Rotator Cuff Repair Augmentation Using Osteoinductive Growth Factors

Rotator cuff injuries (RCIs) present a major health problem due to high incidences of degenerative tears greater than 3 cm and prevalence of re-tears following surgical procedures. Since healing and functional restoration relies upon bone ingrowth into the tendon, it is hypothesised that sustained delivery of osteoinductive factors including bone morphogenetic proteins (BMPs), specifically BMP2–7, may significantly improve RCI tendon-bone healing. Here, growth factor candidates and delivery mechanisms are reviewed, specifically for improved RCI healing through enhanced bone ingrowth. In addition to BMPs, other potentially osteogenic factors including platelet-derived growth factors (PDGF), fibroblast growth factor (FGF), transforming growth beta isoforms (TGF-β1 and TGF-3) and parathyroid hormone (PTH) are evaluated since they can induce bone formation at the healing tendon attachment site. Several challenges must be addressed prior to clinical translation. The majority of published studies utilise in vivo animal models. In general, BMP-7 demonstrates a stronger stimulating effect when compared to BMP-2; the reported effectiveness of BMP-2 is often conflicting. Alternative factors, including PDGF and PTH, also demonstrate potential for assisting bone growth in enthesis healing. The use of sustained and biomimetic delivery systems appears to have the greatest positive effects. Some studies have demonstrated a dose-dependent effect, in conjunction with varying age, indicating that stratified therapies could be a viable solution for RCI healing. To adequately resolve potential treatments for RCI, further expanded and correlated animal trials must be undertaken, and indicative human trials are required with consideration of surgical and patient-specific influences

Quantitative anatomy of the posterior cricoid region

The anatomy of the posterior cricoid cartilage region was examined to obtain a better quantitative understanding of this region. The mean height and width of the posterior cricoid cartilage in the midline measured 24.5 mm and 25 mm respectively. The mean distance between the fibres for the left and right posterior cricoarytenoid muscles was 5 mm at the midpoint of the posterior cricoid cartilage. The height of these muscles averaged 19 mm for left sides and 20 mm for right sides. The mean distances from the midpoint and superior midline of the posterior cricoid cartilage to the inferior laryngeal nerve were 14 mm and 15 mm respectively for left sides and 17 mm and 18 mm respectively for right sides. It is hoped that these data will be of use to clinicians performing invasive procedures in this area

Examining Movement-Specific Reinvestment and Performance in Demanding Contexts.

Two experiments examined the roles of the dimensions of movement-specific reinvestment (movement self-consciousness and conscious motor processing) on performance under demanding conditions. In Experiment 1, novice golfers practiced a golf putting task and were tested under low- and high-anxiety conditions. Conscious motor processing was not associated with putting proficiency or movement variability; however, movement self-consciousness was positively associated with putting proficiency and appeared to be negatively associated with variability of impact velocity in low-anxiety conditions, but not in high-anxiety conditions. Increased anxiety and effort possibly left few attention resources for movement self-consciousness under high anxiety. In Experiment 2, participants performed a quiet standing task in single- and dual-task conditions. Movement self-consciousness was positively associated with performance when attention demands were low (single task) but not when attention demands were high (dual task). The findings provide insight into the differential influence of the two dimensions of movement-specific reinvestment under demanding conditions

Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning

Learning classifier systems (LCSs) are population-based predictive systems that were originally envisioned as agents to act in reinforcement learning (RL) environments. These systems can suffer from population bloat and so are amenable to compaction techniques that try to strike a balance between population size and performance. A well-studied LCS architecture is XCSF, which in the RL setting acts as a Q-function approximator. We apply XCSF to a deterministic and stochastic variant of the FrozenLake8x8 environment from OpenAI Gym, with its performance compared in terms of function approximation error and policy accuracy to the optimal Q-functions and policies produced by solving the environments via dynamic programming. We then introduce a novel compaction algorithm (Greedy Niche Mass Compaction - GNMC) and study its operation on XCSF's trained populations. Results show that given a suitable parametrisation, GNMC preserves or even slightly improves function approximation error while yielding a significant reduction in population size. Reasonable preservation of policy accuracy also occurs, and we link this metric to the commonly used steps-to-goal metric in maze-like environments, illustrating how the metrics are complementary rather than competitive

