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In a recent study, we have identified BPH03 as a promising scaffold for the development of compounds aimed at modulating the interaction between PED/PEA15 (Phosphoprotein Enriched in Diabetes/Phosphoprotein Enriched in Astrocytes 15) and PLD1 (phospholipase D1), with potential applications in type II diabetes therapy. PED/PEA15 is known to be overexpressed in certain forms of diabetes, where it binds to PLD1, thereby reducing insulin-stimulated glucose transport. The inhibition of this interaction reestablishes basal glucose transport, indicating PED as a potential target of ligands capable to recover glucose tolerance and insulin sensitivity. In this study, we employ computational methods to provide a detailed description of BPH03 interaction with PED, evidencing the presence of a hidden druggable pocket within its PLD1 binding surface. We also elucidate the conformational changes that occur during PED interaction with BPH03. Moreover, we report new NMR data supporting the in-silico findings and indicating that BPH03 disrupts the PED/PLD1 interface displacing PLD1 from its interaction with PED. Our study represents a significant advancement toward the development of potential therapeutics for the treatment of type II diabetes.

This paper describes the theoretical and practical aspects of Immersive Education, an educational methodology based on interactive narratives, articulated as emotional journeys, to develop competencies. It has been developed throughout three school years (2021–2024) with more than 400 students (8–12 years old) in Public Schools in Italy and Spain. Immersive Education can be integrated with curricular school activities and can be used to target both curricular and transversal learning objectives, specifically the ones connected with the Personal, Social and Learning to learn Key Competence (LifeComp European framework). The paper describes the inspirations that led to the creation of the methodology, including similar experiential learning approaches. It then analyses the theoretical principles of the methodology, dividing them in four key-concepts, along with psychological evidence supporting them. The four key-concepts describe how immersive education aims at being a motivation trigger, featuring a dramatic structure, how it is based on the involvement of the self, and how it focuses on fostering a continuous engagement. It continues with a detailed analysis of implementation strategies, specifically about the management of emotional triggers and reactions, enriched by numerous examples taken from the projects implemented with the students. The conclusions open the way to future research directions to measure the impact of this approach on the development of transversal and specific competences.

Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, machine learning can be applied to agriculture. Better crop management, plant health assessment, and early disease detection are some of the main challenges facing the agricultural sector. Plant phenotyping can play a key role in addressing these challenges, especially when combined with machine learning techniques. Therefore, this study reviews available scientific literature on the applications of machine learning algorithms in plant phenotyping with a specific focus on sunflowers. The most common algorithms in the agricultural field are described to emphasise possible uses. Subsequently, the overview highlights machine learning application on phenotyping in three primaries areas: crop management (i.e., yield prediction, biomass estimation, and growth stage monitoring), plant health (i.e., nutritional status and water stress), and disease detection. Finally, we focus on the adoption of machine learning techniques in sunflower phenotyping. The role of machine learning in plant phenotyping has been thoroughly investigated. Artificial neural networks and stacked models seems to be the best way to analyse data.

This paper describes the theoretical and practical aspects of Immersive Education, an educational methodology based on interactive narratives, articulated as emotional journeys, to develop competencies. It has been developed throughout three school years (2021–2024) with more than 400 students (8–12 years old) in Public Schools in Italy and Spain. Immersive Education can be integrated with curricular school activities and can be used to target both curricular and transversal learning objectives, specifically the ones connected with the Personal, Social and Learning to learn Key Competence (LifeComp European framework). The paper describes the inspirations that led to the creation of the methodology, including similar experiential learning approaches. It then analyses the theoretical principles of the methodology, dividing them in four key-concepts, along with psychological evidence supporting them. The four key-concepts describe how immersive education aims at being a motivation trigger, featuring a dramatic structure, how it is based on the involvement of the self, and how it focuses on fostering a continuous engagement. It continues with a detailed analysis of implementation strategies, specifically about the management of emotional triggers and reactions, enriched by numerous examples taken from the projects implemented with the students. The conclusions open the way to future research directions to measure the impact of this approach on the development of transversal and specific competences. [ABSTRACT FROM AUTHOR]

