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Method for biochemical monitoring of iodine. Determination of iodide-ion in urine with an ion-selective electrode

2022· article· en· W4214708196 on OpenAlex
Г. И. Бебешко, Maria Dittrich

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

VenueIndustrial laboratory Diagnostics of materials · 2022
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIodineIodideAshingChemistryUrineUreaPopulationSodiumDetection limitChromatographySodium iodideInorganic chemistryBiochemistryMedicine

Abstract

fetched live from OpenAlex

Determination of iodine in urine is an important methodology in the assessment of thyroid disorders. This indicator is often used in epidemiological studies of the state of iodine nutrition of the population, since the widespread prevalence of human iodine deficiency diseases is directly related to the lack of iodine intake with food and water. A method for the iodide ion determination in urine has been developed based on preliminary preservation of the sample in the presence of a buffer solution containing 4.28 %wt. H 2 O 2 at pH 6.8 – 7.5 and measurements of the potential of the iodide selective electrode directly in the preserved sample solution without separation of the interfering components. After mixing the sample with a buffer solution in a ratio of 1:1, it is preserved after 18 – 24 h and stored for at least 30 days. The interfering effect of macro- and micro-components has been studied. It is shown that the amount of sodium chloride in the sample should be taken into account only in studying the severe iodine deficiency (≤20 μg/liter) and urea does not affect the potential of the electrode. To assess the total effect of the organic components of urine, we compared the results of parallel determinations of iodine in the samples, one of which was preserved, and organics was removed from the second one by alkaline ashing. It is shown that the discrepancies in the results were random and did not exceed 11.3 %. Iodine loss has not been determined, the bias between the concentration of the introduced and found additives was insignificant. Thus, in a buffer solution with hydrogen peroxide, not only the preservation of the urine sample for a long time takes place, but also the interfering influence of inorganic and organic components of the sample matrix on the membrane of the ion-selective electrode is eliminated. Metrological evaluation of the developed methodology was performed, which showed the precision and trueness of the procedure. The method was tested in an experiment on the correction and enrichment of iodine in the diet of schoolchildren. The low cost, convenient and easy to use equipment, the possibility of long-term storage of preserved samples makes the method mobile and suitable for biochemical monitoring of iodine consumption and deficiency during a large-scale population survey.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.033
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.311
Teacher spread0.284 · 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