The future of regenerative medicine: urinary system

Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Conventional approaches to developing biomaterials and implants require intuitive tailoring of manufacturing protocols and biocompatibility assessment. This leads to longer development cycles, and high costs. To meet existing and unmet clinical needs, it is critical to accelerate the production of implantable biomaterials, implants and biomedical devices. Building on the Materials Genome Initiative, we define the concept 'biomaterialomics' as the integration of multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools throughout the entire pipeline of biomaterials development. The Data Science-driven approach is envisioned to bring together on a single platform, the computational tools, databases, experimental methods, machine learning, and advanced manufacturing (e.g., 3D printing) to develop the fourth-generation biomaterials and implants, whose clinical performance will be predicted using 'digital twins'. While analysing the key elements of the concept of 'biomaterialomics', significant emphasis has been put forward to effectively utilize high-throughput biocompatibility data together with multiscale physics-based models, E-platform/online databases of clinical studies, data science approaches, including metadata management, AI/ Machine Learning (ML) algorithms and uncertainty predictions. Such integrated formulation will allow one to adopt cross-disciplinary approaches to establish processing-structure-property (PSP) linkages. A few published studies from the lead author's research group serve as representative examples to illustrate the formulation and relevance of the 'Biomaterialomics' approaches for three emerging research themes, i.e. patient-specific implants, additive manufacturing, and bioelectronic medicine. The increased adaptability of AI/ML tools in biomaterials science along with the training of the next generation researchers in data science are strongly recommended. STATEMENT OF SIGNIFICANCE: This leading opinion review paper emphasizes the need to integrate the concepts and algorithms of the data science with biomaterials science. Also, this paper emphasizes the need to establish a mathematically rigorous cross-disciplinary framework that will allow a systematic quantitative exploration and curation of critical biomaterials knowledge needed to drive objectively the innovation efforts within a suitable uncertainty quantification framework, as embodied in 'biomaterialomics' concept, which integrates multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools, like machine learning. The formulation of this approach has been demonstrated for patient-specific implants, additive manufacturing, and bioelectronic medicine.

Stem Cell-Based Therapies: What Interventional Radiologists Need to Know

As the basic units of biological organization, stem cells and their progenitors are essential for developing and regenerating organs and tissue systems using their unique self-renewal capability and differentiation potential into multiple cell lineages. Stem cells are consistently present throughout the entire human development, from the zygote to adulthood. Over the past decades, significant efforts have been made in biology, genetics, and biotechnology to develop stem cell-based therapies using embryonic and adult autologous or allogeneic stem cells for diseases without therapies or difficult to treat. Stem cell-based therapies require optimum administration of stem cells into damaged organs to promote structural regeneration and improve function. Maximum clinical efficacy is highly dependent on the successful delivery of stem cells to the target tissue. Direct image-guided locoregional injections into target tissues offer an option to increase therapeutic outcomes. Interventional radiologists have the opportunity to perform a key role in delivering stem cells more efficiently using minimally invasive techniques. This review discusses the types and sources of stem cells and the current clinical applications of stem cell-based therapies. In addition, the regulatory considerations, logistics, and potential roles of interventional Radiology are also discussed with the review of the literature.

Implantation of Autologous Selected Renal Cells in Diabetic Chronic Kidney Disease Stages 3 and 4-Clinical Experience of a "First in Human" Study

Introduction

Animal models of chronic kidney disease demonstrate that a redundant population of therapeutically bioactive selected renal cells (SRCs) can be delivered to the kidney through intraparenchymal injection and arrest disease progression. Direct injection of SRCs has been shown to attenuate nuclear factor-κB, which is known to drive tissue inflammation, as well as the transforming growth factor-β-mediated plasminogen activator inhibitor-1 response that drives tissue fibrosis.

