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Record W2740315567 · doi:10.1088/1361-6579/aa82d8

The feasibility of <i>in vivo</i> detection of lanthanum using a <sup>241</sup> Am K x-ray fluorescence system

2017· article· en· W2740315567 on OpenAlexaff
Joanna Nguyen, Zaid Keldani, Eric Da Silva, Ana Pejović‐Milić, James L Gräfe

Bibliographic record

VenuePhysiological Measurement · 2017
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLanthanum carbonateX-ray fluorescenceSemiconductor detectorIn vivoLanthanumRadiochemistryDetection limitNuclear medicineMaterials scienceChemistryFluorescenceAnalytical Chemistry (journal)Biomedical engineeringDetectorPhysicsCalciumMedicineOpticsChromatographyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Lanthanum (La) is commonly used in phosphate binders in the form of lanthanum carbonate in patients with end-stage kidney disease undergoing hemodialysis treatments. With this administration, there is the potential for La storage in the body with bone being the main site of concern. However, the long-term effects of residual La in the body on bone health are not yet known. In this work, we investigate the feasibility of using a K x-ray fluorescence (K-XRF) spectroscopy system to measure bone La in vivo. APPROACH: Am source was used to excite the HAp phantoms doped with various known concentrations of La placed in a 90° geometry relative to the photon source and high-purity germanium (HPGe) detector. MAIN RESULTS: HAp and is comparable to previously reported in vivo bone La concentrations. SIGNIFICANCE: The technique developed in this study shows promising results and provides an alternative method to invasive biopsy sampling techniques to monitor the accumulation of bone La. To the best of our knowledge, this is the first reported work that seeks to non-invasively measure bone La via in vivo XRF.

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 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 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 score0.066
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.084
GPT teacher head0.263
Teacher spread0.179 · 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 teacher head, 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

Citations5
Published2017
Admission routes1
Has abstractyes

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