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COVID-19 (SARS-CoV-2) disease severity and stages varies from asymptomatic, mild flu-like symptoms, moderate, severe, critical, and chronic disease. COVID-19 disease progression include lymphopenia, elevated proinflammatory cytokines and chemokines, accumulation of macrophages and neutrophils in lungs, immune dysregulation, cytokine storms, acute respiratory distress syndrome (ARDS), etc. Development of vaccines to severe acute respiratory syndrome (SARS), Middle East Respiratory Syndrome coronavirus (MERS-CoV), and other coronavirus has been difficult to create due to vaccine induced enhanced disease responses in animal models. Multiple betacoronaviruses including SARS-CoV-2 and SARS-CoV-1 expand cellular tropism by infecting some phagocytic cells (immature macrophages and dendritic cells) via antibody bound Fc receptor uptake of virus. Antibody-dependent enhancement (ADE) may be involved in the clinical observation of increased severity of symptoms associated with early high levels of SARS-CoV-2 antibodies in patients. Infants with multisystem inflammatory syndrome in children (MIS-C) associated with COVID-19 may also have ADE caused by maternally acquired SARS-CoV-2 antibodies bound to mast cells. ADE risks associated with SARS-CoV-2 has implications for COVID-19 and MIS-C treatments, B-cell vaccines, SARS-CoV-2 antibody therapy, and convalescent plasma therapy for patients. SARS-CoV-2 antibodies bound to mast cells may be involved in MIS-C and multisystem inflammatory syndrome in adults (MIS-A) following initial COVID-19 infection. SARS-CoV-2 antibodies bound to Fc receptors on macrophages and mast cells may represent two different mechanisms for ADE in patients. These two different ADE risks have possible implications for SARS-CoV-2 B-cell vaccines for subsets of populations based on age, cross-reactive antibodies, variabilities in antibody levels over time, and pregnancy. These models place increased emphasis on the importance of developing safe SARS-CoV-2 T cell vaccines that are not dependent upon antibodies.

Background: Vasculitis diseases include Kawasaki disease (KD), Kawasaki disease shock syndrome (KDSS), Multisystem Inflammatory Syndrome (MIS), Henoch–Schönlein purpura (HS), or IgA vasculitis, and additional vasculitis diseases. These diseases are often preceded by infections or immunizations. Disease incidence rates are higher in children than in adults. These diseases have been extensively studied, but understanding of the disease etiology remains to be established. Objective: Many studies have failed to demonstrate an association between vasculitis diseases and vaccination; this study examines possible associations. Methods: Herein, the Vaccine Adverse Event Reporting System (VAERS) database is retrospectively examined for associations between vasculitis diseases and immunizations. Results: For some vaccines, the number of rare cases of KD, MIS, and HS are higher than the background rates. These rare cases are predicted to occur in individuals with (1) genetic risk factors with (2) antibody titer levels above the primary immune response level. Herein, the model of humoral immune response antibodies bound to antigens (pathogen or vaccine) creating immune complexes is proposed. These immune complexes are proposed to bind Fc receptors on immune cells and platelets, resulting in cell activation and the release of inflammatory molecules including histamine and serotonin. Immune complexes and inflammatory molecules including serotonin and histamine likely trigger vasculitis. Elevated serotonin and possibly histamine drive initial vasoconstrictions, disrupting blood flow. Increased blood flow pressure from cardiac capillary vasoconstrictions is predicted to trigger coronary artery aneurysms (CAA) or lesions (CAL) in some patients. For KDSS and MIS patients, these cardiac capillary vasoconstrictions are predicted to result in ischemia followed by ventricular dysfunction. Ongoing ischemia can result in long-term cardiac damage. Cases associated with pathogens are likely to have persistent infections triggering disease onset. Conclusion: The proposed model of immune complexes driving disease initial disease etiology by Fc receptor activation of immune cells and platelets, resulting in elevated histamine and serotonin levels, is testable and is consistent with disease symptoms and current treatments.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H 2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

Personal fitness/health tracking devices that include electrodermal activity sensors enable tracking of vasomotor symptoms (hot flashes).  Multiple conditions are associated with vasomotor symptoms.  This article describes nighttime tracking of vasomotor symptoms for an individual over a two-year period.  This volunteer was a participant in a longitudinal study on volunteers wearing physiological monitors.  Personal tracking of vasomotor symptoms will provide new insights on the differences between conditions and impacts on individual's health.

Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitute one of the deadliest pandemics in modern history demonstrating cardiovascular, gastrointestinal, hematologic, mucocutaneous, respiratory, neurological, renal and testicular manifestations and further complications. COVID-19-induced excessive immune response accompanied with uncontrolled release of cytokines culminating in cytokine storm seem to be the common pathogenetic mechanism of these complications. The aim of this narrative review is to elucidate the relation between anaphylaxis associated with profound hypotension or hypoxemia with pro-inflammatory cytokine release. COVID-19 relation with Kounis syndrome and post-COVID-19 vaccination correlation with heparin-induced thrombocytopenia with thrombosis (HITT), especially serious cerebral venous sinus thrombosis, were also reviewed. Methods: A current literature search in PubMed, Embase and Google databases was performed to reveal the pathophysiology, prevalence, clinical manifestation, correlation and treatment of COVID-19, anaphylaxis with profuse hypotension, Kounis acute coronary syndrome and thrombotic events post vaccination. Results: The same key immunological pathophysiology mechanisms and cells seem to underlie COVID-19 cardiovascular complications and the anaphylaxis-associated Kounis syndrome. The myocardial injury in patients with COVID-19 has been attributed to coronary spasm, plaque rupture and microthrombi formation, hypoxic injury or cytokine storm disposing the same pathophysiology with the three clinical variants of Kounis syndrome. COVID-19-interrelated vaccine excipients as polysorbate, polyethelene glycol (PEG) and trometamol constitute potential allergenic substances. Conclusion: Better acknowledgement of the pathophysiological mechanisms, clinical similarities, multiorgan complications of COVID-19 or other viral infections as dengue and human immunodeficiency viruses along with the action of inflammatory cells inducing the Kounis syndrome could identify better immunological approaches for prevention, treatment of the COVID-19 pandemic as well as post-COVID-19 vaccine adverse reactions.

High throughput sequencing (HTS) of DNA forensic samples is expanding from the sizing of short tandem repeats (STRs) to massively parallel sequencing (MPS).  HTS panels are expanding from the FBI 20 core Combined DNA Index System (CODIS) loci to include SNPs.  The calculation of random man not excluded, P(RMNE), is used in DNA mixture analysis to estimate the probability that a person is present in a DNA mixture.  This calculation encounters calculation artifacts with expansion to larger panel sizes.  Increasing the floating-point precision of the calculations allows for increased panel sizes but with a corresponding increase in computation time.  The Taylor series higher precision libraries used fail on some input data sets leading to algorithm unreliability.  Herein, a new formula is introduced for calculating P(RMNE) that scales to larger SNP panel sizes while being computationally efficient (patent pending).

Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual’s muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

Background: Capabilities for generating and storing large amounts of data relevant to individual health and performance are rapidly evolving and have the potential to accelerate progress toward quantitative and individualized understanding of many important issues in health and medicine. Recent advances in clinical and laboratory technologies provide increasingly complete and dynamic characterization of individual genomes, gene expression levels for genes, relative abundance of thousands of proteins, population levels for thousands of microbial species, quantitative imaging data, and more - all on the same individual.  Personal and wearable electronic devices are increasingly enabling these same individuals to routinely and continuously capture vast amounts of quantitative data including activity, sleep, nutrition, environmental exposures, physiological signals, speech, and neurocognitive performance metrics at unprecedented temporal resolution and scales. While some of the companies offering these measurement technologies have begun to offer systems for integrating and displaying correlated individual data, these are either closed/proprietary platforms that provide limited access to sensor data or have limited scope that focus primarily on one data domain (e.g. steps/calories/activity, genetic data, etc.). Methods: The Integrated Biomedical System is developed as a Ruby on Rails application with a relational database. Results: Data from multiple wearable monitors for activity, sleep, and physiological measurements, phone GPS tracking, individual genomics, air quality monitoring, etc. have been integrated into the Integrated Biomedical System. Conclusions: The Integrated Biomedical System is being developed to demonstrate an adaptable open-source tool for reducing the burden associated with integrating heterogeneous genome, interactome, and exposome data from a constantly evolving landscape of biomedical data generating technologies.  The Integrated Biomedical System provides a scalable and modular framework that can be extended to include support for numerous types of analyses and applications at scales ranging from personal users, communities and groups, to potentially large populations.

New strategies for prevention and treatment of type 2 diabetes (T2D) require improved insight into disease etiology. We analyzed 386,731 common single-nucleotide polymorphisms (SNPs) in 1464 patients with T2D and 1467 matched controls, each characterized for measures of glucose metabolism, lipids, obesity, and blood pressure. With collaborators (FUSION and WTCCC/UKT2D), we identified and confirmed three loci associated with T2D--in a noncoding region near CDKN2A and CDKN2B, in an intron of IGF2BP2, and an intron of CDKAL1--and replicated associations near HHEX and in SLC30A8 found by a recent whole-genome association study. We identified and confirmed association of a SNP in an intron of glucokinase regulatory protein (GCKR) with serum triglycerides. The discovery of associated variants in unsuspected genes and outside coding regions illustrates the ability of genome-wide association studies to provide potentially important clues to the pathogenesis of common diseases.

High throughput sequencing (HTS) of DNA forensic samples is expanding from the sizing of short tandem repeats (STRs) to massively parallel sequencing (MPS).  HTS panels are expanding from the FBI 20 core Combined DNA Index System (CODIS) loci to include SNPs.  The calculation of random man not excluded, P(RMNE), is used in DNA mixture analysis to estimate the probability that a person is present in a DNA mixture.  This calculation encounters calculation artifacts with expansion to larger panel sizes.  Increasing the floating-point precision of the calculations allows for increased panel sizes but with a corresponding increase in computation time.  The Taylor series higher precision libraries used fail on some input data sets leading to algorithm unreliability.  Herein, a new formula is introduced for calculating P(RMNE) that scales to larger SNP panel sizes while being computationally efficient (patent pending).