principiascientificinternational--2020-09-24--Are Vaccines Part of a Global Medical Tyranny?

Australian researcher into vaccines , Dr Judy Wilyman presents a selection of the evidence that supports the claim that vaccines are destroying the genetic fabric of society .
She writes : In 1960 Australian Frank MacFarlane Burnet received the Nobel Prize for immunology .
At this time he stated : “ Genetics , nutrition , psychological and environmental factors may play a more important role in resistance to disease than the assumed benefits of artificial immunity induced by vaccination ” .
He considered that “ genetic deterioration of the population may be a consequence of universal mass vaccination and he @ @ @ @ @ @ @ be against the best interests of the state ” .
In addition to these statements , Stanley Plotkin , who is considered the ‘ Father of World Vaccinology ’ stated in 2019 that ‘ antibody titre is not a reliable indicator because we do not know precisely how antibodies work ’ .
This is significant because the efficacy of all vaccines is based solely on the surrogate of antibody titre .
And as we know many vaccinated children are still getting the diseases they are vaccinated against .
It is also important to @ @ @ @ @ @ @ more complex than just an antibody response , and natural immunity is not the same as artificial vaccine-induced immunity ( antibody titre ) .
By 2004 ~45 % of children 0-14 years of age in all highly vaccinated populations , had a chronic illness and in 2020 this figure is now closer to 50 % in many countries .
Many parents are now long-term carers for children who will never reach their potential in life .
In addition , the incidence of autism is predicted to be 1 in 2 children by 2032 @ @ @ @ @ @ @ prevalent in boys than girls .
Yet governments globally have ignored these facts and the overwhelming science linking these diseases to vaccines for three decades .
They have also ignored the well known contraindications to vaccines that are due to genetics ( family history ) , by reducing all of these contraindications to just one – anaphylaxis .
And family history is not enough – you must try the vaccine first .
On the advice of the medical-industry complex , governments and doctors are claiming that this significant increase in chronic illness in @ @ @ @ @ @ @ vaccination .
Governments have ignored basic scientific principles of evidence-based medicine to provide this response to parents for decades .
My Publications on the Ethics of Mandatory and Coercive Vaccination Policies ‘ A new strain of influenza or a change in surveillance ?
‘ After investigating the Swine flu ‘ pandemic ’ of 2009 , that did not turn out to be a ‘ pandemic ’ , I had this article published in the Australasian College of Environmental and Nutritional Medicine ( ACNEM ) Vol 28 , No 4 , Dec 2009 .
@ @ @ @ @ @ @ a disease can be used to give the appearance of an increased number of cases which can be misused by the media to create fear about a new virus .
This can be achieved through statistical manipulation as we have observed in both 2009 and now in 2020 with COVID19 .
Mandatory and Coercive Vaccination : how ethical is this policy ?
’ – A poster presentation at the Australian Health Promotion Association conference in Perth 2009 .
An article published in the Medical Veritas Journal in 2015 – The Ethics of Childhood @ @ @ @ @ @ @ against influenza ?
Influenza is a disease that the majority of children and adults are not at risk of dying from – has this changed in 2020 or is it a change to the diagnostic criteria for influenza ?
Whilst it can be stated that there has been a serious outbreak of disease in some countries in 2020 , this can not be described as a “ global pandemic ” because this declaration was based on changing the definition of a pandemic in 2009 and on the flawed assumptions used in the mathematical @ @ @ @ @ @ @ .
This is explained in my video presentation here and in this document that has just been released – ‘ Global Report 2019-nCOV : There is no global pandemic .
The data is clear ’ .
• Class action against the Australian government ’ s disproportionate response to SARS-Cov2 and the National state of Emergency .
This legal document describes the Commonwealth Biosecurity Act 2015 that states that healthy people should not be medically tested or quarantined .
Please download it and stand up for your human rights .
• ‘ Global Report @ @ @ @ @ @ @ .
The data is clear ’ .
• Curfew ‘ invalid ’ and everyone can ignore it says Michael Wyles QC – comment on the Victorian Lockdown • Corona Brucella – the second Wave of Corona by investigative journalist James Grundvig • Open letter from Medical doctors and Health Professionals to all Belgian Authorities .
• The Significant Events needed to Create an Appearance of a Global Pandemic by Judy Wilyman PhD .
Some of the Ingredients of Vaccines Did you know that antibiotics are in most vaccines ?
Many people are allergic @ @ @ @ @ @ @ the serious risk of anaphylactic shock to this and many other vaccine ingredients .
Are you being informed of this before you give consent to your newborn baby being vaccinated ?
Please consider whether you want the substances listed below injected into the tissues of your new born infant before the the body systems are fully developed .
These ingredients and many more are present in vaccines and the vaccination schedule has expanded to mandating 16 vaccines in Australian social services policies that require ~52 doses from birth to adolescence .
And the @ @ @ @ @ @ @ anaphylaxis , Kawasaki ’ s Disease ( vasculitis ) , Chronic Fatigue Syndrome ( CFS ) , autoimmune disorders ( diabetes , childhood rheumatoid arthritis , arthritis , multiple sclerosis etc . )
, thrombocytopenia purpura ( ITP ) , autism , speech delay , neurological disorders , encephalopathy , meningitis , ADHD , childhood cancers , and many more that has increased in direct correlation to the vaccination program – a plausible cause of this illness .
But your doctor will inform you that this is ‘ just a coincidence ’ because @ @ @ @ @ @ @ never funded a causality study that would disprove this association .
That is , a study that uses an inert placebo in the unvaccinated trial group to prove the safety of each vaccine over an appropriate long-term time period that includes the delay in the appearance of these diseases – or the safety of the combination of vaccines on the government schedule : Borax ( ‘ sodium borate ’ – causes infertility and is found in HPV vaccines and hep A ) About the author : Dr Judy Wilyman PhD : I have @ @ @ @ @ @ @ and informally since 1993 when I vaccinated my first child .
Like most people questioning vaccines , I have not come from an anti-vaccination position and the debate is not about pro or anti-vaccination .
It is about safety , efficacy and necessity for each vaccine on the schedule .
Are they all safe ?
And are they all effective and necessary ?
In 2015 I completed a PhD at the University of Wollongong answering these questions .
My thesis is titled ‘ A critical analysis of the Australian Government ’ s rationale @ @ @ @ @ @ @ Chapter 7 , I present a discussion of the claims made by the government about the safety and efficacy of vaccines that are not supported by scientific evidence .
Master of Science ( Population Health ) , Faculty of Health Sciences , School of Public Health , University of Wollongong .
PhD in : A critical analysis of the Australian government ’ s rationale for its vaccination policy ’ ( the science , politics and ethics of Australia ’ s vaccination policies ) , UOW School of Humanities and Social Inquiry .
My @ @ @ @ @ @ @ Loss of Health Freedom – is now available .
This book transforms my PhD into a more readable format and it includes three forewords that are written by health professionals and scientists who have endorsed my research .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

Are Vaccines Part of a Global Medical Tyranny?
Written by Dr Judy Wilyman PhD
Australian researcher into vaccines, Dr Judy Wilyman presents a selection of the evidence that supports the claim that vaccines are destroying the genetic fabric of society. She writes:
In 1960 Australian Frank MacFarlane Burnet received the Nobel Prize for immunology. At this time he stated:
“Genetics, nutrition, psychological and environmental factors may play a more important role in resistance to disease than the assumed benefits of artificial immunity induced by vaccination”.
He considered that “genetic deterioration of the population may be a consequence of universal mass vaccination and he postulated that in the long-term vaccination may be against the best interests of the state”.
In addition to these statements, Stanley Plotkin, who is considered the ‘Father of World Vaccinology’ stated in 2019 that ‘antibody titre is not a reliable indicator because we do not know precisely how antibodies work’. This is significant because the efficacy of all vaccines is based solely on the surrogate of antibody titre. And as we know many vaccinated children are still getting the diseases they are vaccinated against.
It is also important to note that the human immune system is more complex than just an antibody response, and natural immunity is not the same as artificial vaccine-induced immunity (antibody titre).
By 2004 ~45% of children 0-14 years of age in all highly vaccinated populations, had a chronic illness and in 2020 this figure is now closer to 50% in many countries.
Many parents are now long-term carers for children who will never reach their potential in life. In addition, the incidence of autism is predicted to be 1 in 2 children by 2032; a disease that is 4-times more prevalent in boys than girls.
Yet governments globally have ignored these facts and the overwhelming science linking these diseases to vaccines for three decades. They have also ignored the well known contraindications to vaccines that are due to genetics (family history), by reducing all of these contraindications to just one – anaphylaxis. And family history is not enough – you must try the vaccine first.
On the advice of the medical-industry complex, governments and doctors are claiming that this significant increase in chronic illness in children is a ‘coincidence’ after vaccination. Governments have ignored basic scientific principles of evidence-based medicine to provide this response to parents for decades.
My Publications on the Ethics of Mandatory and Coercive Vaccination Policies
‘A new strain of influenza or a change in surveillance?‘ After investigating the Swine flu ‘pandemic’ of 2009, that did not turn out to be a ‘pandemic’, I had this article published in the Australasian College of Environmental and Nutritional Medicine (ACNEM) Vol 28, No 4, Dec 2009. The article describes how increased surveillance of a disease can be used to give the appearance of an increased number of cases which can be misused by the media to create fear about a new virus. This can be achieved through statistical manipulation as we have observed in both 2009 and now in 2020 with COVID19.
