BIO-TECH VENTURES

First, medical AI should be modular. A single model trying to “know everything” is risky and often inaccurate. Instead, a system of specialized agents - one focused on blood tests, another on microbiome results, another on genetic data - can work together like a team of doctors. Each agent brings its expertise, and their combined effort creates a broader, more accurate picture of a patient’s health.

Second, reasoning in medicine must be structured and careful. Good clinical practice always involves planning, testing, reviewing, and correcting mistakes. AI can follow a similar cycle: make an initial plan, execute it, review the outcome, and adjust. When combined with a memory of past results, this allows the system to spot long-term trends, such as slow changes in kidney function or early warning signs of diabetes.

Third, trust depends on transparency. Doctors and patients must understand why the AI reached a particular conclusion. That means clear explanations, references to reliable medical sources, and visible reasoning steps. AI should not act as a mysterious “black box,” but rather as a partner whose advice can be checked and verified. Until regulations fully catch up, human oversight - where a physician reviews AI-generated insights - remains essential.

Another crucial issue is the problem of a "ghost in a shell" - AI hallucinations - when a system “invents” information that sounds convincing but is totally false. In medicine, this can be dangerous or even life-threatening. To reduce this risk, medical AI should always be required to ground its answers in verified medical databases, include source citations, and mark uncertain information clearly. Human-in-the-loop review and strong validation processes are the best safeguards against such errors.

AI assistants in healthcare should not aim to replace doctors, but to amplify their abilities and empower patients with clearer information. By being modular, careful in reasoning, transparent in explanations, and cautious about hallucinations, AI can become a trustworthy partner in modern medicine - helping people make better decisions about their health while keeping safety at the center.

Multiple earlier experiments starting with parabiosis (connecting the blood systems of old and young mice) showed that older mice display signs of rejuvenation, like improved muscle and brain function. However, later works rejected whole "blood transfers" concept and instead found that simply diluting old plasma with a neutral solution (saline and albumin) produced improvements in brain, liver, and muscle in mice. This leads to a conclusion that there is something in the old blood, that is damaging organs. The less its concentration is, the better the body it overall. However, the mechanism was not clear for long time.

Scientists at Korea University have uncovered a striking new mechanism where aging signals can spread through the bloodstream. A specific form of the protein HMGB1 (when in its reduced ReHMGB1 state) acts as a "messenger of aging". When this form is released by aging or stressed cells, it travels through blood and can trigger cellular aging (or senescence) in distant tissues. Researchers demonstrated this effect in human cell cultures and in mice: giving mice ReHMGB1 caused increased markers of aging (like p16 and p21), inflammation, and weakened muscle function. Moreover, mice treated with antibodies that block HMGB1 showed improved tissue regeneration and physical performance, suggesting that reducing the harmful form of HMGB1 might reverse age-related declines. 

In order to reduce harmful aging signals and support better body function, potential treatments may include some king of anti-HMGB1 antibodies. The danger is that the protein is contained inside our cells and works in DNA packaging processes. Hence, these could be lab-designed molecules that bind to and neutralize ReHMGB1 in the bloodstream, but should not be getting inside the cells. Of course, one should not omit his or her lifestyle-based approaches. While direct human-use therapies aren’t yet available, supportive measures like anti-inflammatory diets, exercise, and good sleep may help lower overall inflammation and possibly reduce harmful HMGB1 release indirectly. Last, but not least, development of some kind of "Redox Modulators" could help. Since the oxidized form of HMGB1 (OxHMGB1) doesn’t trigger aging effects, researchers could explore drugs that shift the balance toward OxHMGB1, making harmful aging signals less likely without messing with anti-bodies attacking it.

The original article was published under the title: "Aging Spreads Through The Body Like An Infection, And This Protein Could Be To Blame". It is misleading. Spread of ReHMGB1 happens only in the bloodstream of a body, it does not go outside of it. The Korean research focused on bloodborne spread of aging signals via HMGB1, not through external or casual contact. Therefore, even though close human relationships often involve shared environments and routines, processes like hugging, physical proximity, or intimacy do not transfer aging proteins. So, being close to an older person does not make a younger person age faster and visa versa. Aging "spreads" only through bloodstream or inside the body - not across people.

