Kenneth L. Urish

Antioxidant levels represent a major determinant in the regenerative capacity of muscle stem cells.

Stem cells are classically defined by their multipotent, long-term proliferation, and self-renewal capabilities. Here, we show that increased antioxidant capacity represents an additional functional characteristic of muscle-derived stem cells (MDSCs). Seeking to understand the superior regenerative capacity of MDSCs compared with myoblasts in cardiac and skeletal muscle transplantation, our group hypothesized that survival of the oxidative and inflammatory stress inherent to transplantation may play an important role. Evidence of increased enzymatic and nonenzymatic antioxidant capacity of MDSCs were observed in terms of higher levels of superoxide dismutase and glutathione, which appears to confer a differentiation and survival advantage. Further when glutathione levels of the MDSCs are lowered to that of myoblasts, the transplantation advantage of MDSCs over myoblasts is lost when transplanted into both skeletal and cardiac muscles. These findings elucidate an important cause for the superior regenerative capacity of MDSCs, and provide functional evidence for the emerging role of antioxidant capacity as a critical property for MDSC survival post-transplantation.

Initial failure in myoblast transplantation therapy has led the way toward the isolation of muscle stem cells: potential for tissue regeneration.

Myoblast transfer therapy can restore dystrophin expressing myofibers in mdx mice and patients with Duchenne muscular dystrophy (DMD). However, the effectiveness of this technique is hindered by numerous limitations, including minimal distribution of cells after injection, immune rejection, and poor cell survival. Initial studies revealed that only a small population of cells was responsible for muscle regeneration. Compared with myoblast transplantation, the injection of a population of myogenic cells purified with the pre-plate technique results in a superior regeneration of dystrophin-expressing myofibers. These postnatal muscle-derived stem cells (MDSC) undergo self-renewal, display long-term proliferation, and differentiate into multiple lineages. This review examines the initial obstacles encountered in myoblast transplantation, the regenerative properties of MDSC, and the potential use of these stem cells not only for DMD therapy but also for multiple applications, including bone repair and blood reconstitution.

T2 texture index of cartilage can predict early symptomatic OA progression: data from the osteoarthritis initiative

OBJECTIVE There is an interest in using Magnetic Resonance Imaging (MRI) to identify pre-radiographic changes in osteoarthritis (OA) and features that indicate risk for disease progression. The purpose of this study is to identify image features derived from MRI T2 maps that can accurately predict onset of OA symptoms in subjects at risk for incident knee OA. METHODS Patients were selected from the Osteoarthritis Initiative (OAI) control cohort and incidence cohort and stratified based on the change in total Western Ontario and McMaster Universities Arthritis (WOMAC) score from baseline to 3-year follow-up (80 non-OA progression and 88 symptomatic OA progression patients). For each patient, a series of image texture features were measured from the baseline cartilage T2 map. A linear discriminant function and feature reduction method was then trained to quantify a texture metric, the T2 texture index of cartilage (TIC), based on 22 image features, to identify a composite marker of T2 heterogeneity. RESULTS Statistically significant differences were seen in the baseline T2 TIC between the non-progression and symptomatic OA progression populations. The baseline T2 TIC differentiates subjects that develop worsening of their WOMAC score OA with an accuracy between 71% and 76%. The T2 TIC differences were predominantly localized to a dominant knee compartment that correlated with the mechanical axis of the knee. CONCLUSION Baseline heterogeneity in cartilage T2 as measured with the T2 TIC index is able to differentiate and predict individuals that will develop worsening of their WOMAC score at 3-year follow-up.

Pulse Lavage is Inadequate at Removal of Biofilm from the Surface of Total Knee Arthroplasty Materials

In acute periprosthetic infection, irrigation and debridement with component retention has a high failure rate in some studies. We hypothesize that pulse lavage irrigation is ineffective at removing biofilm from total knee arthroplasty (TKA) components. Staphylococcus aureus biofilm mass and location was directly visualized on arthroplasty materials with a photon collection camera and laser scanning confocal microscopy. There was a substantial reduction in biofilm signal intensity, but the reduction was less than a ten-fold decrease. This suggests that irrigation needs to be further improved for the removal of biofilm mass below the necessary bioburden level to prevent recurrence of acute infection in total knee arthroplasty.

