Antimicrobial metallic copper surfaces kill Staphylococcus haemolyticus via membrane damage

Recently, copper (Cu) in its metallic form has regained interest for its antimicrobial properties. Use of metallic Cu surfaces in worldwide hospital trials resulted in remarkable reductions in surface contaminations. Yet, our understanding of why microbes are killed upon contact to the metal is still limited and different modes of action have been proposed. This knowledge, however, is crucial for sustained use of such surfaces in hospitals and other hygiene-sensitive areas. Here, we report on the molecular mechanisms by which the Gram-positive Staphylococcus haemolyticus is inactivated by metallic Cu. Staphylococcus haemolyticus was killed within minutes on Cu but not on stainless steel demonstrating the antimicrobial efficacy of metallic Cu. Inductively coupled plasma mass spectroscopy (ICP-MS) analysis and in vivo staining with Coppersensor-1 indicated that cells accumulated large amounts of Cu ions from metallic Cu surfaces contributing to lethal damage. Mutation rates of Cu- or steel-exposed cells were similarly low. Instead, live/dead staining indicated cell membrane damage in Cu- but not steel-exposed cells. These findings support a model of the cellular targets of metallic Cu toxicity in bacteria, which suggests that metallic Cu is not genotoxic and does not kill via DNA damage. In contrast, membranes constitute the likely Achilles’ heel of Cu surface-exposed cells

Antimicrobial metallic copper surfaces kill Staphylococcus haemolyticus via membrane damage

Recently, copper (Cu) in its metallic form has regained interest for its antimicrobial properties. Use of metallic Cu surfaces in worldwide hospital trials resulted in remarkable reductions in surface contaminations. Yet, our understanding of why microbes are killed upon contact to the metal is still limited and different modes of action have been proposed. This knowledge, however, is crucial for sustained use of such surfaces in hospitals and other hygiene-sensitive areas. Here, we report on the molecular mechanisms by which the Gram-positive Staphylococcus haemolyticus is inactivated by metallic Cu. Staphylococcus haemolyticus was killed within minutes on Cu but not on stainless steel demonstrating the antimicrobial efficacy of metallic Cu. Inductively coupled plasma mass spectroscopy (ICP-MS) analysis and in vivo staining with Coppersensor-1 indicated that cells accumulated large amounts of Cu ions from metallic Cu surfaces contributing to lethal damage. Mutation rates of Cu- or steel-exposed cells were similarly low. Instead, live/dead staining indicated cell membrane damage in Cu- but not steel-exposed cells. These findings support a model of the cellular targets of metallic Cu toxicity in bacteria, which suggests that metallic Cu is not genotoxic and does not kill via DNA damage. In contrast, membranes constitute the likely Achilles’ heel of Cu surface-exposed cells

A sustainable electrical interface to mitigate emissions due to power supply in ports

The paper presents a proposal of an innovative sustainable power supply solution for seaports with the related design and control. This solution differs from the classical solution for the presence of a smart electrical interface composed by two basic components: the first one, a rotating converter instead of the widely used static converter that ensures higher and therefore much more detectable short-circuit currents; the second, an advanced static var compensator specifically designed for enhancing power quality issues and hence favoring these seaport connection to the main grid for cold ironing applications. The designed control strategy for the tailored power supply solution is proven successful and effective by the numerical applications reported in the last part of the paper

Different Apathy Profile in Behavioral Variant of Frontotemporal Dementia and Alzheimer's Disease: A Preliminary Investigation

Apathy is one of the most common behavioral symptoms of dementia; it is one of the salient features of behavioral variant of frontotemporal dementia (bvFTD) but is also very frequent in Alzheimer's disease. This preliminary investigation was aimed at assessing the type of apathy-related symptoms in a population of bvFTD and AD subjects showing comparable apathy severity. Each patient underwent a comprehensive neuropsychological assessment; behavioral changes were investigated by the neuropsychiatric inventory (NPI), using the NPI-apathy subscale to detect apathetic symptoms. At univariate analysis, bvFTD subjects showed lack of initiation (χ2 = 4.602, p = 0.032), reduced emotional output (χ2 = 6.493, p = 0.008), and reduced interest toward friends and family members (χ2 = 4.898, p = 0.027), more frequently than AD subjects. BvFTD displayed higher scores than AD on NPI total score (p = 0.005) and on subscales assessing agitation (p = 0.004), disinhibition (p = 0.007) and sleep disturbances (p = 0.025); conversely, AD subjects were more impaired on memory, constructional abilities, and attention. On multivariate logistic regression, reduced emotional output was highly predictive of bvFTD (OR = 18.266; p = 0.008). Our preliminary findings support the hypothesis that apathy is a complex phenomenon, whose clinical expression is conditioned by the site of anatomical damage. Furthermore, apathy profile may help in differentiating bvFTD from AD