Mandatory and Coercive Vaccination: how ethical is this policy?’ – A poster presentation at the Australian Health Promotion Association conference in Perth 2009.
An article published in the Medical Veritas Journal in 2015 – The Ethics of Childhood Influenza: should Australian children be immunised against influenza? Influenza is a disease that the majority of children and adults are not at risk of dying from – has this changed in 2020 or is it a change to the diagnostic criteria for influenza?
Whilst it can be stated that there has been a serious outbreak of disease in some countries in 2020, this cannot be described as a “global pandemic” because this declaration was based on changing the definition of a pandemic in 2009 and on the flawed assumptions used in the mathematical modelling for this virus in all countries. This is explained in my video presentation here and in this document that has just been released – ‘Global Report 2019-nCOV: There is no global pandemic. The data is clear’.
Some of the Ingredients of Vaccines
Did you know that antibiotics are in most vaccines? Many people are allergic to antibiotics and using any vaccine carries the serious risk of anaphylactic shock to this and many other vaccine ingredients. Are you being informed of this before you give consent to your newborn baby being vaccinated?
Please consider whether you want the substances listed below injected into the tissues of your new born infant before the the body systems are fully developed. These ingredients and many more are present in vaccines and the vaccination schedule has expanded to mandating 16 vaccines in Australian social services policies that require ~52 doses from birth to adolescence.
And the ‘new norm’ – allergies, anaphylaxis, Kawasaki’s Disease (vasculitis), Chronic Fatigue Syndrome (CFS), autoimmune disorders (diabetes, childhood rheumatoid arthritis, arthritis, multiple sclerosis etc.), thrombocytopenia purpura (ITP), autism, speech delay, neurological disorders, encephalopathy, meningitis, ADHD, childhood cancers, and many more that has increased in direct correlation to the vaccination program – a plausible cause of this illness.
But your doctor will inform you that this is ‘just a coincidence’ because the Australian government and vaccine manufacturers have never funded a causality study that would disprove this association. That is, a study that uses an inert placebo in the unvaccinated trial group to prove the safety of each vaccine over an appropriate long-term time period that includes the delay in the appearance of these diseases – or the safety of the combination of vaccines on the government schedule:
Antibiotics: Neomycin, Polymxin, Gentamicin, Kanamycin
Foreign Protein includes:
Human Foetal Cells
Chick embryo Cells and Bovine Serum
Recombinant Human Albumin (genetically engineered DNA)
Potassium Chloride
Aluminium hydroxide
Aluminium hydroxide/phosphate
Aluminium phosphate
Thimerosal (50% mercury compound) (flu vaccine multidose vials and infanrix-hexa and hep B 2013)
Borax (‘sodium borate’ – causes infertility and is found in HPV vaccines and hep A)
Polysorbate 80 – causes infertility
Formaldehyde
Egg protein
Gelatin
Phenol
Monosodium glutamate (MSG)
Phenoxyethanol
Yeast
About the author: Dr Judy Wilyman PhD: I have been studying the vaccination topic both formally and informally since 1993 when I vaccinated my first child. Like most people questioning vaccines, I have not come from an anti-vaccination position and the debate is not about pro or anti-vaccination. It is about safety, efficacy and necessity for each vaccine on the schedule. Are they all safe? And are they all effective and necessary?
In 2015 I completed a PhD at the University of Wollongong answering these questions.
My thesis is titled ‘A critical analysis of the Australian Government’s rationale for its vaccination policy’. In Chapter 7, I present a discussion of the claims made by the government about the safety and efficacy of vaccines that are not supported by scientific evidence.
Bachelor of Science, University of NSW
Diploma of Education (Science), University of Wollongong
Master of Science (Population Health), Faculty of Health Sciences, School of Public Health, University of Wollongong.
PhD in: A critical analysis of the Australian government’s rationale for its vaccination policy’ (the science, politics and ethics of Australia’s vaccination policies), UOW School of Humanities and Social Inquiry.
My book – Vaccination: Australia’s Loss of Health Freedom – is now available. This book transforms my PhD into a more readable format and it includes three forewords that are written by health professionals and scientists who have endorsed my research.
Website: Vaccination Decisions
PRINCIPIA SCIENTIFIC INTERNATIONAL, legally registered in the UK as a company incorporated for charitable purposes. Head Office: 27 Old Gloucester Street, London WC1N 3AX.
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method.
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principiascientificinternational--2020-09-25--More researchers showing COVID-19 may not be infectious at all

More researchers showing COVID-19 may not be infectious at all A growing body of research suggests that a significant number of confirmed COVID-19 infections in the U.S. — perhaps as many as 9 out of every 10 — may not be infectious at all , with much of the country ’ s testing equipment possibly picking up mere fragments of the disease rather than full-blown infections .
Elevated ‘ cycle thresholds ’ may be detecting virus long after it is past the point of infection .
Confirmed cases of the disease have been the focal point of public health authorities @ @ @ @ @ @ @ with countries across the globe working frantically to shore up their testing infrastructure and ensure that most citizens who want a COVID-19 test can obtain one with relative ease .
Many politicians , meanwhile — including most state governors in the U.S. — have tied reopening policies to the number of cases detected in the local community , with regions and localities often being permitted to reopen in staggered “ phases ” only when they have reached successively lower benchmarks of average new daily cases in the area .
Numerous institutions , meanwhile @ @ @ @ @ @ @ attempt to preempt the spread of the virus .
American colleges and universities , for instance , have turned to mass testing in order to closely monitor incidences of the disease among students , particularly residential students living on campus .
Yet a burgeoning line of scientific inquiry suggests that many confirmed infections of COVID-19 may actually be just residual traces of the virus itself , a contention that — if true — may suggest both that current high levels of positive viruses are clinically insignificant and that the mitigation measures used to @ @ @ @ @ @ @ Cycle threshold ’ set very high for many tests At issue is the method by which many COVID-19 tests detect a patient ’ s viral load within a given sample .
Polymerase chain reaction tests , which have been widely deployed to determine if individuals are infected with the disease , function by amplifying DNA samples to the point that an antigen can be detected and classified .
The “ cycle threshold ” is the number of amplification cycles a PCR test goes through before a target pathogen is detected .
A lower @ @ @ @ @ @ @ of the virus was present in the sample ; a higher threshold means the machine had to work harder to detect the virus in the sample , indicating a lower viral load and more likely a non-infectious patient .
According to a rundown of PCR tests compiled by the Foundation for Innovative New Diagnostics , many manufacturers of PCR tests set the cycle threshold cutoff for a positive sample at up to around 40 cycles , a level numerous public health officials believe is guaranteed to return what are effectively false positive results @ @ @ @ @ @ @ .
“ I ’ m shocked that people would think that 40 could represent a positive , ” Juliet Morrison , a virology professor at the University of California , Riverside , told the New York Times in August .
Health authorities elsewhere have indicated similar skepticism of high-threshold tests .
A spokeswoman for Taiwan ’ s Central Epidemic Command Center said in June that the agency only assigns positive cases to samples with Cts of 35 or less , with authorities there believing that any samples with Cts of more than 32 @ @ @ @ @ @ @ non-infectious .
A team of researchers at Oxford , meanwhile , wrote in a preprint paper last week that , based on a review of various sample collections , swabs requiring more than 30 cycles were “ associated with non-infectious samples.
” Binary positive-negative test results — in which cycle thresholds are not considered — will “ result in false positives with segregation of large numbers of people who are no longer infectious and hence not a threat to public health , ” they wrote .
Preprint papers have not yet been through @ @ @ @ @ @ @ results and conclusions can be changed prior to full publication .
Yet several other research projects have indicated similar results .
One , published in April by public health authorities out of France , found that “ patients with Ct values equal or above 34 do not excrete infectious viral particles.
” Similarly , a study out of Ireland seeking to determine “ the duration of infectivity ” of COVID-19 patients found that , of numerous samples subject to PCR testing , scientists were unable to achieve positive culture growth in any that @ @ @ @ @ @ @ of those thresholds are notably smaller than the maximum number of cycles instituted by many test manufacturers , suggesting that there may be many nominally positive COVID-19 cases that are innocuous far as infectiousness and illness are concerned .
Echoing those concerns , researchers at Harvard in May argued that “ the Ct value from positive test results , when interpreted in context , can help to refine clinical decision making , ” and that a cycle threshold of around 34 may be a useful tool for determining when a patient is truly @ @ @ @ @ @ @ merely carrying remnants of the virus .
Such a policy , if implemented , could have momentous implications for public health policy in the U.S. and elsewhere .
Presently , in many industries and at many institutions , a single positive COVID-19 case can result in a complete shutdown of the affected company or university or elementary school , followed by a rush to have everyone tested out of concern that the virus may have spread .
A greater emphasis on the cycle threshold of positive tests may preempt such disruptive policies by @ @ @ @ @ @ @ infectious and which are detecting low viral loads at much less threat of infectivity .
Early indications suggest the number of clinically trivial positive cases in the U.S. might be startlingly high .
