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Why are MSCs therapeutic? New data: new insight.

ABSTRACT: Adult marrow-derived mesenchymal stem cells (MSCs) are able to differentiate into bone, cartilage, muscle, marrow stroma, tendon-ligament, fat and other connective tissues. The questions can be asked, what do MSCs do naturally and where is the MSC niche? New insight and clinical experience suggest that MSCs are naturally found as perivascular cells, summarily referred to as pericytes, which are released at sites of injury, where they secrete large quantities of bioactive factors that are both immunomodulatory and trophic. The trophic activity inhibits ischaemia-caused apoptosis and scarring while stimulating angiogenesis and the mitosis of tissue intrinsic progenitor cells. The immunomodulation inhibits lymphocyte surveillance of the injured tissue, thus preventing autoimmunity, and allows allogeneic MSCs to be used in a variety of clinical situations. Thus, a new, enlightened era of experimentation and clinical trials has been initiated with xenogenic and allogeneic MSCs.

SUBMITTER: Caplan AI

PROVIDER: S-EPMC8793150 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Why are MSCs therapeutic? New data: new insight.

Caplan A I AI

The Journal of pathology 20090101 2

Adult marrow-derived mesenchymal stem cells (MSCs) are able to differentiate into bone, cartilage, muscle, marrow stroma, tendon-ligament, fat and other connective tissues. The questions can be asked, what do MSCs do naturally and where is the MSC niche? New insight and clinical experience suggest that MSCs are naturally found as perivascular cells, summarily referred to as pericytes, which are released at sites of injury, where they secrete large quantities of bioactive factors that are both im ...[more]

PMID: 19023885

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Project description:Strokes within pediatric populations are considered to be the 10th leading cause of death in the United States of America, with over half of such events occurring in children younger than one year of life. The multifactorial etiopathology that has an influence on stroke development and occurrence signify the importance of the timely recognition of both modifiable and non-modifiable factors for adequate diagnostic and treatment approaches. The early recognition of a stroke and stroke risk in children has the potential to advance the application of neuroprotective, thrombolytic, and antithrombotic interventions and rehabilitation strategies to the earliest possible timepoints after the onset of a stroke, improving the outcomes and quality of life for affected children and their families. The recent development of molecular genetic methods has greatly facilitated the analysis and diagnosis of single-gene disorders. In this review, the most significant single gene disorders associated with pediatric stroke are presented, along with specific therapeutic options whenever they exist. Besides monogenic disorders that may present with stroke as a first symptom, genetic polymorphisms may contribute to the risk of pediatric and perinatal stroke. The most frequently studied genetic risk factors are several common polymorphisms in genes associated with thrombophilia; these genes code for proteins that are part of the coagulation cascade, fibrolysis, homocystein metabolism, lipid metabolism, or platelets. Single polymorphism frequencies may not be sufficient to completely explain the stroke causality and an analysis of several genotype combinations is a more promising approach. The recent steps forward in our understanding of the disorders underlying strokes has given us a next generation of therapeutics and therapeutic targets by which to improve stroke survival, protect or rebuild neuronal connections in the brain, and enhance neural function. Advances in DNA sequencing and the development of new tools to correct human gene mutations have brought genetic analysis and gene therapy into the focus of investigations for new therapeutic options for stroke patients.

Project description:BackgroundThe data missing from patient profiles in intensive care units (ICUs) are substantial and unavoidable. However, this incompleteness is not always random or because of imperfections in the data collection process.ObjectiveThis study aimed to investigate the potential hidden information in data missing from electronic health records (EHRs) in an ICU and examine whether the presence or missingness of a variable itself can convey information about the patient health status.MethodsDaily retrieval of laboratory test (LT) measurements from the Medical Information Mart for Intensive Care III database was set as our reference for defining complete patient profiles. Missingness indicators were introduced as a way of representing presence or absence of the LTs in a patient profile. Thereafter, various feature selection methods (filter and embedded feature selection methods) were used to examine the predictive power of missingness indicators. Finally, a set of well-known prediction models (logistic regression [LR], decision tree, and random forest) were used to evaluate whether the absence status itself of a variable recording can provide predictive power. We also examined the utility of missingness indicators in improving predictive performance when used with observed laboratory measurements as model input. The outcome of interest was in-hospital mortality and mortality at 30 days after ICU discharge.ResultsRegardless of mortality type or ICU day, more than 40% of the predictors selected by feature selection methods were missingness indicators. Notably, employing missingness indicators as the only predictors achieved reasonable mortality prediction on all days and for all mortality types (for instance, in 30-day mortality prediction with LR, we achieved area under the curve of the receiver operating characteristic [AUROC] of 0.6836±0.012). Including indicators with observed measurements in the prediction models also improved the AUROC; the maximum improvement was 0.0426. Indicators also improved the AUROC for Simplified Acute Physiology Score II model-a well-known ICU severity of illness score-confirming the additive information of the indicators (AUROC of 0.8045±0.0109 for 30-day mortality prediction for LR).ConclusionsOur study demonstrated that the presence or absence of LT measurements is informative and can be considered a potential predictor of in-hospital and 30-day mortality. The comparative analysis of prediction models also showed statistically significant prediction improvement when indicators were included. Moreover, missing data might reflect the opinions of examining clinicians. Therefore, the absence of measurements can be informative in ICUs and has predictive power beyond the measured data themselves. This initial case study shows promise for more in-depth analysis of missing data and its informativeness in ICUs. Future studies are needed to generalize these results.

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Why are MSCs therapeutic? New data: new insight.

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Why are MSCs therapeutic? New data: new insight.

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