The Role of Viral Pathogens in Horse Respiratory Diseases: A Cytological and Molecular Approach Using Next-Generation Sequencing.

(1) Background: Respiratory problems may be associated with pathogens among which viruses may play an important role in causing or promoting clinical signs. However, traditional diagnostic methods for equine infectious diseases, such as PCR, are limited to known pathogens and often miss rare or novel viruses. Metagenomic next-generation sequencing is a transformative method that allows the sequencing of all genomes present in a sample.

VP-net: an end-to-end deep learning network for elastic wave velocity prediction in human skin using optical coherence elastography.

Introduction: Acne vulgaris, one of the most common skin conditions, affects up to 85% of late adolescents, currently no universally accepted assessment system. The biomechanical properties of skin provide valuable information for the assessment and management of skin conditions. Wave-based optical coherence elastography (OCE) quantitatively assesses these properties of tissues by analyzing induced elastic wave velocities.

Systematic Review on Learning-based Spectral CT.

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications.

LRR-CED: low-resolution reconstruction-aware convolutional encoder-decoder network for direct sparse-view CT image reconstruction.

. Sparse-view computed tomography (CT) reconstruction has been at the forefront of research in medical imaging. Reducing the total x-ray radiation dose to the patient while preserving the reconstruction accuracy is a big challenge.

Multi-channel convolutional analysis operator learning for dual-energy CT reconstruction.

Dual-energy computed tomography (DECT) has the potential to improve contrast and reduce artifacts and the ability to perform material decomposition in advanced imaging applications. The increased number of measurements results in a higher radiation dose, and it is therefore essential to reduce either the number of projections for each energy or the source x-ray intensity, but this makes tomographic reconstruction more ill-posed.We developed the multi-channel convolutional analysis operator learning (MCAOL) method to exploit common spatial features within attenuation images at different energies and we propose an optimization method which jointly reconstructs the attenuation images at low and high energies with mixed norm regularization on the sparse features obtained by pre-trained convolutional filters through the convolutional analysis operator learning (CAOL) algorithm.

Statin-associated necrotizing autoimmune myopathy with concurrent myasthenia gravis.

Statin treatment has been associated with necrotizing autoimmune myopathy and has been linked to myasthenia gravis. We present an unprecedented clinical challenge with both disorders occurring in a patient treated with statins few months earlier.

Regularization by denoising sub-sampled Newton method for spectral CT multi-material decomposition.

Spectral Computed Tomography (CT) is an emerging technology that enables us to estimate the concentration of basis materials within a scanned object by exploiting different photon energy spectra. In this work, we aim at efficiently solving a model-based maximum-a-posterior problem to reconstruct multi-materials images with application to spectral CT. In particular, we propose to solve a regularized optimization problem based on a plug-in image-denoising function using a randomized second order method.

Quantitative cone-beam CT reconstruction with polyenergetic scatter model fusion.

Scatter can account for large errors in cone-beam CT (CBCT) due to its wide field of view, and its complicated nature makes its compensation difficult. Iterative polyenergetic reconstruction algorithms offer the potential to provide quantitative imaging in CT, but they are usually incompatible with scatter contaminated measurements. In this work, we introduce a polyenergetic convolutional scatter model that is directly fused into the reconstruction process, and exploits information readily available at each iteration for a fraction of additional computational cost.

Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source.

Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the x-ray attenuation in terms of mass or electron density is an ill-posed problem when a single polyenergetic source is used with a spectrally indiscriminate detector. Existing approaches to single source polyenergetic modelling often impose consistency with a physical model, such as water-bone or photoelectric-Compton decompositions, which will either require detailed prior segmentation or restrictive energy dependencies, and may require further calibration to the quantity of interest.

Compressive sensing of full wave field data for structural health monitoring applications.

Numerous nondestructive evaluations and structural health monitoring approaches based on guide waves rely on analysis of wave fields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. The informative content which can be extracted from these inspections is relevant; however, the acquisition process is generally time-consuming, posing a limit in the applicability of such approaches. To reduce the acquisition time, we use a random sampling scheme based on compressive sensing (CS) to minimize the number of points at which the field is measured.

Identification of stroke etiology may contribute to improve the outcome in dedicated units.

Background: The purpose of our study is to investigate whether stroke unit (SU) care and the utilization of Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria may contribute to reduce death and disability in hospitalized patients after a first-ever ischemic stroke (IS).

Methods: Data included in the present study were derived from our previous study on the incidence and outcome of cerebrovascular diseases in the district of Udine, performed from April 1, 2007, to March 31, 2009.

Results: We identified 429 hospitalized first-ever IS cases, 297 of 429 (69.

The contribution of assessing cognitive impairment in radiologically-isolated syndrome (RIS): a single case report follow-up study.

Radiologically-isolated syndrome (RIS) is a recently-defined entity, described as the incidental discovery of lesions suggestive of multiple sclerosis (MS) on brain magnetic resonance imaging (MRI) scans demonstrating dissemination in space (DIS) without symptom expression and with a normal neurological examination. Recent studies demonstrate that RIS patients present similar features of cognitive impairment as MS patients. We describe a case of a RIS patient in whom investigating cognitive functions was a useful tool for diagnostic and therapeutic decisions.

Model-based compressive sensing for damage localization in Lamb wave inspection.

Compressive sensing (CS) has emerged as a potentially viable technique for the efficient compression and analysis of high-resolution signals that have a sparse representation in a fixed basis. In this work, we have developed a CS approach for ultrasonic signal decomposition suitable to achieve high performance in Lamb-wave-based defect detection procedures. In the proposed approach, a CS algorithm based on an alternating minimization (AM) procedure is adopted to extract the information about both the system impulse response and the reflectivity function.

Stroke incidence and 30-day and six-month case fatality rates in Udine, Italy: a population-based prospective study.

Background: Stroke incidence in high-income countries is reported to decrease, and new data on stroke incidence and outcome are needed to design stroke services and to ameliorate stroke management.

Methods: This study is part of a two-year prospective community-based registry of all cerebrovascular events in the district of Udine (153,312 inhabitants), Friuli-Venezia Giulia region, northeast of Italy, between 1 April 2007 and 31 March 2009. Overlapping sources for case finding were used, combining hot and cold pursuit.

Incidence of transient ischemic attack and early stroke risk: validation of the ABCD2 score in an Italian population-based study.

Background And Purpose: The importance of transient ischemic attack (TIA) lies on the short-term risk of stroke, and the ABCD2 score may improve early stroke risk prediction. However, population-based studies are still needed. We aimed to provide data on TIA incidence and to evaluate the ABCD2 predictive ability for early recurrent stroke in a population-based study.

[Regional institutional accreditation measures for nephrology in Italy].

The process of institutional accreditation has been initiated in Italy too because it is considered to be the criterion upon which new relations within the National Health Service must be based. These relations include payment for the service as well as choice of quality assessment and revision of the activities carried out and the services provided. This paper describes the regulations in force regarding Institutional accreditation and the specific regulations of Italian regional credit laws on nephrology.

[Adverse effects of corticosteroids].

Due to their anti-inflammatory and immunosuppressive properties, as well as their action on the hematopoietic system and the calcium phosphate turnover, corticosteroids are widely employed in the treatment of many diseases. However, the therapeutic use of these compounds is frequently associated with unwanted, mainly type A, effects that are directly dependent on the wide spectrum of their pharmacological activities. In this study these side effects are critically reviewed and classified on the basis of the organs and systems involved.