Bio-Tech Ventures researchers are curious about another aspect of the aging problem. What is the reason causing cells to emit ReHMGB1? Is it embedded in our DNA? Can we adjust it without messing with genes? When humanity can overcome the initial triggering factor, it can extend its lifespan. In a meanwhile, tests revealing the true biological age in combination with healthy nutrition, peptide therapies and appropriate lifestyle are the only ways to last longer and better!

Scientists used ultra-deep sequencing (very detailed DNA analysis) on over 300 blood samples from healthy individuals and found that methylation changes happen either randomly or in coordinated clusters. With this data, a deep learning model was trained and could predict a person’s age. Moreover, they showed that these methylation patterns are stable over time - even in samples collected 10 years apart from the same individuals. Age prediction was not affected by sex, smoking status, or BMI. Even as few as 50 DNA molecules were enough for accurate age estimation, suggesting that each human cell "remembers" time.

It is hard to overvalue the true biological Aging measurement tools. This work could significantly improve “epigenetic clocks” that estimate true age of a patient, which may differ from chronological age and correlate more with health, disease risk, and lifespan. Of course, it is also important in forensics. The ability to detect age from a tiny DNA sample (just 50 molecules!) has potential applications in criminal investigations and identification of bodies. Last, but not least, is medical research. Understanding how the body "records time" at the molecular level could help scientists track disease progression, treatment effects, and aging processes with high precision. It is especially important for anti-aging treatments.

Bio-Tech Ventures team believes that with further validation, the suggested method could become a key tool in the growing field of personalized and preventive medicine and individual AI-advisory.  

In the context of modern generative AI (like language models or image generators), the “ghost” refers to the illusion of understanding or consciousness - when the AI seems to “know” or “think” but is really just generating output based on statistical patterns in training data. However, an issue of much deeped magnitude emerges when the AI creates or invents facts, not conclusions, based on data. These false facts fabricated with confidence are sometimes called "hallucinations" and they are expecially dangerous in medical advisory field.

Modern neural networks are pattern recognizers and generators, trained on enormous data sets. They don’t have an imbedded truth-checking mechanism and a structured model of the real world (yet too complex). They also have a serious memory issue of where each fact came from. When prompted, AI doesn’t search a database - it predicts the most likely next word or output based on patterns in its training. That’s why it may create names, dates, references, or numbers that sound plausible but are fictional. This is different from inference or conclusion (which would be reasoned from true data). It’s improvised fact-creation or, in metaphorical terms, the "ghost" from the machine is speaking, but there’s no grounding in reality.

In healthcare, false lab values or misrepresented symptoms could lead to wrong treatment. In broader sense science, invented citations or findings could damage research integrity. It erodes trust and introduces risk, especially when AI is used in fields where accuracy is critical. Bio-Tech Ventures experts are aware of these limitations. This is why we do our best in preventing the "hallucinations" from happening. AI systems need structural safeguards imbedded at their design stage. The following principles should apply:

• Data Provenance (Source Tracking) - the AI should cite or link to actual sources for every factual claim, like a footnote or document trail. This link should be "live" and verifiable. 

• Fact vs. Opinion Tagging - AI should always label its output as “retrieved fact” or “calculated conclusion” or “generated guess” - allowing a human user to judge its reliability.

• Last, but very important, Memory Structuring. Usage of modular memory systems and personal memory for user-specific data in combination with Global Knowledge for verified facts and Quarantine Zone for unverified or speculative content should lover the risk of false advisory.

Besides of these hardcoded ethical limits may and should block the AI from inventing facts in sensitive domains (e.g., medicine, law) and force it to defer to external sources. It is the burden of the designer of an AI-system to make sure the rules are obeyed. Otherwise, the enormouns volume of information makes it impossible (time- and competence- wise) to check and verify each single advice of neural network. Hence, any flaw in the initial build of its internal logic may give a birth to a ghost, which may harm people.

Many myths contain strikingly similar themes that could reflect real encounters with advanced beings. For instance, Sumerian texts speak of the Anunnaki, who genetically engineered humans ("to bear the workload of the gods"). Same story goes with the Biblical Accounts: the Nephilim (hybrid offspring of "sons of God" and human women) and humans created from clay. Egyptian myths are about roughly the same. One of the possible Interpretation of this conincidents in believes of people spread over the planet is that ancient humans, lacking scientific vocabulary, described advanced technology in mythological terms (e.g., "gods," "magic," "divine fire" etc.). Consequently, in their primitive eyes genetic engineering could have been remembered as "sculpting humans from clay." From a genetic engineering stand point analysis of ancient myths reveal quite some interesting facts:

• Gene editing tech & Synthetic Biology: We now have the ability to edit genomes, clone animals, and even create hybrid species. If humans were engineered, the technology required (gene splicing, mitochondrial manipulation) is not beyond feasibility for a civilization just a few thousand years ahead of us.

