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Record W2090261099 · doi:10.5858/arpa.2011-0343-le

Systemic Inflammation or Monoclonal Gammopathy?

2011· letter· en· W2090261099 on OpenAlexaff
Yu Chen

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2011
Typeletter
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsHorizon Health NetworkDr. Everett Chalmers Regional Hospital
Fundersnot available
KeywordsMonoclonal gammopathyInflammationMonoclonal gammopathy of undetermined significanceMedicineParaproteinemiasPathologyMonoclonal antibodyMonoclonalImmunologyAntibody

Abstract

fetched live from OpenAlex

To the Editor.—It is good laboratory practice to perform oligoclonal banding analysis with parallel cerebrospinal fluid (CSF) and serum samples.1 The most sensitive method for the detection of oligoclonal immunoglobulin (Ig) bands is isoelectric focusing, followed by IgG immunofixation to denote local IgG synthesis. Intrathecal synthesis of immunoglobulins manifested as oligoclonal banding only in CSF typically presents in about 90% of multiple sclerosis cases.1 In 2010, the College of American Pathologists (CAP) began offering a new proficiency survey on oligoclonal bands, OLI, which includes paired CSF and serum samples for laboratories performing these assays. Through these proficiency testing and education endeavors, participating laboratories have demonstrated improved performance. For example, many laboratories now realize that identical multiple bands in both CSF and serum (mirror pattern) may indicate a systemic immune reaction rather than typical multiple sclerosis.2 However, there are still many discrepancies and difficulties among different laboratories in interpreting the CSF/serum mirror pattern, as indicated by the 2 most recent CAP surveys.The sample OLI-06 from the M-B 2010 survey was analyzed by isoelectric focusing, as shown in Figure 1, A. Of the total 129 participating laboratories, 120 laboratories (93%) reported it as a systemic immune reaction (inflammation), whereas 6 laboratories (4.7%) found the presence of monoclonal proteins.3 Similarly, the sample OLI-01 from the M-A 2011 survey was analyzed by isoelectric focusing as shown in Figure 2, A. Of the total 144 participating laboratories, 40 laboratories (27.8%) reported it as a systemic immune reaction (inflammation), whereas 96 laboratories (66.7%) found the presence of monoclonal proteins.4 Eventually, the CAP survey committee graded these 2 proficiency tests as “lack of participant or referee consensus” because of failure to reach a minimum 90% consensus.Actually, serum immunofixation on the 2010 M-B OLI-06 serum sample revealed one IgG-λ and 2 IgG-κ monoclonal bands in γ zone (Figure 1, B). A monoclonal IgG-κ band with a polyclonal background was also demonstrated on the 2011 M-A OLI-01 serum sample (Figure 2, B).The Committee of the European Concerted Action for Multiple Sclerosis published a consensus report on 5 typical types of CSF and serum isoelectric focusing patterns.5 There are 2 abnormal mirror CSF/serum patterns, that is, type 4, identical oligoclonal bands in CSF and serum indicating systemic inflammation, and type 5, monoclonal bands in CSF and serum suggesting monoclonal protein; neither demonstrates local IgG synthesis.5 Monoclonal gammopathy should be differentiated from systemic inflammation if mirrored IgG bands are present in both CSF and serum. Monoclonal proteins tend to form clusters and are more prominent, with higher concentrations and stronger immunoreaction. Immunofixation is the definitive test for evaluating any equivocal bands. In conclusion, the mirror CSF/serum pattern is indicative of serum proteins (including immunoglobulins and monoclonal proteins) entering the CSF by passive diffusion or through disruption of the blood-brain barrier.

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)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0030.001
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0110.006

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 head0.049
GPT teacher head0.309
Teacher spread0.259 · 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 designCase report
Domainnot available
GenreCommentary

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

Citations5
Published2011
Admission routes1
Has abstractyes

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