Biology subjects

Shinde, N.

Publications and source records attributed to Shinde, N..

3 recordsLinked to original sources

bioRxiv2026

Hornbill abundance and habitat correlates in Kali Tiger Reserve, Western Ghats, India-Insights from collaborative monitoring

1.The future of species, particularly large-bodied birds, under climate threats, is increasingly unclear. Protected areas (PAs) can mitigate the impacts of global change, but are not completely immune. This makes it imperative to monitor populations even inside PAs. In the forests of the Western Ghats, three hornbill species are found--Malabar Grey Hornbill, Malabar Pied Hornbill and Great Hornbill. Kali Tiger Reserve, of Karnataka state, India, is known for its healthy hornbill populations, yet few systematic surveys have attempted to estimate their abundance, distributions and habitat affiliations. In this study, we documented the distributions of the three hornbills, estimated the density of Malabar Grey Hornbills and assessed correlates of hornbill encounter rates within the reserve. Malabar Grey Hornbills were the most abundant and widely distributed, found in all ranges of the reserve. Gund, Kadra and Phansoli had the most detections of Malabar Pied and Great Hornbills. Encounter rates of Malabar Grey Hornbill were positively correlated with food-tree stem density, those of Malabar Pied Hornbill negatively correlated with basal area, while those of Great Hornbill not significantly associated with any variable. Malabar Grey Hornbills had a density of 5.1 per km2 (mean flock size = 1.2). While encounter rates of Malabar Pied and Great Hornbills were low, these numbers track the breeding season, when vocal activity is low and females are inside nests. This survey represents a partnership between researchers and the Karnataka forest department, aimed towards inculcating the collaborative spirit of research and monitoring.

ecology↗

bioRxiv2026

Comparative Transcriptomic Analysis of ATRA-Resistant and ATRA-Sensitive APL Cell Lines Identifies LncRNA Biomarkers Associated with Drug Resistance

Acute promyelocytic leukemia is a distinct subtype of acute myeloid leukemia characterized by the t(15;17) translocation, leading to the PML (Promyelocytic leukemia protein)-RARA (Retinoic Acid Receptor Alpha) fusion protein. Although PML-RARA fusion is common, there are 20 more fusion events also reported in APL. All -trans retinoic acid (ATRA) is a standard drug for APL, leading to significant improvement in patient outcomes; nevertheless, a small fraction of patients still experience relapse, and some patients exhibit resistance to the drug. Long non-coding RNAs (LncRNAs) are recognized as promising biomarkers for cancer diagnosis, prognosis, and treatment response. In this study, we used ATRA-Resistant (AP1060) and ATRA -Sensitive (NB4), both treated and untreated cell line transcriptomic data retrieved from the NCBI Gene Expression Omnibus(GEO) database to perform transcriptomic analysis with bioinformatic tools. We utilized the LncRAnalyzer pipeline to predict the lncRNAs, followed by differential expression analysis using DESeq2. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct lncRNA co-expression modules associated with ATRA resistance. BEDTools is used to identify cis-acting target genes of lncRNAs.LncRNA -miRNA sponging identified by miRanda algorithm. The identified miRNAs reveal their significant role in APL and other leukemia subtypes. The results of the study show that the identified lncRNAs from the miRNA-LncRNA network are promising biomarkers for ATRA resistance.

cancer biology↗

bioRxiv2025

Estrogen Signaling During Abrupt Involution Leads to Long-Term Metabolic Dysfunction Similar to Estrogen Receptor Negative Breast Cancer

Epidemiological data links lack of breastfeeding with increased risk of breast cancer. Breast tissue undergoes remodeling to pre-pregnancy state after birth through involution. Long-term breastfeeding leads to gradual involution (GI). Lack of breastfeeding leads to abrupt involution (AI). While estrogen impacts repopulation of adipocytes, AI causes several precancerous changes in the mouse mammary gland. The impact of AI on adipocyte repopulation and metabolism is yet to be elucidated. ObjectivesTo investigate effects of AI on mammary gland metabolism and its potential link to breast cancer. MethodsAt partum (day 0), FVB/n dams were randomized to AI or GI and standardized to 6 pups. AI mice had pups removed on day 7 postpartum to mimic short-term breastfeeding. GI mice had 3 pups each were removed on day 28 and 31 postpartum to mimic gradual weaning. Mammary glands were harvested on day 28, 56, and 120 postpartum. Subset of AI mice had long-term sustained release tamoxifen placed subscapular on day 8 postpartum. Metabolic changes were assessed using: 1) transcriptional; 2) functional; 3) oxidative stress; and 4) metabolites analysis. ResultsDay 28 GI glands sustains/continues milk synthesis pathways impacting metabolic comparison with day28 AI glands. Day 28 AI when compared to day 56 GI showed upregulation of estrogen signaling, neutrophil degranulation, glucose metabolism, RNA synthesis, and down regulation of adipogenesis and glycolysis. At day 120, AI glands had downregulation of oxidative phosphorylation and upregulation of mitochondria dysfunction similar to pregnancy associated estrogen receptor negative breast cancer. Tamoxifen treatment of AI dams showed metabolic pathways and estrogen signaling similar to that of GI glands on day 28. ConclusionEarly metabolic phenotypes in AI and GI glands may be caused by differences in adipocyte repopulation related to estrogen signaling. Long-term metabolic effects of AI lead to similar metabolic effects found in breast cancer.

cancer biology↗