• Sudden Brain Expansion: Homo sapiens experienced a rapid increase in brain size and cognitive ability around 200,000–70,000 years ago, with no clear evolutionary precursor. This aligns with the idea of targeted genetic upgrades.

• Missing Genetic Link: The divergence between humans and Neanderthals/Denisovans is still not fully explained. Some geneticists argue that humans may be a hybrid species, possibly engineered from multiple hominid lineages.

There are of course the counterarguments too:

• There is no direct DNA Evidence. If there were aliens who modified us, we’d expect unexplainable genetic sequences (e.g., synthetic genes or non-terrestrial markers). So far, no such "alien signature" has been found. Unless, of course, they have altered the entire planetary fauna. Well... this is what the Old testament actually literally says... 

• Natural evolution explanations by mainstream science attributes human intelligence to climate change, social competition, and dietary shifts, not external intervention. However, "mainstream" opinion could be manipulated and usually keeps itself very dogmatic. For instance, the Church believed in Geo-centric model of Universe for centuries. 

So, genetic engineering of humans by an advanced species is technologically plausible, but lacking direct proof. If this hypothesis is taken as a basis, then these "creation" tales encode real events then we may have been genetically modified from pre-existing hominids (like Homo erectus) by an advanced civilization. Some of these myths explicitly state that selected beings (like Adam and Eve, or rullers of Sumeria) lived longer. What does it imply? Are there any other species on Earthg who naturally last more than humans?

Apparently, sharks, turtles, jellyfish, and lobsters exhibit negligible senescence - they don’t weaken with age as humans do. Some jellyfish are even biologically "immortal". Bowhead whales live over 200 years with minimal cancer risk. Key difference with us is that these species have superior DNA repair mechanisms, telomere maintenance, and resistance to cellular damage. Humans, in contrast, seem to be "programmed" to degrade. May be due to its intelligence?

What about the tales of about other civilizations that lived longer? Besides of Angels. Reading European myths provides us with Elves and Dwarves who express both longevity and certain physical traits reflecting it. For instance, elves (in Norse/Germanic myths) are described as long-lived or almost immortal creatures, with large ears and pointed features. Dwarves (same origin) are also long-lived, with large noses and ears. Suprisingly or not, but in human biology ears and noses grow throughout life because cartilage continues expanding - possibly this is a side effect of an aging mechanism. The longer we live, the larger our ears and noses are. So, of elves and dwarves were "real" (mythological reflection of a contact with an intelligent race), then their exaggerated facial features might indicate slowed or even absent aging programs, while human cartilage growth could be a byproduct of a deliberately limited lifespan.

Digging deep into understanding of aging mechanism may reveal its secrets and programming code. With uprising of AI this task becomes more and more feasible. Perhaps one day the humankind will discover the coding patterns of its creators and some "longevity pill" will join our daily dosage of nutrition.

Today, many people wait until they get ill to visit a doctor. Due to high cost of medical services and low number of general practicioners these visits could be delayed for weeks if even for months if one looks for a narrow expert. But what if an AI could monitor your health continuously, noticing early warning signs before problems appear? What if a person can get a better understanding of his age and consequetive issues? Modern smart watchet and fit-braselets already gather a lot of data. Adding actual physical diagnostic results to it may lead to a better estimage of real biological age and its tracking.

Most of our negative body development are built over time due to exposure to stress, environmental factors, but also nutrition practices and fitness habbits. Advising on food, exercise, sleep based on real-time feedback from our body (via wearable sensors and test results) would be very beneficial. And these should be personalized recommendations - not generic “eat healthy” tips, but suggestions tailored to an individual, his or her goals, and personal biology.

This burden may and should be brought up on AI shoulders. It would act like a digital health coach, helping you make small daily changes that add up to big long-term benefits - from disease prevention to improved energy and mood. Unfortunatelly, modern AI systems are powerful, but still limited. 

First of all, most AI models (even advanced ChatGPT 4.o) is not design to “remember” your history. Every time you chat, it starts fresh and a conversation has limited length. This is fine for general advice, but not for personal health and daily monitoring.

