Hypo-uricemie renale hereditaire chez un sujet d'origine caucasienne : presentation d'un cas clinique et revue de la litterature Hereditary renal hypouricemia in a Caucasian patient: A case report and review of the literature
Bibliographic record
Abstract
MOTS CLES Hypo-uricemie ; Acide urique ; Insuffisance renale aigue ; Exercice ; URAT1 ; Mutation ; Analyse moleculaire ; Caucasien Resume L’hypo-uricemie renale hereditaire se caracterise par un niveau serique d’acide urique abaisse, une fraction d’excretion de l’acide urique superieure a la normale et l’absence d’autre cause d’hypo-uricemie hyperuricosurique. Cette pathologie, le plus souvent causee par une mutation du transporteur URAT1, est relativement frequente dans les populations d’origine asiatique, mais tres rare chez les Caucasiens. Son association avec l’insuffisance renale aigue induite par l’exercice est bien connue. Cet article presente le cas d’un homme d’origine italienne âge de 47 ans chez qui un diagnostic d’hypo-uricemie renale hereditaire a ete pose apres un episode d’insuffisance renale aigue induite par l’exercice. Une analyse moleculaire du gene SLC22A12 codant pour URAT1 a ete realisee sur l’ADN genomique du patient. Le depistage de polymorphisme par analyse simple brin (SSCP) et le sequencage direct n’ont revele aucune mutation d’URAT1. Ce resultat suggere qu’un autre gene puisse etre implique dans l’hypouricemie familiale. # 2009 Association Societe de nephrologie. Publie par Elsevier Masson SAS. Tous droits reserves.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".