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Refinement of the SPG9 locus on chromosome 10q23.3‐24.2 and exclusion of candidate genes

2008· article· en· W2091348110 on OpenAlexaff
Emanuele Panza, Tommaso Pippucci, Roberto Cusano, Cristiana Lo Nigro, Laura Maria Pradella, Sara Contardi, Guy A. Rouleau, Giovanni Stévanin, Roberto Ravazzolo, Rocco Liguori, P. Montagna, G. Cara Romeo, Marco Seri

Bibliographic record

VenueEuropean Journal of Neurology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsHôpital Notre-Dame
FundersAgence Nationale de la Recherche
KeywordsLocus (genetics)Candidate geneGeneticsHereditary spastic paraplegiaGenePositional cloningBiologyGenetic heterogeneityDisease gene identificationExome sequencingPhenotype

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The hereditary spastic paraplegias (HSPs) are a heterogeneous group of neurodegenerative disorders, characterized by a progressive spasticity of the lower limbs. So far, 33 different loci (SPGs) have been mapped and the 15 genes responsible have been identified. We mapped a locus responsible for a form of spastic paraplegia, complicated by bilateral cataracts, gastroesophageal reflux with persisting vomiting and amyotrophy to chromosome 10q23.3-q24.2, in an Italian family. The critical region was in a 12 cm chromosomal interval between markers D10S564 and D10S603 (SPG9, MIM601162). In the same region, two other forms of HSP have been recently mapped: SPG27 and SPG33. In the latter case, the gene responsible has been identified. MATERIALS AND METHODS: To better characterize this region, we genotyped individuals from SPG9-linked families using additional markers and reduced the candidate region to a 4.8 Mb, excluding several genes by positional cloning. RESULTS: The refined SPG9 locus is positioned completely within SPG27 and does not include the SPG33 gene. DISCUSSION: Fifty-two transcripts are present in the refined critical region and 25 strong candidates have been excluded as disease causing genes by direct sequencing. Six of them were also excluded as responsible for SPG27.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.040
GPT teacher head0.231
Teacher spread0.191 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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