Biology subjects

Adam, R.

Publications and source records attributed to Adam, R..

7 recordsLinked to original sources

bioRxiv2026

Integrated transcriptomic and proteomic analyses identify novel biomarkers of bladder outlet obstruction

Bladder outlet obstruction leads to pathological remodeling and emergence of lower urinary tract symptoms. Although relief of obstruction is associated with symptomatic improvement, it is not universally successful, reflecting persistent alterations in the bladder. Reliable surrogate biomarkers of obstruction are lacking, particularly early in the disease course before irreversible damage to the bladder may have occurred. In this study, re-analysis of publicly available transcriptomic datasets from diverse rodent models of obstruction identified tissue transcripts including Cthrc1, Grem1, Ltbp2 and Msn that were induced in response to injury. Candidate markers were validated experimentally in an independent model of neurogenic obstruction demonstrating time-dependent changes. Candidate markers were also attenuated with either surgical removal of obstruction or treatment with anticholinergic medication or inosine. Integrated analysis of tissue transcriptomics data and tissue and urine proteomics data from a model of neurogenic obstruction revealed significant concordance between markers observed in tissue and urine. Urinary proteomics analysis identified a statistically significant increase in MSN in patients with neurogenic bladder compared to unaffected controls. These findings identify tissue and urine biomarkers of both non-neurogenic and neurogenic obstruction that may reflect early changes in obstructive uropathy that could be monitored in a non-invasive manner.

bioinformatics↗

bioRxiv2025

Differential effects of neurodegenerative disorders on verbal creative idea generation and its cognitive cornerstones

Clinical research has documented a heterogeneous effect of neurodegenerative disorders on creativity. Some disorders are associated with impaired creative performance, while others may preserve, or even enhance, it. However, the underlying cognitive mechanisms that give rise to the heterogeneous behavioural manifestations remain poorly understood. From a theory-driven approach, we conducted a neuropsychological investigation to examine how frontotemporal lobar degeneration (FTLD), and Alzheimer's Disease (AD) differentially affected the cognitive mechanisms underlying creative thought (semantic cognition, episodic memory, executive control functions). In parallel, we assessed participants' verbal creative idea generation performance using the ideational fluency task (also known as the Alternate Uses Task). We analysed data from 24 individuals with FTLD [clinical consensus diagnosis corticobasal syndrome (CBS: n=20) or progressive supranuclear palsy (PSP: n=4)], 24 individuals with clinical consensus diagnosis AD, and 24 healthy individuals. We reached four major conclusions. First, while both disease groups exhibited deficits in controlled semantic retrieval and executive control functions, only participants with AD exhibited degradation in semantic representations and episodic memory. Second, both disease groups generated fewer responses in both typical and creative conditions across objects that were context-free - i.e., associated with multiple contexts (e.g., brick) and context-bound -i.e., associated with a dominant context (e.g., table knife). Third, when given a context-free object prompt, the ability to generate novel responses appeared to be preserved in participants with FTLD, which contrasted with an impaired ability when prompted to give creative uses for the context-bound object. Fourth, participants with AD produced similar levels of response novelty for both context-free and context-bound objects. From a clinical-cognitive neuroscience perspective, this study demonstrates that distinct cognitive profiles resulting from different neurodegenerative conditions yield differential effects on creative thought. As the first study to show that the contextual information of semantic stimuli can mediate the novelty of verbal responses, we suggest that future research should carefully examine how this factor influences creative task performance.

neuroscience↗

bioRxiv2024

Machine Learning-based Classification of transcriptome Signatures of non-ulcerative Bladder Pain Syndrome

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non- ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)- based approach for the identification of mRNA signatures specific to non-ulcerative BPS. Using next-generation sequencing (NGS) transcriptome data from bladder biopsies of patients with BPS, benign prostatic obstruction with DO and controls, our statistical approach successfully identified 13 candidate genes capable of discerning BPS from control and DO patients. This set was subsequently validated using Quantitative Polymerase Chain Reaction (QPCR) in a larger patient cohort. To confirm our findings, we applied both supervised and unsupervised ML approaches to the QPCR dataset. Notably, a three-mRNA signature TPPP3, FAT1, and NCALD, emerged as a robust classifier, effectively distinguishing patients with non- ulcerative BPS from controls and patients with DO. This signature was universally selected by both supervised and unsupervised approaches. The ML-based framework used to define BPS classifiers not only establishes a solid foundation for comprehending the specific gene expression changes in the bladder of the patients with BPS but also serves as a valuable resource and methodology for advancing signature identification in other fields. The proposed ML pipeline demonstrates its efficacy in handling challenges associated with limited sample sizes, offering a promising avenue for applications in similar domains.

