Segmentation of Corneal Endothelial Cells Contour by Means of a Genetic Algorithm

Corneal images acquired by in-vivo microscopy provide clinical information on the cornea endothelium health state. The reliable estimation of the clinical morphometric parameters requires the accurate detection of cell contours in a large number of cells. Thus for the practical application of this analysis in clinical settings an automated method is needed. We propose the automatic segmentation of corneal endothelial cells contour through an innovative technique based on a genetic algorithm, which combines information about the typical regularity of endothelial cells shape with the pixels intensity of the actual image. Ground truth values for the clinical parameters were obtained from manually drawn cell contours. Results show that an accurate automatic estimation is achieved: for each parameter, the mean difference between its manual estimation and the automated one is always less than 4%, and the maximum difference is always less than 7%

Molecular markers as a tool for phylogenetic studies in <i>Proseriata</i> (Platyhelminthes: Neoophora)

The order Proseriata is one of the most abundant groups of the meiofauna, particularly common in high-energy habitats. Studying Proseriata is difficult, as they are very minute animals with few morphological features that can be used for taxonomic analysis. The lack of diagnostic characters hinders the study of Proseriata by means of traditional methods, and molecular analyses are in most cases needed to reconstruct the phylogeny of Proserata and to provide reliable taxonomic assessment. Here, the results of five study cases were reported: i) the new recently discovered species, Pseudomonocelis paupercula was studied by means of an integrative taxonomic approach that include morphology, karyology, molecular phylogeny, reproductive biology and parentage analyses; ii) the Parotoplana tubifera species group was also investigated by an integrative approach that includes morphology, karyology and molecular phylogeny, and four new Parotoplana species were described; iii) phylogenetic relationships within the genus Monocelis, and within the family Monocelididae were investigated, and two new Mediterranean species belonging to the genus Monocelis was retrieved; iv) the first molecular clock for Proseriata was calibrated, that can be an appealing integration to the integrative taxonomic approach, and can provide phylogenetic reconstruction more accurate in future analyses; v) universal primers were designed to obtain a wider molecular sampling in Proseriata, so far very scarce. = L'ordine Proseriata costituisce uno dei più abbondanti gruppi della meiofauna, i cui rappresentanti sono particolarmente comuni in habitat ad alta energia. Gli studi sui Proseriata sono particolarmente problematici, in quanto l'ordine è rappresentato da organismi di ridotte dimensioni con pochi caratteri diagnostici utili ai fini tassomici. Per questo motivo i Proseriata non possono essere studiati solamente con metodi tradizionali e negli ultimi anni ci si è avvalsi di un approccio tassonomico integrato, comprendente analisi molecolari, sia per le ricostruzioni filogenetiche, sia per l'inquadramento tassonomico. Questo elaborato è costituito da cinque linee di ricerca: i) una nuova specie di recente scoperta, Pseudomonocelis paupercula, è stata descritta e analizzata mediante approccio tassonomico integrato; ii) quattro nuove specie appartenenti al gruppo di specie Parotoplana tubifera sono state descritte e sono state studiate le relazioni filogenetiche all'interno del gruppo e della famiglia Otoplanidae; iii) sono state chiarite le relazioni filogenetiche all'interno del genere Monocelis e della famiglia Monocelididae; questo studio ha portato alla scoperta di due nuove specie del genere Monocelis; iv) è stata eseguita la prima calibrazione dell'orologio molecolare nei Proseriati, che consente di implementare l'approccio tassonomico integrato; v) sono stati disegnati primer universali per i Proseriati, al fine di ampliare l'attuale campionamento molecolare sinora esiguo

Automated Morphometric Analysis of in-vivo Human Corneal Endothelium

In-vivo specular and confocal microscopy provide information on the corneal endothelium health state. The reliable estimation of the clinical parameters requires the accurate detection of cell contours. We propose a method for the automatic segmentation of cell contour. The centers of the cells are detected by convolving the original image with Laplacian of Gaussian kernels, whose scales are set according to the cell size preliminary estimated through a frequency analysis. A structure made by connected vertices is derived from the centers, and it is fine-tuned by combining information about the typical regularity of endothelial cells shape with the pixels intensity of the actual image. Ground truth values for the clinical parameters were obtained from manually drawn cell contours. An accurate automatic estimation is achieved on 30 images: for each clinical parameter, the mean difference between its manual estimation and the automated one is always less than 7%

Mitochondrial DNA reveals genetic structuring of <i>Pinna nobilis</i> across the Mediterranean Sea

Pinna nobilis is the largest endemic Mediterranean marine bivalve. During past centuries, various human activities have promoted the regression of its populations. As a consequence of stringent standards of protection, demographic expansions are currently reported in many sites. The aim of this study was to provide the first large broad-scale insight into the genetic variability of P. nobilis in the area that encompasses the western Mediterranean, Ionian Sea, and Adriatic Sea marine ecoregions. To accomplish this objective twenty-five populations from this area were surveyed using two mitochondrial DNA markers (COI and 16S). Our dataset was then merged with those obtained in other studies for the Aegean and Tunisian populations (eastern Mediterranean), and statistical analyses (Bayesian model-based clustering, median-joining network, AMOVA, mismatch distribution, Tajima’s and Fu’s neutrality tests and Bayesian skyline plots) were performed. The results revealed genetic divergence among three distinguishable areas: (1) western Mediterranean and Ionian Sea; (2) Adriatic Sea; and (3) Aegean Sea and Tunisian coastal areas. From a conservational point of view, populations from the three genetically divergent groups found may be considered as different management units

