Biology subjects

Arnold, D.

Publications and source records attributed to Arnold, D..

11 recordsLinked to original sources

bioRxiv2025

Genetic diversity in horseshoe bat ACE2 and sarbecovirus spike proteins mutually shape one another

Angiotensin-converting enzyme 2 (ACE2) serves as the entry receptor for a wide diversity of sarbecoviruses naturally harboured by horseshoe bats (genus Rhinolophus). Despite the extensive circulation of these viruses in many horseshoe bat species, the potential interactions between virus and receptor evolution remain poorly understood. We sampled individuals of the intermediate horseshoe bat (Rhinolophus affinis) across Vietnam and identified 15 genotypes of ACE2 proteins, 10 of which are previously unreported. Phylogenetic analysis and infectivity assays with a panel of 36 sarbecovirus spike proteins indicated that the R. affinis ACE2 phylogeny has geographic structuring and genotypes originating from different geographic regions exhibit distinct infectivity phenotypes. We detected site-specific positive selection on ACE2 site 24 with the associated substitutions largely affecting the receptors sarbecovirus infectivity profile. Together, our findings suggest that the R. affinis within-species ACE2 diversity has likely been shaped through selection by past sarbecovirus infection. Similarly on the virus end, we use mutagenesis assays and structural analysis through cryo-EM, to delineate the proximal evolution of the Ra22QT77 spike defined by specialization to the ACE2 genotypes of horseshoe bats found in and near southern Vietnam, where the virus was sampled. Our findings contribute to a better understanding of host-sarbecovirus co-evolution dynamics and provide valuable insights into the receptor usage determinants of these viruses. HighlightsO_LIWe identify a total of 15 ACE2 genotypes in R. affinis bats from Vietnam. C_LIO_LIACE2 intraspecific polymorphism is geographically separated and associated with distinct sarbecovirus infectivity. C_LIO_LISite 24 of R. affinis ACE2 experiences positive selection and controls susceptibility to sarbecoviruses. C_LIO_LIBat ACE2s and sarbecovirus spikes are bidirectionally shaped by each others evolution. C_LI

microbiology↗

bioRxiv2024

Control of limb loading during active horizontal perturbations at moderate and fast trots in rats

To understand how small animals cope with complex, unstructured, and unpredictable substrates, we analyzed the kinetics of rats (n = 10) moving at a fast and at a moderate trot over an unperturbed substrate and a substrate subjected to active horizontal perturbations. Perturbations were active single forwards or backwards displacements of an instrumented platform by amplitudes of 5mm or 10mm in 0.05s. Single leg ground reaction forces (SLGRF) were collected for unperturbed and perturbed locomotion (hindlimbs: 50/102, forelimbs: 45/130, respectively). When negotiating horizontal perturbations, rats displayed gait resetting (braking, accelerating) and non-resetting behaviors. Feedforward strategies differed between the fore- and hindlimbs. In circa 60% of the perturbed trials, forelimbs started the step in acceleration mode, while hindlimbs began the stance mostly in non-resetting mode ([~]45%). In about 50% of all perturbed steps, the impulse provided by the SLGRF displayed a change in behavior according to the expected response to the perturbation. The remaining 50% retained the feedforward strategy. Still, most perturbed trials displayed changes in SLGRF patterns that indicated passive and active reactions to platform shifts. Our results indicate that rats sensorimotor control system tunes fore- and hindlimbs differently in expectation of a perturbation. In addition, the tendon-muscle systems of the limbs are recruited to prevent leg collapse at the beginning and end of the stance. At lower speeds, spinal and/or higher center commands have enough time to re-adapt limb behavior. At higher speeds of locomotion, rats rely more on their limbs intrinsic stability and on feedforward control.

