Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% 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
2 citing papers in PubMed, 2 citations in OpenAlex.
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
16 authors at 4 institutions in 1 country.
Enrique Almanza-AguileraCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.ORCID 0000-0002-4805-0774
Álvaro HernáezCardiovascular Risk, Nutrition and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain.ORCID 0000-0001-8593-1477
Dolores CorellaCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.ORCID 0000-0002-2366-4104
Albert SanllorenteCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Emilio RosCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.ORCID 0000-0002-2573-1294
Olga PortolésCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.
Julieta ValussiCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Ramon EstruchCardiovascular Risk, Nutrition and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), 08036 Barcelona, Spain.ORCID 0000-0003-1260-4445
Oscar ColtellCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.ORCID 0000-0002-4518-8495
Isaac SubiranaCardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Silvia CanudasCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.ORCID 0000-0002-5630-1588
Cristina RazquinCentro de Investigación Biomédica en Red Fisiopatologia de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain.ORCID 0000-0003-3480-2645
Gemma BlanchartCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Lara NonellMicroarrays Analysis Service, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Montserrat FitóCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.
Olga CastañerCardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), 08003 Barcelona, Spain.ORCID 0000-0003-3169-997X
Instituto de Salud Carlos III · ESHospital Del Mar · ESUniversitat de València · ESUniversitat Jaume I · ES
Funding
Agència de Gestió d'Ajuts Universitaris i de Recerca [2017 SGR 222Fundació la Marató de TV3 201512.31Instituto de Salud Carlos III JR17/00022, and PI15/00047
6 · The paper itself
Abstract
We aimed to explore the differences in the whole transcriptome of peripheral blood mononuclear cells between elderly individuals with and without type 2 diabetes (T2D). We conducted a microarray-based transcriptome analysis of 19 individuals with T2D and 15 without. Differentially expressed genes according to linear models were submitted to the Ingenuity Pathway Analysis system to conduct a functional enrichment analysis. We established that diseases, biological functions, and canonical signaling pathways were significantly associated with T2D patients when their logarithms of Benjamini-Hochberg-adjusted
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.
Cancer Signaling Transcriptome Is Upregulated in Type 2 Diabetes Mellitus. · full record | OpenQuestion