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Record W3203916574 · doi:10.1042/bsr20211646

Multifunctionality of prostatic acid phosphatase in prostate cancer pathogenesis

2021· article· en· W3203916574 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.

Bibliographic record

VenueBioscience Reports · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsIONICS Mass Spectrometry (Canada)
Fundersnot available
KeywordsPathogenesisProstateAcid phosphataseProstatic acid phosphataseCancerProstate cancerCancer researchPhosphataseBiologyMedicineInternal medicineBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The role of human prostatic acid phosphatase (PAcP, P15309|PPAP_HUMAN) in prostate cancer was investigated using a new proteomics tool termed signal sequence swapping (replacement of domains from the native cleaved amino terminal signal sequence of secretory/membrane proteins with corresponding regions of functionally distinct signal sequence subtypes). This manipulation preferentially redirects proteins to different pathways of biogenesis at the endoplasmic reticulum (ER), magnifying normally difficult to detect subsets of the protein of interest. For PAcP, this technique reveals three forms identical in amino acid sequence but profoundly different in physiological functions, subcellular location, and biochemical properties. These three forms of PAcP can also occur with the wildtype PAcP signal sequence. Clinical specimens from patients with prostate cancer demonstrate that one form, termed PLPAcP, correlates with early prostate cancer. These findings confirm the analytical power of this method, implicate PLPAcP in prostate cancer pathogenesis, and suggest novel anticancer therapeutic strategies.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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