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Record W2051190783 · doi:10.1371/journal.ppat.1004539

The Shear Stress of Host Cell Invasion: Exploring the Role of Biomolecular Complexes

2015· review· en· W2051190783 on OpenAlexafffund
Michelle L. Tonkin, Martin J. Boulanger

Bibliographic record

VenuePLoS Pathogens · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsPathogenIntracellularBiologyBiophysicsHost factorsContext (archaeology)Shear stressCell biologyNanotechnologyMicrobiologyMaterials scienceVirologyVirus

Abstract

fetched live from OpenAlex

Biological fluids, such as blood and mucosal secretions, continuously flow within the human body and form prominent barriers to pathogen colonization and invasion of host cells Consequently, pathogens have evolved sophisticated molecular strategies to overcome the mechanical shear forces associated with resisting the flow of biological fluids; in particular, membrane anchored biomolecular complexes enable controlled deceleration, tight adhesion and, in the case of intracellular pathogens, penetration through the host cell membrane (Fig. The architecture of these biomolecular complexes have been the subject of numerous structural and biophysical investigations, which have yielded high resolution molecular blueprints of the host pathogen interface. However, our understanding of precisely how these biomolecular complexes function is somewhat limited by the technical challenges associated with measuring or modelling the effects of shear flow and related forces on protein complexes in the context of biological membranes To highlight the potential for correlating structural and biophysical data with the extent of dynamic shear stress experienced during diverse host cell invasion processes, we review here several structurally characterized invasion complexes from protozoan, bacterial, and viral pathogens.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.271
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2015
Admission routes2
Has abstractyes

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