The relationship between investor materiality and the sustainable development goals: A methodological framework

The world has great expectations for how the private sector, both companies and investors, can support the 17 Sustainable Development Goals (SDGs). In fact, it is generally believed that these goals cannot be achieved without strong support from the private sector. But will making the world a better place hurt financial returns? The answer is "No" if companies focus on the SDGs and their associated targets that benefit from strong performance on the material environmental, social, and governance (ESG) issues that matter to investors. In this paper we map the 30 generic ESG issues identified by the Sustainability Accounting Standards Board (SASB) to the SDGs and their targets. We show that some SASB issues are more material for a given SDG than others. We also show that some SASB issues are more important to the SDGs in general than others. We also map the material ESG issues for each of SASB's 79 industries to the SDGs and to their targets. For each sector, there are particular SDGs where it has high impact and for each SDG there are particular sectors that have a high impact on it, and some sectors are more important to the SDGs in aggregate than others. The same is true at the target level. This mapping can be used as a guide for both companies and investors who want to understand how value-creating ESG performance can contribute to the SDGs. This paper is divided into four parts. Part I explains the motivation for this study. Part II explains our methodology and Part III the results. Part IV concludes with a summary of our results and some reflections on how our mapping methodology can be improved

Students with Learning Disabilities at University. Design of a Protocol for Usability of Teaching and Individual Study

The Learning Disabilities (LD) creates a real difficulty in the study, because they assume the evolution of certain prerequisites and involve a number of functions that impact against the decoding of the alphabetic code. By definition they have an evolutionary nature, ie they vary with the age of the person. This article explores the characteristics of LD in adulthood and the impact with theuniversity teaching. It presents the results of an interdisciplinary project in progress (educational,medical and engineering area) at University of Florence, suitable to provide a procedural protocol for the usability of teaching in university and to support individual study. The purpose of project is to design of a protocol for usability of teaching and individual study, even at university level as indicated by the recent Italian legislation (Law 170/2010)

A key for the identification of larvae of Anoplophora chinensis, Anoplophora glabripennis and Psacothea hilaris (Coleoptera Cerambycidae Lamiinae) in Europe

Anoplophora chinensis (Förster), A. glabripennis (Motschulsky) and Psacothea hilaris (Pascoe) (Coleoptera Cerambycidae Lamiinae) are longhorned beetles native to the far eastern regions of Asia and were recently accidentally introduced into Europe. The three exotic species are harmful insects to broadleaved plant species, and much attention is being paid to prevent further introductions and spread in the European Union. Severe phytosanitary measures are applied with the aim of eradicating outbreaks of the pests. Crucial for control is rapid identification of the longhorned species during phytosanitary inspections, both in entry ports and in the rest of the territory of the European Union. Taxonomic keys and descriptions of the adult morphology are available in the literature, but there are significant gaps in the taxonomy of larval morphology, and thus molecular analyses are required. During monitoring activities, a practical morphological taxonomic key would be a rapid and useful tool for species identification of the larvae. In the present work, a taxonomic key provided with detailed morphological pictures is proposed for the identification of the larvae of the three exotic species A. chinensis, A. glabripennis and P. hilaris among the closely related species of the native fauna of Europe

Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques

Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). One-hundred-and-eighty-one subjects diagnosed with MS underwent 3T-MRI and were followed up for two to six years at two sites, with disability progression defined according to the expanded-disability-status-scale (EDSS) increment at the follow-up. The patients' 3DT1 images were bias-corrected, brain-extracted, registered onto MNI space, and divided into slices along coronal, sagittal, and axial projections. Deep learning image classification models were applied on slices and devised as ResNet50 fine-tuned adaptations at first on a large independent dataset and secondly on the study sample. The final classifiers' performance was evaluated via the area under the curve (AUC) of the false versus true positive diagram. Each model was also tested against its null model, obtained by reshuffling patients' labels in the training set. Informative areas were found by intersecting slices corresponding to models fulfilling the disability progression prediction criteria. At follow-up, 34% of patients had disability progression. Five coronal and five sagittal slices had one classifier surviving the AUC evaluation and null test and predicted disability progression (AUC > 0.72 and AUC > 0.81, respectively). Likewise, fifteen combinations of classifiers and axial slices predicted disability progression in patients (AUC > 0.69). Informative areas were the frontal areas, mainly within the grey matter. Briefly, 3DT1 images may give hints on disability progression in MS patients, exploiting the information hidden in the MRI of specific areas of the brain

