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Record W4403940362 · doi:10.7554/elife.95852.4.sa4

Author response: PUFA stabilizes a conductive state of the selectivity filter in IKs channels

2024· peer-review· en· W4403940362 on OpenAlexaff
Alessia Golluscio, Jodene Eldstrom, Jessica J. Jowais, Marta E. Perez, Kevin P. Cunningham, Alicia de la Cruz, Xiaoan Wu, Valentina Corradi, D. Peter Tieleman, David Fedida, H. Peter Larsson

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsSelectivityState (computer science)ChemistryComputer scienceAlgorithmBiochemistry

Abstract

fetched live from OpenAlex

Travelling through the heart are waves of electrical activity that cause muscle cells to contract and pump blood around the body. The waves are generated by charged ions which flow via tiny channels in and out of the muscle cells. This electrical activity spreads quickly from one cell to the next to make sure all the muscle cells contract at the right time. When these ion channels are compromised, this can lead to heart problems such as long QT syndrome (LQTS). In patients with LQTS, electrical activity in the heart does not follow the typical rhythm, which can result in an irregular heartbeat and lead to cardiac arrest. The most common cause of LQTS is mutations in the channel KCNQ1, which allows potassium ions to flow out of heart muscle cells. This outflux of potassium restores the electrical charge inside the cell so that it is ready to receive another electrical wave and contract at the right time. Current treatments for LQTS do not target KCNQ1 channels directly and have side effects. An alternative approach could be to use a group of molecules called polyunsaturated fatty acids (or PUFAs for short) which increase the flow of ions that pass through KCNQ1. However, it is not fully understood how PUFAs achieve this. Previous research showed that PUFAs activate KCNQ1 via two independent sites: one at the voltage sensor which decides whether the channel is open or closed (Site I), and another at the pore domain ions pass through (Site II). While it is well understood how PUFAs activate the channel at Site I, little is known about the activation mechanism that occurs at Site II. To investigate, Golluscio et al. modified egg cells from the frog Xenopus laevis to express KCNQ1 channels. Experiments investigating the electrical properties of KCNQ1 revealed that the selective filter in the pore domain – which permits potassium but no other ions to pass through – is usually unstable. However, PUFAs help to stabilize this filter, causing KCNQ1 to stay open more often and allow potassium ions to flow out of muscle cells. The findings of Golluscio et al. suggest that PUFAs could represent an important therapeutic tool to treat LQTS and potentially other cardiac disorders. However, further studies in heart cells, animals and eventually humans will be required to confirm this conclusion.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.208
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0110.008
Insufficient payload (model declined to judge)0.2080.072

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 head0.038
GPT teacher head0.345
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2024
Admission routes1
Has abstractyes

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