The modulus of elasticity of the extracellular matrix (ECM), often referred to in a biological context as “stiffness,” naturally varies within the body, e.g., hard bones and soft tissue. Moreover, it has been found to have a profound effect on the behavior of anchorage‐dependent cells. The fabrication of matrix substrates with a defined modulus of elasticity can be a useful technique to study the interactions of cells with their biophysical microenvironment. Matrix substrates composed of polyacrylamide hydrogels have an easily quantifiable elasticity that can be changed by adjusting the relative concentrations of its monomer, acrylamide, and cross‐linker, bis‐acrylamide. In this unit, we detail a protocol for the fabrication of statically compliant and radial‐gradient polyacrylamide hydrogels, as well as the functionalization of these hydrogels with ECM proteins for cell culture. Included as well are suggestions to optimize this protocol to the choice of cell type or stiffness with a table of relative bis‐acrylamide and acrylamide concentrations and expected elasticity after polymerization. Curr. Protoc. Cell Biol. 47:10.16.1‐10.16.16. © 2010 by John Wiley & Sons, Inc.

Mesenchymal stem cell (MSC) differentiation is regulated in part by tissue stiffness, yet MSCs can often encounter stiffness gradients within tissues caused by pathological, e.g., myocardial infarction ∼8.7±1.5 kPa/mm, or normal tissue variation, e.g., myocardium ∼0.6±0.9 kPa/mm; since migration predominantly occurs through physiological rather than pathological gradients, it is not clear whether MSC differentiate or migrate first. MSCs cultured up to 21 days on a hydrogel containing a physiological gradient of 1.0±0.1 kPa/mm undergo directed migration, or durotaxis, up stiffness gradients rather than remain stationary. Temporal assessment of morphology and differentiation markers indicates that MSCs migrate to stiffer matrix and then differentiate into a more contractile myogenic phenotype. In those cells migrating from soft to stiff regions however, phenotype is not completely determined by the stiff hydrogel as some cells retain expression of a neural marker. These data may indicate that stiffness variation, not just stiffness alone, can be an important regulator of MSC behavior.

Although artificial intelligence (AI)-based algorithms for diagnosis hold promise for improving care, their safety and effectiveness must be ensured to facilitate wide adoption. Several recently proposed regulatory frameworks provide a solid foundation but do not address a number of issues that may prevent algorithms from being fully trusted. In this article, we review the major regulatory frameworks for software as a medical device applications, identify major gaps, and propose additional strategies to improve the development and evaluation of diagnostic AI algorithms. We identify the following major shortcomings of the current regulatory frameworks: (1) conflation of the diagnostic task with the diagnostic algorithm, (2) superficial treatment of the diagnostic task definition, (3) no mechanism to directly compare similar algorithms, (4) insufficient characterization of safety and performance elements, (5) lack of resources to assess performance at each installed site, and (6) inherent conflicts of interest. We recommend the following additional measures: (1) separate the diagnostic task from the algorithm, (2) define performance elements beyond accuracy, (3) divide the evaluation process into discrete steps, (4) encourage assessment by a third-party evaluator, (5) incorporate these elements into the manufacturers' development process. Specifically, we recommend four phases of development and evaluation, analogous to those that have been applied to pharmaceuticals and proposed for software applications, to help ensure world-class performance of all algorithms at all installed sites. In the coming years, we anticipate the emergence of a substantial body of research dedicated to ensuring the accuracy, reliability, and safety of the algorithms.

BACKGROUNDSevere combined immunodeficiency due to adenosine deaminase (ADA) deficiency (ADA-SCID) is a rare and life-threatening primary immunodeficiency. METHODSWe treated 50 patients with ADA-SCID (30 in the United States and 20 in the United Kingdom) with an investigational gene therapy composed of autologous CD34+ hematopoietic stem and progenitor cells (HSPCs) transduced ex vivo with a self-inactivating lentiviral vector encoding human ADA. Data from the two U.S. studies (in which fresh and cryopreserved formulations were used) at 24 months of follow-up were analyzed alongside data from the U.K. study (in which a fresh formulation was used) at 36 months of follow-up. RESULTSOverall survival was 100% in all studies up to 24 and 36 months. Event-free survival (in the absence of reinitiation of enzyme-replacement therapy or rescue allogeneic hematopoietic stem-cell transplantation) was 97% (U.S. studies) and 100% (U.K. study) at 12 months; 97% and 95%, respectively, at 24 months; and 95% (U.K. study) at 36 months. Engraftment of genetically modified HSPCs persisted in 29 of 30 patients in the U.S. studies and in 19 of 20 patients in the U.K. study. Patients had sustained metabolic detoxification and normalization of ADA activity levels. Immune reconstitution was robust, with 90% of the patients in the U.S. studies and 100% of those in the U.K. study discontinuing immunoglobulin-replacement therapy by 24 months and 36 months, respectively. No evidence of monoclonal expansion, leukoproliferative complications, or emergence of replication-competent lentivirus was noted, and no events of autoimmunity or graft-versus-host disease occurred. Most adverse events were of low grade. CONCLUSIONSTreatment of ADA-SCID with ex vivo lentiviral HSPC gene therapy resulted in high overall and event-free survival with sustained ADA expression, metabolic correction, and functional immune reconstitution. (Funded by the National Institutes of Health and others; ClinicalTrials.gov numbers, NCT01852071, NCT02999984, and NCT01380990.