the King’s Holly has lived 1.46 million days thus far, other trees have a lifespan of just 3650 days, ceasing to be alive even before a human reaches puberty; Finding longevity drugs based on the 400,000 percent different longevity difference between
trees goes with doing HPLC, something better than electrophoresis like laser spectroscopy, electrophoresis or some other thing, to find all the chemicals, proteins, peptides, lipids, in the plants, as well as at human tissue, then finding those chemicals,
proteins, peptides, lipids difference between the 1.46 million day longevity plant, the 3650 day plant, and the human;
I read humans share 60% of their genome with the banana, that suggests some plant genes, and plant gene products, and the amount of those chemical plant gene products, have most longevizing molecule versions that can be quantified as to longevity effects
at yeast and mice;
finding longevity chemicals: the group of chemicals (and genes) at both the (3650 day tree and the human) that are different than the chemicals that the (kings holly and the human share) are places where the chemicals (and the genes) at the humans could
improve and the king’s holly is the source of improvement;
At homologous genes an organisms that noticed it had the 3650 day plant version rather than the kings holly would notice an opportunity to have more longevizing chemicals endogenously produced
finding longevity chemicals: dosing yeast and mice with the chemical that the kings holly gene makes, that the human does not, noting the homologous but different gene, could find longevity drugs;
engineering mice and yeast to make that shared homologous kings holly gene then finding out if it longevizes them produces new longevity genes
This same approach works for finding longevizing chemicals between groups like million year lifespan endoliths comparison grouped with similar-to-endolith with different habitat organisms with 365 day lifespans, 214 year old whales, and whales with
briefer lifespans, 400 year lifespan clams, and clams with annual lifespans, and supercentenarian humans with 18 year marmosets;
The genes and gene products (chemicals) that the 400 year clam shares with the annual clam are ignored when narrowing the list of chemicals and genes at the human to find 400 year clam genes with longevity effects;
Now, although the amount of the chemicals matters the same thing can be done with chemicals, proteins, peptides, and lipids at the bodies of the various trees and other organisms
If the chemical is the the 3650 day plant and the king’s holly, ignore it, if it is only at the king’s holly put it in a database;
This works better at varieties of the same species with widely varying lifespans, if there are any species that interbreed but have 2-4 times different longevity, then ignoring the chemicals they share, then making a database of the chemicals only at the
long lived variety, then at humans finding if any of the database chamicals
There is a thing here though that kind of makes it improvable, for each 14 million chemicals the kings holly contains, and the 3650 plant overlaps 90% of them, that is still 1.4 million chemicals that might have longevity effects;
I think geneticists who write computer programs already know all about this, but if you have like 100 groups of related-organisms pairs (king’s holly 3650 day tree),(mouse, beaver), (214 year whale, less longevity whale), (human, primate with 1/5th
human lifespan) with the group members as far apart as possible as to longevity, and then compare the amount the very different most long lived species converge towards each others gene versions, notably moving away from their species-similar organisim,
then you find a possible math convergence around better versions of genes, or better versions of physiochemicals
The high longevity organisms at each of the 100 bowls of 2 or 3 longevity heterogenous organisms each
This technique can be used for other things like, 100 bowls of 2 or 3 mammals each, and the species similar mammals differ as much as possible on behavior, then you look at how the bowl leaders (of very different species) converge on various
characteristics, these can be genes, fMRI of brain areas, even things like parenting styles; a human, or niftily, a deep learning AI can then make a list of trends
(Mathematically you would expect the beaver to be more like the mouse, but if the beaver is more like the whale, the human, and the King’s holly then there might be a longevity trend at that homologous gene, similarly you might expect a human to be
more like a marmoset than a whale or the king’s holly, but at genes where the king’s holly is more similar that could suggest a “different chemical is better” trend, then noting the upper longevity organisms at each of the 100 bowls each with two
or three species in them (mouse beaver, 214 year whale, less longevized whale) (longevized bat, less longevized bat) (human, primate with 1/5th human longevity)
The 100 bowls of three high distalness (long lived, otherwise) yet each bowl with similar species could be repeated at species that have particularly wide longevity ranges, perhaps birds as well; if this finds a longevity trend for a group of genes at
very different birds, then the genes the different bowl gnes most share
also the 100 bowls thing of 2 or 3 organisms thing works with longevity chemicals as well, if 100 bowls find like 5000 circulatory chemicals shared at the long lived organisms out of each bowl, then those 5000 chemicals are compared to the chemicals in a
human, any of the 100 bowl shared longevity chemicals the human does not (yet) have could be tested on yeast and mice and human tissue culture to find out if they are longevizing; this works with homologous genes as well, if you have 100 bowls of clams,
birds, sharks, endoliths, plants, and other things, and the distal organisms in each bowl have and above-chance occurence of shared genes, then those could be longevity genes and a human would compare their genome to that shared at the 100 bowls of very
