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Record W2081444082 · doi:10.1194/jlr.m021725

Lack of “immunological fitness” during fasting in metabolically challenged animals

2012· article· en· W2081444082 on OpenAlexaff
Ingrid Wernstedt Asterholm, John McDonald, Pierre-Gilles Blanchard, Madhur K. Sinha, Qiang Xiao, Jehangir Mistry, Joseph M. Rutkowski, Yves Deshaies, Rolf A. Brekken, Philipp E. Scherer

Bibliographic record

VenueJournal of Lipid Research · 2012
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversité Laval
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNovo Nordisk FondenNational Cancer InstituteNational Institutes of HealthVetenskapsrådetVINNOVAUniversity of Texas Southwestern Medical Center
KeywordsBiologyIntermittent fastingPhysiologyEndocrinology

Abstract

fetched live from OpenAlex

Obesity is associated with infi ltration of proinfl ammatory macrophages in adipose tissue and with a low-grade state of infl ammation as judged by systemic and tissue measurements of proinfl ammatory cytokines and acute-phase reactants ( 1 ). Numerous studies indicate that increased levels of free FAs (FFAs) are critical for the pathogenesis of the metabolic syndrome ( 2 ). For instance, palmitate can get channeled into increased biosynthesis of ceramides, which can cause insulin resistance, infl ammation, and apoptosis ( 3-5 ). Furthermore, intermediates of FFAs, through their conversion to triglycerides (lysophosphatidic acid, phosphatidic acid and diacylglycerol), can activate proinfl ammatory kinases ( 6 ). FFAs may also enhance infl ammation through binding and signaling through Toll-like receptor-4 (TLR4) ( 7 ). Thus, failure of adipose tissue to expand and/ or buffer excess FFAs may be the starting point for obesityand lipodystrophy-related metabolic disturbances. In obesity, as well as in critically ill patients, FFAs are chronically elevated and can induce a vicious proinfl ammatory cycle over the course of which adipocytes and macrophages further aggravate local and systemic infl ammation ( 8 ). In support of this hypothesis, intensive insulin treatment that inhibits lipolysis and hyperglycemia has been successful in the reduction of infl ammation and, more importantly, mortality of critically ill patients ( 9 ). In healthy individuals, lipolysis is effi ciently suppressed by insulin in the fed state. However, recent studies by Kosteli et al. ( This is also consistent with a central role for FFAs in metabolic infl ammation. In fact, the highest levels of FFAs in the system are found close to the site of release Abstract Subclinical infl ammation is frequently associated with obesity. Here, we aim to better defi ne the acute infl ammatory response during fasting. To do so, we analyzed representatives of immune-related proteins in circulation and in tissues as potential markers for adipose tissue infl ammation and modulation of the immune system. Lipopolysaccharide treatment or high-fat diet led to an increase in circulating serum amyloid (SAA) and 1-acid glycoprotein (AGP), whereas adipsin levels were reduced. Mouse models that are protected against diet-induced challenges, such as adiponectin-overexpressing animals or mice treated with PPAR agonists, displayed lower SAA levels and higher adipsin levels. An oral lipid gavage, as well as prolonged fasting, increased circulating SAA concurrent with the elevation of free FA levels. Moreover, prolonged fasting was associated with an increased number of Mac2-positive crown-like structures, an increased capillary permeability, and an increase in several M2-type macrophage markers in adipose tissue. This fasting-induced increase in SAA and M2-type macrophage markers was impaired in metabolically challenged animals. These data suggest that metabolic infl exibility is associated with a lack of "immunological fi tness." -Asterholm,

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.171
GPT teacher head0.421
Teacher spread0.250 · 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 designObservational
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

Citations46
Published2012
Admission routes1
Has abstractyes

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