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Record W4210959231 · doi:10.1128/9781555819194.ch27

Molecular Mechanisms of Phagosome Formation

2017· book-chapter· en· W4210959231 on OpenAlexaff
Valentin Jaumouillé, Sergio Grinstein

Bibliographic record

VenueASM Press eBooks · 2017
Typebook-chapter
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsPhagosomePhagocytosisCell biologyPinocytosisEndocytosisBiologyReceptorActin cytoskeletonCell surface receptorVacuoleCytoskeletonChemistryCytoplasmBiochemistryCell

Abstract

fetched live from OpenAlex

Phagocytosis culminates with the entrapment of the target particles within large vacuoles called phagosomes. Because of the multiplicity of phagocytic receptors, it is becoming apparent that a variety of different signaling cascades can be activated during the process. However, several aspects of phagocytosis appear to be conserved, distinguishing it from other mechanisms of cellular uptake such as endocytosis and macropinocytosis. First, phagocytosis can accommodate a wide variety of particle sizes, from hundreds of nanometers to tens of micrometers (1, 2), as well as complex particle morphologies (3, 4). Second, phagocytosis requires the progressive engagement of phagocyte surface receptors around the entire particle (5). This ratchet mechanism has been described as the “zipper” model, which contrasts with the limited number of independent receptors that need to be activated by soluble ligands to trigger macropinocytosis (6). Third, phagocytosis is an active mechanism that involves local remodeling of the actin cytoskeleton, which drives the deformation of the plasma membrane and the progression of the receptor/ligand “ratchet” around the particle (7 – 10). In addition, as the actin cytoskeleton is tightly associated with the plasma membrane, signaling mediated by phospholipids appears to be a common feature of phagocytosis. Phosphoinositides in particular play a critical role, as phosphatidylinositol 3-kinase (PI3K) is seemingly involved in virtually all known phagocytic systems (11 – 14). These different features impose a temporal progression of the phagosome formation, which can be described by the following sequence of events: (i) binding of the ligand to surface receptors; (ii) activation of receptor-mediated signaling cascades; (iii) remodeling of the actin cytoskeleton; (iv) progressive engagement of additional receptors around the particle; and (v) membrane fusion, leading to the closure of the phagosome (Fig. 1). Yet despite these conserved traits, one cannot fully appreciate the molecular mechanisms involved in phagosome formation without taking into account the diversity of phagocytic receptors and the variety of signaling cascades they induce individually and cooperatively. Thus, here, we chose to focus on some of the best-characterized receptors and signaling pathways in order to give an overview of the many roads that lead to phagosome formation, whereas phagosome maturation and subsequent responses will be described elsewhere.

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)0.001
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.005

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 head0.028
GPT teacher head0.242
Teacher spread0.214 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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