Biology subjects

Dave, N.

Publications and source records attributed to Dave, N..

9 recordsLinked to original sources

bioRxiv2026

A Systematic Review and Independent Benchmarking of Automated Nerve Morphometry Methods

Objective: To systematically review automated nerve morphometry tools and independently benchmark their performance on independent optic nerve datasets. Design: Systematic review and comparative benchmarking study. Controls: Benchmarking was performed using paraphenylenediamine-stained mouse (n = 85) and rat (n = 44) optic nerve images with manually annotated axon counts as ground truth. Methods: Published studies describing automated or semi-automated neural tissue morphometry tools were identified through systematic searches of PubMed, Embase, and Scopus through January 2026 following PRISMA guidelines. Data extraction covered 70 fields across tool capabilities, imaging modality, species, automation level, and validation approach. Eighteen eligible tools (8 deep learning [DL], 10 classical computer vision [CV]) were benchmarked on both mouse and rat independent datasets. Main Outcome Measures: Performance was assessed by mean absolute percentage error (MAPE), Pearson correlation, and median predicted-to-ground-truth ratio. Tools were ranked per image and compared using Friedman tests with Nemenyi post-hoc analysis. Results: Seventy-one studies met inclusion criteria, spanning from 1999 to 2026. Deep learning methods represented 38% (27/71) of studies, increasing from 0% before 2017 to over 55% of publications after 2020. Axon counting was the most common output (73%, 52/71), while only 35% (25/71) reported g-ratio. Among benchmarked tools, Marina (CV, 2010) achieved the lowest average MAPE (32.9%). The top five tools (MAPE ranging from 32.9 to 44.8%) included both CV and DL methods and were statistically indistinguishable by Friedman-Nemenyi analysis (p > 0.05). Performance varied substantially across datasets: AxonJ (CV) achieved the second best MAPE on rat images (27.7%) but the worst on mouse images (438.6%). Conclusions: No single tool demonstrated consistently superior performance across both datasets. Classical and deep learning approaches achieved comparable accuracy for axon counting. Tool selection should be guided by target species, tissue preparation protocol, and desired morphometric outputs. This systematic review and independent benchmarking study provide an evidence base for tool selection in optic nerve research.

bioengineering↗

bioRxiv2026

Comparison of Deep Learning Tools for Optic Nerve Axon Quantification Finds Limited Generalizability on Independent Validation

PurposeMachine learning approaches for automated quantification of optic nerve histology have emerged as potential tools for objective assessment of axonal injury in experimental glaucoma models. However, the generalizability of these models to independent datasets remains unclear. Guided by a scoping review of the literature, this study performed independent validation testing of publicly available models on a novel rat optic nerve dataset to assess their generalizability. MethodsWe conducted a scoping review following PRISMA-ScR guidelines. PubMed, EMBASE, Scopus, and Cochrane CENTRAL were searched from 2000 through 2025. Two reviewers independently screened records and extracted data on model characteristics and performance metrics. Additionally, we performed independent validation of three models (AxoNet, AxonDeepSeg, AxoNet 2.0) on a novel rat optic nerve dataset comprising 57 images with 9,514 manually annotated axons. Because AxonDeep is not publicly available, we instead evaluated AxonDeepSeg, a separate publicly available deep learning-based tool that, while not previously applied to optic nerve tissue, is widely used for nerve fiber segmentation. ResultsFrom 2,036 records, four manuscripts describing three deep learning models met inclusion criteria. Published correlation coefficients between model predictions and reference counts ranged from 0.959 to 0.99. On independent validation, performance was reduced: AxoNet 2.0 achieved the highest correlation (r = 0.89), followed by AxonDeepSeg (r = 0.86) and AxoNet (r = 0.79). Segmentation quality metrics revealed high precision (>0.94) but low recall (0.18 to 0.27), with Dice coefficients of 0.29 to 0.40, substantially below published benchmarks of 0.81. ConclusionsDeep learning models for optic nerve histology demonstrate strong within-study performance but show meaningful performance decrements when applied to independent datasets. The observed generalizability gap (correlations 0.07 to 0.182 points below published values) demonstrates the need for standardized validation datasets and multi-center testing before widespread adoption of these tools.

bioengineering↗

bioRxiv2025

NCK adaptor proteins regulate clathrin-coated pit dynamics and EGF-stimulated PI3K-Akt signaling

