1]. It reports observations on 522 patients with confirmed CoViD-19 symptomatology, compared to 40 control subjects. In brief, notable T cytopoenia was recorded by flow cytometry in the CD4+ and the CD8+ populations, which were significantly yet inversely correlated with remarkably increased serum levels of the pro-inflammatory cytokines IL-6, IL-10 and TNF-a. Flow cytometry established a progressive increase in the expression of programmed cell death marker-1 (PD-1) and T cell immunoglobulin & mucin domain 3 (Tim-3) as patients (n=14) deteriorated from prodromal to symptomatic CoViD-19 requiring intensive care. Here, we interpret these observations of Diao et al from our current understanding of T cell immunophysiology and immunopathology following an immune challenge in the form of sustained viral infection, as is the case in CoViD-19, with emphasis on exhausted T cells (Tex). Recent clinical trials to rescue Tex show promising outcomes. The relevance of these interventions for the prevention and treatment of CoViD-19 is discussed. Taken together, the data of Diao et al could proffer the first glimpse of immunopathology and possible immunotherapy for patients with CoViD-19.

Novel developments in bioinformation, bioinformatics and biostatistics, including artificial intelligence (AI), play a timely and critical role in translational care. Case in point, the extent to which viral immune surveillance is regulated by immune cells and soluble factors, and by non-immune factors informs the administration of health care. The events by which health is regained following viral infection is an allostatic process, which can be modeled using Hilbert's and Volterra's mathematical biology criteria, and biostatistical methodologies such as linear multiple regression. Health regained following viral infection can be given as Y being the sum-total of the positive factors and events (∏) that inherently push allostasis forward (i.e., the orderly process of immune activation and maturation) and the negative (N) factors and events that, allostatically speaking, interfere with regaining health. Any gaps in knowledge are filled by AI-aided immune tweening. Proof of concept can be tested with the fast-gaining infection using tick-borne Bunyavirus that cause severe fever with thrombocytopenia syndrome (SFTS).

Translational science conceptualizes healthcare as a concerted set of processes that integrate research findings from the bench to the bedside. This model of healthcare is effectiveness-focused, patient-centered, and evidence-based, and yields evidence-based revisions of practice-based guidelines, which emerge from research synthesis protocols in comparative effectiveness research that are disseminated in systematic reviews. Systematic reviews produce qualitative and quantitative consensi of the best available evidence. The quantitative consensus is derived from meta-analysis protocols that are often achieved by probabilistic approach Bayesian statistical models.

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