Chemical Carbonylation of Arginine in Peptides and Proteins.

The chemoselective incorporation of arginine carbonylation post-translational modification (PTM) within proteins represents an underexplored frontier. This is largely due to the poor nucleophilicity and resistance to chemical oxidation of arginine. Drawing inspiration from the metal catalyzed oxidation (MCO) processes of arginine, we introduce a chemical methodology aimed at generating glutamate-5-semialdehyde from arginine residues within peptides and proteins.

Integrated machine learning based groundwater quality prediction through groundwater quality index for drinking purposes in a semi-arid river basin of south India.

The main objective of this study is to predict and monitor groundwater quality through the use of modern Machine Learning (ML) techniques. By employing ML techniques, the research effectively evaluates groundwater quality to forecast its future trends. Five machine learning models Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), Extreme Gradient and Boosting (XGBoost) were used here to predict the water quality by assessing the physical and chemical parameters such as electrical conductivity (EC), hydrogen ion (pH) concentration, total dissolved solids (TDS), chemical parameters such as, sodium (Na), magnesium (Mg), calcium (Ca), potassium (K), bicarbonates (HCO), fluoride (F), sulphate (SO), chloride (Cl), and nitrate (NO) in 94 dug and bore wells from the semi-arid river basin (Arjunanadi) in Tamil Nadu, India.

Validation of pre-treatments for cost effective production of bioethanol from floral wastes.

The present study has focused on validating pre-treatment methods for cost effective production of bioethanol from discarded and otherwise waste flowers which are renewable, abundantly available and eco-friendly. Floral waste was collected from various dumpsites and banquet halls and subjected to physical, chemical and biological pre-treatments. Biological pre-treatment by enzymatic hydrolysis using crude cellulase enzyme (5%) yielded 39.

Oral health-related knowledge, attitude and practices among nurses: a hospital-based questionnaire survey from a tertiary healthcare setting in Faridabad, India.

Background: Nurses play an integral part in the comprehensive delivery of healthcare services and contribute significantly to the success of public health initiatives. The knowledge, attitude and practices of nurses in the domain of oral health influence their own oral hygiene as well as that of the community. Their impact on overall oral health of the community is due to the fact that they provide health education as the primary contact of patients and their family members.

Dynamic Mapping of the Methylproteome Using a Chemoenzymatic Approach.

Dynamic protein post-translational methylation is essential for cellular function, highlighted by the essential role of methylation in transcriptional regulation and its aberrant dysregulation in diseases, including cancer. This underscores the importance of cataloging the cellular methylproteome. However, comprehensive analysis of the methylproteome remains elusive due to limitations in current enrichment and analysis pipelines.