Second, it is about understanding the complexity of the issue. Health data is usually messy and very individual. One person’s perfect diet might harm another. AI models still struggle with context and long-term reasoning.

Last, but not least - privacy and data protection. Your data must be stored securely and not mixed with others, but the AI must still learn from global patterns to get smarter. So, the data should be fed to it while being anonymous. 

Economically, private AI-assistant is becoming more and more feasible. Cloud computing and subscription-based services (like health apps) allow AI to serve millions at relatively low cost. Devices like smartphones and wearables are already common, making connection easy. As AI becomes more efficient, it could cost as little as a gym membership, but with far more value. Of course, in the beginning only the developped nations will be covered with digital advice. However, over time it would be possible to bring advice to every remote location. 

Still, before this happens there are technical issues that are to be addressed and solved. One of them is the model of organizing AI's memory. In order to provide a personalized advice to every patient, the following should be implemented:

• Personal Layer: Stores your data, previous advice given, test results, life style preferences etc. This is private, secure, and segregated from ID data (name, date of birth etc.).

• Global Knowledge Layer: Holds general medical facts, studies, and data from others (anonymized). AI uses this to stay up-to-date and to provide with an advice based on the personal layered data mapped into the "common" knowledge base.

So the solution is in Separation + Integration. These layers stay separate, but the AI can combine them smartly, offering advice based on you + the best global knowledge. Think of it like a doctor with a personal file on you, but also access to the world’s best medical research.

Bio-Tech Ventures trully believes that a personal AI health assistant can improve quality of life, prevent disease, and reduce healthcare costs. It won’t replace doctors, but it can empower people to take charge of their health every day. With the right memory structure and smart design, such AI can be both personal and powerful — just like the future of medicine should be.

Thanks to the modern development of generative AI, it’s now possible to imagine a digital "assistant" that goes beyond giving simple answers with short memory of its prompts. These systems can already summarize scientific papers, answer complex biology questions, and even suggest hypotheses. So why not ask them to analyze lab results too?

The AI-assistant would combine three technologies:

• Natural Language Processing (NLP) - to understand the researcher’s instructions and questions, without him being a coder/programmer.

• Structured Data Analysis - to interpret lab data formats like .csv or .xls files with test results.

• Domain Knowledge in Bioinformatics - to apply correct statistical tests, reference values, and clinical thresholds.

One could think of it as a well-trained junior scientist who never gets tired and can learn more every day. However, current open source models and those available, like ChatGPT or DeepSeek lack very important feature. An AI can already handle many routine tasks: comparing results, plotting graphs, detecting outliers, and explaining what a certain marker usually means. But complex cases still require human judgment, experience, and sometimes intuition.

Still, the future looks promising. With better training data, fine-tuned models, and integration into lab software, AI can become a powerful tool — especially for scientists who design tests but don’t have time to analyze every result themselves. To bridge this gap, advanced AI systems are starting to rely on modular memory + reasoning architectures. 

Instead of forgetting everything after each prompt, modular memory systems (like vector stores, semantic graphs, long-term memory buffers) allow the AI to recall prior test results, to understand project-level context (e.g. the goal of the current experiment) and to track evolving biological hypotheses.

This leads to responses that align with the full history of the experiment — much like a human collaborator would do. In addition to that a future advanced AI-assistants will be trained to use external softwasre and coding tools like R-scripts for statistical analysis, open sourced bioinformatics libraries and graphing or modeling software. Thereby, instead of trying to replace everything, the AI will act like a smart operator that knows when and how to use tools (just like a bioinformatician does).

Bio-Tech Ventures is a firm believer that our future is with AI and it should become a powerful tool expanding inspiration and capabilities of our scientists. There is much more achievable together!

 They discovered this using a computer model of cell control systems (a “digital twin”) and then tested it in the lab and in mice. In these experiments, cancer cells with the three genes switched off slowed their growth and started showing markers of normal cell function. This approach is called differentiation therapy – instead of killing cancer cells, you make them mature into harmless, normal-like cells. This idea already works in one blood cancer (acute promyelocytic leukemia), but hasn’t yet been successful in most other cancers. The KAIST study is pre-clinical: only tested on lab cells and mice, not yet in humans. A big challenge: delivering treatment to shut down three genes at once inside a human tumor without harming healthy tissues.