The New York Times said last month that a review of the cycle thresholds of positive cases in Nevada , New York and Massachusetts indicated that “ up to 90 percent of people testing positive carried barely any virus.
” Those numbers , if extrapolated nationwide , could suggest that a significant proportion of the mitigation and preparation measures currently @ @ @ @ @ @ @ excessive relative to the actual level of infectious cases around the country .
Ultimately it can be difficult to determine the cycle thresholds used at laboratories across the country , making that kind of extrapolation difficult .
A spokeswoman for LabCorp — one of the largest clinical laboratory groups in the world — said the company “ does not include the CT value in result reporting.
” “ Our CT cutoff is based on extensive validation , ” she said , “ and is within the accepted range to accurately identify individuals currently @ @ @ @ @ @ @ its website says it has performed 13.5 million COVID-19 tests , about 15 % of the country ’ s total number of tests .
At the Center for Evidence-Based Medicine at Oxford University , researchers stressed last month that “ PCR detection of viruses is helpful so long as its limitations are understood ; while it detects RNA in minute quantities , caution needs to be applied to the results as it often does not detect infectious virus.
” “ If this is not understood , PCR results may lead to restrictions for @ @ @ @ @ @ @ present an infection risk , ” they wrote .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

More researchers showing COVID-19 may not be infectious at all
Written by Daniel Payne
A growing body of research suggests that a significant number of confirmed COVID-19 infections in the U.S. — perhaps as many as 9 out of every 10 — may not be infectious at all, with much of the country’s testing equipment possibly picking up mere fragments of the disease rather than full-blown infections.
Elevated ‘cycle thresholds’ may be detecting virus long after it is past the point of infection.
Confirmed cases of the disease have been the focal point of public health authorities and governments worldwide for many months, with countries across the globe working frantically to shore up their testing infrastructure and ensure that most citizens who want a COVID-19 test can obtain one with relative ease.
Many politicians, meanwhile — including most state governors in the U.S. — have tied reopening policies to the number of cases detected in the local community, with regions and localities often being permitted to reopen in staggered “phases” only when they have reached successively lower benchmarks of average new daily cases in the area.
Numerous institutions, meanwhile, have adopted testing protocols in an attempt to preempt the spread of the virus. American colleges and universities, for instance, have turned to mass testing in order to closely monitor incidences of the disease among students, particularly residential students living on campus.
Yet a burgeoning line of scientific inquiry suggests that many confirmed infections of COVID-19 may actually be just residual traces of the virus itself, a contention that — if true — may suggest both that current high levels of positive viruses are clinically insignificant and that the mitigation measures used to suppress them may be excessive.
‘Cycle threshold’ set very high for many tests
At issue is the method by which many COVID-19 tests detect a patient’s viral load within a given sample. Polymerase chain reaction tests, which have been widely deployed to determine if individuals are infected with the disease, function by amplifying DNA samples to the point that an antigen can be detected and classified.
The “cycle threshold” is the number of amplification cycles a PCR test goes through before a target pathogen is detected. A lower cycle threshold means that a higher amount of the virus was present in the sample; a higher threshold means the machine had to work harder to detect the virus in the sample, indicating a lower viral load and more likely a non-infectious patient.
According to a rundown of PCR tests compiled by the Foundation for Innovative New Diagnostics, many manufacturers of PCR tests set the cycle threshold cutoff for a positive sample at up to around 40 cycles, a level numerous public health officials believe is guaranteed to return what are effectively false positive results that have detected fragments of the virus.
“I’m shocked that people would think that 40 could represent a positive,” Juliet Morrison, a virology professor at the University of California, Riverside, told the New York Times in August.
Health authorities elsewhere have indicated similar skepticism of high-threshold tests. A spokeswoman for Taiwan’s Central Epidemic Command Center said in June that the agency only assigns positive cases to samples with Cts of 35 or less, with authorities there believing that any samples with Cts of more than 32 are likely (though not definitely) non-infectious.
A team of researchers at Oxford, meanwhile, wrote in a preprint paper last week that, based on a review of various sample collections, swabs requiring more than 30 cycles were “associated with non-infectious samples.”
Binary positive-negative test results — in which cycle thresholds are not considered — will “result in false positives with segregation of large numbers of people who are no longer infectious and hence not a threat to public health,” they wrote.
Preprint papers have not yet been through the peer review process, so their results and conclusions can be changed prior to full publication. Yet several other research projects have indicated similar results. One, published in April by public health authorities out of France, found that “patients with Ct values equal or above 34 do not excrete infectious viral particles.”
Similarly, a study out of Ireland seeking to determine “the duration of infectivity” of COVID-19 patients found that, of numerous samples subject to PCR testing, scientists were unable to achieve positive culture growth in any that required more than 34.3 cycles.
Both of those thresholds are notably smaller than the maximum number of cycles instituted by many test manufacturers, suggesting that there may be many nominally positive COVID-19 cases that are innocuous far as infectiousness and illness are concerned.
Echoing those concerns, researchers at Harvard in May argued that “the Ct value from positive test results, when interpreted in context, can help to refine clinical decision making,” and that a cycle threshold of around 34 may be a useful tool for determining when a patient is truly infectious and when he or she is merely carrying remnants of the virus.
Such a policy, if implemented, could have momentous implications for public health policy in the U.S. and elsewhere. Presently, in many industries and at many institutions, a single positive COVID-19 case can result in a complete shutdown of the affected company or university or elementary school, followed by a rush to have everyone tested out of concern that the virus may have spread.
A greater emphasis on the cycle threshold of positive tests may preempt such disruptive policies by signaling which positive test results are truly infectious and which are detecting low viral loads at much less threat of infectivity.
Early indications suggest the number of clinically trivial positive cases in the U.S. might be startlingly high. The New York Times said last month that a review of the cycle thresholds of positive cases in Nevada, New York and Massachusetts indicated that “up to 90 percent of people testing positive carried barely any virus.”
Those numbers, if extrapolated nationwide, could suggest that a significant proportion of the mitigation and preparation measures currently in place across the U.S. might be excessive relative to the actual level of infectious cases around the country.
Ultimately it can be difficult to determine the cycle thresholds used at laboratories across the country, making that kind of extrapolation difficult. A spokeswoman for LabCorp — one of the largest clinical laboratory groups in the world — said the company “does not include the CT value in result reporting.”
“Our CT cutoff is based on extensive validation,” she said, “and is within the accepted range to accurately identify individuals currently infected with SARS-CoV-2.” The company on its website says it has performed 13.5 million COVID-19 tests, about 15% of the country’s total number of tests.
At the Center for Evidence-Based Medicine at Oxford University, researchers stressed last month that “PCR detection of viruses is helpful so long as its limitations are understood; while it detects RNA in minute quantities, caution needs to be applied to the results as it often does not detect infectious virus.”
“If this is not understood, PCR results may lead to restrictions for large groups of people who do not present an infection risk,” they wrote.
Read more at justthenews.com
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principiascientificinternational--2020-09-25--Diabetes dramatically reduces the kidney’s ability clean itself

Written by Medical College of Georgia at Augusta University The kidneys often become bulky and dysfunctional in diabetes , and now scientists have found that one path to this damage dramatically reduces the kidney ’ s ability to clean up after itself .
The natural cleanup is called autophagy , which literally means “ self-eating , ” and it ’ s a constant throughout our bodies as debris , like misfolded proteins and damaged cell powerhouses called mitochondria , get packaged into a double-membrane sack , then destroyed by enzymes to help keep cells and organs functioning at a premium @ @ @ @ @ @ @ face of disease challenges like diabetes , but the scientists have found a pathway that then quickly decreases autophagy in both animal models and humans with varying stages of this chronic condition , leaving the kidneys more vulnerable , Dr. Zheng Dong and his colleagues report in the Journal of Clinical Investigation .
“ This is the first time we understand there is a novel pathway that leads to autophagy ’ s dysfunction in a chronic kidney disease condition like diabetes , ” says Dong , cellular biologist and Leon H. Charbonnier Endowed @ @ @ @ @ @ @ and Anatomy at the Medical College of Georgia at Augusta University .
“ I think it also suggests that we have a targeted pathway to prevent or slow progression of kidney failure , ” says Dong , the study ’ s corresponding author , who is also a senior career scientist and director of research development at the Charlie Norwood Veterans Affairs Medical Center in Augusta .
Dr. Zhengwei Ma , MCG research associate , is first author .
Diabetes affects about 100 million adults in the United States , diabetic kidney disease @ @ @ @ @ @ @ is the leading cause of chronic kidney disease and kidney failure , according to the Centers for Disease Control and Prevention .
Scientists like Dong studying the hazardous intersection of diabetes and the kidneys were giving conflicting reports on the state of autophagy : Some saying it went up , others finding it went down .
Dong and his colleagues have now found both were correct .
They found autophagy levels naturally , initially increase in response to the stress of diabetes , but quickly drop off as a protein best known as @ @ @ @ @ @ @ normally involved in regulating autophagy .
What follows is unhealthy overgrowth — of individual cells and the organ — called hypertrophy , scarring , inflammation and protein spilling into the urine , a classic sign the kidneys are failing .
“ This helps us not just understand the phenomenon — that there is initial activation , then it comes down — but we understand what actually causes that down-regulation in a disease state , ” Dong says .
