Biology subjects

Dawson, S.

Publications and source records attributed to Dawson, S..

6 recordsLinked to original sources

bioRxiv2026

Decades of Parkinson's disease neuropathology yield a sparse and underpowered map of neuronal vulnerability: a systematic review and meta-analysis

Selective vulnerability is widely assumed in Parkinson's disease (PD), but whether dopaminergic neurons of the substantia nigra are uniquely vulnerable has not been established. Explanations of neuronal degeneration in Parkinson's disease often centre on the distinctive properties of substantia nigra dopaminergic neurons. Whether these properties are necessary for substantial neuronal loss remains unclear. We preregistered a systematic review of 166 post-mortem case-control studies published between 1963 and 2025 and synthesised neuronal counts and densities from 152 studies using a multilevel meta-analysis. After six decades, only 18% of countable brain atlas labels had been examined, and most populations were represented by a single study. Substantial loss beyond dopaminergic and classically pigmented populations shows that neither dopaminergic identity nor neuromelanin is necessary for marked degeneration, challenging key tenets of selective vulnerability in PD. Comparisons across other anatomical and physiological features remain limited by sparse sampling and uncertainty. We identify less-studied populations with substantial estimated loss and estimate the additional sampling needed to improve precision under specified assumptions. These findings direct replication and comparative counting towards uncertainties that limit explanations of neuronal loss across affected and potentially spared populations.

neuroscience↗

bioRxiv2026

From flexible to anticipatory processing: alpha and beta oscillatory signatures of feedback-guided strategy adaptation and memory updating

When humans learn under conditions of uncertainty, they dynamically adjust how they prepare for and respond to feedback. In navigating uncertain environments, the brain minimizes error by continuously refining internal models via memory updating (MU). Feedback is critical for MU, and anticipatory neural mechanisms shape how feedback is processed, likely reflecting learned environmental certainty. However, the literature has largely focused on post-feedback activity, leaving pre-feedback certainty-related mechanisms less understood. The present study aims to address this gap by examining how certainty modulates anticipatory states, preceding feedback and subsequent MU. We examined oscillatory activity prior to performance feedback in a reanalysis of EEG data previously published by Hassall and colleagues (2023). Twenty-one participants (16 female, Mage = 25.81 years) predicted the strength of cartoon characters with varying predictability levels which were learned through exposure. Feedback on prediction accuracy was presented via an animated rising bar. Results revealed that theta power is modulated by accumulative feedback. Linear mixed-effects models revealed an interaction between predictability-related certainty and learning stage: in late learning, higher performance was associated with increased pre-feedback alpha and beta power for low-certainty trials, whereas in early learning, higher performance was associated with decreased beta power. These learning-related modulations in alpha and beta power suggest that initial learning is marked by adaptable exploratory processing. Subsequent learning exhibited increased alpha-mediated inhibition and beta-related anticipatory activity for lower certainty trials, indicative of dynamic strategy refinement and selective engagement of task-relevant information. These results demonstrate that certainty shapes preparatory oscillatory activity associated with MU.

neuroscience↗

bioRxiv2026

An integrated, scaled approach to resolve TSC2 variants of uncertain significance

Obtaining a precise genetic tuberous sclerosis diagnosis is a challenge as many missense TSC2 variants are variants of uncertain significance (VUS). VUS in TSC2 have been resolved by one-at-a-time functional assays, but these assays cannot scale to the 3,634 TSC2 missense VUS observed so far. To address this challenge, we used massively parallel sequencing to measure the steady-state abundance of almost 9,000 TSC2 missense variants and developed an mTOR pathway activity assay using genome editing and cell sorting to generate activity scores for 391 missense variants. 1,288 of 8,891 (14.49%) missense variants assayed had altered TSC2 abundance, and 69 of 391 (17.65%) missense variants assayed had altered mTOR pathway activity. Calibration and integration of these data into classification of variants identified in a clinical cohort putatively reclassified 212 of 276 (76.8%) TSC2 missense VUS. These datasets will lead to improved genetic diagnosis of tuberous sclerosis with potential positive impacts on the clinical management of patients and their families.

