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Record W2102879530 · doi:10.1155/2013/748127

Dynamics of B-Cell Populations in CSF and Blood in Patients Treated with a Combination of Rituximab and Mitoxantrone

2013· article· en· W2102879530 on OpenAlexaff
Evgeniy Evdoshenko, А. L. Maslyanskiy, С. В. Лапин, L. G. Zaslavsky, Ruth Dobson, Арег А. Тотолян, A A Skoromets, Amit Bar‐Or

Bibliographic record

VenueISRN Neurology · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMitoxantroneMethylprednisoloneRituximabMedicineCD19RegimenInternal medicineMultiple sclerosisGastroenterologyImmunologyChemotherapyPeripheral bloodLymphoma

Abstract

fetched live from OpenAlex

Background. Mitoxantrone (MTX) and Rituximab (RTX) are successfully used for treatment of multiple sclerosis (MS) and can be combined to increase efficacy. Objective. We used MTX, RTX, and methylprednisolone in a single combined regiment and observed patients prospectively. Methods. We present results of observational pilot study of combined therapy of RTX and MTX in 28 patients with active MS. Therapeutic protocol consisted of two infusions within 14 days. First infusion was 1000 mg methylprednisolone (MP) IV, 1000 mg RTX IV, and 20 mg MTX IV. On day 14, 1000 mg MP IV and 1000 mg RTX IV were given. Patients were followed prospectively from 12 to 48 months. Results and Conclusion. There were no relapses among all 28 patients during the observation period. B-cell depletion of CD19+ and CD19+/CD27+ memory B-cell subpopulation in both compartments was confirmed in all patients at 6 months. We found a more rapid reconstitution of B cells in the CSF than in the peripheral blood and longstanding depression of CD19+CD27+ memory B-cell. Conclusion. Effectiveness of combined regimen of RTX and MTX could be related to longstanding depletion of CD19+CD27+ memory B-cell subset.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.210

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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 designObservational
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

Citations8
Published2013
Admission routes1
Has abstractyes

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