On October 3, 2016, the Nobel Prize in Physiology or Medicine was awarded to Yoshinori Ohsumi for “discoveries of the mechanisms for autophagy.” Just a few weeks earlier, at an acceptance speech for the 2016 Paul Janssen Award, Yoshinori Ohsumi stated that although he performs research in a simple organism—baker’s yeast—he always hoped his research would have an impact upon human health.
(ur abstract för https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5240711/)
«Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort the structures of around 100,000 unique proteins have been determined, but this represents a small fraction of the billions of known protein sequences. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’—has been an important open research problem for more than 50 years. Despite recent progress existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14), demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.»
For the production of medical knowledge as a public good
Initiated by BUKO Pharma-Kampagne and medico international (Germany), Outras Palavras (Brazil), People’s Health Movement and Society for International Development
The world has become a patient. The disease is called Covid-19 and it has shown us all the unavoidable interconnectedness of the planet. A remedy is only possible globally or not at all - this is one of the most important lessons of the pandemic that no one can escape. In the interest of humanity, the world should work together in solidarity, and within the framework of global political institutions to find a vaccine and medicines that can be produced and distributed on a need basis.
Diza ligger vaken på nätterna bredvid sin fyra månader gamla son. I huvudet snurrar allt hon har läst på nätet. Ska hon tillåta att han vaccineras mot sjukdomar som mässling och polio? När träffade hon senast någon med mässling? Trots att vi lever i en pandemi tycks antivaccin-rörelsen koppla ett allt hårdare grepp om de unga föräldrarna. Journalisterna Anna Nordbeck och Malin Olofsson har infiltrerat antivaccinationsrörelsen i mer än 1,5 år. De har förvånats över all värme och gemenskap som präglar rörelsen. Men ju djupare in i rörelsen de lyckats komma, desto tydligare har det också blivit att det finns metoder och mål som oroliga föräldrar inte ska få reda på.
teksten er hentet fra Knut Ruyter (red.): Forskningsetikk: Beskyttelse av enkeltpersoner og samfunn (2003)
Til alle tider – og særlig etter den vitenskapelige revolusjonen på 1600-tallet – har det blant forskere eksistert en eller annen form for regulering av egen atferd som et uttrykk for forskningens eget normsystem. I tillegg har forskere o …
THE RACE BETWEEN KNOWLEDGE AND DATA IN MEDICINE
Researchers, doctors and biologists benefit from the massive amount of available information as health data becomes digitized. But it also becomes harder and harder for human brains to uncover the complexity and extract insights. Data is generated at a much faster pace than knowledge. This is THE scientific challenge. We need to create the tools to help human collective intelligence extract knowledge from this influx of data. Parts of these technologies already exist, parts need to be invented. OWKIN creates AI technologies to advance knowledge and discover the medicine of tomorrow.
E. Ernest Boateng. International Journal Of Multidisciplinary Studies And Innovative Research, 7 (7):
428-439(November 2021)Keywords: HIV, Antiretroviral therapy, Atwima Nwabiagya.
M. Arhin, C. Dovia, C. Todoko, und D. Agbeko. International Journal Of Multidisciplinary Studies And Innovative Research, (März 2021)Keywords: HIV, Deadliest Diseases, Hohoe Municipality, HIV infections.