Public and patient involvement: a survey on knowledge, experience and opinions among researchers within a precision oncology European project

Participatory research; Patient engagement; Precision oncologyInvestigación participativa; Compromiso del paciente; Oncología de precisiónRecerca participativa; Compromís del pacient; Oncologia de precisióBackground Patient and Public Involvement (PPI) is slowly but steadily being implemented in all phases of clinical research. As part of the European project “Building Data Rich Clinical Trials” a survey was launched to investigate the knowledge, experiences and opinions on this topic of clinicians and researchers from seven European clinical and non-clinical centers (Cancer Core Europe). Methods An invitation to take part in a cross-sectional web survey was sent to 199 clinicians and researchers working in the field of precision oncology. The questionnaire was developed ad hoc because no existing questionnaires met the purpose of this study. The analysis takes account of whether respondents had experience on PPI or not. Results On a total of 101 respondents, this survey reveals that 76.2% of them knew about PPI before answering the questionnaire, 54.5% had experience in the previous five years and 86.1% were interested in a training course on this topic. PPI knowledge grew together with career seniority (peak of 86.5% for established career professionals), while the group most interested in a course was the early-career professionals (100.0%). Finally, the majority of respondents stated they had no training or education on PPI (67.3% of experienced and 82.6% of not-experienced respondents). Conclusions This survey shows that most cancer researchers knew the term PPI, even if only a little more than half of them had any relative experience. Opinions on PPI benefits, negative effects, barriers and requirements differed between the groups of PPI experienced and not-experienced respondents, showing that experience itself can influence respondents’ opinions. Most of respondents reported they would prefer a training course based on practical rather than theoretical tools.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 965397

Mapping of Asbestos Cement Roofs and Their Weathering Status Using Hyperspectral Aerial Images

and (ii) the development of a spectral index related to the roof weathering status. Aerial images were collected through the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) sensor, which acquires data in 102 channels from the visible to the thermal infrared spectral range. An image based supervised classification was performed using the Spectral Angle Mapper (SAM) algorithm. The SAM was trained through a set of pixels selected on roofs of different materials. The map showed an average producer's accuracy (PA) of 86% and a user's accuracy (UA) of 89% for the asbestos cement class. A novel spectral index, the "Index of Surface Deterioration" (ISD), was defined based on measurements collected with a portable spectroradiometer on asbestos cement roofs that were characterized by different weathering statuses. The ISD was then calculated on the MIVIS images, allowing the distinction of two weathering classes (i.e., high and low). The asbestos cement map was handled in a Geographic Information System (GIS) in order to supply the municipalities with the cadastral references of each property having an asbestos cement roof. This tool can be purposed for municipalities as an aid to prioritize asbestos removal, based on roof weathering status

In Vitro and In Vivo Assessment of a New Workflow for the Acquisition of Mandibular Kinematics Based on Portable Tracking System with Passive Optical Reflective Markers

Clinical use of portable optical tracking system in dentistry could improve the analysis of mandibular movements for diagnostic and therapeutic purposes. A new workflow for the acquisition of mandibular kinematics was developed. Reproducibility of measurements was tested in vitro and intra- and inter-rater repeatability were assessed in vivo in healthy volunteers. Prescribed repeated movements (n = 10) in three perpendicular directions of the tracking-device coordinate system were performed. Measurement error and coefficient of variation (CV) among repetitions were determined. Mandibular kinematics of maximum opening, left and right laterality, protrusion and retrusion of five healthy subjects were recorded in separate sessions by three different operators. Obtained records were blindly examined by three observers. Intraclass correlation coefficient (ICC) was calculated to estimate inter-rater and intra-rater reliability. Maximum in vitro measurement error was 0.54 mm and CV = 0.02. Overall, excellent intra-rater reliability (ICC > 0.90) for each variable, general excellent intra-rater reliability (ICC = 1.00) for all variables, and good reliability (ICC > 0.75) for inter-rater tests were obtained. A lower score was obtained for retrusion with “moderate reliability” (ICC = 0.557) in the inter-rater tests. Excellent repeatability and reliability in optical tracking of primary movements were observed using the tested portable tracking device and the developed workflow

Presenting evidence-based health information for people with multiple sclerosis : the IN-DEEP project protocol

