MétaCan
Menu
Back to cohort
Record W1991653634 · doi:10.1038/srep01129

Novel TPR-containing subunit of TOM complex functions as cytosolic receptor for Entamoeba mitosomal transport

2013· article· en· W1991653634 on OpenAlexfundno aff
Takashi Makiuchi, Fumika Mi‐ichi, Kumiko Nakada‐Tsukui, Tomoyoshi Nozaki

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldMedicine
TopicAmoebic Infections and Treatments
Canadian institutionsnot available
FundersJapan Science and Technology AgencyMinistry of Health, Labour and WelfareMinistry of Education, Culture, Sports, Science and TechnologyJapan Society for the Promotion of ScienceDalhousie UniversityJapan Health Sciences Foundation
KeywordsCytosolProtein subunitReceptorComputational biologyBiologyCell biologyChemistryBioinformaticsBiochemistryGeneEnzyme

Abstract

fetched live from OpenAlex

Under anaerobic environments, the mitochondria have undergone remarkable reduction and transformation into highly reduced structures, referred as mitochondrion-related organelles (MROs), which include mitosomes and hydrogenosomes. In agreement with the concept of reductive evolution, mitosomes of Entamoeba histolytica lack most of the components of the TOM (translocase of the outer mitochondrial membrane) complex, which is required for the targeting and membrane translocation of preproteins into the canonical aerobic mitochondria. Here we showed, in E. histolytica mitosomes, the presence of a 600-kDa TOM complex composed of Tom40, a conserved pore-forming subunit, and Tom60, a novel lineage-specific receptor protein. Tom60, containing multiple tetratricopeptide repeats, is localized to the mitosomal outer membrane and the cytosol, and serves as a receptor of both mitosomal matrix and membrane preproteins. Our data indicate that Entamoeba has invented a novel lineage-specific shuttle receptor of the TOM complex as a consequence of adaptation to an anaerobic environment.

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 categoriesInsufficient payload (model declined to judge)
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 score0.565
Threshold uncertainty score0.998

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)0.0030.000

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 head0.032
GPT teacher head0.279
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.

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

Citations40
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueScientific ReportsSame topicAmoebic Infections and TreatmentsFrench-language works237,207