Category Archives: Longevity Medicine

When confronted with ads selling products that promote health and longevity, it's always important to remember that the wellness industrys primary goal is to make money.

Take ashwagandha, an herb whose use in Ayurvedic medicine dates back for millennia but is currently being marketed as a silver bullet for stress. Market research shows that the global market for this extract was valued at $864.3 million in 2021 and is projected to hit $2.5 billion by 2031. In 2021, spending on ashwagandha increased more than 225 percent compared to 2020.

But ashwagandhas role as a solution for all the stress in our lives is still not completely understood, despite its ever-increasing popularity.

Rashmi Mullur, an integrative endocrinologist at the University of California, Los Angeles, and the VA in Los Angeles, helps Inverse break down the facts and fables of the plant.

Ashwagandha (Withania somnifera) is an herb found in India, Africa, and the Middle East thats classified as an adaptogen, an all-encompassing term given to a plant or mushroom that purportedly helps lower stress in the body. It also contains a group of bioactive compounds known as withanolides, which are associated with antioxidant and anti-inflammatory effects. Ashwagandha extract is typically sold in the form of a supplement.

The term adaptogen, Mullur says, isnt used in medical literature. Rather, its a descriptor of any extract or food that mitigates stress in the body. While it doesnt have a formal medical definition, it can be a convenient layperson label. Still, Mullur says it doesnt shed any light on the biological mechanisms at work.

Mullur says that we believe ashwagandha helps relieve stress by binding to the same receptors as the stress hormone cortisol, though researchers are still not sure of all the mechanisms at play.

When studying various types of stress, researchers often designate cortisol as a proxy for stress levels. But Mullur says it's not a linear relationship. The hormone is indeed a key player in the bodys stress response, but its mere presence doesnt indicate stressful conditions. She says human cortisol levels exhibit a diurnal pattern, meaning they ebb and flow over the course of a day. For the average unstressed person, Mullur says, cortisol peaks in the morning, drops, peaks mid-afternoon, and drops again. On the other hand, those living with chronic stress lose that pattern of cortisol secretion and simply flatline, consistently producing the hormone all day.

Clinical trials for ashwagandha are also all over the place, Mullur says. They vary in size, dose, and disorders treated. There are no absolute levels. This means studies of it arent standardized, and results can be misleading. Since all these studies vary, even promising ones cant provide useful, applicable information for Mullur. I cant take that data and generalize it to an average person experiencing stress, she says.

Moreover, supplements arent regulated by the Food and Drug Administration, which means they may be full of adulterating factors and compounds you didnt plan on ingesting or may contain varying amounts of the actual extract.

Mullur cautions against buying supplements from self-proclaimed holistic vendors and influencers. When it comes to the supplement industry, I think it's all bad, she says. Rather, using ashwagandha under the supervision of an integrative or traditional provider may potentially help with stress, though again, the studies are not yet established.

She says ashwagandha and other similar herbal supplements are safest and most effective in small doses for short periods of time. In fact, Mullur says that there have been a few cases of jaundice-induced liver failure from taking too much ashwagandha for too long.

If youre interested in exploring this herb, Mullur advises that you stay away from social media and stick to integrative and traditional medical practitioners.

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Does Ashwagandha Help Relieve Stress? Here's What the ... - Inverse

Total mosquito activity at untreated and treated nets

A total of 3725 mosquitoes were assessed over 745 WHO cone tests using strains of KS, NG, BF and VK7 exposed to P2, OS, P3, IG2 and UT nets. Mosquitoes exposed to UT nets had a propensity to crawl along the net surface (Fig.2a). The mean total movement events observed during cone tests on UT nets was 4175 (SD 2154) in KS, 4671 (SD 1655) in NG, 3636 (SD 1619) in BF and 1975 (SD 1769) in VK7 (Fig.3). Susceptible strains typically had higher total activity than resistant strains. During exposure to treated nets, mosquito activity became dispersed throughout the cone and crawling on the net surface was reduced (Fig.2b). The mean total movement events (Fig.3) during ITN tests by strain was 4905 (SD 1120) in KS, 5326 (SD 904) in NG, 4022 (SD 1470) in BF, and 2737 (SD 1582) in VK7. Significant differences between the total movement comparing UT nets and ITNs by strain are indicated in Additional file 2: Table S1.

