MétaCan
Menu
Back to cohort
Record W4205841742 · doi:10.1186/s13223-021-00596-5

The frequencies of peripheral blood CD5+CD19+ B cells, CD3−CD16+CD56+ NK, and CD3+CD56+ NKT cells and serum interleukin-10 in patients with multiple sclerosis and neuromyelitis optica spectrum disorder

2022· article· en· W4205841742 on OpenAlexvenueno aff
Leila Khani, Mir Hadi Jazayeri, Reza Nedaeinia, Mahmood Bozorgmehr, Seyed Masood Nabavi, Gordon A. Ferns

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersIran University of Medical Sciences
KeywordsImmunologyCD3Natural killer T cellCD5CD19CD16MedicineImmune systemBiologyFlow cytometryCD8

Abstract

fetched live from OpenAlex

Abstract Background Multiple sclerosis (MS) and neuromyelitis optica syndrome disease (NMOSD) are inflammatory diseases of the central nervous system. The pathogenesis and treatments for these two conditions are very different. Natural killer (NK) and natural killer T (NKT) cells are immune cells with an important role in shaping the immune response. B cells are involved in antigen presentation as well as antibody and cytokine production. There is conflicting evidence of the roles of NK, NKT, and B cells in the two conditions. We aimed to compare the frequency of CD3−CD16+CD56+NK, CD3+CD56+NKT, and CD5+CD19+B cells in the peripheral blood and serum Interleukin-10 (IL-10) in patients with MS and NMOSD. Methods CD19+CD5+B, CD3−CD16+CD56+NK, and CD3+CD56+NKT cells were quantitated by flow cytometry in 15 individuals with Interferon-Beta (IFN-β) treated relapsing–remitting MS (RRMS), 15 untreated RRMS, and 15 NMOSD patients as well as 30 healthy controls (HC). Serum IL-10 was measured using an enzyme-linked immunosorbent assay (ELISA). Results The percentage of CD3−CD56+CD16+NK cells in the peripheral blood of IFN-treated MS (1.81 ± 0.87) was significantly lower than for untreated RRMS (4.74 ± 1.80), NMOSD (4.64 ± 1.26) and HC (5.83 ± 2.19) (p < 0.0001). There were also differences for the percentage of CD3−CD16+and CD3−CD56+cells (p < 0.001 and p < 0.0007; respectively). IFN-treated RRMS (2.89 ± 1.51) had the lowest proportion of CD3+CD56+among the study groups (p < 0.002). Untreated RRMS (5.56 ± 3.04) and NMOSD (5.47 ± 1.24) had higher levels of CD3+CD56+than the HC (3.16 ± 1.98). The mean percentage of CD19+CD5+B cells in the peripheral blood of untreated RRMS patients (1.32 ± 0.67) was higher compared to the patients with NMOSD (0.30 ± 0.20), HC (0.5 ± 0.22) and IFN-treated RRMS (0.81 ± 0.17) (p < 0.0001). Serum interleukin-10 was significantly higher in the IFN-treated RRMS (8.06 ± 5.39) and in HC (8.38 ± 2.84) compared to untreated RRMS (5.07 ± 1.44) and the patients with NMOSD (5.33 ± 2.56) (p < 0.003). Conclusions The lower proportion of CD3−CD56+CD16+NK and CD3+CD56+cells in peripheral blood of IFN-treated RRMS compared to other groups suggests the importance of immunomodulation in patients with RRMS disorder. Based on the differences in CD19+CD5+B cells and serum IL-10 between patients and HC, supplementary assessments could be of value in clarifying their roles in autoimmunity.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.252
Teacher spread0.233 · 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 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

Citations21
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAllergy Asthma and Clinical ImmunologySame topicMultiple Sclerosis Research StudiesFrench-language works237,207