MétaCan
Menu
Back to cohort
Record W2912258931 · doi:10.3390/cells8020115

Recent Insights into NCL Protein Function Using the Model Organism Dictyostelium discoideum

2019· review· en· W2912258931 on OpenAlexafffund
Meagan D. McLaren, Sabateeshan Mathavarajah, Robert J. Huber

Bibliographic record

VenueCells · 2019
Typereview
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaBanting Research Foundation
KeywordsDictyosteliumDictyostelium discoideumBiologyModel organismMulticellular organismBatten diseaseOrganismNeurodegenerationAmoeba (genus)GeneGenomeComputational biologyNeuronal ceroid lipofuscinosisFunction (biology)GeneticsNeuroscienceDiseaseCell biologyMedicine

Abstract

fetched live from OpenAlex

The neuronal ceroid lipofuscinoses (NCLs) are a group of devastating neurological disorders that have a global distribution and affect people of all ages. Commonly known as Batten disease, this form of neurodegeneration is linked to mutations in 13 genetically distinct genes. The precise mechanisms underlying the disease are unknown, in large part due to our poor understanding of the functions of NCL proteins. The social amoeba Dictyostelium discoideum has proven to be an exceptional model organism for studying a wide range of neurological disorders, including the NCLs. The Dictyostelium genome contains homologs of 11 of the 13 NCL genes. Its life cycle, comprised of both single-cell and multicellular phases, provides an excellent system for studying the effects of NCL gene deficiency on conserved cellular and developmental processes. In this review, we highlight recent advances in NCL research using Dictyostelium as a biomedical model.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.103
GPT teacher head0.357
Teacher spread0.254 · 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
GenreReview

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

Citations25
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueCellsSame topicLysosomal Storage Disorders ResearchFrench-language works237,207