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Questions on unusual Mimivirus-like structures observed in human cells

2017· preprint· en· W2601361529 on OpenAlexaff
Elena Angela Lusi, Dan Maloney, Federico Caicci, P. Guarascio

Bibliographic record

VenueF1000Research · 2017
Typepreprint
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsBioinformatics Solutions (Canada)
Fundersnot available
KeywordsBiologyGiant VirusImmunogold labellingVirologyUltrastructureAnatomyGenomeGeneticsGene

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background:</ns4:bold> Mimiviruses or giant viruses that infect amoebas have the ability to retain the Gram stain, which is usually used to colour bacteria. There is some evidence suggesting that Mimiviruses can also infect human cells. Guided by these premises, we performed a routine Gram stain on a variety of human specimens to see if we could detect the same Gram positive blue granules that identify Mimiviruses in the amoebas. <ns4:bold>Methods:</ns4:bold> We analysed 24 different human specimens (liver, brain, kidney, lymph node and ovary) using Gram stain histochemistry, electron microscopy immunogold, high resolution mass spectrometry and protein identification. <ns4:bold>Results:</ns4:bold> We detected in the human cells Gram positive granules that were distinct from bacteria. The fine blue granules displayed the same pattern of the Gram positive granules that diagnose Mimiviruses in the cytoplasm of the amoebas. Electron microscopy confirmed the presence of human Mimiviruses-like structures and mass spectrometry identified histone H4 peptides, which had the same footprints as giant viruses. However, some differences were noted: the Mimivirus-like structures identified in the human cells were ubiquitous and manifested a distinct mammalian retroviral antigenicity. <ns4:bold>Conclusions:</ns4:bold> Our main hypotheses are that the structures could be either giant viruses having a retroviral antigenicity or ancestral cellular components having a viral origin. However, other possible alternatives have been proposed to explain the nature and function of the newly identified structures. </ns4:p>

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.087
GPT teacher head0.374
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

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

Citations10
Published2017
Admission routes1
Has abstractyes

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