different species; mathematically it would be possible to list in order the genes shared between bowls, and the longevity trend of just that group of bowl-set organisims, so it would be possible to find the likely most longevizing versions of the bowl-
shared genes;
at endoliths, 100 bowls as a way to find new human longevity genes has nifty characteristics; endoliths can be bacteria, fungi, algae or lichen, very different species, but they all share lifespans longer than the entire span of human culture; first find
briefer species that are most genetically similar to the endoliths, (3 century lichens) (24 hour bacteria) to put in the bowls, with each of the 100 bowls having an endolith; do HPLC on all the organisms chemicals, and sequence the genomes of the 200 or
300 organisms in the 100 bowls, then find where the endoliths converge towards each other, across widely differing species, and away from the other organisms at their bowl,
The chemicals (proteins, peptides, others) that subsets of endoliths produce that have varied amounts of convergence at different subsets of the 100 bowls can be tested as longevity cheimcals;
encouragingly, the 10,000 year lifespan creosote bush produces NDGA, which is also published as causing greater longevity at mice, so chemicals that 100 different endoliths converge on, at unexpected divergence from the other organisms in their similar
species bowl, could be longevity drugs and chemicals;
similarly, the long lifespan but species heterogenity of endoliths (algae, bacteria, fungi) if there are any converged on homologous genes could actually suggests genetics of greater longevity at humans, that can be tested on mice, let’s say the
endoliths all have mitochondrial DNA that causes mitochondrial uncoupling, then a human could look through a database of mammal genetics and genomes and find out if any mammals had uncoupled mitochondria, and the effect it had on that species being above
the median, or high above the median on longevity; (I read that mitochondrial uncoupling actuallu doubles c elegans lifespan, it just seems possible to have a 100 bowl convergence be able to find it as well)
do the “are there any mammals like the converged endoliths’ homologous genes unusualness of form, and, how is it going for them?” thing automatically with computers, also, the technique can be used with any group of species like birds, or
tortoises, or even bowls of plants, along with the kings holly there are many trees with multimillenia lifespans
when they do, that version of that mammal gene is unusually likely to be a longevity gene, and using yeast and mouse full lifespan to quantify its effects is beneficial and produces a longevity gene; notably though the gene sometimes makes a product like
a protein, endolith converged, then found at mammal genes’ proteins could be screened as to longevity effect; I read that sme endoliths, after you put them in a comfy environment grow rapidly, and a kilogram of cultured endolith might provide enough
converged-endolith-gene product to dose shrews, c elegans, yeast, and human tissue culture; (it is kind of nice with 100 bowls you get to skip screening a library, you just culture and gather material from of the species at one of the bowls that makes
the converged on chemical, a mathematician would be able to suggest the optimal number of bowls, with endoliths perhaps it is 300 because, if there is convergence on some chemicals, rather than the numerics of screening a library you already have a
source)
mathematically
I think a mathematican would be able to come up with an equation and a number to communicate divergence from species similars and convergence on high longevity;
Doing the 100 bowls thing on endoliths, or plants, finds chemicals that are common between high longevity organisms, that took some mathematically less predictable paths, to develop a shared trait, which produces chemicals and has genes that can be
tested on other species to find out if the trend
There could be a 100 bowl convergence with three layers being outside a mathematically predicted form; three data points, i think i heard, can make a trend, and at 100 bowls of two or three organisms, the divergence from other organisms at the same bowl,
and the convergence on specific chemicals and genes among the high longevity bowl organisms, suggests that if there is a third thing then the longevity trends will have greater predictive ablity for specific chemicals and genes (gene versions); one
possible approach to making three data areas to make a trend from is to put a mid-longevity specied in each of the 100 bowls and find out if any of them are shared any of the chemicals (or gemes) that the highest longevity longevity animals comverge on
then the actual chemical and kind of cytochemical and tissue chemical network that the organisms with the greatest longevity at each bowl have, notably where this shared convergence on cytocommunication network form diverges from the similar species in
the same bowl;
I read 60% of the human genome is shared with the banana, so if there is a human tissue chemical, made from a gene that is the same as that of a 3650 day tree, and there is an alternate version of that chemical and gene produced at the kings holly, then
that is a human and tree shared chemical with what may be a much greater longevity version; yeast and mice could be utilized to find out if putting the king’s holly homologous gene at a mammal causes greater longevity;
senolytic dasatinib with quercetin treatment, 190 days compared with 140 days greater longevity from start of treatment, about 35% greater longevity, “20-month-old male mice treated with D+Q”, “For all dasatinib+quercetin (D+Q) treatments, D (5mg/
kg, drug/body weight) and Q (50mg/kg) were administrated by oral gavage in 100-150 μL 10% PEG400. For treating 20-month-old mice, D+Q was delivered either once monthly or every 2 weeks, with essentially identical effects.once every 2 weeks (bi-weekly)
for 4 months.”
