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Record W2495915470 · doi:10.3389/fnmol.2016.00057

Ammonia as a Potential Neurotoxic Factor in Alzheimer's Disease

2016· review· en· W2495915470 on OpenAlexafffund
Aida Adlimoghaddam, Mohammad Golam Sabbir, Benedict C. Albensi

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2016
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersNatural Sciences and Engineering Research Council of CanadaAlzheimer's SocietyResearch Manitoba
KeywordsGlutamatergicNeuroscienceNeurotoxinAmmoniaNeurotransmissionDiseaseGlutamate receptorNeurotoxicityAlzheimer's diseaseExcitatory postsynaptic potentialBiologyMedicineInhibitory postsynaptic potentialToxicityEndocrinologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Ammonia is known to be a potent neurotoxin that causes severe negative effects on the central nervous system. Excessive ammonia levels have been detected in the brain of patients with neurological disorders such as Alzheimer disease (AD). Therefore, ammonia could be a factor contributing to the progression of AD. In this review, we provide an introduction to the toxicity of ammonia and putative ammonia transport proteins. We also hypothesize how ammonia may be linked to AD. Additionally, we discuss the evidence that support the hypothesis that ammonia is a key factor contributing to AD progression. Lastly, we summarize the old and new experimental evidence that focuses on energy metabolism, mitochondrial function, inflammatory responses, excitatory glutamatergic, and GABAergic neurotransmission, and memory in support of our ammonia-related hypotheses of AD.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.033
GPT teacher head0.347
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations100
Published2016
Admission routes2
Has abstractyes

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