>>18692998 (LB)
>WHAT DO YOU THINK HAPPENS NEXT?
>Malone and Alchem
wonder when Malone resigned from Alchem's 'toxic work environment?'
Medical Countermeasures Analysis of 2019-nCoV and Vaccine Risks for Antibody-Dependent Enhancement (ADE)
March 09, 2020 / Source
Darrell O. Ricke * and Robert W. Malone **
*Biological and Chemical Technologies Massachusetts Institute of Technology Lincoln Laboratory Lexington, MA USA.
**Chief Medical Officer, Alchem Laboratories
Version 1 : Received: 6 March 2020 / Approved: 8 March 2020 / Online: 8 March 2020 (15:35:27 CET)
Background: In 80% of patients, COVID-19 presents as mild disease1,2. 20% of cases develop severe (13%) or critical (6%) illness. More severe forms of COVID-19 present as clinical severe acute respiratory syndrome, but include a T-predominant lymphopenia3, high circulating levels of proinflammatory cytokines and chemokines, accumulation of neutrophils and macrophages in lungs, and immune dysregulation including immunosuppression4. Methods: All major SARS-CoV-2 proteins were characterized using an amino acid residue variation analysis method. Results predict that most SARS-CoV-2 proteins are evolutionary constrained, with the exception of the spike (S) protein extended outer surface. Results were interpreted based on known SARS-like coronavirus virology and pathophysiology, with a focus on medical countermeasure development implications. Findings: Non-neutralizing antibodies to variable S domains may enable an alternative infection pathway via Fc receptor-mediated uptake. This may be a gating event for the immune response dysregulation observed in more severe COVID-19 disease. Prior studies involving vaccine candidates for FCoV5,6 SARS-CoV-17-10 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) 11 demonstrate vaccination-induced antibody-dependent enhancement of disease (ADE), including infection of phagocytic antigen presenting cells (APC). T effector cells are believed to play an important role in controlling coronavirus infection; pan-T depletion is present in severe COVID-19 disease3 and may be accelerated by APC infection. Sequence and structural conservation of S motifs suggests that SARS and MERS vaccine ADE risks may foreshadow SARS-CoV-2 S-based vaccine risks. Autophagy inhibitors may reduce APC infection and T-cell depletion12 13. Amino acid residue variation analysis identifies multiple constrained domains suitable as T cell vaccine targets. Evolutionary constraints on proven antiviral drug targets present in SARS-CoV-1 and SARS-CoV-2 may reduce risk of developing antiviral drug escape mutants. Interpretation: Safety testing of COVID-19 S protein-based B cell vaccines in animal models is strongly encouraged prior to clinical trials to reduce risk of ADE upon virus exposure.
Ricke, D.O.; Malone, R.W. Medical Countermeasures Analysis of 2019-nCoV and Vaccine Risks for Antibody-Dependent Enhancement (ADE). Preprints 2020, 2020030138 (doi: 10.20944/preprints202003.0138.v1).
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FLSurgeonGen was justified in removing the flawed Patone et al., study from his FL COVID jab report
@FLSurgeonGen was justified in removing the flawed Patone et al., study (see below*) from from his FL COVID jab report for the same reason the UF "task force" don't want to be reminded how their Omnicron model over estimated mortality by 10X!
Because Omnicron rendered all prior pathogenic C19 variants extinct along with their risks of myocarditis, there’s simply no empirical evidence that post Omnicron COVID infections increase the risk of myocarditis over the risky EVA gene therapy jabs.
*https://www.frontiersin.org/articles/10.3389/fmed.2023.1126945/full
excerpt:
For Patone et al.'s study, a case of myocarditis is one that results in death or in hospital admission for myocarditis—some of these admissions occurred in temporal proximity (1–28 days) to a COVID-19 vaccination, some in temporal proximity (1–28 days) to a positive COVID-19 test, and some, “baseline cases,” did not have either of these temporal associations.
Flaw 1: Because the study population consists of only vaccinated individuals and any unvaccinated person who dies from myocarditis in temporal proximity to a positive COVID test will not be able to later vaccinate, the numerator 114 won't include any cases of myocarditis resulting in death.
Flaw 2: COVID-related myocarditis risk among the unvaccinated is, of course, unrelated to vaccination. Because the study population consists of only vaccinated individuals, this creates an illogical dependence of Patone et al.'s computation of the incidence of positive-test-associated myocarditis among the unvaccinated on the decision to later vaccinate or not made by a very small number of individuals in England—those individuals, ages 13 and up, hospitalized with positive-test-associated myocarditis during the study period while unvaccinated. We know 114 of those individuals later chose to vaccinate, but we do not know how many chose not to vaccinate. What if none had chosen to vaccinate? Then, the numerator 114 in Patone et al.'s main analysis of incidence would be 0 and the study would have shown 0 risk of positive-test-associated myocarditis among the unvaccinated. On the other hand, if, during the study period, those (in England, age 13 and up) hospitalized while unvaccinated with positive-test-associated myocarditis later chose to vaccinate with higher probability than a “generic” unvaccinated person having had a positive COVID test, then Patone et al.'s incidence quotient Q will overstate risk.
Design Flaws 1 and 2, described above, were introduced into Patone et al.'s study at a late stage—after nearly all study data had been collected and analyzed. Reading the preprint version (3) of Patone et al.'s published paper (1) reveals that, as originally designed, Patone et al.'s study did not include an analysis of the incidence of positive-test-associated myocarditis among the unvaccinated. Rather, positive-test-associated myocarditis events, pre-first-dose and post-first-dose, were combined to compute myocarditis incidence following a positive test independent of vaccination status.
Flaw 3: Patone et al.'s description of their study in (1) doesn't include sufficient details for a reader or reviewer to determine how baseline myocarditis incidence is computed. For instance, it appears that baseline incidence depends on “seasonal variation” in myocarditis infection as well as hospital-admission pressure [(1), “Study Design and Oversight,” p. 744]; however, no details are included to explain how these factors influence baseline rates. There is evidence that myocarditis is not seasonal (4).
https://twitter.com/REALspark_gap/status/1647016506147098624?s=20