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082705/
so that is 350 mg for a 70 kg human, 8 times, or 4 times at monthly 2.8 grams, mouse dose compensation factor changes that to 233 mg for all 8 doses.
The quercetin is 2.91 grams per dose, so 8 doses is 23.3 grams
At roayl jelly amking mice live midway between 24 and 26% longer 500 ppm at ad libitum food mixed with 9 parts trehalose was used, at mice that is 25 g a day human dose, or using mouse compendation factor that is 2.09 g/ad libitum feeding, the 50 ppm/ad
libitum feeding was almost identicallly longevizing (112 weeks compared with 110 weeks high dose) and is 250 mg ad libitum feeding human dose, or 2.08 mg ad libitum feeding human dose with mouse compensation dose
That suggests enteric coated 20 grams of trehalose and royal jelly could be effective as an oral dose, coadministered with 2.08 grams royal jelly enteric capsule dose with food
That compares with 60 mg/kg of food at precis of paper, and at medium dose that is 60 mg/kg or 4.2 grams per 24 hours, or 420 mg per 24/hours at a 70 Kh human, without mouse comepensation factor the high dose is 25 gram ad libitum with trehalose and 2.09
grams with mouse compensation factor; note this does not function with high dose medium dose order or magnitude difference
The very large dose, based on mice eating 1/6 of their body mass a day, then calculating a dose on a human eating
Highest high mouse dose is 4.2 grams a day ad libitum with food, lowest high mouse dose is 350 mg, highest medium mouse dose is 420 mg ad libitum, lowest medium mouse dose is 42 mg
most of the mutants with long lifespan had mutations in the age1 gene [4]. This gene turned out to be the catalytic subunit of class-I phosphatidylinositol 3-kinase
(PI3K).
Sirtuins, epigenetics of sirutins, sirtuin supplements. it is possible endoliths like million year lifespan endoliths have novel sirtuin effecting chemicals
Mammals possess seven sirtuins (SIRT1–7) that occupy different subcellular compartments such as the nucleus (SIRT1, -2, -6, -7), cytoplasm (SIRT1 and SIRT2) and the mitochondria (SIRT3, -4 and -5).
sitruins are deacetylases, SIRT6 is shown in previous studies to be a critical epigenetic regulator of glucose metabolism, it is possible that other things that upregulate or are actual deacetylases, including non epigenetic deacetylases could be
longevity or healthspan drugs, screening a library of molecules that do about the same thing as SIRT6 could find a longevity hieghtening epigenetic drug that is more effective than SIRT6, sirt6 is linked to aging, temoleres and inflammation
SIRT like resveratrol-mimicking drugs such as SRT1720 could extend the lifespan of obese mice by 44%. However, “feeding chow infused with the highest dose of SRT1720 beginning at one year of age increased mean lifespan by 18%, and maximum lifespan by 5%
, as compared to other short-lived obese, diabetic mice; however, treated animals still lived substantially shorter lives than normal-weight mice fed normal chow with no drug.[2] In a later study, SRT1720 increased mean lifespan of obese, diabetic mice
by 21.7%, similar to the earlier study, but there was no effect on maximum lifespan in this study.[3] In normal-weight mice fed a standard rodent diet, SRT1720 increased mean lifespan by just 8.8%, and again had no effect on maximum lifespan.[3]”
43% greater maximumn lifespan from GDF15 is published “Female hNAG-1 mice (mice expressing hNAG-1/hGDF15) have significantly increased mean and median life spans in two transgenic lines. The effect is stronger in mice on high fat diet than on low fat
diet. hNAG-1 mice display reduced body and adipose tissue weight, lowered serum IGF-1, insulin and glucose levels, improved insulin sensitivity, and increased oxygen utilization, oxidative metabolism and energy expenditure.
