I tend to ask chatGPT for a summary of the transcript of videos so that I don't have to spend the time watching them. I have done this for the ALS Scientific Advisory Council from about a month ago which follows (the critique is of chatGPT - my critique is that they don't talk about mitochondria, the closest they come to epigenetics is DNA methylation): International Alliance of ALS/MND Associations Scientific Advisory Council Webinar – Transcript Summary Opening & Housekeeping Jessica Mabe (Programs Coordinator, International Alliance) welcomed attendees and introduced the webinar, noting caption availability (via Zoom chat or QR code) and thanking sponsor Mitsubishi Tanabe Pharma . The Scientific Advisory Council Chair & Moderator: Dr Nicholas Cole (Head of Research, MND Association, UK) Panelists: Dr Kuldip Dave – Vice President of Research, ALS Association (USA) Dr Nadia Sethi – Co‑chair, NE...
I think it is useful to try to identify: a) The most heavily energy using neurons b) The balance in those cells between OxPhos (which produces Reactive Oxygen Species - ROS) and Glycolysis I will be using various LLMs to search for information relating to this and will be spending time checking the responses for hallucinations, but I may not at the time of you reading this page finished validating everything. I will also be concentrating on validating the analysis for dopaminergic and motor neurons because those are the neurons which cause PD and ALS/MND. In principle the rank is not really valid. Although this table is produced using a ranking that is not going to be reliable, it is still useful. What I am trying to get from this is to identify the cells which would be vulnerable to rapid deterioration through ROS. The first step is those with a high energy usage. This, however, I would expect to vary from time to time and any actual accurate calculation for one human being ...