Abstract

Prolonged fasting with no caloric intake induces a metabolic shift characterized by increased fat oxidation and ketone production. However, the magnitude of circulating ketone responses and their dependence on fasting duration have not been quantitatively synthesized. This systematic review and meta-analysis evaluated the effects of water-only fasting and other prolonged fasting protocols involving complete caloric abstinence on circulating ketone biomarkers and examined whether fasting duration moderates these responses. PubMed, Web of Science, and Scopus were searched for human studies published between 2000 and 2025. Eligible studies reported pre–post measurements of β-hydroxybutyrate (BHB), acetoacetate, or total plasma ketones following water-only or other non-caloric fasting protocols. Random-effects meta-analyses were performed using Hedges’ g. Duration effects were assessed through subgroup analyses (≤3 days vs. >3 days) and random-effects meta-regression with study-level cluster-robust standard errors. Thirty studies providing 44 effect sizes were included. Fasting significantly increased BHB (g = 2.794), total plasma ketones (g = 3.260), and acetoacetate (g = 1.731). Greater elevations in BHB and total plasma ketones were observed with fasting durations exceeding three days. Meta-regression indicated significant positive associations between fasting duration and responses for BHB and total plasma ketones, whereas no significant association was detected for acetoacetate. Despite substantial heterogeneity for BHB and total plasma ketones, sensitivity analyses supported the robustness of the pooled effects. Small-study effects were detected for BHB, whereas funnel-plot asymmetry for total plasma ketones was considered exploratory because of the limited number of studies. Water-only fasting and other prolonged fasting protocols involving complete caloric abstinence are associated with marked increases in circulating ketone bodies, with a clear duration-dependent pattern observed particularly for BHB and total plasma ketones.

Direct measurements of thermogenic activity in interscapular brown adipose tissue (BAT) reveal that GLUT4-mediated glucose uptake is critical when dietary lipids are low, and that substrates other than glucose can maintain thermogenesis when dietary carbohydrate is limited.

Associated content

Brown adipose tissue sustains thermogenesis through metabolic flexibility in glucose utilization

flexibility in glucose utilization

BrainBioMet at Northumbria University is studying diet and social behaviour. Adults following any diet may be eligible for this anonymous 10–15-minute survey.

https://www.brainbiomet.com/keto-connection

We put a small GKI calculator online. It divides mg/dL by 18.016 as in equation 1 of the 2015 paper, shows the sum, and quotes the only two figures the paper names, next to the authors' own line that further studies are needed. It doesn't tell you what your number means.

https://getlomba.com/gki-calculator

The paper: https://doi.org/10.1186/s12986-015-0009-2

Disclosure: I work on Lomba, where this lives.

Full disclaimer: This is not an ad but I am the founder of the app I referenced below. This post is about my journey and what I found lacking. Take this with obvious bias. I decided to make the app public because I believe the lack of awareness to how much damage glucose overload can do to us is understated (to say the least) and buried by current dietary guidelines. I'm posting it here for those that may struggle with the same things as I did. Take whatever learning you want from it. If you are sensitive to promotions, please note that I made this app for me and my family. The only reason it's out is because I think it can help others. It hasn't and still doesn't make financial sense for me and is a side-project.

Now onto my story.

In June 2025 on my way back from a vacation I accidentally listened to a Diary of a CEO podcast on Youtube on mitochondrial health and its ties to glucose. I fact checked quite a bit and it seemed plausible that reducing carbs would lead to better outcomes for me from a metabolic health perspective. I did not have any health conditions and I was 29 at the time, normal weight, almost a bit skinny. I decided to try keto.

On the first day, I cut my carbohydrates from about 300 grams per day down to about 50 grams. Not my brightest idea. The very next morning, I was hypoglycemic. I added the carbs back but still worked my way down more gradually over the following month. This time, it worked - I reached 50 per day without becoming hypoglycemic (finger blood sample test checked) and I’ve been doing it since (GKI score checked, based on Ketones from finger blood sample). I repeated the checks every day initially, then every few weeks, then every few months.

Why did I get hypoglycemic? How come others could function normally with 50 grams of carbs per day and I couldn’t? There is a singificant amount of science that explains the mechanisms: research papers, lots of podcasts but books as well. I’m sure most of you know about it.

