Biology subjects

Richard, G.

Publications and source records attributed to Richard, G..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

DeepImageTranslator: a free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis

ObjectivesThe advent of deep-learning has set new standards in an array of image translation applications. At present, the use of these methods often requires computer programming experience. Non-commercial programs with graphical interface usually do not allow users to fully customize their deep-learning pipeline. Therefore, our primary objective is to provide a simple graphical interface that allows students and researchers with no programming experience to easily create, train, and evaluate custom deep-learning models for image translation. We also aimed to test the applicability of our tool (the DeepImageTranslator) in two different tasks: semantic segmentation and noise reduction of CT images. MethodsThe DeepImageTranslator was implemented using the Tkinter library; backend computations were implemented using Pillow, Numpy, OpenCV, Augmentor, Tensorflow, and Keras libraries. Convolutional neural networks (CNNs) were trained using DeepImageTranslator and assessed with three-way cross-validation. The effects of data augmentation, deep-supervision, and sample size on model accuracy were also systematically assessed. ResultsThe DeepImageTranslator a simple tool that allows users to customize all aspects of their deep-learning pipeline, including the CNN, the training optimizer, the loss function, and the types of training image augmentation scheme. We showed that DeepImageTranslator can be used to achieve state-of-the-art accuracy and generalizability in semantic segmentation and noise reduction. Highly accurate 3D segmentation models for body composition can be obtained using training sample sizes as small as 17 images. Therefore, for studies with small datasets, researchers can randomly select a very small subset of images for manual labeling, which can then be used to train a specialized CNN model with DeepImageTranslator to fully automate segmentation of the entire dataset, thereby saving tremendous time and effort. ConclusionsAn open-source deep-learning tool for accurate image translation with a user-friendly graphical interface was presented and evaluated. This standalone software can be downloaded for Windows 10 at: https://sourceforge.net/projects/deepimagetranslator/

bioinformatics↗

bioRxiv2021

Long distance runners in the marine realm: New insights into genetic diversity, kin relationships and social fidelity of Indian Ocean male sperm whales

BackgroundAdult male sperm whales (Physeter macrocephalus) are long distance runners of the marine realm, feeding in high latitudes and mating in tropical and subtropical waters where stable social groups of females and immatures live. Several areas of uncertainty still limit our understanding of their social and breeding behaviour, in particular concerning the potential existence of geographical and/or social fidelities. In this study, using underwater observation and sloughed-skin sampling, we looked for male social fidelity to a specific matrilineal sperm whale group near Mauritius. In addition, we captured a wider picture of kin relationships and genetic diversity of male sperm whales in the Indian Ocean thanks to biopsies of eight unique individuals taken in a feeding ground near the Kerguelen and Crozet Archipelagos (Southern Indian Ocean). ResultsTwenty-six adult male sperm whales, of which 13 were sampled, were identified when socializing with adult females and immatures off Mauritius. Long-term underwater observation recorded several noteworthy social interactions between adult males and adult females and/or immatures. We identified seven possible male recaptures over different years (three by direct observation, and four at the gametic level), which supports a certain level of male social fidelity. Several first- and second-degree kin relationships were highlighted between members of the social unit and adult males, confirming that some of the adult males observed in Mauritian waters are reproductive. Male social philopatry to their natal group can be excluded, as none of the males sampled shared the haplotype characteristic of the matrilineal social group. Mitochondrial DNA control region haplotype and nucleotide diversities calculated over the 21 total male sperm whales sampled were similar to values found by others in the Indian Ocean. ConclusionsOur study strongly supports the existence of some levels of male sperm whale social fidelity, not directed to their social group of birth, in the Indian Ocean. Males sampled in breeding and feeding grounds are linked by kin relationships. Our results support a model of male mediated gene flow occurring at the level of the whole Indian Ocean, likely interconnected with large-scale geographical fidelity to ocean basin, and a small-scale social fidelity to matrilineal social groups.

ecology↗

bioRxiv2021

The genome sequence of the cereal pest Sitophilus oryzae: an unprecedented transposable element content

