← Search

Data · dataset · 2026

Unravelling patient predictors of mesenchymal stem cell expansion in an orthopaedic setting

Listed in ZivaHub and Deakin Research Online and DMU Figshare — shown once because both records carry DOI 10.17034/32633931.v1

The use of mesenchymal stem cells (MSCs) in cell therapy treatments is not a new concept, with an increasing amount of clinical trials and therapies being developed worldwide.

Description

In the case of autologous cell therapy treatment cells are collected from a patient, cultured ex vivo before being reintroduced at a greater concentration for therapeutic effect. The success of these types of treatment is reliant on the ability of the cells to expand ex vivo and failing to reach a desired quantity or doing so too slowly may result in an unsuccessful treatment.

This study aims to explore patient predictors and the feasibility of conducting a larger study to develop a clinical tool to predict stem cell growth based on relatively easy to collect measures before collecting a bone marrow aspirate.<br><br>Twenty-five patients undergoing interpedical screw implants were recruited and bone marrow aspirates were collected from the vertebral body. MSCs were isolated from this sample and a panel of assays conducted to; confirm the MSC nature of the cells via flow cytometry; colony forming and osteogenic potential of the cells via colony forming unit assess; proliferative ability of the MSCs via population doubling times.

Read the rest (3 more)

Participants were later invited to the Northern Ireland Clinical Research Facility and a range of potential predictor measures collected focused around demographics, body composition, lifestyle and dietary choices, circulating hormone levels and markers of bone turnover. <br><br>These form the basis of the pilot model and using R the sample correlation coefficients between each variable explored and a predictive model defined.The final pilot model consisted of measures of body fat, the ratio of LDL to HDL cholesterol, physical activity, age and the circulating adipose hormones adiponectin, leptin and obestatin.

This model was unable to produce a statistically significant estimate of the MSC growth, with body fat percentage and physical activity contributing the most significant estimates. The measures of bone turnover appear to have no relationship to MSC growth characteristics within this setting. These finding imply that individuals that are physically active with a relatively low body fat percentage have MSCs which are more proliferative.<br><br>Utilising this model an estimate of the number of participants required to complete a larger study was calculated, 80 further recruitments would be required, and this would not be feasible in Northern Ireland in a reasonable period of time.

Instead, collaborations with international clinical trials may provide an opportunity to develop a database including measures of stem cell efficacy and predictors to further develop a robust predictive model and clinical tool.<br>

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Medical biotechnology 70%
Provenance · 3 source records, 14 field assertions
SourceKeyLast seenRaw
ZivaHuboai:figshare.com:article/3263393112 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/3263393112 d agoJSON v1
DMU Figshareoai:figshare.com:article/3263393112 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:3206enrichment · zivahub uct ac zataxonomy-embedding@1.1.0title+keywords+description (70%)
concepts[field].local:field:earth-environmentalmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:earth-environmentalmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:life-sciencesmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:medicine-healthmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:medicine-healthmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:medicine-healthmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
descriptionsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/description
license_textsource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
publication_datesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
titlesource · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0/metadata/dc/title