Evidence map›Paper›PMID 31608105›Full record

ArticleFrontiers in genetics2019

Candidate Genes and MiRNAs Linked to the Inverse Relationship Between Cancer and Alzheimer's Disease: Insights From Data Mining and Enrichment Analysis.

Cristina Battaglia, Marco Venturin, Aleksandra Sojic, Nithiya Jesuthasan, Alessandro Orro, Roberta Spinelli, Massimo Musicco, Gianluca De Bellis, Fulvio Adorni

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Extracting Significant Comorbid Diseases from MeSH Index of PubMed.Methods in molecular biology (Clifton, N.J.) · 2022
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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

9 authors.

Cristina BattagliaDepartment of Medical Biotechnology and Translational Medicine (BIOMETRA), University of Milan, Segrate, Italy.
Marco VenturinDepartment of Medical Biotechnology and Translational Medicine (BIOMETRA), University of Milan, Segrate, Italy.
Aleksandra SojicDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.
Nithiya JesuthasanDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.
Alessandro OrroDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.
Roberta SpinelliIstituto Istruzione Superiore Statale IRIS Versari, Cesano Maderno, Italy.
Massimo MusiccoDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.
Gianluca De BellisDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.
Fulvio AdorniDepartment of Biomedical Sciences, Institute of Biomedical Technologies-National Research Council (ITB-CNR), Segrate, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence of cancer and Alzheimer's disease (AD) increases exponentially with age. A growing body of epidemiological evidence and molecular investigations inspired the hypothesis of an inverse relationship between these two pathologies. It has been proposed that the two diseases might utilize the same proteins and pathways that are, however, modulated differently and sometimes in opposite directions. Investigation of the common processes underlying these diseases may enhance the understanding of their pathogenesis and may also guide novel therapeutic strategies. Starting from a text-mining approach, our

Indexed as

Alzheimercancerdata miningenrichment analysisgenesinverse relationshipmiRNAsprotein-protein interaction network

Identifiers

PMID31608105
PMCPMC6771301

What OpenQuestion holds

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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.