Cancer pain management in an oncological ward in a comprehensive cancer center with an established palliative care unit.

Abstract BACKGROUND: This survey was performed to draw information on pain prevalence, intensity, and management from a sample of patients who were admitted to an oncologic center where a palliative care unit (PCU) has been established for 13 years. METHODS: Cross-sectional survey in an oncological department performed 1 day per month for six consecutive months. RESULTS: Of the 385 patients, 69.1, 19.2, 8.6, and 3.1 % had no pain, mild, moderate, and severe pain, respectively. Inpatients and patients with a low Karnofsky score showed higher levels of pain intensity (p < 0.0005). One hundred twenty-eight patients with pain or receiving analgesics were analyzed for pain management index (PMI). Only a minority of patients had negative PMI score, which was statistically associated with inpatient admission (p = 0.011). Fifty of these 128 patients had breakthrough pain (BTP), and all of them were receiving some medication for BTP. CONCLUSION: It is likely that the presence of PCU team providing consultation, advices, and cultural pressure, other than offering admissions for difficult cases had a positive impact on the use of analgesics, as compared with previous similar surveys performed in oncological setting, where a PCU was unavailable. This information confirms the need of the presence of a PCU in a high volume oncological department

Effect of Pre-Qualification Test on Space Charge Accumulation Phenomenon

This paper is focused on the measurement of space charge in flat specimens deriving from a cable subjected to the Pre-Qualification (PQ) test. In particular, before starting the PQ test and after finishing them, the flat specimens have been taken from the cable. This with the aim to evaluate the effect of PQ test on the space charge accumulation phenomenon. The PEA cell has been used for the space charge detection, while the Standard IEEE 1732-2017 has been followed for the measurement procedure. For both unaged and aged specimens, the space charge and the related electric field distribution have been reported in the paper. Measurement results highlight that the more accentuated electric field distortion has been observed during the test carried out on the aged specimen stressed under positive polarity

Development of a new PEA Cell for model cables

In this work, a prototype of a new PEA cell configuration has been built and its principle of operation investigated and described. The reasons that led the authors to this work are due to the fact that the traditional cell still presents some issues. In particular, it known that that for cable specimens the reflection phenomenon and the signal attenuation are the main responsible factors that affecting the main output signal. Concerning the acoustic wave attenuation phenomenon, it was found that the signal magnitude can increase by replacing the metallic ground electrode with a polymeric acoustic coupler and the PVDF absorber with a metallic block. Based on this, after a description of the classic and the new PEA cell structure, in the present paper the acoustic wave behavior in the sensor/absorber interface has been simulated by means of a previously developed model. Simulation results show that in the new PEA cell the signal sensed by piezoelectric sensor is doubled in comparison with that detected in the traditional configuration. However, in the first experimental test carried out with the built PEA cell prototype in a model cable specimen it has been observed that the magnitude of the space charge profile needs to be further improved

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets

A global multinational survey of cefotaxime-resistant coliforms in urban wastewater treatment plants

The World Health Organization Global Action Plan recommends integrated surveillance programs as crucial strategies for monitoring antibiotic resistance. Although several national surveillance programs are in place for clinical and veterinary settings, no such schemes exist for monitoring antibiotic-resistant bacteria in the environment. In this transnational study, we developed, validated, and tested a low-cost surveillance and easy to implement approach to evaluate antibiotic resistance in wastewater treatment plants (WWTPs) by targeting cefotaxime-resistant (CTX-R) coliforms as indicators. The rationale for this approach was: i) coliform quantification methods are internationally accepted as indicators of fecal contamination in recreational waters and are therefore routinely applied in analytical labs; ii) CTX-R coliforms are clinically relevant, associated with extended-spectrum β-lactamases (ESBLs), and are rare in pristine environments. We analyzed 57 WWTPs in 22 countries across Europe, Asia, Africa, Australia, and North America. CTX-R coliforms were ubiquitous in raw sewage and their relative abundance varied significantly (<0.1% to 38.3%), being positively correlated (p < 0.001) with regional atmospheric temperatures. Although most WWTPs removed large proportions of CTX-R coliforms, loads over 10 colony-forming units per mL were occasionally observed in final effluents. We demonstrate that CTX-R coliform monitoring is a feasible and affordable approach to assess wastewater antibiotic resistance status. [Abstract copyright: Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org

A global multinational survey of cefotaxime-resistant coliforms in urban wastewater treatment plants

The World Health Organization Global Action Plan recommends integrated surveillance programs as crucial strategies for monitoring antibiotic resistance. Although several national surveillance programs are in place for clinical and veterinary settings, no such schemes exist for monitoring antibiotic-resistant bacteria in the environment. In this transnational study, we developed, validated, and tested a low-cost surveillance and easy to implement approach to evaluate antibiotic resistance in wastewater treatment plants (WWTPs) by targeting cefotaxime-resistant (CTX-R) coliforms as indicators. The rationale for this approach was: i) coliform quantification methods are internationally accepted as indicators of fecal contamination in recreational waters and are therefore routinely applied in analytical labs; ii) CTX-R coliforms are clinically relevant, associated with extended-spectrum β-lactamases (ESBLs), and are rare in pristine environments. We analyzed 57 WWTPs in 22 countries across Europe, Asia, Africa, Australia, and North America. CTX-R coliforms were ubiquitous in raw sewage and their relative abundance varied significantly (&lt;0.1% to 38.3%), being positively correlated (p &lt; 0.001) with regional atmospheric temperatures. Although most WWTPs removed large proportions of CTX-R coliforms, loads over 103 colony-forming units per mL were occasionally observed in final effluents. We demonstrate that CTX-R coliform monitoring is a feasible and affordable approach to assess wastewater antibiotic resistance status

Tackling antibiotic resistance: the environmental framework

Antibiotic resistance is a threat to human and animal health worldwide, and key measures are required to reduce the risks posed by antibiotic resistance genes that occur in the environment. These measures include the identification of critical points of control, the development of reliable surveillance and risk assessment procedures, and the implementation of technological solutions that can prevent environmental contamination with antibiotic resistant bacteria and genes. In this Opinion article, we discuss the main knowledge gaps, the future research needs and the policy and management options that should be prioritized to tackle antibiotic resistance in the environment

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