Ron Put

Yep, and this was before the Covid madness which made things worse. I trust that things self-correct in the long run, it's just takes a really, really long run in some cases.

Low compared to what though? If to the "normal" range prevalent in the US, Europe and elsewhere where they have discovered fast food, consider yourself lucky.

You might find this interesting:

Physicist Claims To Have Solved the Mystery of Consciousness TOPICS:Bar-Ilan UniversityBrainNeurosciencePopularPsychology By BAR-ILAN UNIVERSITY AUGUST 14, 2022 Scientists have developed a new conceptual and mathematical framework to understand consciousness from a relativistic point of view. According to the theory, all that’s needed to solve the hard problem of consciousness is to change our assumptions about it. When we realize that consciousness is a physical, relativistic phenomenon, the mystery of consciousness naturally dissolves. How do 3 pounds of brain tissue create thoughts, feelings, mental images, and a detailed inner world? The ability of the brain to create consciousness has baffled people for millennia. The mystery of consciousness lies in the fact that each of us has subjectivity, with the ability to sense, feel, and think. In contrast to being under anesthesia or in a dreamless deep sleep, while we’re awake we don’t “live in the dark” — we experience the world and ourselves. However, it remains a mystery how the brain creates the conscious experience and what area of the brain is responsible. According to Dr. Nir Lahav, a physicist from Bar-Ilan University in Israel, “This is quite a mystery since it seems that our conscious experience cannot arise from the brain, and in fact, cannot arise from any physical process.” As bizarre as it sounds, the conscious experience in our brain, cannot be found or reduced to some neural activity. “Think about it this way,” says Dr. Zakaria Neemeh, a philosopher from the University of Memphis, “when I feel happiness, my brain will create a distinctive pattern of complex neural activity. This neural pattern will perfectly correlate with my conscious feeling of happiness, but it is not my actual feeling. It is just a neural pattern that represents my happiness. That’s why a scientist looking at my brain and seeing this pattern should ask me what I feel, because the pattern is not the feeling itself, just a representation of it.” Because of this, we can’t reduce the conscious experience of what we sense, feel, and think to any brain activity. We can only find correlations to these experiences. After more than 100 years of neuroscience, we have very strong evidence that the brain is responsible for the creation of our conscious abilities. So how is it possible that these conscious experiences can’t be found anywhere in the brain (or in the body) and can’t be reduced to any neural complex activity? This mystery is known as the hard problem of consciousness. It is such a difficult problem that until a couple of decades ago only philosophers discussed it. Even today, although we have made huge progress in our understanding of the neuroscientific basis of consciousness, still there is no satisfactory theory that explains what consciousness is and how to solve this hard problem. In the journal Frontiers in Psychology, Dr. Lahav and Dr. Neemeh recently published a new physical theory that claims to solve the hard problem of consciousness in a purely physical way. According to the researchers, when we change our assumption about consciousness and assume that it is a relativistic phenomenon, the mystery of consciousness naturally dissolves. In the paper, the authors developed a conceptual and mathematical framework to understand consciousness from a relativistic point of view. According to Dr. Lahav, the lead author of the paper, “consciousness should be investigated with the same mathematical tools that physicists use for other known relativistic phenomena.” In order to understand how relativity dissolves the hard problem, think about a different relativistic phenomenon, constant velocity. First, let’s choose two observers, Alice and Bob. Bob is on a train that moves with constant velocity and Alice watches him from the platform. There is no absolute physical answer to the question “what is the velocity of Bob?” The answer is dependent on the frame of reference of the observer. From Bob’s frame of reference, he will measure that he is stationary and Alice, with the rest of the world, is moving backward. But from Alice’s frame of reference, Bob is the one that’s moving and she is stationary. They have opposite measurements, yet both of them are correct, just from different frames of reference. We find the same situation in the case of consciousness because, according to the theory, consciousness is a relativistic phenomenon. Now Alice and Bob are in different cognitive frames of reference. Bob will measure that he has conscious experience, but Alice just has brain activity with no sign of the actual conscious experience. On the other hand, Alice will measure that she is the one that has consciousness and Bob has just neural activity with no clue of its conscious experience. Just as in the case of velocity, although they have opposite measurements, both of them are correct, but from different cognitive frames of reference. As a result, because of the relativistic point of view, there is no problem with the fact that we measure different properties from different frames of reference. The fact that we cannot find the actual conscious experience while measuring brain activity is because we’re measuring from the wrong cognitive frame of reference. According to the new theory, the brain doesn’t create our conscious experience, at least not through computations. The reason that we have conscious experience is because of the process of physical measurement. In a nutshell, different physical measurements in different frames of reference manifest different physical properties in these frames of reference, although these frames measure the same phenomenon. For example, suppose that Bob measures Alice’s brain in the lab while she’s feeling happiness. Although they observe different properties, they actually measure the same phenomenon from different points of view. Because of their different kinds of measurements, different kinds of properties have been manifested in their cognitive frames of reference. For Bob to observe brain activity in the lab, he needs to use measurements of his sensory organs like his eyes. This kind of sensory measurement manifests the substrate that causes brain activity – the neurons. Consequently, in his cognitive frame Alice has only neural activity that represents her consciousness, but no sign of her actual conscious experience itself. However, for Alice to measure her own neural activity as happiness, she uses different kinds of measurements. She doesn’t use sensory organs, she measures her neural representations directly by interaction between one part of her brain with other parts. She measures her neural representations according to their relations to other neural representations. This is a completely different measurement than what our sensory system does and, as a result, this kind of direct measurement manifests a different kind of physical property. We call this property conscious experience. As a result, from her cognitive frame of reference, Alice measures her neural activity as conscious experience. Using the mathematical tools that describe relativistic phenomena in physics, the theory shows that if the dynamics of Bob’s neural activity could be changed to be like the dynamics of Alice’s neural activity, then both will be in the same cognitive frame of reference and would have the exact same conscious experience as the other. Now Dr. Lahav and Dr. Neemeh want to continue to examine the exact minimal measurements that any cognitive system needs in order to create consciousness. The implications of such a theory are huge. It can be applied to determine which animal was the first animal in the evolutionary process to have consciousness, which patients with consciousness disorders are conscious, when a fetus or baby begins to be conscious, and which AI systems already today have a low degree (if any) of consciousness. Reference: “A Relativistic Theory of Consciousness” by Nir Lahav and Zachariah A. Neemeh, 12 May 2022, Frontiers in Psychology. DOI: 10.3389/fpsyg.2021.704270

