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Due to the emergence of the coronavirus disease (COVID 19), education systems in most countries have adapted and quickly changed their teaching strategy to online teaching. This paper presents the design and implementation of a novel Internet of Things (IoT) device, called MEIoT weather station, which incorporates an exogenous disturbance input, within the National Digital Observatory of Smart Environments (OBNiSE) architecture. The exogenous disturbance input involves a wind blower based on a DC brushless motor. It can be controlled, via Node-RED platform, manually through a sliding bar, or automatically via different predefined profile functions, modifying the wind speed and the wind vane sensor variables. An application to Engineering Education is presented with a case study that includes the instructional design for the least-squares regression topic for linear, quadratic, and cubic approximations within the Educational Mechatronics Conceptual Framework (EMCF) to show the relevance of this proposal. This work's main contribution to the state-of-the-art is to turn a weather monitoring system into a hybrid hands-on learning approach thanks to the integrated exogenous disturbance input.Neofusicoccum parvum is a fungal plant-pathogen belonging to the family Botryosphaeriaceae, and is considered one of the most aggressive causal agents of the grapevine trunk disease (GTD) Botryosphaeria dieback. In this study, the mycovirome of a single strain of N. parvum (COLB) was characterized by high throughput sequencing analysis of total RNA and subsequent bioinformatic analyses. Contig annotations, genome completions, and phylogenetic analyses allowed us to describe six novel mycoviruses belonging to four different viral families. The virome is composed of two victoriviruses in the family Totiviridae, one alphaendornavirus in the family Endornaviridae, two mitoviruses in the family Mitoviridae, and one narnavirus belonging to the family Narnaviridae. The presence of the co-infecting viruses was confirmed by sequencing the RT-PCR products generated from total nucleic acids extracted from COLB. This study shows that the mycovirome of a single N. parvum strain is highly diverse and distinct from that previously described in N. parvum strains isolated from grapevines.Fusion cages composed of titanium and its alloys are emerging as valuable alternative to standard polyetheretherketone (PEEK) ones routinely used in cervical and lumbar spine surgery. Aim of this study was to evaluate osteo-inductive and osteo-conductive ability of an innovative trabecular titanium (T-Ti) scaffold on human mesenchymal stem cells (hMSCs), in both absence and presence of biochemical osteogenic stimuli. Same abilities were assessed on PEEK and standard 2D plastic surface, the latter meant as gold-standard for in vitro differentiation studies. hMSCs adhered and colonized both T-Ti and PEEK scaffolds. In absence of osteogenic factors, T-Ti triggered osteogenic induction of MSCs, as demonstrated by alkaline phosphatase activity and calcium deposition increments, while PEEK and standard 2D did not. Addition of osteogenic stimuli reinforced osteogenic differentiation of hMSCs cultured on T-Ti in a significantly higher manner with respect to standard 2D plastic culture surfaces, whereas PEEK almost completely abolished the process. T-Ti driven differentiation towards osteoblasts was confirmed by gene and marker expression analyses, even in absence of osteogenic stimuli. These results clearly indicate superior in vitro osteo-inductive and osteo-conductive capacity of T-Ti compared to PEEK, and make ground for further studies supporting the use of T-Ti cages to improve bone fusion.The results of the qualitative composition analysis of the dried biomass extracts of in vitro callus, cell suspension, and root cultures show that the main biologically active substances (BAS) in the medicinal plant, Rhodiola rosea, are 6-C-(1-(4-hydroxyphenyl)ethyl)aromadendrin (25 mg, yield 0.21%), 2-(3,7-dihydroxy-2-(2-hydroxypropan-2-yl)-2,3-dihydrobenzofuran-5-yl)-6,7-dihydroxychroman-4-one (23 mg, yield 0.2%), 2-(3,4-dimethoxyphenyl)-5,7-dimethoxychroman-4-one (175 mg, yield 1.5%), 5,7-dihydroxy-2-(4-hydroxy-3-(2-(4-hydroxyphenyl)-4-oxo-4H-chromen-6-yl)phenyl)-4H-chromen-4-one (45 mg, yield 0.5%), 5,6,7,8-tetrahydroxy-4-methoxyflavone (0.35 mg, 0.5%). BAS from the dried biomass extracts of in vitro callus, cell suspension, and root cultures of Rhodiola rosea will be used for the production of pharmaceuticals and dietary supplements with antitumor, antimicrobial, and antioxidant effects.Visceral hemangiosarcoma (HSA) is one of the more frequent cancers in dogs and has a high metastatic rate and poor prognosis, as clinical signs only become apparent in advanced stages of tumor development. In order to improve early and differential diagnostic capabilities and hence, prognosis for dogs with HSA, two types of biomarker are needed a point-of-care diagnostic biomarker and a prognostic biomarker-preferentially based on samples obtained with minimally invasive methods. In this study, we applied a lectin magnetic bead array-coupled tandem mass spectrometry (LeMBA-MS/MS) workflow through discovery and validation phases to discover serum glycoprotein biomarker candidates for canine HSA. By this approach, we found that Datura stramonium (DSA), wheat germ agglutinin (WGA), Sambucus nigra (SNA), and Pisum sativum (PSA) lectins captured the highest number of validated candidate glycoproteins. Secondly, we independently validated serum LeMBA-MS/MS results by demonstrating the in situ relationship of lectin-binding with tumor cells. Using lectin-histochemistry and immunohistochemistry (IHC) for key proteins on tissues with HSA and semi-quantitation of the signals, we demonstrate that a combination of DSA histochemistry and IHC for complement C7 greatly increases the prospect of a more specific diagnosis of canine HSA.Advances in high-throughput technologies encourage the generation of large amounts of multiomics data to investigate complex diseases, including breast cancer. Given that the aetiologies of such diseases extend beyond a single biological entity, and that essential biological information can be carried by all data regardless of data type, integrative analyses are needed to identify clinically relevant patterns. To facilitate such analyses, we present a permutation-based framework for random forest methods which simultaneously allows the unbiased integration of mixed-type data and assessment of relative feature importance. Through simulation studies and machine learning datasets, the performance of the approach was evaluated. The results showed minimal multicollinearity and limited overfitting. [https://www.selleckchem.com/products/d-1553.html selleck kinase inhibitor] To further assess the performance, the permutation-based framework was applied to high-dimensional mixed-type data from two independent breast cancer cohorts. Reproducibility and robustness of our approach was demonstrated by the concordance in relative feature importance between the cohorts, along with consistencies in clustering profiles.