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Record W7132986223

Deuterium Magnetic Resonance Spectroscopy of Early Treatment-induced Changes in Tumour Lactate

2021· dissertation· W7132986223 on OpenAlexaff
Josephine Lydia Tan

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExtracellularNuclear magnetic resonance spectroscopyIn vitroApoptosisMagnetic resonance imagingProgrammed cell deathCellCell culture
DOInot available

Abstract

fetched live from OpenAlex

An emerging hallmark of many tumour cells is aberrant metabolism, characterized in part by elevated lactate production. In response to treatment, tumour cells exhibit a change in lactate production that precedes late-stage morphological measurements conventionally used to assess tumour response. These metabolic changes can be non-invasively measured by Deuterium (2H) Magnetic Resonance Spectroscopy (MRS), but there has been limited work exploring the feasibility of using 2H-lactate as a marker of early tumour response to treatment. In this thesis, the biological processes associated with treatment-induced changes in the 2H-lactate signal were established in an in vitro tumour model. Significant decreases in 2H-lactate were observed 48 hours after treatment with a chemotherapeutic agent and associated with apoptotic cell death and decreased extracellular lactate. These findings offer the opportunity to build a framework for preclinical 2H MRS studies of tumour metabolism, with the goal of enhancing assessment of tumour response in the clinic.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.028
GPT teacher head0.376
Teacher spread0.348 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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