Composite outputs from individual ViCTA analyses demonstrate behavioural differences between untreated and insecticide-treated bednets. a composite summary image using the Kisumu strain of An. gambiae (KS) on an untreated net constructed by sampling video every 0.1s and merging darkest components of each frame, b Composite summary output of KS on net treated with Interceptor G2 (IG2), c composite image of Ngousso strain of An. coluzzii (NG) on untreated net, d Composite summary output of NG exposed to PermaNet 3

Total mosquito movement activity for all net treatments grouped by strain. Baseline behaviour on UT net is at the left side of each panel; 95% CI are indicated by error bars

The regional occupancy of mosquitoes in cones revealed variation in the responses of Anopheles spp. to different ITNs in terms of absolute (Fig.4a) and relative (Fig.4b) occupancy. During exposure to P2, mosquitoes were 1.482.11 times more active in the upper half of the cone (UHC) than in the UT net (Table 1, P2 vs UT upper region: KS OR 2.11; 95% CI 1.64, 2.7; P0.0010; NG OR 1.78; 95% CI 1.39, 2.27; P0.0010; BF OR 1.48; 95% CI 1.14, 1.92; P0.0010; VK7 OR 1.67; 95% CI 1.29, 2.15, P0.0010). Although activity was increased, there were no significant differences in the proportion of time spent in the upper and lower parts of the cone compared to the UT net (borderline result for KS Table 2 P2 vs UT: KS OR 0.51; 95% CI 0.25, 1.02; P=0.0582).

Regional activity in ViCTA analysis. a Mean absolute regional activity in LHC (bottom) vs UHC (top) regions for all strains and treatments. b Mean proportional regional activity. Baseline behaviour on UT net is shown in the top rows. 95% CI are indicated by error bars

In OS tests, all strains spent 1.552.67 times more time in the UHC than in the UT net, and the proportional LHC occupancy was 6675% lower (Table 1, OS vs UT upper region: KS OR 2.67; 95% CI 2.1, 3.41; P0.0010; NG OR 2.54; 95% CI 2.01, 3.2; P0.0010; BF OR 1.75; 95% CI 1.31, 2.34; P0.0010; VK7 OR 1.55; 95% CI 1.21, 1.98, P0.0010; Table 2 OS vs UT KS OR 0.34; 95% CI 0.25, 1.02; P=0.0582; NG OR 0.59; 95% CI 0.29, 1.18; P=0.1922; BF OR 0.56; 95% CI 0.26, 1.22; P=0.2117; VK7 OR 0.72; 95% CI 0.36, 1.42, P=0.5579); in P3 tests, mosquitoes spent 1.483.6 times more time in the UHC and were 65% less likely to move in the LHC (Table 1, P3 vs UT upper region: KS OR 2.79; 95% CI 2.16, 3.60; P0.0010; NG OR 3.38; 95% CI 2.67, 4.27; P0.0010; BF OR 1.48; 95% CI 1.13, 1.94; P=0.0015; VK7 OR 2.43; 95% CI 1.91, 3.08, P0.0010; Table 2, P3 vs UT: KS OR 0.35; 95% CI 0.18, 0.71; P0.0010; NG OR 0.23; 95% CI 0.11, 0.46; P0.0010; BF OR 0.55; 95% CI 0.25, 1.21; P=0.1930; VK7 OR 0.23; 95% CI 0.11, 0.45, P0.0010). Insecticide-susceptible and insecticide-resistant strains exhibited different behaviours during exposure to IG2: in the susceptible strains, between 50 and 74% less activity was observed in the LHC during IG2 tests compared to the UT net (Table 2 IG2 vs UT: KS OR 0.50; 95% CI 0.25, 0.99; P=0.0470; NG OR 0.26; 95% CI 0.13, 0.52; P0.0010), which was not observed in the two resistant strains (Table 2 IG2 vs UT: BF OR 1.74; 95% CI 0.8, 3.75; P=0.2372; VK7 OR 0.55; 95% CI 0.28, 1.08; P=0.1025).

Although mosquito resting could be indirectly inferred as the reciprocal of mosquito movement activity counts per frame (5n, where n is the number of moving mosquitoes detected per frame), a stricter measure was used. A resting frame was defined as a video frame where none of the five mosquitoes moved, compared to the previous frame. The total number of resting frames was calculated for each assay. Resting behaviour showed stark differences between susceptible and resistant strains (Fig.5) with VK7 mosquitoes found to be resting for a large proportion of the cone assays.

