11 posts
A functional biomarker measures how well a system is working — a ratio, a rate, or a response to a challenge — rather than a single resting concentration. Here is how to build them from CGM, blood panels, proteomics, and RNA-seq, and where they break.
What fasting, post-meal, and 24-hour continuous glucose numbers look like in people without diabetes, what the reference data say, and how to analyze your own CGM export.
What post-meal glucose looks like in people without diabetes, where the 140 and 180 mg/dL thresholds come from, and a protocol for extracting real numbers from your own CGM export.
A continuous glucose monitor measures how you eat. It does not cause fat loss. What the data supports, and how to run your own meal experiments.
A practical account of continuous glucose monitor insertion, comfort, accuracy limits, and how to work with the exported data if you are not diabetic and want a metabolic baseline.
Why a post-meal glucose reading in the 80s is usually a healthy result, why you can feel shaky at that number anyway, and how to tell a real reading from sensor noise using your own CGM and lab data.
A practical guide to wearing a CGM without diabetes. Covers which sensors to buy, how accurate they are and what a normal glucose curve looks like.
What a post-meal glucose of 83, 87, or 94 mg/dL means, why the timing of the reading matters more than the number, and how to measure your own postprandial response properly with CGM and blood work.
A working method for turning a raw Libre or Dexcom export into an ambulatory glucose profile, per-meal response curves, and metrics you can defend — including what the numbers can and cannot tell you.
What the post-meal glucose numbers are for people without diabetes, where the thresholds come from, and how to compute peak, time-to-peak, and incremental AUC from your own CGM export.
A CGM measures the output of your glucose system. It does not measure the input. What a sensor can and cannot tell you about insulin sensitivity.