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Record W7066911406

Investigation of Stage-Specific Distinction in the Leishmania mexicana Translational Machinery

2024· other· en· W7066911406 on OpenAlexaff

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2024
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsYork University
Fundersnot available
KeywordsNucleofectionContext (archaeology)Leishmania mexicanaRNA
DOInot available

Abstract

fetched live from OpenAlex

Leishmaniasis is a parasitic infection found in tropical, subtropical and southern European regions. The Leishmania life cycle is digenic and transitions between the sandfly and human hosts, which have distinct environmental conditions. Near-constitutive transcription in kinetoplasts renders gene regulation overwhelmingly post-transcriptional, placing heightened regulatory emphasis on RNA binding protein function. Modulation of translation plays a major role in parasite survival and adaptation. Our knowledge of the molecular mechanisms of translation in Leishmania remains limited, and it is unknown to what extent the composition of the translational machinery varies throughout the parasite life cycle Therefore, to expand this knowledge, enrichment strategies for Leishmania ribosomes were evaluated in order to generate samples suitable for mass spectrometry analysis of stage-specific ribosome-associated proteins. Immunoprecipitation was employed using antibodies against ribosomal protein P0 (also known as uL10) to capture the ribosomes on beads, which were subsequently analysed by mass spectrometry. Polysome profiling was also performed to identify the ideal conditions for RNA digestion to ensure the enrichment of ribosomes, to isolate both translating and non-translating ribosomes from L. mexicana promastigote stages and specifically exclude any RNA binding proteins (RBPs) interacting with an mRNA mid-translation. Further optimisation is required to realise this strategy. Bioinformatic analyses of mass spectrometry data have enabled comparisons of the translational machinery between the procyclic (PCF) and the metacyclic promastigotes (META). This has highlighted differentially abundant proteins involved in specific processes, which are key to cell regulation, translation and differentiation. It also illustrates how post-translational modifications (PTM) promote parasitic adaptation; specifically, protein kinase activity and phosphoregulation in META differentiation and metacyclogenesis. Key findings from our mass spectrometry include the enrichment of CRK9, RDK2 kinases and serine/threonine phosphatases in META.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.047
GPT teacher head0.189
Teacher spread0.142 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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