Registration of Magnetic Resonance Image Series for Knee Articular Cartilage Analysis Data from the Osteoarthritis Initiative

Objective: Although conventional radiography is used to assess osteoarthritis in a clinical setting, it has limitations, including an inability to stage early cartilage degeneration. There is a growing interest in using quantitative magnetic resonance imaging to identify degenerative changes in articular cartilage, including the large multicentered study, the Osteoarthritis Initiative (OAI). There is a demand for suitable image registration and segmentation software to complete this analysis. The objective of this study was to develop and validate the open source software, ImageK, that registers 3 T MRI T2 mapping and double echo steady state (DESS) knee MRI sequences acquired in the OAI protocol. Methods: A C++ library, the insight toolkit, was used to develop open source software to register DESS and T2 mapping image MRI sequences using Mattes’s Multimodality Mutual information metric. Results: Registration was assessed using three separate methods. A checkerboard layout demonstrated acceptable visual alignment. Fiducial markers placed in cadaveric knees measured a registration error of 0.85 voxels. Measuring the local variation in Mattes’s Mutual Information metric in the local area of the registered solution showed precision within 1 pixel. In this group, the registered solution required a transform of 56 voxels in translation and 1 degree of rotation. Conclusion: The software we have developed, ImageK, provides free, open source image analysis software that registers DESS and T2 mapping sequences of knee articular cartilage within 1 voxel accuracy. This image registration software facilitates quantitative MRI analyses of knee articular cartilage.

Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative.

The purpose of this study is to evaluate the ability of a machine learning algorithm to classify in vivo magnetic resonance images (MRI) of human articular cartilage for development of osteoarthritis (OA). Sixty‐eight subjects were selected from the osteoarthritis initiative (OAI) control and incidence cohorts. Progression to clinical OA was defined by the development of symptoms as quantified by the Western Ontario and McMaster Universities Arthritis (WOMAC) questionnaire 3 years after baseline evaluation. Multi‐slice T2‐weighted knee images, obtained through the OAI, of these subjects were registered using a nonlinear image registration algorithm. T2 maps of cartilage from the central weight bearing slices of the medial femoral condyle were derived from the registered images using the multiple available echo times and were classified for “progression to symptomatic OA” using the machine learning tool, weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND‐CHRM). WND‐CHRM classified the isolated T2 maps for the progression to symptomatic OA with 75% accuracy. Clinical significance: Machine learning algorithms applied to T2 maps have the potential to provide important prognostic information for the development of OA.

A Multicenter Study of Irrigation and Debridement in Total Knee Arthroplasty Periprosthetic Joint Infection: Treatment Failure Is High

BACKGROUND In total knee arthroplasty (TKA) periprosthetic joint infection (PJI), irrigation and debridement (I&D) with component retention is a treatment option with a wide variation in reported failure rates. The purpose of this study was to determine failure rates, outcomes, and factors that predict failure in I&D for TKA PJI. METHODS A multicenter observational study of patients with a TKA PJI and subsequently undergoing an I&D with retention of components was conducted. The primary outcome was failure rate of I&D, where failure was defined as any subsequent surgical procedures. RESULTS Two hundred sixteen cases of I&D with retention of components performed on 206 patients met inclusion criteria. The estimated long-term failure rate at 4 years was 57.4%. Time-to-event analyses revealed that the median survival time was 14.32 months. Five-year mortality was 19.9%. Multivariable modeling revealed that time symptomatic and organism were independent predictors of I&D failure. Culture-negative status had a higher hazard for failure than culture-positive patients. When primary organism and time symptomatic were selected to produce an optimized scenario for an I&D, the estimated failure rate was 39.6%. CONCLUSION I&D with retention of components has a high failure rate, and there is a high incidence of more complex procedures after this option is chosen. The patient comorbidities we investigated did not predict I&D success. Our results suggest that I&D has a limited ability to control infection in TKA and should be used selectively under optimum conditions.

