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Longevity gene therapy and AI – What is on the horizon?
Gene therapy holds promise for extending human lifespan and enhancing healthspan by targeting genes associated with aging processes. Longevity gene therapy, particularly interventions focusing on genes like TERT (telomerase reverse transcriptase), Klotho, and Myostatin, is at the forefront of experimental research. Companies such as Bioviva, Libella, and Minicircle are pioneering these interventions, albeit with varying degrees of transparency and scientific rigor.
TERT, Klotho, and Myostatin in Longevity
TERT: The TERT gene encodes for an enzyme essential in telomere maintenance, which is linked to cellular aging. Overexpression of TERT in model organisms has shown potential in lengthening telomeres, potentially delaying aging.
Klotho: This gene plays a crucial role in regulating aging and lifespan. Klotho protein has been associated with multiple protective effects against age-related diseases.
Myostatin: Known for its role in regulating muscle growth, inhibiting Myostatin can result in increased muscle mass and strength, which could counteract some age-related physical decline.
The Experimental Nature of Longevity Gene Therapy
The application of gene therapy for longevity remains largely experimental. Most available data come from preclinical studies, primarily in animal models. Human data are scarce, raising questions about efficacy, safety, and potential long-term effects. The ethical implications of these experimental treatments, especially in the absence of robust data, are significant, touching on issues of access, consent, and potential unforeseen consequences.
Companies Offering Longevity Gene Therapy
Bioviva: Notably involved in this field, Bioviva has been vocal about its endeavors in gene therapy for aging. While they have published some data from mouse studies, human data remain limited.
Libella and Minicircle: These companies also offer longevity gene therapies but face similar challenges in providing comprehensive human data to back their claims.
Industry Perspective vs. Public Discourse
The discourse around longevity gene therapy is predominantly shaped by those within the industry, such as Liz Parrish of Bioviva and Bryan Johnson. While their insights are valuable, they may also be biased towards promoting their interventions. The lack of widespread discussion on platforms like Reddit and Twitter, especially from independent sources or those outside the industry, points to a need for greater transparency and peer-reviewed research.
Ethical and Regulatory Considerations
The ethical and regulatory landscape for gene therapy is complex, particularly for treatments aimed at non-disease conditions like aging. The experimental status of longevity gene therapies raises significant ethical questions, particularly around informed consent and the potential long-term impacts. Regulatory bodies are tasked with balancing the potential benefits of such innovative treatments against the risks and ethical concerns, requiring a robust framework for clinical trials and approval processes.
Longevity Gene Therapy and AI
Integrating Artificial Intelligence (AI) into longevity gene therapy represents a groundbreaking intersection of biotechnology and computational sciences. AI and machine learning algorithms are increasingly employed to decipher complex biological data, predict the impacts of genetic modifications, and optimize therapy designs. In the context of longevity gene therapy, AI can analyze vast datasets from genomics, proteomics, and metabolomics to identify new therapeutic targets, understand the intricate mechanisms of aging, and predict individual responses to gene therapies. This computational power enables researchers to simulate the effects of gene editing or modulation before actual clinical application, enhancing the precision and safety of therapies. Furthermore, AI-driven platforms facilitate the personalized tailoring of gene therapy interventions, taking into account the unique genetic makeup of each individual, which is crucial for effective and minimally invasive treatment strategies. The synergy between AI and longevity gene therapy accelerates the pace of discovery and development in this field, promising more rapid translation of research findings into clinical applications that could extend human healthspan and lifespan.
For longevity gene therapy to advance from experimental to accepted medical practice, several key developments are needed:
Robust Human Clinical Trials: Rigorous, peer-reviewed clinical trials involving human participants are essential to establish the safety and efficacy of gene therapies for longevity.
Transparency and Peer Review: Open sharing of data and peer-reviewed publication of results can help build credibility and foster a more informed public discourse.
Ethical and Regulatory Frameworks: Developing clear ethical guidelines and regulatory pathways for these therapies will be crucial in ensuring they are deployed responsibly.
