Biology subjects

NAWN, D.

Publications and source records attributed to NAWN, D..

3 recordsLinked to original sources

bioRxiv2025

Development of Severity Index for Oral Epithelial Dysplasia Using Fuzzy Group Decision Making Algorithm

BackgroundOral epithelial dysplasia (OED) grading suffers from several levels of uncertainties and imprecision. An index is preferred in this context to improve reliability and reduce subjectivity in diagnostic decision making. In this study, a fuzzy logic-based disease severity index (SI) is formulated considering standard histopathological features used in OED grading. MethodsOral onco-pathologists were asked to independently provide weights of different features, according to their clinical significance in the context of dysplasia. Aggregated weight of each feature was calculated from individual assessment of different onco-pathologists by a fuzzy logic-based group decision making algorithm. Confidence levels of experts were also included to improve robustness of the method. SI was generated by integrating abnormality score of each feature with its weight. Abnormality degree of each feature was expressed in linguistic terms by onco-pathologists which were subsequently represented by a triangular fuzzy number. Fuzzy membership function was used as it can capture the ambiguity of experts opinion regarding abnormality of individual feature. Finally, defuzzification was used to get a crisp index from weighted sum of all features. ResultSI was found to be statistically different (p<0.01) for different grades of dysplasia i.e mild, moderate and severe with added advantage of stratifying each grade in low and high subcategory. ConclusionKey contribution of our work is that we have developed a fuzzy logic-based group consensus process regarding weights of histopathological features for OED grading. Present methodology of developing SI can be applied to other medical decision-making problems as well. HighlightsO_LIA severity index is proposed to improve reproducibility of oral epithelial dysplasia grading. C_LIO_LIClinical significance of each histopathological and cytopathological feature in the context of dysplasia is reflected by its weight. C_LIO_LIA fuzzy logic-based group decision making algorithm is used to reduce subjectivity of features weights. C_LIO_LIConfidence level of oral onco-pathologists are given due importance in derivation of aggregated weight of each feature. C_LIO_LIAbnormality score of each feature is evaluated in fuzzy scale to capture clinicians ambiguity. C_LIO_LIPresent methodology may be useful for developing indices of other diseases. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/633806v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@5a5e28org.highwire.dtl.DTLVardef@dba3a9org.highwire.dtl.DTLVardef@1d5cc7corg.highwire.dtl.DTLVardef@16404b5_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

cancer biology↗

bioRxiv2025

Proximal relationships of moonlighting Proteins in Escherichia coli: a mathematical genomic perspective

Moonlighting proteins in Escherichia coli (E.coli) perform multiple independent functions without altering their primary amino acid sequence, challenging the "one gene-one enzyme" hypothesis. Bacterial proteins serve various functions, including host cell adhesion, extracellular matrix interaction, and immune modulation, while also supporting essential physiological processes within the bacteria. Identifying these proteins in pathogens and tracking their genetic changes is crucial for understanding bacterial survival and virulence. A quantitative understanding of these proteins is pivotal as it enables the identification of specific patterns and relationships between amino acid composition, protein stability, and functional versatility. This study quantitatively analyzes fifty E. coli moonlighting proteins, focusing on their structural and functional features. Key findings include variability in amino acid composition, with alanine predominating, and a preference for non-polar residues, which may enhance protein stability. Quantitative features analyses identified seven distinct proximal sets, reflecting the proteins spatial arrangements of amino acids, structural diversity, and functional roles in processes such as metabolism, stress response, and gene regulation. These results deepen our understanding of the multifunctionality of E. coli moonlighting proteins, indicating their adaptability and implications for bacterial survival and pathogenicity.

genomics↗

bioRxiv2024

Methuselah Proteins in Longevity: Unraveling Their Impact Through Mathematical Genomics

This study provides a quantitative and comprehensive analysis of 18 Methuselah (mth) protein variants from fruit flies, focusing on their evolutionary relationships, structural features, and functional roles in aging and longevity. Phylogenetic analysis identified two major clades of mth proteins, with the first clade indicating conserved functions across Drosophila species and the second clade reflecting gene duplication and diversification. The study found five distinct functional subclasses of mth proteins through amino acid frequency and poly-string analyses, linked to their structural diversity and role in longevity. Structural topology and post-translational modifications reveal similarities with G-protein-coupled receptors (GPCRs), suggesting that mth proteins are crucial for signal transduction and cellular health. Variability in propeptide cleavage sites and intrinsic protein disorder further highlight adaptive roles in signaling. The findings underscore the importance of a quantitative and comprehensive approach to studying Methuselah genes, offering insights into their functional versatility and evolutionary dynamics. This enhanced quantitative understanding contributes to advancing research on aging and longevity.

genomics↗