animal behavior and cognition↗

bioRxiv2023

Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images

Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers from inter-rater variability. Automated methods to detect MRI artifacts could improve the efficiency of the process. Such automated methods have achieved high accuracy using small datasets, with balanced proportions of MRI data with and without artifacts. With the current trend towards big data in neuroimaging, there is a need for automated methods that achieve accurate detection in large and imbalanced datasets. Deep learning (DL) is the ideal MRI artifact detection algorithm for large neuroimaging databases. However, the inference generated by DL does not commonly include a measure of uncertainty. Here, we present the first stochastic DL algorithm to generate automated, high-performing MRI artifact detection implemented on a large and imbalanced neuroimaging database. We implemented Monte Carlo dropout in a 3D AlexNet to generate probabilities and epistemic uncertainties. We then developed a method to handle class imbalance, namely data-ramping to transfer the learning by extending the dataset size and the proportion of the artifact-free data instances. We used a 34,800 scans (98% clean) dataset. At baseline, we obtained 89.3% testing accuracy (F1 = 0.230). Following the transfer learning (with data-ramping), we obtained 94.9% testing accuracy (F1 = 0.357) outperforming focal cross-entropy (92.9% testing accuracy, F1 = 0.304) incorporated for comparison at handling class imbalance. By implementing epistemic uncertainties, we improved the testing accuracy to 99.5% (F1 = 0.834), outperforming the results obtained in previous comparable studies. In addition, we estimated aleatoric uncertainties by incorporating random flips to the MRI volumes, and demonstrated that aleatoric uncertainty can be implemented as part of the pipeline. The methods we introduce enhance the efficiency of managing large databases and the exclusion of artifact images from big data analyses. HighlightsO_LIWe address the difficulty in automatically detecting artifacts in a large, imbalanced image database. C_LIO_LIWe reproduced high accuracy in detecting artifacts in small balanced datasets. C_LIO_LIWe implemented Monte Carlo (MC) dropout in 3D AlexNet to generate uncertainty metrics. C_LIO_LIWe transfer the learning from a small balanced dataset to a large imbalanced dataset, outperforming focal loss. C_LIO_LIWe outperformed artifact detection in previous studies using comparable large imbalanced datasets C_LIO_LIThe user can select an operating point to consider manual inspection vs. artifact detection error. C_LI

bioinformatics↗

bioRxiv2023

Active surface flows accelerate the coarsening of lipid membrane domains

Phase separation of multicomponent lipid membranes is characterized by the nucleation and coarsening of circular membrane domains that grow slowly in time as [~]t1/3, following classical theories of coalescence and Ostwald ripening. In this work, we study the coarsening kinetics of phase-separating lipid membranes subjected to nonequilibrium forces and flows transmitted by motor-driven gliding actin filaments. We experimentally observe that the activity-induced surface flows trigger rapid coarsening of non-circular membrane domains that grow as [~]t2/3, a 2x acceleration in the growth exponent compared to passive coalescence and Ostwald ripening. We analyze these results by developing analytical theories based on the Smoluchowski coagulation model and the phase field model to predict the domain growth in the presence of active flows. Our work demonstrates that active matter forces may be used to control the growth and morphology of membrane domains driven out of equilibrium.

biophysics↗

bioRxiv2022

Antibody binding reports spatial heterogeneities in cell membrane organization

The spatial organization of cell membrane glycoproteins and glycolipids is critical for mediating the binding of ligands, receptors, and macromolecules on the plasma membrane. However, we currently do not have the methods to quantify the spatial heterogeneities of macromolecular crowding on live cell surfaces. In this work, we combine experiment and simulation to report crowding heterogeneities on reconstituted membranes and live cell membranes with nanometer spatial resolution. By quantifying the effective binding affinity of IgG monoclonal antibodies to engineered antigen sensors, we discovered sharp gradients in crowding within a few nanometers of the crowded membrane surface. Our measurements on human cancer cells support the hypothesis that raft-like membrane domains exclude bulky membrane proteins and glycoproteins. Our facile and high-throughput method to quantify spatial crowding heterogeneities on live cell membranes may facilitate monoclonal antibody design and provide a mechanistic understanding of plasma membrane biophysical organization.

biophysics↗

bioRxiv2022

Molecular machines stimulate intercellular calcium waves and cause muscle contraction

Intercellular calcium waves (ICW) are complex signaling phenomena that control many essential biological activities, including smooth muscle contraction, vesicle secretion, gene expression, and changes in neuronal excitability. Accordingly, the remote stimulation of ICW may result in versatile new biomodulation and therapeutic strategies. Here, we demonstrate that light-activated molecular machines (MM), molecules that rotate and perform mechanical work on the molecular scale, can remotely stimulate ICW. Live-cell calcium tracking and pharmacological experiments reveal that MM-induced ICW are driven by the activation of inositol triphosphate (IP3) mediated signaling pathways by unidirectional, fast-rotating MM. We then demonstrated that MM-induced ICW can be used to control muscle contraction in vitro in cardiomyocytes and animal behavior in vivo in Hydra vulgaris. Consequentially, this work demonstrates a new strategy for the direct control of cell signaling and downstream biological function using molecular-scale devices.

bioengineering↗

bioRxiv2022

Alterations in platelet proteome signature and impaired platelet integrin αIIbβ3 activation in patients with COVID-19