https://brownstone.org/articles/the-global-march-of-folly/ The Global March of Folly BY MARTIN KULLDORFF, JAYANTA BHATTACHARYA APRIL 6, 2022 LAW, POLICY, PUBLIC HEALTH 7 MINUTE READ SHARE | PRINT | EMAIL Throughout the pandemic, the media have eagerly compared Covid statistics between different countries. But such comparisons are often deceptive. Take, for example, the use of Covid case counts. These depend not only on the number of people infected but also on the amount of testing performed. While useful for evaluating whether cases are increasing or decreasing within a particular country, they are deceptive when comparing countries. If we truly wanted to know, it would be easy, through random seroprevalence surveys that measure the proportion of people with antibodies. But not all governments have been eager to conduct these surveys, while some scientists have even got into trouble for doing them. Comparing Covid death tolls between countries, as many journalists have done, is equally problematic. A Covid death is defined differently in different countries, with varying testing thresholds and a different maximum number of days required between a positive test and death. Therefore, countries vary in the proportion of reported Covid deaths that, firstly, are genuinely due to Covid, secondly, have Covid as a contributing factor but not as the main cause, and, thirdly, that show whether an individual died with rather than from Covid. This confusion can lead to an over-reporting of Covid deaths. If we truly wanted to know, it would be easy. We could randomly select some reported deaths and evaluate their medical charts. Surprisingly few such studies have been performed. Other countries have under-reported Covid mortality. For example, Nicaragua has reported very few Covid deaths. However, from reports that carpenters were working overtime to fulfill the burgeoning demand for wooden burial coffins in 2020, we certainly know that large numbers of people were dying from Covid there. The media have also been tripped up by several significant variables. For example, the pandemic arrived and surged at different times in different countries, and even within countries – as you would expect from any pandemic. During the first wave in 2020, some countries were praised for their strict lockdowns and low Covid mortality, but subsequent waves hit some of them so badly that they now have among the highest mortality numbers in the world. Covid is also seasonal. This means that it follows different seasonal patterns in different regions. This fact also tripped up journalists. In 2021, many journalists (often New York-based) blamed the seasonal summer wave in the southern United States on Covid policies. But when the subsequent winter wave arrived in the northern US, it was clear to all that it was a seasonal effect. Extreme Covid restrictions, such as those imposed by Australia, Hong Kong and New Zealand, certainly kept the virus at bay for a while. But that just postponed the inevitable. All countries have to work their way through the pandemic sooner or later. Moreover, the focus on Covid cases, death counts and so on, ignores the collateral public-health damage from Covid restrictions. These have contributed to deaths from other diseases, and such deaths are just as tragic as Covid deaths. A basic public-health principle is that one should never focus on one single disease but consider public health as a whole. Even if the lockdowns reduced Covid mortality, for which there is scant evidence, one must also consider the harm that the lockdowns caused on other health conditions such as worsening cardiovascular-disease outcomes, missed cancer screening and treatment, lower childhood-vaccination rates, and deteriorating mental health. Given all this, how should we compare countries’ handling of the pandemic? While not perfect, the best way is to compare excess mortality; that is, the observed total number of deaths during the pandemic minus the average number of deaths observed during the years before the pandemic. Since the pandemic is not yet over, we do not have the full picture yet. Nevertheless, a recent article in the Lancetpresents excess deaths for 2020-2021 for almost every country in the world. The map below shows the results: Global distribution of estimated excess-mortality rate due to the Covid-19 pandemic, for the cumulative period, 2020-21 What can we learn from these data? How did three main pandemic strategies compare: (a) a do-nothing, let-it-rip approach; (b) focused protection of high-risk older people with only limited restrictions on others, and (c) general lockdowns and restrictions on all age groups? Belarus and Nicaragua did little to protect older people and they imposed very few Covid restrictions. They also report among the lowest Covid mortality numbers. From the excess-mortality data, it is clear that they did not escape the pandemic. Nicaragua had 274 excess deaths per 100,000 population, which is precisely the same as the regional average. Belarus had 483 excess deaths per 100,000, higher than the average for either Eastern Europe (345) or Central Europe (316). In Western Europe, the Scandinavian countries had the lightest Covid restrictions while they tried to protect their older