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Alternative Processing: Neuronal Nitric Oxide Synthase

2011· other· en· W4245871487 on OpenAlexaff
Philip A. Marsden, Derek C. Newton, Albert K.Y. Tsui

Bibliographic record

VenueEncyclopedia of Life Sciences · 2011
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsExonUntranslated regionBiologyPromoterGeneMessenger RNAGeneticsFive prime untranslated regionStart codonTranscription (linguistics)Gene expressionMolecular biology

Abstract

fetched live from OpenAlex

Abstract The human neuronal nitric oxide synthase (nNOS) gene is expressed from multiple promoters and is subject to alternate messenger ribonucleic acid (mRNA) processing. These complex molecular mechanisms contribute to regulating gene expression and function in multiple tissues and cell types. In the case of nNOS, these distinct promoters give rise to mRNA transcripts with untranslated leader sequences that have differing lengths, nucleotide composition and three‐dimensional structure. These distinct leader sequences have robust effects on translational efficiency. In disease settings, these have functional relevance. For example, in settings of low oxygen content, a unique promoter becomes trancriptionally active. In contrast to basally expressed transcripts, this hypoxia‐induced mRNA is very efficiently translated. To accommodate diverse biological roles, multiple mechanisms have evolved to produce a diverse range of nNOS mRNA transcripts from a single genetic locus. Key Concepts: Mammalian genes can have more than one promoter. Having more than one promoter implies that the gene has more than one version of exon 1. Initiation of transcription in different regions of genomic DNA imparts different nucleotide sequences to the leader regions of messenger ribonucleic acid transcripts, also known as the 5′‐untranslated region (5′‐UTR). Different leader sequences may, or may not, affect protein structure depending on whether the initiator AUG codon for translation of the protein lies in exon 1 or downstream. If multiple versions of exon 1 all have their own initiator AUG codon, then the encoded protein will exist if different forms, each with a uniqueN‐terminal peptide sequence. Different 5′‐UTRs of messenger ribonucleic acid transcripts can have functional effects on expression of the encoded protein. The 5′‐UTRs of messenger ribonucleic acid transcripts can affect translational efficiency. The 5′‐UTRs of messenger ribonucleic acid transcripts can affect subcellular messenger ribonucleic acid transcript localisation. The 5′‐UTRs of messenger ribonucleic acid transcripts can affect messenger ribonucleic acid transcript stability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2011
Admission routes1
Has abstractyes

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