Biology subjects

Kraut, M.

Publications and source records attributed to Kraut, M..

6 recordsLinked to original sources

bioRxiv2020

THE INFLUENCE OF PRE-SUPPLEMENTARY MOTOR AREA TARGETED HIGH-DEFINITION TRANSCRANIAL DIRECT CURRENT STIMULATION ON INHIBITORY CONTROL

AO_SCPLOWBSTRACTC_SCPLOWThe neural underpinnings of inhibitory control, an executive cognitive control function, has been a topic of interest for several decades due to both its clinical significance and the maturation of cognitive science disciplines. Behavioral, imaging, and electrophysiological studies suggest that the pre-supplementary motor area (preSMA) serves as a primary hub in a network of regions engaged in inhibition. High-definition transcranial direct current stimulation (HD-tDCS) allows us to modulate neural function to assess cortical contribution to cognitive functioning. The present study targeted HD-tDCS modulation of preSMA to affect inhibition. Participants were randomly assigned to receive 20 min of Sham, Anodal, or Cathodal stimulation prior to completing a semantically cued go/nogo task while electroencephalography (EEG) data were recorded. Both anodal and cathodal stimulation improved inhibitory performance as measured by faster reaction times and increased (greater negative) N2 event-related potentials (ERPs). In contrast, the Sham group did not show such changes. We did not find support for the anodal/cathodal dichotomy for HD neural stimulation. These findings constitute an early investigation into role of the preSMA in inhibitory control and in exploring application of HD-tDCS to the preSMA in order to improve inhibitory control.

neuroscience↗

bioRxiv2020

Swarm Learning as a privacy-preserving machine learning approach for disease classification

Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis and COVID-19 is an important goal of precision medicine. We recently illustrated that leukemia patients are identified by machine learning (ML) based on their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, blockchain-based peer-to-peer networking and coordination as well as privacy protection without the need for a central coordinator thereby going beyond federated learning. Using more than 14,000 blood transcriptomes derived from over 100 individual studies with non-uniform distribution of cases and controls and significant study biases, we illustrate the feasibility of SL to develop disease classifiers based on distributed data for COVID-19, tuberculosis or leukemias that outperform those developed at individual sites. Still, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

bioinformatics↗

bioRxiv2020

Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

Despite the epidemics of chronic obstructive pulmonary disease (COPD), the cellular and molecular mechanisms of this disease are far from being understood. Here, we characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for: machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort. These high-resolution approaches revealed: massive transcriptional plasticity of macrophages in the alveolar space with increased levels of invading and proliferating cells, loss of MHC expression, reduced cellular motility, altered lipid metabolism, and a metabolic shift reminiscent of mitochondrial dysfunction in COPD patients. Collectively, single-cell omics of multi-tissue samples was used to build the first cellular and molecular framework for COPD pathophysiology as a prerequisite to develop molecular biomarkers and causal therapies against this deadly disease.

systems biology↗

bioRxiv2019

Disrupted neural synchrony mediates the relationship between white matter integrity and cognitive performance in older adults.

Our main goal was to determine the influence of white matter integrity on the dynamic coupling between brain regions and the individual variability of cognitive performance in older adults. EEG was recorded while participants performed a task specifically designed to engage working memory and inhibitory processes, and the associations among functional activity, structural integrity, and cognitive performance were assessed. We found that the association between white matter microstructural integrity and cognitive functioning with aging is mediated by time-varying alpha and gamma phase-locking value (PLV). Specifically, older individuals with better preservation of the inferior fronto-occipital fasciculus showed greater task-related modulations of alpha and gamma long-range PLV between the inferior frontal gyrus and occipital lobe, lower local phase-amplitude coupling in occipital lobes, and better cognitive control performance. Our results help delineate the role of individual variability of white matter microstructure in dynamic synchrony and cognitive performance during normal aging, and show that even small reductions in white matter integrity can lead to altered communications between brain regions, which in turn can result in reduced efficiency of cognitive functioning. Significance statementCognitive aging is associated with large individual differences, as some individuals maintain cognitive performance similar to that of young adults while others are significantly impaired. We hypothesized that individual differences in white matter integrity would influence the functional synchrony between frontal and posterior brain regions, and cognitive performance in older adults. We found that the association between reduced tract integrity and worse cognitive performance in older adults was mediated by task-related modulations of coupling synchrony in the alpha and gamma bands. Results offer a mechanistic explanation for the neural basis of the variability of cognitive performance in older adults who do not have any clinically diagnosable neuropathology, and for the association between structural network integrity and cognition in older adults.

