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Record W4389240050 · doi:10.1158/1538-7755.disp23-c024

Abstract C024: Room temperature stabilization of fecal samples supports important microbiome insights to expand access

2023· article· en· W4389240050 on OpenAlexaff
Savannah Colameco, Jean M. Macklaim, Ashlee G. Brown, Tara Crawford Parks

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsOutotec (Canada)
Fundersnot available
KeywordsReproducibilityFecesMicrobiomeColorectal cancerGut microbiomeHomogenization (climate)MedicineBiologyBioinformaticsChromatographyChemistryInternal medicineCancerEcology

Abstract

fetched live from OpenAlex

Abstract Analysis of microbial signatures associated with colorectal cancer has potential to improve access and adherence to cancer screening programs through non-invasive sampling, particularly in underserved communities. Lack of reproducibility between studies remains a challenge and has limited the ability to translate research findings into scalable clinical applications. The common practice of storing samples at -80°C/-112°F is inconvenient, often not feasible, and may introduce bias if samples are not handled carefully and consistently. Large-scale screening programs would benefit from room temperature stabilization and sample homogenization at the point of collection, without the logistical considerations for rapid and long-term freezing. To evaluate the potential of room temperature stability, fecal samples from adult and pediatric individuals were self-collected at home using the OMNIgene™•GUT Dx device with corresponding unstabilized samples stored at -80°C/-112°F. Metagenomics sequencing was utilized to generate microbiome profiles and identify taxa-associated biomarkers relevant to gastrointestinal health and aging. Stabilized samples were compared to freshly collected unstabilized samples (n=18) to evaluate any bias introduced by the stabilizing solution. The same stabilized samples were compared to unstabilized samples stored at -80°C/-112°F to evaluate stability over time. In addition, reproducibility was evaluated by performing DNA extractions in triplicate from ten stabilized fecal samples. Finally, the ability of the room temperature stabilization to capture expected differences between groups was evaluated by comparing adult and pediatric (n=30 per group) samples and looking for known signatures specific to each group. This research demonstrated equivalent stability over time between stabilized samples at room temperature and unstabilized samples stored at -80°C/-112°F, showing preservation of both highly abundant and rare members of the microbial community. Findings indicate that room temperature stabilization does not introduce bias relative to freshly collected unstabilized samples and produces sufficient sample homogenization to yield reproducible microbial profiles. The comparison between adult and pediatric stabilized fecal samples highlights an enrichment for pediatric-specific signatures, such as Bifidobacterium and Veillonella species, and further captures the lower diversity of pediatric samples relative to more developed adult microbiota. These results demonstrate that the OMNIgene™•GUT Dx device enables the preservation of microbial community structure with room temperature stabilization and sample homogenization for use in the detection of biomarkers in fecal samples. Simple logistics of room temperature storage, combined with an easy-to-use self-collection design and compatibility with standard postal shipping assist integration into clinical workflows and enable at-home collections from diverse populations, especially at-risk, minority populations without easy access to clinical services. Citation Format: Savannah Colameco, Jean M. Macklaim, Ashlee Brown, Tara Crawford Parks. Room temperature stabilization of fecal samples supports important microbiome insights to expand access [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C024.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.390
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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