Mean mosquito resting period by strain and treatment. Seconds count based on number of measured frames where none of the five mosquitoes moved compared to the previous frame, out of a total of 1800 frames over the 3min of the cone test. Numbers adjacent to each bar indicate mean number of seconds resting

Over 92% of mosquitoes successfully blood-fed after tests with UT nets, with most mosquitoes feeding at 1h [KS 91.7% (176/192); NG 96% (192/200); BF 95.88% (93/97) and VK7 93.43% (199/213)]. After ITN tests, none of the mosquitoes exposed to P3, or the susceptible strains exposed to P2 and OS, survived long enough to feed. Of the few KS and NG mosquitoes that lived long enough to take a blood meal after IG2 tests, approximately half fed at 1h PE (PE) [KS 53.85% (7/13), NG 53.33% (16/30)]. In the resistant strains, compared to UT nets, BF mosquitoes were at least 90% less likely to feed at 1h PE when exposed to ITNs (Additional file 2: Table S2 BF: IG2 OR 0.10; 95% CI 0.00, 2.56; P=0.2325; OS OR 0.01; 95% CI 0.00, 0.25; P=0.0028; P2 OR 0.00; 95% CI 0.00, 0.02; P0.0010). P2 had the largest immediate inhibitory effect [blood-feeding success=9.8% (9/92)], followed by OS [48.57% (17/35)] and IG2 [61.86% (73/118)]. At 24h PE, approximately one third of BF mosquitoes (31.11%, 14/45) that were unfed at 1h after IG2 exposure, and all mosquitoes that were unfed at 1h after exposure to P2 and OS tests, blood-fed (P2 n=83; OS n=18).

ITN exposure did not have a significant effect on the blood-feeding behaviour of VK7 mosquitoes at either 1h or 24h PE. Most mosquitoes successfully fed at 1h [P2: 93.90% (77/82); OS: 87.50% (42/48); IG2 62.07% (18/29)].

The mean total weight of blood meals taken after tests with UT netting was 12.47g (SD=7.64). BMW per strain on UT netting was as follows: KS 12.26g (SD=7.89), NG 11.74g (SD=6.13), BF 10.48g (SD=6.42) and VK7 13.10g (SD=8.93). After ITN exposure, blood meal weights decreased (range 6.86g to 12.20g Fig.6 and Additional file 2: Table S3), significantly so in NG and VK7 strains (NG 2=5.47; df=1; P=0.0193; VK7 2=13.94; df=3; P=0.0030), where, compared to UT, at least 4.0g less blood was ingested (Additional file 2: Table S3 NG IG2=4.44g; 95% CI 8.23, 0.65; P=0.0225, VK7: OS=4.06g; 95% CI 6.84, 1.27; P=0.0045 and P2=4.19g; 95% CI 7.12, 1.36; P=0.0042). Activity in the LHC during tests was significantly associated with smaller blood meal weights in VK7 mosquitoes, and blood meals became 9.3 times smaller as activity increased (estimate=9.35g; 95% CI 17.76, 0.93; P=0.0298) regardless of treatment.

Mean haematin concentration of blood-fed mosquitoes which took a blood meal at 1h and 24h. Error bars at 95% CI are included only for cases where n>2. Numbers adjacent to each bar indicate sample size

In VK7 mosquitoes that could not feed at 1h PE but which recovered to feed at 24h PE, blood meal weights were 1.45 times smaller blood meals compared to those that fed at 1h PE (estimate=1.45g; 95% CI 2.93, 0.03; P=0.0551). The sizes of individual mosquitoes had a significant effect on blood meal weights in the NG, BF and VK7 strains (NG 2=5.94; df=1; P=0.0148; BF 2=17.55; df=1; P<0.0001; and VK7 2=11.18; df=1; P=0.0008) and as size increased, so did the size of the blood meal (NG estimate=5.49; 95% CI 0.91, 10.03; P=0.0201, BF estimate=8.28; 95% CI 4.09, 12.47; P0.0010 and VK7 estimate=4.19; 95% CI 1.73, 6.65; P0.0010).

After UT net tests, the 24-h mortality was 0.485.45% and the median longevity was 1214days (Additional file 2: Table S4, Additional file 2: S5). For all ITNs, 24-h mortality for KS and NG was 85.37100% and 3.4620.83% for resistant BF and VK7 (Additional file 2: Table S4). No mosquitoes survived P3 exposure and no susceptible mosquitoes survived P2. The median longevity for resistant strains after ITN tests was 914days (Additional file 2: Table S5). KS and NG mosquitoes were at least 47.55 times more likely to die when exposed to IG2 or OS compared to a UT net (Additional file 2: Table S4).

