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Record W203432939 · doi:10.1007/978-1-60761-999-4_3

Standardized Isolation of Human Mesenchymal Stromal Cells with Red Blood Cell Lysis

2011· article· en· W203432939 on OpenAlexfundno aff
Patrick Horn, Simone Bork, Wolfgang Wagner

Bibliographic record

VenueMethods in molecular biology · 2011
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftStem Cell Network
KeywordsMesenchymal stem cellLysisCD34Bone marrowPeripheral blood mononuclear cellHemolysisStromal cellImmunophenotypingBiologyChemistryImmunologyCell biologyFlow cytometryCancer researchStem cellBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Human mesenchymal stromal cells (MSC) raise high hopes for tissue engineering and therapeutic -applications. So far, it is not possible to isolate pure fractions from bone marrow and therefore MSC cell preparations notoriously represent heterogeneous mixtures of different cell types. The composition of -subpopulations can already be affected by the initial steps of cell preparation. Usually, isolation of MSC involves density fractionation to separate the mononuclear cells (MNCs) from erythrocytes and -granulocytes. However, this method is difficult to standardize especially under GMP conditions. Here, we describe an alternative approach for isolation of human MSC based on red blood cell (RBC) lysis with ammonium chloride. This results in a slightly higher number of fibroblastic colony forming units (CFU-F), whereas morphological analysis of the CFU-F reveals the same heterogeneous composition of MSC cultures indicating that the proportion of subpopulations is not affected by RBC lysis. Immunophenotype (CD73+, CD90+, CD105+, CD31-, CD34-, CD45-), adipogenic, and osteogenic differentiation potential of MSC were also similar with both methods. In conclusion, RBC lysis comprises an efficient method for the isolation of human MSC from bone marrow aspirate. This technique is faster and can be standardized more easily for clinical application of MSC.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.192
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.408
Teacher spread0.359 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations53
Published2011
Admission routes1
Has abstractyes

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