Qualitative research in social and organizational psychology: the Italian way

Our paper provides a mapping of qualitative research in social and organizational psychology. This mapping was directed by the authors’ choices and this means that scholars from other perspectives are likely to offer different readings of the same topic. The first choice was to not consider the clinical and developmental psychological research, so to deepen our exploration of the two areas in which we work on, and on which we have a more articulated perspective. These two areas differ for some aspects, but they also present some relevant common elements, as it is demonstrated by the fact that scholars working in social and organizational psychology are part of the same academic recruitment field (“11/E3 Social psychology and work and organizational psychology”). The first section of the article consists of a short history of qualitative research in Italian psychology. To deepen the focus on the most recent developments, in the second section we present a review of the scientific articles published in the last five years

Simulating the effect of climatic variations on the long-term performance of different agroforestry systems within field trials using virtual experiments

Agroforestry systems can reduce some of the adverse effects of climate change in agriculture by e.g. serving as a windbreak or shade provider to protect crops or grazing livestock and supporting beneficial species for pest control. The prediction of the long-term performance of different agroforestry options is however difficult to obtain through field quantify experiments due to the length of time trees grow for experiments. Numerical modelling can contribute to a better understanding of a system’s performance, since the effect of different climatic alterations can be tested using virtual experiments for different periods of time. Within the Horizon 2020 AGROMIX project, we are analysing the long-term performance of eight different agroforestry trials (Figure 1), using different modelling approaches. The trials are spread over three biogeographic regions (Mediterranean, Continental, and Atlantic) and are of varying age (4 to 33 years). In total, six silvoarable and five silvopastoral farming systems are maintained at the eight field trials. Through the use of different numerical models the effect of changes in temperature and precipitation patterns or the occurrence of extreme events such as droughts or late spring frost on the different agroforestry systems will be predicted. Additionally, experimental data on crop performance as well as animal behaviour and welfare, in particular under heat stress, are being obtained and will potentially be included in the model predictions. This poster aims to give an overview on the field trials and the numerical modelling approaches that are being applied to predict long-term system performance

Materials in particulate form for tissue engineering. 2 Applications in bone

Materials in particulate form have been the subjects of intensive research in view of their use as drug delivery systems. While within this application there are still issues to be addressed, these systems are now being regarded as having a great potential for tissue engineering applications. Bone repair is a very demanding task, due to the specific characteristics of skeletal tissues, and the design of scaffolds for bone tissue engineering presents several difficulties. Materials in particulate form are now seen as a means of achieving higher control over parameters such as porosity, pore size, surface area and the mechanical properties of the scaffold. These materials also have the potential to incorporate biologically active molecules for release and to serve as carriers for cells. It is believed that the combination of these features would create a more efficient approach towards regeneration. This review focuses on the application ofmaterials in particulate formfor bone tissue engineering. A brief overview of bone biology and the healing process is also provided in order to place the application in its broader context. An original compilation of molecules with a documented role in bone tissue biology is listed, as they have the potential to be used in bone tissue engineering strategies. To sum up this review, examples of works addressing the above aspects are presented

Delivery systems made of natural-origin polymers for tissue engineering and regenerative medicine applications

There is an emergent need in the development of more specific and effective therapeutic agent carriers to help on the regeneration of a plethora of tissues. The ultimate aim of bioactive factors delivery systems development is to improve the human health with the fewest possible adverse reactions. While there have been many polymeric scaffolds and matrices with different forms and compositions developed to load and deliver bioactive factors, the delivery strategy should be established based on the type of molecules to deliver and mechanisms to control their release. As most bioactive factors such as proteins and genes are water-soluble, natural polymers are more favored than synthetic ones for this purpose. A core-shell structuring of biomaterials (in the cases of particles or fibers) where water-based polymers being placed in the inner core part may be the most common design principal to secure bioactive factors during the processing of synthetic drug delivery scaffolds.(undefined)info:eu-repo/semantics/submittedVersio

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

A Nonlinear Sliding Surface in Sliding Mode Control to Reduce Vibrations of a Three-Link Flexible Manipulator

Many mechanical systems often show nonlinear behavior related to particular operating conditions or to the nonlinear characteristic of the elements (springs, dampers, etc.) making up the system. In these cases, common engineering practice is to linearize the equation of motion around a particular operating point and to design a linear controller. Although this approach is simple, its main disadvantage is that stability properties and validity of the controller are only local. For these reasons, over the last decades, nonlinear control techniques have been investigated more and more in order to improve control performance. In particular, in this paper, sliding mode control (SMC) technique, which is based on the model of the system (model-based), is considered because of its easy implementation, especially on simple mechanical systems, and the considerable robustness of the controller even under significant model uncertainties. This technique is analyzed numerically with respect to the pendulum system to better understand the influence of the control action on the system dynamics. A nonlinear sliding surface is also considered, recalling the terminal sliding mode (TSM) control already analyzed in the scientific literature. This sliding surface is characterized for the numerical system, and then it is applied experimentally in order to control a highly nonlinear system, consisting of a three-link flexible manipulator. For this system, a nonlinear modal model is developed, and a nonlinear observer is designed. Finally, results of experimental tests on the manipulator are reported, in order to compare the performances of the linear embedded control and the sliding mode controllers with the linear and nonlinear sliding surface

Non-linear control logics for vibrations suppression: A comparison between model-based and non-model-based techniques

Non-linear behavior is present in many mechanical system operating conditions. In these cases, a common engineering practice is to linearize the equation of motion around a particular operating point, and to design a linear controller. The main disadvantage is that the stability properties and validity of the controller are local. In order to improve the controller performance, non-linear control techniques represent a very attractive solution for many smart structures. The aim of this paper is to compare non-linear model-based and non-model-based control techniques. In particular the model-based sliding-mode-control (SMC) technique is considered because of its easy implementation and the strong robustness of the controller even under heavy model uncertainties. Among the non-model-based control techniques, the fuzzy control (FC), allowing designing the controller according to if-then rules, has been considered. It defines the controller without a system reference model, offering many advantages such as an intrinsic robustness. These techniques have been tested on the pendulum nonlinear system