The medical genetics of dystrophinopathies: Molecular genetic diagnosis and its impact on clinical practice

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An Open System for Collection and Automatic Recognition of Pottery through Neural Network Algorithms

In the last ten years, artificial intelligence (AI) techniques have been applied in archaeology. The ArchAIDE project realised an AI-based application to recognise archaeological pottery. Pottery is of paramount importance for understanding archaeological contexts. However, recognition of ceramics is still a manual, time-consuming activity, reliant on analogue catalogues. The project developed two complementary machine-learning tools to propose identifications based on images captured on-site, for optimising and economising this process, while retaining key decision points necessary to create trusted results. One method relies on the shape of a potsherd; the other is based on decorative features. For the shape-based recognition, a novel deep-learning architecture was employed, integrating shape information from points along the inner and outer profile of a sherd. The decoration classifier is based on relatively standard architectures used in image recognition. In both cases, training the algorithms meant facing challenges related to real-world archaeological data: the scarcity of labelled data; extreme imbalance between instances of different categories; and the need to take note of minute differentiating features. Finally, the creation of a desktop and mobile application that integrates the AI classifiers provides an easy-to-use interface for pottery classification and storing pottery data

Rapid, comprehensive analysis of the dystrophin transcript by a custom micro-fluidic exome array

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Monoclonal antibodies to murine thrombospondin-1 and thrombospondin-2 reveal differential expression patterns in cancer and low antigen expression in normal tissues

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Heterobimetallic conducting polymers based on salophen complexes via electrosynthesis

In this work, we report the first electrochemical synthesis of two copolymeric bimetallic conducting polymers by a simple anodic electropolymerization method. The adopted precursors are electroactive transition metal (M = Ni, Cu and Fe) salophen complexes, which can be easily obtained by direct chemical synthesis. The resulting films, labeled poly-NiCu and poly-CuFe, were characterized by cyclic voltammetry in both organic and aqueous media, attenuated total reflectance Fourier transform infrared spectroscopy, UV-vis spectroscopy, scanning electron microscopy, and coupled energy dispersive X-ray spectroscopy. The films are conductive and exhibit great electrochemical stability in both organic and aqueous media (resistant over 100 cycles without significant loss in current response or changes in electrochemical behavior), which makes them good candidates for an array of potential applications. Electrochemical detection of ascorbic acid was performed using both materials

Macrophages: A minimally invasive tool for monitoring collagen VI myopathies

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MAPPA. Metodologie Applicate alla Predittività del Potenziale Archeologico. 2

La carta di potenziale archeologico della città di Pisa. L'algoritmo elaborato ad hoc per il calcolo del potenziale archeologico. Il MOD: il primo archivio italiano open data di documenti archeologici

Smart Bandaid Integrated with Fully Textile OECT for Uric Acid Real-Time Monitoring in Wound Exudate

: Hard-to-heal wounds (i.e., severe and/or chronic) are typically associated with particular pathologies or afflictions such as diabetes, immunodeficiencies, compression traumas in bedridden people, skin grafts, or third-degree burns. In this situation, it is critical to constantly monitor the healing stages and the overall wound conditions to allow for better-targeted therapies and faster patient recovery. At the moment, this operation is performed by removing the bandages and visually inspecting the wound, putting the patient at risk of infection and disturbing the healing stages. Recently, new devices have been developed to address these issues by monitoring important biomarkers related to the wound health status, such as pH, moisture, etc. In this contribution, we present a novel textile chemical sensor exploiting an organic electrochemical transistor (OECT) configuration based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for uric acid (UA)-selective monitoring in wound exudate. The combination of special medical-grade textile materials provides a passive sampling system that enables the real-time and non-invasive analysis of wound fluid: UA was detected as a benchmark analyte to monitor the health status of wounds since it represents a relevant biomarker associated with infections or necrotization processes in human tissues. The sensors proved to reliably and reversibly detect UA concentration in synthetic wound exudate in the biologically relevant range of 220-750 μM, operating in flow conditions for better mimicking the real wound bed. This forerunner device paves the way for smart bandages integrated with real-time monitoring OECT-based sensors for wound-healing evaluation

De-Escalation and Discontinuation of Empirical Antibiotic Treatment in a Cohort of Allogeneic Hematopoietic Stem Cell Transplantation Recipients during the Pre-Engraftment Period

To investigate rates and outcomes of antibiotic de-escalation during pre-engraftment neutropenia in allogeneic hematopoietic stem cell transplantation (HSCT) recipients. 110 consecutive HSCTs performed between January 2013 and March 2014 were analyzed. De-escalation was defined as narrowing the spectrum of antibiotic treatment either within (early) or after 96 hours (late) from starting antibiotics. Discontinuation, considered a form of de-escalation, was defined as stopping antibiotics before engraftment. De-escalation failure was defined as restarting/escalating antibiotics within 96 hours after de-escalation. Predictors of de-escalation were analyzed. Among 102 patients who started antibiotics and were included, 68 (67%) received monotherapy (mainly piperacillin-tazobactam, n = 58), whereas 34 (33%) received combination therapy (mainly meropenem plus glycopeptide, n = 24). Median duration of neutropenia was 17 days. Bloodstream infections (BSIs) were diagnosed in 28 patients (20%). Early de-escalation rate was 25.5% (n = 26) and mostly consisted of reducing the spectrum of \u3b2-lactams (n = 11, 42%). In comparison with theoretical scenario of continuing therapy until engraftment, the median savings in terms of antibiotic days were 10 for meropenem, 8 for piperacillin-tazobactam, and 7 for vancomycin. Failure rate of early de-escalation was 15% (4/26). Late de-escalation rate was 30.4% (n = 31) and failure rate 19% (6/31). The rate of de-escalation any time before engraftment was 55.9% (n = 57), including discontinuation in 33 patients (32%). Death at day 60 after HSCT occurred in 3 patients who never underwent de-escalation. Acute myeloid disease and BSIs were independent predictors of early de-escalation. De-escalation, including discontinuation, is feasible and safe in pre-engraftment neutropenia after allogeneic HSCT

Blood Stream Infections in Allogeneic Hematopoietic Stem Cell Transplant Recipients: Reemergence of Gram-Negative Rods and Increasing Antibiotic Resistance

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