Biology subjects

Pande, P.

Publications and source records attributed to Pande, P..

3 recordsLinked to original sources

bioRxiv2026

Contributions of human-caused climate change and individual emitters to global coral bleaching

Coral bleaching is among the most infamous climate impacts. Yet the extent of bleaching due to human-caused climate change, as opposed to natural El Nino variability, and the contributions of individual countries and carbon majors (fossil fuel and cement producers) remains unquantified. Here, we leverage coral monitoring globally across 4,479 sites from 1985-2024 to link specific emitters to marine heat stress and bleaching. For events with >10% of corals bleached at a site, we find that 99% (95% CI: 88-100%) were attributable to human-caused climate change. Even during major El Ninos, 97-100% of bleaching events were attributable to human-caused climate change and the extent of damage increases over time from 23% of sites bleached (95% CI: 3-35%) during 1998 to 71% of sites (95% CI: 37-85%) during 2023-2024. Emissions of the United States, the largest historical emitter, contributed to 51% (95% CI: 39-65%) of bleaching events. Emissions linked to Chevron, Saudi Aramco, Gazprom, and ExxonMobil each contributed to 14% (95% CI: 11-19%) of bleaching events -- roughly double the contribution of the 39 countries of the Alliance for Small Island States. It is virtually certain emissions of China, the United States, and Indonesia caused bleaching in their coastal waters. Strong inequalities exist where countries with high socioeconomic dependence on coral reefs experienced 54% of bleaching yet contributed only 5% to bleaching. As global warming rapidly nears levels catastrophic for warm-water corals, our results show the massive contribution from anthropogenic emissions to historical coral beaching and help fill an important evidentiary gap on accountability for non-economic loss and damage from climate change.

ecology↗

bioRxiv2023

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By fine-tuning the final two layers of the neural network at a lower learning rate of the TrailMap model, we demonstrate an improved recall and an occasionally improved adjusted F1- score within our test dataset over using the originally trained TrailMap model. Availability and implementation: The software and data are freely available at https://github.com/pnnl/brain_ohsu and https://data.pnl.gov/group/204/nodes/dataset/35673, respectively.

neuroscience↗

bioRxiv2017

Comparison of Small Gut and Whole Gut Microbiota of First-Degree Relatives with Adult Patients with Celiac Disease and Controls

Recent studies on celiac disease (CeD) have shown the role of gut microbiota alterations in CeD pathogenesis. Whether this alteration in the microbial community is the cause or effect of the disease is not well understood, especially in adult onset of disease. The first-degree relatives (FDRs) of CeD patients may provide an opportunity to study gut microbiome in pre-disease state as FDRs are genetically susceptible to CeD. By using 16S rRNA gene sequencing, we observed between the disease condition (CeD), pre-disease (FDR) and control subjects. However, differences were observed at the level of amplicon sequence variant (ASV), suggesting alterations in specific taxa between pre-diseases and diseased condition. Duodenal biopsies showed higher differences in ASVs compared to faecal samples indicating larger disruption of microbiota at disease site. Increased abundance of specific Helicobacter ASVs were observed in duodenum of CeD when compared to FDR (p < 0.01). In case of fecal samples CeD microbiome and Actinomyces. In addition, predicted functional metagenome showed reduced ability of gluten that ecosystem level diversity measures (except in the duodenum) were not significantly different is characterized by reduced abundance of beneficial taxa such as Akkermansia, Ruminococcus degradation by CeD faecal microbiota in comparison to FDRs and controls.

microbiology↗