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Record W4380577130 · doi:10.1080/15476286.2023.2221946

Special focus on the ribosome life cycle

2023· editorial· en· W4380577130 on OpenAlexaff
Marlene Oeffinger

Bibliographic record

VenueRNA Biology · 2023
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
Fundersnot available
KeywordsBiologyFocus (optics)RibosomeEvolutionary biologyTranslation (biology)Computational biologyGeneticsCell biologyRNAGeneMessenger RNA

Abstract

fetched live from OpenAlex

Special focus on the ribosome life cycleIn all cells and tissues, protein production is carried out by a ubiquitous machine -the ribosome, a three Mega Dalton macromolecular complex that is essential across all domains of life.It was 65 years ago, in 1958, that the ribosome as protein production machinery was first named by Richard Roberts [1][2][3].Five years later, in January 1963, Jonathan Warner, Paul Knopf and Alex Rich published the first paper on the characterization of polyribosomes, or polysomes, from rabbit reticulocyte lysate [4].The very same year, work by Alfred Gierer in Tubingen, also using reticulocytes [5] and Hans Noll in Pittsburgh, using rat liver [6] independently suggested that protein synthesis was conducted on structures with multiple ribosomes scanning a single mRNA, and in 1964, description of the A(cceptor) and P(eptidyl) sites (the E, or exit, site was only identified by Knut Nierhaus in 1981 [7]) and mRNA and tRNA, followed [8-14].In the span of a little over a year and a half, views of protein synthesis evolved from a vague idea of an interaction between mRNA, tRNA and ribosomes to a basic model that guides ongoing research into mechanisms of translation regulation to this day: ribosomes move from one end of an mRNA to another, and each has a site for a tRNA attached to the growing polypeptide and a site for the incoming tRNA attached to an amino acid.It also became clear very early on that the ribosome itself is composed of both RNA and proteins and investigation into its composition and biogenesis began in the 1950s and 60s, in bacteria and eukaryotes, respectively [3].In 1962, Klaus Scherrer, Harriet Latham, and James E. Darnell demonstrated the existence of precursor ribosomal RNAs (rRNAs) in HeLa cells [15], while R. J. Britten, B. J. McCarthy, and Richard Roberts suggested that ribosomes are formed in a stepwise manner [16,17].The nucleolus was identified as the site of ribosome biogenesis only 2 years later [18], the same year as rRNA base methylation [19] and both rRNA and 'nascent' ribosomes of different molecular mass were isolated from human nuclei for the first time in 1967 [15,19,20].It was in 1972 that a study by Kumar & Warner on nuclear vs cytoplasmic ribosomes in human cells revealed a considerable difference in protein content [21].At the time, these 'extra proteins' within nuclear ribosomes werein retrospect, correctly -hypothesized to function in the processing of rRNA precursors, and while ribosomes were moved to the cytoplasm, these 'extra proteins' stayed behind and were surmised to be re-utilized in further rounds of ribosome production [5].These 'extra' proteins are now known to be the many ribosome biogenesis factors that are required to modify, process, and fold the ribosomal RNAs (rRNA) and assemble them with the ribosomal proteins (r-proteins) into mature ribosomes prior to their

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
Research integrity0.0020.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.012
GPT teacher head0.256
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2023
Admission routes1
Has abstractyes

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