IntroductionDespite the well-established evidence supporting the restorative potential of nature exposure, the neurophysiological underpinnings of the restorative cognitive/emotional effect of nature are not yet fully understood. The main purpose of the current study was to investigate the association between exposure to nature and electroencephalography (EEG) functional connectivity in the distress network.MethodsFifty-three individuals (11 men and 42 women; mean age 21.38 ± 1.54 years) were randomly assigned to two groups: (i) a green group and (ii) a gray group. A slideshow consisting of images depicting natural and urban scenarios were, respectively, presented to the green and the gray group. Before and after the slideshow, 5 min resting state (RS) EEG recordings were performed. The exact low-resolution electromagnetic tomography (eLORETA) software was used to execute all EEG analyses.ResultsCompared to the gray group, the green group showed a significant increase in positive emotions (F1; 50 = 9.50 p = 0.003) and in the subjective experience of being full of energy and alive (F1; 50 = 4.72 p = 0.035). Furthermore, as compared to urban pictures, the exposure to natural images was associated with a decrease of delta functional connectivity in the distress network, specifically between the left insula and left subgenual anterior cingulate cortex (T = −3.70, p = 0.023).DiscussionOur results would seem to be in accordance with previous neurophysiological studies suggesting that experiencing natural environments is associated with brain functional dynamics linked to emotional restorative processes.

During the act of counting, our perceptual system may rely on information coming from different sensory channels. However, when the information coming from different sources is discordant, such as in the case of a de-synchronization between visual stimuli to be counted and irrelevant auditory stimuli, the performance in a sequential counting task might deteriorate. Such deterioration may originate from two different mechanisms, both linked to exogenous attention attracted by auditory stimuli. Indeed, exogenous auditory triggers may infiltrate our internal "counter", interfering with the counting process, resulting in an overcount; alternatively, the exogenous auditory triggers may disrupt the internal "counter" by deviating participants' attention from the visual stimuli, resulting in an undercount. We tested these hypotheses by asking participants to count visual discs sequentially appearing on the screen while listening to task-irrelevant sounds, in systematically varied conditions: visual stimuli could be synchronized or de-synchronized with sounds; they could feature regular or irregular pacing; and their speed presentation could be fast (approx. 3/sec), moderate (approx. 2/sec), or slow (approx. 1.5/sec). Our results support the second hypothesis since participants tend to undercount visual stimuli in all harder conditions (de-synchronized, irregular, fast sequences). We discuss these results in detail, adding novel elements to the study of crossmodal interference.

BackgroundThe peptide VLL-28, identified in the sequence of an archaeal protein, the transcription factor Stf76 from Sulfolobus islandicus, was previously identified and characterized as an antimicrobial peptide, possessing a broad-spectrum antibacterial activity.MethodsThrough a combined approach of NMR and Circular Dichroism spectroscopy, Dynamic Light Scattering, confocal microscopy and cell viability assays, the interaction of VLL-28 with the membranes of both parental and malignant cell lines has been characterized and peptide mechanism of action has been studied.ResultsIt is here demonstrated that VLL-28 selectively exerts cytotoxic activity against murine and human tumor cells. By means of structural methodologies, VLL-28 interaction with the membranes has been proven and the binding residues have been identified. Confocal microscopy data show that VLL-28 is internalized only into tumor cells. Finally, it is shown that cell death is mainly caused by a time-dependent activation of apoptotic pathways.ConclusionsVLL-28, deriving from the archaeal kingdom, is here found to be endowed with selective cytotoxic activity towards both murine and human cancer cells and consequently can be classified as an ACP.General significanceVLL-28 represents the first ACP identified in an archaeal microorganism, exerting a trans-kingdom activity.

Previous research consistently reported that subjects that were exclusively breastfed (eBF) vs. not-exclusively breastfed (neBF) during infancy (0–6 months) showed increased scores of general intelligence measures (e.g., the intelligence quotient). However, the existent literature largely neglected whether breastfeeding also affects specific cognitive processes, such as attention and working memory (WM) capacity. We tested whether eBF vs. neBF subjects showed performance differences in relation to these two core cognitive functions. The Attention Network Test (ANT), to measure alerting, orienting, and conflict, and the Change Colour Task (CCT), to measure visuospatial WM capacity, were administered to 144 participants divided according to age (6-, 10-, and 18-year-old participants) and breastfeeding (eBF or neBF during 0–6 months of life). Importantly, the sub-groups were homogenous in terms of maternal education, a factor potentially affecting the relation between breastfeeding and cognition. While we found increased performance as a function of participants’ age in both tasks, we failed to observe effects related to breastfeeding, as evidenced by Bayesian analyses. These findings highlight for the first time that the pattern of nutrition provided during early infancy does not appear to affect the development of attention and WM capacity, at least starting from the age considered in the present study.

The Stroop effect is a well-documented phenomenon, demonstrating both interference and facilitation effects. Many versions of the Stroop task were created, according to the purposes of its applications, varying in numerous aspects. While many versions are developed to investigate the mechanisms of the effect itself, the Stroop effect is also considered a general measure of attention, inhibitory control, and executive functions. In this paper, we implement “eStroop”: a new digital version based on verbal responses, measuring the main processes involved in the traditional effect. eStroop features four categories of stimuli in four different colors: (1) geometrical shapes, (2) neutral words, (3) congruent words, and (4) incongruent words. The results of the administration to 307 University students confirm the Stroop effect and offer baseline data for future research and clinical testing. Direct comparisons with other recent versions of the task are discussed, offering insights into differences and similarities between different task variables.

The public health has declared an international state of emergency due to the spread of a new coronavirus (SARS-CoV-2) representing a real pandemic threat so that to find potential therapeutic agents is a dire need. To this aim, the SARS-CoV-2 spike (S) glycoprotein represents a crucial target for vaccines, therapeutic antibodies, and diagnostics. Since virus binding to ACE-2 alone could not be sufficient to justify such severe infection, in order to facilitate medical countermeasure development and to search for new targets, two further regions of S protein have been taken into consideration here. One is represented by the recently identified ganglioside binding site, exactly localized in our study in the galectin-like domain, and the other one by the putative integrin binding sites contained in the RBD. We propose that a cooperating therapy using inhibitors against multiple targets altogether i.e., ACE2, integrins and sugars could be definitely more effective.

Osteoporosis is a disease characterized by low bone mass and alterations of bone microarchitecture, with an increased risk of fractures. It is a multifactorial disorder that is more frequent in postmenopausal women but can be associated to other diseases (inflammatory and metabolic diseases). At present, several options are available to treat osteoporosis trying to block bone reabsorption and reduce the risk of fracture. Anyway, these drugs have safety and tolerance problems in long-term treatment. Recently, gut microbiota has been highlighted to have strong influence on bone metabolism, becoming a potential new target to modify bone mineral density. Such evidences are mainly based on mouse models, showing an involvement in modulating the interaction between the immune system and bone cells. Germ-free mice represent a basic model to understand the interaction between microbiota, immune system, and bone cells, even though data are controversial. Anyway, such models have unequivocally demonstrated a connection between such systems, even if the mechanism is unclear. Gut microbiota is a complex system that influences calcium and vitamin D absorption and modulates gut permeability, hormonal secretion, and immune response. A key role is played by the T helper 17 lymphocytes, TNF, interleukin 17, and RANK ligand system. Other important pathways include NOD1, NOD2, and Toll-like receptor 5. Prebiotics and probiotics are a wide range of substances and germs that can influence and modify microbiota. Several studies demonstrated actions by different prebiotics and probiotics in different animals, differing according to sex, age, and hormonal status. Data on the effects on humans are poor and controversial. Gut microbiota manipulation appears a possible strategy to prevent and treat osteopenia and/or osteoporosis as well as other possible bone alterations, even though further clinical studies are necessary to identify correct procedures in humans.

Multiple sclerosis (MS) belongs to demyelinating diseases, which are progressive and highly debilitating pathologies that imply a high burden both on individual patients and on society. Currently, several treatment strategies differ in the route of administration, adverse events, and possible risks. Side effects associated with multiple sclerosis medications range from mild symptoms, such as flu-like or irritation at the injection site, to serious ones, such as progressive multifocal leukoencephalopathy and other life-threatening events. Moreover, the agents so far available have proved incapable of fully preventing disease progression, mostly during the phases that consist of continuous, accumulating disability. Thus, new treatment strategies, able to halt or even reverse disease progression and specific for targeting solely the pathways that contribute to the disease pathogenesis, are highly desirable. Here, we provide an overview of the recent literature about peptide-based systems tested on experimental autoimmune encephalitis (EAE) models. Since peptides are considered a unique therapeutic niche and important elements in the pharmaceutical landscape, they could open up new therapeutic opportunities for the treatment of MS.

The present work is focused on a detailed description of an in-house, particle-in-cell code developed by the authors, whose main aim is to perform highly accurate plasma simulations on an off-the-shelf computing platform in a relatively short computational time, despite the large number of macro-particles employed in the computation. A smart strategy to set up the code is proposed, and in particular, the parallel calculation in GPU is explored as a possible solution for the reduction in computing time. An application on a Hall-effect thruster is shown to validate the PIC numerical model and to highlight the strengths of introducing highly accurate schemes for the electric field interpolation and the macroparticle trajectory integration in the time. A further application on a helicon double-layer thruster is presented, in which the particle-in-cell (PIC) code is used as a fast tool to analyze the performance of these specific electric motors.