Does Cultural Diversity of Board of Directors Affect Corporate Environmental Performance? Evidence From the Energy Sector

This paper has a twofold objective. First, it intends to investigate if and how the cultural diversity of the board of directors affects the corporate environmental performance of energy firms. Second, it aims at verifying if the relationship between board cultural diversity and corporate environmental performance varies across different legal systems. To address this topic, panel data methodology was used on a sample of 153 firms operating in the energy sector, from 32 countries, over the period 2013-2018. The findings suggest that a higher board’s cultural heterogeneity positively affects corporate environmental performance. Moreover, the study reveals that this link is stronger among energy firms from civil law countries compared to energy firms from common law countries

The Virtuous Circle of Intellectual Capital and Corporate Environmentalism: Evidence from the Food Industry

The purpose of this paper is to address the relationship between intellectual capital and corporate environmentalism, assuming that intellectual capital may be an important precondition to foster environmental commitment and that, on the other side, corporate environmentalism may positively determine the level of intellectual capital in a reciprocal and virtuous circle. To address this topic, we conducted two OLS regression analysis on a worldwide sample of 235 firms operating in the food industry, over an eight years’ time horizon (2010-2017), with 1,686 firm-year observations gathered from Asset-4ESG and Worldscope. Results confirm our hypotheses thus providing important theoretical and managerial implications

Adult IDH wild-type glioblastoma ultrastructural investigation suggests a possible correlation between morphological biomarkers and Ki-67 index

Glioblastoma is an aggressive brain tumor with an average life expectancy between 14 and 16 months after diagnosis. The Ki-67 labeling index (LI), a measure of cellular proliferation, is emerging as a prognostic marker in GBM. In this study, we investigated the ultrastructure of glioblastoma tissue from 9 patients with the same molecular profile (adult IDH wild-type glioblastoma, wild-type ATRX, and positive for TP53 expression, GFAP expression, and EGFR overexpression) to find possible ultrastructural features to be used as biomarkers and correlated with the only parameter that differs among our samples, the Ki-67 LI. Our main results were the visualization of the anatomical basis of astrocyte-endothelial cells crosstalk; the ultrastructural in situ imaging of clusters of hyperactivated microglia cells (MsEVs); the ultrastructural in situ imaging of microglia cells storing lipid vesicles (MsLVs); the ultrastructural in situ imaging of neoplastic cells mitophagy (NCsM). The statistical analysis of our data indicated that MsEVs and MsLVs correlate with the Ki-67 LI value. We can thus assume they are good candidates to be considered morphological biomarkers correlating to Ki-67 LI. The role of NCsM instead must be further evaluated. Our study findings demonstrate that by combining ultrastructural characteristics with molecular information, we can discover biomarkers that have the potential to enhance diagnostic precision, aid in treatment decision-making, identify targets for therapy, and enable personalized treatment plans tailored to each patient. However, further research with larger sample sizes is needed to validate these findings and fully utilize the potential of ultrastructural analysis in managing glioblastoma

Prominent Changes in Cerebro-Cerebellar Functional Connectivity During Continuous Cognitive Processing

While task-dependent responses of specific brain areas during cognitive tasks are well established, much less is known about the changes occurring in resting state networks (RSNs) in relation to continuous cognitive processing. In particular, the functional involvement of cerebro-cerebellar loops connecting the posterior cerebellum to associative cortices, remains unclear. In this study, 22 healthy volunteers underwent a multi-session functional magnetic resonance imaging (fMRI) protocol composed of four consecutive 8-min resting state fMRI (rs-fMRI) scans. After a first control scan, participants listened to a narrated story for the entire duration of the second rs-fMRI scan; two further rs-fMRI scans followed the end of story listening. The story plot was purposely designed to stimulate specific cognitive processes that are known to involve the cerebro-cerebellar loops. Almost all of the identified 15 RSNs showed changes in functional connectivity (FC) during and for several minutes after the story. The FC changes mainly occurred in the frontal and prefrontal cortices and in the posterior cerebellum, especially in Crus I-II and lobule VI. The FC changes occurred in cerebellar clusters belonging to different RSNs, including the cerebellar network (CBLN), sensory networks (lateral visual network, LVN; medial visual network, MVN) and cognitive networks (default mode network, DMN; executive control network, ECN; right and left ventral attention networks, RVAN and LVAN; salience network, SN; language network, LN; and working memory network, WMN). Interestingly, a k-means analysis of FC changes revealed clustering of FCN, ECN, and WMN, which are all involved in working memory functions, CBLN, DMN, and SN, which play a key-role in attention switching, and RSNs involved in visual imagery. These results show that the cerebellum is deeply entrained in well-structured network clusters, which reflect multiple aspects of cognitive processing, during and beyond the conclusion of auditory stimulation

