Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc., contribute to widespread crop losses globally. On the other hand, biotic stresses, such as those caused by insects, fungi, and weeds, further exacerbate these challenges. These stressors can hinder plant systems at various levels, including molecular, cellular, and development processes. To overcome these challenges, multi-omics computational approaches offer a significant tool for characterizing the plant’s biomolecular pool, which is crucial for maintaining homeostasis and signaling response to environmental changes. Integrating multiple layers of omics data, such as proteomics, metabolomics, ionomics, interactomics, and phenomics, simplifies the study of plant resistance mechanisms. This comprehensive approach enables the development of regulatory networks and pathway maps, identifying potential targets for improving resistance through genetic engineering or breeding strategies. This review highlights the valuable insights from integrating multi-omics approaches to unravel plant stress responses to both biotic and abiotic factors. By decoding gene regulation and transcriptional networks, these techniques reveal critical mechanisms underlying stress tolerance. Furthermore, the role of secondary metabolites in bio-based products in enhancing plant stress mitigation is discussed. Genome editing tools offer promising strategies for improving plant resilience, as evidenced by successful case studies combating various stressors. On the whole, this review extensively discusses an advanced multi-omics approach that aids in understanding the molecular basis of resistance and developing novel strategies to improve crops’ or organisms’ resilience to abiotic and biotic stresses.

Stein-Leventhal syndrome, often known as polycystic ovarian syndrome (PCOS), is a syndrome that affects women's reproductive health. PCOS is one of the most common endocrine and metabolic disorders in women of reproductive age. The etiology of PCOS remains unknown mainly, and the estimation of PCOS burden in a specific geographical location will impact disease control strategies. Hence, this study estimated the pooled prevalence of PCOS in Indian women. Databases such as PubMed, CINHAL, Scopus, and Google Scholar were thoroughly searched. Only those published Indian studies that reported the prevalence of PCOS from 2010 to 2021 and had at least one of the following diagnostic PCOS criteria were included in the systematic review: the National Institutes of Health (NIH), Rotterdam's criteria, or/and Androgen Excess Society (AES). MetaXL version 5.3 software was used for data analysis. The risk of bias was assessed using modified Joanna Briggs Institute criteria for cross-sectional studies. Out of 17132 articles, 11 articles were selected for systematic review and meta-analysis. The pooled prevalence of PCOS was 11.33(7.69-15.59) using the random effect. The proportion of Hirsute using the Ferriman-Gallwey score was highly variable, ranging from 1.6% to 37.9% (n=6). The prevalence rate of PCOS is high among Indian women. The pooled prevalence of PCOS was close to 10% using Rotterdam's criteria and AES criteria, while it was 5.8% using NIH criteria. The study's overall finding emphasizes the need for more acceptable and uniform diagnostic criteria for screening PCOS. At the same time, policy-makers should consider giving more importance to PCOS in their effort to control non-communicable diseases.