high-risk population. Sweden was heavily criticised for this by the international media. The Guardian, for instance, reported in 2020 that life in Sweden felt ‘surreal’, with ‘couples stroll[ing] arm in arm in the spring sunshine’. Many journalists, politicians and scientists expected that the lighter Scandinavian touch would lead to disaster. That did not happen. Sweden has among the lowest reported Covid mortality numbers in Europe. Of the European countries with more than one million people, Denmark (94), Finland (81), Norway (7), and Sweden (91) are four of only six countries with excess mortality less than 100 per 100,000 inhabitants, the other two being Ireland (12) and Switzerland (93). What about the UK, with its more heavy-handed Covid restrictions? Compared to the Western European average of 140 excess deaths per 100,000, England had 126, Scotland 131, Wales 135, and Northern Ireland 132. In the US, South Dakota imposed few Covid restrictions, while Florida tried to protect older people without too many restrictions on the general population. Did that result in the predicted disaster? No. Compared to the national average of 179 excess deaths per 100,000, Florida had 212 while South Dakota had 156. Countries in Sub-Saharan Africa report the lowest Covid mortality globally, with seven deaths per 100,000, but their excess mortality is 102 deaths per 100,000. Without age-stratified numbers, we do not know how much of this difference is due to the under-reporting of Covid deaths as opposed to the harsh lockdowns that caused malnutrition and starvation among the poor. The countries with the highest excess mortality are Bolivia (735), Bulgaria (647), Eswatini (635), North Macedonia (583), Lesotho (563), and Peru (529), with no other countries topping 500 excess deaths per 100,000. According to the Oxford Stringency Index, Peru has endured some of the world’s harshest Covid restrictions while those in Bulgaria, Eswatini and Lesotho were closer to the average. Bolivia had very harsh restrictions in 2020, but not in 2021. Though excess-mortality data should still be treated with caution, they do show that the few places that rejected draconian Covid restrictions did not see the catastrophic death counts that some had predicted. The pandemic is not over, and with different seasonal patterns in different regions and different levels of population immunity, some countries have not yet seen the worst. For example, 40 per cent of all reported Covid deaths in Denmark occurred during the first 80 days of 2022. Denmark is not as extreme a case as Hong Kong, where 97 per cent of all reported Covid deaths have been in 2022. The biggest weakness of excess-mortality statistics is that while they count Covid deaths, they do not fully capture the deaths, not to mention the collateral public-health damage, that come from Covid restrictions themselves. Missed cancer screenings and treatments do not lead to immediate deaths, but a woman who missed her cervical cancer screening may now die three or four years from now instead of living another 15 or 20 years. The mortality statistics do not reflect non-fatal collateral damage such as increasing mental-health problems or missed educational opportunities, either. Those harms need to be tallied and addressed in the years to come. Politicians argued that the draconian lockdowns were needed to protect lives. From the excess-mortality data, we now know they were not. Instead, they have contributed to the enormous collateral damage that we will have to live with for many years to come. It is tragic. In her classic book, The March of Folly, historian Barbara Tuchman describes how nations sometimes pursue actions contrary to their interests. She starts with Troy and the Trojan horse and ends with the US and the Vietnam War. By ignoring basic, long-standing principles of public health during the pandemic, most nations marched down the path of folly together. The leaders of those nations will be fine, except for some early retirements. The devastation on children, the poor, the working class and the middle class, on the other hand, will take decades to repair. Republished from Spiked-Online Authors Martin Kulldorff Martin Kulldorff, Senior Scholar at Brownstone Institute, is an epidemiologist and biostatistician. He is Professor of Medicine at Harvard University (on leave) and a Fellow at the Academy of Science and Freedom. His research focuses on infectious disease outbreaks and the monitoring of vaccine and drug safety, for which he has developed the free SaTScan, TreeScan, and RSequential software. Co-Author of the Great Barrington Declaration. READ MORE Jayanta Bhattacharya Jay Bhattacharya, Senior Scholar at Brownstone Institute, is a physician, epidemiologist and health economist. He is Professor at Stanford Medical School, a Research Associate at the National Bureau of Economics Research, a Senior Fellow at the Stanford Institute for Economic Policy Research, a Faculty Member at the Stanford Freeman Spogli Institute, and a Fellow at the Academy of Science and Freedom. His research focuses on the economics of health care around the world with a particular emphasis on the health and well-being of vulnerable populations. Co-Author of the Great Barrington Declaration.

