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Record W3156031737 · doi:10.1038/s41420-021-00458-4

Necroptosis in ALS: a hot topic in-progress

2021· article· en· W3156031737 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCell Death Discovery · 2021
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchChildren's Hospital FoundationFondation de l'Hôpital de Montréal pour enfantsGovernment of CanadaFondation des EtoilesRégion Auvergne-Rhône-Alpes
KeywordsNecroptosisBiologyProgrammed cell deathApoptosisGenetics

Abstract

fetched live from OpenAlex

Interest in potential implications of necroptosis (Fig. 1 )—i.e., a recently uncovered programmed cell death pathway—in neurodegenerative diseases has been growing over the recent years 1 , 2 . However, very few studies addressed its role in amyotrophic lateral sclerosis (ALS). Dominguez et al. 3 recently brought some negative findings on this topic: (i) the genetic inactivation of receptor-interacting protein kinase (RIPK)1 did not protect against motor neuron degeneration in the superoxide dismutase (SOD)1 model of ALS and (ii) phosphorylated (p)-RIPK1 did not accumulate in the spinal cords of ALS compared to non-ALS patients. These findings raise doubts about the implication of necroptosis in the pathophysiology of ALS. In contrast, other studies detected robust activation of RIPK1, RIPK3, and mixed lineage kinases domain-like (MLKL) proteins in preclinical as well as clinical studies of ALS 4 , 5 , 6 , 7 . The discrepancies between these studies 4 , 5 and others 3 , 8 might be explained by (i) the use of western blotting in whole-tissue extracts 4 , 5 , 8 versus in situ immunolabelling targeting motor neurons 7 , (ii) the removal of circulating blood cells—a rich source of necroptotic markers 9 —in some studies but not in others, (iii) the various time frame of tissue sampling, which matches or not the transient expression of necroptotic markers 10 , or (iv) technical limitations in the availability and specificity of in vivo tools of detection of necroptotic markers 3 , 4 , 5 , 7 , 8 . Fig. 1: Schematic overview of necroptotic cell death. Necroptosis is triggered by inflammatory mediators, including TNF-α and FasL. Upon the recruitment of adapter proteins, the phosphorylation of RIPK1 is induced. The necrosome is composed of interaction and activation (i.e. phosphorylation) of RIPK1, RIPK3, and MLKL. Necroptosis of the cell is induced by mitochondrial fission through interaction of MLKL with mitochondrial phosphatase PGAM5 and Drp1 recruitment. Phosphorylated MLKL also triggers cell death through the disruption of the plasma membrane integrity 1 , 2 . Other mechanisms by which MLKL induces cell death remains to be elucidated. Pharmacological or genetic modulations ( ⊥ ) of necroptosis signaling can target RIPK1, RIPK3, MLKL, as well as their phosphorylated forms 12 , 13 , 14 . Drp1 dynamin-related protein 1, FADD Fas-associated protein with Death Domain, Fas-L Fas-ligand, MLKL mixed lineage kinases domain-like, p phosphorylated, PGAM5 phosphoglycerate mutase family member 5, RIPK receptor-interacting protein kinases, TNFα tumor necrosis factor α, TNFR1 tumor necrosis factor receptor 1, TRADD tumor necrosis factor receptor type 1-associated death. Full size image

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.494

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 studies0.0000.000
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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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