Evidence map›Paper›PMID 14525620›Full record

ArticleCardiovascular diabetology2003

Cardiovascular diabetology in the core of a novel interleukins classification: the bad, the good and the aloof.

Enrique Z Fisman, Michael Motro, Alexander Tenenbaum

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.2field-weighted citation impact, top 13% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 55 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Enrique Z FismanCardiac Rehabilitation Institute, Sheba Medical Center, 52621 Tel-Hashomer, Israel. zfisman@post.tau.ac.il
Michael Motro
Alexander Tenenbaum
Tel Aviv University · ILSheba Medical Center · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe impressive correlation between cardiovascular disease and glucose metabolism alterations has raised the likelihood that atherosclerosis and type 2 diabetes may share common antecedents. Inflammation is emerging as a conceivable etiologic mechanism for both. Interleukins are regulatory proteins with ability to accelerate or inhibit inflammatory processes. PRESENTATION OF THE HYPOTHESIS: A novel interleukins classification is described, based on their role in diabetes and atherosclerosis, hypothesizing that each interleukin (IL) acts on both diseases in the same direction--regardless if harmful, favorable or neutral. TESTING THE HYPOTHESIS: The 29 known interleukins were clustered into three groups: noxious (the "bad", 8 members), comprising IL-1, IL-2, IL-6, IL-7, IL-8, IL-15, IL-17 and IL-18; protective (the "good", 5 members), comprising IL-4, IL-10, IL-11, IL-12 and IL-13; and "aloof", comprising IL-5, IL-9, IL-14, IL-16 and IL-19 through IL-29 (15 members). Each group presented converging effects on both diseases. IL-3 was reluctant to clustering. IMPLICATIONS: These observations imply that 1) favorable effects of a given IL on either diabetes or atherosclerosis predicts similar effects on the other; 2) equally, harmful IL effects on one disease can be extrapolated to the other; and 3) absence of influence of a given IL on one of these diseases forecasts lack of effects on the other. These facts further support the unifying etiologic theory of both ailments, emphasizing the importance of a cardiovascular diabetologic approach to interleukins for future research. Pharmacologic targeting of these cytokines might provide an effective means to simultaneously control both atherosclerosis and diabetes.

Identifiers

PMID14525620
PMCPMC212422
OpenAlexW2123367498

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.