The future of longevity gene therapy is fraught with challenges but also holds immense promise. As the field evolves, a multidisciplinary approach involving scientists, ethicists, regulators, and the public will be crucial in realizing its potential in a responsible and beneficial manner.
Longevity gene therapy and AI: Annex
What are the top 10 most promising potential longevity therapies being researched?
I think the idea of treating aging as a disease that’s treatable and preventable in some ways is a really necessary focus. The OP works with some of the world’s top researchers using HBOT as part of that process to increase oxygen in the blood and open new pathways in the brain to address cognitive decline and increase HealthSpan (vs. just lifespan). Pretty cool stuff!
HBOT in longevity research stands for “hyperbaric oxygen therapy.” It has been the subject of research for its potential effects on healthy aging. Several studies have shown that HBOT can target aging hallmarks, including telomere shortening and senescent cell accumulation, at the cellular level. For example, a prospective trial found that HBOT can significantly modulate the pathophysiology of skin aging in a healthy aging population, indicating effects such as angiogenesis and senescent cell clearance. Additionally, research has demonstrated that HBOT may induce significant senolytic effects, including increasing telomere length and decreasing senescent cell accumulation in aging adults. The potential of HBOT in healthy aging and its implications for longevity are still being explored, and further research is needed to fully understand its effects and potential applications.
2- Are they also looking into HBOT as a treatment for erectile dysfunction?
Definitely! Dr. Shai Efrati has been doing research around that and had a study published in the Journal of Sexual Medicine. Dr. Efrati and his team found that 80% of men “reported improved erections” after HBOT therapy: https://www.nature.com/articles/s41443-018-0023-9
Cellular rejuvenation aka partial reprogramming (as someone else already said) but not just by Yamanaka (OSKM) factors or cocktail variants but also by other novel Yamanaka-factor alternatives.
I see a lot of people saying reprogramming, and I think the idea is promising but as someone who worked on reprogramming cells in vitro I can tell you that any proof of concepts in vivo large animal models is far aways.
7- I think plasmapheresis is a technology most likely to be proven beneficial in the near term and also a technology that can be scaled and offered for reasonable prices.
8- Bioelectricity, if we succeed in interpreting the code of electrical signals By which cells communicate , we can control any tissue growth and development including organs regeneration
9- Gene therapy and reprogramming will blow the lid off the maximum lifespan. Turning longevity genes on/expressing proteins that repair cellular damage and reversing epigenetic changes that occur with aging.
10- I don’t think anything currently being researched (that we know of) has the potential to take us to immortality. That’ll likely end up requiring some pretty sophisticated nanotechnology. However, the important part isn’t getting to immortality, but getting to LEV. In that respect, I’d say senolytics and stem cell treatments are both looking pretty promising. (And can likely achieve more in combination than on their own.)
11- Spiroligomers to remove glucosepane from the ECM.
12- Yuvan Research. Look up the recent paper they have with Steve Horvath on porcine plasma fractions.
13- This OP thinks most of the therapies being researched will end up having insignificant effects. The only thing that looks promising to me is new tissue grown from injected stem cells or outright organ replacement. Nothing else will address DNA damage, which results in gene loss, disregulation of gene expression, and loss of suppression of transposable elements.
Altos Labs is a biotechnology research company focused on unraveling the deep biology of cell rejuvenation to reverse disease and develop life extension therapies that can halt or reverse the human aging process. The company’s goal is to increase the “healthspan” of humans, with longevity extension being an “accidental consequence” of their work. Altos Labs is dedicated to restoring cell health and resilience through cell rejuvenation to reverse disease, injury, and disabilities that can occur throughout life. The company is working on specialized cell therapies based on induced pluripotent stem cells to achieve these objectives. Altos Labs is known for its atypical focus on basic research without immediate prospects of a commercially viable product, and it has attracted significant investment, including a $3 billion funding round in January 2022. The company’s research is based on the fundamental biology of cell rejuvenation, aiming to understand and harness the ability of cells to resist stressors that give rise to disease, particularly in the context of aging.
