13 research outputs found
Cyber Security and Risk Disclosure: A Literature Review for Theory and Practice
Corporations and SMEs are facing ‘new’ external and internal pressures, which frequently result in modifications to their corporate governance structures and accounting/reporting systems. Because of the digital transformation, the environment – be it real or virtual – in which these companies operate has experienced significant changes. Business operations are a key and important component of human development all over the world – not only financially – and their influence on societal and environmental conditions as well as their necessary preservation are essentially undeniable. However, these operations increasingly undergo cyber-attacks that dramatically represent true causes of disruptions and breakdowns, eluding international governments’ inspection and sophisticated corporate control systems. The concepts of governance, internal control and accountability are critical for the protection of sustainable business activities from cyber-attacks, and their effectiveness is arguably dependent on corporations’ ability to govern themselves well and demonstrate accountability to their many stakeholders (across their entire value chain) also in relation to cyber dynamics. This should be accomplished by implementing well-accepted governance system standards that are globally harmonized with ‘Environment, Social and Governance’ (ESG) reporting and performance measurement tools capable of strategically assessing and evaluating risk exposure and providing forward-looking information on a multiple level. Few studies have adequately explored these issues in this defining setting, and due to the contrasting evidence arising from the extant literature, there is still no undisputed identification of effective measurement, reporting and disclosure systems for cyber risk and crime anticipation and/or neutralization
ECMO for COVID-19 patients in Europe and Israel
Since March 15th, 2020, 177 centres from Europe and Israel have joined the study, routinely reporting on the ECMO support they provide to COVID-19 patients. The mean annual number of cases treated with ECMO in the participating centres before the pandemic (2019) was 55. The number of COVID-19 patients has increased rapidly each week reaching 1531 treated patients as of September 14th. The greatest number of cases has been reported from France (n = 385), UK (n = 193), Germany (n = 176), Spain (n = 166), and Italy (n = 136) .The mean age of treated patients was 52.6 years (range 16–80), 79% were male. The ECMO configuration used was VV in 91% of cases, VA in 5% and other in 4%. The mean PaO2 before ECMO implantation was 65 mmHg. The mean duration of ECMO support thus far has been 18 days and the mean ICU length of stay of these patients was 33 days. As of the 14th September, overall 841 patients have been weaned from ECMO
support, 601 died during ECMO support, 71 died after withdrawal of ECMO, 79 are still receiving ECMO support and for 10 patients status n.a. . Our preliminary data suggest that patients placed
on ECMO with severe refractory respiratory or cardiac failure secondary to COVID-19 have a reasonable (55%) chance of survival. Further extensive data analysis is expected to provide invaluable information on the demographics, severity of illness, indications and different ECMO management strategies in these patients
Accounting for ‘ESG’ under Disruptions: A Systematic Literature Network Analysis
Corporations and small/medium enterprises (SMEs) are subject to a variety of external and internal pressures that often lead to changes in their corporate governance structures and accounting/reporting systems. The environment in which these organizations are collocated has undergone a deep process of change, due to the COVID-19 pandemic, climate change, the blockchain, and the energy industry crisis. Business activities represent a critical and a vital component of human existence across the globe—one that is not restricted to a financial standpoint—and their impact on societal, environmental and animal conditions is now undisputed. However, these activities are frequently coupled with allegations of their being the actual causes of those disruptions and collapses that persist in escaping the scrutiny of international governments. For the effective delivery of sustainable business activities, the concepts of governance and accountability are crucial, and the future of the inhabitants of planet Earth is arguably dependent on the ability of corporations (through their entire value chain) to govern themselves well and to demonstrate accountability to their many stakeholders. This should be achieved through the adoption of good governance standards which are well accepted, and that are globally harmonised with ‘Environmental, Social and Governance’ (ESG) reporting tools that are able to strategically assess and evaluate risk exposure and provide forward-looking information. In this critical context, few studies have actually examined these issues thoroughly, and, because the findings of those studies have been contradictory, there is still no definitive understanding of the causes of weak accounting and reporting tools for ESG dynamics under conditions of disruption. A systematic literature network analysis (SLNA) is used in this study to examine the evolution of the ESG reporting research domain based on existing relationships (e.g., aggregation, cross-citations and isolation) among authors contributing to the field. The findings demonstrate the current state of the art, disclosing interesting and timely future research directions. Furthermore, this study employs a novel approach known as SLNA to conduct the analyses, confirming its efficacy as a tool for dynamic analysis also within the field of sustainability accounting research
I Principal Adverse Impact - "PAI" - nelle politiche di sostenibilitÃ
Dopo aver proposto una breve disamina del contesto normativo di riferimento, si cerca di sintetizzare in maniera sistematica il tema dei principali impatti negativi sui fattori di sostenibilità ; si partirà da una argomentazione sulle policy per il governo del rischio e le esternalità negative per poi affrontare in maniera più strutturata, e in chiave prettamente economico-aziendale, gli indicatori sintetici "PAI"
Chemical Genomics-Based Antifungal Drug Discovery: Targeting Glycosylphosphatidylinositol (GPI) Precursor Biosynthesis
Steadily increasing antifungal drug resistance and persistent high rates of fungal-associated mortality highlight the dire need for the development of novel antifungals. Characterization of inhibitors of one enzyme in the GPI anchor pathway, Gwt1, has generated interest in the exploration of targets in this pathway for further study. Utilizing a chemical genomics-based screening platform referred to as the Candida albicans fitness test (CaFT), we have identified novel inhibitors of Gwt1 and a second enzyme in the glycosylphosphatidylinositol (GPI) cell wall anchor pathway, Mcd4. We further validate these targets using the model fungal organism Saccharomyces cerevisiae and demonstrate the utility of using the facile toolbox that has been compiled in this species to further explore target specific biology. Using these compounds as probes, we demonstrate that inhibition of Mcd4 as well as Gwt1 blocks the growth of a broad spectrum of fungal pathogens and exposes key elicitors of pathogen recognition. Interestingly, a strong chemical synergy is also observed by combining Gwt1 and Mcd4 inhibitors, mirroring the demonstrated synthetic lethality of combining conditional mutants of GWT1 and MCD4. We further demonstrate that the Mcd4 inhibitor M720 is efficacious in a murine infection model of systemic candidiasis. Our results establish Mcd4 as a promising antifungal target and confirm the GPI cell wall anchor synthesis pathway as a promising antifungal target area by demonstrating that effects of inhibiting it are more general than previously recognized.Genome Canada (Firm)Genome Quebe
Discovery of Novel Chemotypes to a G-Protein-Coupled Receptor through Ligand-Steered Homology Modeling and Structure-Based Virtual Screening
Linking High-Throughput Screens to Identify MoAs and Novel Inhibitors of <i>Mycobacterium tuberculosis</i> Dihydrofolate Reductase
Though
phenotypic and target-based high-throughput screening approaches
have been employed to discover new antibiotics, the identification
of promising therapeutic candidates remains challenging. Each approach
provides different information, and understanding their results can
provide hypotheses for a mechanism of action (MoA) and reveal actionable
chemical matter. Here, we describe a framework for identifying efficacy
targets of bioactive compounds. High throughput biophysical profiling
against a broad range of targets coupled with machine learning was
employed to identify chemical features with predicted efficacy targets
for a given phenotypic screen. We validate the approach on data from
a set of 55 000 compounds in 24 historical internal antibacterial
phenotypic screens and 636 bacterial targets screened in high-throughput
biophysical binding assays. Models were built to reveal the relationships
between phenotype, target, and chemotype, which recapitulated mechanisms
for known antibacterials. We also prospectively identified novel inhibitors
of dihydrofolate reductase with nanomolar antibacterial efficacy against <i>Mycobacterium tuberculosis</i>. Molecular modeling provided
structural insight into target–ligand interactions underlying
selective killing activity toward mycobacteria over human cells