Clinically Translatable Cell Tracking and Quantification by MRI in Cartilage Repair Using Superparamagnetic Iron Oxides

Background: Articular cartilage has very limited intrinsic regenerative capacity, making cell-based therapy a tempting approach for cartilage repair. Cell tracking can be a major step towards unraveling and improving the repair process of these therapies. We studied superparamagnetic iron oxides (SPIO) for labeling human bone marrow-derived mesenchymal stem cells (hBMSCs) regarding effectivity, cell viability, long term metabolic cell activity, chondrogenic differentiation and hBMSC secretion profile. We additionally examined the capacity of synovial cells to endocytose SPIO from dead, labeled cells, together with the use of magnetic resonance imaging (MRI) for intra-articular visualization and quantification of SPIO labeled cells. Methodology/Prinicipal Findings: Efficacy and various safety aspects of SPIO cell labeling were determined using appropriate assays. Synovial SPIO re-uptake was investigated in vitro by co-labeling cells with SPIO and green fluorescent protein (GFP). MRI experiments were performed on a clinical 3.0T MRI scanner. Two cell-based cartilage repair techniques were mimicked for evaluating MRI traceability of labeled cells: intra-articular cell injection and cell implantation in cartilage defects. Cells were applied ex vivo or in vitro in an intra-articular environment and immediately scanned. SPIO labeling was effective and did not impair any of the studied safety aspects, including hBMSC secretion profile. SPIO from dead, labeled cells could be taken up by synovial cells. Both injected and implanted SPIO-labeled cells could accurately be visualized by MRI in a clinically relevant sized joint model using clinically applied cell doses. Finally, we quantified the amount of labeled cells seeded in cartilage defects using MR-based relaxometry. Conclusions: SPIO labeling appears to be safe without influencing cell behavior. SPIO labeled cells can be visualized in an intra-articular environment and quantified when seeded in cartilage defects.Biomechanical EngineeringMechanical, Maritime and Materials Engineerin

Comparative Study on the Therapeutic Potential of Neurally Differentiated Stem Cells in a Mouse Model of Multiple Sclerosis

Background: Transplantation of neural stem cells (NSCs) is a promising novel approach to the treatment of neuroinflammatory diseases such as multiple sclerosis (MS). NSCs can be derived from primary central nervous system (CNS) tissue or obtained by neural differentiation of embryonic stem (ES) cells, the latter having the advantage of readily providing an unlimited number of cells for therapeutic purposes. Using a mouse model of MS, we evaluated the therapeutic potential of NSCs derived from ES cells by two different neural differentiation protocols that utilized adherent culture conditions and compared their effect to primary NSCs derived from the subventricular zone (SVZ). Methodology/Principal Findings: The proliferation and secretion of pro-inflammatory cytokines by antigen-stimulated splenocytes was reduced in the presence of SVZ-NSCs, while ES cell-derived NSCs exerted differential immunosuppressive effects. Surprisingly, intravenously injected NSCs displayed no significant therapeutic impact on clinical and pathological disease outcomes in mice with experimental autoimmune encephalomyelitis (EAE) induced by recombinant myelin oligodendrocyte glycoprotein, independent of the cell source. Studies tracking the biodistribution of transplanted ES cellderived NSCs revealed that these cells were unable to traffic to the CNS or peripheral lymphoid tissues, consistent with the lack of cell surface homing molecules. Attenuation of peripheral immune responses could only be achieved through multiple high doses of NSCs administered intraperitoneally, which led to some neuroprotective effects within the CNS

Identification of Genes Directly Involved in Shell Formation and Their Functions in Pearl Oyster, Pinctada fucata

Mollusk shell formation is a fascinating aspect of biomineralization research. Shell matrix proteins play crucial roles in the control of calcium carbonate crystallization during shell formation in the pearl oyster, Pinctada fucata. Characterization of biomineralization-related genes during larval development could enhance our understanding of shell formation. Genes involved in shell biomineralization were isolated by constructing three suppression subtractive hybridization (SSH) libraries that represented genes expressed at key points during larval shell formation. A total of 2,923 ESTs from these libraries were sequenced and gave 990 unigenes. Unigenes coding for secreted proteins and proteins with tandem-arranged repeat units were screened in the three SSH libraries. A set of sequences coding for genes involved in shell formation was obtained. RT-PCR and in situ hybridization assays were carried out on five genes to investigate their spatial expression in several tissues, especially the mantle tissue. They all showed a different expression pattern from known biomineralization-related genes. Inhibition of the five genes by RNA interference resulted in different defects of the nacreous layer, indicating that they all were involved in aragonite crystallization. Intriguingly, one gene (UD_Cluster94.seq.Singlet1) was restricted to the ‘aragonitic line’. The current data has yielded for the first time, to our knowledge, a suite of biomineralization-related genes active during the developmental stages of P.fucata, five of which were responsible for nacreous layer formation. This provides a useful starting point for isolating new genes involved in shell formation. The effects of genes on the formation of the ‘aragonitic line’, and other areas of the nacreous layer, suggests a different control mechanism for aragonite crystallization initiation from that of mature aragonite growth

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

A Biological Global Positioning System: Considerations for Tracking Stem Cell Behaviors in the Whole Body

Many recent research studies have proposed stem cell therapy as a treatment for cancer, spinal cord injuries, brain damage, cardiovascular disease, and other conditions. Some of these experimental therapies have been tested in small animals and, in rare cases, in humans. Medical researchers anticipate extensive clinical applications of stem cell therapy in the future. The lack of basic knowledge concerning basic stem cell biology-survival, migration, differentiation, integration in a real time manner when transplanted into damaged CNS remains an absolute bottleneck for attempt to design stem cell therapies for CNS diseases. A major challenge to the development of clinical applied stem cell therapy in medical practice remains the lack of efficient stem cell tracking methods. As a result, the fate of the vast majority of stem cells transplanted in the human central nervous system (CNS), particularly in the detrimental effects, remains unknown. The paucity of knowledge concerning basic stem cell biology—survival, migration, differentiation, integration in real-time when transplanted into damaged CNS remains a bottleneck in the attempt to design stem cell therapies for CNS diseases. Even though excellent histological techniques remain as the gold standard, no good in vivo techniques are currently available to assess the transplanted graft for migration, differentiation, or survival. To address these issues, herein we propose strategies to investigate the lineage fate determination of derived human embryonic stem cells (hESC) transplanted in vivo into the CNS. Here, we describe a comprehensive biological Global Positioning System (bGPS) to track transplanted stem cells. But, first, we review, four currently used standard methods for tracking stem cells in vivo: magnetic resonance imaging (MRI), bioluminescence imaging (BLI), positron emission tomography (PET) imaging and fluorescence imaging (FLI) with quantum dots. We summarize these modalities and propose criteria that can be employed to rank the practical usefulness for specific applications. Based on the results of this review, we argue that additional qualities are still needed to advance these modalities toward clinical applications. We then discuss an ideal procedure for labeling and tracking stem cells in vivo, finally, we present a novel imaging system based on our experiments

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

Tie2 identifies a hematopoietic monocytes required for tumor lineage of proangiogenic vessel formation and a mesenchymal population of pericyte progenitors

Bone marrow-derived cells contribute to tumor angiogenesis. Here, we demonstrate that monocytes expressing the Tie2 receptor (Tie2-expressing monocytes [TEMs]) (1) are a distinct hematopoietic lineage of proangiogenic cells, (2) are selectively recruited to spontaneous and orthotopic tumors, (3) promote angiogenesis in a paracrine manner, and (4) account for most of the proangiogenic activity of myeloid cells in tumors. Remarkably, TEM knockout completely prevented human glioma neovascularization in the mouse brain and induced substantial tumor regression. Besides TEMs and endothelial cells (ECs), Tie2 expression distinguished a rare population of tumor stroma-derived mesenchymal progenitors representing a primary source of tumor pericytes. Therefore, Tie2 expression characterizes three distinct cell types required for tumor neovascularization: ECs, proangiogenic cells of hematopoietic origin, and pericyte precursors of mesenchymal origin.status: publishe