We used quantified electroencephalography (qEEG) to define the features of encephalopathy in patients released from the intensive care unit after severe illness from COVID-19. Artifact-free 120–300 s epoch lengths were visually identified and divided into 1 s windows with 10% overlap. Differential channels were grouped by frontal, parieto-occipital, and temporal lobes. For every channel and window, the power spectrum was calculated and used to compute the area for delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands. Furthermore, Shannon’s spectral entropy (SSE) and synchronization by Pearson’s correlation coefficient (ρ) were computed; cases of patients diagnosed with either infectious toxic encephalopathy (ENC) or post-cardiorespiratory arrest (CRA) encephalopathy were used for comparison. Visual inspection of EEGs of COVID patients showed a near-physiological pattern with scarce anomalies. The distribution of EEG bands was different for the three groups, with COVID midway between distributions of ENC and CRA; specifically, temporal lobes showed different distribution for EEG bands in COVID patients. Besides, SSE was higher and hemispheric connectivity lower for COVID. We objectively identified some numerical EEG features in severely ill COVID patients that can allow positive diagnosis of this encephalopathy.

Profilin has been implicated in cell motility and in a variety of cellular processes, such as membrane extension, endocytosis, and formation of focal complexes. In vivo, profilin replenish the pool of ATP-actin monomers by increasing the rate of nucleotide exchange of ADP-actin for ATP-actin, promoting the incorporation of new actin monomers at the barbed end of actin filaments. For this report, we generated a membrane-permeable version of profilin I (PTD4-PfnI) for the alteration of intracellular profilin levels taking advantage of the protein transduction technique. We show that profilin I induces lamellipodia formation independently of growth factor presence in primary bovine trabecular meshwork (BTM) cells. The effects are time- and concentration-dependent and specific to the profilin I isoform. Profilin II, the neuronal isoform, failed to extend lamellipodia in the same degree as profilin I. H133S, a mutation in the polyproline binding domain, showed a reduced ability to induce lamellipodia. H199E, mutation in the actin binding domain failed to induce membrane spreading and inhibit fetal bovine serum (FBS) -induced lamellipodia extension. Incubation with a synthetic polyproline domain peptide (GP5)3, fused to a transduction domain, abolished lamellipodia induction by profilin or FBS. Time-lapse microscopy confirmed the effects of profilin on lamellipodia extension with a higher spreading velocity than FBS. PTD4-Pfn I was found in the inner lamellipodia domain, at the membrane leading edge where it colocalizes with endogenous profilin. While FBS-induced lamellipodia formation activates Rac1, PTD4-Pfn I stimulation did not induce Rac1 activation. We propose a role of profilin I favoring lamellipodia formation by a mechanism downstream of growth factor.

Multiple Sclerosis (MS) is an autoimmune disease driving inflammatory and degenerative processes that damage the central nervous system (CNS). However, it is not well understood how these events interact and evolve to evoke such a highly dynamic and heterogeneous disease. We established a hypothesis whereby the variability in the course of MS is driven by the very same pathogenic mechanisms responsible for the disease, the autoimmune attack on the CNS that leads to chronic inflammation, neuroaxonal degeneration and remyelination. We propose that each of these processes acts more or less severely and at different times in each of the clinical subgroups. To test this hypothesis, we developed a mathematical model that was constrained by experimental data (the expanded disability status scale [EDSS] time series) obtained from a retrospective longitudinal cohort of 66 MS patients with a long-term follow-up (up to 20 years). Moreover, we validated this model in a second prospective cohort of 120 MS patients with a three-year follow-up, for which EDSS data and brain volume time series were available. The clinical heterogeneity in the datasets was reduced by grouping the EDSS time series using an unsupervised clustering analysis. We found that by adjusting certain parameters, albeit within their biological range, the mathematical model reproduced the different disease courses, supporting the dynamic CNS damage hypothesis to explain MS heterogeneity. Our analysis suggests that the irreversible axon degeneration produced in the early stages of progressive MS is mainly due to the higher rate of myelinated axon degeneration, coupled to the lower capacity for remyelination. However, and in agreement with recent pathological studies, degeneration of chronically demyelinated axons is not a key feature that distinguishes this phenotype. Moreover, the model reveals that lower rates of axon degeneration and more rapid remyelination make relapsing MS more resilient than the progressive subtype. Therefore, our results support the hypothesis of a common pathogenesis for the different MS subtypes, even in the presence of genetic and environmental heterogeneity. Hence, MS can be considered as a single disease in which specific dynamics can provoke a variety of clinical outcomes in different patient groups. These results have important implications for the design of therapeutic interventions for MS at different stages of the disease.