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Culture Conditions for Generating Human Bone Marrow Stromal Cells Influence Cell Immunophenotype and In Vivo Biodistribution in Immune Deficient Mice.

2004· article· en· W2555269684 on OpenAlexaff
Joanna Vergidis, Garnet Suck, Xinghua Wang, Peter W. Zandstra, Armand Keating

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsPrincess Margaret Cancer CentreToronto General HospitalOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsBone marrowMesenchymal stem cellStromal cellImmunophenotypingFlow cytometryBiologyBiodistributionImmunologyTransplantationIn vivoStem cellPathologyMolecular biologyCancer researchCell biologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Bone marrow stromal cells (MSCs) show promise for cell and gene therapies but their utility is currently limited by low levels of engraftment. A better understanding of factors underlying cell trafficking in vivo is likely to lead to enhanced MSC engraftment and tissue targeting. To address this issue, we studied the immunophenotype and transplantation potential of MSCs derived from two different culture systems, serially passaged adherent layers from standard long-term bone marrow cultures (LTBMC) and a novel stirred suspension bioreactor culture (SSBC) supplemented with IL-3 and SCF. MSCs were characterized as CD45 (−), VCAM-1 (+), CD44 (+), SH-3 (+), and CD49e (+) by flow cytometry. At earlier time points, the SSBC system generated 1.8x more MSCs compared with the LTBMC system when analyzing the CD45-negative fraction by flow cytometry. By the end of culture, however, the LTBMC system generated 7.3x more cells. Interestingly, 66% of the CD45 (−) cells from the bioreactor system were negative for both HLA Class I and II antigens. Furthermore, flow cytometry revealed that the bioreactor-derived cells expressed very low levels of the cell adhesion markers, VCAM-1 and CD44. These data suggest that the SSBC system generates cells that may have greater migratory freedom in vivo. Biodistribution patterns of the human MSCs derived from the two sources were examined in 11 completely unconditioned six-week old SCID mice. Six weeks after intravenous infusion of MSCs, femoral and tibial bone marrow, lung, liver, bone, spleen, brain, heart, and blood were analyzed for donor human cell engraftment by PCR and fluorescence in situ hybridization (FISH) against the murine background. Engraftment was determined by PCR with primers from the human alpha-satellite region (chromosome 17) that amplify a specific 850 bp fragment. One tibial bone marrow sample, two femoral bone marrow samples, one bone sample, and four lung samples from nine mice receiving LTBMC MSC were positive by PCR. In contrast, all of the same tissues from the mouse receiving SSBC MSC were negative for human donor cells, including the lung, with the intriguing exception of a positive PCR signal in heart tissue. The presence of donor MSC was confirmed in PCR+ specimens by FISH using a human Cy3- and a murine FITC-pan-centromeric probe. The frequencies of donor LTBMC MSC in the tibial bone marrow, femoral bone marrow, bone, and lung were 0.79%, 1.60%, 0.58%, and 1.99%, respectively. Donor bioreactor-derived MSCs accounted for 0.41% of the cardiomyocytes from one recipient, despite the absence of cardiac injury. Compared with LTBMC MSCs, SSBC-derived cells appear to display an unusual biodistribution pattern which may be attributable to the altered immunophenotype. The present study underscores the importance of culture conditions in influencing the immunophenotype of MSCs and holds promise for developing targeted cell therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 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

Citations2
Published2004
Admission routes1
Has abstractyes

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