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Record W3112748913 · doi:10.1097/mpa.0000000000001717

Delayed Processing of Secretin-Induced Pancreas Fluid Influences the Quality and Integrity of Proteins and Nucleic Acids

2020· article· en· W3112748913 on OpenAlexaff
Zobeida Cruz‐Monserrate, Kristyn Gumpper, Sabrina Kaul, Niharika Badi, Samantha Terhorst, Kelly Dubay, Gregory B. Lesinski, William Fisher, Amy L. McElhany, Luis F. Lara, Somashekar G. Krishna, Thomas A. Mace, Natalia Higuita‐Castro, Lilibeth Ortega‐Pineda, Michael A. Freitas, Alice Hinton, Dhiraj Yadav, Phil A. Hart, Stephen J. Pandol, Saima Ahmed, Benoit Fatou, Hanno Steen, Darwin L. Conwell

Bibliographic record

VenuePancreas · 2020
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsPancreas Centre (Canada)
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer Institute
KeywordsNucleic acidRNARNase PChemistryPancreatic juicePancreasNucleaseBiochemistryNucleic acid quantitationDNAMolecular biologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: Endoscopic pancreatic function tests are used to diagnose pancreatic diseases and are a viable source for the discovery of biomarkers to better characterize pancreatic disorders. However, pancreatic fluid (PF) contains active enzymes that degrade biomolecules. Therefore, we tested how preservation methods and time to storage influence the integrity and quality of proteins and nucleic acids. METHODS: We obtained PF from 9 subjects who underwent an endoscopic pancreatic function test. Samples were snap frozen at the time of collection; after 1, 2, and 4 hours on ice; or after storage overnight at 4°C with or without RNase or protease inhibitors (PIs). Electrophoresis and mass spectrometry analysis determined protein abundance and quality, whereas nucleic acid integrity values determined DNA and RNA degradation. RESULTS: Protein degradation increased after 4 hours on ice and DNA degradation after 2 hours on ice. Adding PIs delayed degradation. RNA was significantly degraded under all conditions compared with the snap frozen samples. Isolated RNA from PF-derived exosomes exhibited similar poor quality as RNA isolated from matched PF samples. CONCLUSIONS: Adding PIs immediately after collecting PF and processing the fluid within 4 hours of collection maintains the protein and nucleic acid integrity for use in downstream molecular analyses.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.266
Teacher spread0.225 · 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 teacher head, 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

Citations5
Published2020
Admission routes1
Has abstractyes

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