BackgroundPatients with coronavirus disease-19 (COVID-19) are at increased risk of thrombosis, which is associated with altered platelet function and coagulopathy, contributing to excess mortality. ObjectivesWe aimed to characterise the mechanism of altered platelet function in COVID-19 patients. MethodsThe platelet proteome, platelet functional responses and platelet-neutrophil aggregates were compared between patients hospitalised with COVID-19 and healthy control subjects using Tandem Mass Tag (TMT) proteomic analysis, Western blotting and flow cytometry. ResultsCOVID-19 patients showed a different profile of platelet protein expression (858 altered out of 5773 quantified). Levels of COVID-19 plasma markers were enhanced in COVID-19 platelets. Gene ontology (GO) pathway analysis demonstrated that levels of granule secretory proteins were raised, whereas some platelet activation proteins, such as the thrombopoietin receptor and PKC, were lowered. Basally, COVID-19 platelets showed enhanced phosphatidylserine (PS) exposure, with unaltered integrin IIb{beta}3 activation and P-selectin expression. Agonist-stimulated integrin IIb{beta}3 activation and PS exposure, but not P-selectin expression, were significantly decreased in COVID-19 patients. COVID-19 patients had high levels of platelet-neutrophil aggregates, even under basal conditions, compared to controls. This interaction was disrupted by blocking P-selectin, demonstrating that platelet P-selectin is critical for the interaction. ConclusionsOverall, our data suggests the presence of two platelet populations in patients with COVID-19: one with circulating platelets with an altered proteome and reduced functional responses and another with P-selectin expressing neutrophil-associated platelets. Platelet driven thromboinflammation may therefore be one of the key factors enhancing the risk of thrombosis in COVID-19 patients. Essentials- COVID-19 patient platelet function and platelet proteins were compared with healthy controls - Proteomic analysis of platelets indicated that COVID-19 decreased platelet activation proteins - Agonist induced PS exposure and integrin IIb{beta}3 activation were impaired in COVID-19 - COVID-19 led to maximal levels of P-selectin dependent platelet-neutrophil aggregates

cell biology↗

bioRxiv2021

Highly accurate retinotopic maps of the physiological blind spot in human visual cortex

The physiological blind spot is a naturally occurring scotoma corresponding with the optic disc in the retina of each eye. Even during monocular viewing, observers are usually oblivious to the scotoma, in part because the visual system extrapolates information from the surrounding area. Unfortunately, studying this visual field region with neuroimaging has proven difficult, as it occupies only a small part of retinotopic cortex. Here we used functional magnetic resonance imaging and a novel data-driven method for mapping the retinotopic organization in and around the blind spot representation in V1. Our approach allowed for highly accurate reconstructions of the extent of an observers blind spot, and out-performed conventional model-based analyses. This method opens exciting opportunities to study the plasticity of receptive fields after visual field loss, and our data add to evidence suggesting that the neural circuitry responsible for impressions of perceptual completion across the physiological blind spot most likely involves regions of extrastriate cortex - beyond V1.

neuroscience↗

bioRxiv2021

Diffusely abnormal white matter converts to T2 lesion volume in the absence of acute inflammation

Diffusely abnormal white matter (DAWM), characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive MS (SPMS). However, little is known about changes of DAWM over time and their relation to focal white matter lesions (FWML). The objectives of this work were: 1) To characterize the longitudinal evolution of FWML, DAWM, and DAWM that transforms into FWML, and 2) To determine whether gadolinium enhancement, known to be associated with the development of new FWML, is also related to DAWM voxels that transform into FWML. Our data included 4220 MRI scans of 689 SPMS participants, followed for 156 weeks and 2677 scans of 686 RRMS participants, followed for 96 weeks. FWML and DAWM were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, DAWM voxels at each visit that transformed into FWML on the last MRI scan as well as their overlap with gadolinium enhancing lesion masks were identified. Our results showed that the average yearly rate of conversion of DAWM-to-FWML was 1.27cc for SPMS and 0.80cc for RRMS. FWML in SPMS participants significantly increased (t=3.9; p=0.0001) while DAWM significantly decreased (t=-4.3 p<0.0001) and the ratio FWML:DAWM increased (t=12.7; p<0.00001). RRMS participants also showed an increase in the FWML:DAWM Ratio (t=6.9; p<0.00001) but without a significant change of the individual volumes. Gadolinium enhancement was associated with 7.3% and 18.7% of focal New T2 lesion formation in the infrequent scans of the RRMS and SPMS cohorts, respectively. In comparison, only 0.1% and 0.0% of DAWM-to-FWML voxels overlapped with gadolinium enhancement. We conclude that DAWM transforms into FWML over time, in both RRMS and SPMS. DAWM appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

neuroscience↗

bioRxiv2019

Automated Separation of Diffusely Abnormal White Matter from Focal White Matter Lesions on MRI in Multiple Sclerosis

