Minimal inhibitory and Mutant prevention concentrations of enrofloxacin for Pasteurella multocida from rabbits affected by pasteurellosis

Pasteurella multocida is the agent of one of the most significant diseases in rabbits and it is associated with a heterogeneous clinical picture. Drugs belonging to the fluoroquinolones class are useful to control pasteurellosis. Among them, enrofloxacin is one of the most used molecules in rabbit industry and it is the only one fluoroquinolone registered for this species in Italy. Enrofloxacin adopted dosages are currently based on Minimum Inhibitory Concentration (MIC). Nevertheless, MIC is not effective against possible pathogen sub-populations with lower susceptibility that may be selectively amplified, leading to possible problems of antibiotic resistance. Mutant Prevention Concentration (MPC) could represent an approach to minimize the risk of resistance selection in pathogens. The aim of this work was to test the sensitivity to enrofloxacin of P. multocida strains isolated from rabbits affected by pasteurellosis to evaluate if MPC-based dosages can represent a valid option. The study was performed on ten strains of P. multocida isolated from rabbits from two industrial farms of Puglia, South Italy. The sensitivity to enrofloxacin has been evaluated by MIC tests by microdilution method and MPC tests performed according to Marcusson et al. (2005) with minor modifications. The results of MIC and MPC tests have revealed that MPC dosages are on average 8,4 times higher than MIC dosages. This data highlight that, although MPC-based dosages are useful to prevent the selection of potential mutant, they could be higher than MIC-based ones, leading to possible issues related to their application in field, for example the potential risk of possible toxicity for animals and residues in meat

Elevated n-terminal pro-brain natriuretic peptide is associated with mortality in tobacco smokers independent of airflow obstruction

Background: Tobacco use is associated with an increased prevalence of cardiovascular disease. N-terminal pro-brain natiuretic peptide (NT-proBNP), a widely available biomarker that is associated with cardiovascular outcomes in other conditions, has not been investigated as a predictor of mortality in tobacco smokers. We hypothesized that NT-proBNP would be an independent prognostic marker in a cohort of well-characterized tobacco smokers without known cardiovascular disease. Methods: Clinical data from 796 subjects enrolled in two prospective tobacco exposed cohorts was assessed to determine factors associated with elevated NT-proBNP and the relationship of these factors and NT-proBNP with mortality. Results: Subjects were followed for a median of 562 (IQR 252 - 826) days. Characteristics associated with a NT-proBNP above the median (≥49 pg/mL) were increased age, female gender, and decreased body mass index. By time-to-event analysis, an NT-proBNP above the median (≥49 pg/mL) was a significant predictor of mortality (log rank p = 0.02). By proportional hazard analysis controlling for age, gender, cohort, and severity of airflow obstruction, an elevated NT-proBNP level (≥49 pg/mL) remained an independent predictor of mortality (HR = 2.19, 95% CI 1.07-4.46, p = 0.031). Conclusions: Elevated NT-proBNP is an independent predictor of mortality in tobacco smokers without known cardiovascular disease, conferring a 2.2 fold increased risk of death. Future studies should assess the ability of this biomarker to guide further diagnostic testing and to direct specific cardiovascular risk reduction inventions that may positively impact quality of life and survival. © 2011 Stamm et al

O IMPACTO DAS ATIVIDADES ANTRÓPICAS NAS ÁREAS ÚMIDAS NA PLANÍCIE DE INUNDAÇÃO DO RIO GRAVATAÍ - RS

A bacia hidrográfica do rio Gravataí se localiza na região leste do estado do Rio Grande do Sul. A importância da preservação das áreas úmidas junto à planície de inundação do rio Gravataí é imprescindível para o equilíbrio ecológico e hidrodinâmico do rio. O objetivo deste trabalho é identificar as mudanças ocorridas nas áreas úmidas. Foram realizados registros fotográficos e análise de imagens satelitais, no período de 2006 a 2012, avaliando a degradação das áreas úmidas

Validation of an Engineered Cell Model for In Vitro and In Vivo HIF-1 alpha Evaluation by Different Imaging Modalities