Of course, you are free to do so, except where security concerns may require you to take it off. But neither you, nor "The Science" weaponized by the zealots, should ever again be allowed to force the rest of society to do as you do. Rubber bands or not. I can only hope that at some point a major democracy will have the political will to do a thorough investigation and call those who were in power to answer for wrecking the economy and the lives of so many. If one does it, maybe more will. And we will be better for it.

One should always ask questions if unsatisfied with the supporting information underlying a currently accepted practice. The Covid-triggered mass idiocy showed us what happens when "The Science" becomes a religion. I read with interest findings like this, and actually enjoy the debate, as it forces me learn, and sometimes to reevaluate my positions. I also believe that each adult should be able to ultimately control what they do and how they treat their own body, and accept the consequences. Having said that, I tend to agree with Dean on this, based on what I know about the topic. Thus I successfully dropped my LDL-C significantly below 100, largely by eliminating my daily consumption of fat, primarily as EVOO. Time will tell, maybe. Mccoy makes a valid point about CAC. Here is a larger and longer food for thought: The association of 14-year dietary cholesterol trajectories with the risk of cardio-metabolic diseases, all-cause mortality and serum lipids Results Compared to the participants with persistently low dietary cholesterol intake, participants with gradually increasing cholesterol intake throughout adulthood were more likely to have hypertension (HR = 1.14, 95% CI: 1.03, 1.28) and to die due to all causes (HR = 2.19, 95% CI: 1.57, 3.05). Moreover, participants with persistently high cholesterol intake were more likely to die due to all causes (HR = 2.26, 95% CI 1.47, 3.47). The total cholesterol (TC):HDL-cholesterol (HDL-C) ratio and apolipoprotein B (ApoB) in these two groups were also significantly elevated compared to the group with persistently low dietary cholesterol intake (all P < 0.05). An association between trajectories of cholesterol and the incidence of diabetes was also observed; however, such an association became non significant after additional adjustment for other nutrients, food consumption and social environment.

