290 surgical procedures for ulnar nerve entrapment at the elbow: Physiopathology, clinical experience and results

Ulnar nerve entrapment at the elbow is an important and relatively frequent pathological condition that may be related to diffent causes depending on individual or external factors. The cause of the nerve lesion is also idiopathic in about one-quarter to one-third of cases. This variable aetiopathogenetic presentation has often suggested different diagnostic and clinical approaches and, moreover, various surgical procedures. We present our 8-years surgical experience with 290 cases of ulnar nerve entrapment at the elbow analysing the salient clinical features and the results of the surgical treatment in the light of the relevant literature available on this topic

Synthetic approaches to difluoroindolecarboxylic acid ethyl esters

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Abnormal Pain Sensation in Mice Lacking the Prokineticin Receptor PKR2: Interaction of PKR2 with Transient Receptor Potential TRPV1 and TRPA1

The amphibian Bv8 and the mammalian prokineticin 1 (PROK1) and 2 (PROK2) are new chemokine-like protein ligands acting on two G protein-coupled receptors, prokineticin receptor 1 (PKR1) and 2 (PKR2), participating to the mediation of diverse physiological and pathological processes. Prokineticins (PKs), specifically activating the prokineticin receptors (PKRs) located in several areas of the central and peripheral nervous system associated with pain, play a fundamental role in nociception. In this paper, to improve the understanding of the prokineticin system in the neurobiology of pain, we investigated the role of PKR2 in pain perception using pkr2 gene-deficient mice. We observed that, compared to wildtype, pkr2-null mice were more resistant to nociceptive sensitization to temperatures ranging from 46 to 48 \ub0C, to capsaicin and to protons, highlighting a positive interaction between PKR2 and the non-selective cation channels TRPV1. Moreover, PKR2 knock-out mice showed reduced nociceptive response to cold temperature (4 \ub0C) and to mustard oil-induced inflammatory hyperalgesia, suggesting a functional interaction between PKR2 and transient receptor potential ankyrin 1 ion (TRPA1) channels. This notion was supported by experiments in dorsal root ganglia (DRG) cultures from pkr1 and\u2013pkr2-null mice, demonstrating that the percentage of Bv8-responsive DRG neurons which were also responsive to mustard oil was much higher in PKR1 12/ 12 than in PKR2 12/ 12 mice. Taken together, these findings suggest a functional interaction between PKR2 and TRP channels in the development of hyperalgesia. Drugs able to directly or indirectly block these targets and/or their interactions may represent potential analgesics

Euphorbia kurtzii Subils

Rio Carnero, ruta 9, antes de llegar a Jesús MaríapublishedVersio

Oenothera siambonensis W. Dietr.

Ruta Nº 64: Próximo a El PortezueloUniversidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentin

Dark blood ischemic LGE segmentation using a deep learning approach

The extent of ischemic scar detected by Cardiac Magnetic Resonance (CMR) with late gadolinium enhancement (LGE) is linked with long-term prognosis, but scar quantification is time-consuming. Deep Learning (DL) approaches appear promising in CMR segmentation. Purpose: To train and apply a deep learning approach to dark blood (DB) CMR-LGE for ischemic scar segmentation, comparing results to 4-Standard Deviation (4-SD) semi-automated method. Methods: We trained and validated a dual neural network infrastructure on a dataset of DB-LGE short-axis stacks, acquired at 1.5T from 33 patients with ischemic scar. The DL architectures were an evolution of the U-Net Convolutional Neural Network (CNN), using data augmentation to increase generalization. The CNNs worked together to identify and segment 1) the myocardium and 2) areas of LGE. The first CNN simultaneously cropped the region of interest (RoI) according to the bounding box of the heart and calculated the area of myocardium. The cropped RoI was then processed by the second CNN, which identified the overall LGE area. The extent of scar was calculated as the ratio of the two areas. For comparison, endo- and epi-cardial borders were manually contoured and scars segmented by a 4-SD technique with a validated software. Results: The two U-Net networks were implemented with two free and open-source software library for machine learning. We performed 5-fold cross-validation over a dataset of 108 and 385 labelled CMR images of the myocardium and scar, respectively. We obtained high performance (> ∼0.85) as measured by the Intersection over Union metric (IoU) on the training sets, in the case of scar segmentation. With regards to heart recognition, the performance was lower (> ∼0.7), although improved (∼ 0.75) by detecting the cardiac area instead of heart boundaries. On the validation set, performances oscillated between 0.8 and 0.85 for scar tissue recognition, and dropped to ∼0.7 for myocardium segmentation. We believe that underrepresented samples and noise might be affecting the overall performances, so that additional data might be beneficial. Figure1: examples of heart segmentation (upper left panel: training; upper right panel: validation) and of scar segmentation (lower left panel: training; lower right panel: validation). Conclusion: Our CNNs show promising results in automatically segmenting LV and quantify ischemic scars on DB-LGE-CMR images. The performances of our method can further improve by expanding the data set used for the training. If implemented in a clinical routine, this process can speed up the CMR analysis process and aid in the clinical decision-making

New generalized fuzzy metrics and fixed point theorem in fuzzy metric space

In this paper, in fuzzy metric spaces (in the sense of Kramosil and Michalek (Kibernetika 11:336-344, 1957)) we introduce the concept of a generalized fuzzy metric which is the extension of a fuzzy metric. First, inspired by the ideas of Grabiec (Fuzzy Sets Syst. 125:385-389, 1989), we define a new G-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by M Grabiec). Next, inspired by the ideas of Gregori and Sapena (Fuzzy Sets Syst. 125:245-252, 2002), we define a new GV-contraction of Banach type with respect to this generalized fuzzy metric, which is a generalization of the contraction of Banach type (introduced by V Gregori and A Sapena). Moreover, we provide the condition guaranteeing the existence of a fixed point for these single-valued contractions. Next, we show that the generalized pseudodistance J:X×X→[0,∞) (introduced by Włodarczyk and Plebaniak (Appl. Math. Lett. 24:325-328, 2011)) may generate some generalized fuzzy metric NJ on X. The paper includes also the comparison of our results with those existing in the literature

Avaliação da atividade antimicrobiana de extratos brutos de capim annoni-2.

A utilização de plantas com finalidade medicinal acompanha toda a evolução da humanidade, sendo muitas vezes, um dos únicos recursos terapêuticos da comunidade no tratamento e prevenção de doenças.JAI