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Record W6958670783 · doi:10.6084/m9.figshare.c.7086327

Correlative light-electron microscopy methods to characterize the ultrastructural features of the replicative and dormant liver stages of Plasmodium parasites

2024· other· en· W6958670783 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldMathematics
TopicMathematics and Applications
Canadian institutionsNovartis (Canada)
Fundersnot available
KeywordsPlasmodium bergheiPlasmodium (life cycle)Parasite hostingHepatocyteMalariaOrganelleUltrastructureProtozoa

Abstract

fetched live from OpenAlex

Abstract Background The infection of the liver by Plasmodium parasites is an obligatory step leading to malaria disease. Following hepatocyte invasion, parasites differentiate into replicative liver stage schizonts and, in the case of Plasmodium species causing relapsing malaria, into hypnozoites that can lie dormant for extended periods of time before activating. The liver stages of Plasmodium remain elusive because of technical challenges, including low infection rate. This has been hindering experimentations with well-established technologies, such as electron microscopy. A deeper understanding of hypnozoite biology could prove essential in the development of radical cure therapeutics against malaria. Results The liver stages of the rodent parasite Plasmodium berghei, causing non-relapsing malaria, and the simian parasite Plasmodium cynomolgi, causing relapsing malaria, were characterized in human Huh7 cells or primary non-human primate hepatocytes using Correlative Light-Electron Microscopy (CLEM). Specifically, CLEM approaches that rely on GFP-expressing parasites (GFP-CLEM) or on an immunofluorescence assay (IFA-CLEM) were used for imaging liver stages. The results from P. berghei showed that host and parasite organelles can be identified and imaged at high resolution using both CLEM approaches. While IFA-CLEM was associated with more pronounced extraction of cellular content, samples’ features were generally well preserved. Using IFA-CLEM, a collection of micrographs was acquired for P. cynomolgi liver stage schizonts and hypnozoites, demonstrating the potential of this approach for characterizing the liver stages of Plasmodium species causing relapsing malaria. Conclusions A CLEM approach that does not rely on parasites expressing genetically encoded tags was developed, therefore suitable for imaging the liver stages of Plasmodium species that lack established protocols to perform genetic engineering. This study also provides a dataset that characterizes the ultrastructural features of liver stage schizonts and hypnozoites from the simian parasite species P. cynomolgi. Graphical Abstract

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.793
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0090.000

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 head0.044
GPT teacher head0.373
Teacher spread0.329 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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