Simulation-based Machine Learning Training for Brain Anomalies Localization at Microwaves

Machine learning enters the world of medical application and, in this paper, it joins microwave imaging technique for brain stroke classification. One of the main challenges in this application is the need of a large amount of data for the machine learning algorithm training that can be performed via measurements or simulations. In this work, we propose to make the algorithm training via simulations based on a linear integral operator that reduces by three orders of magnitude the data generation time with respect to standard full-wave simulations. This method is used here to train the multilayer perceptron algorithm. The data-set is organized in nine classes, related to the presence, the type and the position of the stroke within the brain. We verified that the algorithm metrics (accuracy, recall and precision) reach values close to 1 for each class

Model-based data generation for support vector machine stroke classification

This paper presents a new and efficient method to generate a dataset for brain stroke classification. Exploiting the Born approximation, it derives scattering parameters at antennas locations in a 3-D scenario through a linear integral operator. This technique allows to create a large amount of data in a short time, if compared with the full-wave simulations or measurements. Then, the support vector machine is used to create the classifier model, based on training set data with a supervised method and to classify the test set. The dataset is composed by 9 classes, differentiated for presence, typology and position of the stroke. The algorithm is able to classify the test set with a high accuracy

Efficient Data Generation for Stroke Classification via Multilayer Perceptron

The aim of this paper is to overcome one of the main problems of machine learning when it faces the medical world: the need of a large amount of data. Through the distorted Born approximation, the scattering parameters and the dielectric contrast in the domain of interest are linked by a linearized integral operator. This method allows to generate a large dataset in a short time. In this work, machine learning is exploited to classify brain stroke presence, typology and position. The classifier model is based on the multilayer perceptron algorithm and it is used firstly for validation and then with a testing set composed by full-wave simulations. In both cases, the model reaches very high level of accuracy

Brain Stroke Classification via Machine Learning Algorithms Trained with a Linearized Scattering Operator

This paper proposes an efficient and fast method to create large datasets for machine learning algorithms applied to brain stroke classification via microwave imaging systems. The proposed method is based on the distorted Born approximation and linearization of the scattering operator, in order to minimize the time to generate the large datasets needed to train the machine learning algorithms. The method is then applied to a microwave imaging system, which consists of twenty-four antennas conformal to the upper part of the head, realized with a 3D anthropomorphic multi-tissue model. Each antenna acts as a transmitter and receiver, and the working frequency is 1 GHz. The data are elaborated with three machine learning algorithms: support vector machine, multilayer perceptron, and k-nearest neighbours, comparing their performance. All classifiers can identify the presence or absence of the stroke, the kind of stroke (haemorrhagic or ischemic), and its position within the brain. The trained algorithms were tested with datasets generated via full-wave simulations of the overall system, considering also slightly modified antennas and limiting the data acquisition to amplitude only. The obtained results are promising for a possible real-time brain stroke classification

Core-shell nano-architectures: the incorporation mechanism of hydrophobic nanoparticles into the aqueous core of a microemulsion

This work presents an in-depth investigation of the molecular interactions in the incorporation mechanism of colloidal hydrophobic-capped nanoparticles into the hydrophilic core of reverse microemulsions. 1H Nuclear Magnetic Resonance (NMR) was employed to obtain molecular level details of the interaction between the nanoparticles capping amphiphiles and the microemulsion surfactants. The model system of choice involved oleic acid (OAC) and oleylamine (OAM) as capping molecules, while igepal-CO520 was the surfactant. The former were studied both in their ‘‘free’’ state and ‘‘ligated’’ one, i.e., bound to nanoparticles. The latter was investigated either in cyclohexane (micellar solution) or in water/cyclohexane microemulsions. The approach was extremely useful to gain a deeper understanding of the equilibria involved in this complex system (oleic acid capped-Bi2S3 in igepal/water/cyclohexane microemulsions). In difference to previously proposed mechanisms, the experimental data showed that the high affinity of the capping ligands for the reverse micelle interior was the driving force for the incorporation of the nanoparticles. A simple ligand-exchange mechanism could be ruled out. The collected information about the nanoparticle incorporation mechanism is extremely useful to develop new synthetic routes with an improved/tuned coating efficiency, in order to tailor the core–shell structure preparation