% change in avg or median lifespan
Female mean lifespan is up to 43% higher.”
The RNA microRNA 17 that increases longevity could be a longevity drug immediately with online ordering and enteric coated capsules or possibly snortable form, or both
microRNA 17
Mus musculus
Pro-Longevity
16%
Gdf15
growth differentiation factor 15
Mus musculus
Pro-Longevity
43%
A list of longevity increasing genes is at
http://genomics.senescence.info/genes/search.php?search=&show=4&sort=1&organism=Mus+musculus&long_influence=pro&lifespan_effect=increase&search=&page=1Mir17 Growth/differentiation factor 15 (GDF15)
Nasal liposomes,
liposome formulations showed a mean diameter in the range of 175 nm to 219 nm with polydispersity index lower than 0.22, a lightly negative zeta potential and excellent encapsulation efficiency. Moreover, along with good mucoadhesive properties,
multifunctional liposomes showed a markedly increase in tacrine permeability, which can be related to liposome fusion
with cellular membrane,
C-Pc liposomes were more effectively taken up by Neuro2a cells than free C-Pc and were biocompatible, maintaining the anti-oxidative properties of C-Pc. When optimal C-Pc liposomes were administered to middle cerebral artery occlusion (MCAO) rats 2 h
after onset, infarct sizes were smaller and behavioral activities improved compared with the same metrics in free C-Pc-treated rats. Liposomal delivery still reduced infarct sizes and improved behavioral activity 6 h after onset, whereas free C-Pc did
not.
Intranasal liposomes had a longer half-life in the brain than intranasally or orally administered free drug
Piperine is an antidepressant works better as a snortable liposome, “Antidepressant and cognitive effects of piperine-en- capsulated liposomes (PL) were investigated in male Wistar rats. Oral piperine (5 mg/kg body weight/day) and intranasal PL (7.2 μ
g/day) were randomly as-signed to daily administer for 14 days to rats which were subjected to forced swimming, Morris water maze and spontaneous motor behavior tests. PL sig-nificantly exhibited anti-depression like activity and cognitive enhancing
effects, in comparison to the con-trol groups after the first dose (p < 0.01) and the ef-fects could be maintained throughout the period of study. Quantitative analysis of the brain homogenates by HPLC indicated that piperine, delivered either orally or
nasally, distributed to the hippocampus at a higher extent than the cortex and that the time to peak concentration of nasal PL was shorter than for the oral piperine. Intranasal PL was, thus, potential in delivery of piperine, at a low dose, to exert its
an-tidepressant and cognitive enhancing activities.”
siRNA drugs can be administered with liposomes, “ntranasal delivery of the siRNA targeting Beclin1 significantly depleted the target protein expression levels in brain tissues with no evidence of toxicity.”
we developed a nose-to-brain delivery system combined with cell-penetrating peptide (CPP), Cell-Penetrating Peptides (CPPs), also known as protein transduction domains (PTDs), membrane translocating sequences (MTSs), and Trojan peptides are short
peptides (≤40 amino acids), with the ability to gain access to the interior of almost any cell. They are highly cationic and usually rich in arginine and lysine amino acids. They have the exceptional property of carrying into the cells a wide variety
of covalently and noncovalently conjugated cargoes such as proteins, oligonucleotides, and even 200 nm liposomes.
melatonin antidepressants, mood elevators exist, “Agomelatine is a structural analog of melatonin”, it is possible that like tyhe pineal peptide AEDG causes greater longevity molecular variations of these mood improving drus could be simulataneously
longevizing and mood improving, “agomelatine. Agomelatine is a melatonergic agonist and a 5HT2c antagonist (i.e., it has a unique mechanism of action). The melatonergic function appears to improve sleep patterns, whereas the serotonergic antagonism
results in the release of norepinephrine and dopamine.”
Previously described is finding the genetics of having good dreams, I favor making the genetics of having good dreams part of the human germline, also, amount persons above the 99th percentile of longevity they could find those at the 99% of having
actively good dreams and an absence of dreams the person would prefer to have skipped, this is a guide to finding the genetics of more beneficial sleep, it may even be possible that there are those at the 99th percentile of longevity who dream twice as
much as others, dreaming good dreams twice as often is beneficial to humans and is beneficial to make a part of the human germline
g (like IQ) gene “klotho-enhanced mice performed better on a variety of learning and memory tests, regardless of age. In one test, the mice remembered the location of a hidden target in a maze better, which allowed them to find it twice as fast as
control mice.”
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