Background - Increasingly, evidence-based health information, in particular evidence from systematic reviews, is being made available to lay audiences, in addition to health professionals. Research efforts have focused on different formats for the lay presentation of health information. However, there is a paucity of data on how patients integrate evidence-based health information with other factors such as their preferences for information and experiences with information-seeking. The aim of this project is to explore how people with multiple sclerosis (MS) integrate health information with their needs, experiences, preferences and values and how these factors can be incorporated into an online resource of evidence-based health information provision for people with MS and their families.Methods - This project is an Australian-Italian collaboration between researchers, MS societies and people with MS. Using a four-stage mixed methods design, a model will be developed for presenting evidence-based health information on the Internet for people with MS and their families. This evidence-based health information will draw upon systematic reviews of MS interventions from The Cochrane Library. Each stage of the project will build on the last. After conducting focus groups with people with MS and their family members (Stage 1), we will develop a model for summarising and presenting Cochrane MS reviews that is integrated with supporting information to aid understanding and decision making. This will be reviewed and finalised with people with MS, family members, health professionals and MS Society staff (Stage 2), before being uploaded to the Internet and evaluated (Stages 3 and 4).Discussion - This project aims to produce accessible and meaningful evidence-based health information about MS for use in the varied decision making and management situations people encounter in everyday life. It is expected that the findings will be relevant to broader efforts to provide evidence-based health information for patients and the general public. The international collaboration also permits exploration of cultural differences that could inform international practice.<br /

Analytical aspects of diterpene alkaloid poisoning with monkshood.

A sensitive and specific method for aconitine extraction from biological samples was developed. Aconitine, the main toxic alkaloid from plants belonging to Aconitum species (family Ranunculaceae), was determined in plant material by an external standard method, and by a standard addition calibration method in biological fluids. Described here is one fatal case and five intoxications of accidental aconitine poisoning following the ingestion of aconite mistaken for an edible grass, Aruncus dioicus (Walt.) Fernald, "mountain asparagus", and Cicerbita alpina (L.) Wallroth. The aconitine content in urine was in the range 2.94 μg/mL (dead patient) – 0.20 μg/mL (surviving patients), which was almost two to four times higher than that in plasma

Is drop-out from obesity treatment a predictable and preventable event?

BACKGROUND: Attrition is an important but understudied issue that plays a vital role in the successful treatment of obesity. To date, most studies focusing on attrition rates and/or its predictors have been based on pretreatment data routinely collected for other purposes. Our study specifically aims at identifying the predictors of drop-out focusing on empirically or theoretically-based factors. METHODS: We conducted a retrospective observational study in an academic outpatient clinical nutrition service in Pavia, Italy. We examined a total of 98 adult obese patients (36 males, 62 females) who underwent a 6-month dietary behavioral weight-loss treatment at our Center. Pre-treatment and treatment-related variables were collected or calculated from clinical charts in order to discriminate those subjects who completed treatment from those who abandoned it before its completion. Multivariable regression analysis was used to identify the independent predictors of drop-out. RESULTS: The drop-out rates were 21% at 1 month and 57% at 6 months. Compared with completers, noncompleters were significantly younger in terms of age at first dieting attempt (24.0 ± 10.7 vs. 31.3 ± 11.2 years, P = 0.005), had lower diastolic blood pressure (87.8 ± 9.7 vs. 92.7 ± 11.4 mmHg, P = 0.022), had a lower baseline body fat percentage (38.5 ± 6.4 vs. 41.2 ± 4.4% weight, P = 0.015), and had a lower percentage of early weight loss (-1.8 ± 1.8% vs. -3.1 ± 2.1%, P = 0.035). Moreover, noncompleters significantly differed from completers with regard to type of referral (34.1% vs. 53.3% sent by a physician, P = 0.036) and SCL-90 anger-hostility subscale (0.83 ± 0.72 vs. 0.53 ± 0.51, P = 0.022). A multivariable logistic regression analysis including pre-treatment variables showed that body fat percentage (P = 0.030) and SCL-90 anger-hostility subscale (P = 0.021) were independently associated with attrition. In a multivariable model considering both pre-treatment and treatment-related factors, attrition was found to be independently related to the age at first dieting attempt (P = 0.016) and the achievement of early weight loss (P = 0.029). CONCLUSIONS: Our data confirm that psychopathological tracts, early dieting attempts, and a poor initial treatment response are key independent predictors of drop-out from obesity treatment