bioinformatics↗

bioRxiv2023

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis

BackgroundIn recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. ResultsTo address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. ConclusionSpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan. Key PointsO_LIA deep learning model was trained to detect and segment spheroids in images from microscopes and Incucytes. C_LIO_LIThe model performed well on both types of images with the total loss decreasing significantly during the training process. C_LIO_LIA web tool called SpheroScan was developed to facilitate the analysis of spheroid images, which includes prediction and visualization modules. C_LIO_LISpheroScan is efficient and scalable, making it possible to handle large datasets with ease. C_LIO_LISpheroScan is user-friendly and accessible to researchers, making it a valuable resource for the analysis of spheroid image data. C_LI

bioinformatics↗

bioRxiv2022

A snapshot of brain and cognition in healthy mid-life and older adults

Deficits in memory are seen as a canonical sign of ageing and a prodrome to dementia in older adults. However, the nature of cognitive and brain changes across a wider aperture of adulthood is not well known. We quantify the relationship between cognitive function and brain morphology from mid-life to older adulthood, and the influence of age, sex, amyloid and genetic risk for dementia. We analyzed three observational cohorts (PISA, AIBL, ADNI) with cognitive, genetic and neuroimaging measures comprising a total of 1570 healthy mid-life and older adults (mean age 72, range 49-90 years, 1330 males) and 1365 age- and sex-matched adults with mild cognitive impairment or Alzheimers disease. Among healthy adults, we find robust modes of co-variation between regional sulcal width and multidomain cognitive function that change from mid-life to the older age range. The most prominent cortical changes in mid-life are predominantly associated with changes in executive functions, whereas they are most strongly associated with poorer memory function in older age. These cognitive changes are accompanied by an age-dependent pattern of sulcal widening. Amyloid exerts a weak, but significant, influence on cognition, but not on sulcal width. The APOE {varepsilon}4 allele also exerts a weak influence on cognition, but only significantly in the (larger and older) AIBL cohort. These findings provide new insights into brain and cognition in mid-life and older adults, suggesting that cognitive screening in mid-life cohorts should encompass executive functions as well as memory.

neuroscience↗

bioRxiv2020

Structural alterations in the macaque frontoparietal white matter network after recovery from prefrontal cortex lesions

Unilateral damage to the frontoparietal network typically impairs saccade target selection within the contralesional visual hemifield. Severity of deficits and the degree of recovery have been associated with widespread network dysfunction, yet it is not clear how these behavioural and functional changes relate with the underlying structural white matter pathways. Here, we investigated whether recovery after unilateral prefrontal cortex (PFC) lesions was associated with structural white matter remodeling in the distributed frontoparietal network. Diffusion-weighted MRI was acquired in four macaque monkeys before the lesions and at 2-4 months post-lesion, after recovery of deficits in saccade selection of contralesional targets. Probabilistic tractography was used to reconstruct inter- and intra-hemispheric frontoparietal fiber tracts: bilateral superior longitudinal fasciculus (SLF) and transcallosal fibers connecting bilateral PFC or bilateral posterior parietal cortex (PPC). After behavioural recovery, tract-specific fractional anisotropy in contralesional SLF and transcallosal PPC increased after small lesions and decreased after larger lesions compared to pre-lesion. These findings indicate that remote fiber tracts may provide optimal compensation after small PFC lesions. However, larger lesions may have induced widespread structural damage and hindered compensatory remodeling in the structural frontoparietal network.

neuroscience↗

bioRxiv2020

Tracing the evolutionary history and global expansion of Candida auris using population genomic analyses

Candida auris has emerged globally as a multidrug-resistant yeast that can spread via nosocomial transmission. An initial phylogenetic study of isolates from Japan, India, Pakistan, South Africa, and Venezuela revealed four populations (Clades I, II, III, and IV) corresponding to these geographic regions. Since this description, C. auris has been reported in over 30 additional countries. To trace this global emergence, we compared the genomes of 304 C. auris isolates from 19 countries on six continents. We found that four predominant clades persist across wide geographic locations. We observed phylogeographic mixing in most clades; Clade IV, with isolates mainly from South America, demonstrated the strongest phylogeographic substructure. C. auris isolates from two clades with opposite mating types were detected contemporaneously in a single healthcare facility in Kenya. We estimated a Bayesian molecular clock phylogeny and dated the origin of each clade within the last 339 years; outbreak-causing clusters from Clades I, III, and IV originated 34-35 years ago. We observed high rates of antifungal resistance in Clade I, including four isolates resistant to all three major classes of antifungals. Mutations that contribute to resistance varied between the clades, with Y132F in ERG11 as the most widespread mutation associated with azole resistance and S639P in FKS1 for echinocandin resistance. Copy number variants in ERG11 predominantly appeared in Clade III and were associated with fluconazole resistance. These results provide a global context for the phylogeography, population structure, and mechanisms associated with antifungal resistance in C. auris. ImportanceIn less than a decade, C. auris has emerged in healthcare settings worldwide; this species is capable of colonizing skin and causing outbreaks of invasive candidiasis. In contrast to other Candida species, C. auris is unique in its ability to spread via nosocomial transmission and its high rates of drug resistance. As part of the public health response, whole-genome sequencing has played a major role in characterizing transmission dynamics and detecting new C. auris introductions. Through a global collaboration, we assessed genome evolution of isolates of C. auris from 19 countries. Here, we described estimated timing of the expansion of each C. auris clade and of fluconazole resistance, characterized discrete phylogeographic population structure of each clade, and compared genome data to sensitivity measurements to describe how antifungal resistance mechanisms vary across the population. These efforts are critical for a sustained, robust public health response that effectively utilizes molecular epidemiology.

genomics↗