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Record W2897087893 · doi:10.1016/j.jalz.2018.07.049

P4‐228: AN AMYLOID‐BETA‐DERIVED PEPTIDE TRANSFORMS RAT GLIAL PROGENITOR CELLS INTO MICROGLIA

2018· article· en· W2897087893 on OpenAlexaff
Diane Van Alstyne

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsPenticton Regional Hospital
Fundersnot available
KeywordsProgenitor cellMicrogliaBiologyCell biologyMonocyteChemotaxisReceptorImmunologyStem cellInflammationBiochemistry

Abstract

fetched live from OpenAlex

Septapeptides (“septas”), previously identified as meningitis-specific antigens, defined by a rubella virus monoclonal antibody, were found in human Monocyte Chemoattractant Protein (hMCP-1) and on the surface of meningitis-causing bacteria, viruses and spirochetes. Some bacterial septas were tested for Ca mobilization through receptor-associated heterotrimeric G-protein binding on THP-1 cells, progenitor cells of circulating peripheral macrophages. Certain of the free septas acted on their own as mild agonists of Ca mobilization. Their signal transduction activity may be mediated through a single (or a single class) of receptor, but the data do not link this with the MCP-1 receptor on THP-1 cells. These data support the notion that (1) infectious organisms may conserve and employ these sequences in order to facilitate their transport through the BBB to infect the CNS and (2) the hypothesis that the septas represent muteins of the MCP-1 active site for monocyte stem cell activation to macrophages. Other MCP muteins have since been identified in the AD-associated agents, amyloid beta and prions, as well as in viruses like HIV, known to establish chronic infections in the CNS. Rat glial progenitor cells in tissue culture were used to test for hMCP-1 activity in septas derived from amyloid beta. Nanomolar concentrations of the amyloid beta septa HHQKLVF were found to transform more than 60% of rat glial progenitor cells into mature microglia in tissue culture. These data support the hypothesis that an amyloid beta-derived septa may serve to activate stem cells to increase the number of microglia available to combat chronic infection in the CNS. VanAlstyne & Sharma. April 23, 1996. US Patent No. 5,510,264. VanAlstyne & Sharma. Sept. 17, 1996. US Patent No. 5,556,757. Van Alstyne & Sharma. Dec. 6, 2011. US Patent No. 8,071,102. Singh and Van Alstyne. 1978.Brain Res. 155:418-421. Pope and Van Alstyne. 1981.Virology 113(2):776-780. Van Alstyne and Paty. 1983.Virology 124:173-180 Van Alstyne, Jan. 4, 2018. US Patent Application 62/613,621. Van Alstyne. June 20, 2018 Poster(3035) presentation at Keystone Symposia Conference “Advances in Neurodegenerative Disease Research and Therapy”. Session Z3.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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