorescent protein; GTPases: guanosine triphosphatases; HK2: hexokinase 2; K phaffii: Komagataella phaffii; LD: lipid droplet; MAP1LC3/LC3: microtubule-associated protein1 light chain 3; MAPK: mitogen-activated protein kinase; Mec1: mitosis entry checkpoint 1; MTOR: mechanistic target of rapamycin kinase; NAD (+): nicotinamide adenine dinucleotide; OGD: oxygen and glucose deprivation; PAS: phagophore assembly site; PCD: programmed cell death; PtdIns3K: class III phosphatidylinositol 3-kinase; PtdIns3P: phosphatidylinositol-3-phosphate; ROS: reactive oxygen species; S. cerevisiae: Saccharomyces cerevisiae; SIRT1: sirtuin 1; Snf1: sucrose non-fermenting 1; STK11/LKB1: serine/threonine kinase 11; TFEB: transcription factor EB; TORC1: target of rapamycin complex 1; ULK1: unc-51 like kinase 1; Vps27: vacuolar protein sorting 27; Vps4: vacuolar protein sorting 4.

Mec1 is a DNA damage sensor, which performs an essential role in the DNA damage response pathway and glucose starvation-induced autophagy. However, the functions of Mec1 in autophagy remain unclear. In response to glucose starvation, Mec1 forms puncta, which are recruited to mitochondria through the adaptor protein Ggc1. Here, we show that Mec1 puncta also contact the phagophore assembly site (PAS) via direct binding with Atg13. Functional analysis of the Atg13–Mec1 interaction revealed two previously unrecognized protein regions, the M ec1- B inding R egion (MBR) on Atg13 and the A tg13- B inding R egion (ABR) on Mec1, which mediate their mutual association under glucose starvation conditions. Disruption of the MBR or ABR impairs the recruitment of Mec1 puncta and Atg13 to the PAS, consequently blocking glucose starvation-induced autophagy. Additionally, the MBR and ABR regions are also crucial for DNA damage-induced autophagy. We thus propose that Mec1 regulates glucose starvation-induced autophagy by controlling Atg13 recruitment to the PAS.

Endothelial dysfunction is a pivotal factor in the pathogenesis of atherosclerosis, driving plaque formation, inflammation, and thrombosis. This review synthesizes classical mechanisms and emerging perspectives on endothelial dysfunction, emphasizing its role in atherogenesis. Traditional contributors, including lifestyle factors, lipid dysregulation, shear stress, and nitric oxide (NO) deficiency, are discussed alongside novel insights from single-cell RNA sequencing, metabolomics, and intercellular communication. scRNA-seq has unveiled endothelial cell (EC) heterogeneity and endothelial-to-mesenchymal transition (EndMT) as critical contributors to plaque instability. Metabolites such as trimethylamine N-oxide (TMAO) and homocysteine derivatives exacerbate endothelial injury, while gut microbiome interactions further modulate disease progression. Exosome-mediated crosstalk between ECs, immune cells, and vascular smooth muscle cells (VSMCs) highlights new pathways in vascular inflammation and remodeling. Current pharmacotherapies, such as lipid-lowering and anti-inflammatory drugs, improve endothelial function, and emerging strategies like nanotechnology and exosome-based therapies show promise as well. Integrating classical and novel approaches could enhance our understanding of endothelial biology and lead to targeted therapies, addressing atherosclerosis-related diseases.

Body mass index (BMI) and blood biomarkers are not enough to predict cardiovascular disease risk. Apolipoprotein B was identified to be associated with cardiovascular disease (CVD) progression. The Dual-energy X-ray Absorption (DXA) results could be considered as a predictor for cardiovascular disease in a more refined way based on fat distribution. The prediction of CVD risk by simple indicators still cannot meet clinical needs. The association of ApoB with specific fat depot features remains to be explored to better co-predict cardiovascular disease risk. An amount of 5997 adults from National Health and Nutrition Examination Survey (NHANES) were enrolled. Their demographic information, baseline clinical condition, blood examination, and DXA physical examination data were collected. Multivariate regression was used to assess the correlation between ApoB and site-specific fat characteristics through different adjusted models. Smooth curve fittings and threshold analysis were used to discover the turning points with 95% confidence intervals. ApoB is positively correlated with arms percent fat, legs percent fat, trunk percent fat, android percent fat, gynoid percent fat, arm circumference and waist circumference after adjustment with covariates for age, gender, race, hypertension, diabetes, hyperlipidemia, coronary heart disease, smoking status and vigorous work activity. The smooth curve fitting and threshold analysis also showed that depot-specific fat had lower turning points of ApoB in both males and females within the normal reference range of ApoB. Meanwhile, females have a lower increase in ApoB per 1% total percent fat and android percent fat than males before the turning points, while females have a higher growth of ApoB per 1% gynoid percent fat than males. The combined specific fat-depot DXA and ApoB analysis could indicate the risk of CVD in advance of lipid biomarkers or DXA alone.