The known tumor suppressor is p53 , the microRNA is miR-214 and the autophagy gene @ @ @ @ @ @ @ , one of the first genes found to regulate this important metabolic function .
To measure the impact of this path on autophagy , they used levels of the protein LC3 , found in the membranes of those sacks where cell parts gets piled for elimination , which is considered a reliable biomarker of autophagy levels .
They consistently found , in both animals and humans , higher activity of p53 and miR-214 and lower ULK1 and autophagy over a relatively short period of time .
In a mouse model of type 1 @ @ @ @ @ @ @ nine weeks there was no difference in the autophagy biomarker compared to healthy controls .
Two weeks later the biomarker was somewhat lower in the diabetic mice , and by age 11 weeks , it was significantly lower .
The diabetic mice were smaller overall but had larger kidneys because of hypertrophy and signs of renal tubule damage , including scarring and inflammation .
“ Initially there is an increase , then a decrease and it keeps going down , ” Dong says , noting the apparent link between less autophagy and greater @ @ @ @ @ @ @ was protein in the urine and kidney failure .
Kidney cells incubated in high glucose also show this initial increase then , as little as a day later , an autophagy decrease , Dong says .
When they knocked out the autophagy gene , both kidney failure and hypertrophy got even worse , and when they activated the gene it prevented the downward progression .
They found in this dynamic pathway that autophagy went down because levels of the autophagy activating gene ULK1 went significantly down , and that ULK1 went down because @ @ @ @ @ @ @ about 30 genes involved in autophagy and they found ULK1 most consistently down in their diabetes models and in kidney biopsies from patients with diabetes .
So they backed up a step to find what was regulating miR-214 and found p53 , the known tumor suppressor that is also known to regulate the cell cycle and which they also think is a stress responder , likely to help eliminate bad cells .
When they knocked out or suppressed miR-214 from the cells of the long tubules right off the kidneys ’ filtering units @ @ @ @ @ @ @ of valuable items like proteins and amino acids normally happens , ULK1 expression and autophagy activity did not decrease in diabetes .
There was less unhealthy overgrowth of the kidney and better kidney function , indicated by less spilling of protein .
So they went back one step again , this time blocked p53 and saw miR-214 levels did not go up and the downstream benefits of blocking its action were essentially the same .
When they compared human samples of patients with diabetes to biopsies of healthy kidneys , none of the @ @ @ @ @ @ @ it was present in 15 of the 20 biopsies of patients who had diabetes and varying stages of related kidney problems .
There were similar findings about miR-214 .
The healthy kidneys showed high levels of ULk1 as they should and diabetes biopsies had low levels of this well-established frontline autophagy gene .
“ We have a signaling pathway that is very important to hypertrophy , for cell death and inflammation in diabetes that finally leads to kidney failure , ” Dong says , and interfering with that pathway could make a big @ @ @ @ @ @ @ kidneys are in jeopardy .
“ Instead of progressing in 10 to 12 years into kidney failure , we may be able to slow it down to 20 or 30 years or prevent it from happening , ” he says .
miR-214 is a logical intervention target because it clearly stands in the way of autophagy in the face of diabetes and normally has no obvious role in kidney function , Dong says .
p53 is likely not a good target for a chronic problem like diabetic kidney disease because of its clear @ @ @ @ @ @ @ says , however increasing ULK1 levels is another treatment possibility .
Hypertrophy is part of the pathogenic process that leads to kidney failure , Dong says , as tubular cells have to work harder and get bigger as a result , like an arm muscle responding to weight lifting , but at some point it results in dysfunction .
Autophagy is activated to protect those renal tubule cells .
“ This helps the cell combat stress to enable it to still survive , ” Dong says .
And it may be a key @ @ @ @ @ @ @ an acute kidney injury , which as the name implies , indicates some sort of sudden damage to the kidneys like a blockage of blood flow or a serious burn .
“ We know in patients with acute kidney injury , the outcome is very different in different people , ” Dong says .
The kidneys of generally healthy people tend to recover with proper care , while those with existing health problems that affect the kidneys , like hypertension and diabetes , or who are simply over age 75 , may proceed @ @ @ @ @ @ @ or an organ transplant to survive .
It was known that autophagy is protective and activated in an acute kidney injury and Dong got the idea that maybe in diabetes that protection is lost or at least impaired .
A subsequent study by another investigator showed that people with obesity related type 2 diabetes did have impaired autophagy , which matched what they were seeing in the lab , so he decided to focus on why the decrease .
Metabolic changes occur in diabetes , like high levels of glucose , inflammation and @ @ @ @ @ @ @ mitochondria , can dysfunction ; and the endoplasmic reticulum where proteins are properly folded , can be disrupted .
The kidney can grow larger , initially likely to accommodate the challenging work environment , but if it continues , the kidney , much like a heart in failure , may become enlarged , and its function diminished or destroyed , Dong says .
Patients with diabetes who develop hypertrophy are more likely to develop end stage renal disease , the scientists write .
While he is not certain impaired autophagy completely explains the @ @ @ @ @ @ @ contributes to it .
Cell stress is a major instigator of the low , so-called basal , level of autophagy that is going on all the time throughout the body .
Problems with autophagy already are associated with diseases from cancer to Alzheimer ’ s and heart disease , and it ’ s also implicated in diabetes .
Some cells need more rigorous autophagy , like high-functioning neurons that are supposed to last a lifetime , and the podocytes that wrap around tiny capillaries in the approximately 1 million filtering units inside each @ @ @ @ @ @ @ them in a healthy condition their whole life , ” Dong says of the podocytes that keep a tight grip on capillaries with little foot-like extensions and are essential to the essential filtering role of the kidney , like keeping proteins from being lost in the urine .
Renal tubule cells , which were the focus of the study , and carry urine out of the filtering units toward the bladder , filtering salt and water along the way , are the most prominent kidney cell type and they normally function well with @ @ @ @ @ @ @ says .
Evidence of inadequate clearance of dysfunctional components has been found in the tubule cells of the kidney , and there is a consensus that autophagy is impaired in this common kidney condition , Dong says .
Both type 1 and 2 diabetes tend to be lifelong conditions and the kidneys an early target of high levels of glucose in the blood which damages blood vessels , which can drive up blood pressure , which causes more damage .
Ultimately the oversized kidneys will shrink because of degeneration and scarring .
For @ @ @ @ @ @ @ with diabetes and 14 people without diabetes were provided by the Department of Nephrology of Changzheng Hospital at the Second Military Medical University in Shanghai .
Other collaborators on the study include scientists from the Department of Emergency Medicine at Second Xiangya Hospital at Central South University in Changsha , China ; and the Center for Cutaneous Biology and Immunology Research , Department of Dermatology at Henry Ford Health System in Detroit .
The research was funded by the Department of Veterans Affairs and the National Institutes of Health .
PRINCIPIA SCIENTIFIC INTERNATIONAL @ @ @ @ @ @ @ a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

Diabetes dramatically reduces the kidney’s ability clean itself
Written by Medical College of Georgia at Augusta University
The kidneys often become bulky and dysfunctional in diabetes, and now scientists have found that one path to this damage dramatically reduces the kidney’s ability to clean up after itself.
The natural cleanup is called autophagy, which literally means “self-eating,” and it’s a constant throughout our bodies as debris, like misfolded proteins and damaged cell powerhouses called mitochondria, get packaged into a double-membrane sack, then destroyed by enzymes to help keep cells and organs functioning at a premium.
Autophagy tends to increase in the face of disease challenges like diabetes, but the scientists have found a pathway that then quickly decreases autophagy in both animal models and humans with varying stages of this chronic condition, leaving the kidneys more vulnerable, Dr. Zheng Dong and his colleagues report in the Journal of Clinical Investigation.
“This is the first time we understand there is a novel pathway that leads to autophagy’s dysfunction in a chronic kidney disease condition like diabetes,” says Dong, cellular biologist and Leon H. Charbonnier Endowed Chair in the Department of Cellular Biology and Anatomy at the Medical College of Georgia at Augusta University.
“I think it also suggests that we have a targeted pathway to prevent or slow progression of kidney failure,” says Dong, the study’s corresponding author, who is also a senior career scientist and director of research development at the Charlie Norwood Veterans Affairs Medical Center in Augusta. Dr. Zhengwei Ma, MCG research associate, is first author.
Diabetes affects about 100 million adults in the United States, diabetic kidney disease is a major complication of diabetes and is the leading cause of chronic kidney disease and kidney failure, according to the Centers for Disease Control and Prevention.
Scientists like Dong studying the hazardous intersection of diabetes and the kidneys were giving conflicting reports on the state of autophagy: Some saying it went up, others finding it went down. Dong and his colleagues have now found both were correct.
They found autophagy levels naturally, initially increase in response to the stress of diabetes, but quickly drop off as a protein best known as a tumor suppressor activates a microRNA not normally involved in regulating autophagy. What follows is unhealthy overgrowth — of individual cells and the organ — called hypertrophy, scarring, inflammation and protein spilling into the urine, a classic sign the kidneys are failing.
“This helps us not just understand the phenomenon — that there is initial activation, then it comes down — but we understand what actually causes that down-regulation in a disease state,” Dong says.
