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Record W2121265058 · doi:10.1139/apnm-2014-0434

Monosodium <scp>l</scp>-glutamate and dietary fat exert opposite effects on the proximal and distal intestinal health in growing pigs

2014· article· en· W2121265058 on OpenAlexvenueno aff
Zemeng Feng, Tiejun Li, Chunli Wu, Lihua Tao, François Blachier, Yulong Yin

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2014
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsnot available
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsMonosodium glutamateFood scienceGlutamate receptorEndocrinologyChemistryInternal medicineMedicineBiology

Abstract

fetched live from OpenAlex

The Chinese population has undergone rapid transition to a high-fat diet. Furthermore, monosodium L-glutamate (MSG) is widely used as a flavour enhancer in China. Previous studies have reported that high-fat diet modifies intestinal metabolism and physiology. However, little information is available on the effects of oral MSG on intestine, and no study focus on the interaction of dietary fat and MSG for intestinal health. The aim of the present study was to evaluate the effects of MSG and dietary fat on intestinal health in growing pigs, and to try to identify possible interactions between these 2 nutrients for such effects. A total of 32 growing pigs were used and fed with 4 isonitrogenous and isocaloric diets (basal diet, high-fat diet, basal diet with 3% MSG and high fat diet with 3% MSG). Parameters related to reactive oxygen species metabolism, epithelial morphology, pro-inflammation factors and tight junction protein expression and several species of intestinal microbe were measured. Overall, dietary fat and MSG had detrimental effects on several of the physiological and inflammatory parameters measured in the proximal intestine, while exerting beneficial effects on the distal intestine in growing pigs, with generally antagonistic effects. These results may be of particular relevance for nutritional concerns in patients with intestinal diseases.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.585

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 head0.010
GPT teacher head0.235
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

Citations31
Published2014
Admission routes1
Has abstractyes

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