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Development and validation of a coupled numerical model for offshore floating multi-purpose platforms

A multi-purpose platform (MPP) is an offshore system designed to serve the purposes of more than one off-shore industry. Over the past decades, a number of industries have expanded or are expanding, from onshore to offshore locations. In the present work, the MPP proposed in the framework of Blue Growth Farm project is considered. The aim here is to develop and validate a coupled aero-hydro-servo-elastic numerical model, which will be used to predict the dynamic response of the MPP under a wide range of environmental condi-tions. Model test research was conducted to validate the developed numerical model. The model test was carried out in the water basin at Centrale Nantes, employing the Froude scale strategy. An innovative ap-proach to modelling wind load in the experimental environment was proposed and applied. This paper re-ports the up-to-date research outcome of the Blue Growth Farm project - numerical model development and validation

Proximal hyperspectral analysis in grape leaves for region and variety identification.

Reflectance measurements of plants of the same species can produce sets of data with differences between spectra, due to factors that can be external to the plant, like the environment where the plant grows, and to internal factors, for measurements of different varieties. This paper reports results of the analysis of radiometric measurements performed on leaves of vines of several grape varieties and on several sites. The objective of the research was, after the application of techniques of dimensionality reduction for the definition of the most relevant wavelengths, to evaluate four machine learning models applied to the observational sample aiming to discriminate classes of region and variety in vineyards. The tested machine learning classification models were Canonical Discrimination Analysis (CDA), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Support Vector Machine (SVM). From the results, we reported that the LGBM model obtained better accuracy in spectral discrimination by region, with a value the 0.93, followed by the RF model. Regarding the discrimination between grape varieties, these two models also achieved better results, with accuracies of 0.88 and 0.89. The wavelengths more relevant for discrimination were at ultraviolet, followed by those at blue and green spectral regions. This research pointed toward the importance of defining the wavelengths more relevant to the characterization of the reflectance spectra of leaves of grape varieties and revealed the effective capability of discriminating vineyards by their region or grape variety, using machine learning models. Análise hiperespectral proximal em folhas de videiras para identificação de regiões e variedades RESUMO: Medições de refletância de plantas da mesma espécie podem produzir conjuntos de dados com diferenças entre os espectros, devido a fatores que podem ser externos à planta, como o ambiente onde a planta cresce, e fatores internos, para medições com variedades de plantas. Este artigo reporta resultados da análise de medições por espectrorradiometria efetuadas em folhas de vinhas de variedades e em diferentes localidades. O objetivo desta pesquisa foi, após a aplicação de técnicas de redução de dimensionalidade para a definição dos comprimentos de onda mais relevantes, avaliar quatro modelos de aprendizado de máquina aplicados à amostra observacional visando discriminar classes de região e variedade. Os modelos de classificação de aprendizado de máquina testados foram Canonical Discrimination Analysis (CDA), Light Gradient Boosting Machine (LGBM), Random Forest (RF) e Support Vector Machine (SVM). A partir dos resultados, relatamos que o modelo LGBM obteve melhor acurácia na discriminação espectral por região, com valor de 0,93, seguido pelo modelo RF. Relativamente à discriminação entre castas, estes dois modelos também obtiveram melhores resultados, com acurácias de 0,88 e 0,89. Os comprimentos de onda mais importantes para as discriminações procuradas estiveram na região do ultravioleta, seguidos do azul e do verde. Este trabalho aponta para a importância de detectar os comprimentos de onda mais relevantes para a caracterização dos espectros de reflectância das folhas de variedades de vinhas, e revela a capacidade efetiva de discriminar vinhedos por suas regiões ou variedades, usando modelos de aprendizado de máquina. Palavras-chave: Vinhedos, hiperespectral, aprendizagem de máquina

PerBrain: a multimodal approach to personalized tracking of evolving state-of-consciousness in brain-injured patients: protocol of an international, multicentric, observational study

