Biology subjects

Mark, S.

Publications and source records attributed to Mark, S..

9 recordsLinked to original sources

bioRxiv2023

Extracellular vesicles from patients with coronary artery disease (CAD) demonstrate enhanced pro-coagulatory activity.

AimsExtracellular vesicles (EVs) carry unique repertoires of biologically active cargo that hold promise as novel biomarkers and future interventional targets for cardiovascular diseases (CVDs). However, it is unclear as to how the number, location, cellular origin, and size of these EVs within the circulation relate to the development of CVDs such as coronary artery disease (CAD). The current study compared these novel markers in arterial and venous blood samples in individuals undergoing coronary assessment with angiography.. EVs were then characterized from those presenting with and without CAD. Methods and ResultsArterial and venous blood samples were collected from individuals with confirmed CAD following coronary angiography and a matched cohort in whom there was no evidence of disease. EV fractions were isolated from 500{micro}L of platelet free plasma (PFP) by size exclusion chromatography. EVs were analyzed by Nanoparticle Tracking Analysis and flow cytometry to characterize number, size and cellular origin. A thrombin generation assay was used to assess the pro-coagulatory activity of the isolated circulating EVs. Proteomics was used to determine the protein cargo carried within the EVs. Coagulatory activity of EVs isolated from CAD patients was significantly higher in when compared to controls, although the numbers of EVs did not differ. There were higher numbers of endothelial-derived EVs in arterial blood compared with venous blood. Linear regression models revealed that plasma triacylglycerol concentration and age independently predicted circulating EV numbers in CAD patients. Proteomics revealed several proteins associated with coagulation upregulated in patients with CAD. ConclusionsAlthough the absolute numbers of EVs in CAD patients were not elevated, EVs in CAD patients had greater pro-coagulant activity, highlighting a potentially important role for EVs in the pathogenesis of CAD. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LICAD patients displayed a greater EV-induced thrombin generation capability when compated to those with no disease. C_LIO_LIThe proteomic profile of arterial-derived EVs in patients with CAD demonstrated several proteins associated with coagulation that may be a risk factor for developing a future event. C_LI What are the clinical implications?O_LIThe identification of EVs in patients with CAD with upregulated coagulation proteins may be a novel biomarker for the development of future events and may identify a high risk patient group that may benefit for more aggressive cardiovascular risk intervention. C_LI

physiology↗

bioRxiv2023

Flexible and abstract neural representations of structural knowledge

Humans ability for generalisation is outstanding. It is flexible enough to identify cases where knowledge from prior tasks is relevant, even when many features of the current task are different, such as the sensory stimuli or the size of the task state space. We have previously shown that in abstract tasks, humans can generalise knowledge in cases where the only cross-task shared feature is the statistical rules that govern the tasks state-state relationships. Here, we hypothesized that this capacity is associated with generalisable representations in the entorhinal cortex (EC). This hypothesis was based on the ECs generalisable representations in spatial tasks and recent discoveries about its role in the representation of abstract tasks. We first develop an analysis method capable of testing for such representations in fMRI data, explain why other common methods would have failed for our task, and validate our method through a combination of electrophysiological data analysis, simulations and fMRI sanity checks. We then show with fMRI that EC representations generalise across complex non-spatial tasks that share a hexagonal grid structural form but differ in their size and sensory stimuli, i.e. their only shared feature is the rules governing their statistical structure. There was no clear evidence for such generalisation in EC for non-spatial tasks with clustered, as opposed to planar, structure.

neuroscience↗

bioRxiv2021

Generative replay for compositional visual understanding in the prefrontal-hippocampal circuit

Understanding the visual world is a constructive process. Whilst a frontal-hippocampal circuit is known to be essential for this task, little is known about the associated neuronal computations. Visual understanding appears superficially distinct from other known functions of this circuit, such as spatial reasoning and model-based planning, but recent models suggest deeper computational similarities. Here, using fMRI, we show that representations of a simple visual scene in these brain regions are relational and compositional - key computational properties theorised to support rapid construction of hippocampal maps. Using MEG, we show that rapid sequences of representations, akin to replay in spatial navigation and planning problems, are also engaged in visual construction. Whilst these sequences have previously been proposed as mechanisms to plan possible futures or learn from the past, here they are used to understand the present. Replay sequences form constructive hypotheses about possible scene configurations. These hypotheses play out in an optimal order for relational inference, progressing from predictable to uncertain scene elements, gradually constraining possible configurations, and converging on the correct scene configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry, and a role for generative replay in constructive inference and hypothesis testing.

neuroscience↗

bioRxiv2019

Transferring structural knowledge across cognitive maps in humans and models

Relations between task elements often follow hidden underlying structural forms such as periodicities or hierarchies, whose inferences fosters performance. However, transferring structural knowledge to novel environments requires flexible representations that are generalizable over particularities of the current environment, such as its stimuli and size. We suggest that humans represent structural forms as abstract basis sets and that in novel tasks, the structural form is inferred and the relevant basis set is transferred. Using a computational model, we show that such representation allows inference of the underlying structural form, important task states, effective behavioural policies and the existence of unobserved state-trajectories. In two experiments, participants learned three abstract graphs during two successive days. We tested how structural knowledge acquired on Day-1 affected Day-2 performance. In line with our model, participants who had a correct structural prior were able to infer the existence of unobserved state-trajectories and appropriate behavioural policies.

neuroscience↗

bioRxiv2019

Found in Transcription: Gene fusions arise through defects in RNA processing in the absence of chromosomal rearrangements.

