Biology subjects

Patterson, B.

Publications and source records attributed to Patterson, B..

10 recordsLinked to original sources

bioRxiv2026

Beaver population decline on Michipicoten Island, Ontario leads to satellite-measured surface water area reductions

The North American beaver (Castor canadensis) is an ecosystem engineer that strongly influences stream hydrology and ecosystems by constructing dams and canals. Previous research has shown that changes in the extent of beaver ponds and wetlands mapped using aerial photographs can serve as a proxy indicator of shifting regional abundance of beavers. In this study we investigated the use of freely available optical satellite data to measure changes in beaver pond surface water area on the 184 km2 Michipicoten Island in Lake Superior (Ontario, Canada) after a large decline in the beaver population that followed the arrival of grey wolves (Canis lupus). Inter-annual variability in pond extents was measured using sub-pixel mapping methods applied to the 30 m resolution Landsat (1985-2023) and 10 m Sentinel-2 (2016-2023) satellite records. After a > 90% decline in the number of surveyed beaver colonies between 2015-2018, beaver pond surface water area was reduced by 38-42% for ponds < 0.5 ha and by 48% for ponds < 0.1 ha by 2023. While these recent ponding reductions occurred during a period of above average precipitation, two previous smaller reductions were associated with low precipitation, water balance index, and Lake Superior water levels, suggesting that they were caused by drought and not beaver colony declines. While further testing is warranted, our results show that satellite-mapped changes in beaver ponds can provide a cost-effective metric for assessing large-scale population trends in the boreal zone.

ecology↗

bioRxiv2024

Loss of αBa-crystallin, but not αA-crystallin, increases age-related cataract in the zebrafish lens

The vertebrate eye lens is an unusual organ in that most of its cells lack nuclei and the ability to replace aging protein. The small heat shock protein -crystallins evolved to become key components of this lens, possibly because of their ability to prevent aggregation of aging protein that would otherwise lead to lens opacity. Most vertebrates express two -crystallins, A- and B-crystallin, and mutations in each are linked to human cataract. In a mouse knockout model only the loss of A-crystallin led to early-stage lens cataract. We have used the zebrafish as a model system to investigate the role of -crystallins during lens development. Interestingly, while zebrafish express one lens-specific A-crystallin gene (cryaa), they express two B-crystallin genes, with one evolving lens specificity (cryaba) and the other retaining the broad expression of its mammalian ortholog (cryabb). In this study we used individual mutant zebrafish lines for all three -crystallin genes to determine the impact of their loss on age-related cataract. Surprisingly, unlike mouse knockout models, we found that the loss of the Ba-crystallin gene cryaba led to an increase in lens opacity compared to cryaa null fish at 24 months of age. Loss of A-crystallin did not increase the prevalence of cataract. We also used single cell RNA-Seq and RT-qPCR data to show a shift in the lens expression of zebrafish -crystallins between 5 and 10 days post fertilization (dpf), with 5 and 6 dpf lenses expressing cryaa almost exclusively, and expression of cryaba and cryabb becoming more prominent after 10 dpf. These data show that cryaa is the primary -crystallin during early lens development, while the protective role for cryaba becomes more important during lens aging. This study is the first to quantify cataract prevalence in wild-type zebrafish, showing that lens opacities develop in approximately 25% of fish by 18 months of age. None of the three -crystallin mutants showed a compensatory increase in the expression of the remaining two crystallins, or in the abundant {beta}B1-crystallin. Overall, these findings indicate an ontogenetic shift in the functional importance of individual -crystallins during zebrafish lens development. Our finding that the lens-specific zebrafish Ba-crystallin plays the leading role in preventing age-related cataract adds a new twist to our understanding of vertebrate lens evolution.

developmental biology↗

bioRxiv2023

Online Bayesian Optimization of Nerve Stimulation

ObjectiveIn bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs modifying their function. Stimulation devices, capable of triggering exogenous neural signals using electrical wave forms, require a complex and multi-dimensional parameter space in order to control such wave forms. Determining the best combination of parameters (wave form optimization, or dosing) for treating a particular patients illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting, due to the size of the parameter space. Restricting this space, however, may lead to sub-optimal therapeutic results, reduced responder rates, and adverse effects. ApproachAs an alternative to a full parameter search, we present a flexible machine learning, data acquisition and processing framework for optimizing neural stimulation parameters requiring as few steps as possible using Bayesian optimization. Such optimization builds a model of the neural and physiological responses to stimulations enabling it to optimize stimulation parameters and to provide estimates of the accuracy of the response model. The vagus nerve innervates, among other thoracic and visceral organs, the heart, thus controlling heart rate and is therefore ideal for demonstrating the effectiveness of our approach. Main results. The efficacy of our optimization approach was first evaluated on simulated neural responses, then applied to vagus nerve stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target heart rates and optimizing neural B-fibre activations despite high intersubject variability. SignificanceAn optimized stimulation waveform was achieved in real time with far fewer stimulations than required by alternative optimization strategies, thus minimizing exposure to side effects. Uncertainty estimates helped avoiding stimulations outside a safe range. Our approach shows that a complex set of neural stimulation parameters can be optimized in real-time for a patient to achieve a personalized precision dosing.