Shotgun proteomics as a powerful tool for the study of the proteomes of plants, their pathogens, and plant-pathogen interactions

The interaction between plants and pathogenic microorganisms is a multifaceted process mediated by both plant- and pathogen-derived molecules, including proteins, metabolites, and lipids. Large-scale proteome analysis can quantify the dynamics of proteins, biological pathways, and posttranslational modifications (PTMs) involved in the plant–pathogen interaction. Mass spectrometry (MS)-based proteomics has become the preferred method for characterizing proteins at the proteome and sub-proteome (e.g., the phosphoproteome) levels. MS-based proteomics can reveal changes in the quantitative state of a proteome and provide a foundation for understanding the mechanisms involved in plant–pathogen interactions. This review is intended as a primer for biologists that may be unfamiliar with the diverse range of methodology for MS-based shotgun proteomics, with a focus on techniques that have been used to investigate plant–pathogen interactions. We provide a summary of the essential steps required for shotgun proteomic studies of plants, pathogens and plant–pathogen interactions, including methods for protein digestion, identification, separation, and quantification. Finally, we discuss how protein PTMs may directly participate in the interaction between a pathogen and its host plant

Large-scale protein and phosphoprotein profiling to explore potato resistance mechanisms to Spongospora subterranea infection

Potato is one of the most important food crops for human consumption. The soilborne pathogen Spongospora subterranea infects potato roots and tubers, resulting in considerable economic losses from diminished tuber yields and quality. A comprehensive understanding of how potato plants respond to S. subterranea infection is essential for the development of pathogen-resistant crops. Here, we employed label-free proteomics and phosphoproteomics to quantify systemically expressed protein-level responses to S. subterranea root infection in potato foliage of the susceptible and resistant potato cultivars. A total of 2,669 proteins and 1,498 phosphoproteins were quantified in the leaf samples of the different treatment groups. Following statistical analysis of the proteomic data, we identified oxidoreductase activity, electron transfer, and photosynthesis as significant processes that differentially changed upon root infection specifically in the resistant cultivar and not in the susceptible cultivar. The phosphoproteomics results indicated increased activity of signal transduction and defense response functions in the resistant cultivar. In contrast, the majority of increased phosphoproteins in the susceptible cultivar were related to transporter activity and sub-cellular localization. This study provides new insight into the molecular mechanisms and systemic signals involved in potato resistance to S. subterranea infection and has identified new roles for protein phosphorylation in the regulation of potato immune response

Kinetic Control of Interpenetration in Fe-Biphenyl-4,4 '-dicarboxylate Metal-Organic Frameworks by Coordination and Oxidation Modulation

Phase control in the self-assembly of metal–organic frameworks (MOFs) is often a case of trial and error; judicious control over a number of synthetic variables is required to select the desired topology and control features such as interpenetration and defectivity. Herein, we present a comprehensive investigation of self-assembly in the Fe–biphenyl-4,4′-dicarboxylate system, demonstrating that coordination modulation can reliably tune between the kinetic product, noninterpenetrated MIL-88D(Fe), and the thermodynamic product, two-fold interpenetrated MIL-126(Fe). Density functional theory simulations reveal that correlated disorder of the terminal anions on the metal clusters results in hydrogen bonding between adjacent nets in the interpenetrated phase and this is the thermodynamic driving force for its formation. Coordination modulation slows self-assembly and therefore selects the thermodynamic product MIL-126(Fe), while offering fine control over defectivity, inducing mesoporosity, but electron microscopy shows MIL-88D(Fe) persists in many samples despite not being evident by diffraction. Interpenetration control is also demonstrated using the 2,2′-bipyridine-5,5′-dicarboxylate linker; it is energetically prohibitive for it to adopt the twisted conformation required to form the interpenetrated phase, although multiple alternative phases are identified due to additional coordination of Fe cations to its N donors. Finally, we introduce oxidation modulation—the use of metal precursors in different oxidation states from that found in the final MOF—to kinetically control self-assembly. Combining coordination and oxidation modulation allows the synthesis of pristine MIL-126(Fe) with BET surface areas close to the predicted maximum for the first time, suggesting that combining the two may be a powerful methodology for the controlled self-assembly of high-valent MOFs