The known tumor suppressor is p53, the microRNA is miR-214 and the autophagy gene this pair conspires to suppress is ULK1, one of the first genes found to regulate this important metabolic function.
To measure the impact of this path on autophagy, they used levels of the protein LC3, found in the membranes of those sacks where cell parts gets piled for elimination, which is considered a reliable biomarker of autophagy levels.
They consistently found, in both animals and humans, higher activity of p53 and miR-214 and lower ULK1 and autophagy over a relatively short period of time.
In a mouse model of type 1 diabetes, for example, at age nine weeks there was no difference in the autophagy biomarker compared to healthy controls. Two weeks later the biomarker was somewhat lower in the diabetic mice, and by age 11 weeks, it was significantly lower. The diabetic mice were smaller overall but had larger kidneys because of hypertrophy and signs of renal tubule damage, including scarring and inflammation.
“Initially there is an increase, then a decrease and it keeps going down,” Dong says, noting the apparent link between less autophagy and greater hypertrophy. By 20 weeks, there was protein in the urine and kidney failure. Kidney cells incubated in high glucose also show this initial increase then, as little as a day later, an autophagy decrease, Dong says.
When they knocked out the autophagy gene, both kidney failure and hypertrophy got even worse, and when they activated the gene it prevented the downward progression.
They found in this dynamic pathway that autophagy went down because levels of the autophagy activating gene ULK1 went significantly down, and that ULK1 went down because miR-214 went way up. There are about 30 genes involved in autophagy and they found ULK1 most consistently down in their diabetes models and in kidney biopsies from patients with diabetes.
So they backed up a step to find what was regulating miR-214 and found p53, the known tumor suppressor that is also known to regulate the cell cycle and which they also think is a stress responder, likely to help eliminate bad cells.
When they knocked out or suppressed miR-214 from the cells of the long tubules right off the kidneys’ filtering units, where a lot of the resorption of valuable items like proteins and amino acids normally happens, ULK1 expression and autophagy activity did not decrease in diabetes. There was less unhealthy overgrowth of the kidney and better kidney function, indicated by less spilling of protein. So they went back one step again, this time blocked p53 and saw miR-214 levels did not go up and the downstream benefits of blocking its action were essentially the same.
When they compared human samples of patients with diabetes to biopsies of healthy kidneys, none of the normal samples had signs of p53 but it was present in 15 of the 20 biopsies of patients who had diabetes and varying stages of related kidney problems. There were similar findings about miR-214. The healthy kidneys showed high levels of ULk1 as they should and diabetes biopsies had low levels of this well-established frontline autophagy gene.
“We have a signaling pathway that is very important to hypertrophy, for cell death and inflammation in diabetes that finally leads to kidney failure,” Dong says, and interfering with that pathway could make a big difference in the lives of patients whose kidneys are in jeopardy.
“Instead of progressing in 10 to 12 years into kidney failure, we may be able to slow it down to 20 or 30 years or prevent it from happening,” he says.
miR-214 is a logical intervention target because it clearly stands in the way of autophagy in the face of diabetes and normally has no obvious role in kidney function, Dong says. p53 is likely not a good target for a chronic problem like diabetic kidney disease because of its clear function as a tumor suppressor, he says, however increasing ULK1 levels is another treatment possibility.
Hypertrophy is part of the pathogenic process that leads to kidney failure, Dong says, as tubular cells have to work harder and get bigger as a result, like an arm muscle responding to weight lifting, but at some point it results in dysfunction. Autophagy is activated to protect those renal tubule cells.
“This helps the cell combat stress to enable it to still survive,” Dong says. And it may be a key difference in the resilience of kidneys following an acute kidney injury, which as the name implies, indicates some sort of sudden damage to the kidneys like a blockage of blood flow or a serious burn.
“We know in patients with acute kidney injury, the outcome is very different in different people,” Dong says. The kidneys of generally healthy people tend to recover with proper care, while those with existing health problems that affect the kidneys, like hypertension and diabetes, or who are simply over age 75, may proceed to kidney failure, which requires dialysis or an organ transplant to survive. It was known that autophagy is protective and activated in an acute kidney injury and Dong got the idea that maybe in diabetes that protection is lost or at least impaired. A subsequent study by another investigator showed that people with obesity related type 2 diabetes did have impaired autophagy, which matched what they were seeing in the lab, so he decided to focus on why the decrease.
Metabolic changes occur in diabetes, like high levels of glucose, inflammation and oxidative stress; cell powerhouses, called mitochondria, can dysfunction; and the endoplasmic reticulum where proteins are properly folded, can be disrupted. The kidney can grow larger, initially likely to accommodate the challenging work environment, but if it continues, the kidney, much like a heart in failure, may become enlarged, and its function diminished or destroyed, Dong says. Patients with diabetes who develop hypertrophy are more likely to develop end stage renal disease, the scientists write. While he is not certain impaired autophagy completely explains the unhealthy growth, he is confident it contributes to it.
Cell stress is a major instigator of the low, so-called basal, level of autophagy that is going on all the time throughout the body. Problems with autophagy already are associated with diseases from cancer to Alzheimer’s and heart disease, and it’s also implicated in diabetes.
Some cells need more rigorous autophagy, like high-functioning neurons that are supposed to last a lifetime, and the podocytes that wrap around tiny capillaries in the approximately 1 million filtering units inside each kidney.
“You need to keep them in a healthy condition their whole life,” Dong says of the podocytes that keep a tight grip on capillaries with little foot-like extensions and are essential to the essential filtering role of the kidney, like keeping proteins from being lost in the urine.
Renal tubule cells, which were the focus of the study, and carry urine out of the filtering units toward the bladder, filtering salt and water along the way, are the most prominent kidney cell type and they normally function well with relatively low levels of autophagy, Dong says. Evidence of inadequate clearance of dysfunctional components has been found in the tubule cells of the kidney, and there is a consensus that autophagy is impaired in this common kidney condition, Dong says.
Both type 1 and 2 diabetes tend to be lifelong conditions and the kidneys an early target of high levels of glucose in the blood which damages blood vessels, which can drive up blood pressure, which causes more damage. Ultimately the oversized kidneys will shrink because of degeneration and scarring.
For the study, biopsies from 20 people with diabetes and 14 people without diabetes were provided by the Department of Nephrology of Changzheng Hospital at the Second Military Medical University in Shanghai. Other collaborators on the study include scientists from the Department of Emergency Medicine at Second Xiangya Hospital at Central South University in Changsha, China; and the Center for Cutaneous Biology and Immunology Research, Department of Dermatology at Henry Ford Health System in Detroit.
The research was funded by the Department of Veterans Affairs and the National Institutes of Health.
Read the full study here.
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principiascientificinternational--2020-09-25--Dumbest Math Theory Ever? The Greenhouse Gas Effect!

Mainstream climate scientists believe in the dumbest math theory ever devised to try and explain physical reality .
It is called the Greenhouse Effect .
It ’ s so silly an unbelievable that I don ’ t even want to give it the honor of calling it a scientific theory , because it is nothing but ideological mathematics that has never been empirically validated .
In fact it is nothing but a post hoc fallacy : the surface is hotter than what the sun alone can do , therefore greenhouse gases did it !
Today we will play with this @ @ @ @ @ @ @ .
Here are two examples of its typical canonical depiction : Let ’ s get started .
Please create a new file called gheffect , and paste the following into it : Now run it with atmospheric emissivity = 0.792 : W is shorthand for W/m² .
Parameters are taken from NASA Earth Fact Sheet .
As you can see , by delaying outgoing radiation for 14 [ ¹ ] seconds [ ² ] , we have boosted surface up-welling radiation by an additional ~66 % ( 154.8/236.1 W/m² ) .
Amazing , @ @ @ @ @ @ @ program shows , and that ’ s what is claimed : The main prediction of the theory is that as the atmosphere absorbs more infrared radiation , the surface will get warmer .
Let ’ s rerun the program with a higher atmospheric emissivity = 0.8 You would think such intelligent and “ correct ” mathematics would be based on actual experiments , but you would be wrong ; it is not based on anything other than its presuppositions , and has been so for more than a century by name , and @ @ @ @ @ @ @ s outline a very simple experiment to test whether the greenhouse effect is true : Radiation leaves the body and strikes a screen .
After absorption some radiation will go out to the IR camera , and the rest will go back to the person , thereby warming them up further , according to greenhouse effect theory .
Note that we don ’ t even need absorption , merely reflecting back a person ’ s radiation should warm them up .
Let ’ s assume the human body emits 522.7 W/m² ( 37 @ @ @ @ @ @ @ [ Sanchez-Marin 2009 ] ) .
For compatibility with my program , we multiply this figure by 4 , and call it TSI .
Let ’ s assume the screen and air in between together has a total emissivity of 0.9 .
Now run : We see that the screen is “ trapping ” a lot of human radiation from reaching the IR camera , and we expect an extra 296.8 W/m² greenhouse effect , bringing us up to 55°C .
Merely placing a screen in front of us should make us feel @ @ @ @ @ @ @ a sauna .
These people must be really feeling the heat .
But they don ’ t , and for good reason : preventing radiation from reaching a colder place does not cause heating back at the source .