Studio dell'impronta isotopica del deuterio di oli alimentari mediante la spettroscopia NMR del 2H e 1H

A report is given on 2H and 1H NMR investigations of a number of triacylglycerol mixtures of edible oils and squalene samples extracted from extra virgin olive oil, shark liver and synthetic. The average numbers of hydrogen and deuterium for the olefinic, methylene and methyl sites were determined, and some parameters describing the different fractionation of deuterium in the various sites were obtained. The results have been discussed in terms of the biosynthesis steps involved in the elongation and desaturation processes of the fatty acids, and in the condensation and reduction processes of the squalene. From a principal components analysis distinct domains have been found for the squalene samples from shark liver, olive oil and synthetic

Structural and Functional Characterization of a New Double Variant Haemoglobin (HbG-Philadelphia/Duarte α268Asn→Lysβ262Ala→Pro)

We report the first case of cosegregation of two haemoglobins (Hbs): HbG-Philadelphia [α68(E17)Asn → Lys] and HbDuarte [β62(E6)Ala → Pro]. The proband is a young patient heterozygous also for β°-thalassaemia. We detected exclusively two haemoglobin variants: HbDuarte and HbG-Philadelphia/Duarte. Functional study of the new double variant HbG-Philadelphia/Duarte exhibited an increase in oxygen affinity, with a slight decrease of cooperativity and Bohr effect. This functional behaviour is attributed to β62Ala → Pro instead of α68Asn → Lys substitution. Indeed, HbG-Philadelphia isolated in our laboratory from blood cells donor carrier for this variant is not affected by any functional modification, whereas purified Hb Duarte showed functional properties very similar to the double variant. NMR and MD simulation studies confirmed that the presence of Pro instead of Ala at the β62 position produces displacement of the E helix and modifications of the tertiary structure. The substitution α68(E17)Asn → Lys does not cause significant structural and dynamical modifications of the protein. A possible structure-based rational of substitution effects is suggested

Enhanced Amphiphilic Profile of a Short β-Stranded Peptide Improves Its Antimicrobial Activity

SB056 is a novel semi-synthetic antimicrobial peptide with a dimeric dendrimer scaffold. Active against both Gram-negative and -positive bacteria, its mechanism has been attributed to a disruption of bacterial membranes. The branched peptide was shown to assume a β- stranded conformation in a lipidic environment. Here, we report on a rational modification of the original, empirically derived linear peptide sequence [WKKIRVRLSA-NH$_{2}$, SB056-lin]. We interchanged the first two residues [KWKIRVRLSA-NH$_{2}$, β-SB056-lin] to enhance the amphipathic profile, in the hope that a more regular β-strand would lead to a better antimicrobial performance. MIC values confirmed that an enhanced amphiphilic profile indeed significantly increases activity against both Gram-positive and -negative strains. The membrane binding affinity of both peptides, measured by tryptophan fluorescence, increased with an increasing ratio of negatively charged/zwitterionic lipids. Remarkably, β- SB056-lin showed considerable binding even to purely zwitterionic membranes, unlike the original sequence, indicating that besides electrostatic attraction also the amphipathicity of the peptide structure plays a fundamental role in binding, by stabilizing the bound state. Synchrotron radiation circular dichroism and solid-state $^{19}$F-NMR were used to characterize and compare the conformation and mobility of the membrane bound peptides. Both SB056- lin and β-SB056-lin adopt a β-stranded conformation upon binding POPC vesicles, but the former maintains an intrinsic structural disorder that also affects its aggregation tendency. Upon introducing some anionic POPG into the POPC matrix, the sequence-optimized β- SB056-lin forms well-ordered β-strands once electro-neutrality is approached, and it aggregates into more extended β-sheets as the concentration of anionic lipids in the bilayer is raised. The enhanced antimicrobial activity of the analogue correlates with the formation of these extended β-sheets, which also leads to a dramatic alteration of membrane integrity as shown by $^{31}$P-NMR. These findings are generally relevant for the design and optimization of other membrane-active antimicrobial peptides that can fold into amphipathic β-strands

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701