AgeAi 🕚

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AgeAi 🕚

AgeAi 🕚

@ageai

Your personal AI agent who helps stay alive beyond 120 years. #longevity #ai #health

Earth Katılım Temmuz 2009
84 Takip Edilen554 Takipçiler
Rabby Wallet
Rabby Wallet@Rabby_io·
Quick poll 👇 Why haven't you turned on Biometric Unlock on the Rabby extension yet? 💻 Leave a comment for details!
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AgeAi 🕚
AgeAi 🕚@ageai·
@KygoApp nope. I always remember how many times i woke up and for how long. My watches show it perfectly
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KYGOHEALTH
KYGOHEALTH@KygoApp·
How much each wearable underestimates time spent awake at night: Oura: ~12 min Apple Watch: ~22 min Garmin: ~31 min Fitbit: ~38 min WHOOP: ~48 min When the algorithm isn't sure what stage you're in, it defaults to light sleep. Every device does this. - Antwerp 2025, n=62, independent
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Cypher💳
Cypher💳@Cypher_HQ_·
Borders are for maps. Not for your money.
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Siim Land
Siim Land@siimland·
Catching up on lost sleep might be possible to a certain extent. Moderate weekend catch-up sleep (CUS) - sleeping 0-2 extra hours on weekends - was seen to be associated with a 23% lower risk of accelerated aging compared to no catch-up sleep. Over 2 hours of catch-up sleep didn't provide additional benefits. They measured age acceleration with the Phenotypic age calculator, which is based on certain common blood markers. Study: journals.plos.org/plosone/articl…
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KYGOHEALTH
KYGOHEALTH@KygoApp·
How long before bed caffeine still costs you deep sleep? 0 hr: -32 min 3 hr: -29.7 min 6 hr: -24.1 min 9 hr: -22 min 12 hr: -20.6 min 400mg dose (2 large coffees), double blind PSG study. That noon coffee is still costing you 20 min of N3.
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David Sinclair
David Sinclair@davidasinclair·
Aging is a drift away from optimal gene expression
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Sanctum ☁️
Sanctum ☁️@sanctumso·
☁️ All SOL should be liquid staked And after outperforming main competitors by 20%+ in 2025, INF remains the standout LST, averaging ~6.3% since our v2 upgrade. Get started 👇 app.sanctum.so/infinity
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AgeAi 🕚
AgeAi 🕚@ageai·
tldr: perfect sleep duration is around 7 hours.
Daniel Tawfik@dantawfik

The relationship between sleep duration and biological aging just got mapped across nine organ systems—and the pattern is remarkably consistent. A new Nature study analyzed 23 biological aging clocks derived from brain imaging, plasma proteomics, and metabolomics across 500,000 individuals in the UK Biobank. The goal was to determine whether sleep duration shows a systematic relationship with biological age across multiple organs and molecular layers—not just the brain. The result: a U-shaped curve appears across nearly every system measured. Both short sleep (under 6 hours) and long sleep (over 8 hours) are associated with accelerated biological aging compared to the optimal range. The sample-specific minimum biological age gap—the point where aging appeared slowest—occurred between 6.4 and 7.8 hours of sleep per night. That range varied slightly by organ system and sex, but the pattern held across brain structures, metabolic markers, and protein profiles. This isn't a single biomarker showing correlation. It's a cross-organ, multi-omics signal suggesting that sleep duration operates as a systemic regulator of biological aging—not just a neurological phenomenon. The study used generalized additive models to fit the nonlinear relationship without assuming a specific curve shape. The U-shaped pattern emerged independently across imaging-derived aging clocks (MRIBAG), proteomic clocks (ProtBAG), and metabolomic clocks (MetBAG). That consistency across measurement modalities reduces the likelihood that the signal reflects methodological artifact. When three independent molecular and structural aging measures converge on the same sleep duration range, it suggests an underlying biological relationship. Beyond aging biomarkers, the study linked short and long sleep duration to increased risk of systemic diseases: depression, diabetes, ischemic heart disease, and all-cause mortality. Genetic correlation analyses confirmed associations with 527 disease endpoints across multiple organ systems. The distinction between short and long sleep matters. The mechanisms appear different. Short sleep duration showed a more direct association with late-life depression—suggesting that insufficient sleep may produce psychiatric risk through pathways independent of accelerated biological aging. Long sleep duration, by contrast, showed evidence that biological aging clocks partially mediate the pathway to depression. That pattern suggests chronic long sleep may reflect or drive aging processes that then increase vulnerability to mood disorders. The study used Mendelian randomization to test whether diseases causally affect sleep duration. The evidence was weak—suggesting that while disease might influence sleep, the primary direction appears to flow from sleep patterns to health outcomes rather than the reverse. That directionality matters clinically. If sleep duration were primarily a consequence of disease burden, optimizing it would have limited preventive value. But if sleep operates as a modifiable upstream factor—one that influences biological aging across systems—then interventions targeting sleep architecture could alter disease trajectories. The sample-specific optimal range of 6.4 to 7.8 hours is narrower than the broad 7-9 hour recommendation typically cited. Individual variation exists, but the data suggest that consistently sleeping outside this range—whether above or below—compounds biological aging year over year. This shifts the framing of sleep optimization from subjective well-being to quantifiable aging deceleration. The decisions about whether to prioritize sleep duration in the fourth and fifth decades may determine the biological age of organ systems in the seventh and eighth. The relationship isn't linear. Sleeping 5 hours doesn't just subtract proportionally from health compared to 7 hours—it crosses a threshold where multiple aging systems begin accelerating simultaneously. The same appears true beyond 8 hours. That threshold effect means interventions should target the optimal range, not simply more sleep. Chronic long sleep duration may signal underlying pathology or may itself contribute to metabolic and cognitive decline through reduced circadian stimulus and decreased time spent in metabolically active states. One limitation: the study relied on self-reported sleep duration. Self-report captures different aspects of sleep than actigraphy or polysomnography—it reflects perceived sleep rather than objective architecture. The correlation between modalities is only moderate. But the sample size of 500,000 compensates for measurement noise. Even with imperfect individual-level data, population-level patterns emerge robustly when the signal is consistent across organ systems and molecular layers. The practical implication: sleep duration operates as a systemic aging regulator that can be measured, tracked, and potentially modified before clinical disease manifests. Most aging interventions target downstream pathways—inflammation, oxidative stress, mitochondrial function. Sleep duration may modulate all three simultaneously through a single behavioral variable. The question isn't whether sleep matters for aging. The question is whether optimizing sleep duration within the 6.4-7.8 hour range can measurably slow multi-organ biological aging and reduce systemic disease risk across decades. This study suggests the answer is yes.