Had these people had thermometers strapped to them , they would note the virtually zero temperature rise ( due to blocked convection ) .
Look very closely at the videos .
Note the seconds the screens are placed in front of their faces and notice the lack of any thermal reading changes .
None @ @ @ @ @ @ @ of the claims of the greenhouse effect .
So the question remains , why is the surface hotter than the sun can make it alone ?
If we look at the energy budget , we can see a dependency loop between surface and atmosphere : Surface - > Atmo = 350 and Atmo - > Surface = 324 .
So which came first , the chicken or the egg ?
This is nonsense .
You can ’ t have a dependency loop for heat flow .
Let ’ s try a theory that @ @ @ @ @ @ @ empirical evidence .
For this , we ignore the climate “ scientists ” , and go to the geophysicists : Here we see that Earth ’ s geothermal energy is capable of delivering 0 °C to the surface ; This is equivalent to 315.7 W/m² .
We add the sun and subtract latent+sensible heat : Now we get a figure that that ’ s 390 – 381.7 = 8.3 W/m² off , but that ’ s OK because latent and sensible heat are not directly measured but estimated with certain physical assumptions , @ @ @ @ @ @ @ approximation too .
Now we finally realize that the greenhouse effect is a hoax , and nothing but geothermal flipped up-side down .
There is no Downwelling Radiation , there is only Upwelling-from-measurement-instrument Radiation ( See here ) .
Those who read Why is Venus so hot ?
, probably already saw where I was going .
Now doesn ’ t it make more sense than backradiation temperature raising ?
Reality shows abolutely normal geothermal and solar combining to produce what we observe .
We see all normal heating , and no ugly @ @ @ @ @ @ @ does Occam ’ s Razor favor ?
I hope you have enjoyed the return to sanity .
[ ¹ ] We only care about matching 3 decimal places .
If we want to extend it to IEEE754 64-bit precision , it takes 40 seconds .
Not that this matters much ; Most work is accomplished in the first 5 seconds .
[ ² ] I debated with myself whether to use the term seconds or iterations .
Real physical calculations would take mass and heat capacity into account , but since greenhouse theorists @ @ @ @ @ @ @ won ’ t either .
Their simple model is in seconds .
PRINCIPIA SCIENTIFIC INTERNATIONAL , legally registered in the UK as a company incorporated for charitable purposes .
Head Office : 27 Old Gloucester Street , London WC1N 3AX .
Please DONATE TODAY To Help Our Non-Profit Mission To Defend The Scientific Method .

Dumbest Math Theory Ever? The Greenhouse Gas Effect!
Written by Zoe Phin
Mainstream climate scientists believe in the dumbest math theory ever devised to try and explain physical reality. It is called the Greenhouse Effect. It’s so silly an unbelievable that I don’t even want to give it the honor of calling it a scientific theory, because it is nothing but ideological mathematics that has never been empirically validated. In fact it is nothing but a post hoc fallacy: the surface is hotter than what the sun alone can do, therefore greenhouse gases did it!
Today we will play with this silly math theory called the greenhouse effect. Here are two examples of its typical canonical depiction:
Let’s get started. Please create a new file called gheffect, and paste the following into it:
# bash gheffect # Zoe Phin, 2020/03/03 [ -z $TSI ] && TSI=1361 [ -z $ALB ] && ALB=0.306 echo $1 | awk -vALB=$ALB -vTSI=$TSI 'BEGIN { SIG = 5.67E-8 ; CURR = LAST = SUN = TSI*(1-ALB)/4 printf "Sec | Upwelling | Temp | GH Effect | Trapped | To Space
" } { for (i=1 ;; i++) { printf "%3d | %7.3f W | %7.3f C ", i, CURR, (CURR/SIG)^0.25-273.16 CURR = SUN + $1*LAST/2 ; GHE = SUN - (LAST*(1-$1)) printf "| %7.3f W | %7.3f W | %07.3f W
", GHE, CURR-LAST, CURR-GHE if ( sprintf("%.3f", CURR) == sprintf("%.3f", LAST) ) break #if ( CURR==LAST ) break LAST = CURR } }'
Now run it with atmospheric emissivity = 0.792:
$ bash gheffect 0.792 Sec | Upwelling | Temp | GH Effect | Trapped | To Space 1 | 236.133 W | -19.125 C | 187.018 W | 93.509 W | 142.625 W 2 | 329.642 W | 2.971 C | 167.568 W | 37.030 W | 199.104 W 3 | 366.672 W | 10.419 C | 159.866 W | 14.664 W | 221.470 W 4 | 381.336 W | 13.212 C | 156.816 W | 5.807 W | 230.327 W 5 | 387.142 W | 14.296 C | 155.608 W | 2.300 W | 233.834 W 6 | 389.442 W | 14.722 C | 155.130 W | 0.911 W | 235.223 W 7 | 390.352 W | 14.890 C | 154.940 W | 0.361 W | 235.773 W 8 | 390.713 W | 14.957 C | 154.865 W | 0.143 W | 235.991 W 9 | 390.856 W | 14.983 C | 154.835 W | 0.057 W | 236.077 W 10 | 390.912 W | 14.994 C | 154.824 W | 0.022 W | 236.111 W 11 | 390.935 W | 14.998 C | 154.819 W | 0.009 W | 236.125 W 12 | 390.944 W | 14.999 C | 154.817 W | 0.004 W | 236.130 W 13 | 390.947 W | 15.000 C | 154.816 W | 0.001 W | 236.132 W 14 | 390.949 W | 15.000 C | 154.816 W | 0.001 W | 236.133 W
W is shorthand for W/m². Parameters are taken from NASA Earth Fact Sheet.
As you can see, by delaying outgoing radiation for 14 [¹] seconds [²], we have boosted surface up-welling radiation by an additional ~66% (154.8/236.1 W/m²). Amazing, right? That’s what my program shows, and that’s what is claimed:
This is zero in the absence of any long‐wave absorbers, and around 155 W/m² in the present‐day atmosphere [Kiehl and Trenberth, 1997]. This reduction in outgoing LW flux drives the 33°C greenhouse effect … — Attribution of the present‐day total greenhouse effect
The main prediction of the theory is that as the atmosphere absorbs more infrared radiation, the surface will get warmer. Let’s rerun the program with a higher atmospheric emissivity = 0.8
$ bash gheffect 0.8 Sec | Upwelling | Temp | GH Effect | Trapped | To Space 1 | 236.133 W | -19.125 C | 188.907 W | 94.453 W | 141.680 W 2 | 330.587 W | 3.168 C | 170.016 W | 37.781 W | 198.352 W 3 | 368.368 W | 10.746 C | 162.460 W | 15.113 W | 221.021 W 4 | 383.481 W | 13.614 C | 159.437 W | 6.045 W | 230.088 W 5 | 389.526 W | 14.738 C | 158.228 W | 2.418 W | 233.715 W 6 | 391.944 W | 15.184 C | 157.745 W | 0.967 W | 235.166 W 7 | 392.911 W | 15.361 C | 157.551 W | 0.387 W | 235.747 W 8 | 393.298 W | 15.432 C | 157.474 W | 0.155 W | 235.979 W 9 | 393.453 W | 15.461 C | 157.443 W | 0.062 W | 236.072 W 10 | 393.515 W | 15.472 C | 157.431 W | 0.025 W | 236.109 W 11 | 393.539 W | 15.477 C | 157.426 W | 0.010 W | 236.124 W 12 | 393.549 W | 15.478 C | 157.424 W | 0.004 W | 236.130 W 13 | 393.553 W | 15.479 C | 157.423 W | 0.002 W | 236.132 W 14 | 393.555 W | 15.479 C | 157.423 W | 0.001 W | 236.133 W
A 1% rise in atmospheric emissivity (0.8/0.792) predicts a 0.479 °C rise in surface temperature.
You would think such intelligent and “correct” mathematics would be based on actual experiments, but you would be wrong; it is not based on anything other than its presuppositions, and has been so for more than a century by name, and two centuries by concept.
Let’s outline a very simple experiment to test whether the greenhouse effect is true:
Solid Surface v 1) Person => | IR Camera 2) Person <- | -> IR Camera And repeats until "equilibrium"
Radiation leaves the body and strikes a screen. After absorption some radiation will go out to the IR camera, and the rest will go back to the person, thereby warming them up further, according to greenhouse effect theory. Note that we don’t even need absorption, merely reflecting back a person’s radiation should warm them up.
