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Record W4401451954 · doi:10.29169/1927-5951.2024.14.02

Assessing the Efficacy of Natural Pet Products in Protecting Gastric Cells and Reducing Cytotoxicity under Hyperacidity Conditions: An In Vitro Study

2024· article· en· W4401451954 on OpenAlexvenueno aff
Nicolò Lonigro, Elisa Martello, Francesca Perondi, Mauro Bigliati, Z. R. Mohammed, Annalisa Costale, E. Rosso, Natascia Bruni

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsCytotoxicityIn vitroChemistryNatural (archaeology)PharmacologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Gastritis in pets necessitates effective acid suppression for successful treatment. However, the synergistic potential of antacid salts within natural feed products remains underexplored. In this in vitro study, we aimed to compare six supplements comprising natural ingredients for their ability to safeguard gastric cells and mitigate cytotoxicity under hyperacidity conditions. While Product 1 showed ineffectiveness in cell protection, Products 2, 3, 4, and 5 exhibited varying degrees of reversal of hyperacidity-induced cytotoxicity. Notably, Product 6 demonstrated superior efficacy in shielding gastric cells from acidic pH-induced cytotoxicity, displaying a dose-dependent response. These findings highlight the potential of natural supplements, particularly Product 6, as promising candidates for mitigating gastritis-related conditions in pets. Further research, including in vivo studies, is warranted to validate these observations and explore their clinical applicability.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.418
Teacher spread0.332 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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