Reproduction is characterized by a series of massive renovations at molecular, cellular, and tissue levels. Recent studies have strongly tended to reveal the involvement of basic molecular pathways such as autophagy, a highly conserved eukaryotic cellular recycling, during reproductive processes. This review comprehensively describes the current knowledge, updated to September 2022, of autophagy contribution during reproductive processes in males including spermatogenesis, sperm motility and viability, and male sex hormones and females including germ cells and oocytes viability, ovulation, implantation, fertilization, and female sex hormones. Furthermore, the consequences of disruption in autophagic flux on the reproductive disorders including oligospermia, azoospermia, asthenozoospermia, teratozoospermia, globozoospermia, premature ovarian insufficiency, polycystic ovarian syndrome, endometriosis, and other disorders related to infertility are discussed as well.Abbreviations: AKT/protein kinase B: AKT serine/threonine kinase; AMPK: AMP-activated protein kinase; ATG: autophagy related; E_2: estrogen; EDs: endocrine disruptors; ER: endoplasmic reticulum; FSH: follicle stimulating hormone; FOX: forkhead box; GCs: granulosa cells; HIF: hypoxia inducible factor; IVF: in vitro fertilization; IVM: in vitro maturation; LCs: Leydig cells; LDs: lipid droplets; LH: luteinizing hormone; LRWD1: leucine rich repeats and WD repeat domain containing 1; MAP1LC3: microtubule associated protein 1 light chain 3; MAPK: mitogen-activated protein kinase; MTOR: mechanistic target of rapamycin kinase; NFKB/NF-kB: nuclear factor kappa B; P₄: progesterone; PCOS: polycystic ovarian syndrome; PDLIM1: PDZ and LIM domain 1; PI3K: phosphoinositide 3-kinase; PtdIns3P: phosphatidylinositol-3-phosphate; PtdIns3K: class III phosphatidylinositol 3-kinase; POI: premature ovarian insufficiency; ROS: reactive oxygen species; SCs: Sertoli cells; SQSTM1/p62: sequestosome 1; TSGA10: testis specific 10; TST: testosterone; VCP: vasolin containing protein.

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Introduction: A systematic review and meta-analysis of clinical trials were undertaken to evaluate the effect of diacerein intake on cardiometabolic profiles in patients with type 2 diabetes mellitus (T2DM). Methods: Electronic databases such as PubMed, EMBASE, Scopus, Web of Science, Google Scholar, and Cochrane Central Register of Controlled Trials were searched from inception to 31 July 2019. Statistical heterogeneity was evaluated using Cochran’s Q test and I-square (I²) statistic. Data were pooled using random-effects models and weighted mean difference (WMD). Results: From 1,733 citations, seven clinical trials were eligible for inclusion and meta-analysis. A significant reduction in hemoglobin A1c (HbA1c) (WMD -0.73; 95%CI -1.25 to -0.21; P= 0.006; I2= 72.2%) and body mass index (BMI) (WMD -0.55; 95%CI -1.03 to -0.07; P= 0.026; I²= 9.5%) was identified. However, no significant effect of diacerein intake was identified on fasting blood sugar (FBS) (WMD -9.00; 95%CI -22.57 to 4.57; P= 0.194; I2= 60.5%), homeostatic model assessment for insulin resistance (HOMA-IR) (WMD 0.39; 95%CI -0.95 to 1.73; P= 0.569; I²= 2.2%), body weight (WMD - 0.54; 95%CI -1.10 to 0.02; P= 0.059), triglycerides (WMD -0.56; 95%CI -24.16 to 23.03; P= 0.963; I²= 0.0%), total-cholesterol (WMD -0.21; 95%CI -12.19 to 11.78; P= 0.973; I²= 0.0%), HDL-cholesterol (WMD -0.96; 95%CI -2.85 to 0.93; P= 0.321; I²= 0.0%), and LDL-cholesterol levels (WMD -0.09; 95%CI -8.43 to 8.25; P= 0.983; I²= 37.8%). Conclusion: Diacerein intake may reduce HbA1c and BMI; however, no evidence of the effect was observed for FBS, HOMA-IR, body weight, triglycerides, total cholesterol, HDL-cholesterol or LDLcholesterol.