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Record W2951606532 · doi:10.2217/bmm-2017-0374

BDNF and Tau as Biomarkers of Severity in Multiple Sclerosis

2018· article· en· W2951606532 on OpenAlexfundno aff
Azul Islas‐Hernández, Hugo Aguilar-Talamantes, Brenda Bertado-Cortés, Georgina de Jesus Mejia-delCastillo, Raúl Carrera-Pineda, Carlos Cuevas-García, Paola Torre

Bibliographic record

VenueBiomarkers in Medicine · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersMinistère de la Santé et des Services sociaux
KeywordsMedicineMultiple sclerosisInternal medicineOncologyImmunology

Abstract

fetched live from OpenAlex

AIM: Determine if serum levels of tau and BDNF can be used as severity biomarkers in multiple sclerosis (MS). PATIENTS & METHODS: Subjects with MS, older than 18 and younger than 55 years old were included; 74 patients with a diagnosis of relapsing-remitting MS, 11 with secondary-progressive MS, and 88 controls were included. Total tau and BDNF were measured by Western blot. RESULTS: Increased tau and decreased BDNF in MS patients compared with controls was found. Total-tau has a peak in relapsing-remitting MS, the second decile of the multiple sclerosis severity score, and in the lowest expanded disability status scale and is no different than controls for secondary-progressive MS patients and the most severe cases of MS. CONCLUSION: BDNF is a good biomarker for diagnosis of MS but not for severity or progression. Tau appears to have a more active role in the progression of MS.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.153
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.070
GPT teacher head0.299
Teacher spread0.229 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

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