Evidence map›Paper›PMID 40217344›Full record

ReviewActa epileptologica2025

The hidden rhythms of epilepsy: exploring biological clocks and epileptic seizure dynamics.

Ruili Niu, Xuan Guo, Jiaoyang Wang, Xiaofeng Yang

Abstract readReview
In one paragraph

Review in Acta epileptologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

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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

4 authors.

Ruili Niu *Guangzhou National Laboratory, Guangzhou, 510005, China.
Xuan Guo *Guangzhou National Laboratory, Guangzhou, 510005, China.
Jiaoyang Wang *Guangzhou National Laboratory, Guangzhou, 510005, China.
Xiaofeng YangGuangzhou National Laboratory, Guangzhou, 510005, China. xiaofengyang@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epilepsy, characterized by recurrent seizures, is influenced by biological rhythms, such as circadian, seasonal, and menstrual cycles. These rhythms affect the frequency, severity, and timing of seizures, although the precise mechanisms underlying these associations remain unclear. This review examines the role of biological clocks, particularly the core circadian genes Bmal1, Clock, Per, and Cry, in regulating neuronal excitability and epilepsy susceptibility. We explore how the sleep-wake cycle, particularly non-rapid eye movement sleep, increases the risk of seizures, and discuss the circadian modulation of neurotransmitters like gamma-aminobutyric acid and glutamate. We explore clinical implications, including chronotherapy which refers to the practice of timing medical treatments to align with the body's natural biological rhythms, such as the circadian rhythm. Chronotherapy aligns anti-seizure medication administration with biological rhythms. We also discuss rhythm-based neuromodulation strategies, such as adaptive deep brain stimulation, which may dynamically change stimulation in response to predicted seizures in patients, provide additional therapeutic options. This review emphasizes the potential of integrating biological rhythm analysis into personalized epilepsy management, offering novel approaches to optimize treatment and improve patient outcomes. Future research should focus on understanding individual variability in seizure rhythms and harnessing technological innovations to enhance seizure prediction, precision treatment, and long-term management.

Indexed as

Biological rhythmChronotherapyCircadian genesEpilepsyNeuromodulation

Identifiers

PMID40217344
PMCPMC11960285

What OpenQuestion holds

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Registered trials

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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.