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EXCLUSIVE: COVID-19 'has NO credible natural ancestor' and WAS created by Chinese scientists who then tried to cover their tracks with 'retro-engineering' to make it seem like it naturally arose from bats, explosive new study claims​

  • An explosive new study claims researchers found 'unique fingerprints' in COVID-19 samples that they say could only have arisen from manipulation in a laboratory
  • DailyMail.com exclusively obtained the new 22-page paper authored by British Professor Angus Dalgleish and Norwegian scientist Dr. Birger Sørensen set to be published in the Quarterly Review of Biophysics Discovery
  • The study showed there's evidence to suggest Chinese scientists created the virus while working on a Gain of Function project in a Wuhan lab
  • Gain of Function research, which was temporarily outlawed in the US, involves altering naturally-occurring viruses to make them more infectious in order to study their potential effects on humans
  • According to the paper, Chinese scientists took a natural coronavirus 'backbone' found in Chinese cave bats and spliced onto it a new 'spike', turning it into the deadly and highly transmissible COVID-19
  • The researchers, who concluded that COVID-19 'has no credible natural ancestor', also believe scientists reverse-engineered versions of the virus to cover up their tracks
  • 'We think that there have been retro-engineered viruses created,' Dalgleish told DailyMail.com. 'They've changed the virus, then tried to make out it was in a sequence years ago.'
  • The study also points to 'deliberate destruction, concealment or contamination of data' in Chinese labs and notes that 'scientists who wished to share their findings haven't been able to do so or have disappeared'
  • Until recently, most experts had staunchly denied the origins of the virus were anything other than a natural infection leaping from animals to humans
  • Earlier this week, Dr. Anthony Fauci defended US funding of the Wuhan Institute of Virology, saying the $600,000 grant was not approved for Gain of Function research
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