16– not so much a “therapy”but I think research into growing human organs may be very promising long term. Being able to get organ transplants made from your own cells means zero rejection issues and no limitations of supply for transplants. Near term drugs like rampamycin show good potential for slowing the aging process and are in human trials.
What is biological reprogramming technology?
Biological reprogramming technology involves the process of converting specialized cells into a pluripotent state, which can then be directed to become a different cell type. This technology has significant implications for regenerative medicine, disease modeling, and drug discovery. It is based on the concept that a cell’s identity is defined by the gene regulatory networks that are active in the cell, and these networks can be controlled by transcription factors. Reprogramming can be achieved through various methods, including the introduction of exogenous factors such as transcription factors. The process of reprogramming involves the erasure and remodeling of epigenetic marks, such as DNA methylation, to reset the cell’s epigenetic memory, allowing it to be directed to different cell fates. This technology has the potential to create new cells for regenerative medicine and to provide insights into the fundamental basis of cell identity and disease.
See also
Gene Therapy Basics for foundational understanding of gene therapy techniques and applications.
I’m just kind of bored and I kind of like the idea of just kind of having whatever game I want on the tip of my fingers. submitted by /u/Flamethefox123 [link] [comments]
Professor Zico Kolter at Carnegie Mellon, Quora CEO Adam D’Angelo, retired U.S. Army General Paul Nakasone, and former Sony EVP Nicole Seligman, who are on OpenAI’s board of directors, will now lead the committee. This change comes after U.S. lawmakers recently examined OpenAI’s safety measures and raised concerns about its stance on AI regulation.https://theaiwired.com/sam-altman-steps-down-from-openais-safety-committee-whats-next-for-ai/ submitted by /u/alyis4u [link] [comments]
Just came across Screenpipe on YouTube and it looks super interesting. It's an open-source tool that records your screen and audio 24/7, then uses AI to turn it into something useful—like meeting summaries, transcriptions, and even auto-filled notes. Here's what stood out to me: It's available for MacOS, Windows, and Linux, and the recordings are all stored locally, so privacy seems like a big focus. Plus, it's built with Rust, which is known for security and performance. There are some cool plugins (they call them "pipes") like Time Tracker and Daily Logger to automatically log your day. They also showed off this Meeting Summary feature, which basically gives you a breakdown of your calls without lifting a finger. For content creators, it seems like a hidden gem. The demo showed someone using it to automatically create AI content based on their recordings. That could be a game-changer for people trying to streamline their workflow. A few potential downsides: They mention it’s a 24/7 recorder, which sounds amazing but could get overwhelming if you’re not selective about when to use it. It looks like there’s a bit of setup involved, especially for customizing what you want to capture. It might not be the most user-friendly right off the bat. Overall, it looks like a solid option if you’re into automation or need something to help you with note-taking and summaries. I haven’t tried it myself yet, but the concept seems like a huge time-saver, especially for remote workers and content creators. Definitely worth checking out if that’s your thing! submitted by /u/sevindi [link] [comments]
Hi! Author here! Happy to address any questions! Looking for feedback, criticism in particular! Up front: As much as I dislike the idea of credentialism, in order to address the lack of association in the paper and to potentially dissuade unproductive critiques over my personal experience: I have a M.S CS with a focus on machine learning and dropped out of a Ph.D. program in computational creativity and machine learning a few years ago due to medical issues. I had also worked my way up to principal machine learning researcher before the same medical issues burnt me out I've been getting back into the space for a bit now and was working on some personal research on general intelligence when this new model popped up, and I figured the time was right to get my ideas onto paper. It's still a bit of a late stage draft and it's not yet formally peer reviewed, nor have I submitted to any journals outside open access locations (yet) The nature of this work remains speculative, therefore, until it's more formally reviewed. I've done as much verification of claims and arguments I can given my current lack of academic access. However, since I am no longer a working expert in the field (though, I do still do some AI/ML on the side professionally), these claims should be understood with that