Evidence map›Paper›PMID 19263074›Full record

ArticlePflugers Archiv : European journal of physiology2009

Green tea extract protects rats against myocardial infarction associated with left anterior descending coronary artery ligation.

Shih-Rong Hsieh, Dan-Chin Tsai, Jan-Yow Chen, Sen-Wei Tsai, Ying-Ming Liou

Abstract read
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In one paragraph

Article in Pflugers Archiv : European journal of physiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 25 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

5 authors at 2 institutions in 1 country.

Shih-Rong HsiehDepartment of Cardiovascular Surgery, Taichung Veterans General Hospital, Taichung, 407, Taiwan.
Dan-Chin Tsai
Jan-Yow Chen
Sen-Wei Tsai
Ying-Ming Liou
National Chung Hsing University · TWTaichung Veterans General Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is increasing evidence that green tea polyphenols can protect against myocardial damage. Recently, we showed that they bind to cardiac troponin C and alter myofilament Ca(2+) sensitivity in cardiac muscle. In the present study, we examined whether green tea extract (GTE) could prevent the progressive remodeling seen in ischemic myocardium and improve cardiac function by modulation of the contractile apparatus utilizing a myocardial infarction (MI) model in the rat involving ligation of the left anterior descending branch. Using this model, severe myocardial injury was found, including altered cardiac performance and the appearance of extensive fibrosis and left ventricular (LV) enlargement. Supplementation with 400 mg/kg/day of GTE for 4, 18, or 46 days had beneficial effects in preventing the hemodynamic changes. Histopathological studies showed that GTE attenuated the progressive remodeling seen after myocardial injury. Echocardiography confirmed that GTE prevented LV enlargement and improved LV performance in post-MI rats. In addition, we showed that GTE supplementation for 18 or 46 days increased the myofilament Ca(2+) sensitivity of the ischemic myocardium in post-MI rats. These results validate the novel action of green tea polyphenols in protecting against myocardial damage and enhancing cardiac contractility by modulating myofilament Ca(2+) sensitivity in post-MI rats.

Indexed as

AnimalsCamellia sinensisCoronary StenosisLigationMaleMyocardial ContractionMyocardial InfarctionPhytotherapyPlant ExtractsRatsRats, WistarTreatment OutcomePlant Extracts

Identifiers

PMID19263074
OpenAlexW2037088217

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.