Functional observability and target state estimation in large-scale networks.

The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-scale dynamical networks, it is often difficult or physically impossible to have enough sensor nodes to make the system fully observable. Even if the system is in principle observable, high dimensionality poses fundamental limits on the computational tractability and performance of a full-state observer. To overcome the curse of dimensionality, we instead require the system to be functionally observable, meaning that a targeted subset of state variables can be reconstructed from the available measurements. Here, we develop a graph-based theory of functional observability, which leads to highly scalable algorithms to 1) determine the minimal set of required sensors and 2) design the corresponding state observer of minimum order. Compared with the full-state observer, the proposed functional observer achieves the same estimation quality with substantially less sensing and fewer computational resources, making it suitable for large-scale networks. We apply the proposed methods to the detection of cyberattacks in power grids from limited phase measurement data and the inference of the prevalence rate of infection during an epidemic under limited testing conditions. The applications demonstrate that the functional observer can significantly scale up our ability to explore otherwise inaccessible dynamical processes on complex networks.

Cellular and humoral functional responses after BNT162b2 mRNA vaccination differ longitudinally between naive and subjects recovered from COVID-19.

We have analyzed BNT162b2 vaccine-induced immune responses in naive subjects and individuals recovered from coronavirus disease 2019 (COVID-19), both soon after (14 days) and later after (almost 8 months) vaccination. Plasma spike (S)-specific immunoglobulins peak after one vaccine shot in individuals recovered from COVID-19, while a second dose is needed in naive subjects, although the latter group shows reduced levels all along the analyzed period. Despite how the neutralization capacity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mirrors this behavior early after vaccination, both groups show comparable neutralizing antibodies and S-specific B cell levels late post-vaccination. When studying cellular responses, naive individuals exhibit higher SARS-CoV-2-specific cytokine production, CD4+ T cell activation, and proliferation than do individuals recovered from COVID-19, with patent inverse correlations between humoral and cellular variables early post-vaccination. However, almost 8 months post-vaccination, SARS-CoV-2-specific responses are comparable between both groups. Our data indicate that a previous history of COVID-19 differentially determines the functional T and B cell-mediated responses to BNT162b2 vaccination over time.

Application of Optimal Control of Infectious Diseases in a Model-Free Scenario.

Optimal control for infectious diseases has received increasing attention over the past few decades. In general, a combination of cost state variables and control effort have been applied as cost indices. Many important results have been reported. Nevertheless, it seems that the interpretation of the optimal control law for an epidemic system has received less attention. In this paper, we have applied Pontryagin's maximum principle to develop an optimal control law to minimize the number of infected individuals and the vaccination rate. We have adopted the compartmental model SIR to test our technique. We have shown that the proposed control law can give some insights to develop a control strategy in a model-free scenario. Numerical examples show a reduction of 50% in the number of infected individuals when compared with constant vaccination. There is not always a prior knowledge of the number of susceptible, infected, and recovered individuals required to formulate and solve the optimal control problem. In a model-free scenario, a strategy based on the analytic function is proposed, where prior knowledge of the scenario is not necessary. This insight can also be useful after the development of a vaccine to COVID-19, since it shows that a fast and general cover of vaccine worldwide can minimize the number of infected, and consequently the number of deaths. The considered approach is capable of eradicating the disease faster than a constant vaccination control method.

SARS-CoV-2 Proteins Induce Endotoxin Tolerance Hallmarks: A Demonstration in Patients with COVID-19.

According to a large number of reported cohorts, sepsis has been observed in nearly all deceased patients with COVID-19. We and others have described sepsis, among other pathologies, to be an endotoxin tolerance (ET)-related disease. In this study, we demonstrate that the culture of human blood cells from healthy volunteers in the presence of SARS-CoV-2 proteins induced ET hallmarks, including impairment of proinflammatory cytokine production, low MHC class II (HLA-DR) expression, poor T cell proliferation, and enhancing of both phagocytosis and tissue remodeling. Moreover, we report the presence of SARS-CoV-2 blood circulating proteins in patients with COVID-19 and how these levels correlate with an ET status, the viral RNA presence of SARS-CoV-2 in plasma, as well as with an increase in the proportion of patients with secondary infections.

Potential Role of the Galectin-9/TIM-3 Axis in the Disparate Progression of SARS-CoV-2 in a Married Couple: A Case Report.

We report the disparate clinical progression of a couple infected by SARS-CoV-2 based on their immune checkpoint (IC) levels and immune cell distribution in blood from admission to exitus in patient 1 and from admission to discharge and recovery in patient 2. A detailed clinical follow-up accompanied by a longitudinal analysis of immune phenotypes and IC levels is shown. The continuous increase in the soluble IC ligand galectin-9 (Gal-9) and the increment in T-cell immunoglobulin and mucin domain-containing 3 (TIM-3) protein in T cells in patient 1 suggests an activation of the Gal-9/TIM-3 axis and, subsequently, a potential cell exhaustion in this patient that did not occur in patient 2. Our data indicate that the Gal-9/TIM-3 axis could be a potential target in this clinical setting, along with a patent effector memory T-cell reduction.

Proteins from SARS-CoV-2 reduce T cell proliferation: A mirror image of sepsis.

Increased cytokine levels, acute phase reactants and immune checkpoint expression changes have been described in patients with Coronavirus Disease 2019 (COVID-19). Here, we have reported a monocyte polarization towards a low HLA-DR and high PD-L1 expression after long exposure to proteins from SARS-CoV-2. Moreover, CD86 expression was also reduced over SARS-CoV-2 proteins exposure. Additionally, T-cells proliferation was significantly reduced after stimulation with these proteins. Eventually, patients with long-term SARS-CoV-2 infection also exhibited a significant blockade of T-cells proliferation.

Immune Response and COVID-19: A mirror image of Sepsis.

The emergence of SARS-CoV-2 virus and its associated disease COVID-19 have triggered significant threats to public health, in addition to political and social changes. An important number of studies have reported the onset of symptoms compatible with pneumonia accompanied by coagulopathy and lymphocytopenia during COVID-19. Increased cytokine levels, the emergence of acute phase reactants, platelet activation and immune checkpoint expression are some of the biomarkers postulated in this context. As previously observed in prolonged sepsis, T-cell exhaustion due to SARS-CoV-2 and even their reduction in numbers due to apoptosis hinder the response to the infection. In this review, we synthesized the immune changes observed during COVID-19, the role of immune molecules as severity markers for patient stratification and their associated therapeutic options.