How it compares to current immunotherapy cure:

Checkpoint inhibitors – drugs that take the “brakes” off immune cells so they can attack cancer (used in melanoma, lung cancer, and more). Side effects happen when the immune system also attacks healthy tissues (colitis, lung inflammation, thyroid problems), but doctors can often manage these with steroids.

CAR-T therapy – immune cells are taken from a patient, genetically modified in a lab to better target cancer, grown in large numbers, and put back into the patient. Very effective in some blood cancers, but can cause serious short-term immune reactions (cytokine release syndrome, high fever, low blood pressure, confusion) and, rarely, secondary cancers from the genetic changes.

TIL therapy – tumor-fighting immune cells are extracted directly from the tumor, expanded in the lab, and returned to the patient. Approved for advanced melanoma. Side effects mostly come from the strong chemotherapy and immune-boosting drugs used before infusion.

Last, but the most promissing one: cancer vaccines from the patient’s own tumor – lab-made immune stimulators based on the patient’s tumor cells or tumor mutations. Usually well-tolerated but results can be slower and more variable. Examples: sipuleucel-T (prostate cancer), DCVax-L (brain cancer).

For now, this therapy gives almost twice as long survival median rate compared to the other methods. Perhaps, in the future, the KAIST approach could be combined with personalized immune therapy – for example, making tumors “less cancerous” first, then letting the immune system (with or without therapy) finish the job – but that’s not reality yet.

Religious fasting traditions, found in many major faiths such as Christianity, Islam, Judaism, Buddhism, and Hinduism, often encourage believers to abstain from food or reduce food intake for specific periods. For example, during Ramadan, Muslims fast from dawn to sunset, while in Christianity, Lent is observed with sacrifices that often include food. These practices are rooted in spiritual purposes but share a common underlying theme: moderation. By intentionally limiting food intake, individuals are believed to gain greater control over their desires and elevate their spiritual well-being. They also tend to start feeling better.

Recent scientific studies suggest that this practice of food restriction may not only benefit the spirit but also the body. One area of research that has gained attention is calorie restriction (CR), which involves reducing calorie intake without causing malnutrition. Scientific evidence supports the idea that CR can enhance longevity and health by slowing down the aging process. For instance, CR has been shown to improve metabolic health, increase stress resistance, and reduce the risk of age-related diseases in animals. Even short-term mild hunger or reduced calorie intake has been linked to the activation of cellular processes that promote repair, reduce inflammation, and extend lifespan.

Recent publications in the Nature Journal provides some scientific explanation of these processes. When CR is practiced, it causes various changes in the body, particularly in how the body produces and circulates different substances called metabolites. Metabolites are molecules that are involved in the body’s chemical processes. However, scientists weren’t sure which specific metabolites are responsible for the health benefits of CR.

To investigate this, the researchers used a technique called "metabolomics" to study changes in metabolites during CR and then tested their effects. They found that one specific metabolite, called lithocholic acid (LCA), can mimic the positive effects of CR in mice. These effects include activating a protein called AMP-activated protein kinase (AMPK), which is involved in energy regulation. LCA also helped improve muscle regeneration, strength, and running ability in mice, making them physically stronger and more youthful.

Additionally, LCA showed similar benefits in two other species (a small worm and a type of fruit fly), which do not naturally produce LCA. This suggests that LCA can have an effect on these animals when given externally. Importantly, when the AMPK protein was removed in these animals, the benefits of LCA disappeared, meaning AMPK is essential for LCA to work.

In conclusion, this study identifies LCA as a metabolite that can produce anti-aging effects similar to calorie restriction. These effects depend on the activation of AMPK, which is important for energy regulation in the body. This finding suggests that LCA could be a potential tool for promoting health and longevity in a way that mimics the benefits of calorie restriction. 

Scientific findings presented above lead us to modern bio-hacking opportunities, that require millions in investments, lengthy FDA approvals and years of further research, testing and trials. But essentially, there is a cheaper and faster solution - to follow some recommendations embedded in various religion traditions, that had no scientific explanation before.

Scientific exploration of food restriction and its positive impact on aging and longevity provides a modern explanation for the practices of fasting found in many religious traditions. Both reflect the principle that moderation in food intake can trigger biological processes that promote health, extend life, and enhance vitality. Whether for spiritual enlightenment or health benefits, fasting represents an intersection between ancient wisdom and modern science, offering insights into how human beings can optimize their health and longevity. One may even draw a conclusion that Gods, or whoever gave us our believes in the past, actually knew much more about how our bodies operate.