BACKGROUND: Disorders of consciousness (DoC) are severe neurological conditions in which consciousness is impaired to various degrees. They are caused by injury or malfunction of neural systems regulating arousal and awareness. Over the last decades, major efforts in improving and individualizing diagnostic and prognostic accuracy for patients affected by DoC have been made, mainly focusing on introducing multimodal assessments to complement behavioral examination. The present EU-funded multicentric research project “PerBrain” is aimed at developing an individualized diagnostic hierarchical pathway guided by both behavior and multimodal neurodiagnostics for DoC patients. METHODS: In this project, each enrolled patient undergoes repetitive behavioral, clinical, and neurodiagnostic assessments according to a patient-tailored multi-layer workflow. Multimodal diagnostic acquisitions using state-of-the-art techniques at different stages of the patients’ clinical evolution are performed. The techniques applied comprise well-established behavioral scales, innovative neurophysiological techniques (such as quantitative electroencephalography and transcranial magnetic stimulation combined with electroencephalography), structural and resting-state functional magnetic resonance imaging, and measurements of physiological activity (i.e. nasal airflow respiration). In addition, the well-being and treatment decision attitudes of patients’ informal caregivers (primarily family members) are investigated. Patient and caregiver assessments are performed at multiple time points within one year after acquired brain injury, starting at the acute disease phase. DISCUSSION: Accurate classification and outcome prediction of DoC are of crucial importance for affected patients as well as their caregivers, as individual rehabilitation strategies and treatment decisions are critically dependent on the latter. The PerBrain project aims at optimizing individual DoC diagnosis and accuracy of outcome prediction by integrating data from the suggested multimodal examination methods into a personalized hierarchical diagnosis and prognosis procedure. Using the parallel tracking of both patients’ neurological status and their caregivers’ mental situation, well-being, and treatment decision attitudes from the acute to the chronic phase of the disease and across different countries, this project aims at significantly contributing to the current clinical routine of DoC patients and their family members. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04798456. Registered 15 March 2021 – Retrospectively registered

Nailfold videocapillaroscopy and serum VEGF levels in scleroderma are associated with internal organ involvement

Purpose: Nailfold videocapillaroscopy (NVC) identifies the microvascular hallmarks of systemic sclerosis (SSc) and vascular endothelial growth factor (VEGF) and may play a pivotal role in the associated vasculopathy. The aim of the present study was to compare NVC alterations with clinical subsets, internal organ involvement, and serum VEGF levels in a cohort of selected SSc cases. Methods: We studied 44 patients with SSc who were evaluated within 3\ua0months from enrollment by NVC, skin score, severity index, pulmonary function tests, carbon monoxide diffusing capacity (DLCO), echocardiography, pulmonary high-resolution computed tomography (HRCT), gastroesophageal (GE) endoscopy or manometry or X-ray, and serum autoantibodies. Serum VEGF-A levels were determined by ELISA in 72 SSc patients and 31 healthy controls. Results: Giant capillaries were inversely correlated with age (p\ua0=\ua00.034, r\ua0=\ua0 120.34) and to the extent of reticular pattern at HRCT (p\ua0=\ua00.04, r\ua0=\ua0 120.5). Avascular areas were directly correlated with capillaroscopy skin ulcer risk index (CSURI) (p\ua0=\ua00.006, r\ua0=\ua0+0.4) and severity index (p\ua0=\ua00.004, r\ua0=\ua0+0.5). The mean capillary density was directly correlated to the ulcer number (p\ua0=\ua00.02, r\ua0=\ua0+0.4) and to DLCO/alveolar volume (p\ua0=\ua00.02, r\ua0=\ua0+0.4) and inversely correlated with severity index (p\ua0=\ua00.01, r\ua0=\ua0 120.4) and skin score (p\ua0=\ua00.02, r\ua0=\ua0 120.4). Serum VEGF levels were higher in the SSc population vs controls (p\ua0=\ua00.03) and inversely correlated with DLCO (p\ua0=\ua00.01, r\ua0= 120.4) and directly with ground-glass and reticular pattern at HRCT (p\ua0=\ua00.04, r\ua0=\ua0+0.4 for both). Conclusions: Our data suggest the importance of NVC not only for the diagnosis, but also for the global evaluation of SSc patients. Of note, serum VEGF levels may act as a biomarker of interstitial lung involvement