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

This paper presents a method for mapping the nitrogen (N) status in a maize field using hyperspectral remote sensing imagery. An airborne survey was conducted with an AISA Eagle hyperspectral sensor over an experimental farm where maize (Zea mays L.) was grown with two N fertilization levels (0 and 100 kg N ha-1) in four replicates. Leaf and canopy field data were collected during the flight. The nitrogen (N) status has been estimated in this work based on the Nitrogen Nutrition Index (NNI) defined as the ratio between the leaf actual N concentration (%Na) of the crop and the minimum N content required for the maximum biomass production (critical N concentration (%Nc)) calculated through the dry mass at the time of the flight (Wflight). The inputs required to calculate the NNI (i.e. %Na and Wflight) have been estimated through regression analyses between field data and remotely sensed vegetation indices. MCARI/MTVI2 (Modified Chlorophyll Absorption Ratio Index / Modified Triangular Vegetation Index 2) showed the best performances in estimating the %Na (R2 = 0.59) and MTVI2 in estimating the Wflight (R2 = 0.80). The %Na and the Wflight were then mapped and used to compute the NNI map over the entire field. The NNI map agreed with the NNI estimated using field data through traditional destructive measurements (R2 = 0.70) confirming the potential of using remotely sensed indices to assess the crop N condition. Finally, a method to derive a pixel based variable rate N fertilization map was proposed as the difference between the actual N content and the optimal N content. We think that the proposed operational methodology is promising for precision farming since it represents an innovative attempt to derive from an aerial hyperspectral image a variable rate N fertilization map based on the actual crop N status.JRC.H.4-Monitoring Agricultural Resource

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

JRC.H.4-Monitoring Agricultural Resource

Forest species mapping using airborne hyperspectral APEX data

Abstract The accurate mapping of forest species is a very important task in relation to the increasing need to better understand the role of the forest ecosystem within environmental dynamics. The objective of this paper is the investigation of the potential of a multi-temporal hyperspectral dataset for the production of a thematic map of the dominant species in the Forêt de Hardt (France). Hyperspectral data were collected in June and September 2013 using the Airborne Prism EXperiment (APEX) sensor, covering the visible, near-infrared and shortwave infrared spectral regions with a spatial resolution of 3 m by 3 m. The map was realized by means of a maximum likelihood supervised classification. The classification was first performed separately on images from June and September and then on the two images together. Class discrimination was performed using as input 3 spectral indices computed as ratios between red edge bands and a blue band for each image. The map was validated using a testing set selected on the basis of a random stratified sampling scheme. Results showed that the algorithm performances improved from an overall accuracy of 59.5% and 48% (for the June and September images, respectively) to an overall accuracy of 74.4%, with the producer's accuracy ranging from 60% to 86% and user's accuracy ranging from 61% to 90%, when both images (June and September) were combined. This study demonstrates that the use of multi-temporal high-resolution images acquired in two different vegetation development stages (i.e., 17 June 2013 and 4 September 2013) allows accurate (overall accuracy 74.4%) local-scale thematic products to be obtained in an operational way

Mapping surface features of an Alpine glacier through multispectral and thermal drone surveys

Glacier surfaces are highly heterogeneous mixtures of ice, snow, light-absorbing impurities and debris material. The spatial and temporal variability of these components affects ice surface characteristics and strongly influences glacier energy and mass balance. Remote sensing offers a unique opportunity to characterize glacier optical and thermal properties, enabling a better understanding of different processes occurring at the glacial surface. In this study, we evaluate the potential of optical and thermal data collected from field and drone platforms to map the abundances of predominant glacier surfaces (i.e., snow, clean ice, melting ice, dark ice, cryoconite, dusty snow and debris cover) on the Zebrù glacier in the Italian Alps. The drone surveys were conducted on the ablation zone of the glacier on 29 and 30 July 2020, corresponding to the middle of the ablation season. We identified very high heterogeneity of surface types dominated by melting ice (30% of the investigated area), dark ice (24%), clean ice (19%) and debris cover (17%). The surface temperature of debris cover was inversely related to debris-cover thickness. This relation is influenced by the petrology of debris cover, suggesting the importance of lithology when considering the role of debris over glaciers. Multispectral and thermal drone surveys can thus provide accurate high-resolution maps of different snow and ice types and their temperature, which are critical elements to better understand the glacier’s energy budget and melt rates