Indeed some of these living creatures have evolved unique biological mechanisms that allow them to maintain their health and functioning well into old age, which has led to assumptions that studying their longevity and aging processes could hold the key to extending human lifespan and improving overall health.

Sharks, for example, have been found to exhibit very low incidences of cancer, despite their long lifespans and exposure to environmental toxins and stressors. Researchers believe this may be due to the efficiency of their DNA repair mechanisms, which help to prevent the accumulation of mutations that can lead to cancer in humans. Crocodiles also display impressive longevity, with some species living well over a century without experiencing the same age-related declines in muscle mass, cognitive function, or immune system function that humans do.

Similarly, turtles are known for their longevity, often living for several decades or even centuries without showing signs of aging. Some researchers have attributed this to the unique structure of their cells, which allows them to maintain their telomere length, the protective caps at the ends of chromosomes that shorten with age in most animals. By preserving their telomeres, turtles are able to stave off the cellular damage and dysfunction that typically accompany aging in other species.

In contrast, humans and other animals that are more "young" in terms of evolution, tend to show more rapid declines in health and functioning as they age. This can be attributed to a number of factors, including genetic predispositions, environmental influences, and lifestyle choices. The aging process in humans is complex and multifaceted, involving a combination of genetic, biological, and environmental factors that contribute to the development of age-related diseases and decline.

Despite these differences, researchers are increasingly focusing on studying the aging mechanisms of long-lived animals in the hopes of uncovering new insights into how to promote healthy aging in humans. By understanding the ways in which sharks, crocodiles, turtles, and other long-lived species are able to resist the effects of aging and disease, scientists may be able to develop novel interventions and therapies that could extend human lifespan and improve overall health and well-being.

Ultimately, the potential for studying the aging mechanisms of long-lived animals to revolutionize human health and longevity is promising. By unraveling the mysteries of how these animals are able to maintain their health and functioning well into old age, researchers may be able to identify new strategies for preventing age-related diseases, enhancing cellular repair mechanisms, and promoting overall well-being in humans. While there is still much to learn, the insights gained from studying these remarkable animals offer hope for a future in which humans may one day live longer, healthier lives.

Melittin is a peptide found in bee venom that has been studied for its potential anti-cancer properties. In recent years, there has been growing interest in the use of this chemical as a therapeutic agent for various types of cancer. This peptide exerts its anti-cancer effects through a variety of mechanisms. One of the key ways in which it inhibits cancer cell growth is by inducing apoptosis, or programmed cell death. Studies have shown that melittin can activate the intrinsic apoptotic pathway in cancer cells, leading to cell death. Additionally, peptide has been shown to disrupt the cell membrane of cancer cells, leading to cell lysis (dissolution of cells in human body).

Melittin also has anti-inflammatory properties, which can help to inhibit the growth and spread of cancer cells. Inflammation is a key driver of cancer progression, and by reducing inflammation, the peptide may help to slow the growth of tumors.

Furthermore, the peptide has been shown to inhibit angiogenesis, the process by which tumors form new blood vessels to supply themselves with nutrients. By blocking angiogenesis, melittin can help to starve tumors of the nutrients they need to grow and spread.

Several studies have demonstrated the anti-cancer effects of melittin in various types of decease. For example, a study published in the journal Oncotarget found that the peptide inhibited the growth of breast cancer cells both in vitro and in vivo. The researchers reported that melittin induced apoptosis in the cancer cells and inhibited tumor growth in mouse models.

Another study published in the journal PLOS One found that this peptide inhibited the growth of prostate cancer cells by inducing apoptosis and disrupting the cell membrane. The researchers concluded that melittin had potential as a novel therapeutic agent for prostate cancer.

In addition to breast and prostate cancer, the peptide has also shown promise in the treatment of other types of cancer, including lung cancer, pancreatic cancer, and melanoma. A study published in the journal Toxins in 2018 found that melittin inhibited the growth of melanoma cells by inducing apoptosis and inhibiting angiogenesis.

While the R&D on melittin as a cancer treatment is still in the early stages, there is growing interest in the potential clinical applications of this compound. One of the advantages of this peptide as a cancer treatment is that it is a naturally occurring compound that is well-tolerated by the body. This makes it an attractive candidate for use in cancer therapy.