Let’s assume the human body emits 522.7 W/m² (37 °C) (Emissivity: 0.9961, [Sanchez-Marin 2009]). For compatibility with my program, we multiply this figure by 4, and call it TSI. Let’s assume the screen and air in between together has a total emissivity of 0.9. Now run:
$ TSI=2090.8 bash gheffect 0.9 Sec | Upwelling | Temp | GH Effect | Trapped | To Space 1 | 362.754 W | 9.658 C | 326.478 W | 163.239 W | 199.515 W 2 | 525.993 W | 37.188 C | 310.154 W | 73.458 W | 289.296 W 3 | 599.451 W | 47.498 C | 302.809 W | 33.056 W | 329.698 W 4 | 632.507 W | 51.830 C | 299.503 W | 14.875 W | 347.879 W 5 | 647.382 W | 53.725 C | 298.016 W | 6.694 W | 356.060 W 6 | 654.076 W | 54.566 C | 297.346 W | 3.012 W | 359.742 W 7 | 657.088 W | 54.943 C | 297.045 W | 1.356 W | 361.398 W 8 | 658.443 W | 55.112 C | 296.909 W | 0.610 W | 362.144 W 9 | 659.053 W | 55.188 C | 296.848 W | 0.274 W | 362.479 W 10 | 659.328 W | 55.222 C | 296.821 W | 0.124 W | 362.630 W 11 | 659.451 W | 55.238 C | 296.809 W | 0.056 W | 362.698 W 12 | 659.507 W | 55.244 C | 296.803 W | 0.025 W | 362.729 W 13 | 659.532 W | 55.248 C | 296.801 W | 0.011 W | 362.743 W 14 | 659.543 W | 55.249 C | 296.799 W | 0.005 W | 362.749 W 15 | 659.548 W | 55.250 C | 296.799 W | 0.002 W | 362.752 W 16 | 659.550 W | 55.250 C | 296.799 W | 0.001 W | 362.753 W 17 | 659.552 W | 55.250 C | 296.799 W | 0.000 W | 362.753 W
We see that the screen is “trapping” a lot of human radiation from reaching the IR camera, and we expect an extra 296.8 W/m² greenhouse effect, bringing us up to 55°C. Merely placing a screen in front of us should make us feel as if we’re stepping inside a sauna.
https://youtu.be/fpx7hsoYEt4 – Look at all the trapped radiation!
https://youtu.be/Fx49t4sv7f0 – Look at all the trapped radiation!
These people must be really feeling the heat. But they don’t, and for good reason: preventing radiation from reaching a colder place does not cause heating back at the source. Had these people had thermometers strapped to them, they would note the virtually zero temperature rise (due to blocked convection). Look very closely at the videos. Note the seconds the screens are placed in front of their faces and notice the lack of any thermal reading changes. None!
All empirical evidence shows the opposite of the claims of the greenhouse effect.
So the question remains, why is the surface hotter than the sun can make it alone?
Energy Budget
If we look at the energy budget, we can see a dependency loop between surface and atmosphere: Surface -> Atmo = 350 and Atmo -> Surface = 324. So which came first, the chicken or the egg? This is nonsense. You can’t have a dependency loop for heat flow. Let’s try a theory that does not cause mental anguish and lacks empirical evidence. For this, we ignore the climate “scientists”, and go to the geophysicists:
Here we see that Earth’s geothermal energy is capable of delivering 0 °C to the surface; This is equivalent to 315.7 W/m². We add the sun and subtract latent+sensible heat:
315.7 + 168 – 24 – 78 = 381.7 = Upwelling Radiadtion
Now we get a figure that that’s 390 – 381.7 = 8.3 W/m² off, but that’s OK because latent and sensible heat are not directly measured but estimated with certain physical assumptions, and/or the 0 °C geothermal is an approximation too.
Now we finally realize that the greenhouse effect is a hoax, and nothing but geothermal flipped up-side down. There is no Downwelling Radiation, there is only Upwelling-from-measurement-instrument Radiation (See here). Those who read Why is Venus so hot?, probably already saw where I was going. Now doesn’t it make more sense than backradiation temperature raising? Reality shows abolutely normal geothermal and solar combining to produce what we observe. We see all normal heating, and no ugly backwards zig-zag heating.
Let’s summarize:
Upwelling ^ | | ^ ^ v | | | =============================== | Latent Sensible Solar ---+ Heat Heat | ^ ^ | | | +------ Geothermal
Now which explanation does Occam’s Razor favor?
I hope you have enjoyed the return to sanity.
Sincerely, -Zoe
Notes
[¹] We only care about matching 3 decimal places. If we want to extend it to IEEE754 64-bit precision, it takes 40 seconds. Not that this matters much; Most work is accomplished in the first 5 seconds.
[²] I debated with myself whether to use the term seconds or iterations. Real physical calculations would take mass and heat capacity into account, but since greenhouse theorists don’t use these, I won’t either. Their simple model is in seconds.
Read more at phzoe.com
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principiascientificinternational--2020-09-25--CDC Posts Unproven Guidance that COVID-19 Remains Suspended in Air

The CDC continues to beclown itself .
The radical politicized health organization admitted to randomly posting unproven guidance on the COVID-19 virus on their website.What a disgrace !
This comes after a report last week that the CDC included 5,692 intentional injuries and poisonings in their total US coronavirus death count .
This follows a previous Gateway Pundit report that only 9,210 COVID-19 victims in the US died from the coronavirus alone .
The rest involved patients with serious comorbidities .
This was such an egregious mistake that even the wholly biased WHO even called them out !
We need @ @ @ @ @ @ @ Disease Control and Prevention said Monday that it erroneously posted guidance that said the coronavirus spreads through airborne particles that can remain suspended in the air and travel beyond six feet .
The updated guidance , posted on the CDC ’ s website on Friday , also recommended that people use air purifiers to reduce airborne germs indoors to prevent the disease from spreading , according to Reuters .
“ A draft version of proposed changes to these recommendations was posted in error to the agency ’ s official website , ” the @ @ @ @ @ @ @ currently updating its recommendations regarding airborne transmission of SARS-CoV-2 ( the virus that causes COVID-19 ) .
Once this process has been completed , the update language will be posted.
” Earlier in the day , the World Health Organization said it contacted the CDC about the guidance change .
The WHO had not seen any “ new evidence ” on airborne particles and was checking with the CDC to “ better understand ” the exact nature of the change , Dr. Mike Ryan , executive director of the WHO ’ s health @ @ @ @ @ @ @ conference at the agency ’ s Geneva headquarters .
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CDC Posts Unproven Guidance that COVID-19 Remains Suspended in Air
Written by Jim Hoft
The CDC continues to beclown itself. The radical politicized health organization admitted to randomly posting unproven guidance on the COVID-19 virus on their website.What a disgrace!
This comes after a report last week that the CDC included 5,692 intentional injuries and poisonings in their total US coronavirus death count.
This follows a previous Gateway Pundit report that only 9,210 COVID-19 victims in the US died from the coronavirus alone. The rest involved patients with serious comorbidities.
This was such an egregious mistake that even the wholly biased WHO even called them out! We need a new CDC!
CNBC reported:
The Centers for Disease Control and Prevention said Monday that it erroneously posted guidance that said the coronavirus spreads through airborne particles that can remain suspended in the air and travel beyond six feet. The updated guidance, posted on the CDC’s website on Friday, also recommended that people use air purifiers to reduce airborne germs indoors to prevent the disease from spreading, according to Reuters. “A draft version of proposed changes to these recommendations was posted in error to the agency’s official website,” the CDC said Monday. “CDC is currently updating its recommendations regarding airborne transmission of SARS-CoV-2 (the virus that causes COVID-19). Once this process has been completed, the update language will be posted.” Earlier in the day, the World Health Organization said it contacted the CDC about the guidance change. The WHO had not seen any “new evidence” on airborne particles and was checking with the CDC to “better understand” the exact nature of the change, Dr. Mike Ryan, executive director of the WHO’s health emergencies program, said during a news conference at the agency’s Geneva headquarters.
Read more at www.thegatewaypundit.com
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principiascientificinternational--2020-09-25--Harvard epidemiologist: lockdowns a disaster

The White House press conference of September 23rd 2020 , featuring Dr. Scott Atlas , was an extraordinary thing to watch .
Against a hostile media ( of course ) , Atlas flat-out contradicted the CDC ’ s Dr. Redfield and taught the up-to-date science that the country needs to hear — the very research that Dr. Fauci had bizarrely tried , in his exchange with Rand Paul , to claim did not exist .
The main exchange Atlas had with the press involved Redfield ’ s claim that 90 percent of Americans were still susceptible to the virus .
@ @ @ @ @ @ @ Atlas said .
First , he said , Redfield was basing this claim on surveillance data showing that nine percent of Americans had antibodies .
The problem here , said Atlas , is that much of this state-by-state data is old , going back to March or April , before cases had really begun to spread in many states .
“ The immunity to the infection is not solely determined by the percent of people who have antibodies .
If you look at the research — and there ’ s been about 24 @ @ @ @ @ @ @ T-cells , that ’ s a different type of immunity than antibodies… .
According to the papers from Sweden , Singapore , and elsewhere , there is cross-immunity , highly likely from other infections , and there is also T-cell immunity .
And the combination of those makes the antibodies a small fraction of the people that have immunity .
So the answer is no , it is not 90 percent of people that are susceptible to the infection.
” Later in the exchange Atlas refers the media to top epidemiologists : Jay @ @ @ @ @ @ @ Sunetra Gupta at Oxford , and Martin Kulldorff of Harvard Medical School .
Well , as it happens , Martin Kulldorff is my guest on today ’ s episode of the Tom Woods Show .
Kulldorff , a professor of medicine at Harvard Medical School , is a biostatistician and epidemiologist whose research centers on the early detection and monitoring of infectious disease outbreaks .
He has been against lockdowns from day 1 .
I asked him whether , with a harsh enough lockdown , suppression of the virus was even possible .
@ @ @ @ @ @ @ looking at , and whether the number of “ cases ” even mattered .