BackgroundThe rice weevil Sitophilus oryzae is one of the most important agricultural pests, causing extensive damage to cereal in fields and to stored grains. S. oryzae has an intracellular symbiotic relationship (endosymbiosis) with the Gram-negative bacterium Sodalis pierantonius and is a valuable model to decipher host-symbiont molecular interactions. ResultsWe sequenced the Sitophilus oryzae genome using a combination of short and long reads to produce the best assembly for a Curculionidae species to date. We show that S. oryzae has undergone successive bursts of transposable element (TE) amplification, representing 72% of the genome. In addition, we show that many TE families are transcriptionally active, and changes in their expression are associated with insect endosymbiotic state. S. oryzae has undergone a high gene expansion rate, when compared to other beetles. Reconstruction of host-symbiont metabolic networks revealed that, despite its recent association with cereal weevils (30 Kyear), S. pierantonius relies on the host for several amino acids and nucleotides to survive and to produce vitamins and essential amino-acids required for insect development and cuticle biosynthesis. ConclusionsHere we present the genome of an agricultural pest beetle, which may act as a foundation for pest control. In addition, S. oryzae may be a useful model for endosymbiosis, and studying TE evolution and regulation, along with the impact of TEs on eukaryotic genomes.

genomics↗

bioRxiv2020

Women with a history of previous childbirths show less evident white matter brain ageing

Maternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter (WM) and WM ageing trajectories later in life. Utilising global and regional brain-age prediction based on multi-shell diffusion MRI data, we investigated the association between previous childbirths and WM brain age in 8,895 women in the UK Biobank cohort (age range = 54 - 81 years). The results showed that number of previous childbirths was negatively associated with WM brain age, potentially indicating a protective effect of parity on brain WM later in life. Both global WM and grey matter brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global WM association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain WM characteristics later in life, longitudinal studies are required to establish causality and determine how parity may influence womens WM trajectories across the lifespan.

neuroscience↗

bioRxiv2020

Brain disconnectivity mapping of post-stroke fatigue

Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remain unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual brain disconnectome maps in 84 stroke survivors in the chronic phase ([≥] 3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue are not simply explained by lesion characteristics or brain disconnectome measures in stroke patients in a chronic phase, and are discussed in light of methodological considerations.

neuroscience↗

bioRxiv2020

Long-reads assembly of the Brassica napus reference genome, Darmor-bzh

BackgroundThe combination of long-reads and long-range information to produce genome assemblies is now accepted as a common standard. This strategy not only allow to access the gene catalogue of a given species but also reveals the architecture and organisation of chromosomes, including complex regions like telomeres and centromeres. The Brassica genus is not exempt and many assemblies based on long reads are now available. The reference genome for Brassica napus, Darmor-bzh, which was published in 2014, has been produced using short-reads and its contiguity was extremely low if compared to current assemblies of the Brassica genus. FindingsHere, we report the new long-reads assembly of Darmor-bzh genome (Brassica napus) generated by combining long-reads sequencing data, optical and genetic maps. Using the PromethION device and six flowcells, we generated about 16M long-reads representing 93X coverage and more importantly 6X with reads longer than 100Kb. This ultralong-reads dataset allows us to generate one of the most contiguous and complete assembly of a Brassica genome to date (contigs N50 > 10Mb). In addition, we exploited all the advantages of the nanopore technology to detect modified bases and sequence transcriptomic data using direct RNA to annotate the genome and focus on resistance genes. ConclusionUsing these cutting edge technologies, and in particular by relying on all the advantages of the nanopore technology, we provide the most contiguous Brassica napus assembly, a resource that will be valuable for the Brassica community for crop improvement and will facilitate the rapid selection of agronomically important traits.

genomics↗

bioRxiv2020

Evidence for reduced long-term potentiation-like visual cortical plasticity in schizophrenia and bipolar disorder

