SynthesisNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2021
MicroRNAs in temporal lobe epilepsy: a systematic review.
Synthesis in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Expression Profile of miRs in Mesial Temporal Lobe Epilepsy: Systematic Review.International journal of molecular sciences · 2022Pooled it
- MicroRNAs in the abscopal effect: bridging radiotherapy and systemic anti-tumor immunity for enhanced cancer therapy.Clinical & experimental metastasis · 2025Review
- Circulating miRNAs as Novel Clinical Biomarkers in Temporal Lobe Epilepsy.Non-coding RNA · 2024Review
- Evaluation of MicroRNAs in Pediatric Epilepsy.Turkish archives of pediatrics · 2023Article
- Systemic inflammation as a biomarker of seizure propensity and a target for treatment to reduce seizure propensity.Epilepsia open · 2023Review
- The role of miR-153 and related upstream/downstream pathways in cancers: from a potential biomarker to treatment of tumor resistance and a therapeutic target.Medical oncology (Northwood, London, England) · 2022Review
- MicroRNAs and SUDEP: news in small matters.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
objectiveAbout 30% of patients with epilepsy have drug-resistant seizures. The aim of the current endeavor was to systematically review the existing evidence on the potential applications of microRNAs as biomarkers in people with difficult to treat temporal lobe epilepsy (TLE).
methodsMEDLINE (accessed from PubMed) and Scopus from inception to March 18, 2020 were systematically searched for related published articles. In both electronic databases, the following search strategy was implemented, and these keywords (in the title/abstract) were used: "microRNA" AND "temporal lobe epilepsy." Articles written in English that were human studies in people with epilepsy were all included in this search.
resultsWe could identify 16 articles about different aspects of microRNAs in the serum of patients with TLE. However, only three studies robustly investigated microRNAs as potential biomarkers in the diagnosis of drug-resistant TLE (microRNA-155 (upregulated), microRNA-129-2-3p (upregulated), microRNA-153 (downregulated)). One small study provided class II, and two small studies provided class III evidence.
conclusionWhile this systematic review identified three studies that provided some evidence on the potential applications of circulating serum microRNAs as biomarkers in people with drug-resistant TLE, the evidence is not robust yet. While these findings provide a new horizon, substantial challenges remain before the roles of microRNAs as biomarkers in the diagnosis of drug-resistant TLE can be translated into clinical practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.