Tag Archives: Biohacking

Quantifying Biological Age: Blood Test #6 in 2022

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The Excel file to calculate Levine’s Biological Age is embedded in this link from my website:
https://michaellustgarten.com/2019/09/09/quantifying-biological-age/

Breaths Per Minute While Asleep: What’s Optimal?

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Papers referenced in the video:
Mean nocturnal respiratory rate predicts cardiovascular and allcause mortality in community-dwelling older men and women
https://pubmed.ncbi.nlm.nih.gov/31151958/

Measurement of respiratory rate using wearable devices and applications to COVID-19 detection
https://pubmed.ncbi.nlm.nih.gov/34526602/

Improve Lung Function, Reduce Blood Pressure, Slow Brain Aging?

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Papers referenced in the video:
Biological aging of human body and brain systems (preprint)
https://www.medrxiv.org/content/10.1101/2022.09.03.22279337v1.full.pdf

A Physiology Clock for Human Aging (preprint)
https://www.biorxiv.org/content/10.1101/2022.04.14.488358v1.full

Spirometry Reference Equations for Central European Populations from School Age to Old Age https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0052619

An Integrated, Multimodal, Digital Health Solution for Chronic Obstructive Pulmonary Disease: Prospective Observational Pilot Study
https://pubmed.ncbi.nlm.nih.gov/35142291/

Influence of Inspiratory Muscle Training of Various Intensities on the Physical Performance of Long-Distance Runners
https://pubmed.ncbi.nlm.nih.gov/33312301/

Time-efficient, high-resistance inspiratory muscle strength training for
cardiovascular aging
https://pubmed.ncbi.nlm.nih.gov/34389471/

Optimal Blood Pressure Keeps Our Brains Younger
https://pubmed.ncbi.nlm.nih.gov/34675795/

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716867/

DHEA-S Is A Weakness In My Data: Blood Test #5 in 2022

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Papers referenced in the video:
Total cholesterol and all-cause mortality by sex and age: a prospective cohort study among 12.8 million adults
https://pubmed.ncbi.nlm.nih.gov/30733566/

The Value of Serum Albumin and High-Density Lipoprotein Cholesterol in Defining Mortality Risk in Older Persons with Low Serum Cholesterol
https://pubmed.ncbi.nlm.nih.gov/11559371/

Reference intervals of nine steroid hormones over the life-span analyzed by LC-MS/MS: Effect of age, gender, puberty, and oral contraceptives
https://pubmed.ncbi.nlm.nih.gov/31201927/

Incomplete Pattern of Steroidogenic Protein Expression in Functioning Adrenocortical Carcinomas
https://pubmed.ncbi.nlm.nih.gov/32751564/

Serum dehydroepiandrosterone sulfate levels predict longevity in men: 27-year follow up study in a community based cohort (Tanushimaru study)
https://pubmed.ncbi.nlm.nih.gov/18422949/

Quantifying Biological Age: Blood Test #5 in 2022

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TruDiagnostic Discount Link (Epigenetic Testing)
CONQUERAGING!

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https://www.bmq30trk.com/4FL3LK/GTSC3/

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Papers referenced in the video:
A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study
https://pubmed.ncbi.nlm.nih.gov/30596641/

Underlying features of epigenetic aging clocks in vivo and in vitro
https://pubmed.ncbi.nlm.nih.gov/32930491/

Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants
https://pubmed.ncbi.nlm.nih.gov/33684206/

Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations
https://pubmed.ncbi.nlm.nih.gov/29340580/

The Excel file to calculate Levine’s Biological Age is embedded in this link from my website:
https://michaellustgarten.com/2019/09/09/quantifying-biological-age/

Biohacking the Oral Microbiome

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Bristle Discount Link:
ConquerAging15
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Papers referenced in the video:
Interconnections Between the Oral and Gut Microbiomes: Reversal of Microbial Dysbiosis and the Balance Between Systemic Health and Disease https://pubmed.ncbi.nlm.nih.gov/33652903/

