Biology subjects

Glass, D.

Publications and source records attributed to Glass, D..

6 recordsLinked to original sources

bioRxiv2026

Superposition eyes of diurnal and nocturnal hawkmoths are imperfect spheres and lack acute zones.

Superposition compound eyes improve sensitivity by pooling light from multiple facets and are widespread among nocturnal insects, including moths and beetles. Optical theory predicts that superposition eyes must be nearly spherical to form coherent images and therefore lack highly pronounced acute zones with high spatial resolution. To examine this, we imaged eyes of six hawkmoths (Sphingidae) spanning diurnal and nocturnal activity with high-resolution microcomputed tomography. Our automated pipeline created detailed eye maps quantifying morphological parameters. We measured local eye curvature (radial distance), interommatidial angle ({Delta}{varphi}), facet size and crystalline cone skewness (tilt of cone axes relative to the local surface normal). All species show more curvature in the dorso-ventral plane with flattening in the antero-posterior plane. However, their eyes still retain near-spherical curvature globally, with diurnal species showing greater distortion. For facet parameters, spatial acuity is generally highest (lowest {Delta}{varphi}) near the eye center and decreases gradually toward the periphery. However, overall variation in spatial acuity is low and these eyes lack distinct acute zones. Facet size gradually changes from center to periphery, increasing in some species and decreasing in the others. Cone skewness is present in all six species (0{degrees}-10{degrees}), but in two diurnal species of hummingbird hawkmoths it increases markedly in the posterior region (15{degrees}-30{degrees}) possibly compensating for regional eye flatness. This paper provides foundational data of ommatidial and eye shape measurements and advances our assumptions about how superposition eyes function.

animal behavior and cognition↗

bioRxiv2026

Myeloma and therapy reshape the bone marrow niche to durably constrain immune reconstitution and vaccine responsiveness

Infections are the most common cause of non-relapse mortality in multiple myeloma (MM), but the basis of persistent immune dysfunction is obscured by patient heterogeneity and complex treatment regimens, including autologous stem cell transplant (ASCT). We performed longitudinal multi-omic profiling of matched bone marrow and peripheral blood from MM patients across diagnosis, induction, ASCT, and recovery. We found the tumor imposes a compartment-specific immune program where the marrow exhibits metabolic and inflammatory changes that bias hematopoiesis and alter cytotoxic effector programs not mirrored in blood. Adaptive immune reconstitution is impaired up to two years post-ASCT. Half of patients fail to mount IgG responses to high-dose non-adjuvanted influenza vaccine, a defect overcome by the lipid nanoparticle (LNP) adjuvanted COVID mRNA vaccine, which elicited responses in all patients, supporting adjuvanted influenza vaccine strategies in MM. Together these findings define how myeloma and its treatment durably reshape immunity from the marrow outward. HighlightsO_LIMultiple Myeloma marrow and blood show opposing metabolic and inflammatory states C_LIO_LIInduction therapy selects durable myeloma plasma-cell transcriptional states C_LIO_LIB cell and follicular helper T deficits blunt antigen responses after transplant C_LIO_LICOVID-19 vaccination builds immune memory with variable responses to flu vaccination C_LI eTOCMultiple myeloma and its treatment leave a lasting imprint on the bone marrow niche. By profiling bone marrow and blood longitudinally at diagnosis, through induction, autologous transplant, and recovery, we show that marrow-local metabolic and inflammatory constraints persist and help explain why influenza vaccination often fails while mRNA vaccination succeeds.

