HMN 2026: How Our body is doing fat-math (better than you’d imagine)

Remember seeing your triglyceride levels in your lab report? Ah! Fats you may dismiss, thinking of the next gym work you need to head to. Fatty acids are broken down via a process called ?-oxidation. But did you ever wonder if your body burns some fat before other fat, as if it has a mind of its own? It does. Here’s the thing: Your body isn’t being picky but efficiently picky. Mathly picky to be precise. Calculations that would impress a high school math teacher.

The oxygen economy

Let me set the scene. You’re exercising, you’re out of breath, your cells are busy trying to make ATP—that’s your body’s energy currency. But here’s the constraint: You’re running low on oxygen. And oxygen is always the limiting factor. Always.

So if you’re a cell in this situation, which fatty acid would you burn? Would you just grab whatever’s nearby and move on?

Nope. Your cells are way smarter than that.

What I observed using calculations, derivations, and examining thermodynamic aspects is that our body runs on what I call an “oxygen economy.” When oxygen is rate-limiting—which is basically all the time—our cells “preferentially” burn fatty acids that give them the most ATP per oxygen molecule consumed.

Note, I said preferentially, not randomly. This selective mobilization in white adipose tissues has been known for a long time but not fully explained, until probably now.

Think about it like choosing a car for a cross-country road trip where you can only stop for gas twice. You wouldn’t pick a gas guzzler, right? You’d optimize for fuel efficiency. Our cells do the same thing, except they’re optimizing for ATP per oxygen atom. I call this P:O_?-ox—fancy terminology for “bang for your oxygen buck.”

That “?-ox” represents the process through which fatty acids are broken down. The entire thing rests on the premise that mitochondrial efficiencies of P:O ratios are known. I went with classical assumptions of 3 and 2 for NADH⁺ H⁺ and FADH₂. But the model holds for any efficiency of phosphorylation.

The work has been published in the journal BBA Advances.

The mathematical sweet spot

When I started mapping this efficiency across different types of fatty acids—different chain lengths, different numbers of double bonds—patterns started emerging, cool ones that told something.

First off, the process, which can be represented by a general equation, follows the pattern of a rectangular hyperbola.

Values in decimals mattered. An efficiency ratio of 2.804 mattered over 2.823. How? Experimental data already show it.

Efficiencies plateau off at higher chain lengths. So, no use storing higher chain lengths even if they yield way more ATPs.

Interestingly, for a given chain length, if you increase the double bonds, efficiency actually increases, though ATP production is reduced slightly. The rate of increase again plateaued at higher chain lengths. This meant the curves had to intersect somewhere. And that point of intersection sits right around 1.6 double bonds. Surface plots reveal this beautifully.

Now, you can’t actually have 1.6 double bonds in a molecule. But here’s what it meant: That mathematical convergence tells us that fats with one or two double bonds offer optimal efficiency, regardless of how long the chain is.

And what dominates human fat tissues? Mono and di unsaturated fats—especially oleic acid, the same stuff in olive oil. One double bond. Right in the sweet spot. Even if newly determined mitochondrial efficiencies are taken into account, the coefficients in the equation, and hence the theoretical cross-over points, are the things that change. So instead of 1.6, it would be somewhere close by. What doesn’t change is the optimal chain length and double bonds for synthesis and burn.

This isn’t perchance. This is evolution optimizing your fat storage for oxygen-limited metabolism.

The odd-chain mystery

Here’s a quick detour. Ever heard of odd-chain fatty acids? They’re fatty acids with an odd number of carbons in their chain—15, 17, instead of the usual 16, 18. They exist in nature. We eat them. But they’re incredibly rare in our adipose tissue. Why?

The model answers: energetic penalty. When you break down an odd-chain fatty acid, you end up with propionyl-CoA instead of the usual acetyl-CoA. And propionyl-CoA is metabolically expensive to deal with. So, your body says, “Nope. Not storing that. Not worth the oxygen cost.” Odd-chain fatty acids are rare. Not random. Ruthlessly efficient.

It’s not passive—it’s strategic

For a long time, we thought of fat metabolism as straightforward: Eat fats, store them, burn them when needed. Supply and demand.

But my model suggests something way more. If there’s a mathematical pattern governing which fats get mobilized, and that pattern depends on oxygen and ATP levels, then there must be proteins actively sensing these things and making decisions in real time.

I call this the “oxygen- and ATP-sensitive regulatory axis.” Imagine proteins that work like smart thermostats, except instead of sensing temperature, they’re sensing oxygen availability and energy status. And instead of adjusting your heat, they’re flipping switches: “Burn this fat now” or “Save that one for later.”

We may have not identified these regulatory proteins yet. But when the math and biology line up this perfectly, nature has usually already figured it out. We just need to find it.

This story is part of Science X Dialog, where researchers can report findings from their published research articles. Visit this page for information about Science X Dialog and how to participate.

Natarajan Ganesan, Ph.D., is an Assistant Professor in the Department of Life Sciences at the New York Institute of Technology. His research bridges molecular biophysics, drug-DNA interactions, cancer genomics, metabolism, and computational biology.

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