genetics↗

bioRxiv2024

A CONTRIBUTION TO THE ANATOMY OF TWO RARE CETACEAN SPECIES: THE HOURGLASS DOLPHIN (Lagenorhynchus cruciger) AND THE SPECTACLED PORPOISE (Phocoena dioptrica)

The anatomical description of the hourglass dolphin (Lagenorhynchus cruciger) and the spectacled porpoise (Phocoena dioptrica) remains largely unexplored, due to limited specimen availability and preservation challenges. This study employed digital imaging techniques, conventional histology and computed tomography to provide visualisation of anatomical structures for a detailed analysis. We present a comprehensive analysis of the gross macroscopical and microscopical morphology of two hourglass dolphins and four spectacled porpoises. The hourglass dolphins were characterised by their distinctive black and white pigmentation and a hooked dorsal fin, while the spectacled porpoises were defined by their large dorsal fin, lack of a visible rostrum and unique eye markings. Morphometric measurements and skeletal characteristics aligned with the literature, while internal anatomy (organs and systems) were similar to other odontocetes. Although precise lung measurements were challenging, qualitative assessments indicated relatively large lungs for their body size, supporting the "short dive, big lung" hypothesis and suggesting that these species are not deep divers. The spectacled porpoise dorsal fin was uniquely large with a well-developed blood supply; this is hypothesised to act as a thermoregulatory window, helping to manage body heat. Overall, this study provides new data on the anatomy of the hourglass dolphin and spectacled porpoise, contributing insights that may influence future research on these rare species. The findings highlight the importance of anatomical studies in explaining evolutionary relationships within cetaceans and their ecological roles in the Southern Ocean ecosystems.

evolutionary biology↗

bioRxiv2019

Microbial community dynamics and coexistence in a sulfide-driven phototrophic bloom

Phototrophic microbial mats commonly contain multiple phototrophic lineages that coexist based on their light, oxygen and nutrient preferences. Here we show that similar coexistence patterns and ecological niches can occur in suspended phototrophic blooms of an organic-rich estuary. The water column showed steep gradients of oxygen, pH, sulfate, sulfide, and salinity. The upper part of the bloom was dominated by aerobic phototrophic Cyanobacteria, the middle and lower parts were dominated by anoxygenic purple sulfur bacteria (Chromatiales) and green sulfur bacteria (Chlorobiales), respectively. We found multiple uncultured phototrophic lineages and present metagenome-assembled genomes of two uncultured organisms within the Chlorobiales. Apparently, those Chlorobiales populations were affected by Microviridae viruses. We suggest a sulfur cycle within the bloom in which elemental sulfur produced by phototrophs is reduced to sulfide by Desulfuromonas sp. These findings improve our understanding of the ecology and ecophysiology of phototrophic blooms and their impact on biogeochemical cycles.

microbiology↗

bioRxiv2018

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM

Many real-world data sets, especially in biology, are produced by highly multivariate and nonlinear complex dynamical systems. In this paper, we focus on brain imaging data, including both calcium imaging and functional MRI data. Standard vector-autoregressive models are limited by their linearity assumptions, while nonlinear general-purpose, large-scale temporal models, such as LSTM networks, typically require large amounts of training data, not always readily available in biological applications; furthermore, such models have limited interpretability. We introduce here a novel approach for learning a nonlinear differential equation model aimed at capturing brain dynamics. Specifically, we propose a variable-projection optimization approach to estimate the parameters of the multivariate (coupled) van der Pol oscillator, and demonstrate that such a model can accurately represent nonlinear dynamics of the brain data. Furthermore, in order to improve the predictive accuracy when forecasting future brain-activity time series, we use this analytical model as an unlimited source of simulated data for pretraining LSTM; such model-specific data augmentation approach consistently improves LSTM performance on both calcium and fMRI imaging data.

neuroscience↗