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Record W1523992425 · doi:10.1186/s12967-015-0585-y

Alternative transcripts of the SERPINA1 gene in alpha-1 antitrypsin deficiency

2015· article· en· W1523992425 on OpenAlexaff
Nerea Matamala, María Teresa Martínez, Beatriz Lara, Laura Pérez‐Lago, Irene Vázquez-Domínguez, Azucena Jiménez, Miguel Barquín, Ilaria Ferrarotti, Ignacio Blanco, Sabina Janciauskiene, Beatriz Martínez–Delgado

Bibliographic record

VenueJournal of Translational Medicine · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsUniversity Hospital Foundation
FundersInstituto de Salud Carlos III
KeywordsBiologyAlternative splicingGeneExonAlpha 1-antitrypsin deficiencyGene expressionGeneticsAlleleGenotypeMolecular biologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: SERPINA1 is the gene for alpha-1 antitrypsin (AAT), an acute phase protein with anti-protease and immunoregulatory activities. Mutations in SERPINA1 gene cause AAT deficiency and predispose individuals to early-onset emphysema and liver diseases. Expression of the SERPINA1 gene is regulated by different promoters and alternative splicing events among non-coding exons 1A, 1B and 1C. METHODS: We have developed three quantitative PCR (QT-PCR) assays (1A, 1B and 1C). These assays were applied for the analysis of SERPINA1 alternative transcripts in: (1) 16 human tissues and (2) peripheral blood leukocytes from 33 subjects with AAT mutations and 7 controls. RESULTS: Tissue-specific expression was found for the SERPINA1 transcripts. The 1A transcripts were mainly expressed in leukocytes and lung tissue while those detected with the 1B assay were highly restricted to leukocytes. Only 1B transcripts significantly correlated with serum AAT levels. The 1C transcripts were specifically found in lung, liver, kidney and pancreas. Furthermore, the expression of transcripts was related to AAT genotypes. While deficient variants of AAT had no pronounced effect on the transcript expression, null alleles were associated with significant reduction of different transcripts. CONCLUSIONS: The possibility to discriminate between SERPINA1 alternative splicing products will help us to understand better the regulation of SERPINA1 gene and its association with SERPINA1 mutations-related diseases.

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)0.000
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 score0.019
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.030
GPT teacher head0.278
Teacher spread0.248 · 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

Citations37
Published2015
Admission routes1
Has abstractyes

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