In recent years, researchers have been exploring different ways to deliver melittin to cancer cells, including encapsulating the peptide in nanoparticles or liposomes. These delivery methods can help to target the peptide directly to the cancer cells, while minimizing off-target effects on healthy cells.

Bio-Tech Ventures perceives peptides as the future of personalized medicine. We tailor our research efforts at studying the mechanisms of how these protein chains are affecting cells in order to extend both the human longevity and its quality of life.

The measurement of biologic age is seen as a key factor in determining overall efficiency of procedures and drugs aimed at promoting health and longevity, and could revolutionize the field of aging research. By accurately determining a person's biologic age, researchers hope to develop targeted treatments and interventions that can slow down the aging process and promote overall wellness and quality of life.

There is no officially approved and scientifically proven quantitative tool for measuring of age. Thus the partnership between Bio-tech Ventures and the German researchers is poised to be a game-changer in the field of anti-aging research. With access to cutting-edge technology and expertise, the team is set to develop innovative testing methods that could pave the way for the development of new longevity drugs and bio-hacking techniques.

This collaboration marks a significant milestone in the quest for increased human lifespan and overall well-being. The research lab team and Bio-tech Ventures are committed to pushing the boundaries of scientific knowledge and working towards a future where age is no longer a barrier to a healthy and vibrant life.

Bio-Tech Ventures inherited Potsdam as an R&D center for laboratory studies. In addition to this town, the city of Hennigsdorf in the Oberhavel district has also established itself as an important biotechnology center, especially in such areas as diagnostics, medical technology, pharmaceuticals, drug development and related industry services. Recently Hennigsdorf became the second destination for delegations of Japanese biotechnology companies. Today guests visited the Hennigsdorf Innovation Forum, where they met the young Life Science OHV cluster and got a presentation about local companies including WeDiag and Bio-Tech Ventures.

Recent mice studies conducted by researchers from Medical School of the National University of Singapore on IL-11, a pro-inflammatory cytokine of the IL-6 family, demonstrated a negative effect on age-associated diseases and lifespan. As animal age, protein concentration rise across cell types and tissues to to modulate cellular, tissue- and overall-level ageing pathologies. Elimination of IL-11 protects against metabolic decline, multi-morbidity and frailty in old age. Administration of anti-bodies to 75-week-old mice for 25 weeks improves metabolism and muscle function, and reduces ageing biomarkers and frailty across sexes. In lifespan studies, genetic deletion of IL-11 extended their lives by 24.9% on average.

Humans also produce Il-11. However, described approach requires extensive studies and clinical trials before it may be applied on people. There might be side effects association with the anti-bodies that are targeting the aging protein. Moreover, the mechanism that cause the body to produce the IL-11 and other similar symptom causing proteins is not identified and requires deepest epigenetic layer of looking for the actual bio-programming if one perceives a human body as a sophisticated biological machine.

As long as the programming is not identified, biohacking is the best approach to manage longevity. Bio-Tech Ventures studies target other methodologies in order to find the cause of the problem. It is important to develop a measurement tool that reflects the actual biologic age based on scientific facts and test results. With new AI advances this task becomes feasible.

There were several topics highlighted, among them:

• the growing role of prompt engineering in generative AI (creation of neural-network answers based on the right questioning).

• machine learning for early detection of Cancer with immune responses and CT 3D imaging.

In addition to speech given by Mrs.Guergana Savova (Harvard Medical School) our scientists have shared the experience of using generative AI for chat scripting and automated advisory and communication between patients and hospitals with minimal medical personnel involvement.

Together with Mrs. Tina Hernandez-Boussard (Stanford Medicine, Boussard Lab) the advantages of AI in analysis 3D imaging was discussed in connection with identification of tumor tissues (digital-biopsy) and their earliest stage of growth.

Targeting of a novel intracellular immune checkpoint for the treatment of solid tumors is in line with Bio-Tech Ventures studies on early diagnostics and identification of immune response using AI for NGS and aimed at development of individualized therapy. Another match was professor’s evidence on virus-specific T-cells to be delivered allogeneically (e.g. from another patient) via MHC-typing and patient human leukocyte antigen (HLA)-matching to provide pragmatic treatment in a large-scale therapeutic setting. This could be extrapolated also with xeno-transplant techniques currently studied by Bio-Tech Ventures in relation with diabetes, but for cancer treatments, since some species (like sharks) do not have oncology at all.