I think both Huberman and Attia have rather strong biases on some topics, but I listen to both as both offer a lot of good information too. In the case of alcohol, I have gone from being a cheerleader for moderate (mostly red wine) drinking to personally reducing my wine intake to practically zero, or about a glass a month lately. A large part of the reason has to do with the increased accuracy of the trackers I wear and the data is there -- even a single glass affects my sleep, my RHR, HRV and my stress level. It's consistent. I have stopped eating desserts for similar reasons, as my data shows similar effects after eating a couple of slices of cake. It affect my sleep similarly but to a lesser extent than wine or any other alcohol. And this is just with my Garmin, the two CGMs I wore just confirmed that while my sentience loves cake, my body doesn't. Once one separates from one's strong biases the scientific evidence is right there and it starts making sense. Same for olive oil, but that seems to get people more riled up than even wine. 😄 Kombucha cheers!

Nothing really new in the article. Similar observations have been made since at least the 1960s, at least as far as I am aware. Technically all life reacts to its environment and there is no particular reason why plants would be precluded from having a degree of subjective experiences. But I have a sneaking suspicion that this is intended as a jab at the moral superiority of the vegans lurking here... 🙂

One additional point, on the accuracy of the CGMs: The first 12-24 hours are kind of random, with dubious value in terms of accuracy. This is confirmed by numerous posts and reviews from actual diabetics who compare it to their blood glucose data. It seems to settle down after that. I am in about 48 hours on the second sensor and this one appears more in line with my lab test, showing an average of about 85. The spikes are also about 10 points lower and so are the dips (it has gone down to the mid-60s on a couple of occasions). The first sensor appeared to track about 10 points higher than the second one and the pattern is fairly consistent so far. mccoy, did you go through only a single sensor? Based on my reading and experience, while the curve pattern may be valid, the actual values may be a bit off depending on the sensor.

The BP fluctuations appear to be normal and within the normal range. Did you sign up for a full year with Akktia? Like CGMs, it appears to be valuable to establish patterns.

Maybe I will try ayahuasca at some point, there are semi-legitimate guides where I live. I was just turned off by the side effects as described to me. I was with my wife on a week-long river and walking trek fairly deep in the forest, in a small remote village, and decided against spending a day squatting and throwing up. The old woman who was going to prepare it had already given me a particularly stringy chicha she had masticated herself and I had not had the heart to refuse, which I guess contributed to my reluctance. While I am not depressive, there is a fair amount of evidence that psilocybin has some rather interesting beneficial effects, with minimal potential for harm. See this, for example: "The new Yale research found that these compounds increase the density of dendritic spines, small protrusions found on nerve cells which aid in the transmission of information between neurons. Chronic stress and depression are known to reduce the number of these neuronal connections. ... They found increases in the number of dendritic spines and in their size within 24 hours of administration of psilocybin. These changes were still present a month later. Also, mice subjected to stress showed behavioral improvements and increased neurotransmitter activity after being given psilocybin." I don't meditate purposefully, but I found the mushrooms experience to be rather profound, the way I imagine deep meditation is. On another note, I find that after a while, luxury resorts tend to offer a similar experience no matter where they are in the world. Kind of like Michelin-star restaurants, and even major museums. They have their place, of course, but in the end, the experience can become monotonous. If comfort is such a priority, one may as well stay home 🙂

Interesting, I did not know about pharmuasca. How does it compare in terms of experience and side effects? I am generally leery of ingesting pharma substances provided by a "friend of a friend" and it has deterred me from trying stuff like LSD or MDMA. I was all set to do ayahuasca in Ecuador a few years ago until the guide told me about subsequent vomiting and diarrhea, which made me decide against it. I have done mushrooms recently and it provided an enhanced state of meditation and introspection that I found enriching. No hallucinations.

