CLCA: Maximum Common Molecular Substructure Queries within the MetRxn Database

The challenge of automatically identifying the preserved molecular moieties in a chemical reaction is referred to as the atom mapping problem. Reaction atom maps provide the ability to locate the fate of individual atoms across an entire metabolic network. Atom maps are used to track atoms in isotope labeling experiments for metabolic flux elucidation, trace novel biosynthetic routes to a target compound, and contrast entire pathways for structural homology. However, rapid computation of the reaction atom mappings remains elusive despite significant research. We present a novel substructure search algorithm, canonical labeling for clique approximation (CLCA), with polynomial run-time complexity to quickly generate atom maps for all the reactions present in MetRxn. CLCA uses number theory (i.e., prime factorization) to generate canonical labels or unique IDs and identify a bijection between the vertices (atoms) of two distinct molecular graphs. CLCA utilizes molecular graphs generated by combining atomistic information on reactions and metabolites from 112 metabolic models and 8 metabolic databases. CLCA offers improvements in run time, accuracy, and memory utilization over existing heuristic and combinatorial maximum common substructure (MCS) search algorithms. We provide detailed examples on the various advantages as well as failure modes of CLCA over existing algorithms

A Systematic Literature Review on the Transition to Circular Business Models for Small and Medium-Sized Enterprises (SMEs)

The transition of a business to a circular business model (CBM) calls for significant and ongoing shifts in different business management models and strategies. However, there is a lack of research focused on the technological, financial, societal, and institutional influences on the CBM transition in small and/or medium-sized enterprises (SMEs). To address this gap, our study develops a theoretical framework for the transition towards CBM. We conducted a systematic literature review with the objective of determining the relationships among technological, financial, societal, and institutional influences for CBMs. Following this, we then established a conceptual framework that comprises these four key influences for a transition plan in the context of an innovative business model with a focus on the value proposition, value creation, and value delivery. An illustrative case example of the manufacturing industry for the transition plan to CBM was presented as well. The proposed framework is designed to lead the shift towards circular economy-oriented business models that aim to promote sustainability in business. In addition, we uncovered several potential avenues for further investigation. We expect the framework towards both contribute to the expansion of the existing body of research in the field and provide business practitioners with guidelines on the CBMs’ transition for SMEs

Molecular insight into amyloid oligomer destabilizing mechanism of flavonoid derivative 2-(4′ benzyloxyphenyl)-3-hydroxy-chromen-4-one through docking and molecular dynamics simulations

<p>Aggregation of amyloid peptide (Aβ) has been shown to be directly related to progression of Alzheimer’s disease (AD). Aβ is neurotoxic and its deposition and aggregation ultimately lead to cell death. In our previous work, we reported flavonoid derivative (compound 1) showing promising result in transgenic AD model of Drosophila. Compound 1 showed prevention of Aβ-induced neurotoxicity and neuroprotective efficacy in Drosophila system. However, mechanism of action of compound 1 and its effect on the amyloid is not known. We therefore performed molecular docking and atomistic, explicit-solvent molecular dynamics simulations to investigate the process of Aβ interaction, inhibition, and destabilizing mechanism. Results showed different preferred binding sites of compound 1 and good affinity toward the target. Through the course of 35 ns molecular dynamics simulation, conformations_5 of compound 1 intercalates into the hydrophobic core near the salt bridge and showed major structural changes as compared to other conformations. Compound 1 showed interference with the salt bridge and thus reducing the inter strand hydrogen bound network. This minimizes the side chain interaction between the chains A–B leading to disorder in oligomer. Contact map analysis of amino acid residues between chains A and B also showed lesser interaction with adjacent amino acids in the presence of compound 1 (conformations_5). The study provides an insight into how compound 1 interferes and disorders the Aβ peptide. These findings will further help to design better inhibitors for aggregation of the amyloid oligomer.</p

Data_Sheet_1_Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India.docx

India is home to the highest global number of women and children suffering from anemia, with one in every two women impacted. India's current strategy for targeting areas with a high anemia burden is based on district-level averages, yet this fails to capture the substantial small area variation in micro-geographical (small area) units such as villages. We conducted statistical and econometric analyses to quantify the extent of small area variation in the three grades of anemia (severe, moderate, and mild) among women and children across 36 states/union territories and 707 districts of India. We utilized data from the fifth round of the National Family Health Survey conducted in 2019–21. The final analytic sample for analyses was 183,883 children aged 6–59 months and 690,153 women aged 15–49 years. The primary outcome variable for the analysis was the three anemia grades among women and children. We adopted a three-level and four-level logistic regression model to compute variance partitioning of anemia among women and children. We also computed precision-weighted prevalence estimates of women and childhood anemia across 707 districts and within-district, between-cluster variation using standard deviation (SD). For severe anemia among women, small area (villages or urban blocks) account for highest share (46.1%; Var: 0.494; SE: 0.150) in total variation followed by states (39.4%; Var: 0.422; SE: 0.134) and districts (12.8%; Var: 0.156; SE: 0.012). Similarly, clusters account for the highest share in the variation in severe (61.3%; Var: 0.899; SE: 0.069) and moderate (46.4%: Var: 0.398; SE: 0.011) anemia among children. For mild and moderate anemia among women, however, states were the highest source of variation. Additionally, we found a high and positive correlation between mean prevalence and inter-cluster SD of moderate and severe anemia among women and children. In contrast, the correlation was weaker for mild anemia among women (r = 0.61) and children (0.66). In this analysis, we are positing the critical importance of small area variation within districts when designing strategies for targeting high burden areas for anemia interventions.</p