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Record W4386022837 · doi:10.1371/journal.pone.0288138

Tau protein aggregation associated with SARS-CoV-2 main protease

2023· article· en· W4386022837 on OpenAlexfundno aff
Raphael J. Eberle, Mônika A. Coronado, Ian Gering, Simon Sommerhage, Karolina Korostov, Anja Stefanski, Kai Stühler, Victoria Kraemer‐Schulien, Lara Blömeke, Oliver Bannach, Dieter Willbold

Bibliographic record

VenuePLoS ONE · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftHelmholtz-GemeinschaftWeston Brain InstituteALS AssociationAlzheimer's AssociationMichael J. Fox Foundation for Parkinson's Research
KeywordsProteasesProteaseViral replicationBiologyVirologyNeuropathologyVirusImmune systemCell biologyEnzymeBiochemistryImmunologyMedicine

Abstract

fetched live from OpenAlex

The primary function of virus proteases is the proteolytic processing of the viral polyprotein. These enzymes can also cleave host cell proteins, which is important for viral pathogenicity, modulation of cellular processes, viral replication, the defeat of antiviral responses and modulation of the immune response. It is known that COVID-19 can influence multiple tissues or organs and that infection can damage the functionality of the brain in multiple ways. After COVID-19 infections, amyloid-β, neurogranin, tau and phosphorylated tau were detected extracellularly, implicating possible neurodegenerative processes. The present study describes the possible induction of tau aggregation by the SARS-CoV-2 3CL protease (3CLpro) possibly relevant in neuropathology. Further investigations demonstrated that tau was proteolytically cleaved by the viral protease 3CL and, consequently, generated aggregates. However, more evidence is needed to confirm that COVID-19 is able to trigger neurodegenerative diseases.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.280
Teacher spread0.237 · 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.

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

Citations16
Published2023
Admission routes1
Has abstractyes

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