Privacy in crowdsourcing:a systematic review

The advent of crowdsourcing has brought with it multiple privacy challenges. For example, essential monitoring activities, while necessary and unavoidable, also potentially compromise contributor privacy. We conducted an extensive literature review of the research related to the privacy aspects of crowdsourcing. Our investigation revealed interesting gender differences and also differences in terms of individual perceptions. We conclude by suggesting a number of future research directions.</p

MIRRAGGE – Minimum Information Required for Reproducible AGGregation Experiments

Reports on phase separation and amyloid formation for multiple proteins and aggregation-prone peptides are recurrently used to explore the molecular mechanisms associated with several human diseases. The information conveyed by these reports can be used directly in translational investigation, e.g., for the design of better drug screening strategies, or be compiled in databases for benchmarking novel aggregation-predicting algorithms. Given that minute protocol variations determine different outcomes of protein aggregation assays, there is a strong urge for standardized descriptions of the different types of aggregates and the detailed methods used in their production. In an attempt to address this need, we assembled the Minimum Information Required for Reproducible Aggregation Experiments (MIRRAGGE) guidelines, considering first-principles and the established literature on protein self-assembly and aggregation. This consensus information aims to cover the major and subtle determinants of experimental reproducibility while avoiding excessive technical details that are of limited practical interest for non-specialized users. The MIRRAGGE table (template available in Supplementary Information) is useful as a guide for the design of new studies and as a checklist during submission of experimental reports for publication. Full disclosure of relevant information also enables other researchers to reproduce results correctly and facilitates systematic data deposition into curated databases.This work was supported by (i) the European Regional Development Fund (ERDF) through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT—Fundação para a Ciência e a Tecnologia (FCT/MCTES) in the framework of grants POCI-01-0145-FEDER-031173, POCI-01-0145-FEDER-007274, POCI-01-0145-FEDER-031323 (“Institute for Research and Innovation in Health Sciences”), UID/Multi/04046/2013 (BioISI) and PTDC/NEUNMC/2138/2014 (to CMG). SV was funded by the Spanish Ministry of Economy and Competitiveness (BIO2016-78310-R) and by ICREA (ICREA-Academia 2015). ZG and ZB were funded by Slovak research agentures VEGA 02/0145/17, 02/0030/18 and APVV-18-0284. RS was funded by VEGA 02/0163/19. DEO was funded by the Lundbeck Foundation (grant no. R276-2018-671) and the Independent Research Foundation Denmark | Natural Sciences (grant no. 8021-00208B). AP research was supported by UK Dementia Research Institute (RE1 3556) and by ARUK (ARUK-PG2019B-020)

Estimation of the severity of breathlessness in the emergency department: a dyspnea score

BACKGROUND: Dyspnea is a frequent complaint in emergency departments (ED). It has a significant amount of subjective and affective components, therefore the dyspnea scores, based on the patients' rating, can be ambiguous. Our purpose was to develop and validate a simple scoring system to evaluate the severity of dyspnea in emergency care, based on objectively measured parameters. METHODS: We performed a double center, prospective, observational study including 350 patients who were admitted in EDs with dyspnea. We evaluated the patients' subjective feeling about dyspnea and applied our Dyspnea Severity Score (DSS), rating the dyspnea in 7 Dimensions from 0 to 3 points. The DSS was validated using the deterioration of pH, base-excess and lactate levels in the blood gas samples (Objective Classification Scale (OCS) 9 points and 13 points groups). RESULTS: All of the Dimensions correlated closely with the OCS values and with the subjective feeling of the dyspnea. Using multiple linear regression analysis we were able to decrease the numbers of Dimensions from seven to four without causing a significant change in the determination coefficient in any OCS groups. This reduced DSS values (exercise tolerance, cooperation, cyanosis, SpO2 value) showed high sensitivity and specificity to predict the values of OCS groups (the ranges: AUC 0.77-0.99, sensitivity 65-100%, specificity 64-99%). There was a close correlation between the subjective dyspnea scores and the OCS point values (p /=7 points without correction factors) can be useful at the triage or in pre-hospital care