A Brief Introduction to Oral Diseases: Caries, Periodontal Disease, and Oral Cancer
https://tinyurl.com/z45d6djt

Xylitol, mutans streptococci, and dental plaque
https://pubmed.ncbi.nlm.nih.gov/19717413/

Growth Inhibition of Streptococcus mutans with Low Xylitol Concentrations
https://pubmed.ncbi.nlm.nih.gov/18176823/

The antimicrobial activity of essential oils and essential oil components towards oral bacteria https://pubmed.ncbi.nlm.nih.gov/7478759/

Nitrate as a potential prebiotic for the oral microbiome
https://pubmed.ncbi.nlm.nih.gov/32732931/

A Physiology Clock for Human Aging: BP and FEV1 As Top Predictors

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Papers referenced in the video:

A Physiology Clock for Human Aging (preprint) https://www.biorxiv.org/content/10.1101/2022.04.14.488358v1

Spirometry Reference Equations for Central European Populations from School Age to Old Age https://pubmed.ncbi.nlm.nih.gov/23320075/

An Integrated, Multimodal, Digital Health Solution for Chronic Obstructive Pulmonary Disease: Prospective Observational Pilot Study https://pubmed.ncbi.nlm.nih.gov/35142291/

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716867/

Methionine Restriction Extends Lifespan-What’s Optimal For Protein Intake? n=1 Analysis

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Papers referenced in the video:

Life-Span Extension in Mice by Preweaning Food Restriction and by Methionine Restriction in Middle Age https://pubmed.ncbi.nlm.nih.gov/19414512/

Low methionine ingestion by rats extends life span https://pubmed.ncbi.nlm.nih.gov/8429371/

Fasting glucose level and all-cause or cause-specific mortality in Korean adults: a nationwide cohort study https://pubmed.ncbi.nlm.nih.gov/32623847/

Total plasma homocysteine and cardiovascular risk profile. The Hordaland Homocysteine Study https://pubmed.ncbi.nlm.nih.gov/7474221/

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716867/

Association between low-density lipoprotein cholesterol and cardiovascular mortality in statin non-users: a prospective cohort study in 14.9 million Korean adults https://pubmed.ncbi.nlm.nih.gov/35218344/

Blood counts in adult and elderly individuals: defining the norms over eight decades of life https://pubmed.ncbi.nlm.nih.gov/32030733/

How Much Oxalate Is Too Much? n=1 Analysis

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Papers referenced in the video:

Dietary oxalate to calcium ratio and incident cardiovascular events: a 10-year follow-up among an Asian population https://pubmed.ncbi.nlm.nih.gov/35346210/

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716867/

Association between low-density lipoprotein cholesterol and cardiovascular mortality in statin non-users: a prospective cohort study in 14.9 million Korean adults https://pubmed.ncbi.nlm.nih.gov/35218344/

Joint distribution of lipoprotein cholesterol classes. The Framingham study) AND abbott lipoproteins 1983 https://pubmed.ncbi.nlm.nih.gov/6573877/

Incidental lymphopenia and mortality: a prospective cohort study https://pubmed.ncbi.nlm.nih.gov/31932337/

Blood counts in adult and elderly individuals: defining the norms over eight decades of life https://pubmed.ncbi.nlm.nih.gov/32030733/

Effect of Aging on Serum Uric Acid Levels: Longitudinal Changes in a Large Japanese Population Group https://pubmed.ncbi.nlm.nih.gov/12242321/

Liver enzymes and risk of all-cause mortality in general populations: a systematic review and meta-analysis. https://pubmed.ncbi.nlm.nih.gov/24585856/

Increased red blood cell distribution width (RDW) is associated with higher glycosylated hemoglobin (HbA1c) in the elderly https://pubmed.ncbi.nlm.nih.gov/25651746/