BackgroundSeveral lines of research suggest that impairments in long-term potentiation (LTP)-like synaptic plasticity might be a key pathophysiological mechanism in schizophrenia (SZ) and bipolar disorder type I (BDI) and II (BDII). Using modulations of visually evoked potentials (VEP) of the electroencephalogram, impaired LTP-like visual cortical plasticity has been implicated in patients with BDII, while there has been conflicting evidence in SZ, a lack of research in BDI, and mixed results regarding associations with symptom severity, mood states, and medication. MethodsWe measured the VEP of patients with SZ spectrum disorders (n=31), BDI (n=34), BDII (n=33), and other BD spectrum disorders (n=2), and age-matched healthy control participants (n=200) before and after prolonged visual stimulation. ResultsCompared to healthy controls, modulation of VEP component N1b, but not C1 or P1, was impaired both in patients within the SZ spectrum ({chi}2=35.1, p=3.1x10-9) and BD spectrum ({chi}2=7.0, p=8.2x10-3), including BDI ({chi}2=6.4, p=0.012), but not BDII ({chi}2=2.2, p=0.14). N1b modulation was also more severely impaired in SZ spectrum than BD spectrum patients ({chi}2=14.2, p=1.7x10-4). The reduction in N1b modulation was related to PANSS total scores ({chi}2=10.8, p=1.0x10-3), and nominally to number of psychotic episodes ({chi}2=4.9, p=0.027). Conclusions. These results suggest that LTP-like plasticity is impaired in SZ and BDI, but not BDII, and related to psychotic symptom severity. Adding to previous genetic, pharmacological, and anatomical evidence, these results implicate aberrant synaptic plasticity as a mechanism underlying SZ and BD.

neuroscience↗

bioRxiv2020

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilks theorem analysis showed that the FA fine metric of the RSI model and orientation dispersion (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.

neuroscience↗

bioRxiv2020

Experience-dependent modulation of the visual evoked potential: testing effect sizes, retention over time, and associations with age in 415 healthy individuals

Experience-dependent modulation of the visual evoked potential (VEP) is a promising proxy measure of synaptic plasticity in the cerebral cortex. However, existing studies are limited by small to moderate sample sizes as well as by considerable variability in how VEP modulation is quantified. In the present study, we used a large sample (n = 415) of healthy volunteers to compare different quantifications of VEP modulation with regards to effect sizes and retention of the modulation effect over time. We observed significant modulation for VEP components C1 (Cohens d = 0.53), P1 (d = 0.66), N1 (d = -0.27), N1b (d = -0.66), but not P2 (p = 0.1), and in one time-frequency cluster (~30 Hz and ~70 ms post-stimulus; d = -0.48), 2-4 minutes after 2 Hz prolonged visual stimulation. For components N1 (d = -0.21) and N1b (d = -0.38), as well for the time-frequency cluster (d = -0.33), this effect was retained after 54-56 minutes. Moderate to high correlations ({rho} = [0.39, 0.69]) between modulation at different postintervention blocks revealed a relatively high temporal stability in the modulation effect for each VEP component. However, different VEP components also showed markedly different temporal retention patterns. Finally, P1 modulation correlated positively with age (t = 5.26), and was larger for female participants (t = 3.91), with no effects of either age or sex on N1 and N1b potentiation. These results provide strong support for VEP modulation, and especially N1b modulation, as a robust measure of synaptic plasticity, but underscore the need to differentiate between components, and to control for demographic confounders.

neuroscience↗

bioRxiv2019

TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients: Case-control differences, reliability, and sensitivity to cognitive training