neuroscience↗

bioRxiv2023

Using neural biomarkers to personalize dosing of vagus nerve stimulation

BackgroundVagus nerve stimulation (VNS) is an established therapy for treating a variety of chronic diseases, such as epilepsy, depression, obesity, and for stroke rehabilitation. However, lack of precision and side-effects have hindered its efficacy and extension to new conditions. ObjectiveTo achieve a better understanding of the relationship between VNS parameters and neural and physiological responses to enable the design of personalized dosing procedures to improve precision and efficacy of VNS therapies. MethodsWe used biomarkers from recorded evoked neural activity and short-term physiological responses (throat muscle, cardiac and respiratory activity) to understand the response to a wide range of VNS parameters in anaesthetised pigs. Using signal processing, Gaussian processes (GP) and parametric regression models we analyse the relationship between VNS parameters and neural and physiological responses. ResultsFirstly, we observe inter-subject variability for both neural and physiological responses. Secondly, we illustrate how considering multiple stimulation parameters in VNS dosing can improve the efficacy and precision of VNS therapies. Thirdly, we describe the relationship between different VNS parameters and the evoked neural activity and show how spatially selective electrodes can be used to improve fibre recruitment. Fourthly, we provide a detailed exploration of the relationship between the activations of neural fibre types and different physiological effects, and show that recordings of evoked neural activity are powerful biomarkers for predicting the short-term physiological effects of VNS. Finally, based on these results, we discuss how recordings of evoked neural activity can help design VNS dosing procedures that optimize short-term physiological effects safely and efficiently. ConclusionUnderstanding of evoked neural activity during VNS provide powerful biomarkers that could improve the precision, safety and efficacy of VNS therapies.

neuroscience↗

bioRxiv2023

Intraspecific encounters can induce home-range shifts

Direct encounters, in which two or more individuals are physically close to one another, are a topic of increasing interest as more and better movement data become available. Recent progress, including the development of statistical tools for estimating robust measures of changes in animals space use over time, facilitates opportunities to link direct encounters between individuals with the long-term consequences of those encounters. Working with movement data for coyotes (Canis latrans) and grizzly bears (Ursus arctos horribilis), we investigate whether close intraspecific encounters were associated with spatial shifts in the animals range distributions, as might be expected if one or both of the individuals involved in an encounter were seeking to reduce or avoid conflict over space. We analyze the movement data of a pair of coyotes in detail, identifying how a shift in home range location resulting from altered movement behavior was apparently a consequence of a close intraspecific encounter. With grizzly bear movement data, we approach the problem from the perspective of a set of encounter pairs within a population. We find support for the hypotheses that 1) close intraspecific encounters between bears are, on average, associated with subsequent shifts in range distributions and 2) encounters defined at finer spatial scales are followed by greater changes in space use. Our results suggest that animals can undertake long-term, large-scale spatial shifts in response to close intraspecific encounters that have the potential for conflict. These results lend support for existing theory on the evolution of territories and space use (e.g., Maynard-Smiths bourgeois strategy regarding low-conflict coexistence). Overall, we find that analyses of movement data in a pairwise context can 1) identify distances at which individuals proximity to one another may alter behavior and 2) facilitate testing of population-level hypotheses concerning the potential for direct encounters to alter individuals space use. Open Research StatementMovement data for the coyotes and grizzly bears are posted on Movebank.org as datasets 1614661371 and 1044288582, respectively. Statistical tools for estimating, manipulating, and comparing home ranges from movement data are implemented in the open-source R package ctmm. R scripts used to carry out specific analyses for this study are openly available on GitHub at https://github.com/anagkrish/encounter_homerangeshift.

ecology↗

bioRxiv2022

Maternal dietary deficiencies in folates or choline during pregnancy and lactation worsen stroke outcome in 3-month-old male and female mouse offspring