Viable bacteria persist on antibiotic spacers following two-stage revision for periprosthetic joint infection†

Treatment in periprosthetic joint infection (PJI) remains challenging. The failure rate of two‐stage revision and irrigation and debridement with component retention in PJI suggests that biofilm cells have a high tolerance to antibiotic chemotherapy. Previous work has demonstrated that biofilm cells have high antibiotic tolerance in vitro, but there is little clinical evidence to support these observations. The aim of this study was to determine if retrieved antibiotic spacers from two‐stage revision total knee arthroplasty for PJI have evidence of remaining viable bacteria. Antibiotic poly (methyl methacrylate) (PMMA) spacers from two‐stage revision total knee arthroplasty for PJI were prospectively collected and analyzed for bacterial 16s rRNA using polymerase chain reaction (PCR), reverse transcription (RT)‐PCR, quantitative RT‐PCR (qRT‐PCR), and single genome analysis (SGA). PCR and RT‐PCR identified bacterial species on 53.8% (7/13) of these samples. When initial culture negative cases are excluded, 68% (6/9) samples were identified with bacterial species. A more rigorous qRT‐PCR analysis showed a strong positive signal for bacterial contamination in 30.7% (4/13) of cases. These patients did not show any clinical evidence of PJI recurrence after 15 months of follow‐up. Because the half‐life of bacterial rRNA is approximately a few days, the identification of bacteria rRNA on antibiotic PMMA spacers suggests that viable bacteria were present after conclusion of antibiotic therapy. This study provides evidence for the high tolerance of biofilm cells to antibiotics in vivo and the important role of bacterial persisters in PJI.

Elimination of Antibiotic Resistant Surgical Implant Biofilms Using an Engineered Cationic Amphipathic Peptide WLBU2

Antibiotics are unable to remove biofilms from surgical implants. This high antibiotic tolerance is related to bacterial persisters, a sub-population of bacteria phenotypically tolerant to antibiotics secondary to a reduced metabolic state. WLBU2 is an engineered cationic amphipathic peptide designed to maximize antimicrobial activity with minimal mammalian cell toxicity. The objective of this study was to test the ability of WLBU2 to remove Staphylococcus aureus surgical implant biofilms. WLBU2 effectively treated S. aureus biofilms formed by a variety of clinical MSSA and MRSA strains and created culture-negative implants in the in vitro biofilm model. Blocking bacterial metabolism by inhibiting oxidative phosphorylation did not affect WLBU2 killing compared to decreased killing by cefazolin. In the surgical implant infection animal model, WLBU2 decreased biofilm mass as compared to control, untreated samples. WLBU2 could rapidly eliminate implants in vitro and had sufficient efficacy in vivo with minimal systemic toxicity.

Automated classification and visualization of fluorescent live cell microscopy images

Robotic, high‐throughput microscopy is a powerful tool for small molecule screening and classifying cell phenotype, proteomic and genomic data. An important hurdle in the field is the automated classification and visualization of results collected from a data set of tens of thousands of images. We present a method that approaches these problems from the perspective of flow cytometry with supporting open‐source code. Image analysis software was created that allowed high‐throughput microscopy data to be analysed in a similar manner as flow cytometry. Each cell on an image is considered an object and a series of gates similar to flow cytometry is used to classify and quantify the properties of cells including size and level of fluorescent intensity. This method is released with open‐source software and code that demonstrates the methods implementation. Accuracy of the software was determined by measuring the levels of apoptosis in a primary murine myoblast cell line after exposure to staurosporine and comparing these results to flow cytometry.