Attentional deficits following stroke are common and pervasive, and are important predictors for functional recovery. Attentional functions comprise a set of specific cognitive processes allowing to attend, filter and select among a continuous stream of stimuli. These mechanisms are fundamental for more complex cognitive functions such as learning, planning and cognitive control, all crucial for daily functioning, including social interactions. The distributed functional neuroanatomy of these processes is a likely explanation for the high prevalence of attentional impairments following stroke, and underscores the importance of a clinical implementation of computational approaches allowing for sensitive and specific modeling of attentional sub-processes. The Theory of Visual Attention (TVA) offers a theoretical, computational, neuronal and practical framework to assess the efficiency of visual selection performance and parallel processing of multiple objects. Here, using a whole-report experimental paradigm in a cross-sectional case-control comparison and in six repeated assessments over the course of a three-week intensive computerized cognitive training (CCT) intervention in chronic stroke patients (> 6 months since hospital admission, NIHSS < 7 at hospital discharge), we assessed the sensitivity and reliability of TVA parameters reflecting short-term memory capacity (K), processing speed (C) and perceptual threshold (t0). Cross-sectional group comparisons documented lower short-term memory capacity, slower processing speed and higher perceptual threshold in patients compared to age-matched healthy controls. Further, longitudinal analyses revealed high reliability of the TVA parameters in stroke patients, and higher processing speed at baseline was associated with larger cognitive benefits of the CCT. The results support the feasibility, reliability and sensitivity of TVA-based assessment of attentional functions in chronic stroke patients.

neuroscience↗

bioRxiv2019

Clinical utility of brain age prediction in stroke patients: A longitudinal study

Cognitive deficits are important predictors for outcome, independence and quality of life after stroke, but often remain unnoticed and unattended because other impairments are more evident. Computerized cognitive training (CCT) is among the candidate interventions that may alleviate cognitive difficulties, but the evidence supporting its feasibility and effectiveness is scarce, partly due to the lack of tools for outcome prediction and monitoring. Magnetic resonance imaging (MRI) provides candidate markers for disease monitoring and outcome prediction. By integrating information not only about lesion extent and localization, but also regarding the integrity of the unaffected parts of the brain, advanced MRI provides relevant information for developing better prediction models in order to tailor cognitive intervention for patients, especially in a chronic phase.\n\nUsing brain age prediction based on MRI based brain morphometry and machine learning, we tested the hypotheses that stroke patients with a younger-appearing brain relative to their chronological age perform better on cognitive tests and benefit more from cognitive training compared to patients with an older-appearing brain. In this randomized double-blind study, 54 patients who suffered mild stroke (>6 months since hospital admission, NIHSS<7 at hospital discharge) underwent 3-weeks CCT and MRI before and after the intervention. In addition, patients were randomized to one of two groups receiving either active or sham transcranial direct current stimulation (tDCS). We tested for main effects of brain age gap (estimated age - chronological age) on cognitive performance, and associations between brain age gap and task improvement. Finally, we tested if longitudinal changes in brain age gap during the intervention were sensitive to treatment response. Briefly, our results suggest that longitudinal brain age prediction based on automated brain morphometry is feasible and reliable in stroke patients. However, no significant association between brain age and both performance and response to cognitive training were found.

neuroscience↗

bioRxiv2019

Selection following gene duplication shapes recent genome evolution in the pea aphid Acyrthosiphon pisum

Ecology of insects is as wide as their diversity, which reflects their high capacity of adaptation in most of the environments of our planet. Aphids, with over 4,000 species, have developed a series of adaptations including a high phenotypic plasticity and the ability to feed on the phloem-sap of plants, which is enriched in sugars derived from photosynthesis. Recent analyses of aphid genomes have indicated a high level of shared ancestral gene duplications that might represent a basis for genetic innovation and broad adaptations. In addition, there is a large number of recent, species-specific gene duplications whose role in adaptation remains poorly understood. Here, we tested whether duplicates specific to the pea aphid Acyrthosiphon pisum are related to genomic innovation by combining comparative genomics, transcriptomics, and chromatin accessibility analyses. Consistent with large levels of neofunctionalization, we found that most of the recent pairs of gene duplicates evolved asymmetrically, showing divergent patterns of positive selection and gene expression. Genes under selection involved a plethora of biological functions, suggesting that neofunctionalization and tissue specificity, among other evolutionary mechanisms, have orchestrated the evolution of recent paralogs in the pea aphid and may have facilitated host-symbiont cooperation. Our comprehensive phylogenomics analysis allowed to tackle the history of duplicated genes to pave the road towards understanding the role of gene duplication in ecological adaptation.