Recent advancements in high throughput sequencing analysis have enabled the characterization of cancer-driving fusions, improving our understanding of cancer development. Most fusion calling methods, however, examine either RNA or DNA information alone and are limited to a rigid definition of what constitutes a fusion. For this study we developed a pipeline that incorporates several fusion calling methods and considers both RNA and DNA to capture a more complete representation of the tumour fusion landscape. Interestingly, most of the fusions we identified were specific to RNA, with no evidence of corresponding genomic restructuring. Further, while the average total number of fusions in tumour and normal brain tissue samples is comparable, their overall fusion profiles vary significantly. Tumours have an over-representation of fusions occurring between coding genes, whereas fusions involving intergenic or non-coding regions comprised the vast majority of those in normals. Tumours were also more abundant in unique, sample-specific fusions compared to normals, though several fusions exhibited strong recurrence in the tumour type examined (diffuse intrinsic pontine glioma; DIPG) and were absent from both normal tissues and other cancers. Intriguingly, tumours also show broad up- or down-regulation of spliceosomal gene expression, which significantly correlates with fusion number (p=0.007). Our results show that RNA-specific fusions are abundant in both tumour and normal tissue and are associated with spliceosomal gene dysregulation. RNA-specific fusions should be considered as a potential mechanism that may contribute to cancer formation initiation and maintenance alongside more traditional structural events.

genomics↗

bioRxiv2019

The Tolman-Eichenbaum Machine: Unifying space and relational memory through generalisation in the hippocampal formation

The hippocampal-entorhinal system is important for spatial and relational memory tasks. We formally link these domains; provide a mechanistic understanding of the hippocampal role in generalisation; and offer unifying principles underlying many entorhinal and hippocampal cell-types. We propose medial entorhinal cells form a basis describing structural knowledge, and hippocampal cells link this basis with sensory representations. Adopting these principles, we introduce the Tolman-Eichenbaum machine (TEM). After learning, TEM entorhinal cells include grid, band, border and object-vector cells. Hippocampal cells include place and landmark cells, remapping between environments. Crucially, TEM also predicts empirically recorded representations in complex non-spatial tasks. TEM predicts hippocampal remapping is not random as previously believed. Rather structural knowledge is preserved across environments. We confirm this in simultaneously recorded place and grid cells.\n\nOne Sentence SummarySimple principles of representation and generalisation unify spatial and non-spatial accounts of hippocampus and explain many cell representations.

neuroscience↗

bioRxiv2019

Molecular evolution across developmental time reveals rapid divergence in early embryogenesis

Ontogenetic development hinges on the changes in gene expression in time and space within an organism, suggesting that the demands of ontogenetic growth can impose or reveal predictable pattern in the molecular evolution of genes expressed dynamically across development. Here we characterize co-expression modules of the C. elegans transcriptome, using a time series of 30 points from early-embryo to adult. By capturing the functional form of expression profiles with quantitative metrics, we find fastest evolution in the distinctive set of genes with transcript abundance that declines through development from young embryos. These genes are highly enriched for oogenic function (maternal provisioning), are non-randomly distributed in the genome, and correspond to a life stage especially prone to inviability in inter-species hybrids. These observations conflict with the \"early conservation model\" for the evolution of development, and provide only qualified support for the \"hourglass model.\" Genes in co-expression modules that peak toward adulthood also evolve fast, being hyper-enriched for roles in spermatogenesis, implicating a history of sexual selection and relaxation of selection on sperm as key factors driving rapid change to ontogenetically distinguishable co-expression modules of genes. These predictable trends of molecular evolution for dynamically-expressed genes across ontogeny might predispose particular life stages, early embryogenesis in particular, to hybrid dysfunction in the speciation process.

evolutionary biology↗

bioRxiv2019

Genetic and environmental perturbations drive modular transcriptome responses

Understanding the plasticity, robustness, and modularity of transcriptome expression to genetic and environmental conditions is crucial to deciphering how organisms adapt in nature. To test how genome architecture influences transcriptome profiles, we quantified expression responses for distinct temperature-adapted genotypes of the nematode Caenorhabditis briggsae when exposed to chronic temperature stresses throughout development. We found that 56% of the 8795 differentially-expressed genes show genotype-specific changes in expression in response to temperature (genotype-by-environment interactions, GxE). Most genotype-specific responses occur under heat stress, indicating that cold versus heat stress responses involve distinct genomic architectures. The 22 co-expression modules that we identified differ in their enrichment of genes with genetic versus environmental versus interaction effects, as well as their genomic spatial distributions, functional attributes, and rates of molecular evolution at the sequence level. Genes in modules enriched for simple effects of either genotype or temperature alone tend to evolve especially rapidly, consistent with disproportionate influence of adaptation or weaker constraint on these subsets of loci. Chromosome scale heterogeneity in nucleotide polymorphism, however, rather than the scale of individual genes, predominate as the source of genetic differences among expression profiles, and natural selection regimes are largely decoupled between coding sequences and non-coding flanking sequences that contain cis-regulatory elements. These results illustrate how the form of transcriptome modularity and genome structure contribute to predictable profiles of evolutionary change.

genomics↗

bioRxiv2018

What is a cognitive map? Organising knowledge for flexible behaviour

It is proposed that a cognitive map encoding the relationships between entities in the world supports flexible behaviour, but the majority of the neural evidence for such a system comes from studies of spatial navigation. Recent work describing neuronal parallels between spatial and non-spatial behaviours has rekindled the notion of a systematic organisation of knowledge across multiple domains. We review experimental evidence and theoretical frameworks that point to principles unifying these apparently disparate functions. These principles describe how to learn and use abstract, generalisable knowledge and suggest map-like representations observed in a spatial context may be an instance of general coding mechanisms capable of organising knowledge of all kinds. We highlight how artificial agents endowed with such principles exhibit flexible behaviour and learn map-like representations observed in the brain. Finally, we speculate on how these principles may offer insight into the extreme generalisations, abstractions and inferences that characterise human cognition.

neuroscience↗