The longevity of KS mosquitoes was influenced by activity during tests and mosquitoes were 11.93 times more likely to die as the LHC activity increased regardless of treatment (including UT). In VK7 mosquitoes, observed longevity also was influenced by the activity in the cone during tests (treatment*activity interaction: 2=9.11; df=3; P=0.0278) and as the proportion of activity in the LHC increased, the likelihood of dying increased for UT and P2 (Additional file 2: Fig. S3a). In IG2 tests, mosquitoes were more likely to die when greater activity was recorded in the UHC, and, compared with UT, mosquitoes were significantly more likely to die when the proportion of activity close to the net was less than 50% (Additional file 2: Fig. S3b).

Mosquitoes that did not blood-feed at 1h PE were at least 17 times more likely to die at 24h PE (Additional file 2: Table S4 KS 2=0.00; df=1; P=0.9987, NG 2=25.80; df=1; P<0.0001, BF 2=19.40; df=1; P<0.0001 and VK7 2=24.54; df=1; P<0.0001). The amount of blood ingested had a slight impact on longevity: BF and VK7 mosquitoes were 7% and 2% less likely to die as the BMW increased, respectively (Additional file 2: Table S5 BF HR 0.93; 95% CI 0.90, 0.93; P<0.0001 and VK7 HR 0.98; 95% CI 0.97, 0.99; P=0.0012). The effect of treatment on longevity varied with wing length for all strains, for example, smaller mosquitoes lived longer PE to UT netting (all strains) and were more likely to die if they were exposed to IG2 for all the strains except BF (Additional file 2: Fig. S2 a, b).

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Video augmentation of the WHO cone assay to quantify mosquito ... - Parasites & Vectors

THURSDAY, Nov. 16, 2023 (HealthDay News) -- Shrinkage of one of the brain's key memory centers appears to herald thinking declines, a new study finds.

The region in question is the hippocampus, a two-sided structure located roughly above each ear and embedded deep within the brain's temporal lobe. It's long been known to play a crucial role in the storage and transference of short- and long-term memory.

The new research was published Nov. 15 in the journal Neurology. It focused on brain scan data collected from 128 people averaging 72 years of age.

A team led by Dr. Bernard Hanseeuw, of Harvard Medical School in Boston, used the scans to track changes in brain levels of amyloid plaques or tau tangles. Both are linked to the onset of Alzheimer's disease.

The team also used the scans, which were taken annually, to chart any changes in the size of an individual's hippocampus over the course of seven years.

People who showed the most significant shrinkage in their hippocampus were also most likely to display thinking declines over the study period, Hanseeuw's group reported.

This seemed to occur independently of changes in levels of either amyloid or tau, they noted. They estimated that hippocampus shrinkage might account for 10% of thinking declines.

These results suggest that neurodegenerative diseases other than Alzheimers are contributing to this decline, and measuring the hippocampus volume may help us evaluate these causes that are currently difficult to measure, Hanseeuw said in a news release from the American Academy of Neurology.

This could help us better predict who would respond to these new drugs as well as peoples trajectories of cognitive decline," he reasoned.

More information:

Find out more about the brain and the hippocampus at Johns Hopkins Medicine.

Excerpt from:
One Part of Your Brain Could Point to Mind's Decline - HealthDay

As most people want to live longer and with good health, Sheba Medical Center at Tel Hashomer will open in September on its campus the worlds first public hospital longevity center to provide advanced, research-based medicine for maintaining and improving peoples physiological and mental functions.

The Sheba Longevity Center is being planned to promote longer, healthier lives, built on multidisciplinary fields of healthcare and technology.

It will first focus on a pilot study and treatment for some 2,000 patients aged 40 and over in the fields of cognition, sleep, frailty and menopause before branching out to other fields. This effort will pioneer a new type of patient care.

Longevity is an international issue that requires global cooperation, said Prof. Tzipi Strauss, the founder and creator of the center. Today, Sheba has brought together players from across the globe to share knowledge, collaborate and raise awareness of the possibilities this field brings. Through this new annual conference and our clinic, we hope to continue our mission of democratizing the field of longevity, making it accessible to all.

The Sheba Longevity Conference, held this week, united global longevity stakeholders to discuss advances and breakthroughs in medicine for healthier, longer lives. The event featured discussions on how multidisciplinary fields of healthcare, including genomic testing, dieting, stem cell aging and artificial intelligence (AI), could be applied to longevity practice. Attendees included leading researchers from the US, Europe, Africa, the Gulf region and East Asia alongside senior Israeli government officials and health tech leaders.