genomics↗

bioRxiv2019

Functional brain network modeling in sub-acute stroke patients and healthy controls during rest and continuous attentive tracking

A cerebral stroke is characterized by compromised brain function due to an interruption in cerebrovascular blood supply. Although stroke incurs focal damage determined by the vascular territory affected, clinical symptoms commonly involve multiple functions and cognitive faculties that are insufficiently explained by the focal damage alone. Functional connectivity (FC) refers to the synchronous activity between spatially remote brain regions organized in a network of interconnected brain regions. Functional magnetic resonance imaging (fMRI) has advanced this system-level understanding of brain function, elucidating the complexity of stroke outcomes, as well as providing information useful for prognostic and rehabilitation purposes.\n\nWe tested for differences in brain network connectivity between a group of patients with minor ischemic strokes in sub-acute phase (n=44) and matched controls (n=100). As neural network configuration is dependent on cognitive effort, we obtained fMRI data during rest and two load levels of a multiple object tacking (MOT) task. Network nodes and time-series were estimated using independent component analysis (ICA) and dual regression, with network edges defined as the partial temporal correlations between node pairs. The full set of edgewise FC went into a cross-validated regularized linear discriminant analysis (rLDA) to classify groups and cognitive load.\n\nMOT task performance and cognitive tests revealed no significant group differences. While multivariate machine learning revealed high sensitivity to experimental condition, with classification accuracies between rest and attentive tracking approaching 100%, group classification was at chance level, with negligible differences between conditions. Repeated measures ANOVA showed significantly stronger synchronization between a temporal node and a sensorimotor node in patients across conditions. Overall, the results revealed high sensitivity of FC indices to task conditions, and suggest relatively small brain network-level disturbances after clinically mild strokes.

neuroscience↗

bioRxiv2019

Brain age prediction reveals aberrant brain white matter in schizophrenia and bipolar disorder: A multi-sample diffusion tensor imaging study

BackgroundSchizophrenia (SZ) and bipolar disorders (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, BD, and healthy controls across 10 cohorts. MethodsWe trained six cross-validated models using different combinations of DTI data from 927 healthy controls (HC, 18-94 years), and applied the models to the test sets including 648 SZ (18-66 years) patients, 185 BD patients (18-64 years), and 990 HC (17-68 years), estimating brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results. Results10-fold cross-validation revealed high accuracy for all models. Compared to controls, the model including all feature sets significantly over-estimated the age of patients with SZ (d=-.29) and BD (d=.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy (FA) based models showed larger group differences than the models based on other DTI-derived metrics. ConclusionsBrain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

neuroscience↗

bioRxiv2019

A randomized, double blind study of computerized cognitive training in combination with transcranial direct current stimulation (tDCS) in stroke patients - utility of fMRI as marker for training outcome

Computerized cognitive training (CCT) combined with transcranial direct current stimulation (tDCS) has showed some promise in alleviating cognitive impairments in patients with brain disorders, but the robustness and possible mechanisms are unclear. In this prospective double-blind randomized clinical trial, we investigated the feasibility and effectiveness of combining CCT and tDCS, and tested the predictive value of and training-related changes in fMRI-based brain activation during attentive performance (multiple object tracking) obtained at inclusion, before initiating training, and after the three-weeks intervention in chronic stroke patients (> 6 months since hospital admission). Patients were randomized to one of two groups, receiving CCT and either (1) tDCS targeting left dorsolateral prefrontal cortex (1 mA), or (2) sham tDCS, with 40s active stimulation (1 mA) before fade out of the current. 77 patients were enrolled in the study, 54 completed the cognitive training, and 48 completed all training and MRI sessions. We found significant improvement in performance across all trained tasks, but no additional gain of tDCS. fMRI-based brain activation showed high reliability, and higher cognitive performance was associated with increased tracking-related activation in the dorsal attention network (DAN) and default mode network (DMN) as well as anterior cingulate after compared to before the intervention. We found no significant associations between cognitive gain and brain activation measured before training or in the difference in activation after intervention. Combined, these results show significant training effects on trained cognitive tasks in stroke survivors, with no clear evidence of additional gain of concurrent tDCS.