A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors

Code comprehension has been recently investigated from physiological and cognitive perspectives through the use of medical imaging. Floyd et al (i.e., the original study) used fMRI to classify the type of comprehension tasks performed by developers and relate such results to their expertise. We replicate the original study using lightweight biometrics sensors which participants (28 undergrads in computer science) wore when performing comprehension tasks on source code and natural language prose. We developed machine learning models to automatically identify what kind of tasks developers are working on leveraging their brain-, heart-, and skin-related signals. The best improvement over the original study performance is achieved using solely the heart signal obtained through a single device (BAC 87% vs. 79.1%). Differently from the original study, we were not able to observe a correlation between the participants' expertise and the classifier performance (tau = 0.16, p = 0.31). Our findings show that lightweight biometric sensors can be used to accurately recognize comprehension tasks opening interesting scenarios for research and practice.Comment: Author version submitted to ICPC2019 (Replication track

Visual field loss and vision-related quality of life in the Italian Primary Open Angle Glaucoma Study.

The aim of this study was to examine the relationship between visual field (VF) loss, vision-related quality of life (QoL) and glaucoma-related symptoms in a large cohort of primary open angle glaucoma (POAG) patients. POAG patients with or without VF defects or "glaucoma suspect" patients were considered eligible. QoL was assessed using the validated versions of the 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and glaucoma-related symptoms were assessed using the Glaucoma Symptom Scale (GSS). Patients were classified as having VF damage in one eye (VFD-1), both eyes (VFD-2), or neither eye (VFD-0). 3227 patients were enrolled and 2940 were eligible for the analysis. 13.4% of patients were classified in the VFD-0, 23.7% in the VFD-1, and 62.9% in the VFD-2 group. GSS visual symptoms domain (Func-4) and GSS non-visual symptoms domain (Symp-6) scores were similar for the VFD-0 and VFD-1 groups (p = 0.133 and p = 0.834 for Func-4 and Symp-6, respectively). VFD-0 group had higher scores than VFD-2 both in Func-4 (p < 0.001) and Symp-6 domains (p = 0.035). Regarding the NEI-VFQ-25, our data demonstrated that bilateral VF defects are associated with vision-related QoL deterioration, irrespective of visual acuity

Assessment of a Vision-Based Technique for an Automatic Van Herick Measurement System

The adoption of artificial intelligence (AI) methods within the instrumentation and measurements field is nowadays an attractive research area. On the one hand, making machines learn from data how to perform an activity, rather than hard code sequential instructions, is a convenient and effective solution in many modern research areas. On the other hand, AI allows for the compensation of inaccurate or not complete models of specific phenomena or systems. In this context, this article investigates the possibility to exploit suitable machine learning (ML) techniques in a vision-based ophthalmic instrument to perform automatic anterior chamber angle (ACA) measurements. In particular, two convolutional neural network (CNN)-based networks have been identified to automatically classify acquired images and select the ones suitable for the Van Herick procedure. Extensive clinical trials have been conducted by clinicians, from which a realistic and heterogeneous image dataset has been collected. The measurement accuracy of the proposed instrument is derived by extracting measures from the images of the aforementioned dataset, as well as the system performances have been assessed with respect to differences in patients' eye color. Currently, the ACA measurement procedure is performed manually by appropriately trained medical personnel. For this reason, ML and vision-based techniques may greatly improve both test objectiveness and diagnostic accessibility, by enabling an automatic measurement procedure

Numerical and experimental analysis of the leaning Tower of Pisa under earthquake

Twenty years have passed from the most recent studies about the dynamic behavior of the leaning Tower of Pisa. Significant changes have occurred in the meantime, the most important ones concerning the soil-structure interaction. From 1999 to 2001, the foundation of the monument was consolidated through under-excavation, and the "Catino" at the basement was rigidly connected to the foundation. Moreover, in light of the recent advances in the field of earthquake engineering, past studies about the Tower must be revised. Therefore, the present research aims at providing new data and results about the structural response of the Tower under earthquake. As regards the experimental assessment of the Tower, the dynamic response of the structure recorded during some earthquakes has been analyzed in the time- and frequency-domain. An Array 2D test has been performed in the Square of Miracles to identify a soil profile suitable for site response analyses, thus allowing the definition of the free-field seismic inputs at the base of the Tower. On the other hand, a synthetic evaluation of the seismic input in terms of response spectra has been done by means of a hybrid approach that combines Probabilistic and Deterministic Seismic Hazard Assessment methods. Furthermore, natural accelerograms have been selected and scaled properly. A finite element model that takes into account the inclination of the structure has been elaborated, and it has been updated taking into account the available experimental results. Finally, current numerical and experimental efforts for enhancing the seismic characterization of the Tower have been illustrated