Evidence map›Paper›PMID 21616174›Full record

ReviewInternational immunopharmacology2011

Toll-like receptors are key players in neurodegeneration.

Daniela S Arroyo, Javier A Soria, Emilia A Gaviglio, Maria C Rodriguez-Galan, Pablo Iribarren

Open access · greenAbstract readReview
In one paragraph

Review in International immunopharmacology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
7.5field-weighted citation impact, top 3% 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

54 citing papers in PubMed, 114 citations in OpenAlex.

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  8. iScience · 2023
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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.

Daniela S ArroyoCentro de Investigaciones en Bioquimica Clinica e Inmunologia-CONICET, Departamento de Bioquimica Clinica, Facultad de Ciencias Quimicas, Universidad Nacional de Cordoba, Cordoba, Argentina.
Javier A Soria
Emilia A Gaviglio
Maria C Rodriguez-Galan
Pablo Iribarren
Consejo Nacional de Investigaciones Científicas y Técnicas · ARUniversidad Nacional de Córdoba · AR

Funding

The role of chemoattractant receptors in central nervous system diseasesR01TW007621 · FIC · NATIONAL RESEARCH COUNCIL OF ARGENTINA · PI IRIBARREN, PABLO · 2008 to 2012
$250k
FIC NIH HHS 1R01TW007621-01A2FIC NIH HHS R01 TW007621
6 · The paper itself

Abstract

The activation of innate immune response is initiated by engagement of pattern-recognition receptors (PPRs), such as Toll-like receptors (TLRs). These receptors are expressed in peripheral leukocytes and in many cell types in the central nervous system (CNS). The expression of TLRs in CNS was mainly studied in astrocytes and microglial cells. However, new evidence indicates that these receptors may play an important role in neuronal homeostasis. The expression of TLRs in the CNS is variable and can be modulated by multiple factors, including pro-inflammatory molecules, which are elevated in neurodegenerative diseases and can increase the expression of TLRs in CNS cells. Moreover, activation of TLRs induces the release of pro-inflammatory cytokines. Therefore, TLRs have been shown to play a role in several aspects of neurodegenerative diseases. Here we will discuss results reported in the recent literature concerning the participation of TLRs in neurodegenerative diseases.

Indexed as

AnimalsAstrocytesCell SurvivalCellular MicroenvironmentCentral Nervous SystemCytokinesGene Expression RegulationHumansInflammationInflammation MediatorsMicrogliaMolecular Targeted TherapyNeurodegenerative DiseasesNeuronsToll-Like ReceptorsCytokinesInflammation MediatorsToll-Like Receptors

Identifiers

PMID21616174
PMCPMC3183240
OpenAlexW2040892689

What OpenQuestion holds

Textmetadata
LicenceTDM
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.