cancer biology↗

bioRxiv2023

The developmental gene disco regulates diel-niche evolution in adult moths

AbstractAnimals shift activity periods to reduce predation, minimize competition, or exploit new resources, and this can drive sensory system evolution. But adaptive mechanisms underlying niche- shifts are poorly understood, and model organisms are often too distantly related to reveal the genetic drivers. To address this, we examined expression patterns between two closely related silk moths that have undergone temporal niche divergence. We found 200-700 differentially expressed genes, including day upregulation in eye development and visual processing genes, and night upregulation of antennal and olfactory brain development genes. Further, clusters of circadian, sensory, and brain development genes co-expressed with diel-activity. In both species, eight genes showed expression significantly correlated to diel activity, and are involved in vision, olfaction, brain development, neural plasticity, energy utilization, and cellular maintenance. We repeatedly recovered disco, a zinc- finger transcription factor involved in antennal development, circadian activity, and optic lobe brain development in flies. While disco mutants have circadian arrhythmia, most studies attribute this to improper clock neuron development, not adult circadian maintenance. Comparing predicted 3D protein structure across moth and fly genetic models revealed disco likely retained developmental function with a conserved zinc finger domain, but gained functional zinc finger domains absent in D. melanogaster. These regions have several mutations between nocturnal and diurnal species that co- occur with higher levels of predicted phosphorylation sites. With robust circadian expression, functional nocturnal and diurnal mutations, and structural and sequence conservation, we hypothesize that disco may be a master regulator contributing to diel-activity diversification in adult moths. SignificanceInsect diel-activity patterns are diverse, yet the underlying evolutionary processes are poorly understood. Light environment powerfully entrains circadian rhythms and drives diel-niche and sensory evolution. To investigate its impact, we compared gene expression in closely related day- and night-active wild silk moths, with otherwise similar ecologies. Expression patterns that varied with diel activity included genes linked to eye development, neural plasticity and cellular maintenance. Notably, disco, which encodes a zinc-finger transcription factor involved in pupal Drosophila optic lobe and antennal development, shows robust adult circadian mRNA cycling in moth heads, is highly conserved in moths, and has additional zinc-finger domains with specific nocturnal and diurnal mutations. We hypothesize that disco may contribute to diversification of adult diel-activity patterns in moths.

evolutionary biology↗

bioRxiv2022

A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA and ATAC sequencing

As part of the Human Cell Atlas initiative, we generated transcriptomic (scRNA-seq; 86,708 cells) and regulatory (scATAC-seq; 59,118 cells) profiles of the normal postmenopausal ovary and fallopian tube (FT) at single-cell resolution. In the FT, 22 cell clusters integrated into 11 cell types, including ciliated and secretory epithelial cells, while the ovary had 17 distinct cell clusters defining 6 major cell types. The dominant cell type in both the postmenopausal ovary and FT was stromal cells, which expressed several genes associated with aging. The fimbrial end of the FT had a significant number and variety of immune cells and active communication with the ovary; the ovary contained mostly stromal cells but few immune cells. The epithelial cells of the normal FT expressed multiple ovarian cancer risk-associated genes (CCDC170, RND3, TACC2, STK33, and ADGB). By integrating paired single-cell transcriptomics and chromatin accessibility data we found that the regulatory landscape of the fimbriae was markedly different from the isthmus and ampulla. Intriguingly, several cell types in the FT had comparable gene expression but different transcriptional regulations. Our single-cell transcriptional and regulatory maps allowed us to disentangle the complex cellular makeup of the postmenopausal FT and ovary and will contribute to a better understanding of gynecologic diseases in menopause.

genomics↗

bioRxiv2019

A practical computerized decision support system for predicting the severity of Alzheimer’s disease of an individual

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on the group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heavily on cognitive and functional assessments (CFA). In this study, we developed a computational framework using a suite of machine learning tools for identifying key markers in predicting the severity of Alzheimers disease (AD) from a large set of biological and clinical measures. Six machine learning approaches, namely Kernel Ridge Regression (KRR), Support Vector Regression (SVR), and k-Nearest Neighbor (kNNreg) for regression and Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (kNNclass) for classification, were used for the development of predictive models. We demonstrated high predictive power of CFA. Predictive performance of models incorporating CFA was shown to be consistently higher accuracy than those based solely on biomarker modalities. We found that KRR and SVM were the best performing regression and classification methods respectively. The optimal SVM performance was observed for a set of four CFA test scores (FAQ, ADAS13, MoCA, MMSE) with multi-class classification accuracy of 83.0%, 95%CI = (72.1%, 93.8%) while the best performance of the KRR model was reported with combined CFA and MRI neuroimaging data, i.e., R2 = 0.874, 95%CI = (0.827, 0.922). Given the high predictive power of CFA and their widespread use in clinical practice, we then designed a data-driven and self-adaptive computerized clinical decision support system (CDSS) prototype for evaluating the severity of AD of an individual on a continuous spectrum. The system implemented an automated computational approach for data pre-processing, modelling, and validation and used exclusively the scores of selected cognitive measures as data entries. Taken together, we have developed an objective and practical CDSS to aid AD diagnosis.

neuroscience↗

bioRxiv2017

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, United Kingdom, and United States, comprising a total of 52,506 phenotyped individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs at a genome-wide level of significance in KITLG, DOCK8, and a broad region of 9q32. In a bivariate analysis combining the nevus results with those from a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level of significance. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis via genes we can show to be expressed under control of the MITF melanocytic cell lineage regulator.

genetics↗