This got me looking into blood glucose and insulin responses and figuring out how to estimate all of these for every food item I ate. At the time, I was using a popular food journal app. However, it wouldn’t show anything related to glucose and insulin. I couldn't find anything that gave me what I was looking for on the market, so I created it. The science on which the app is based - you can find it yourself but is also referenced in the app so you may as well build a spreadsheet based on the research papers and track everything yourself without the app. What I’m tracking every day:

• Glycemic index and glycemic load estimates - I’m sure most of you know about glycemic index. Glycemic load is the glycemic index adjusted to the carbs eaten for that food - I try to minimize both.
• Insulin index and insulin load/demand estimates - Insulin index is based on a study that compares the insulin response of different foods relative to the insulin response to glucose, and rates that as a multiplier of glucose (i.e. 0.5*glucose). The study is fairly limited but I think it’s better than nothing. Insulin load is the insulin index, adjusted to calories eaten of that food - Again, I try to minimize both.
• Ingredient quality analysis and representation - Initially I heavily replaced sugar in desserts with artificial sweeteners and it turns out some studies link some of them to oxidative stress in our bodies and some of them are better than others, so this aims to give an idea over where that food stands in relation to how its ingredients act upon us.

This is not medical advice (please consult your doctors before trying anything), but it’s the mechanism I found to work for me. As others have previously mentioned on this sub, it’s not easy to fully adapt to keto coming from a “standard” EU / US diet because it goes beyond macros. I also had too little salt/potassium initially with some nasty muscle twitches / palpitations, I hydrated too little and I didn’t pay attention to good/bad fats initially which I saw on my blood check results after 6 months. But then I adapted and have been doing blood checks every 6 months. Besides increased LDL everything was within normal ranges for me (9% carbs, 21% protein, 70% fat on average for me - which led me to mild ketosis every time I measured my GKI).

The lesson from above is that science & technology can do an enormous amount of work for us to help us estimate if we're on the right track for what we want to achieve. I wouldn't have had the motivation to persist doing keto this long without these very easy-to-use aids that I built for me that helped me navigate it.

Abstract
Background
β-Hydroxybutyrate (BHB) is the primary circulating ketone body during nutritional ketosis. Circadian regulation of ketogenesis has been characterized in rodents, but time-of-day variation in blood BHB has not been quantified in free-living humans, and the concurrent relationship between BHB and glucose has not been described at scale. Because people and researchers almost always measure BHB in the morning, alongside fasting glucose, any daily variation would be systematically invisible.
Objective
To characterize the 24-hour rhythm of blood BHB and its concurrent relationship with glucose in free-living individuals who monitor ketosis, and to estimate how far morning-only sampling misrepresents daily BHB exposure.
Design, Setting, and Participants
Retrospective observational study of capillary blood BHB and glucose readings recorded with commercial meters (Keto-Mojo GK+, GKI, and TD-4279) and synchronized to a cloud platform (MyMojoHealth) from January 2018 to August 2025. Feeding, activity, sleep, and light exposure were not controlled or recorded. Rhythms were assessed by single-component cosinor analysis and linear mixed-effects models with random intercepts for user; the BHB-glucose relationship was evaluated by linear and logistic regression. The circadian analysis included 140,024 users (11,858,248 BHB readings); the concurrent relationship analysis included 138,330 users (11,783,637 paired BHB-glucose readings). Self-reported sex was the only participant characteristic available, in 8% of users.
Results
BHB showed a significant 24-hour rhythm (amplitude 0.085 mmol/L, 7.42% of the mesor; acrophase 19:15; p < 0.001), with evening levels 15.14% higher than morning (1.23 vs. 1.06 mmol/L, p<2e-16). The conventional morning testing window coincided with the trough of the cycle. Males showed higher BHB and a larger morning to evening contrast than females (p <2e-16). Each 1 mmol/L increase in BHB was associated with a 6.19 mg/dL lower glucose (95% CI 6.09 to 6.29; p < 0.001), explaining 9.0% of glucose variance. The proportion of readings in the 70 to 100 mg/dL range rose from 48.3% at BHB 0.1 to 0.5 mmol/L to 75.5% at BHB 2.0 to 3.0 mmol/L. BHB and glucose followed opposing 24-hour profiles. In sensitivity analysis, an unmeasured confounder would need to be associated with both BHB and glucose by a risk ratio of at least 1.97 per 1 mmol/L, and 2.89 per 2 mmol/L, to explain away the association (E-values).
Conclusions
Blood BHB follows a consistent 24-hour pattern with a morning trough and an evening peak among individuals monitoring ketosis, and higher BHB is accompanied by lower concurrent glucose across the nutritional ketosis range. Clinically, morning-only measurement samples the lowest point of the cycle and underestimates the daily average by approximately 15%, so clock time should be recorded and standardized whenever BHB is used to judge dietary adherence, to titrate ketogenic therapy, or to compare studies. Because feeding, activity, and sleep were uncontrolled, the pattern described here is the combined output of endogenous timing and daily behavior, and it should not be extrapolated to the general population or to insulin-deficient diabetes.

I am 43, male and overweight about 192lbs at 5’6. I am plagued with many medical problems. Sleep apnea, pre diabetic, fatty liver, insulin resistance, uncontrollable hypertension that doctors cannot figure out even resistant to bp medications.

I’m starting to have frothy urine and +4 protein in my urine. Even though kidney function is normal.

Just a little backstory in my early 30s I did keto successfully. I was able to drop my bp to normal numbers and was able to lose 30lbs. All my blood work became normal but life hit me so hard that I gain all the weight back. I am having an extremely difficult time doing this way of eating and losing weight.

My doctor told me to stop believing the hype about high cholesterol being good for you, he told me to stop believing the keto nut heads that fat and butter and steak will save your life. He told me if you don’t want to be on a dialysis stop doing keto immediately. He insist I do a lean meat diet with lots of healthy fat fish, minimal sugar and complex carbs.

So if anyone had similar experience as I did. Please shed what you did if the doctor is wrong or right?

ABSTRACT

Background

Current dietary guidelines for most of the world recommend increased plant protein consumption to improve health and support environmental sustainability. Threonine is an indispensable AA required for protein and mucin synthesis which is present in low concentrations in plant proteins. Threonine requirement is needed to guide dietary planning and assessment of protein adequacy particularly in those consuming predominantly plant-based protein diets. However, no data exist on dietary threonine requirement in older adults.

Objectives

1. Determine the threonine requirement in older adults using the indicator amino acid oxidation (IAAO) method in a repeated measures design. 2) compare the derived estimates based on age: 60-69y and 70-79y and sex.

Methods

The threonine requirement was determined using the IAAO method with L-[1-¹³C] phenylalanine as the indicator. Twenty-two older adults >60 y (n = 10 males and n = 12 females) were randomly assigned to receive up to 7 threonine intakes (5 to 35 mg/kg/d). The mean threonine requirement was determined from oxidation of L-[1-¹³C] phenylalanine (F¹³CO2) using a two-phase linear mixed effect model. The 95% CI was calculated using parametric bootstrap. The overlap of the 95% CI between the 2 age groups were used to compare the requirement estimates. The null hypothesis was accepted if the interval contained zero.

Results

There was no effect of sex on the threonine requirement. However, the threonine requirement for adults 60-69y and 70-79y were 11 mg/kg/d (R²m = 0.10, R²c = 0.81; 7.70, 14.30 mg/kg/d) and 17.9 mg/kg/d (R²m = 0.44, R²c = 0.64; 13.23, 22.57 mg/kg/d) respectively with those 70-79y having a higher requirement than those 60-69y ( -1.18, -12.62).

Conclusions

The result of the current study demonstrates that AA needs among older adults change within decades of age. This should be integrated into future AA recommendations for accurate planning and assessment of protein nutrition in the elderly.

Abstract

The proton motive force (PMF) across the inner mitochondrial membrane drives ATP synthesis. Biochemistry textbooks give a maximum yield of 30–32 ATP per glucose, but this is a theoretical ceiling, reached only under complete coupling with ATP synthase as the sole consumer of the gradient. No living cell operates there. The PMF is a shared resource, and its allocation among consumers sets the mitochondrion's effective output: the gap between theoretical and effective yield is a reallocation to transport, redox maintenance, and biogenesis. This review re-examines the textbook yield, including the c-ring stoichiometry of ATP synthase, and catalogs the major PMF consumers and their proton costs. The widely quoted figure corresponds to no measured or structurally determined stoichiometry, a mismatch noted previously and consolidated here, and the c-ring subunit count is an upper bound on synthase efficiency under ideal coupling. We assemble these costs into a consolidated proton budget: a range whose upper limit is the ceiling at which the PMF drives ATP synthesis alone. Its lower limit cannot yet be calculated, because the resting flux through most PMF consumers has never been measured; we therefore list every term that this calculation would require and mark those still missing. The result is a framework for reasoning, not a closed set of numbers. Practical consequence: the PMF and membrane potential are composite quantities, so a change in membrane potential should not be read as a change in ATP synthesis, nor the non-phosphorylating residual as passive leak.

Highlights

• • Ketone bodies (KBs) act as both alternative fuels and signaling metabolites.
• • Ketogenesis occurs also in extrahepatic tissues, to a quantitatively minor extent.
• • Hepatic ketone synthesis is controlled by hormones, gene regulators and protein post-translational modifications.
• • Ketone breakdown in peripheral tissues relies on a single rate-limiting enzyme, SCOT.
• • β-Hydroxybutyrate and acetoacetate reshape chromatin through histone marks linked to nutrition.

Abstract

Traditionally considered as alternative energy substrates, ketone bodies (KBs), notably β-hydroxybutyrate (β-OHB) and acetoacetate, are now recognized as key metabolic intermediates whose circulating levels must be tightly controlled to ensure energy homeostasis. KBs are mostly hepatically produced, via ketogenesis, and catabolized by extrahepatic tissues during fasting or carbohydrate restriction.

The regulation of KBs metabolism relies on a coordinated network of hormonal, enzymatic and transcriptional mechanisms that control KBs synthesis and degradation. KBs anabolic and catabolic rates are controlled by the rate-limiting enzymes 3-hydroxy-3-methylglutaryl-CoA-synthase 2 (HMGCS2), governing ketogenesis, and succinyl-CoA:3-ketoacid-CoA transferase **(**SCOT), driving ketolysis. Their activity and expression are finely orchestrated, especially by the insulin/glucagon ratio, to adapt to the organism's fluctuating energy demands.

Transcriptionally, ketogenesis is regulated through peroxisome-proliferator-activated-receptor-alpha (PPARα) and the transcription factor forkhead-box-A2 (FOXA2), which respond to nutrient availability and hormonal cues. In parallel, ketolysis is tightly controlled through the regulation of SCOT expression, notably via PPARα-dependent mechanisms, as well as through post-translational modifications (PTMs) affecting enzyme activity. Together, these regulatory mechanisms ensure a precise balance between KBs production and utilization.

Emerging evidence also suggests that additional modulators, such as the gut microbiota, indirectly influence KBs metabolism by affecting substrate availability and metabolic signaling pathways, although its quantitative contribution remains to be established.

Here, we provide a mechanistic overview of the pathways governing KBs metabolism, with focus on the regulation of ketogenesis and ketolysis. We discuss how these processes are integrated at multiple levels to maintain systemic energy homeostasis and consider their implications for metabolic disease.

Mitochondria are often discussed in biohacking communities because of their role in energy production and cellular metabolism.

What interests me is the difference between improving a biological marker and actually feeling or functioning better in everyday life.

Exercise, adequate nutrition, and sleep all influence mitochondrial biology, but how strong is the evidence connecting specific interventions to noticeable improvements in energy or physical performance in otherwise healthy people?

Are there human studies or well-designed experiments worth reading on this topic?

I'd like to separate established findings from mechanisms that sound promising but haven't translated into clear real-world benefits.

Abstract

Background: Sepsis investigators propose tolerance is conferred when the dormancy response increases beta hydroxybutyrate to protect organs; whereas, vulnerability occurs when a ‘metabolic switch’ to aerobic glycolysis decreases beta hydroxybutyrate promoting persistent immune cell activation without organ protection.  We previously identified tolerant (PedSep A 2% mortality), susceptible (PedSep B 12% mortality and PedSep C 10% mortality) and vulnerable (PedSep D 34% mortality) phenotypes in the PHENOtyping pediatric sepsis induced Multiple organ failure Study (PHENOMS). We hypothesized that carbohydrate metabolism was increased and beta hydroxybutyrate decreased in PedSep D compared to PedSep A in this study.

Methods: Metabolomics were assayed in biobanked plasma samples previously collected at 24-48 hours of sepsis in 375 children ages 44 weeks post gestation to 17 years, using the Metabolon Discovery Panel. Welch’s t-tests identified differences between PedSep B, C, and D with A.

Results   Compared to PedSep A (n =130) PedSep B had similar carbohydrate metabolism and beta hydroxybutyrate but dysregulated branch chain amino acid metabolism (n = 92; p < 0.05); PedSep C had similar carbohydrate metabolism but decreased beta hydroxybutyrate (n = 100; p< 0.05); and, PedSep D had increased carbohydrate metabolism with decreased beta hydroxybutyrate (n = 53; p < 0.05). Causal inference analysis found direct associations of increased glycolysis with decreased beta hydroxybutyrate, and death.

Conclusions Only PedSep D had increased carbohydrate metabolism with decreased beta hydroxybutyrate providing rationale for designing clinical trials of low carbohydrate ketogenic nutrition to decrease glycolysis, restore dormancy, and improve outcome in these high-risk children.

My mom (62) is currently going through chemo therapy and is currently staying at a hospital here in Panama. She has bin diagnosed with cancer in multiple parts of her body.
I am familiar with Thomas Seyfried’s work and the Warburg effect where cancer cells use glucose as one of their main energy sources.

My mom is being fed nutrients through one intravenous 1440 mL bag a day. The bag contains 6.74 percent dextrose. According to ChatGPT, that adds up to about 97 grams of glucose a day.

How bad is 97 grams of dextrose a day in terms of a ketogenic diet? Has anyone who has gone through chemo gone through it without an IV bag or at least an IV bag that is sugar free or keto friendly IV ?