Biology subjects

Grainger, J.

Publications and source records attributed to Grainger, J..

5 recordsLinked to original sources

bioRxiv2026

Blood-brain barrier dysfunction predicts cognitive trajectory after ischemic stroke

Ischemic stroke doubles the risk of dementia.1-4 Stroke severity and location affect cognition early,5,6 but late dementia risk is not related to infarct characteristics, nor is it reduced by preventing additional strokes,3,6,7 and its mechanism is unknown. We identified a plasma proteomic signature of chronic stroke that was consistent with blood-brain barrier (BBB) dysfunction, including a 58% decrease in plasma levels of platelet-derived growth factor B and downregulation of its pathway compared to healthy controls. During 2 years of follow-up, the stroke-specific proteome was accentuated in stroke survivors who subsequently declined in the processing speed/executive function cognitive domain. To test BBB function, we performed dynamic contrast-enhanced MRI 6-9 months after stroke in an additional cohort and found 1.7-fold higher whole brain BBB leakage compared to controls. Finally, we compared autopsy tissue from people with infarcts and dementia at death to those with infarcts and no dementia. Those who died with dementia had dramatic loss of vascular mural cell coverage compared to those without dementia (median 0.7% vs. 27%). Thus, our proteomic, functional, and structural data implicate chronic BBB dysfunction in cognitive decline late after stroke, revealing potential proteomic and imaging biomarkers and, importantly, a novel target for intervention.

neuroscience↗

bioRxiv2024

Non-Human Recognition of Orthography: How is it implemented and how does it differ from Human orthographic processing

The ability to robustly recognize strings of letters, a cornerstone of reading, was observed in baboons and pigeons despite their lack of phonological and semantic knowledge. Here, we apply a comparative modeling approach to investigate the neuro-cognitive basis of orthographic decision behavior in humans, baboons, and pigeons, addressing whether phylogenetic relatedness entails similar underlying neuro-cognitive phenotypes. We use the highly transparent SpeechLess Reader (SLR) model, which assumes letter-string recognition based on a computational implementation of predictive coding, whereby orthographic decisions rely on prediction-error signals emerging from multiple representational levels: visual-pixel, letter, and letter-sequence representations. We investigate which representations species use during successful orthographic decision-making. We introduce multiple SLR variants, each including one or more prediction-error representations, and compare the simulations of each variant with orthographic decisions from individuals of three species after learning letter strings without meaning. Humans predominantly relied on letter-sequence-level representations, resulting in the highest task performance in behavior and model simulations. Baboons also relied on sequence-based representations, but in combination with pixel- and letter-level representations. In contrast, pigeons relied more on pixel and letter-level representations. These findings suggest that the orthographic representations used in orthographic decisions reflect phylogenetic distance: Humans and baboons use more similar representations than pigeons. Overall, the description of orthographic decisions based on a small set of representations and computations was highly successful in describing behavior, even for humans who mastered reading in its entirety.

animal behavior and cognition↗

bioRxiv2023

UVAE: Integration of Heterogeneous Unpaired Data with Imbalanced Classes

We introduce the Unbiasing Variational Autoencoder (UVAE), a computational framework for the integration of unpaired biomedical data streams such as clinical flow cytometry. UVAE addresses batch effect correction and data alignment by training a semi-supervised model on partially labelled datasets, enabling simultaneous normalisation and integration of diverse data within a shared latent space. The framework implements a probabilistic model for batch effect normalisation and balances class contents during training to ensure accurate representation of underlying cell composition. We apply UVAE to integrate heterogeneous clinical flow cytometry data from COVID-19 patients. The integrated data enhances the statistical signal of cell types associated with disease severity, enables clustering of subpopulations without the impediment of batch effects, and improves the performance of longitudinal regression for predicting peak disease severity from temporal patient samples.

bioinformatics↗

bioRxiv2023

Sentence superiority in the reading brain

When a sequence of written words is briefly presented and participants are asked to identify just one word at a post-cued location, then word identification accuracy is higher when the word is presented in a grammatically correct sequence compared with an ungrammatical sequence. This sentence superiority effect has been reported in several behavioral studies and two EEG investigations. Taken together, the results of these studies support the hypothesis that the sentence superiority effect is primarily driven by rapid access to a sentence-level representation via partial word identification processes that operate in parallel over several words. Here we used MEG to examine the neural structures involved in this early stage of written sentence processing, and to further specify the timing of the different processes involved. Source activities over time showed grammatical vs. ungrammatical differences first in the left inferior frontal gyrus (IFG: 325-400 ms), then the left anterior temporal lobe (ATL: 475-525 ms), and finally in both left IFG and left posterior superior temporal gyrus (pSTG: 550-600 ms). We interpret the early IFG activity as reflecting the rapid bottom-up activation of sentence-level representations, including syntax, enabled by partly parallel word processing. Subsequent activity in ATL and pSTG is thought to reflect the constraints imposed by such sentence-level representations on on-going word-based semantic activation (ATL), and the subsequent development of a more detailed sentence-level representation (pSTG). These results provide further support for a cascaded interactive-activation account of sentence reading.

neuroscience↗

bioRxiv2018

Astroplastic: A start-to-finish process for polyhydroxybutyrate production from solid human waste using genetically engineered bacteria to address the challenges for future manned Mars missions

Space exploration has long been a source of inspiration, challenging scientists and engineers to find innovative solutions to various problems. One of the current focuses in space exploration is to send humans to Mars. However, the challenge of transporting materials to Mars and the need for waste management processes are two major obstacles for these long-duration missions.\n\nTo address these two challenges a process called Astroplastic was developed that produces polyhydroxybutyrate (PHB) from solid human waste, which can be used to 3D print useful items for astronauts. PHB granules are naturally produced by bacteria such as Ralstonia eutropha and Pseudomonas aeruginosa for carbon and energy storage. The phaJ, phaC, and phaCBA genes were cloned from these native PHB-producing bacteria into Escherichia coli. These genes code for enzymes that aid in PHB production by converting products of glycolysis and {beta}-oxidation pathways, such as acetyl-CoA and enoyl-CoA, into PHB. To ensure a continuous PHB production system and to eliminate the need for cell lysis to extract PHB, recombinant E. coli was engineered to use the genes in its natural type I secretion system to secrete PHB. The C-terminal of the HlyA secretion tag was fused to phasin (PhaP), a protein originally from R. eutropha. Phasin-HlyA electrostatically binds PHB granules and transports them outside of the cell.\n\nIn addition to genetically engineering bacteria, a concept for start-to-finish PHB production process was designed. Integrating expert feedback and experimental results, conditions for each step of the process including the collection and storage of waste, volatile fatty acid (VFA) fermentation, VFA extraction, PHB fermentation, and PHB extraction were optimized. The optimized system will provide a sustainable and continuous PHB production system, which will address the problems of transportation costs and waste management for future space missions.\n\nFinancial DisclosureMindfuel Science Alberta Foundation Genome Alberta GenScript Polyferm Canada GeekStarter Alberta Integrated DNA Technologies University of Calgary University of Calgary Cumming School of Medicine University of Calgary Bachelor of Sciences University of Calgary Schulich School of Engineering University of Calgary OBrien Centre for the Bachelor of Health Sciences City of Calgary Alberta Innovates The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityAll data are freely available without restriction.

synthetic biology↗