The Sheba center will build on the existing strong foundations of the hospital, and benefit from its multidisciplinary experts, said internal medicine Prof. Evelyne Bischof at the Shanghai University of Medicine and Health Sciences who will be the director and manage day-to-day operations. Built on a base of clinical evidence, using AI and the latest cutting-edge health tech, the Sheba Longevity Center will combine the best elements of modern-day medical care. Based in Sheba, the city of health, our partnerships across the world will help us achieve a truly global impact.

The Longevity Center will collaborate closely with Shebas innovation arm, ARC (Accelerate, Redesign, Collaborate) to promote innovation in the field and incubate start-ups that will contribute to longer, healthier lives. The center will also establish an educational hub working closely with academic institutes, longevity associations and regulatory bodies to build the next generation of longevity scientists.

In 10 years time, due to changing demographics and rising costs, we will not be able to provide the same level of care that we are providing today; we need transformation to continue providing quality care, added Prof. Yitshak Kreiss, the director-general of Sheba, Israels largest hospital. The approach being pioneered by Prof. Strauss will see a shift from treating diseases to promoting health, building towards longer, healthier aging within a center that will provide world-leading, clinically backed, integrative medicine.

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Sheba to launch worlds first dedicated longevity clinic - The Jerusalem Post

Aging happens. While the rate may vary from species to species and even person to person, targeting aging may extend the average life expectancy more than prevention or treatment of diseases, according to Northeastern experts.

Researchers and pharmaceutical companies continue to search for treatments for chronic diseases such as cancer, heart disease and diabetes. But while medicine has helped reduce mortality, it doesnt look at the larger picture of aging.

Aging plays a crucial role in the onset of many diseases that affect the bodys organs.

Preventative measures to treat aging at the molecular level may provide more benefits than reactive therapeutic approaches that target a single disease or organwhich do not extend lifespans, says Ramkumar Hariharan, a senior scientist at the Institute for Experimental AI at Northeastern University.

Hariharan focuses on human longevity, advanced statistical data analyses, data visualization, and machine learning. He also has experience in building AI applications, with research directed at using large and genomic datasets in biomedicine.

I think aging is the emperor of all maladies, Hariharan says.

Even if scientists cure cancer, the most it would add to the average life expectancy would be two to three years, Hariharan says. Why? Because, like in the movies, if cancer doesnt get you, something else willsuch as a car crash, heart disease or Alzheimers.

The reason is that aging is the single biggest risk factor for developing any one of these diseases, Hariharan says. If you can slow down aging, you get a life-expectancy increase of 30 to 35 years.

So, what exactly is aging other than another day closer to your next birthday? Hariharan defines it as things falling apart at the molecular level, at the cellular level, and the organismal level.

The chances of getting diseases increase as one ages and other functionalities decrease, such as the bodys immune systemmeaning the older you are, the more likely you are to get infectious diseases.

A scientific hypothesis states, Aging is one of the biggest risk factors for developing any of this plethora of diseases, Hariharan says. By slowing down aging or by halting aging, or in the ideal case reversing aging, you must be able to prevent or stave off the initiation of these diseases.

Hariharan is interested in extending the health or cell span, which refers to the years of life that one spends not taking pills to stave off disease.

There may be a finite age in humans from 120 or 130 years old. After all, Jeanne Calment lived to be 122 years old and is considered to have lived the longest life. But what will it take to get there? Unfortunately, the answer is still unclear.

Thats where artificial intelligence can help.

With the help of Pramod Nagare, a senior data engineer working at Northeasterns Institute for Experiential AIs Solutions Hub, Hariharan explained that they are creating a toolbox for biologists studying longevity to input their data and receive meaningful insight.

Called the Artificial Intelligence Longevity Toolbox, or AI-LOT for short, Nagare explained that the AI-assisted program will make it easier for biologists to understand their data.

A prototype of the toolbox will be available to the public in about six months and the team is hoping to build out AI-LOT within three years.

Biologists dont have to look into the technical aspect of whats going on behind the scenes, Nagare says. However, at the same time, theyre getting a feel about knowing their data in much more detail through exploratory data analysis.

There are three main tools Nagare and Hariharan are developing. The first uses data in predictive analytics, allowing researchers to see what will happen next in a pattern of data. The second is a hub of research on longevity medicine, allowing users to summarize key studies and ask questions on what medicines are the most effective.