Contamination of a high-cell-density continuous bioreactor

Continuous fermentations were carried out with a recombinant flocculent Saccharomyces cerevisiae strain in an airlift bioreactor. Once operating under steady state at a dilution rate of 0.45 h−1, the bioreactor was contaminated with Escherichia coli cells. The faster growing E. coli strain was washed out of the bioreactor and the recombinant, slower growing flocculating S. cerevisiae strain remained as the only species detected in the bioreactor. Flocculation, besides allowing for the realization of high-cell-density systems with corresponding unusual high productivity, may be used as a selective property for controlling some contamination problems associated with prolonged continuous operation.Fundação para a Ciência e Tecnologia -PRAXIS XXI/BD/11306/97

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many artificial-intelligence-powered methods have been proposed by the research community for the detection and classification of diabetic retinopathy on fundus retina images. This review article provides a thorough analysis of the use of deep learning methods at the various steps of the diabetic retinopathy detection pipeline based on fundus images. We discuss several aspects of that pipeline, ranging from the datasets that are widely used by the research community, the preprocessing techniques employed and how these accelerate and improve the models' performance, to the development of such deep learning models for the diagnosis and grading of the disease as well as the localization of the disease's lesions. We also discuss certain models that have been applied in real clinical settings. Finally, we conclude with some important insights and provide future research directions

Minimal disease activity in patients with psoriatic arthritis treated with ustekinumab: results from a 24-week real-world study

Psoriatic arthritis (PsA) is a chronic inflammatory joint disease affecting around 40% of psoriasis patients. Minimal disease activity (MDA) criteria have been proposed to identify a state of low disease activity, one of the principal goals of treatment for psoriatic disease. This study investigated treatment with ustekinumab (UST) in the context of a real-world setting. Thirty-four PsA patients who had failure or inadequate response to conventional synthetic disease-modifying antirheumatic drugs or to anti-tumour necrosis factor alpha were enrolled. Demographic and clinical features, MDA criteria, and the impact of psoriatic skin manifestations on patients' quality of life (QoL) using the dermatology life quality index (DLQI) questionnaire were evaluated at baseline and after 24-week treatment. Adverse events were recorded. At week 24, 70.5% of patients (n = 24) achieved MDA. A sub-analysis of dermatological indices of the MDA criteria showed that the psoriasis area severity index score was significantly improved and body surface area was significantly decreased at 24 weeks compared with that at baseline (both p < 0.001). For the rheumatologic indexes, tender joint count, swollen joint count, and tender entheseal points were all significantly improved at 24 weeks of therapy (all p < 0.01 vs. baseline). Mean DLQI value decreased approximately fourfold, and there were no safety concerns. The achievement of MDA as well as the significant improvement in DLQI and lack of adverse events in the context of a real-life setting shown here confirms the efficacy and safety of UST in PsA

On the Energy Performance Design of a Skilled Nursing Facility Building

In Europe, the criteria for designing new buildings are regulated by a set of European Directives and national laws having as a goal the creation of net zero energy buildings by the year 2020. Moreover, according to 2010/31/EU Directive after 31 December 2018, new buildings occupied and owned by public authorities must be nearly zero-energy buildings. The low energy consumption must be accompanied by well-defined thermal characteristics of the building envelope (both opaque and transparent components) and HVAC systems, and must ensure acceptable internal thermal comfort conditions. An interesting case study, proposed in this work, is represented by the elderly nursing building “RelaXXI” which hosts dependent people who require 24-hour special assistance and medical care. Designers focused on the indoor environmental quality as the main goal of the project and the HVAC system has been designed pursuing the maximum integration with the building and its architecture. The aims of this paper are to (1) describe the main design characteristics of the RelaXXI building, (2) analyze the results obtained by dynamic simulation of heating and cooling energy demands, and (3) present the results of performance monitoring completed to date

Health conditions of inmates in Italy

Abstract Background Several studies have shown that prison is characterized by a higher prevalence of chronic diseases than unconfined settings. The aim of this study was to describe the characteristics and health of inmates, focusing on internal diseases. Methods We designed a specific clinical record using the Python programming language. We considered all of the diagnoses according to the ICD-9-CM. Results Of a total of 17,086 inmates, 15,751 were enrolled in our study (M = 14,835; F = 869), corresponding to 92.2% of the entire inmate population (mean age of 39.6 years). The project involved a total of 57 detention facilities in six Italian regions (for a total of 28% of all detainees in Italy), as counted in a census taken on February 3, 2014. From the entire study sample, 32.5% of prisoners did not present any disorders, while 67.5% suffered from at least one disease. The most frequent pathologies were psychiatric (41.3%), digestive (14.5%), infectious (11.5%), cardiovascular (11.4%), endocrine, metabolic, and immune (8.6%), and respiratory (5.4%). Conclusion The findings showed that a large number of detainees were affected by several chronic conditions such as hypertension, dyslipidemia and type 2 diabetes mellitus, with an unusually high prevalence for such a young population. Therefore, a series of preventive measures is recommended to strengthen the entire care process and improve the health and living conditions of prisoners