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Record W1981792498 · doi:10.1002/cyto.a.20453

Cytometry in malaria: Moving beyond Giemsa

2007· letter· en· W1981792498 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCytometry Part A · 2007
Typeletter
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsGiemsa stainMalariaAcridine orangeCytometryDiagnosis of malariaPlasmodium falciparumBiologyBlood smearStainingFlow cytometryStainPathologyMedicineImmunology

Abstract

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The article by Bhakdi et al. in this issue of Cytometry Part A on optimizing flow cytometric detection of mouse malaria parasites (1) is, somewhat remarkably, one of only a few dozen publications in the literature (2-54) in which cytometry is applied to the diagnosis, treatment, or biology of this protean disease. The World Health Organization estimates that 350–500 million cases of malaria occur annually, causing at least a million deaths. Of the 270–400 million cases of the severest form of the disease, due to the parasite Plasmodium falciparum, about 70% of these cases are in Africa and about 20% in southeast Asia (55). The diagnosis of malaria is primarily cell-based and involves visual detection of intraerythrocytic parasites by transmitted light microscopy in a peripheral blood smear stained with Giemsa's stain, a mixture of eosin and methylene azure dyes first described over a century ago (56). Identification of the various stages of parasites depends heavily on morphologic information, requiring observation at high power. Although it has been known for many years that methods based on fluorescence microscopy, using acridine orange (57-59) and other dyes (60-62), compare in accuracy with light microscopy (63) and may require less time and a less skilled observer, the required fluorescent microscope has, until recently, been too expensive for most laboratories in areas where malaria is most prevalent. If malaria were more common in affluent countries, we might expect that cytometry would, by now, have supplanted microscopy of Giemsa-stained smears for malaria diagnosis, just as it has for differential leukocyte counting and reticulocyte counting. Demonstrations of the efficacy of flow cytometry for detection, characterization, and counting of malaria parasites date back to the 1970s (20, 21); acridine orange was used for staining in apparatus with 488 nm laser sources, whereas Hoechst dyes, which are more DNA-selective, were favored where UV excitation was available. It was shown in the mid-1980s that different developmental stages of P. falciparum could be identified by flow cytometry based solely on nucleic acid content, without recourse to morphologic information (25, 27); unfortunately, most people in both the malariology and cytometry communities seem to be unaware of this highly significant finding. The genome of P. falciparum was sequenced in 2002 (64); the haploid genome is approximately 23 Mbp in size and contains 80% adenine + thymine (A+T), the highest such percentage found in any organism analyzed to date. P. vivax, P. malariae, and P. ovale, the other species that cause malaria in humans, have not been completely sequenced but appear to have haploid genome sizes of about 30 Mbp and contain about 60% A+T (65, 66). In clinical diagnosis, it is important to distinguish between malaria caused by P. falciparum and malaria due to the other species. In the former, peripheral blood contains a preponderance of haploid and near-haploid forms; in the latter, the later stages of the parasites, with DNA content as much as 16 times as high as that of the haploid forms, are also common in peripheral blood. One would therefore expect to be able to both detect malaria parasites at low levels of parasitemia and distinguish between cases due to P. falciparum and those due to other species by fluorescence cytometry using a DNA-selective stain. Many recent publications on cytometry in malaria (e.g.,16, 19, 39) have used asymmetric cyanine nucleic acid dyes of the SYTO and YOYO series (Molecular Probes/Invitrogen, Eugene, OR). These dyes, structurally related to thiazole orange (4), can be excited with blue or blue-green (488 nm) light and emit in the green or yellow spectral region. Unlike acridine orange, which quenches on binding to nucleic acids, the cyanines enhance fluorescence substantially on binding, typically by a factor of 1,000 or more; this results in lower background fluorescence, which makes it easier to detect smaller (haploid) forms of the malaria parasite. The cyanine dyes mentioned earlier, however, are not DNA-selective; other Molecular Probes products, e.g., Pico Green and Vybrant DyeCycle Green, have similar fluorescence characteristics and are highly DNA-selective. The last named dye also stains DNA stoichiometrically without the need for permeabilization or fixation and may well prove optimal for staining malaria parasites in both diagnostic and experimental settings. Although fluorescence microscopes can now be made substantially less expensive by using light-emitting diodes (LEDs) as light sources (67-69), the accuracy and precision of malaria diagnosis by fluorescence microscopy are still constrained by the limitations of the human observer (70). We believe that low-resolution fluorescence imaging cytometry, shown feasible in 1994 (71) and now possible to implement in a small, rugged, energy-efficient, and extremely inexpensive form using LED illumination and consumer-grade digital camera chips for detection (15,72), may soon be able to bring effective cytometric diagnosis to the resource-poor areas in which it is most sorely needed, as the malaria pandemic is not likely to subside in the foreseeable future. We encourage our colleagues to contemplate any and all cytometric approaches, including digital imaging, to bring malaria under control in the southern hemisphere.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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