Interesting, thanks Saul! There is accumulating evidence that inflammation plays a significant role in aging-related diseases, including brain functionality. Rapamycin may not be the answer, but the interplay of genes and lifestyle appears to be important.

I have the feeling that the high-fat/low-carb crowd focuses on flat lines too much, at least in part to sell services and products. It's what virtually all outfits that sell sensor subscriptions do, because it's easy to point to peaks and justify the need for the service and the products. Of course, glucose is only one part and I am not sure how valuable it is in the end, without taking insulin into account. I have a pretty high carb intake, averaging 61% of my diet over the past year, with 14% protein and 24% fat, according to Cronometer. Most of the carbs come from chickpeas and other legumes, as well as sweet potatoes and to a lesser extent grains such as steel-cut oats, dark sorghum, and flaxseed. Most of the protein also comes from legumes, and also from tofu, mushrooms (and tomatoes?!). I wish I could go down to 10% of protein, but it seems too hard for me. I noticed glucose peaks as high as 150 when I eat a particularly large meal. Usually, it's legumes, sweet potatoes/yams, crushed tomatoes and greens, but the size appears to be of particular importance. Such peaks usually occur around the first hour and then I am back to around 95-100 about 2 hours later, sometimes 2.5 hours. I wonder if others here who eat very large meals at once, like Michael or Dean, also spike depending on meal size? But the bottom line is that such spies appear to be perfectly normal, as long as there is good insulin sensitivity. Those on high-fat and high-protein diets may spike less as long as they stay away from carbs, but then their insulin sensitivity becomes impaired, resulting in large spikes after relatively minimal carb intake, which to me is not a good thing. January.ai may be more useful to people who are less aware of their diet, but to me, it's pretty useless. I feel the same about all the other similar outfits, such as Zoe, NutriSense, and Levels. Basically, the whole "personalized nutrition" business model. They make flatlining the glucose curve a sport, but I don't see any real scientific evidence that for healthy people it is beneficial, and in fact, they can encourage insulin resistance by promoting high-protein, high-fat diets. The AI part is grossly overstated, basically showing comparisons between meals and the resulting glucose curves. Pretty primitive and simple. They require a Fitbit or Apple Watch but appear to only take HR data from it, which is not all that useful. They don't even utilize sleep and exercise data from the tracker, and both affect glucose curves.

High intake of protein results in insulin resistance. Hight saturated fat intake does the same, I believe. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998345/

I have been buying a different brand, mainly because it's cheaper and organic: https://www.amazon.com/dp/B079FBBHGY?ref=ppx_yo2ov_dt_b_product_details&amp;th=1 I wouldn't worry too much, as I've seen no evidence that vegans are deficient: https://pubmed.ncbi.nlm.nih.gov/2773827/

Lemoine is part of Google’s virtue-signalizing pattern responsible for the pervasive woke biases that brought us well-documented absurdities like the results when you do an image search for “white couple.” His claims are nonsense. A whiny self-important true believer who stomps his feet and demands that his idiocy is taken seriously. People like him were the drivers behind the dangerous censorship that took over during Covid. High time for the tech industry to rid itself of this cancer and ensure that it never succumbs to it again. There is no reason why AI cannot potentially duplicate and surpass human sentiency, but this is definitely not it. For a sane perspective, see this:

It's hard to judge one's own age, but presumably, CR should make one appear younger. Appearance does present health status in broad terms and I would think that all things equal, CR would improve enough health aspects to improve one's general appearance.

