Dynamic loading of human engineered heart tissue enhances contractile function and drives a desmosome-linked disease phenotype.

The role that mechanical forces play in shaping the structure and function of the heart is critical to understanding heart formation and the etiology of disease but is challenging to study in patients. Engineered heart tissues (EHTs) incorporating human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes have the potential to provide insight into these adaptive and maladaptive changes. However, most EHT systems cannot model both preload (stretch during chamber filling) and afterload (pressure the heart must work against to eject blood). Here, we have developed a new dynamic EHT (dyn-EHT) model that enables us to tune preload and have unconstrained contractile shortening of >10%. To do this, three-dimensional (3D) EHTs were integrated with an elastic polydimethylsiloxane strip providing mechanical preload and afterload in addition to enabling contractile force measurements based on strip bending. Our results demonstrated that dynamic loading improves the function of wild-type EHTs on the basis of the magnitude of the applied force, leading to improved alignment, conduction velocity, and contractility. For disease modeling, we used hiPSC-derived cardiomyocytes from a patient with arrhythmogenic cardiomyopathy due to mutations in the desmoplakin gene. We demonstrated that manifestation of this desmosome-linked disease state required dyn-EHT conditioning and that it could not be induced using 2D or standard 3D EHT approaches. Thus, a dynamic loading strategy is necessary to provoke the disease phenotype of diastolic lengthening, reduction of desmosome counts, and reduced contractility, which are related to primary end points of clinical disease, such as chamber thinning and reduced cardiac output.

Understanding the Role of ECM Protein Composition and Geometric Micropatterning for Engineering Human Skeletal Muscle.

Skeletal muscle lost through trauma or disease has proven difficult to regenerate due to the challenge of differentiating human myoblasts into aligned, contractile tissue. To address this, we investigated microenvironmental cues that drive myoblast differentiation into aligned myotubes for potential applications in skeletal muscle repair, organ-on-chip disease models and actuators for soft robotics. We used a 2D in vitro system to systematically evaluate the role of extracellular matrix (ECM) protein composition and geometric patterning for controlling the formation of highly aligned myotubes. Specifically, we analyzed myotubes differentiated from murine C2C12 cells and human skeletal muscle derived cells (SkMDCs) on micropatterned lines of laminin compared to fibronectin, collagen type I, and collagen type IV. Results showed that laminin supported significantly greater myotube formation from both cells types, resulting in greater than twofold increase in myotube area on these surfaces compared to the other ECM proteins. Species specific differences revealed that human SkMDCs uniaxially aligned over a wide range of micropatterned line dimensions, while C2C12s required specific line widths and spacings to do the same. Future work will incorporate these results to engineer aligned human skeletal muscle tissue in 2D for in vitro applications in disease modeling, drug discovery and toxicity screening.

Engineered skeletal muscle tissue for soft robotics: fabrication strategies, current applications, and future challenges.

Skeletal muscle is a scalable actuator system used throughout nature from the millimeter to meter length scales and over a wide range of frequencies and force regimes. This adaptability has spurred interest in using engineered skeletal muscle to power soft robotics devices and in biotechnology and medical applications. However, the challenges to doing this are similar to those facing the tissue engineering and regenerative medicine fields; specifically, how do we translate our understanding of myogenesis in vivo to the engineering of muscle constructs in vitro to achieve functional integration with devices. To do this researchers are developing a number of ways to engineer the cellular microenvironment to guide skeletal muscle tissue formation. This includes understanding the role of substrate stiffness and the mechanical environment, engineering the spatial organization of biochemical and physical cues to guide muscle alignment, and developing bioreactors for mechanical and electrical conditioning. Examples of engineered skeletal muscle that can potentially be used in soft robotics include 2D cantilever-based skeletal muscle actuators and 3D skeletal muscle tissues engineered using scaffolds or directed self-organization. Integration into devices has led to basic muscle-powered devices such as grippers and pumps as well as more sophisticated muscle-powered soft robots that walk and swim. Looking forward, current, and future challenges include identifying the best source of muscle precursor cells to expand and differentiate into myotubes, replacing cardiomyocytes with skeletal muscle tissue as the bio-actuator of choice for soft robots, and vascularization and innervation to enable control and nourishment of larger muscle tissue constructs.

Identifying barriers to the rapid administration of appropriate antibiotics in community-acquired pneumonia.

BACKGROUND: Despite multiple guidelines for management of community-acquired pneumonia (CAP), barriers to guideline use are rarely evaluated. METHODS: We performed quantitative and qualitative surveys of junior doctors before implementation of a CAP management pathway. After implementation, we identified patient-related determinants of pathway adherence by multivariate analysis. RESULTS: We surveyed 83 (77%) of the 108 junior doctors working in acute medicine between August 2001 and July 2002 and selected 8 for in-depth interview. We identified five main themes that influence pathway adherence. First, education (recognized to be insufficient on antimicrobial therapy) and experience: increasing clinical experience was associated with greater knowledge of pathway content, but decreasing likelihood of consulting the pathway. Second, attitudes to CAP: doctors recognized that they had not treated CAP with respect early on. Third, work intensity and lack of senior support were barriers to good practice. Fourth, guideline factors: they need to be simple enough to be easy to use while containing enough information to be useful. Fifth, CAP is sometimes difficult to diagnose on admission. Notably, when given three clinical scenarios only six (7%) of respondents assessed CAP severity correctly. In the intervention study, early administration of antibiotics was associated (P < 0.05) with indicators of increased severity of illness (pulse, respiratory rate, oxygenation and temperature) in addition to being admitted to the intervention hospital (P < 0.001). CONCLUSIONS: Some of the identified barriers could be overcome by undergraduate and postgraduate education. However, equally important are organizational barriers that can only be overcome by systems redesign.

Variance in practice emergency medical admission rates: can it be explained?

BACKGROUND: Emergency admission rates have been rising steadily in recent years, with the majority of the increase owing to emergency medical admissions. Possible causative factors include changing demography, incidence of disease, admission thresholds, multiple admissions, and appropriateness of admission. AIM: To investigate the impact of patient and practice factors on variance in general practices' emergency medical admissions rates. DESIGN OF STUDY: Multiple regression analysis relating emergency medical admission rates of general practices to patient and practice characteristics. SETTING: The study was conducted between 1996 and 1997 in the acute hospital trust serving the study area, Dundee, Scotland. METHOD: Scottish Morbidity Record 1 (SMR1) data, which contains details of all hospital consultant episodes, was used to calculate individual practices emergency medical admission rates. These rates were then standardised to an expected value of 100. Forward selection was used to find a suitable multiple regression model to predict each practice's emergency medical admission rate from practice and patient variables. RESULTS: Crude emergency medical admission rates for general practices showed a 1.8-fold variation between the top and bottom deciles. The deprivation status and age of patients explained 42% of the variance in admission rates (64% with the exclusion of one practice that had a poor fit to the model). After correcting for age and deprivation there was a 1.2-fold variation in general practices' emergency medical admission rates. CONCLUSION: The most important factors in explaining variance in general practices' emergency medical admission rates are socio-demographic, with age and deprivation explaining a large proportion of the variation. We found no evidence to support the contention that general practice factors were linked with admission rates.