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Record W4213262562 · doi:10.1117/1.nph.9.2.021907

Photonics tools begin to clarify astrocyte calcium transients

2022· article· en· W4213262562 on OpenAlexafffund

Bibliographic record

VenueNeurophotonics · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchCanada Research ChairsUniversity of Calgary
KeywordsAstrocyteCalciumCalcium imagingCalcium signalingPhotonics

Abstract

fetched live from OpenAlex

Astrocytes integrate information from neurons and the microvasculature to coordinate brain activity and metabolism. Using a variety of calcium-dependent cellular mechanisms, these cells impact numerous aspects of neurophysiology in health and disease. Astrocyte calcium signaling is highly diverse, with complex spatiotemporal features. Here, we review astrocyte calcium dynamics and the optical imaging tools used to measure and analyze these events. We briefly cover historical calcium measurements, followed by our current understanding of how calcium transients relate to the structure of astrocytes. We then explore newer photonics tools including super-resolution techniques and genetically encoded calcium indicators targeted to specific cellular compartments and how these have been applied to astrocyte biology. Finally, we provide a brief overview of analysis software used to accurately quantify the data and ultimately aid in our interpretation of the various functions of astrocyte calcium transients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.114
GPT teacher head0.355
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2022
Admission routes2
Has abstractyes

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