I am not sure about the accuracy, since I don't have a way to test blood. The sensor may be reading a bit higher, based on A1C, and my fasting blood glucose is usually within the 80s in lab tests. But as you point out, it's the curve and pattern that's more interesting. On the first screenshot in my previous post, the peak between 15:00 and 18:00 was a somewhat strenuous hour-long hike/trail run, which pushed me to 131 at its peak. The following peaks are pizza, cocktails and stuff like that, followed by a late-night munchies snack. Mostly junk food/refined carbs, and I was sort of happy that it never pushed me over 130. I am not insulin resistant (my last insulting lab test was 3.9, at the same time as the fasting glucose of 82). But yesterday I did a glucose challenge, which pushed me way over. I fasted until about 15:00 (so 15 hours or close), with black coffee and green tea as the only consumables. At about 15:00 I drank a solution of 75g of glucose provided by January.ai. Orange, nasty sweet-tasting liquid 🙂 In an hour I peaked to 174, then by the second hour I was down in the 110s and I crashed, hitting 50s about three and a half hours later, still fasting until then. At that point I ate and then dosed off until about 22:00 (I never just dose off). When I woke up I ate some more and continued snacking until about 01:00. In other words, the glucose challenge really screwed me up 😞 Here is a screenshot of what happened during the first 3 and a half hours after the glucose drink, from the LibreLink app: And here is a longer period that shows the crash after 3 and a half hours, and then bounces from food intake and probably my body trying to recover from the glucose challenge: Interestingly, my Garmin watch registered noticeably increased stress (measured mostly from HRV, I think) as soon as I drank the glucose. It's similar to what I see if I drink alcohol. Here is a shot, the orange is the stress after the glucose: I don't remember if you did a glucose challenge while using the sensor, mccoy. If so, what was your experience?

Thanks, Saul! I'd assumed RBC and albumin would go in tandem on CR. I wonder what others on CR are seeing,, and what it means, if anything?

That's what I assumed, thanks. But what about albumin?

It's quite amazing, although I think the Medium piece was a bit optimistic in its interpretations. Sentience presumes self-awareness and feelings, such as fear of death. A dog has them, and so does a cow, a chicken, or a lamb, which is why I do not eat animals. Humans don't until some time after birth, which is why I think the state should have no say in personal carrying-to-term decisions (had to throw this in 😄 ). I see nothing above or in the LaMDA piece that indicates sentience. In fact, I'd be worried if it exhibited fear of death, for obvious reasons. But so far nothing indicates that it does, and hopefully, by the time it does, we'll have a way of addressing it safely. A more immediate concern is that Google develops and shares know-how with China, which has no qualms about using it for political control and exports it to other authoritarian states. Heck, the Left in the US has shown that it has no qualm about using similar tech to suppress free discussion internally. This is a much more immediate issue, IMO.

Well, I am trying it. It's a way to get the first-gen Libre CGM without a prescription in the US. The price is reasonable ($288 with the current discount) and it includes two sensors and an app that hopefully will provide some insights. I've spent three days with it so far. On all three days, I ate mostly at restaurants and mostly food I don't normally eat. It included Indian (including white rice, and bread), Italian (including pasta with pesto, bread), and American (including breaded, fried Brussels sprouts, a sugary cocktail, and a whole mushroom pizza without cheese). I figured this is kind of a trial by fire (or refined carbs). I was pleased that my glucose never went over 130, despite all the refined carbs. What I am less pleased about is that my average glucose is 103. This translates to A1C of about 5.2, so it's not widely off the mark. My A1C is usually about 5. My lab blood test of about 10 days ago shows fasting glucose of 82 (my insulin result was 3.9, so I am unlikely to be insulin resistant). So far, the Libre patch has not gone this low, generally ranging between 95 and 115, with occasionally reaching the low 80s and the high 120s. Here is a screenshot from LibreLink (fasted until about 15:30 yesterday, ended up with the munchies close to midnight and ate 150g or so of Black Garlic with almonds and walnuts...😞) I've set the desirable band to be 70-130 and I was 77% within it. I noticed that Kambucha seems to cause a spike to about 120 or so. I am still waiting for the January.ai app to gather enough data, but here is an example of an insight it offered: Note that the "garlic" is actually Black Garlic, which is rather sweet and I expected it to spike up, but it actually caused a dip. I am pretty happy so far with the app and the info, although who knows what the sensor accuracy is.

Exactly my thought.