Nature as a preferential habitat in growth and socialisation processes in autism. A structured intervention

Dysfunctionality in socialisation is undoubtedly the most crucial characteristic of autism. For a long time, social functioning and its improvement have been considered among the most important interventions in the literature. Individuals with autism are responsive to therapist-mediated and/or peer-mediated interventions that increase their social engagement. The present study examines the impact of outdoor integrated activities, such as music therapy, equine-assisted therapy, and art therapy, in autistic individuals (n=14). The analysis was carried out on the application of a questionnaire assessing three social skill domains: Joint Attention (JA), Imitation (IMI), and Turn-Taking (T-T) mediated by the therapists and by peers. The development and acquisition of these social behaviours were examined in a structured outdoor context (ASO). Data were collected by two independent observers by White's Scale questionnaire. The results revealed that the proposed interventions facilitated and led to an increase in social-behavioural experience

Performance Evaluation of Instrument Transformers in Power Quality Measurements: Activities and Results from 19NRM05 IT4PQ Project

The accuracy of power quality measurements relies on the use of common measurement procedures and traceable measurement systems, which necessarily include instrument transformers. The paper provides an overview of the progress achieved within the EU project 19NRM05 IT4PQ in developing the needed metrological framework, in terms of performance indexes to qualify the instrument transformers for PQ measurements, simplified testing procedures and set-ups, and quantification of their behaviour under multiple influence factor

Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome

The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PPIs), or bacterial infection such as Helicobacter pylori, cause significant microbial alterations. Yet, studies revealing how the commensal bacteria re-organize, due to these perturbations of the gastric environment, are in early phase and rely principally on linear techniques for multivariate analysis. Here we disclose the importance of complementing linear dimensionality reduction techniques with nonlinear ones to unveil hidden patterns that remain unseen by linear embedding. Then, we prove the advantages to complete multivariate pattern analysis with differential network analysis, to reveal mechanisms of bacterial network re-organizations which emerge from perturbations induced by a medical treatment (PPIs) or an infectious state (H. pylori). Finally, we show how to build bacteria-metabolite multilayer networks that can deepen our understanding of the metabolite pathways significantly associated to the perturbed microbial communities

an international multi center serum protein electrophoresis accuracy and m protein isotyping study part i factors impacting limit of quantitation of serum protein electrophoresis

AbstractBackgroundSerum protein electrophoresis (SPEP) is used to quantify the serum monoclonal component or M-protein, for diagnosis and monitoring of monoclonal gammopathies. Significant imprecision and inaccuracy pose challenges in reporting small M-proteins. Using therapeutic monoclonal antibody-spiked sera and a pooled beta-migrating M-protein, we aimed to assess SPEP limitations and variability across 16 laboratories in three continents.MethodsSera with normal, hypo- or hypergammaglobulinemia were spiked with daratumumab, Dara (cathodal migrating), or elotuzumab, Elo (central-gamma migrating), with concentrations from 0.125 to 10 g/L (n = 62) along with a beta-migrating sample (n = 9). Provided with total protein (reverse biuret, Siemens), laboratories blindly analyzed samples according to their SPEP and immunofixation (IFE) or immunosubtraction (ISUB) standard operating procedures. Sixteen laboratories reported the perpendicular drop (PD) method of gating the M-protein, while 10 used tangent skimming (TS). A mean percent recovery range of 80%–120% was set as acceptable. The inter-laboratory %CV was calculated.ResultsGamma globulin background, migration pattern and concentration all affect the precision and accuracy of quantifying M-proteins by SPEP. As the background increases, imprecision increases and accuracy decreases leading to overestimation of M-protein quantitation especially evident in hypergamma samples, and more prominent with PD. Cathodal migrating M-proteins were associated with less imprecision and higher accuracy compared to central-gamma migrating M-proteins, which is attributed to the increased gamma background contribution in M-proteins migrating in the middle of the gamma fraction. There is greater imprecision and loss of accuracy at lower M-protein concentrations.ConclusionsThis study suggests that quantifying exceedingly low concentrations of M-proteins, although possible, may not yield adequate accuracy and precision between laboratories

Stray Parameter Evaluation of Voltage Transformers for PQ Measurement in MV Applications

Power Quality (PQ) monitoring is one of the key tasks in modern power systems. In transmission and distribution grids, PQ phenomena are often measured by inductive Voltage Transformers (VTs) installed for metering and/or protection applications. VTs accuracy requirements should be ideally met under actual operating conditions, which can differ from the calibration ones, in particular for the presence of environmental or circuital influence factors. The impact of such influence factors on the VT performance in PQ measurements is an open issue, not fully addressed in the literature. In this respect, this paper presents a simplified numerical-experimental model of inductive MV VTs, which can be used for the analysis of VT wideband behaviour in PQ applications, also in presence of one or more influence factors. The results provided by the model are experimentally validated and future applications are discussed

Enlightening discriminative network functional modules behind Principal Component Analysis separation in differential-omic science studies

Omic science is rapidly growing and one of the most employed techniques to explore differential patterns in omic datasets is principal component analysis (PCA). However, a method to enlighten the network of omic features that mostly contribute to the sample separation obtained by PCA is missing. An alternative is to build correlation networks between univariately-selected significant omic features, but this neglects the multivariate unsupervised feature compression responsible for the PCA sample segregation. Biologists and medical researchers often prefer effective methods that offer an immediate interpretation to complicated algorithms that in principle promise an improvement but in practice are difficult to be applied and interpreted. Here we present PC-corr: a simple algorithm that associates to any PCA segregation a discriminative network of features. Such network can be inspected in search of functional modules useful in the definition of combinatorial and multiscale biomarkers from multifaceted omic data in systems and precision biomedicine. We offer proofs of PC-corr efficacy on lipidomic, metagenomic, developmental genomic, population genetic, cancer promoteromic and cancer stem-cell mechanomic data. Finally, PC-corr is a general functional network inference approach that can be easily adopted for big data exploration in computer science and analysis of complex systems in physics

An international multi-center serum protein electrophoresis accuracy and M-protein isotyping study. Part I: factors impacting limit of quantitation of serum protein electrophoresis

Background Serum protein electrophoresis (SPEP) is used to quantify the serum monoclonal component or M-protein, for diagnosis and monitoring of monoclonal gammopathies. Significant imprecision and inaccuracy pose challenges in reporting small M-proteins. Using therapeutic monoclonal antibody-spiked sera and a pooled beta-migrating M-protein, we aimed to assess SPEP limitations and variability across 16 laboratories in three continents. Methods Sera with normal, hypo- or hypergammaglobulinemia were spiked with daratumumab, Dara (cathodal migrating), or elotuzumab, Elo (central-gamma migrating), with concentrations from 0.125 to 10 g/L (n\u2009=\u200962) along with a beta-migrating sample (n\u2009=\u20099). Provided with total protein (reverse biuret, Siemens), laboratories blindly analyzed samples according to their SPEP and immunofixation (IFE) or immunosubtraction (ISUB) standard operating procedures. Sixteen laboratories reported the perpendicular drop (PD) method of gating the M-protein, while 10 used tangent skimming (TS). A mean percent recovery range of 80%-120% was set as acceptable. The inter-laboratory %CV was calculated. Results Gamma globulin background, migration pattern and concentration all affect the precision and accuracy of quantifying M-proteins by SPEP. As the background increases, imprecision increases and accuracy decreases leading to overestimation of M-protein quantitation especially evident in hypergamma samples, and more prominent with PD. Cathodal migrating M-proteins were associated with less imprecision and higher accuracy compared to central-gamma migrating M-proteins, which is attributed to the increased gamma background contribution in M-proteins migrating in the middle of the gamma fraction. There is greater imprecision and loss of accuracy at lower M-protein concentrations. Conclusions This study suggests that quantifying exceedingly low concentrations of M-proteins, although possible, may not yield adequate accuracy and precision between laboratories