Methods

We present experience from the first-in-human clinical study with SRCs. Seven male type 2 diabetic patients (63 ± 2 years of age) with chronic kidney disease stage 3 to 4 (estimated glomerular filtration rate 25 ± 2 ml/min) were recruited. After blood and urine sampling, iohexol clearance, magnetic resonance imaging, and renal scintigraphy, patients underwent ultrasound-guided renal biopsy. Two cores of renal tissue were shipped to the manufacturing plant for cell isolation, culture, and product preparation. Formulated SRCs were transported back to study sites (range 59-87 days after biopsy) for intracortical injection using a retroperitoneoscopic technique.

Results

Laparoscopically assisted implantation of SRCs was uneventful in all patients. However, postoperative complications were common and suggest that other techniques of SRC delivery should be used. Kidney volume, split function, and glomerular filtration rate did not change during 12 months of follow-up. An extended 24-month follow-up in 5 of the patients showed a decline in estimated glomerular filtration rate (cystatin C).

Discussion

Postoperative complications following retroperitoneoscopic implantation of SRC in the kidney cortex seem to be related to the surgical procedure rather than to injection of the cell product. No changes in renal function were observed during the original 12-month protocol. Beyond the first 12 months after cell implantation, individual renal function began to deteriorate during further follow-up.

P2Y2 nucleotide receptor activation enhances the aggregation and self-organization of dispersed salivary epithelial cells

Hyposalivation resulting from salivary gland dysfunction leads to poor oral health and greatly reduces the quality of life of patients. Current treatments for hyposalivation are limited. However, regenerative medicine to replace dysfunctional salivary glands represents a revolutionary approach. The ability of dispersed salivary epithelial cells or salivary gland-derived progenitor cells to self-organize into acinar-like spheres or branching structures that mimic the native tissue holds promise for cell-based reconstitution of a functional salivary gland. However, the mechanisms involved in salivary epithelial cell aggregation and tissue reconstitution are not fully understood. This study investigated the role of the P2Y2 nucleotide receptor (P2Y2R), a G protein-coupled receptor that is upregulated following salivary gland damage and disease, in salivary gland reconstitution. In vitro results with the rat parotid acinar Par-C10 cell line indicate that P2Y2R activation with the selective agonist UTP enhances the self-organization of dispersed salivary epithelial cells into acinar-like spheres. Other results indicate that the P2Y2R-mediated response is dependent on epidermal growth factor receptor activation via the metalloproteases ADAM10/ADAM17 or the α5β1 integrin/Cdc42 signaling pathway, which leads to activation of the MAPKs JNK and ERK1/2. Ex vivo data using primary submandibular gland cells from wild-type and P2Y2R(-/-) mice confirmed that UTP-induced migratory responses required for acinar cell self-organization are mediated by the P2Y2R. Overall, this study suggests that the P2Y2R is a promising target for salivary gland reconstitution and identifies the involvement of two novel components of the P2Y2R signaling cascade in salivary epithelial cells, the α5β1 integrin and the Rho GTPase Cdc42.

A population of selected renal cells augments renal function and extends survival in the ZSF1 model of progressive diabetic nephropathy

New treatment paradigms that slow or reverse progression of chronic kidney disease (CKD) are needed to relieve significant patient and healthcare burdens. We have shown that a population of selected renal cells (SRCs) stabilized disease progression in a mass reduction model of CKD. Here, we further define the cellular composition of SRCs and apply this novel therapeutic approach to the ZSF1 rat, a model of severe progressive nephropathy secondary to diabetes, obesity, dyslipidemia, and hypertension. Injection of syngeneic SRCs into the ZSF1 renal cortex elicited a regenerative response that significantly improved survival and stabilized disease progression to renal structure and function beyond 1 year posttreatment. Functional improvements included normalization of multiple nephron structures and functions including glomerular filtration, tubular protein handling, electrolyte balance, and the ability to concentrate urine. Improvements to blood pressure, including reduced levels of circulating renin, were also observed. These functional improvements following SRC treatment were accompanied by significant reductions in glomerular sclerosis, tubular degeneration, and interstitial inflammation and fibrosis. Collectively, these data support the utility of a novel renal cell-based approach for slowing renal disease progression associated with diabetic nephropathy in the setting of metabolic syndrome, one of the most common causes of end-stage renal disease.