Biology subjects

Dunlop, K.

Publications and source records attributed to Dunlop, K..

5 recordsLinked to original sources

bioRxiv2026

Sex-specific growth in invasive pink salmon (Oncorhynchus gorbuscha) from two regions in northern Norway

The recent invasion of pink salmon (Oncorhynchus gorbuscha) along the Norwegian coast has raised significant ecological concerns. Investigating regional differences in marine growth is an important step in evaluating the establishment of pink salmon in new environments. Pink salmon were captured in two northern Norwegian fjords during their return migration to in the summer of 2023; Varangerfjord in Finnmark and Oksfjord in Troms, representing the eastern and western extent of the core areas of the pink salmon invasion. Body size estimates (total length, weight, condition factor) were used to identify differences in sex-specific marine growth at the time of capture. Scales were analyzed to estimate marine somatic growth via the distance between circuli and the position of the last winter circuli (LWC). Estimates of cumulative circuli distance were divided into four marine growth periods that roughly correspond to 1) spring/summer, year one, 2) summer/fall, year one, 3) fall/winter, year one, and 4) spring, year two. Sex-specific and location effects were found in the body size of pink salmon, where males were heavier and had higher body condition than females and Varanger males had the highest estimates of body size. Scale readings revealed that growth rates were highest in the spring of both years (periods 1 and 4), with significantly decreased growth in the fall/winter (periods 2 and 3). Males from the established Varanger location exhibited the highest growth (17-21% total cumulative circuli distance) over all periods compared to the other groups, suggesting that these fish experience more favorable survivorship and marine growth conditions. These insights into pink salmon marine growth emphasize the importance of taking sex and location into consideration in further assessing the species' expansive potential in Norway.

evolutionary biology↗

bioRxiv2025

Proximity to an SGC-DLPFC Individualized Functional Target and outcomes in large rTMS clinical trials for Treatment-Resistant Depression

BackgroundTargeting methods for repetitive transcranial magnetic stimulation (rTMS) in patients with depression now include the use of individual functional scans to target specific functional connectivity (FC) patterns obtained from functional magnetic resonance imaging (fMRI). Potential biomarkers of rTMS response include target FC with the subgenual anterior cingulate cortex (SGC) or the causal depression circuit (CDC), each of which may be candidates for individualized functional targets (iFTs). We assessed the relationship of these two approaches to clinical outcomes in two large rTMS clinical trials. Methods501 subjects with moderate to severe depression underwent 4-6 weeks of daily rTMS to the left dorsolateral prefrontal cortex (DLPFC), targeted using neuronavigation to a common group-based functional target. Resting-state scans acquired at baseline were used to retrospectively compute iFTs using either SGC-DLPFC or CDC-DLPFC FC. The Euclidean distance from the group-based target used in the trial to the centre of gravity of each iFT was computed and correlated with outcomes. ResultsMost subjects iFTs were within 2cm of their group-based target. Proximity to either the SGC- or CDC-iFT was not associated with better outcomes. Sensitivity analyses accounting for treatment target FC, methodology, data quality, or treatment parameters did not change the results. ConclusionsProximity to SGC- or CDC-derived iFTs was not associated with better outcomes in patients who received neuronavigated rTMS to a group-based target. Prospective randomized clinical trials comparing neuronavigated group-based target to neuronavigated iFTs are needed.

neuroscience↗

bioRxiv2023

Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample

BackgroundRecent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder (MDD), but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with deeper clinical phenotyping. The goals of this work were to develop and evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, deeply phenotyped, single-site sample. MethodsWe used regularized canonical correlation analysis (RCCA) to identify data-driven brain-behavior dimensions explaining individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting state fMRI data for N=328 patients with MDD and N=461 healthy controls. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes ResultsThe optimal RCCA model yielded three robust and generalizable brain-behavior dimensions explaining individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified four depression subtypes, each with distinct clinical symptom profiles, abnormal RSFC patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. ConclusionsOur results define dimensional and categorical solutions to parsing neurobiological heterogeneity in MDD that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that RCCA and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

neuroscience↗

bioRxiv2021

Differential and synergistic effects of low birth weight and Western diet on skeletal muscle vasculature, mitochondrial lipid metabolism and insulin signaling in male guinea pigs

Low birth weight (LBW) offspring are at increased risk for developing insulin resistance, a key precursor in metabolic syndrome and type 2 diabetes mellitus. Altered skeletal muscle vasculature, extracellular matrix, amino acid and mitochondrial lipid metabolism, and insulin signaling are implicated in this pathogenesis. Using uteroplacental insufficiency (UPI) to induce intrauterine growth restriction (IUGR) and LBW in the guinea pig, we investigated the relationship between UPI-induced IUGR/LBW and later life skeletal muscle arteriole density, fibrosis, amino acid and mitochondrial lipid metabolism, markers of insulin signaling and glucose uptake, and how a postnatal high-fat, high-sugar "Western" diet (WD) modulates these changes. Muscle of 145-day-old male LBW glucose tolerant offspring displayed diminished vessel density and altered acylcarnitine levels. Disrupted muscle insulin signaling despite maintained whole-body glucose homeostasis also occurred in both LBW and WD-fed male lean offspring. Additionally, postnatal WD unmasked LBW-induced impairment of mitochondrial lipid metabolism as reflected by increased acylcarnitine accumulation. This study provides evidence that early markers of skeletal muscle metabolic dysfunction appear to be influenced by the in utero environment and interact with a high fat-sugar postnatal environment to exacerbate altered mitochondrial lipid metabolism promoting mitochondrial overload.

physiology↗

bioRxiv2020

White matter hyperintensity-associated structural disconnection, resting state functional connectivity, and cognitive control in older adults

ObjectiveWhite matter hyperintensities (WMH) are linked to deficits in cognitive functioning, including cognitive control and memory; however, the structural and functional mechanisms are largely unknown. We investigated the relationship between estimated regional disruptions to white matter fiber tracts from WMH, resting state functional connectivity (RSFC), and cognitive functions in older adults. DesignCross-sectional study. SettingCommunity. ParticipantsFifty-eight cognitively-healthy older adults. MeasurementsTasks of cognitive control and memory, structural MRI, and resting state fMRI. We estimated the disruption to white matter fiber tracts from WMH and its impact on gray matter regions in the cortical and subcortical frontoparietal network, default mode network, and ventral attention network by overlaying each subjects WMH mask on a normative tractogram dataset. We calculated RSFC between nodes in those same networks. ResultsThe interaction of estimated regional WMH burden and RSFC in cortico-striatal regions of the default mode network and frontoparietal network was associated with memory retrieval. Models predicting working memory, cognitive inhibition, and set-shifting were not significant. ConclusionsFindings highlight the role of circuit-level alterations at the structural and functional levels in resting state networks that are related to WMH and impact memory retrieval in older adults.

neuroscience↗