neuroscience↗

bioRxiv2019

Coxiella burnetii epitope-specific T-cell responses in chronic Q fever patients

Infection with Coxiella burnetii, the causative agent of Q fever, can result in life-threatening persistent infection. Reactogenicity hinders worldwide implementation of the only licensed human Q fever vaccine. We previously demonstrated long-lived immunoreactivity in individuals with past symptomatic and asymptomatic Coxiella infection (convalescents) to promiscuous HLA-class II C. burnetii epitopes, providing the basis for a novel T-cell-targeted subunit vaccine. Here we investigated in a cohort of 22 individuals with persistent infection (chronic Q fever) whether they recognize the same set of epitopes, or distinct epitopes that could be candidates for a therapeutic vaccine or aid in the diagnosis of persistent infection.\n\nIndividuals with chronic Q fever showed strong class II epitope-specific cultured ELISpot responses largely overlapping with the peptide repertoire identified previously for convalescents. Five additional peptides were recognized more frequently by chronic subjects, but there was no combination of epitopes uniquely recognized by or non-reactive in chronic Q fever subjects. Consistent with more recent/prolonged exposure, we found, however, stronger direct ex vivo responses to whole-cell C. burnetii and individual peptides in direct ELISpot than in convalescents.\n\nIn conclusion, we have validated and expanded a previously published set candidate epitopes for a novel T-cell targeted subunit Q fever vaccine in the context of chronic Q fever patients and demonstrated that they successfully mounted a T-cell response comparable to that of convalescents. Finally, we demonstrate that individuals treated for chronic Q fever mount a broader ex vivo response to class II epitopes than convalescents, which could be explored for diagnostic purposes.

immunology↗

bioRxiv2019

Dissecting the cognitive phenotype of post-stroke fatigue using drift diffusion modeling of sustained attention

Post-stroke fatigue (PSF) is a prevalent symptom among stroke patients. Its symptom burden is pervasive, persistent and associated with poor rehabilitation outcomes, though its mechanisms are poorly understood. Many patients with PSF experience cognitive difficulties, but studies aiming to identify cognitive correlates of PSF have been largely inconclusive. In contrast to conventional neuropsychological assessment, computational modeling of behavioral data allows for a dissection of specific cognitive processes associated with group or individual differences in fatigue. With the aim to zero in on the cognitive phenotype of PSF, we fitted a hierarchical drift diffusion model (hDDM) to response time data from Attention Network Test (ANT) obtained from 53 chronic stroke patients. The computational model accurately reconstructed the individual level response time distributions in the different ANT conditions, and hDDM regressions identified an interaction between trial number and fatigue symptoms on non-decision time, intuitively indicating that the cognitive phenotype of fatigue entails an increased vulnerability to sustained attentional effort. These novel results demonstrate the significance of considering the sustained nature of cognitive effort when defining the cognitive phenotype of post-stroke fatigue, and suggest that the use of computational approaches offers a further characterization of the specific processes underlying observed behavioral differences.

neuroscience↗

bioRxiv2019

Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling

Genome rearrangements that occur during evolution impose major challenges on regulatory mechanisms that rely on three-dimensional genome architecture. Here, we developed a scaffolding algorithm and generated chromosome-length assemblies from Hi-C data for studying genome topology in three distantly related Drosophila species. We observe extensive genome shuffling between these species with one synteny breakpoint after approximately every six genes. A/B compartments, a set of large gene-dense topologically associating domains (TADs) and spatial contacts between high-affinity sites (HAS) located on the X chromosome are maintained over 40 million years, indicating architectural conservation at various hierarchies. Evolutionary conserved genes cluster in the vicinity of HAS, while HAS locations appear evolutionarily flexible, thus uncoupling functional requirement of dosage compensation from individual positions on the linear X chromosome. Therefore, 3D architecture is preserved even in scenarios of thousands of rearrangements highlighting its relevance for essential processes such as dosage compensation of the X chromosome.

genomics↗