Maternal one-carbon (1C) metabolism plays an important role in early life programming. There is a well-established connection between the fetal environment and the health status of the offspring. However, there is a knowledge gap on how maternal nutrition impacts stroke outcome in offspring. The aim of our study was to investigate the role of maternal dietary deficiencies in folic acid or choline on stroke outcome in 3-month-old offspring. Adult female mice were fed a folic acid deficient diet (FADD), choline deficient diet (ChDD), or control diet (CD) prior to pregnancy. They were continued on diets during pregnancy and lactation. Male and female offspring were weaned onto a CD and at 2 months of age were subject to ischemic stroke within the sensorimotor cortex via photothrombosis damage. At 3-months-of-age, motor function was measured in offspring and tissue was collected for analysis. Mothers maintained on either a FADD or ChDD had reduced levels of S-adenosylmethionine in liver and S-adenosylhomocysteine in plasma. After ischemic stroke, motor function was impaired in 3-month-old offspring from deficient mothers compared to CD animals. In brain tissue, there was no difference in ischemic damage volume. When protein levels were assessed in brain tissue, there were lower levels of neurodegeneration in males compared to females and betaine levels were reduced in offspring from ChDD mothers. Our results demonstrate that a deficient maternal diet during critical timepoints in neurodevelopment results in worse stroke outcomes. This study emphasizes the importance of maternal diet and the impact it can have on offspring health.

neuroscience↗

bioRxiv2022

Dyslexia associated gene, KIAA0319, regulates cell cycle during human neuroepithelium development

Reading Disability (RD), also known as dyslexia, is defined as difficulty processing written language in individuals with normal intellectual capacity and educational opportunity. The prevalence of RD is between 5% and 17%, and the heritability ranges from 44% to 75%. Genetic linkage analysis and genome-wide association studies (GWAS) have identified several genes and regulatory elements linked to RD and reading ability. However, their functions and molecular mechanisms are not well understood. Prominent among these is KIAA0319, encoded in the DYX2 locus of human chromosome 6p22. Association of KIAA0319 has been independently replicated in multiple independent studies and languages. Rodent models suggest that KIAA0319 is involved in neuronal migration, but its precise function is unknown. This studies aim to determine the mechanisms by which KIAA0319 affects reading and language performance. We hypothesize that KIAA0319 plays a critical role in neuronal development. RT-qPCR and quantitative immunofluorescence in the cortical neurons differentiated from H7 hESC show regulatory effects on proliferation and differentiation of neuronal progenitor cells. Knockdown of KIAA0319 expression promotes early exit from the neuroepithelial cell stage and drives cells into cell cycle arrested neuronal progenitor cell stage. This suggests that KIAA0319 act by regulating neurogenesis in the reading related centers of the brain by targeting the cell cycle of proliferative cells. This demonstrates how subtle changes in expression could affect an isolated trait such as reading without global brain effects.

developmental biology↗

bioRxiv2021

Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) Up to 15 Months Post-Infection

The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. Non-classical monocytes are capable of causing inflammation throughout the body in response to fractalkine/CX3CL1 and RANTES/CCR5.

immunology↗

bioRxiv2020

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning

Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined as S1 = (IFN-{gamma} + IL-2)/ CCL4-MIP-1{beta}. Second, a score specific for the severe COVID-19 patients was defined as S2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells. SummaryImmunologic Modeling of Severity and Chronicity of COVID-19

immunology↗

bioRxiv2020

Scalable production of tissue-like vascularised liver organoids from human PSCs.

A lack of physiological parity between 2D cell culture and in vivo, has paved the way towards more organotypic models. Organoids exist for a number of tissues, including the liver. However, current approaches to generate hepatic organoids suffer drawbacks, including a reliance on extracellular matrices (ECM), the requirement to pattern in 2D culture, costly growth factors and a lack of cellular diversity, structure and organisation. Current hepatic organoid models are generally simplistic, composed of hepatocytes or cholangiocytes, which renders them less physiologically relevant when compared to native tissue. Here we aim to address these drawbacks. To address this, we have developed an approach that does not require 2D patterning, is ECM independent combined with small molecules to mimic embryonic liver development that produces massive quantities of liver like organoids. Using single-cell RNA sequencing and immunofluorescence we demonstrate a liver-like cellular repertoire, a higher order cellular complexity, presenting with vascular luminal structures, innervation and a population of resident macrophage - the Kupffer cells. The organoids exhibit key liver functions including drug metabolism, serum protein production, coagulation factor production, bilirubin uptake and urea synthesis. The organoids can be transplanted and maintained in mice producing human albumin long term. The organoids exhibit a complex cellular repertoire reflective of the organ, have de novo vascularization and innervation, enhanced function and maturity. This is a pre-requisite for a myriad of applications from cellular therapy, tissue engineering, drug toxicity assessment, disease modeling, to basic developmental biology.

cell biology↗