Evidence map›Paper›PMID 21437087›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2010

Type 2 diabetes mellitus and inflammation: Prospects for biomarkers of risk and nutritional intervention.

Alaa Badawi, Amira Klip, Pierre Haddad, David Ec Cole, Bibiana Garcia Bailo, Ahmed El-Sohemy, Mohamed Karmali

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06377358 (Lipolysis of Visceral Reserve Fat Using Tecar Therapy), which is not on this map. Cited by 99 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 2 pooled it
7.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06377358 nacompletednot on this mapstarted 2022, after this paper: background citation

Lipolysis of Visceral Reserve Fat Using Tecar Therapy: Anthropometric, Biochemical and NMR Imaging Study.

TypeinterventionalSponsorCAPENERGY MEDICAL, SLRan2022 to 2023Enrolled20ConditionsObesity, Visceral, Obesity, EndocrineArmsTecar Therapy
3 · Its place in the literature

Who cites it

99 citing papers in PubMed, 2 syntheses or guidelines pooled it, 178 citations in OpenAlex.

  1. Pooled it
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  11. Deep Learning-Based Adrenal Gland Volumetry for the Prediction of Diabetes.Endocrinology and metabolism (Seoul, Korea) · 2025
    Observational
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39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Alaa BadawiOffice for Biotechnology, Genomics and Population Health, Public Health Agency of Canada, Toronto, ON, Canada.
Amira Klip
Pierre Haddad
David Ec Cole
Bibiana Garcia Bailo
Ahmed El-Sohemy
Mohamed Karmali
Public Health Agency of Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is a major risk factor for type 2 diabetes mellitus (T2DM), which is a significant health problem worldwide. Active disease is associated with low-grade chronic inflammation resulting in part from the activation of the innate immune system. In obesity, this activation leads to the release of pro-inflammatory cytokines such as tumor necrosis factor-α, interleukin-1β and interleukin-6 that block major anabolic cascades downstream of insulin signaling and thus disrupt insulin homeostasis and action. Cytokines also trigger the production of acute-phase reactants such as C-reactive protein, plasminogen activator inhibitor-1, serum amyloid-A, and haptoglobin. The elevated synthesis of pro-inflammatory cytokines and acute-phase proteins (inflammatory network) characterizes the early (or pre-clinical) stages of T2DM and exhibits a graded increase with the disease progression. Current evidence suggests that understanding inflammatory networks can point to new biomarkers that may permit capturing the interaction between genetic and environmental risk factors in the pathogenesis of T2DM. Such biomarkers have a significant public health potential in the prediction of disease occurrence beyond risk factors presently monitored, such as family history, lifestyle assessment and standard clinical chemistry profiles. Furthermore, inflammatory markers may assist in the evaluation of novel strategies for prevention, particularly in relation to micronutrients. This review discusses the current knowledge linking T2DM risk to inflammatory signaling pathways interacting with the innate immunity system and the prospect of inflammatory markers serving as molecular targets for prevention and/or biomarkers for early risk prediction of T2DM. The potential of micronutrients replenishment to improve insulin action by attenuating inflammation is also evaluated in the context of the public health relevance of this approach.

Indexed as

biomarkersinflammationpreventiontype 2 diabetes

Identifiers

PMID21437087
PMCPMC3047967
OpenAlexW2023863507

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.