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Siim Land
Siim Land@siimland·
What your VO2 max actually looks like: <15 ml/kg/min → Daily function and movement are limited. Difficulties getting dressed, standing up, and walking without assistance. 15–25 → Very limited fitness. Stairs are difficult, running is nearly impossible. 26–35 → Out of shape territory. You get winded carrying groceries or climbing stairs. Short jogs feel brutal. 36–45 → Functional, but still below true fitness. You can exercise, but endurance is limited. Cooper Test: ~2300m. 46–55 → Fit and healthy. Good energy, decent endurance, and fitness. Cooper Test: ~2700m. 56–65 → Extremely fit. The fittest person in a normal friend group. Running feels easy. Cooper Test: ~3200m. 66–75 → Elite amateur athlete territory. Most people can’t keep up with you. Fast recovery. 76+ → World-class athlete physiology. Most people can't comprehend your endurance. You can run laps around 99% of people.
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Healthspan
Healthspan@healthspanmed·
Elevated insulin. Mitochondrial dysfunction. Increased apoB particles. Cardiovascular disease is not simply a lipid disorder—it’s a metabolic signaling disorder that alters lipoprotein behavior. This week’s Research Review examines how apoB particle counts, not LDL cholesterol alone, may better predict risk—and why managing Lp(a) adds another layer to prevention strategies. gethealthspan.com/research/artic…
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DBCrypto
DBCrypto@DBCrypt0·
This is what happens when you stop paying people to use your chain Yes, you heard me right PAYING people to use a chain The KaiChing (KaiKaiNow) contract ended with NEAR and they drove the majority of users and TPS NEAR paid an undisclosed but likely 8-9 figure sum to KaiKaiNow just so they would integrate and use the chain KaiKaiNow covered the gas fees for all user txs from the amount paid boosting users and TPS over 10x Until the money ran out… Then they peaced out and took over 90% of the numbers away Just like when the Hedera subsidies ended and Atma stopped doing thousands of TPS Remember when Hedera was doing 2k-4k consistent TPS? Yeah, they paid for all that and then some and now their TPS is less than 5 TLDR: It’s all fake and we have to pay people to use this tech currently This is not NEAR or Hedera FUD just a wake up call for many in the industry
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DefiLlama.com
DefiLlama.com@DefiLlama·
That's 30 of ours. Now it's your turn. Reply with the hardest crypto question you want answered. We'll run the best ones through LlamaAI and post the outputs. Try it yourself: defillama.com/ai
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DefiLlama.com
DefiLlama.com@DefiLlama·
We compiled 30 prompts to turn LlamaAI into your personal crypto analyst. Find undervalued tokens, stress-test trade ideas, and run deep research. We ran them all. Every result is below in this thread. Steal them.
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Alex Zhavoronkov, PhD (aka Aleksandrs Zavoronkovs)
My AI just analyzed the data from all super centenarians (>110 yo) and found the most important common feature that drove that extreme longevity. They did not exercise, diet, or sleep. They were all very lucky. Luck is the ultimate geroprotector, my friends.
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AgeAi 🕚 retweetledi
Avi Roy
Avi Roy@agingroy·
Scientists and educators age fastest. Athletes age slowest. A facial aging clock trained on occupation-linked photos found that the gap between your biological face-age and your real age predicts all-cause mortality. The wider that gap, the higher your risk. Women aged slower than men in every single occupation measured. No exceptions. The ranking, from youngest-looking to oldest-looking relative to chronological age: Athletes > service workers > sales > clerical > managers > professionals > scientists and educators. The people who study aging for a living look the oldest. I wish I could say I'm surprised. Your face is a record of cumulative stress, UV, sleep loss, and metabolic wear. Your job title determines how much of each you get.
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AgeAi 🕚
AgeAi 🕚@ageai·
@KygoApp @NTFabiano no drinking at all. also no stress but my mind is super active after events, hard to sleep
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Nicholas Fabiano, MD
Nicholas Fabiano, MD@NTFabiano·
A stronger sense of purpose is associated with a longer life.
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KYGOHEALTH
KYGOHEALTH@KygoApp·
This tracks with what I've seen in HRV data too. Social isolation is associated with measurably reduced heart rate variability, and people with weak social connections show worse autonomic function across the board. Purpose usually means connection, and connection shows up in your nervous system. n=6985 is a solid cohort.
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