MétaCan
Menu
Back to cohort
Record W2029070586 · doi:10.1002/cyto.b.10014

Stability of currently used cytometers facilitates the identification of pipetting errors and their volumetric operation: “Time” can tell all

2003· review· en· W2029070586 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 B Clinical Cytometry · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsHealth Canada
Fundersnot available
KeywordsPipetteContext (archaeology)Computer scienceStability (learning theory)Sample (material)Biomedical engineeringStatisticsMathematicsMedicineChromatographyBiologyChemistryMachine learning

Abstract

fetched live from OpenAlex

On November 15, 2001, during the Centers for Disease Control's 3rd National Conference on CD4+ T-Cell Immunophenotyping, in Orlando, Florida, a discussion focused on the consistency of sample delivery and the stability of clinical flow cytometers. These issues were raised in the context of an enquiry about the effectiveness of placing calibrator microfluorospheres (referred to as beads) into all samples during routine, absolute leukocyte enumeration using bead-based single platform technology (SPT). With SPT it is possible to generate absolute and percentage T-cell subsets from one specimen tube with the use of a non-volumetric instrument. A related concern was the reliability of results obtained with SPT, because the parameters generated with SPT rely exclusively on information generated from one tube, and this single measurement might be prone to error due to flow rate (FR) variation and might compare unfavorably with the precision of absolute counts derived from hematologic instruments, e.g., during the assays performed on double platforms. Interestingly, the answers to both dilemmas depend on the stability of the currently used flow cytometers. In particular, the participants at the Orlando meeting were asked to report any aberrant data pertaining to FR measurements during sample acquisition time (AT). Irregularities of FR in tubes will detect pipetting errors that may occur when beads are added to the specimens. The magnitude of pipetting errors will be directly proportional to the volume error. Thus the relation between FR and absolute cell count can be established. Based on this simple relation, an internal quality control (IQC) protocol can be incorporated (1). Such built-in procedures will monitor the quality of pipetting during immunophenotyping. With an empirically established FR value range, an internal error checking routine can be established. If the FR value is stable, the volume of the sample processed during an acceptable AT must be consistent. Consequently, although the role of beads remains important to verify the stability of FR, there is no need to add beads to each specimen. With the newly proposed SPT protocol, the use of beads is limited to calibration verifiers in a daily IQC procedure. This approach was established for clinical volumetric flow cytometers in 1995 (2). During the conference, participants agreed that a study of SPT list mode files was a first step in establishing whether the FR with TruCount beads on Becton Dickinson Biosciences (BDB) flow cytometers and with FlowCount beads on Beckman Coulter (BC) instruments are consistent. We found that AT is not an automatically acquired parameter on BDB instruments. The list mode files contained the parameter “time” only if it was preselected at the AT. Unfortunately this preselection step is not routine practice in many laboratories. This was not an issue with BC instruments, because AT as a parameter is always available from list mode files. Therefore, the initial review of AT values was available to us mostly from BC Epics XL instruments. These results were encouraging and supported the hypothesis that FR values are relatively constant (1). A limited amount of data, which was available from BDB FACSCalibur instruments, was also in concordance with our hypothesis. Next, the lack of available BDB data was addressed. Apparently, the AT information is recorded on each BDB list mode file; it is the print command that is not activated. Thus, a software tool was created to extract the net AT from headers from the existing list mode file. By using the AT and the detected bead numbers, the average bead number per unit time was calculated. The number of beads per second observed on a FACSCalibur was astonishingly constant over months and years. This stability existed despite the fact that, during the 3-year span, the lot numbers for beads were changed several times (Table 1). The next question was whether FR could be used to determine the impact of pipetting errors associated with the addition of suspended beads on any clinical flow cytometer. Various pipetting “errors” were simulated by adding incorrect volumes in increments of known bead concentrations to blood (Fig. 1). Remarkably predictable instrument performance was observed. A 20% volume error (delivering 80 μl instead of 100 μl of bead suspension) was clearly identified outside ±10% coefficient of variation (Fig. 1). Relation between the magnitude of pipetting error and the CD4 T-cell absolute count tested on the Epics-XL. The solid line represents the mean aggregate CD4 T-cell absolute value. The dashed lines represent ±10% of the aggregate mean. The impact of the pipetting error is proportional to the error manifested as the CD4 T-cell absolute count. The impact is more dramatic with “negative” volume errors. We also wondered whether the impact of FR shifts associated with pipetting error affects T-cell subset values. From the aggregate mean of the FR, it was established that, with a ±2 standard deviation (Fig. 2), it was possible to flag inaccurate sample values. The pipetting error discrimination, based on FR values outside the acceptable range, is shown in Figure 2. The precision of bead pipetting was tested with 10 replicates on BC Epics-XL and BDB FacsCalibur instruments with the use of FlowCount beads. Although the number of beads per second differed in the two preparations, both performed consistently. The ±2 standard deviation spread (dashed lines), which was greater for the BC Epics-XL, was adequate for flagging aberrant sample counts in both systems. The SPT protocol with beads was designed to convert non-volumetric cytometers into volumetric instruments. The beads added to each blood sample provided an internal flow counting meter. The inclusion of beads with each sample assayed also provided validation data for the astonishing consistency of FR on the BC and the BDB instruments. The preliminary data presented here suggested that, when clinical flow cytometers are redesigned in the future for leukocyte subset enumeration, emphasis on performance stability and fine control of FR should be included. The preliminary observations also suggested that the role of beads should be relegated to daily IQC as FR verifiers. According to data studied thus far, there is no need to add FR monitoring reagents to each specimen. In the newly designed flow cytometers, feedback loops for fluid controls should ensure constant FR. In addition, FR readings should be monitored constantly with an automatic built-in error-checking software. Whenever a sample analysis occurs outside the acceptable FR range, that specimen should be flagged. The use of beads therefore can be redefined as the optimal IQC verifier reagent, thereby improving the cost effectiveness of immunophenotyping.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.130
GPT teacher head0.371
Teacher spread0.241 · 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