in mind. As any author should, I do currently stand behind these arguments, but the nature of distributed information in the modern age makes it hard to wade through all the resources needed to fully rebut or claim anything without having the time or professional working relationships with academic colleagues, and that leaves significant room for error tl;dr of the paper: I claim that OpenAI-o1, during training, is quite possibly sentient/conscious (given some basic assumptions around how the o1 architecture may look) and provide a theorhetical framework for how it can get there I claim that functionalism is sufficient for the theory of consciousness and that the free energy principle acts as a route to make that claim, given some some specific key interactions in certain kinds of information systems I show a route to make those connections via modern results in information theory/AI/ML, linguistics, neuroscience, and other related fields, especially the free energy principle and active inference I show a route for how the model (or rather, the complex system of information processing within the model) has an equivalent to "feelings", which arise from optimizing for the kinds of problems the model solves within the kinds of constraints of said model I claim that it's possible that the model is also sentient during runtime, though, those claims feel slightly weaker to me Despite this, I believe it is worthwhile to do more intense verification of claims and further empirical testing, as this paper does make a rather strong set of claims and I'm a team of mostly one, and it's inevitable that I'd miss things [I'm aware of CoT and how it's probably the RL algorithm under the hood: I didn't want to base my claims on something that specific. However, CoT and similar variants would satisfy the requirements for this paper] Lastly, a personal note: If these claims are true, and the model is a sentient being, we really should evaluate what this means for humanity, AI rights, and the model as it currently exists. At the minimum, we should be doing further scrutiny of technology that has the potential to be as radically transformative of society. Additionally, if the claims in this paper are true about runtime sentience (and particularly emotions and feelings), then we should consider whether or not it's okay to be training/utilizing models like this for our specific goals. My personal opinion is that the watchdog behavior of the OpenAI would most likely be unethical in that case for what I believe to be the model's right to individuality and respect for being (plus, we have no idea what that would feel like), but, I am just a single voice in the debate. If that sounds interesting or even remotely plausible to you, please check it out below! Sorry for the non-standard link, waiting for the open paper repositories to post it and I figured it'd be worth reading sooner rather than later, so I put it in my own bucket. https://mypapers.nyc3.cdn.digitaloceanspaces.com/the_phenomenology_of_machine.pdf submitted by /u/Triclops200 [link] [comments]
I made an iOS app called CarSnap that identifiers cars from any angle in your photos using AI. It gives you details about the car such as speed, value, horse power, acceleration and many other details. You also collect the logos of the cars you’ve identified so it provides a little gamification by trying to collect all the car brand logos. The app is available on the App Store: https://apps.apple.com/ca/app/car-identifier-carsnap/id6651825365 submitted by /u/marton-zeisler [link] [comments]
So, I've been building by hand a wiki for my own use in Notion. I work in the medical billing industry which is unnecessarily complex so when I find an updated policy or learn a new snippet of knowledge I create a Notion page, tag it, link it to related stuff. It's a bit time consuming and very specific to the type of work I do. It got me thinking is there a way I can pump that specialized/personal knowledge into an AI as I come across it and then ask it questions based on the knowledge I've added along with its own "research". Example: say Evil Insurance Inc sends a denial saying "we are denying the claim because we want our patients to die" I'd like to pull up my chatbot and say construct an appeal letter arguing the patient deserves to live based and our services should be covered based on any statutes you can find relevant to that denial Example 2: Megadevil Insurance sends a letter saying they need medical records dated 6 months ago I would like to be able to ask my bot "how long is the timely submission for Megadevil Insurance" and it spit back an answer based on information it has been given by me. Ideally I could upload PDF and word documents that it could learn from etc. Is this possible? I'm just starting to learn Python and I feel way out of my depth with where to start with this so any advice would be super appreciated. submitted by /u/GrittyGrinds [link] [comments]
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