We talked about the excessive sensitivity of the PCR testing in the United States and what the implications of that are .
We talked about the collateral damage caused by lockdowns .
I asked him for his opinion of Dr. Fauci .
We covered a lot of ground — and I asked him pretty much every question to which a reasonable person would want an answer .
I urge you to find the time to listen : tomwoods.com PRINCIPIA @ @ @ @ @ @ @ UK as a company incorporated for charitable purposes .
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Harvard epidemiologist: lockdowns a disaster
Written by Tom Woods
The White House press conference of September 23rd 2020, featuring Dr. Scott Atlas, was an extraordinary thing to watch. Against a hostile media (of course), Atlas flat-out contradicted the CDC’s Dr. Redfield and taught the up-to-date science that the country needs to hear — the very research that Dr. Fauci had bizarrely tried, in his exchange with Rand Paul, to claim did not exist.
The main exchange Atlas had with the press involved Redfield’s claim that 90 percent of Americans were still susceptible to the virus.
This was wrong on two counts, Atlas said.
First, he said, Redfield was basing this claim on surveillance data showing that nine percent of Americans had antibodies. The problem here, said Atlas, is that much of this state-by-state data is old, going back to March or April, before cases had really begun to spread in many states.
More importantly, Atlas adds:
“The immunity to the infection is not solely determined by the percent of people who have antibodies. If you look at the research — and there’s been about 24 papers at least on the immunity from T-cells, that’s a different type of immunity than antibodies…. According to the papers from Sweden, Singapore, and elsewhere, there is cross-immunity, highly likely from other infections, and there is also T-cell immunity. And the combination of those makes the antibodies a small fraction of the people that have immunity. So the answer is no, it is not 90 percent of people that are susceptible to the infection.”
Later in the exchange Atlas refers the media to top epidemiologists: Jay Bhattacharya and John Ioannidis from Stanford, Sunetra Gupta at Oxford, and Martin Kulldorff of Harvard Medical School.
Well, as it happens, Martin Kulldorff is my guest on today’s episode of the Tom Woods Show.
Kulldorff, a professor of medicine at Harvard Medical School, is a biostatistician and epidemiologist whose research centers on the early detection and monitoring of infectious disease outbreaks.
He has been against lockdowns from day 1.
I asked him whether, with a harsh enough lockdown, suppression of the virus was even possible. We discussed which metrics people should be looking at, and whether the number of “cases” even mattered.
We talked about the excessive sensitivity of the PCR testing in the United States and what the implications of that are. We talked about the collateral damage caused by lockdowns. I asked him for his opinion of Dr. Fauci.
And plenty more.
We covered a lot of ground — and I asked him pretty much every question to which a reasonable person would want an answer.
I urge you to find the time to listen: tomwoods.com
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principiascientificinternational--2020-09-25--COVID Fraud:The UK Government’s Outright Lies to The People

The UK Chief Scientific Officer Sir Patrick Vallance has just lied outright to the British people , yet again like Gates and Ferguson massively exaggerating the threat ( even disregarding that there are no matching deaths for cases ) and no one in the mainstream media notices and calls them on it .
“ At the moment we think that the epidemic is doubling roughly every 7 days , could be a little bit longer a little bit shorter , but roughly every seven days… If , and that ’ s quite a big if , but if that continues @ @ @ @ @ @ @ days then you what you see of course , let ’ s say we have 5000 today there would be 10,000 next week , 20k the week after , 40k the week after and you can see by mid-October if that continues we would end up with something like 50,000 cases in the middle of October per day… ” Doubling every seven days ( x1.104 per day , a little over 10 % per day ) in the dotted pink line , to get to 50,000 cases by mid-October .
Notice you have @ @ @ @ @ @ @ cases , else it would not be 50,000 a day but 6m cases a day .
So , like Ferguson , what he says as parameters and what he charts are utterly different .
Now compare the gradient of the pink line ( double every seven days ) with the actual cases and best-fits for growth for those cases , as illustrated by the other lines .
That ’ s 3.5 % per day , 27 % per week , or 1.27 times .
A bit lower than 2 times .
It will @ @ @ @ @ @ @ , not 50,000 .
Even that however misrepresents the ‘ contagion ’ in two fundamental ways : NO contagion is ‘ exponential ’ , growing exponentially for months .
Try and find any contagion in Google ( “ epidemic chart ” ) .
You will find that for Ebola , Sars , Flu ( 1918 and Seasonal ) , daily graphs are consistently standard humped curves .
DEATHS aren ’ t following the CASES as others have pointed out .
We can see that in the following chart : ( I download WHO @ @ @ @ @ @ @ do my own analysis and prepare my own charts ) .
The pink line in this chart shows what deaths should look like if they ’ re to track cases , using the 16 % death rate that the UK government found popular in the primary contagion .
That is a separate topic .
The red line shows that there simply are no deaths to match .
In fact , while cases have increased 10.8 times since the cases minimum , 14th July , deaths have actually fallen 9 % .
( We @ @ @ @ @ @ @ the daily variation somewhat ) .
To utterly mis-state the present situation in tree fundamental manners ( growth rate , exponential , no deaths ) : that isn ’ t a quirk , a slip , a minor error from the UK ’ s Chief Government Advisor… The pink line in the first chart can not by any stretch of the imagination be argued to be a good fit for the cluster of blue and gold lines which represent actual cases and best-fit growth lines .
This is fraud , pure and simple @ @ @ @ @ @ @ again , but exaggerate the epidemic .
The UK government has just formally re-committed to its original fraud with an entirely new scenario .
Thus the original fraud was not a mistake , any more than this one is .
{ Editor ’ s note : Any UK barrister/lawyer versed in pursuing actions against the government for abuse of power , misfeasance in public office , please contact me asap at : john @ principia-scientific.org } See his interview below on The UK Column : About the author : Andrew Mather is a @ @ @ @ @ @ @ under the title Peerless Reads .
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COVID Fraud:The UK Government’s Outright Lies to The People
Written by Andrew Mather
The UK Chief Scientific Officer Sir Patrick Vallance has just lied outright to the British people, yet again like Gates and Ferguson massively exaggerating the threat (even disregarding that there are no matching deaths for cases) and no one in the mainstream media notices and calls them on it.
“At the moment we think that the epidemic is doubling roughly every 7 days, could be a little bit longer a little bit shorter, but roughly every seven days… If, and that’s quite a big if, but if that continues unabated and this grows doubling every seven days then you what you see of course, let’s say we have 5000 today there would be 10,000 next week, 20k the week after, 40k the week after and you can see by mid-October if that continues we would end up with something like 50,000 cases in the middle of October per day…”
[ITV https://www.youtube.com/watch?v=Z5YAm-GccrE at 8 minutes]
So… here’s a chart with Vallance’s claim:
Doubling every seven days (x1.104 per day, a little over 10% per day) in the dotted pink line, to get to 50,000 cases by mid-October. Notice you have to start with 5 cases not 600 cases, else it would not be 50,000 a day but 6m cases a day. So, like Ferguson, what he says as parameters and what he charts are utterly different.
Now compare the gradient of the pink line (double every seven days) with the actual cases and best-fits for growth for those cases, as illustrated by the other lines. That’s 3.5% per day, 27% per week, or 1.27 times. A bit lower than 2 times. It will give rise to 8,580 cases per day, not 50,000.
Even that however misrepresents the ‘contagion’ in two fundamental ways:
The ‘Exponential’ Meme
Vallance refers to ‘continues unabated’ = same rate = exponential.
Whitty refers explicitly to exponential multiple times.
NO contagion is ‘exponential’, growing exponentially for months. Try and find any contagion in Google (“epidemic chart”). You will find that for Ebola, Sars, Flu (1918 and Seasonal), daily graphs are consistently standard humped curves.
The ‘It’s Real Not Testing’ Meme
DEATHS aren’t following the CASES as others have pointed out.
We can see that in the following chart: (I download WHO data from the WHO Covid-19 Dashboard, do my own analysis and prepare my own charts).
The pink line in this chart shows what deaths should look like if they’re to track cases, using the 16% death rate that the UK government found popular in the primary contagion. That is a separate topic.
The red line shows that there simply are no deaths to match. In fact, while cases have increased 10.8 times since the cases minimum, 14th July, deaths have actually fallen 9%. (We use a weekly average figure to smooth the daily variation somewhat).
To utterly mis-state the present situation in tree fundamental manners (growth rate, exponential, no deaths): that isn’t a quirk, a slip, a minor error from the UK’s Chief Government Advisor…
The pink line in the first chart cannot by any stretch of the imagination be argued to be a good fit for the cluster of blue and gold lines which represent actual cases and best-fit growth lines.
This is fraud, pure and simple, and what does it do yet again, but exaggerate the epidemic.
The UK government has just formally re-committed to its original fraud with an entirely new scenario. Thus the original fraud was not a mistake, any more than this one is.
We need a good lawyer.
{Editor’s note: Any UK barrister/lawyer versed in pursuing actions against the government for abuse of power, misfeasance in public office, please contact me asap at: [email protected]}
Watch Andrew Mather’s Youtube videos.
See his interview below on The UK Column:
About the author: Andrew Mather is a retired British mathematician and posts insightful videos under the title Peerless Reads.
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