A total of 132 Rhizoctonia isolates were recovered from red cabbage plants with root rot and wirestem symptoms in the province of Samsun (Turkey) between 2018 and 2019. Based on the sequence analysis of the internal transcribed spacer (ITS) region located between the 18S and 28S ribosomal RNA genes and including nuclear staining, these 124 isolates were assigned to multinucleate Rhizoctonia solani, and eight were binucleate Rhizoctonia. The most prevalent anastomosis group (AG) was AG 4 (84%), which was subdivided into AG 4 HG-I (81%) and AG 4 HG-III (3%), followed by AG 5 (10%) and AG-A (6%), respectively. The unweighted pair group method phylogenetic tree resulting from the data of 68 isolates with the inter-PBS amplification DNA profiling method based on interspersed retrotransposon element sequences confirmed the differentiation of AGs with a higher resolution. In the greenhouse experiment with representative isolates (n = 24) from AGs on red cabbage (cv. Rondale), the disease severity index was between 3.33 and 4.0 for multinucleate AG isolates and ranged from 2.5 to 3.17 for AG-A isolates. In the pathogenicity assay of six red cabbage cultivars, one isolate for each AG was tested using a similar method, and all cultivars were susceptible to AG 4 HG-I and AG 4 HG-III isolates. Redriver and Remale were moderately susceptible, while Rescue, Travero, Integro, and Rondale were susceptible to the AG 5 isolate. The results indicate that the most prevalent and aggressive AGs of Rhizoctonia are devastating pathogens to red cabbage, which means that rotation with nonhost-crops for these AGs may be the most effective control strategy. This is the first comprehensive study of Rhizoctonia isolates in red cabbage using a molecular approach to assess genetic diversity using iPBS-amplified DNA profiling.Phospholipases-D (PLDs) found in Loxosceles spiders’ venoms are responsible for the dermonecrosis triggered by envenomation. PLDs can also induce other local and systemic effects, such as massive inflammatory response, edema, and hemolysis. Recombinant PLDs reproduce all of the deleterious effects induced by Loxosceles whole venoms. Herein, wild type and mutant PLDs of two species involved in accidents-L. gaucho and L. laeta-were recombinantly expressed and characterized. The mutations are related to amino acid residues relevant for catalysis (H12-H47), magnesium ion coordination (E32-D34) and binding to phospholipid substrates (Y228 and Y228-Y229-W230). Circular dichroism and structural data demonstrated that the mutant isoforms did not undergo significant structural changes. Immunoassays showed that mutant PLDs exhibit conserved epitopes and kept their antigenic properties despite the mutations. Both in vitro (sphingomyelinase activity and hemolysis) and in vivo (capillary permeability, dermonecrotic activity, and histopathological analysis) assays showed that the PLDs with mutations H12-H47, E32-D34, and Y228-Y229-W230 displayed only residual activities. Results indicate that these mutant toxins are suitable for use as antigens to obtain neutralizing antisera with enhanced properties since they will be based on the most deleterious toxins in the venom and without causing severe harmful effects to the animals in which these sera are produced.In this work, we assess three different methods for the extraction of pectin from waste orange peels, using water as extracting solvent. Endoxifen purchase “Hot-water”, Rapid Solid Liquid Dynamic (RSLD) and microwave-assisted extractions have been compared and evaluated in terms of amount and quality of extracted pectin, as well as embodied energy. This analysis provides useful guidelines for pectin production from food waste according to green procedures, enabling the identification of acidic “hot-water” as the most sustainable extraction route.Megalothorax minimus (Neelidae) and Sphaeridia pumilis (Sminthurididae) had already been identified in surface sampling from Sierra de Guadarrama. In Europe, Sminthurinus gisini (Katiannidae) seems to be associated with environments at specific altitudes, and has little representation in this sampling. Pygmarrhopalites custodum Baquero and Jordana sp. nov. (Arrhopalitidae) coexists with two previously identified surface occurring species of the same family (P. elegans and Arrhopalites caecus). However, P. custodum is more abundant, indicating that it occupies an ecological niche tending to troglophile in the mesovoid shallow substratum (MSS). Moreover, it is also more abundant in the MSS of higher altitude corresponding to the bioclimatic zones cryo-oro-Mediterranean and oro-Mediterranean supra forest. Allacma cryptica Baquero and Jordana sp. nov. (Sminthuridae), is another species that had not been previously detected on the surface in the study area. A. cryptica is an addition to a genus which has eight described species. Gisinurus malatestai (Sminthuridae) appears well represented in the MSS, being a species present very occasionally in the Mediterranean area. Two species of the genera Sminthurides (Sminthurididae) and Fasciosminthurus (Bourletiellidae) have been found, but they could not have been identified to the species level. Finally, a few specimens of Dicyrtomina minuta (Dicyrtomidae), an abundant species on the surface, have been captured.Hepatocellular Carcinoma (HCC) is the most common malignant liver tumor, being present in 70% of liver cancer cases. It usually evolves on the top of the cirrhotic parenchyma. The most reliable method for HCC diagnosis is the needle biopsy, which is an invasive, dangerous method. In our research, specific techniques for non-invasive, computerized HCC diagnosis are developed, by exploiting the information from ultrasound images. In this work, the possibility of performing the automatic diagnosis of HCC within B-mode ultrasound and Contrast-Enhanced Ultrasound (CEUS) images, using advanced machine learning methods based on Convolutional Neural Networks (CNN), was assessed. The recognition performance was evaluated separately on B-mode ultrasound images and on CEUS images, respectively, as well as on combined B-mode ultrasound and CEUS images. For this purpose, we considered the possibility of combining the input images directly, performing feature level fusion, then providing the resulted data at the entrances of representative CNN classifiers.