On-Demand Flexible Transit in Fast-Growing Cities: The Case of Dubai

Increase in city population and size leads to growing transport demand and heterogeneous mobility habits. In turn, this may result in economic and social inequalities within the context of rapid economic growth. Provision of flexible transit in fast-growing cities is a promising strategy to overcome the limits of conventional public transport and avoid the use of private cars, towards better accessibility and social inclusion. This paper presents the case of Dubai (UAE), where a demand responsive transit service called MVMANT (a company based in Italy) has been tested in some low demand districts. The contribution of this work relies on the use of an agent-based model calibrated with Geographic Information System (GIS) real data to reproduce the service and find optimal configurations from both the perspective of the transport operator and the community. Different scenarios were simulated, by changing the vehicle assignment strategy and capacity, and comparing MVMANT with a ride-sharing service with smaller vehicles. Results suggest that route choice strategy is important to find a balance between operator and user costs, and that these types of flexible transit can satisfy transport demand with limited total costs compared to other shared mobility services. They can also be effective in satisfying fluctuating demand by adopting heterogeneous fleets of vehicles. Finally, appropriate planning and evaluation of these services are needed to fully explore their potential in covering the gap between low-quality fixed public transport and unsustainable private transport. Document type: Articl

CATASAN Is a New Anti-Biofilm Agent Produced by the Marine Antarctic Bacterium Psychrobacter sp. TAE2020

The development of new approaches to prevent microbial surface adhesion and biofilm formation is an emerging need following the growing understanding of the impact of biofilm-related infections on human health. Staphylococcus epidermidis, with its ability to form biofilm and colonize biomaterials, represents the most frequent causative agent involved in infections of medical devices. In the research of new anti-biofilm agents against S. epidermidis biofilm, Antarctic marine bacteria represent an untapped reservoir of biodiversity. In the present study, the attention was focused on Psychrobacter sp. TAE2020, an Antarctic marine bacterium that produces molecules able to impair the initial attachment of S. epidermidis strains to the polystyrene surface. The setup of suitable purification protocols allowed the identification by NMR spectroscopy and LC-MS/MS analysis of a protein–polysaccharide complex named CATASAN. This complex proved to be a very effective anti-biofilm agent. Indeed, it not only interferes with cell surface attachment, but also prevents biofilm formation and affects the mature biofilm matrix structure of S. epidermidis. Moreover, CATASAN is endowed with a good emulsification activity in a wide range of pH and temperature. Therefore, its use can be easily extended to different biotechnological applications

Comprehensive transcript profiling of two grapevine rootstock genotypes contrasting in drought susceptibility links the phenylpropanoid pathway to enhanced tolerance

In light of ongoing climate changes in wine-growing regions, the selection of drought-tolerant rootstocks is becoming a crucial factor for developing a sustainable viticulture. In this study, M4, a new rootstock genotype that shows tolerance to drought, was compared from a genomic and transcriptomic point of view with the less drought-tolerant genotype 101.14. The root and leaf transcriptome of both 101.14 and the M4 rootstock genotype was analysed, following exposure to progressive drought conditions. Multifactorial analyses indicated that stress treatment represents the main factor driving differential gene expression in roots, whereas in leaves the genotype is the prominent factor. Upon stress, M4 roots and leaves showed a higher induction of resveratrol and flavonoid biosynthetic genes, respectively. The higher expression of VvSTS genes in M4, confirmed by the accumulation of higher levels of resveratrol in M4 roots compared with 101.14, was coupled to an up-regulation of several VvWRKY transcription factors. Interestingly, VvSTS promoter analyses performed on both the resequenced genomes highlighted a significantly higher number of W-BOX elements in the tolerant genotype. It is proposed that the elevated synthesis of resveratrol in M4 roots upon water stress could enhance the plant’s ability to cope with the oxidative stress usually associated with water deficit

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis