Numerical methods using two different approximations of space-filling curves for black-box global optimization

In this paper, multi-dimensional global optimization problems are considered, where the objective function is supposed to be Lipschitz continuous, multiextremal, and without a known analytic expression. Two different approximations of Peano-Hilbert curve to reduce the problem to a univariate one satisfying the Hölder condition are dis- cussed. The first of them, piecewise-linear approximation, is broadly used in global optimization and not only whereas the second one, non- univalent approximation, is less known. Multi-dimensional geomet- ric algorithms employing these Peano curve approximations are intro- duced and their convergence conditions are established. Numerical experiments executed on 800 randomly generated test functions taken from the literature show a promising performance of algorithms em- ploying Peano curve approximations w.r.t. their direct competitors

An Optimized Data Structure for High Throughput 3D Proteomics Data: mzRTree

As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard XML-based portable formats. The structures that are currently employed to manage these data can be highly inefficient, especially when dealing with high-throughput profile data. LC-MS datasets are usually accessed through 2D range queries. Optimizing this type of operation could dramatically reduce the complexity of data analysis. We propose a novel data structure for LC-MS datasets, called mzRTree, which embodies a scalable index based on the R-tree data structure. mzRTree can be efficiently created from the XML-based data formats and it is suitable for handling very large datasets. We experimentally show that, on all range queries, mzRTree outperforms other known structures used for LC-MS data, even on those queries these structures are optimized for. Besides, mzRTree is also more space efficient. As a result, mzRTree reduces data analysis computational costs for very large profile datasets.Comment: Paper details: 10 pages, 7 figures, 2 tables. To be published in Journal of Proteomics. Source code available at http://www.dei.unipd.it/mzrtre

Hydrothermal conversion of giant reed to furfural and levulinic acid: Optimization of the process under microwave irradiation and investigation of distinctive agronomic parameters

The hydrothermal conversion of giant reed (Arundo donax L.) to furfural (FA) and levulinic acid (LA) was investigated in the presence of dilute hydrochloric acid. FA and LA yields were improved by univariate optimization of the main reaction parameters: concentration of the acid catalyst, solid/liquid ratio of the reaction mixture, hydrolysis temperature, and reaction time. The catalytic performances were investigated adopting the efficient microwave (MW) irradiation, allowing significant energy and time savings. The best FA and LA yields were further confirmed using a traditionally heated autoclave reactor, giving very high results, when compared with the literature. Hydrolysis temperature and time were the main reaction variables to be carefully optimized: FA formation needed milder reaction conditions, while LA more severe ones. The effect of the crop management (e.g., harvest time) on FA/LA production was discussed, revealing that harvest time was not a discriminating parameter for the further optimization of both FA and LA production, due to the very high productivity of the giant reed throughout the year. The promising results demonstrate that giant reed represents a very interesting candidate for a very high contemporary production of FA and LA of up to about 70% and 90% of the theoretical yields, respectively

Recurrent Sweet's syndrome in a patient with multiple myeloma

Key Clinical MessageWe report on a case of Sweet's syndrome associated with multiple myeloma, as harbinger for disease relapse

Mutational Profile of Metastatic Breast Cancer Tissue in Patients Treated with Exemestane Plus Everolimus

Background. Everolimus has been shown to overcome endocrine resistance in hormone receptor positive advanced breast cancer patients. Predictive biomarkers of everolimus efficacy have been investigated in primary breast cancer tissue without finding univocal results. The goal of this study was to investigate the mutational burden in the metastatic site of endocrine-resistant tumors treated with everolimus plus exemestane. Patients and Methods. Mass Array Sequenom platform was used to analyse genetic status of 18 cancer-related genes in 25 archival tumor specimens from metastatic lesions and available primary matched breast cancer tissue of patients treated with everolimus and exemestane for advanced disease. An exploratory analysis of everolimus efficacy in terms of progression free survival benefit and single gene mutation was carried out. Results. The overall detection rate of mutation was 30% and 38% from metastatic and primary breast cancer samples, respectively. was the most frequent mutated gene. No primary breast cancer and matched relapse maintained the same mutation profile. Considering molecular pathways, the most of the genes belong to PI3K pathway (, , and ). In patients with detected mutations in breast and/or recurrence tissue the median PFS was 5,6 months while in the subgroup of patients with no mutations the median PFS was 7,5 months. Conclusions. The mutational status of breast cancer recurrence allows the identification of some genes potentially correlating tumor response/resistance to everolimus. The most frequently mutated genes were involved in the PI3K/AKT/mTOR pathway highlighting that the deregulation of this pathway in the relapse plays a crucial role in the mechanisms of everolimus resistance/sensitivity. Owing to the small sample size and the retrospective nature of the study, these correlations need to be validated in a large prospective study

