Biology subjects

Evans, J. A.

Publications and source records attributed to Evans, J. A..

4 recordsLinked to original sources

bioRxiv2025

Melanopsin contributes to circadian photic responses in mice in a sex-dependent manner

Proper entrainment of the bodys circadian rhythms to the environment is critical to human health. Light is one of the strongest cues driving circadian photoentrainment of the central circadian pacemaker, the suprachiasmatic nucleus (SCN), via projections from the melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs). Circadian research has historically centered males, and recent work has revealed multiple sex-differences in circadian circuitry and function, indicating that our understanding of this system in females is severely limited. Moreover, while recent studies have investigated the role of hormonal modulation of light responses, the additional possibility that ipRGC inputs may also be sex-dependent has not been directly tested. Here, we report that not only do ipRGCs in female mice show higher levels of melanopsin expression, but that melanopsin also plays a larger role in shaping circadian photic responses in females compared to males. Collectively, these results define a new retinal source for sex-dependent differences in circadian behavior.

neuroscience↗

bioRxiv2025

Alterations of the composition and spatial organization of the microenvironment following non-dysplastic Barrett's esophagus through progression to cancer

Barretts esophagus (BE), a metaplastic condition that is the only known precursor for esophageal adenocarcinoma (EAC), is relatively common, but progression to cancer is infrequent. BE is inflamed but the contribution of the immune system to the carcinogenic process is unknown. To this end, we contrasted non-dysplastic metaplasia of BE patients, captured when they did not progress (non-progressors), did subsequently, but had not yet progressed (pre-progressors) or had already progressed to EAC (progressors). Using spatial multiplexed 56-protein analysis, serial laser capture microdissection (LCM) RNAseq and shallow whole genome sequencing, we identified prooncogenic immune neighbourhoods and dysregulated immune cell populations predictive of subsequent progression to EAC. Indeed, spatial analysis revealed that M1 macrophages, regulatory natural killer (NK) cells, neutrophils and altered ratios of intraepithelial CD4+ and CD8+ lymphocytes typify tumor microenvironmental (TME) changes associated with cancer initiation. Spatially derived cell-to-cell interactions revealed progression-specific immune cell interaction signatures predominantly involving M1 macrophages NK cells and plasma cells. Furthermore, LCM RNAseq analysis identified gene expression hot signatures enriched in pre-progression and progression samples. Notably, we also observed a correlation between immune cells and copy number alterations in progressor metaplasia. By exposing coordinated changes in the immune cell landscape in patients at high risk of developing EAC, this multi-omic dataset provides novel diagnostic and therapeutic opportunities

cancer biology↗

bioRxiv2023

Limited Diffusion of Scientific Knowledge Forecasts Collapse

Market bubbles emerge when asset prices are driven unsustainably higher than asset values and shifts in belief burst them. We demonstrate the same phenomenon for biomedical knowledge when promising research receives inflated attention. We predict deflationary events by developing a diffusion index that captures whether research areas have been amplified within social and scientific bubbles or have diffused and become evaluated more broadly. We illustrate our diffusion approach contrasting the trajectories of cardiac stem cell research and cancer immunotherapy. We then trace the diffusion of unique 28,504 subfields in biomedicine comprising nearly 1.9M papers and more than 80M citations and demonstrate that limited diffusion of biomedical knowledge anticipates abrupt decreases in popularity. Our analysis emphasizes that restricted diffusion, implying a socio-epistemic bubble, leads to dramatic collapses in relevance and attention accorded to scientific knowledge.

scientific communication and education↗

bioRxiv2020

NERO: A Biomedical Named-entity (Recognition) Ontology with a Large, Annotated Corpus Reveals Meaningful Associations Through Text Embedding

Machine reading is essential for unlocking valuable knowledge contained in the millions of existing biomedical documents. Over the last two decades 1,2, the most dramatic advances in machine-reading have followed in the wake of critical corpus development3. Large, well-annotated corpora have been associated with punctuated advances in machine reading methodology and automated knowledge extraction systems in the same way that ImageNet 4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named-entity analysis tool for biomedicine: (a) a new, Named-Entity Recognition Ontology (NERO) developed specifically for describing entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named-entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named-entity recognition automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.

systems biology↗