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Record W2151895571 · doi:10.2174/1874196701306010014

A Basis of the Crenation of Erythrocyte Ghosts by Electrolytes

2013· article· en· W2151895571 on OpenAlexaff
Pierre Wong

Bibliographic record

VenueThe Open Biology Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsPROTO Manufacturing (Canada)
Fundersnot available
KeywordsBand 3SpectrinDivalentChemistryCationic polymerizationElectrolyteBiophysicsCrystallographyPhosphateErythrocyte membraneMembraneBiochemistryBiologyPolymer chemistry

Abstract

fetched live from OpenAlex

Erythrocyte ghosts isolated in hemolytic hypotonic buffers, pH 7.0-8.0, 0-4°C were previously observed to be crenated by electrolytes. This shape transformation, which occurred rapidly and reversibly, was attributed to electrostatic interactions of cations with flexible filamentous anionic spectrin, the major protein component of the skeleton and/or anionic phospholipids, since divalent cationic salts crenated at concentrations substantially lower than those of monovalent cationic salts and that crenation appeared unrelated to the anion species. However, crenation by electrolytes was markedly influenced by ionic conditions and temperature. A mechanism of the erythrocyte shape control has been previously suggested in which band 3 (AE1), exchanging the monovalent anions Cl - and HCO 3 - and linked to spectrin, plays a pivotal role. Briefly, the alternative recruitment of its inward-facing (band 3 i ) and outward-facing (band 3 o ) conformations contract and relax the skeleton, thereby promoting echinocytosis and stomatocytosis, respectively. Band 3 transports also other anions, including endogenous inorganic phosphate, but at a slow rate. This mechanism would explain the above observations and would lead to some inferences, one of which is a Cl - -dependent crenation by Mg 2+ and Ca 2+ , suggesting that they specifically bind on sites on spectrin.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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 teacher head, not a consensus.

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

Citations2
Published2013
Admission routes1
Has abstractyes

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