Broccoli () leaves exhibit significant antidiabetic potential in alloxan-induced diabetic rats: the putative role of ABC vacuolar transporter for accumulation of Quercetin and Kaempferol.

Background: The global prevalence of diabetes among adults over 18 years of age is expected to increase from 10.5% to 12.2% (between 2021 and 2045).

Diversity and functional traits based indigenous rhizosphere associated phosphate solubilizing bacteria for sustainable production of rice.

Introduction: Rice, particularly Basmati rice, holds significant global importance as a staple food. The indiscriminate use of phosphate-based fertilizers during rice production has led to high residual levels of these chemicals in soil, impacting soil health and fertility. This study aimed to address this challenge by investigating the potential of phosphate solubilizing bacteria (PSB) in improving soil fertility and boosting the growth of Basmati rice.

In silico designing and characterization of outer membrane protein (OmpC) gene from Salmonella enterica and its expression in Nicotiana tabacum for developing a plant-based vaccine against salmonellosis.

Salmonella, a gram-negative bacteria, is the leading cause of foodborne illness globally. Two serovars of Salmonella, S. enteritidis and S.

Efficacy of Platelet-Rich Plasma Intra-articular Injections in Hip and Knee Osteoarthritis.

Osteoarthritis (OA) is a chronic degenerative disorder that causes significant pain and functional limitations. Platelet-rich plasma (PRP) therapy has gained considerable attention in recent years in the treatment of musculoskeletal injuries. In this narrative review, we aim to investigate the role of intra-articular PRP injections in the treatment of knee and hip OA.

Missing Values in Longitudinal Proteome Dynamics Studies: Making a Case for Data Multiple Imputation.

Temporal proteomics data sets are often confounded by the challenges of missing values. These missing data points, in a time-series context, can lead to fluctuations in measurements or the omission of critical events, thus hindering the ability to fully comprehend the underlying biomedical processes. We introduce a Data Multiple Imputation (DMI) pipeline designed to address this challenge in temporal data set turnover rate quantifications, enabling robust downstream analysis to gain novel discoveries.