MétaCan
Menu
Back to cohort
Record W4409036512 · doi:10.1002/cyto.b.22234

Highlights March 2025

2025· article· en· W4409036512 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCytometry Part B Clinical Cytometry · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

[Color figure can be viewed at wileyonlinelibrary.com] This issue of Cytometry Part B Clinical Cytometry presents a rather eclectic selection of flow cytometry-related topics. As a very useful opening, Oak et al. (2025) provide detailed information about the way these authors reorganized their workflow with the aim of providing an integrated diagnosis, both for current immunophenotyping (i.e., lymphocyte subsets) or CD34+ cells enumeration, and for the pathologist-dependent management and interpretation of hematological malignancies. These two aspects were previously taken care of by different Beaker platforms, respectively devoted to clinical pathology (CP) and anatomic pathology (AP) (Sergi, 2022; Tan et al., 2017). Integration of these platforms, developed by the broadly used Epic system (Verona, WI) that provides electronic health records, resulted in the new Beaker system presented in this publication. The CP and AP Beaker platforms are no longer separated but belong to the same structure within a paperless workflow. Ultimately, connection to the laboratory information system (LIS) results in a complete report of patient laboratory data. Because of the widespread use of these solutions in US laboratories, this document opens the way to a broad implementation of the proposed algorithms. Of course, each step needs to be customized as not all institutions immunophenotyping facilities use the 30 panels displayed by the authors, and several other idiosyncrasies need to be considered. Nonetheless, in an era where artificial intelligence is providing increasing help for routine or even sophisticated tasks (Ng et al., 2024), optimizing its use by such a workflow will be of great value. This would not only lessen the burden of sample and assays tracing but also accelerate the delivery of laboratory information critical for customized patient management in the clinic. This paper is followed by a report by the Canadian group of Terra et al. (2025) who compared the 2013 standardized Euroflow recommendations (Van Dongen et al., 2012) to a non-standardized approach for the immunophenotyping of hematological malignancies. These authors reanalyzed 43 samples that had been cryopreserved, using Euroflow panels that had not been used initially. Of note, these samples had been tested before current reclassifications of hematological malignancies. For almost half of these samples (47%), a refined diagnosis was obtained, yet this would have led to a different clinical management of the patients in only 3 cases. Interestingly, 5 cases were reclassified as 3 ETP-ALL and 2 typical BPDCN. Nevertheless, this manuscript emphasizes the use of a comprehensive immunophenotypic panel for acute leukemias, as promoted both by Euroflow (van Dongen et al., 2012) and the European LeukemiaNet (Béné et al., 2011). The third original paper of this issue explains how the 10 color ClearLab panel (Hedley et al., 2021) can be helpful in the characterization of paucicellular samples. This issue is indeed critical since morphological analysis, even on samples enriched by centrifugation, often is at a loss in identifying the cellular components of such samples. Here, Kajstura et al. (2025) demonstrate how flow cytometry is highly valuable in such circumstances. Based on the Food and Drug administration approved recommendations of testing 3 × 106 cells (US FDA, 2017), these authors performed dilutions down to 64 fold and show that there is no change in fluorescence intensity and therefore detection of cells of interest. They used highly relevant samples of bone marrow and lymph node suspensions and demonstrated the efficacy of flow cytometry in samples containing as little as 4 × 103 cells per μL. Clear images of CD19+CD5+ monotypic cells from lineage lymphoproliferative disorders are displayed. This manuscript highlights the sometimes forgotten yet long ago demonstrated exquisite specificity of flow cytometry in detecting immunophenotypic normal/abnormal features. Moving along, the fourth original paper (Bonneville et al., 2025) tackles the critical issue of hemodilution. Several solutions have been proposed over many years to take into account the fact that bone marrow aspiration progressively leads to the collection of a more and more hemodiluted sample. Cytomorphologists rightly required long ago to be provided with smears of the first aspirated drops. Furthermore, all disciplines (flow cytometry, cytogenetics and, accountably to a lesser degree, and molecular hematology) claimed that they wanted the “cleanest” first aspiration. In the paper from Bonneville et al., dilution experiments were performed on 3 from 51 samples and demonstrated that the solution proposed by Holdrinet et al. (1980) provides the best evaluation of true bone marrow cell evaluation. This method takes into account both hemoglobin levels and nucleated blood cells. Here, the authors conclude on the superiority of the modified Holdrinet method to properly evaluate bone marrow cell populations, excluding the peripheral blood compartment. In the fifth publication of this issue (Mestrum et al., 2025), the focus moved to bone marrow evaluation of the expression of Bcl2 and KI67 in samples from patients suspected of myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Comparing 25 samples of MDS and 25 from AML to 50 normal bone marrow samples obtained through hip surgery, the authors conclude that their work leads to a better understanding of the pathophysiology and progression of MDS and AML and explains the low response rate to chemotherapy of these patients. The increasing cytopenia due to the low proliferative activity seen in AML patients may also explain the high therapy-related mortality and high overall mortality. Whether intranuclear Ki67 and Bcl2 should be incorporated in screening panels remains an open issue. Finally, far away from leukocyte disorders, Souissi et al. (2025), on large cohorts of patients and controls, demonstrated that flow cytometry can readily identify patients with G6PD deficiency with better outputs than molecular assays, based on previously published methods (Kahn et al., 2015). The test is based on the GSPD-dependent transformation of methemoglobin into oxyhemoglobin, the latter being transformed into ferrylhemoglobin, yielding a bright fluorescence upon the addition of hydrogen peroxide. All transformations of hemoglobin are performed for each sample until the assessment of GDPD-normal function resulting in bright fluorescence. In letters to the Editor, Shi et al. (2025) draw attention to the efficient use of both anti-TRBC1 and TRBC2 antibodies to safely characterize clonal T-cell proliferations. These authors tested 100 T-lineage cell proliferations and demonstrated that some dim labeling for TRBC1 is in fact nonspecific, clonal cells expressing TRBC2. Their 11 color combinations (for T-cells or Sezary customized) contain the optimal combination identifying TRBC1 and 2 as well as ©™ T-cell receptors. Proper identification of the TCR beta chain of T-lineage lymphoproliferative disorders is both useful for diagnosis and possibly for therapy in a near future with antibody drug conjugates targeting TRBC1 (Nichakawade et al., 2024). Daniel Mazza Matos (2025) reports four new cases of “vanishing counting beads” (Brando et al., 2001) an unexplained phenomenon occurring for some patients in single platform counting of CD34+ cells in leukapheresis samples. This can be avoided by adding proteins (bovine or human plasma) to the tested sample. This rare event (0.5%) can be suspected by comparing the single platform count to that calculated from the white blood cell count of the leukapheresis bag. The third letter, by Zhang et al. (2025), reports on a rare case of acute myeloid leukemia with a PICALM::MLLT10 fusion gene, PHF6 and NF1 mutations, associated with CD7 expression. The few occurrences of this type of leukemia have been shown to be of poor prognosis, with, as in the reported case, failure of rescue by allogeneic hematopoietic stem cell transplantation. All in all, this highlight issue provides a broad array of flow cytometry applications in various pathological conditions, ensuring fruitful reading.

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.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.008
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.004

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 head0.064
GPT teacher head0.432
Teacher spread0.369 · 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