BackgroundPrevious histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelination, axonal loss and immune cell density on histopathology, potentially offering distinct correlations with symptoms.\n\nObjectives1) To automate the separation of FWML and DAWM using T2w MRI intensity thresholds and to investigate their differences in magnetization transfer ratios (MTR), which are sensitive to myelin content; 2) to correlate MTR values in FWML and DAWM with normalized signal intensity values on fluid attenuated inversion recovery (FLAIR), T2w, and T1-weighted (T1w) contrasts, as well as with the ratio of T2w/T1w normalized values, in order to determine whether these normalized intensities can be used as myelin-sensitive markers when MTR is not available.\n\nMethodsUsing similar 3T MRI protocols, 2 MS cohorts of 20 participants each were scanned in 2 centers, including: 3D T1w (MP2RAGE), 3D FLAIR, 2D T2w, and 3D magnetization-transfer (MT) contrasts. We used the first dataset to develop an automated technique to separate FWML from DAWM and the second one to validate the automation of the technique. We applied the automatic thresholds to both datasets and assessed the overlap of the manual and the automated masks using Dice kappa. We also assessed differences in mean MTR values between NAWM, DAWM and FWML, using manually and automatically derived masks in both datasets. Finally, we used the mean intensity of manually-traced areas of NAWM on T2w images as the normalization factor for each MRI contrast, and compared these with the normalized-intensity values obtained using automated NAWM (A-NAWM) masks as the normalization factor. Paired t-tests assessed the MTR differences across tissue types. Wilcoxon Signed Rank test and paired t-tests assessed FWML and DAWM differences in manual and automated derived volumes. Pearson correlations assessed the relationship between MTR and normalized intensity values in the manual and automated derived masks.\n\nResultsThe mean Dice-kappa values for dataset 1 were: 0.8 for DAWM masks and 0.7 for FWML masks. In dataset 2, mean dice-kappa values were: 0.8 for DAWM and 0.8 for FWML. Also, manual and automated DAWM and FWML volumes were not significantly different in both datasets. MTR values (expressed as mean and standard deviation, arbitrary units) were significantly lower in manually derived FWML compared with DAWM in both datasets: 1) FWML: 37.1 {+/-} 3.2 vs DAWM: 43.3 {+/-} 2.1; t=13.2; p<0.0001, and 2) FWML: 32.5 {+/-} 3.9 vs DAWM: 38.8 {+/-} 1.7; t=9.8; p<0.0001. Similar results were obtained using the automatic derived masks in both datasets: 1) FWML: 35.8 {+/-} 2.8 vs DAWM: 43.1 {+/-} 1.6; t=15.3; p<0.0001, and 2) FWML: 31.3 {+/-} 3.1 vs DAWM: 38.1 {+/-} 1.5; t=12.8; p<0.0001. MTR was also significantly lower in manually derived DAWM masks compared with normal appearing white matter (NAWM) in both datasets: 1) NAWM: 46.7 {+/-} 1.3; t=10.1; p<0.0001, and 2) NAWM: 39.3 {+/-} 0.8; t=3.1; p=0.003. Similar results were obtained using the automatic derived masks in both datasets: 1) NAWM: 46.3 {+/-} 1.1; t=13.7; p<0.0001, and 2) NAWM: 39.9 {+/-} 1.1; t=9.6; p<0.0001.\n\nIn both datasets, manually derived FWML and DAWM MTR values showed significant correlations with normalized FLAIR (r=-0.35 to -0.67; p=0.06 to <0.0001), T2w (r=-0.60 to -0.72; p=0.003 to <0.0001), T1w/T2w (r=0.63 to 0.77; p=0.002 to <0.0001), and T1w (r=0.77 to 0.92; p<0.0001) intensities. Finally, normalized intensity values obtained using automatic derived masks were significantly correlated with the manually derived values in both datasets.\n\nConclusionsThe separation of FWML and DAWM on MRI scans of MS patients using automated intensity thresholds on T2w images is feasible. MTR values are significantly lower in FWML than DAWM, and DAWM values are significantly lower than NAWM, reflecting potentially greater demyelination within focal lesions. Normalized intensity values of different MRI contrasts exhibit a significant correlation with MTR values in both tissues of interest and could be used as a proxy to assess demyelination when MTR images are not available.

neuroscience↗

bioRxiv2018

Confidence as a diagnostic tool for perceptual aftereffects

Perceptual judgements are, by nature, a product of both sensation and the cognitive processes responsible for interpreting and reporting subjective experiences. Changed perceptual judgements may thus result from changes in how the world appears (perception), or subsequent interpretation (cognition). This ambiguity has led to persistent debates about how to interpret changes in decision-making, and if cognition can change how the world looks, or sounds, or feels. Here we introduce an approach that can help resolve these ambiguities. In three motion-direction experiments, we measured perceptual judgements and subjective confidence. Sensory encoding changes (i.e. the motion-direction aftereffect) impacted each measure equally, as the perceptual evidence informing both responses had changed. However, decision changes dissociated from reports of subjective uncertainty when non-perceptual effects changed decision-making. Our findings show that subjective confidence can provide important information about the cause of aftereffects, and can help inform us about the organisation of the mind.

neuroscience↗