Evidence map›Paper›PMID 42201874›Full record

ArticlePloS one2026

Modeling the microbial contribution to human energy balance using the Digestion, Absorption, and Microbial Metabolism (DAMM) model.

Taylor L Davis, Blake Dirks, Elvis A Carnero, Karen D Corbin, Steven R Smith, Andrew Marcus, Rosa Krajmalnik-Brown, Bruce E Rittmann

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Taylor L DavisBiodesign Center for Health through Microbiomes, Arizona State University, Tempe, Arizona, United States of America.ORCID https://orcid.org/0000-0003-4414-0905
Blake DirksBiodesign Center for Health through Microbiomes, Arizona State University, Tempe, Arizona, United States of America.
Elvis A CarneroAdventHealth Translational Research Institute, Orlando, Florida, United States of America.
Karen D CorbinAdventHealth Translational Research Institute, Orlando, Florida, United States of America.ORCID https://orcid.org/0000-0003-2065-0003
Steven R SmithAdventHealth Translational Research Institute, Orlando, Florida, United States of America.
Andrew MarcusGreat Lakes Water Authority, Detroit, Michigan, United States of America.ORCID https://orcid.org/0000-0003-3442-6088
Rosa Krajmalnik-BrownBiodesign Center for Health through Microbiomes, Arizona State University, Tempe, Arizona, United States of America.ORCID https://orcid.org/0000-0001-6064-3524
Bruce E RittmannBiodesign Swette Center for Environmental Biotechnology, Arizona State University, Tempe, Arizona, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colonic microorganisms have been linked to human health and disease, specifically metabolic disease states such as obesity, but causal relationships remain to be established. Previous work demonstrated that interactions between the host's diet and intestinal microbiome were associated with human energy balance by affecting the human's energy absorption, quantified by metabolizable energy. We developed the Digestion, Absorption and Microbial Metabolism (DAMM) model, which explicitly accounts for the energy contributions of the colonic microbial community in five steps. 1) The DAMM model breaks down the diet composition into the gross energy of the individual macronutrients. 2) It calculates direct absorption in the upper gastrointestinal tract. 3) It uses microbial stoichiometry to estimate the consumption of the remaining unabsorbed nutrients by microbes in the large intestine. 4) It quantitatively predicts microbial production of short-chain fatty acids (SCFA) and methane in the colon. 5) The DAMM model estimates absorption from the colonic tract to the host, including SCFAs. When used to predict the results from a clinical study that compared two distinctly different diets, the DAMM model captured the directionality and magnitude of change in measured metabolizable chemical oxygen demand (which can be converted to metabolizable energy), estimated substrate availability within the colon, and predicted rate of production of microbially derived short-chain fatty acids. It improved on the accuracy of metabolizable chemical oxygen demand predictions compared to the Atwater factors, increasing the fit from R2 = 88% (Atwater) to R2 = 96% (DAMM). The model reduced systematic bias on one of the diets and decreased the mean difference between measurement and predictions from -22.3 gCOD d-1 to -2.5 gCOD d-1. The DAMM model now can be linked to existing human models that predict changes in body energy stores to extend our understanding of how microbial metabolic processes affect macronutrient absorption and metabolizable energy.

Indexed as

DigestionEnergy MetabolismGastrointestinal MicrobiomeModels, BiologicalColonDietFatty Acids, VolatileHumansIntestinal AbsorptionFatty Acids, Volatile

Identifiers

PMID42201874
PMCPMC13215556

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.