Beta-Blocker Use in Older Hospitalized Patients Affected by Heart Failure and Chronic Obstructive Pulmonary Disease: An Italian Survey From the REPOSI Register

Beta (β)-blockers (BB) are useful in reducing morbidity and mortality in patients with heart failure (HF) and concomitant chronic obstructive pulmonary disease (COPD). Nevertheless, the use of BBs could induce bronchoconstriction due to β2-blockade. For this reason, both the ESC and GOLD guidelines strongly suggest the use of selective β1-BB in patients with HF and COPD. However, low adherence to guidelines was observed in multiple clinical settings. The aim of the study was to investigate the BBs use in older patients affected by HF and COPD, recorded in the REPOSI register. Of 942 patients affected by HF, 47.1% were treated with BBs. The use of BBs was significantly lower in patients with HF and COPD than in patients affected by HF alone, both at admission and at discharge (admission, 36.9% vs. 51.3%; discharge, 38.0% vs. 51.7%). In addition, no further BB users were found at discharge. The probability to being treated with a BB was significantly lower in patients with HF also affected by COPD (adj. OR, 95% CI: 0.50, 0.37-0.67), while the diagnosis of COPD was not associated with the choice of selective β1-BB (adj. OR, 95% CI: 1.33, 0.76-2.34). Despite clear recommendations by clinical guidelines, a significant underuse of BBs was also observed after hospital discharge. In COPD affected patients, physicians unreasonably reject BBs use, rather than choosing a β1-BB. The expected improvement of the BB prescriptions after hospitalization was not observed. A multidisciplinary approach among hospital physicians, general practitioners, and pharmacologists should be carried out for better drug management and adherence to guideline recommendations

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

Fermat-like equations that are not partition regular

By means of elementary conditions on coefficients, we isolate a large class of Fermat-like Diophantine equations that are not partition regular, the simplest examples being xn + ym = zk with k â\u88\u89 n, m

Forensic microbiology and bioterrorism risk (Part II)

The letters containing anthrax, sent in 2001 in USA, showed that pathogens and toxins can be effectively used for terrorist purposes. A new subfield of forensic science, called “microbial forensics”, has been developed. It is a new scientific discipline dedicated to collect and analyze microbiological evidence from a scene of crime. In addition to collecting and analyzing traditional forensic evidences, the microbial forensic investigation will attempt to determine the identity of the causal agent, as so as epidemiologic investigation, but with higher-resolution characterization. The tools for a successful attribution include genetically based-assays to determine the exact strain of isolate, aiming the individualization of the source of the pathogen used in a biological weapon. Following the 2001 anthrax attacks, genotyping of B. anthracis was done on 8 variable number tandem repeats loci (VNTR polymorphisms), with multilocus variable number tandem repeats (MLVA) method. In recent years some research groups have increased the VNTR markers number to 25 loci, while other groups have identified single nucleotide repeat (SNR) polymorphisms, which display very high mutation rates. SNR marker system allows the distinguishing of isolates with extremely low levels of genetic diversity within the same MLVA genotype

Non-Univalent Approximation of Peano Curve for Global Optimization

In this article, multi-dimensional global optimization problems are considered, where the objective function is supposed to be Lipschitz continuous, multiextremal and without a known analytic expression (black-box). Non-Univalent approximation of Peano curve to reduce the problem to a univariate one satisfying the Hölder condition is employed. Geometric frameworks for construction of global optimization algorithms are discussed. Numerical experiments executed on 100 test functions taken from the literature show a promising performance of the algorithms