The epidermal growth factor (EGF) receptor (EGFR) promotes cell growth, proliferation, and survival. EGF binding to EGFR activates receptor kinase activity, leading to membrane recruitment of class IA phosphoinositide-3-kinase (PI3K), thus activating Akt signaling. Clathrin-coated pits (CCPs) are plasma membrane endocytic structures that are enriched in signaling intermediates and regulate in EGF-stimulated Akt activation. The mechanisms and impact of recruitment of certain signaling molecules within the PI3K-Akt pathway to CCPs remains poorly understood. Using total internal reflection fluorescence microscopy (TIRFM), we observed that the adaptor proteins Nck1 and Nck2 are enriched within CCPs and regulate early CCP formation and maturation. Nck1 and Nck2 each support EGF-stimulated Akt phosphorylation. Notably, EGF stimulation triggers Nck-dependent enrichment of PI3K within CCPs, and perturbation of Nck adaptors suppressed cell proliferation and survival. This study identifies novel functions for Nck adaptor proteins in EGFR-mediated recruitment of PI3K-Akt signals within CCPs, Akt activation, and cell physiology.

cell biology↗

bioRxiv2025

Electrochemical Paper Fluidic Device for Extended Real-time Cocaine Monitoring in Simulated Sweat

Cocaine and other illicit substances are known to excrete from the body into sweat, making sweat an advantageous matrix for non-invasive detection and monitoring of substance use and abuse. However, existing detection of illicit substances in sweat remain single-use technologies that arent suitable for real-time, continuous monitoring over the course of an entire day. Long-term, continuous detection is hampered by large, bulky instrumentation, limited sensor stability for multi-hour measurements, and fluidic systems not optimized for minute and variable sweat flow rates. We demonstrate the continuous detection of 0.5 mM cocaine in simulated sweat via a paper fluidic device over the course of 17 hours. Our sensing system uses a biosensor functionalized with a cocaine-binding aptamer and a miniaturized electrochemical potentiostat. Our fluidics are driven by evaporation flow at physiological sweat rates (0.3-0.5 {micro}L/min/cm2). Our development lays critical groundwork towards wearable, continuous detection of illicit substances in sweat.

biochemistry↗

bioRxiv2022

Dietary choline intake is necessary to prevent systems-wide organ pathology and reduce Alzheimers disease hallmarks

Evidence suggests that environmental factors may contribute to Alzheimers disease (AD). The B-like vitamin choline plays key roles in body- and brain-related functions. Choline produced endogenously by the phosphatidylethanolamine N-methyltransferase (PEMT) enzyme in the liver is not sufficient for adequate physiological functions, necessitating daily dietary intake. [~]90% of Americans dont reach the recommended daily choline intake. Thus, its imperative to determine whether dietary deficiency increases disease outcomes. Here, we placed 3xTg-AD, a model of AD, and non-transgenic (NonTg) control mice on either a sufficient choline (ChN) or choline deficient (Ch-; choline deficiency) diet from 3 to 12 (early to late adulthood) months of age. Ch- reduced plasma choline and acetylcholine levels, increased weight, and impaired both glucose metabolism and motor function in NonTg, with 3xTg-AD mice showing greater deficits. Tissue analyses showed cardiac and liver pathology, and elevated Amyloid-{beta} and phosphorylated tau in the hippocampus and cortex of 3xTg-AD Ch- mice. Unbiased proteomic analyses revealed Ch- altered hippocampal networks associated with microtubule function and postsynaptic membrane regulation. In plasma, Ch- altered protein networks associated with insulin metabolism, mitochondrial function, and inflammation. Collectively, our data highlight that dietary choline intake is necessary to prevent systems-wide organ pathology and reduce AD hallmark pathologies.

neuroscience↗

bioRxiv2022

The dually localized EF-hand domain-containing protein TgEFP1 regulates the lytic cycle of Toxoplasma gondii

The propagation of the obligate intracellular parasite Toxoplasma gondii is tightly regulated by calcium signaling. However, the mechanisms by which calcium homeostasis and fluxes are regulated in this human pathogen are not fully understood. To identify Toxoplasmas calcium homeostasis network, we have characterized a novel EF-hand domain-containing protein, which we have named TgEFP1. We have determined that TgEFP1 localizes to a previously described compartment known as the plant-like vacuole or the endo-lysosomal compartment (PLV/ELC), which harbors several proteins related to ionic regulation. Interestingly, partial permeabilization techniques showed that TgEFP1 is also secreted into the parasitophorous vacuole (PV), within which the parasite divides. Ultrastructure expansion microscopy confirmed the unusual dual localization of TgEFP1 at the PLV/ELC and the PV. Furthermore, we determined that the localization of TgEFP1 to the PV, but not to the PLV/ELC, is affected by disruption of Golgi-dependent transport with Brefeldin A. Knockout of TgEFP1 results in faster propagation in tissue culture, hypersensitivity to calcium ionophore-induced egress, and premature natural egress. Thus, our work has revealed an interplay between the PV and the PLV/ELC and a role for TgEFP1 in the regulation of calcium-dependent events.

microbiology↗

bioRxiv2022

A synthetic ancestral Kinesin-13 depolymerises microtubules faster than any natural depolymerising kinesin

The activity of a kinesin is largely determined by the ~350 residue motor domain and this region alone is sufficient to classify a kinesin as a member of a particular family. The Kinesin-13 family are a group of microtubule depolymerising kinesins and are vital regulators of microtubule length. Members of this family are critical to spindle assembly and chromosome segregation in both mitotic and meiotic cell division and play crucial roles in cilium length control and neuronal development. To better understand the evolution of microtubule depolymerisation activity in the Kinesin-13 family, we created a synthetic ancestral Kinesin-13 motor domain. This phylogenetically-inferred ancestral motor domain is the sequence predicted to have existed in the common ancestor of the Kinesin-13 family. Here we show that the ancestral Kinesin-13 motor depolymerises stabilised microtubules faster than any previously tested depolymerase. This potent activity is more than an order of magnitude faster than the most highly studied Kinesin-13, MCAK and allows the ancestral Kinesin-13 to depolymerise doubly-stabilised microtubules that are unaffected by MCAK. These data suggest that the ancestor of the Kinesin-13 family was a super depolymeriser and that members of the Kinesin-13 family have evolved away from this extreme depolymerising activity to provide more controlled microtubule depolymerisation activity in extant cells.

molecular biology↗

bioRxiv2018

A bacterial-like mechanosensitive channel controls osmoregulation and infectivity in Trypanosoma cruzi

Trypanosoma cruzi, the causative agent of Chagas disease, undergoes drastic morphological and biochemical modifications as it passes between hosts and transitions from extracellular to intracellular stages. The osmotic and mechanical aspects of these cellular transformations are not understood. Here we identify and characterize a novel mechanosensitive channel in T. cruzi (TcMscS) belonging to the superfamily of small conductance mechanosensitive channels (MscS). TcMscS is activated by membrane tension and forms a large pore permeable to anions, cations, and small osmolytes. The channel changes its location from the contractile vacuole complex in epimastigotes to the plasma membrane as the parasites develop into intracellular amastigotes. TcMscS knockout parasites show significant fitness defects, including increased cell volume, calcium dysregulation, impaired differentiation, and a dramatic decrease in infectivity. Our work provides mechanistic insights into components supporting pathogen adaptation inside the host thus opening the exploration of mechanosensation as a prerequisite of protozoan infectivity.

microbiology↗

bioRxiv2017

PHENOS: a high-throughput and flexible tool for microorganism growth phenotyping on solid media

BACKGROUNDMicrobial arrays, with a large number of different strains on a single plate printed with robotic precision, underpin an increasing number of genetic and genomic approaches. These include Synthetic Genetic Array analysis, high-throughput Quantitative Trait Loci (QTL) analysis and 2-hybrid techniques. Measuring the growth of individual colonies within these arrays is an essential part of many of these techniques but is useful for any work with arrays. Measurement is typically done using intermittent imagery fed into complex image analysis software, which is not especially accurate and is challenging to use effectively. We have developed a simple and fast alternative technique that uses a pinning robot and a commonplace microplate reader to continuously measure the thickness of colonies growing on solid agar, complemented by a technique for normalizing the amount of cells initially printed to each spot of the array in the first place. We have developed software to automate the process of combining multiple sets of readings, subtracting agar absorbance, and visualizing colony thickness changes in a number of informative ways.\n\nRESULTSThe \"PHENOS\" pipeline (PHENotyping On Solid media), optimized for Saccharomyces yeasts, produces highly reproducible growth curves and is particularly sensitive to low-level growth. We have empirically determined a formula to estimate colony cell count from an absorbance measurement, and shown this to be comparable with estimates from measurements in liquid. We have also validated the technique by reproducing the results of an earlier QTL study done with conventional liquid phenotyping, and found PHENOS to be considerably more sensitive.\n\nCONCLUSIONS\"PHENOS\" is a cost effective and reliable high-throughput technique for quantifying growth of yeast arrays, and is likely to be equally very useful for a range of other types of microbial arrays. A detailed guide to the pipeline and software is provided with the installation files at https://github.com/gact/phenos.

microbiology↗