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Record W2136000113 · doi:10.1128/mmbr.00003-07

Regulation of Vacuolar pH and Its Modulation by Some Microbial Species

2007· review· en· W2136000113 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicrobiology and Molecular Biology Reviews · 2007
Typereview
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchCystic Fibrosis Foundation
KeywordsBiologyPhagosomeEffectorPathogenMicrobiologyImmune systemEndocytic cycleOrganismMycobacterium tuberculosisSymbiosisBacteriaHost (biology)Cell biologyTuberculosisEndocytosisCellEcologyBiochemistryImmunologyGeneticsPhagocytosis

Abstract

fetched live from OpenAlex

To survive within the host, pathogens such as Mycobacterium tuberculosis and Helicobacter pylori need to evade the immune response and find a protected niche where they are not exposed to microbicidal effectors. The pH of the microenvironment surrounding the pathogen plays a critical role in dictating the organism's fate. Specifically, the acidic pH of the endocytic organelles and phagosomes not only can affect bacterial growth directly but also promotes a variety of host microbicidal responses. The development of mechanisms to avoid or resist the acidic environment generated by host cells is therefore crucial to the survival of many pathogens. Here we review the processes that underlie the generation of organellar acidification and discuss strategies employed by pathogens to circumvent it, using M. tuberculosis and H. pylori as examples.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.001
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 head0.031
GPT teacher head0.305
Teacher spread0.274 · 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