Evidence map›Paper›PMID 19486674›Full record

ArticleBiophysical journal2009

An integrated model of electrical spiking, bursting, and calcium oscillations in GnRH neurons.

Patrick A Fletcher, Yue-Xian Li

Abstract read
In one paragraph

Article in Biophysical journal, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. A complete biomechanical model ofProceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  2. Article
  3. A unified model for two modes of bursting in GnRH neurons.Journal of computational neuroscience · 2016
    Article
  4. Article
  5. Article
  6. Article
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

2 authors.

Patrick A FletcherDepartment of Mathematics, University of British Columbia, Vancouver, British Columbia, Canada.
Yue-Xian Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The plasma membrane electrical activities of neurons that secrete gonadotropin-releasing hormone (GnRH) have been studied extensively. A couple of mathematical models have been developed previously to explain different aspects of these activities. The goal of this article is to develop a single model that accounts for the previously modeled experimental results and some more recent results that have not been accounted for. The latter includes two types of membrane potential bursting mechanisms and their associated cytosolic calcium oscillations. One bursting mechanism has not been reported in experiments and is thus regarded as a model prediction. Although the model is mainly based on data collected in immortalized GnRH cell lines, it is capable of explaining some properties of GnRH neurons observed in several other preparations including mature GnRH neurons in hypothalamic slices. We present a spatial model that incorporates a detailed description of calcium dynamics in a three-dimensional cell body with the ion channels evenly distributed on the cell surface. A phenomenological reduction of the spatial model into a simplified form is also presented. The simplified model will facilitate the study of the roles of plasma membrane electrical activities in the pulsatile release of GnRH.

Indexed as

Models, NeurologicalAction PotentialsAlgorithmsApaminCalciumColforsinCyclic AMPEnzyme InhibitorsGonadotropin-Releasing HormoneMembrane PotentialsNeuronsNeurotoxinsSodiumThapsigarginApaminCalciumColforsinCyclic AMPEnzyme InhibitorsGonadotropin-Releasing HormoneNeurotoxinsSodiumThapsigargin

Identifiers

PMID19486674
PMCPMC3304551

What OpenQuestion holds

Textmetadata
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.