Biology subjects

Leonard, B.

Publications and source records attributed to Leonard, B..

4 recordsLinked to original sources

bioRxiv2024

Sex-specific effects of early life unpredictability on hippocampal and amygdala responses to novelty in adolescents

BackgroundUnpredictable childhood experiences are an understudied form of early life adversity that impacts neurodevelopment in a sex-specific manner. The neurobiological processes by which exposure to early-life unpredictability impacts development and vulnerability to psychopathology remain poorly understood. The present study investigates the sex-specific consequences of early-life unpredictability on the limbic network, focusing on the hippocampus and the amygdala. MethodsParticipants included 150 youth (54% female). Early life unpredictability was assessed using the Questionnaire of Unpredictability in Childhood (QUIC). Participants engaged in a task-fMRI scan between the ages of 8 and 17 (223 total observations) measuring BOLD responses to novel and familiar scenes. ResultsExposure to early-life unpredictability associated with BOLD contrast (novel vs. familiar) in a sex-specific manner. For males, but not females, higher QUIC scores were associated with lower BOLD activation in response to novel vs. familiar stimuli in the hippocampal head and amygdala. Secondary psychophysiological interaction (PPI) analyses revealed complementary sex-specific associations between QUIC and condition-specific functional connectivity between the right and left amygdala, as well as between the right amygdala and hippocampus bilaterally. ConclusionExposure to unpredictability in early life has persistent implications for the functional operations of limbic circuits. Importantly, consistent with emerging experimental animal and human studies, the consequences of early life unpredictability differ for males and females. Further, impacts of early-life unpredictability were independent of other risk factors including lower household income and negative life events, indicating distinct consequences of early-life unpredictability over and above more commonly studied types of early life adversity.

neuroscience↗

bioRxiv2023

Efficient Memory Encoding Explains the Interactions Between Hippocampus Size, Individual Experience, and Clinical Outcomes: A Computational Model

The relationship between hippocampal volume and memory function has produced mixed results in neuroscience research, which suggests an additional influencing mechanism. To explore the role of an experience-dependent encoding mechanism, we developed an autoencoder model of the cortex-hippocampus loop and examined how its memory representation is affected by a penalty that prioritizes sparseness. We trained our model with the Fashion MNIST database and a loss function to modify synapses via backpropagation of mean squared recall error. The model exhibited experience-dependent efficient encoding, representing frequently-repeated objects with fewer neurons and smaller loss penalties; representations of similar sizes were found for objects repeated equally. Our findings clarify perplexing results from neurodevelopmental studies by linking increased hippocampal size and memory impairments in autism spectrum disorder (ASD) to decreased sparseness, and explaining dementia symptoms of forgetting with varied neuronal integrity. Our findings propose a novel model that connects observed relationships between hippocampal size and memory to the environmental demands and the underlying biological constraints, contributing to the development of a larger theory on experience-dependent encoding and storage and its failure. Author SummaryThe hippocampus is the brain region where memories are initially formed. A larger hippocampus seems to be associated with better memory performance, but this is not a static relationship; studies suggest that its size might grows with demand (e.g., the need to memorize more information) and that, in certain conditions, larger or smaller volumes of the hippocampus are not associated with better or worse memory. We demonstrate that it is possible to make sense of these findings by assuming that the hippocampus balances the need to correctly remember with the need to minimize resources used to store it, and that the hippocampal size might change as a function of memory demands (the characteristics of the information to memorize) and the underlying biology (e.g., the presence of hippocampal cell damage, or a reduction in hippocampal GABA receptors). We test this hypothesis by building a neural network model; the model correctly predicts existing, puzzling findings in the literature, and can even capture subtle interactions between different phenomena, such as predicting that individuals with Autism Spectrum Disorder would be more susceptible to memory loss in dementia.

neuroscience↗

bioRxiv2022

Novel Antibody Interfaces Revealed Through Structural Mining

Antibodies are fundamental effectors of humoral immunity, and have become a highly successful class of therapeutics. There is increasing evidence that antibodies utilize transient homotypic interactions to enhance function, and elucidation of such interactions can provide insights into their biology and new opportunities for their optimization as drugs. Yet the transitory nature of weak interactions makes them difficult to investigate. Capitalizing on their rich structural data and high conservation, we have characterized all the ways that antibody Fab regions interact crystallographically. This approach led to the discovery of previously unrealized interfaces between antibodies. While diverse interactions exist, {beta}-sheet dimers and variable-constant elbow dimers are recurrent motifs. Disulfide engineering enabled interactions to be trapped and investigated structurally and functionally, providing experimental validation of the interfaces and illustrating their potential for optimization. This work provides first insight into previously undiscovered oligomeric interactions between antibodies, and enables new opportunities for their biotherapeutic optimization.

biochemistry↗

bioRxiv2021

Aerosolization of Mycobacterium tuberculosis by tidal breathing

RationaleInterrupting tuberculosis (TB) transmission requires an improved understanding of how - and when - the causative organism, Mycobacterium tuberculosis (Mtb), is aerosolized. Although Cough is commonly assumed to be the dominant source of Mtb aerosols, recent evidence of Cough-independent Mtb release implies the contribution of alternative mechanisms. ObjectiveTo compare the aerosolization of Mtb and particulate matter from GeneXpert-positive patients during three separate respiratory manoeuvres: Tidal Breathing (TiBr), Forced Vital Capacity (FVC), and Cough. MethodologyBioaerosol sampling and Mtb detection were combined with real-time assessments of CO2 production and particle counts from 39 confirmed TB patients. Measurements and Main ResultsTiBr and FVC produced comparable numbers of particles, with Cough producing >4-fold more. For all manoeuvres, the proportions of particles detected across size categories from 0.5 - 5 m were similar, with minor differences observed only in particles between 1.5 - 2 m (p = 0.014) and >5 m (p = 0.020). Viable Mtb bacilli were detected in 66%, 70%, and 65% of TiBr, FVC, and Cough samples, respectively. Notably, while Cough produced 3-fold more Mtb than TiBr, the relative infrequency of coughing compared to breathing implies that TiBr likely contributes >90% of the daily aerosolised Mtb across a range of Cough frequencies. ConclusionsOur results suggest that, while Cough increases particle aerosolization compared to TiBr, this is not associated with increased Mtb aerosolization. Instead, TiBr produces more Mtb per particle than Cough. Assuming the number of viable Mtb organisms detected provides a proxy measure of patient infectiousness, these observations imply a significant contribution of TiBr to TB transmission.

microbiology↗