neuroscience↗

bioRxiv2019

Identification of selection and inhibition components in a go/nogo task from EEG spectra using a machine learning model

AO_SCPLOWBSTRACTC_SCPLOWPrior Go/NoGo studies have localized specific regions and EEG spectra for which traditional approaches have distinguished between Go and NoGo conditions. A more detailed characterization of the spatial distribution and timing of the synchronization of frequency bands would contribute substantially to the clarification of neural mechanisms that underlie performance of the Go/NoGo task. The present study used a machine learning approach to learn the features that distinguish between ERSPs involved in selection and inhibition in a Go/NoGo task. A neural network classifier was used to predict task conditions for each subject to characterize ERSPs associated with Go versus NoGo trials. The final model accurately identified individual task conditions at an overall rate of 92%, estimated by 5-fold cross-validation. The detailed accounting of EEG time-frequency patterns localized to brain sources (i.e., thalamus, preSMA, orbitofrontal cortex, and superior parietal cortex) provides elaboration on previous findings from fMRI and EEG studies and more information about EEG power changes in multiple frequency bands (i.e., primarily theta power increase, alpha decreases, and beta increases and decreases) within these regions underlying the selection and inhibition processes engaged in the Go and NoGo trials. This extends previous findings, providing more information about neural mechanisms underlying selection and inhibition processes engaged in the Go and NoGo trials, respectively, and may offer insight into therapeutic uses of neuromodulation in neural dysfunction.

neuroscience↗

bioRxiv2017

Cellular reprogramming of human monocytes is regulated by time-dependent IL4 signalling and NCOR2

The clinical and therapeutic value of human in vitro generated monocyte-derived dendritic cell (moDC) and macrophages is well established. However, in line with recent findings regarding myeloid cell ontogeny and due to our limited understanding of their physiological counterparts, transcriptional regulation and heterogeneity, the full potential of these important cellular systems is still underestimated.\n\nIn this study, we use cutting edge high-dimensional analysis methods to better understand the transcriptional organization, phenotypic heterogeneity and functional differences between human ex vivo isolated and in vitro generated mononuclear phagocytes with the aim to better realize their full potential in the clinic.\n\nWe demonstrate that human monocytes activated by MCSF or GMCSF most closely resemble inflammatory macrophages identified in vivo, while IL4 signalling in the presence of GMCSF generates moDCs resembling inflammatory DCs in vivo, but not steady state cDC1 or cDC2. Moreover, these reprogramming regimes lead to activated monocytes that present with profoundly different transcriptomic, metabolic, phenotypic and functional profiles. Furthermore, we demonstrate that CD14+ monocytes are integrating multiple exogenous activation signals such as GMCSF and IL4 in a combinatorial and temporal fashion, resulting in a high-dimensional cellular continuum of reprogrammed monocytes dependent on the mode and timing of cytokine exposure. Utilizing nanostraw-based knockdown technology, we demonstrate that the IL4-dependent generation of moDCs relies on the induction, nuclear localization and function of the transcriptional regulator NCOR2.\n\nFinally, we unravel unappreciated heterogeneity within the clinically moDCs population and propose a novel high-dimensional phenotyping strategy to better tailor clinical quality control strategies for patient need and culture conditions to enhance therapeutic outcome.

immunology↗