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17[P17] strains, also identified in related clinical samples. Despite several limitations, combining RdRp- and VP1-targeted metagenomics is a sensitive approach allowing the study NoV diversity in low-contaminated foods and the identification of NoV strains implicated in outbreaks.We tested the bioactivity of aqueous extracts of Ludwigia spp. (Myrtales Onagraceae) on the biological cycle of Plutella xylostella. We assessed the duration of and viability during the larval, pupal and adult phases, as well as the influence of the extracts on the fecundity and hatching of P. xylostella eggs. Subsequently, we phytochemically screened the extracts. The extracts of L. tomentosa and L. longifolia reduced the pupal weight instead of prolonging the larval stage of P. xylostella. The L. tomentosa effect caused higher larval mortality and reduced the fecundity and hatching of P. xylostella eggs, and L. sericea reduced the egg survival. The phenolic compounds-flavonoids, condensed tannins and alkaloids-were more abundant in L. nervosa, L. tomentosa, L. sericea and L. longifolia. The L. tomentosa, L. longifolia and L. sericea extracts were bioactive, and these species showed the best results regarding their ability to control P. xylostella populations, because these plants produce substances able to inhibit food consumption and interfere with the morphological and physiological transformations of the offspring and the oviposition of adults.In this work, we prepared color-changing colloids by using the electrostatic self-assembly approach. check details The supramolecular structures are composed of a pH-responsive polymeric surfactant and the water-soluble porphyrin 5,10,15,20-tetrakis-(sulfonatophenyl)porphyrin (TPPS). The pH-responsive surfactant polymer was achieved by the chemical modification of an alternating aliphatic polyketone (PK) via the Paal-Knorr reaction with N-(2-hydroxyethyl)ethylenediamine (HEDA). The resulting polymer/dye supramolecular systems form colloids at the submicron level displaying negative zeta potential at neutral and basic pH, and, at acidic pH, flocculation is observed. Remarkably, the colloids showed a gradual color change from green to pinky-red due to the protonation/deprotonation process of TPPS from pH 2 to pH 12, revealing different aggregation behavior.Helicobacter pylori is a class one carcinogen which causes chronic atrophic gastritis, gastric intestinal metaplasia, dysplasia and adenocarcinoma. The mechanisms by which H. pylori interacts with other risk and protective factors, particularly vitamin C in gastric carcinogenesis are complex. Gastric carcinogenesis includes metabolic, environmental, epigenetic, genomic, infective, inflammatory and oncogenic pathways. The molecular classification of gastric cancer subtypes has revolutionized the understanding of gastric carcinogenesis. This includes the tumour microenvironment, germline mutations, and the role of Helicobacter pylori bacteria, Epstein Barr virus and epigenetics in somatic mutations. There is evidence that ascorbic acid, phytochemicals and endogenous antioxidant systems can modify the risk of gastric cancer. Gastric juice ascorbate levels depend on dietary intake of ascorbic acid but can also be decreased by H. pylori infection, H. pylori CagA secretion, tobacco smoking, achlorhydria and chronic atrophic gastritis. Ascorbic acid may be protective against gastric cancer by its antioxidant effect in gastric cytoprotection, regenerating active vitamin E and glutathione, inhibiting endogenous N-nitrosation, reducing toxic effects of ingested nitrosodimethylamines and heterocyclic amines, and preventing H. pylori infection. The effectiveness of such cytoprotection is related to H. pylori strain virulence, particularly CagA expression. The role of vitamin C in epigenetic reprogramming in gastric cancer is still evolving. Other factors in conjunction with vitamin C also play a role in gastric carcinogenesis. Eradication of H. pylori may lead to recovery of vitamin C secretion by gastric epithelium and enable regression of premalignant gastric lesions, thereby interrupting the Correa cascade of gastric carcinogenesis.This study aimed to explore how the type and visual modality of a recommendation agent's identity affect male university students' (1) self-reported responses to agent-recommended symbolic brand in evaluating the naturalness of virtual agents, human, or artificial intelligence (AI) and (2) early event-related potential (ERP) responses between text- and face-specific scalp locations. Twenty-seven participants (M = 25.26, SD = 5.35) whose consumption was more motivated by symbolic needs (vs. functional) were instructed to perform a visual task to evaluate the naturalness of the target stimuli. As hypothesized, the subjective evaluation showed that they had lower attitudes and perceived higher unnaturalness when the symbolic brand was recommended by AI (vs. human). Based on this self-report, two epochs were segmented for the ERP analysis human-natural and AI-unnatural. As revealed by P100 amplitude modulation on visual modality of two agents, their evaluation relied more on face image rather than text. Furthermore, this tendency was consistently observed in that of N170 amplitude when the agent identity was defined as human. However, when the agent identity was defined as AI, reversed N170 modulation was observed, indicating that participants referred more to textual information than graphical information to assess the naturalness of the agent.Vibroarthrography (VAG) is a non-invasive and potentially widely available method supporting the joint diagnosis process. This research was conducted using VAG signals classified to five different condition classes three stages of chondromalacia patellae, osteoarthritis, and control group (healthy knee joint). Ten new spectral features were proposed, distinguishing not only neighboring classes, but every class combination. Additionally, Frequency Range Maps were proposed as the frequency feature extraction visualization method. The results were compared to state-of-the-art frequency features using the Bhattacharyya coefficient and the set of ten different classification algorithms. All methods evaluating proposed features indicated the superiority of the new features compared to the state-of-the-art. In terms of Bhattacharyya coefficient, newly proposed features proved to be over 25% better, and the classification accuracy was on average 9% better.