Cortico-Subcortical White Matter Bundle Changes in Cervical Dystonia and Blepharospasm

Dystonia is thought to be a network disorder due to abnormalities in the basal ganglia-thalamo-cortical circuit. We aimed to investigate the white matter (WM) microstructural damage of bundles connecting pre-defined subcortical and cortical regions in cervical dystonia (CD) and blepharospasm (BSP). Thirty-five patients (17 with CD and 18 with BSP) and 17 healthy subjects underwent MRI, including diffusion tensor imaging (DTI). Probabilistic tractography (BedpostX) was performed to reconstruct WM tracts connecting the globus pallidus, putamen and thalamus with the primary motor, primary sensory and supplementary motor cortices. WM tract integrity was evaluated by deriving their DTI metrics. Significant differences in mean, radial and axial diffusivity between CD and HS and between BSP and HS were found in the majority of the reconstructed WM tracts, while no differences were found between the two groups of patients. The observation of abnormalities in DTI metrics of specific WM tracts suggests a diffuse and extensive loss of WM integrity as a common feature of CD and BSP, aligning with the increasing evidence of microstructural damage of several brain regions belonging to specific circuits, such as the basal ganglia-thalamo-cortical circuit, which likely reflects a common pathophysiological mechanism of focal dystonia

A Role for the Long Noncoding RNA SENCR in Commitment and Function of Endothelial Cells

Despite the increasing importance of long non-coding RNA in physiology and disease, their role in endothelial biology remains poorly understood. Growing evidence has highlighted them to be essential regulators of human embryonic stem cell differentiation. SENCR, a vascular-enriched long non-coding RNA, overlaps the Friend Leukemia Integration virus 1 (FLI1) gene, a regulator of endothelial development. Therefore, we wanted to test the hypothesis that SENCR may contribute to mesodermal and endothelial commitment as well as in endothelial function. We thus developed new differentiation protocols allowing generation of endothelial cells from human embryonic stem cells using both directed and haemogenic routes. The expression of SENCR was markedly regulated during endothelial commitment using both protocols. SENCR did not control the pluripotency of pluripotent cells; however its overexpression significantly potentiated early mesodermal and endothelial commitment. In HUVEC, SENCR induced proliferation, migration and angiogenesis. SENCR expression was altered in vascular tissue and cells derived from patients with critical limb ischemia and premature coronary artery disease compared to controls. Here, we showed that SENCR contributes to the regulation of endothelial differentiation from pluripotent cells and controls the angiogenic capacity of HUVEC. These data give novel insight into the regulatory processes involved in endothelial development and function

Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

This study aimed to optimise techniques for whole transcriptome and small RNA analyses on clinical tissue samples from patients with cardiovascular disease. Clinical samples often represent a particular challenge to extracting RNA of sufficient quality for robust RNA sequencing analysis, and due to availability, it is rarely possible to optimise techniques on the samples themselves. Therefore, we have used equivalent samples from pigs undergoing cardiopulmonary bypass surgery to test different protocols for optimal RNA extraction, and then validated the protocols in human samples. Here we present an assessment of the quality and quantity of RNA obtained using a variety of commercially-available RNA extraction kits on both left ventricular biopsies and blood plasma. RNA extraction from these samples presents different difficulties; left ventricular biopsies are small and fibrous, while blood plasma has a low RNA content. We have validated our optimised extraction techniques on human clinical samples collected as part of the ARCADIA (Association of non-coding RNAs with Coronary Artery Disease and type 2 Diabetes) cohort study, resulting in successful whole transcriptome and small RNA sequencing of human left ventricular tissue