The third use is to develop new drugs. For example, a researcher can narrow down a list of the best molecule candidates for a potential drug from a list of millions with the help of AI. The tool will also be able to suggest molecules that will work.

Instead of completing a sentence, it can complete the structure of a molecule, Hariharan says.

Measuring aging, such as using a thermometer for fever or a sphygmomanometer for blood pressure, is still being developed for biological age. The goal is to use data at the molecular level.

Beth Treffeisen is a Northeastern Global News reporter. Email her at b.treffeisen@northeastern.edu. Follow her on Twitter @beth_treffeisen.

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Can AI Help Scientists Slow the Aging Process? - Northeastern University

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A new publication in the May issue of Nature Aging by researchers from Integrated Biosciences, a biotechnology company combining synthetic biology and machine learning to target aging, demonstrates the power of artificial intelligence (AI) to discover novel senolytic compounds, a class of small molecules under intense study for their ability to suppress age-related processes such as fibrosis, inflammation and cancer.

The paper, "Discovering small-molecule senolytics with deep neural networks," authored in collaboration with researchers from the Massachusetts Institute of Technology (MIT) and the Broad Institute of MIT and Harvard, describes the AI-guided screening of more than 800,000 compounds to reveal three drug candidates with comparable efficacy and superior medicinal chemistry properties than those of senolytics currently under investigation.

"This research result is a significant milestone for both longevity research and the application of artificial intelligence to drug discovery," said Felix Wong, Ph.D., co-founder of Integrated Biosciences and first author of the publication. "These data demonstrate that we can explore chemical space in silico and emerge with multiple candidate anti-aging compounds that are more likely to succeed in the clinic, compared to even the most promising examples of their kind being studied today."

Senolytics are compounds that selectively induce apoptosis, or programmed cell death, in senescent cells that are no longer dividing. A hallmark of aging, senescent cells have been implicated in a broad spectrum of age-related diseases and conditions including cancer, diabetes, cardiovascular disease, and Alzheimer's disease. Despite promising clinical results, most senolytic compounds identified to date have been hampered by poor bioavailability and adverse side effects. Integrated Biosciences was founded in 2022 to overcome these obstacles, target other neglected hallmarks of aging, and advance anti-aging drug development more generally using artificial intelligence, synthetic biology and other next-generation tools.

"One of the most promising routes to treat age-related diseases is to identify therapeutic interventions that selectively remove these cells from the body similarly to how antibiotics kill bacteria without harming host cells. The compounds we discovered display high selectivity, as well as the favorable medicinal chemistry properties needed to yield a successful drug," said Satotaka Omori, Ph.D., Head of Aging Biology at Integrated Biosciences and joint first author of the publication. "We believe that the compounds discovered using our platform will have improved prospects in clinical trials and will eventually help restore health to aging individuals."

In their new study, Integrated Biosciences researchers trained deep neural networks on experimentally generated data to predict the senolytic activity of any molecule. Using this AI model, they discovered three highly selective and potent senolytic compounds from a chemical space of over 800,000 molecules. All three displayed chemical properties suggestive of high oral bioavailability and were found to have favorable toxicity profiles in hemolysis and genotoxicity tests.

Structural and biochemical analyses indicate that all three compounds bind Bcl-2, a protein that regulates apoptosis and is also a chemotherapy target. Experiments testing one of the compounds in 80-week-old mice, roughly corresponding to 80-year-old humans, found that it cleared senescent cells and reduced expression of senescence-associated genes in the kidneys.

"This work illustrates how AI can be used to bring medicine a step closer to therapies that address aging, one of the fundamental challenges in biology," said James J. Collins, Ph.D., Termeer Professor of Medical Engineering and Science at MIT and founding chair of the Integrated Biosciences Scientific Advisory Board. Dr. Collins, who is senior author on the Nature Aging paper, led the team that discovered the first antibiotic identified by machine learning in 2020.

"Integrated Biosciences is building on the basic research that my academic lab has done for the last decade or so, showing that we can target cellular stress responses using systems and synthetic biology. This experimental tour de force and the stellar platform that produced it make this work stand out in the field of drug discovery and will drive substantial progress in longevity research."

More information: Felix Wong et al, Discovering small-molecule senolytics with deep neural networks, Nature Aging (2023). DOI: 10.1038/s43587-023-00415-z

Journal information: Nature Aging

Provided by Ten Bridge Communications

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Artificial intelligence identifies anti-aging drug candidates targeting 'zombie' cells - Phys.org