Designing topographically textured microparticles for induction and modulation of osteogenesis in mesenchymal stem cell engineering

Mesenchymal stem cells are the focus of intense research in bone development and regeneration. The potential of microparticles as modulating moieties of osteogenic response by utilizing their architectural features is demonstrated herein. Topographically textured microparticles of varying microscale features are produced by exploiting phase-separation of a readily soluble sacrificial component from polylactic acid. The influence of varying topographical features on primary human mesenchymal stem cell attachment, proliferation and markers of osteogenesis is investigated. In the absence of osteoinductive supplements, cells cultured on textured microparticles exhibit notably increased expression of osteogenic markers relative to conventional smooth microparticles. They also exhibit varying morphological, attachment and proliferation responses. Significantly altered gene expression and metabolic profiles are observed, with varying histological characteristics in vivo. This study highlights how tailoring topographical design offers cell-instructive 3D microenvironments which allow manipulation of stem cell fate by eliciting the desired downstream response without use of exogenous osteoinductive factors

Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including E. coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate limiting steps in biological ethylene production. We employed a combination of genome scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to the EFE enzyme (WT vs mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges

Takotsubo cardiomyopathy after a dancing session: a case report

<p>Abstract</p> <p>Introduction</p> <p>Stress-induced (Takotsubo) cardiomyopathy is a rare form of cardiomyopathy which presents in a manner similar to that of acute coronary syndrome. This sometimes leads to unnecessary thrombolysis therapy. The pathogenesis of this disease is still poorly understood. We believe that reporting all cases of Takotsubo cardiomyopathy will contribute to a better understanding of this disease. Here, we report a patient who, in the absence of any recent stressful events in her life, developed the disease after a session of dancing.</p> <p>Case presentation</p> <p>A 69-year-old Caucasian woman presented with features suggestive of acute coronary syndrome shortly after a session of dancing. Echocardiography and a coronary angiogram showed typical features of Takotsubo cardiomyopathy and our patient was treated accordingly. Eight weeks later, her condition resolved completely and the results of echocardiography were totally normal.</p> <p>Conclusions</p> <p>Takotsubo cardiomyopathy, though transient, is a rare and serious condition. Although it is commonly precipitated by stressful life events, these are not necessarily present. Our patient was enjoying one of her hobbies (that is, dancing) when she developed the disease. This case has particular interest in medicine, especially for the specialties of cardiology and emergency medicine. We hope that it will add more information to the literature about this rare condition.</p

Vegetable oils composition affects the intestinal lymphatic transport and systemic bioavailability of co-administered lipophilic drug cannabidiol

Although natural sesame oil has been shown to facilitate the lymphatic delivery and oral bioavailability of the highly lipophilic drug cannabidiol (CBD), considerable variability remains an unresolved challenge. Vegetable oils differ substantially in composition, which could lead to differences in promotion of intestinal lymphatic transport of lipophilic drugs. Therefore, the differences in composition of sesame, sunflower, peanut, soybean, olive and coconut oils and their corresponding role as vehicles in promoting CBD lymphatic targeting and bioavailability were investigated in this study. The comparative analysis suggests that the fatty acids profile of vegetable oils is overall similar to the fatty acids profile in the corresponding chylomicrons in rat lymph. However, arachidonic acid (C20:4), was introduced to chylomicrons from endogenous nondietary sources. Overall, fatty acid composition of natural vegetable oils vehicles affected the intestinal lymphatic transport and bioavailability of CBD following oral administration in this work. Olive oil led to the highest concentration of CBD in the lymphatic system and in the systemic circulation in comparison to the other natural vegetable oils following oral administration in rats

Predicting lameness in dairy cattle using untargeted liquid chromatography–mass spectrometry-based metabolomics and machine learning

ABSTRACT: Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0–3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at −86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted