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Record W2013576761 · doi:10.1021/pr2005296

Proteomic Profiling of the Influence of Iron Availability on<i>Cryptococcus gattii</i>

2011· article· en· W2013576761 on OpenAlexaboutno aff
J. Crestani, Paulo C. Carvalho, Xuemei Han, Adriana Seixas, Leonardo Broetto, Juliana de Saldanha da Gama Fischer, Charley Christian Staats, Augusto Schrank, John R. Yates, Marilene Henning Vainstein

Bibliographic record

VenueJournal of Proteome Research · 2011
Typearticle
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of General Medical Sciences
KeywordsCryptococcus gattiiBiologyCryptococcosisProteomicsCryptococcus neoformansCryptococcusYeastMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

Iron is essential and ubiquitous in living organisms. The competition for this micronutrient between the host and its pathogens has been related to disease establishment. Cryptococcus gattii is an encapsulated yeast that causes cryptococcosis mainly in immunocompetent individuals. In this study, we analyzed the proteomic profile of the C. gattii R265 Vancouver Island isolate under iron-depleted and -repleted conditions by multidimensional protein identification technology (MudPIT) and by 2D-GE. Proteins and key mechanisms affected by alteration of iron levels such as capsule production, cAMP-signaling pathway, response to stress, and metabolic pathways related to mitochondrial function were identified. Our results also show both proteomic methodologies employed to be complementary.

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 score0.005
Threshold uncertainty score0.010

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 head0.121
GPT teacher head0.378
Teacher spread0.257 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

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