On biosignatures for Mars

In this work, we address the difficulty of reliably identifying traces of life on Mars. Several independent lines of evidence are required to build a compelling body of proof. In particular, we underline the importance of correctly interpreting the geological and mineralogical context of the sites to be explored for the presence of biosignatures. We use as examples to illustrate this, ALH84001 (where knowledge of the geological context was very limited) and other terrestrial deposits, for which this could be properly established. We also discuss promising locations and formations to be explored by ongoing and future rover missions, including Oxia Planum, which, dated at 4.0 Ga, is the most ancient Mars location targeted for investigation yet

The synthesis of hydroxyapatite from artificially grown Red Sea hydrozoan coral for antimicrobacterial drug delivery system applications

The hydrozoan Millepora dichotoma (MD) is a typical Red Sea species containing a porous skeleton in the form of aragonite crystalline calcium carbonate. Due to environmental considerations, the artificial production of coralline species under controlled conditions is pertinent and underway. Artificially grown MD was used as a raw material for the production of calcium phosphate, mainly hydroxyapatite bioceramics, to be used in the drug delivery systems as a drug carrier or in the tissue engineering such as bone graft. DTA-TGA, XRD, FT-IR, Raman, and SEM analysis were carried out to analyze both unconverted and converted artificial corals. Hydrothermally converted coral fine powders were loaded with gentamicin (Gm) antibiotic, and the drug-loaded particles were analyzed by SEM. Unconverted coral was mainly aragonite, while hydrothermally treated coral was completely converted to hydroxyapatite. Hydrothermally treated coral was showing agglomerated nodules up to 1-μm size consisting of nanocrystalline hydroxyapatite platelets in the size range of less than 100 nm. The general macropore size of the coral was found to be appropriate for osteoid growth, which is 100 to 600 μm range. These artificially grown corals can be easily produced and used for bone growth and repair and other biomedical applications

Mindfulness and Behavior Change

Initiating and maintaining behavior change is key to the prevention and treatment of most preventable chronic medical and psychiatric illnesses. The cultivation of mindfulness, involving acceptance and nonjudgment of present-moment experience, often results in transformative health behavior change. Neural systems involved in motivation and learning have an important role to play. A theoretical model of mindfulness that integrates these mechanisms with the cognitive, emotional, and self-related processes commonly described, while applying an integrated model to health behavior change, is needed. This integrative review (1) defines mindfulness and describes the mindfulness-based intervention movement, (2) synthesizes the neuroscience of mindfulness and integrates motivation and learning mechanisms within a mindful self-regulation model for understanding the complex effects of mindfulness on behavior change, and (3) synthesizes current clinical research evaluating the effects of mindfulness-based interventions targeting health behaviors relevant to psychiatric care. The review provides insight into the limitations of current research and proposes potential mechanisms to be tested in future research and targeted in clinical practice to enhance the impact of mindfulness on behavior change

First Record of Fusarium verticillioides as an Entomopathogenic Fungus of Grasshoppers

Fusarium verticillioides (Saccardo) Nirenberg (Ascomycota: Hypocreales) is the most common fungus reported on infected corn kernels and vegetative tissues, but has not yet been documented as being entomopathogenic for grasshoppers. Grasshoppers and locusts represent a large group of insects that cause economic damage to forage and crops. Tropidacris collaris (Stoll) (Orthoptera: Acridoidea: Romaleidae) is a large and voracious grasshopper that in recent years has become an increasingly recurrent and widespread pest in progressively more greatly extended areas of some of in Argentina's northern provinces, with chemical insecticides being currently the only means of control. During February and March of 2008–09, nymphs and adults of T. collaris were collected with sweep nets in dense woodland vegetation at a site near Tres Estacas in western Chaco Province, Argentina, and kept in screened cages. F. verticillioides was isolated from insects that died within 10 days and was cultured in PGA medium. Pathogenicity tests were conducted and positive results recorded. Using traditional and molecular-biological methods, an isolate of F. verticillioides was obtained from T. collaris, and its pathogenecity in the laboratory was shown against another harmful grasshopper, Ronderosia bergi (Stål) (Acridoidea: Acrididae: Melanoplinae). The mortality caused by F. verticillioides on R. bergi reached 58 ± 6.53% by 10 days after inoculation. This is the first record of natural infection caused by F. verticillioides in grasshoppers

Membrane-binding peptides for extracellular vesicles on-chip analysis

Small extracellular vesicles (sEVs) present fairly distinctive lipid membrane features in the extracellular environment. These include high curvature, lipid-packing defects and a relative abundance in lipids such as phosphatidylserine and ceramide. sEV membrane could be then considered as a "universal" marker, alternative or complementary to traditional, characteristic, surface-associated proteins. Here, we introduce the use of membrane-sensing peptides as new, highly efficient ligands to directly integrate sEV capturing and analysis on a microarray platform. Samples were analysed by label-free, single-particle counting and sizing, and by fluorescence co-localisation immune staining with fluorescent anti-CD9/anti-CD63/anti-CD81 antibodies. Peptides performed as selective yet general sEV baits and showed a binding capacity higher than anti-tetraspanins antibodies. Insights into surface chemistry for optimal peptide performances are also discussed, as capturing efficiency is strictly bound to probes surface orientation effects. We anticipate that this new class of ligands, also due to the versatility and limited costs of synthetic peptides, may greatly enrich the molecular toolbox for EV analysis

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases

Fluidoterapia enteral em cavalos: relato de casos clínicos e cirúrgicos

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