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Activity of HIV entry and fusion inhibitors expressed by the human vaginal colonizing probiotic Lactobacillus reuteri RC-14

2006· article· en· W1984609370 on OpenAlexaff
Janice J. Liu, Gregor Reid, Yonghou Jiang, Mark S. Turner, Che‐Chung Tsai

Bibliographic record

VenueCellular Microbiology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsLactobacillus reuteriBiologyProbioticMicrobiologyLactobacillusPeripheral blood mononuclear cellSecretionFusion proteinMicrobicideHuman immunodeficiency virus (HIV)Sexual transmissionVirologyIn vitroBacteriaGeneBiochemistryRecombinant DNA

Abstract

fetched live from OpenAlex

Novel therapeutic approaches are needed to combat the rapid increase in HIV sexual transmission in women. The probiotic organism Lactobacillus reuteri RC-14 which safely colonizes the human vagina and prevents microbial infections, has been genetically modified to produce anti-HIV proteins which were capable of blocking the three main steps of HIV entry into human peripheral blood mononuclear cells. The HIV entry or fusion inhibitors were fused to the native expression and secretion signals of BspA, Mlp or Sep in L. reuteri RC-14 and the expression cassettes were stably inserted into the chromosome. L. reuteri RC-14 expressed the HIV inhibitors in cell wall-associated and secreted forms. L. reuteri RC-14 expressing CD4D1D2-antibody-like fusion proteins were able to bind single or dual tropic coreceptor-using HIV-1 primary isolates. This is the first study to show that a well-documented and proven human vaginal probiotic strain can express potent functional viral inhibitors, which may potentially lower the sexual transmission of HIV.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.009
GPT teacher head0.187
Teacher spread0.178 · 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

Citations45
Published2006
Admission routes1
Has abstractyes

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