Aortic type B dissection with acute expansion of iliac artery aneurysm in previous endovascular repair with iliac branched graft

We report the case of a patient previously treated with an iliac branch endograft for isolated iliac artery aneurysm who developed, more than 2 years later, a type B aortic dissection resulting in the acute expansion of the previously excluded iliac aneurysm. Successful endovascular salvage is described

Gender-related outcomes in the endovascular treatment of infrainguinal arterial obstructive disease

The purpose of this study was to retrospectively analyze early and midterm results of endovascular infrainguinal peripheral revascularizations in female patients in our single-center experience, paying particular attention to clinical, anatomic, and technical factors affecting perioperative and follow-up outcomes

An unprecedented palladium-arsenic catalytic cycle for nitriles hydration

An unprecedented palladium/arsenic-based catalytic cycle for the hydration of nitriles to the corresponding amides is here described. It occurs in exceptionally mild conditions such as neutral pH and moderate temperature (60°C). The versatility of this new catalytic cycle was tested on various nitriles from aliphatic to aromatic. Also, the effect of ring substitution with electron withdrawing and electron donating groups was investigated in the cases of aromatic nitriles, as well as the effect of potentially interferent functional groups such as hydroxy group or pyridinic nitrogen. Furthermore, a pilot study on the potential suitability of this approach for its scale-up is presented, revealing that the catalytic cycle could be potentially and quickly scaled up

Metallo therapeutics for COVID-19. Exploiting metal-based compounds for the discovery of new antiviral drugs

Introduction: The COVID-19 pandemic poses an unprecedented challenge for the rapid discovery of drugs against this life-threatening disease. Owing to the peculiar features of the metal centers that are currently used in medicinal chemistry, metallodrugs might offer an excellent opportunity to achieve this goal. Areas covered: Two main strategies for developing metal-based drugs against the SARS-CoV-2 are herein illustrated. Firstly, a few clinically approved metallodrugs could be evaluated in patients according to a ‘drug repurposing’ approach. To this respect, the gold drug auranofin seems a promising candidate, but some other clinically established metal compounds are worthy of a careful evaluation as well. On the other hand, libraries of inorganic compounds, featuring a large chemical diversity, should be screened to identify the most effective molecules. This second strategy might be assisted by a pathway-driven discovery approach arising from a preliminary knowledge of the mode of action, exploitable to inhibit the functional activities of the key viral proteins. Also, attention must be paid to selectivity and toxicity issues. Expert opinion: The medicinal inorganic chemistry community may offer a valuable contribution against COVID-19. The screening of metallodrugs’ libraries can expand the explored ‘chemical space’ and increase the chance of finding effective anti-COVID agents

SEM-EDX and SEM-CL to Characterize Lapis Lazuli from Different Provenances

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011

Reactions of medicinal gold(III) compounds with proteins and peptides explored by electrospray ionization mass spectrometry and complementary biophysical methods

Electrospray ionization mass spectrometry (ESI MS) is a powerful investigative tool to analyze the reactions of metallodrugs with proteins and peptides and characterize the resulting adducts. Here, we have applied this type of approach to four experimental anticancer gold(III) compounds for which extensive biological and mechanistic data had previously been gathered, namely, Auoxo6, Au2phen, AuL12, and Aubipyc. These gold(III) compounds were reacted with two representative proteins, i.e., human serum albumin (HSA) and human carbonic anhydrase I (hCA I), and with the C-terminal dodecapeptide of thioredoxin reductase. ESI MS analysis allowed us to elucidate the nature of the resulting metal–protein adducts from which the main features of the occurring metallodrug–protein reactions can be inferred. In selected cases, MS data were integrated and supported by independent 1HNMR and UV–Vis absorption measurements to gain an overall description of the occurring processes. From data analysis, it emerges that most of the investigated gold(III) complexes, endowed with an appreciable oxidizing character, undergo quite facile reduction to gold(I); the resulting gold(I) species tightly associate with the above proteins/peptides with a remarkable selectivity for free cysteine residues. In contrast, in the case of the less-oxidizing Aubipyc complex, the gold(III) oxidation state is conserved, and a gold(III) fragment still containing the original ligand is found to be associated with the target proteins. It is notable that the C-terminal dodecapeptide of thioredoxin reductase containing the characteristic –Gly–Cys–Sec–Gly metal-binding motif is able in all cases to trigger gold(III)-to-gold(I) reduction. Our investigation allowed us to identify in detail the nature of the gold fragments that ultimately bind the protein targets and determine the exact binding stoichiometry; some insight on the reaction kinetics was also gained. Notably, a few clear correlations could be established between the structure of the metal complexes and the nature of the resulting protein adducts. The mechanistic implications of these findings are analyzed and thoroughly discussed. Overall, the present results set the stage to better understand the real target biomolecules of these gold compounds and elucidate at the atomic level their interaction modes with proteins and peptides

Eating Disorders

Anorexia and bulimia are diseases known since ancient times, but in recent years their frequency has been continuously increasing in most industrialized countries. The etiology of these disorders can be traced back to the interaction between genetic predisposition, childhood experiences, and cultural pressures. As regards the course, a certain tendency to chronicity can be observed, and in extreme cases, they can cause death. According to the diagnostic classification of the DSM-5, eating disorders include anorexia nervosa, bulimia nervosa, binge eating disorder (which, compared to DSM-IV, becomes a diagnostic category in its own right), and other specified feeding and eating disorders (OSFED). Both anorexia and bulimia cause potentially serious medical complications. To maximize the chances of good outcomes a multidisciplinary intervention is necessary with staff including professionally heterogeneous figures: a psychiatrist, a psychologist, and a nutritionist. Therapeutic success for these patients is limited. Eating disorders require, among psychiatric disorders, the greatest possible collaboration between different professional figures with different specializations

Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy

Fairness concerns about algorithmic decision-making systems have been mainly focused on the outputs (e.g., the accuracy of a classifier across individuals or groups). However, one may additionally be concerned with fairness in the inputs. In this paper, we propose and formulate two properties regarding the inputs of (features used by) a classifier. In particular, we claim that fair privacy (whether individuals are all asked to reveal the same information) and need-to-know (whether users are only asked for the minimal information required for the task at hand) are desirable properties of a decision system. We explore the interaction between these properties and fairness in the outputs (fair prediction accuracy). We show that for an optimal classifier these three properties are in general incompatible, and we explain what common properties of data make them incompatible. Finally we provide an algorithm to verify if the trade-off between the three properties exists in a given dataset, and use the algorithm to show that this trade-off is common in real data