Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can ...be constrained by boundaries and distorted by inhomogeneities, or to intrinsically discrete systems such as networks. To take into account locality, finiteness and discreteness, dynamical processes can be used to probe the space geometry and define its dimension. Here we show that each point in space can be assigned a relative dimension with respect to the source of a diffusive process, a concept that provides a scale-dependent definition for local and global dimension also applicable to networks. To showcase its application to physical systems, we demonstrate that the local dimension of structural protein graphs correlates with structural flexibility, and the relative dimension with respect to the active site uncovers regions involved in allosteric communication. In simple models of epidemics on networks, the relative dimension is predictive of the spreading capability of nodes, and identifies scales at which the graph structure is predictive of infectivity. We further apply our dimension measures to neuronal networks, economic trade, social networks, ocean flows, and to the comparison of random graphs.
Aberrant neural oscillations hallmark numerous brain disorders. Here, we first report a method to track the phase of neural oscillations in real-time via endpoint-corrected Hilbert transform (ecHT) ...that mitigates the characteristic Gibbs distortion. We then used ecHT to show that the aberrant neural oscillation that hallmarks essential tremor (ET) syndrome, the most common adult movement disorder, can be transiently suppressed via transcranial electrical stimulation of the cerebellum phase-locked to the tremor. The tremor suppression is sustained shortly after the end of the stimulation and can be phenomenologically predicted. Finally, we use feature-based statistical-learning and neurophysiological-modelling to show that the suppression of ET is mechanistically attributed to a disruption of the temporal coherence of the aberrant oscillations in the olivocerebellar loop, thus establishing its causal role. The suppression of aberrant neural oscillation via phase-locked driven disruption of temporal coherence may in the future represent a powerful neuromodulatory strategy to treat brain disorders.
TOR1A is the most common inherited form of dystonia with still unclear pathophysiology and reduced penetrance of 30–40%. ∆ETorA rats mimic the TOR1A disease by expression of the human TOR1A mutation ...without presenting a dystonic phenotype. We aimed to induce dystonia-like symptoms in male ∆ETorA rats by peripheral nerve injury and to identify central mechanism of dystonia development. Dystonia-like movements (DLM) were assessed using the tail suspension test and implementing a pipeline of deep learning applications. Neuron numbers of striatal parvalbumin+, nNOS+, calretinin+, ChAT+ interneurons and Nissl+ cells were estimated by unbiased stereology. Striatal dopaminergic metabolism was analyzed via in vivo microdialysis, qPCR and western blot. Local field potentials (LFP) were recorded from the central motor network. Deep brain stimulation (DBS) of the entopeduncular nucleus (EP) was performed. Nerve-injured ∆ETorA rats developed long-lasting DLM over 12 weeks. No changes in striatal structure were observed. Dystonic-like ∆ETorA rats presented a higher striatal dopaminergic turnover and stimulus-induced elevation of dopamine efflux compared to the control groups. Higher LFP theta power in the EP of dystonic-like ∆ETorA compared to wt rats was recorded. Chronic EP-DBS over 3 weeks led to improvement of DLM. Our data emphasizes the role of environmental factors in TOR1A symptomatogenesis. LFP analyses indicate that the pathologically enhanced theta power is a physiomarker of DLM. This TOR1A model replicates key features of the human TOR1A pathology on multiple biological levels and is therefore suited for further analysis of dystonia pathomechanism.
•Dystonia-like symptoms evolve in ∆ETorA rats after peripheral nerve injury.•Dystonic-like ∆ETorA rats show a striatal dopaminergic dysregulation.•Dystonic-like ∆ETorA rats have higher EP-LFP theta power, modulated by EP-DBS.•∆ETorA model dissociates genetic endophenotype from dystonic network alteration.
Cytokine storm during viral infection is a prospective predictor of morbidity and mortality, yet the cellular sources remain undefined. Here, using genetic and chemical tools to probe functions of ...the S1P
1 receptor, we elucidate cellular and signaling mechanisms that are important in initiating cytokine storm. Whereas S1P
1 receptor is expressed on endothelial cells and lymphocytes within lung tissue, S1P
1 agonism suppresses cytokines and innate immune cell recruitment in wild-type and lymphocyte-deficient mice, identifying endothelial cells as central regulators of cytokine storm. Furthermore, our data reveal immune cell infiltration and cytokine production as distinct events that are both orchestrated by endothelial cells. Moreover, we demonstrate that suppression of early innate immune responses through S1P
1 signaling results in reduced mortality during infection with a human pathogenic strain of influenza virus. Modulation of endothelium with a specific agonist suggests that diseases in which amplification of cytokine storm is a significant pathological component could be chemically tractable.
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► S1P
1 signaling inhibits cytokine storms, potentially fatal immune responses ► S1P
1 signaling in the endothelium protects mice from pathogenic human influenza ► In cytokine storms, cytokine production and leukocyte recruitment are separate events ► S1P
1 signaling suppresses chemokine production by pulmonary endothelial cells
The common flu virus can trigger potentially fatal immune reactions. In a surprising new role, endothelial cells of the lung express a potentially targetable receptor that suppresses this response.
Abstract
Phase synchronizations in models of coupled oscillators such as the Kuramoto model have been widely studied with pairwise couplings on arbitrary topologies, showing many unexpected dynamical ...behaviors. Here, based on a recent formulation the Kuramoto model on weighted simplicial complexes with phases supported on simplices of any order
k
, we introduce linear and non-linear frustration terms independent of the orientation of the
k
+ 1 simplices, as a natural generalization of the Sakaguchi-Kuramoto model to simplicial complexes. With increasingly complex simplicial complexes, we study the the dynamics of the edge simplicial Sakaguchi-Kuramoto model with nonlinear frustration to highlight the complexity of emerging dynamical behaviors. We discover various dynamical phenomena, such as the partial loss of synchronization in subspaces aligned with the Hodge subspaces and the emergence of simplicial phase re-locking in regimes of high frustration.
The intrinsic temporality of learning demands the adoption of methodologies capable of exploiting time-series information. In this study we leverage the sequence data framework and show how ...data-driven analysis of temporal sequences of task completion in online courses can be used to characterise personal and group learners' behaviors, and to identify critical tasks and course sessions in a given course design. We also introduce a recently developed probabilistic Bayesian model to learn sequential behaviours of students and predict student performance. The application of our data-driven sequence-based analyses to data from learners undertaking an on-line Business Management course reveals distinct behaviors within the cohort of learners, identifying learners or groups of learners that deviate from the nominal order expected in the course. Using course grades a posteriori, we explore differences in behavior between high and low performing learners. We find that high performing learners follow the progression between weekly sessions more regularly than low performing learners, yet within each weekly session high performing learners are less tied to the nominal task order. We then model the sequences of high and low performance students using the probablistic Bayesian model and show that we can learn engagement behaviors associated with performance. We also show that the data sequence framework can be used for task-centric analysis; we identify critical junctures and differences among types of tasks within the course design. We find that non-rote learning tasks, such as interactive tasks or discussion posts, are correlated with higher performance. We discuss the application of such analytical techniques as an aid to course design, intervention, and student supervision.
The sphingosine‐1‐phosphate 1 receptor (S1P1R) is expressed by lymphocytes, dendritic cells, and vascular endothelial cells and plays a role in the regulation of chronic inflammation and lymphocyte ...egress from peripheral lymphoid organs. Ozanimod is an oral selective modulator of S1P1R and S1P5R receptors in clinical development for the treatment of chronic immune‐mediated, inflammatory diseases. This first‐in‐human study characterized the safety, pharmacokinetics (PK), and pharmacodynamics (PD) of ozanimod in 88 healthy volunteers using a range of single and multiple doses (7 and 28 days) and a dose‐escalation regimen. Ozanimod was generally well tolerated up to a maximum single dose of 3 mg and multiple doses of 2 mg/d, with no severe adverse events (AEs) and no dose‐limiting toxicities. The most common ozanimod‐related AEs included headache, somnolence, dizziness, nausea, and fatigue. Ozanimod exhibited linear PK, high steady‐state volume of distribution (73–101 L/kg), moderate oral clearance (204–227 L/h), and an elimination half‐life of approximately 17 to 21 hours. Ozanimod produced a robust dose‐dependent reduction in total peripheral lymphocytes, with a median decrease of 65% to 68% observed after 28 days of dosing at 1 and 1.5 mg/d, respectively. Ozanimod selectivity affected lymphocyte subtypes, causing marked decreases in cells expressing CCR7 and variable decreases in subsets lacking CCR7. A dose‐dependent negative chronotropic effect was observed following the first dose, with the dose‐escalation regimen attenuating the first‐dose negative chronotropic effect. Ozanimod safety, PK, and PD properties support the once‐daily regimens under clinical investigation.
To characterise the longitudinal dynamics of C-reactive protein (CRP) and Procalcitonin (PCT) in a cohort of hospitalised patients with COVID-19 and support antimicrobial decision-making. ...Longitudinal CRP and PCT concentrations and trajectories of 237 hospitalised patients with COVID-19 were modelled. The dataset comprised of 2,021 data points for CRP and 284 points for PCT. Pairwise comparisons were performed between: (i) those with or without significant bacterial growth from cultures, and (ii) those who survived or died in hospital. CRP concentrations were higher over time in COVID-19 patients with positive microbiology (day 9: 236 vs 123 mg/L, p < 0.0001) and in those who died (day 8: 226 vs 152 mg/L, p < 0.0001) but only after day 7 of COVID-related symptom onset. Failure for CRP to reduce in the first week of hospital admission was associated with significantly higher odds of death. PCT concentrations were higher in patients with COVID-19 and positive microbiology or in those who died, although these differences were not statistically significant. Both the absolute CRP concentration and the trajectory during the first week of hospital admission are important factors predicting microbiology culture positivity and outcome in patients hospitalised with COVID-19. Further work is needed to describe the role of PCT for co-infection. Understanding relationships of these biomarkers can support development of risk models and inform optimal antimicrobial strategies.
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