Feasibility of electronic patient-reported outcome monitoring and self-management program in aplastic anemia and paroxysmal nocturnal hemoglobinuria-a pilot study (ePRO-AA-PNH).

INTRODUCTION Electronic patient-reported outcomes (ePRO) are increasingly recognized in health care, as they have been demonstrated to improve patient outcomes in cancer, but have been less studied in rare hematological diseases. The aim of this study was to develop and test the feasibility of an ePRO system specifically customized for aplastic anemia (AA) and paroxysmal nocturnal hemoglobinuria (PNH). METHODS After performing a user-centered design evaluation an ePRO system for AA and PNH patients could be customized and the application was tested by patients and their medical teams for 6 months. Symptom-reporting triggered self-management advice for patients and prompts them to contact clinicians in case of severe symptoms, while the medical team received alerts of severe symptoms for patient care. RESULTS All nine included patients showed a high adherence rate to the weekly symptom-reporting (72%) and reported high satisfaction. The system was rated high for usage, comprehensibility, and integration into daily life. Most patients (78%) would continue and all would recommend the application to other AA/PNH patients. Technical performance was rarely a barrier and healthcare providers saw ePRO-AA-PNH as a useful supplement, but the lacking integration into the hospital information system was identified as a major barrier to usage. CONCLUSION An ePRO system customized for AA and PNH was feasible in terms of adherence, satisfaction, and performance, showing a high potential for these rare conditions in terms of data collection and patient guidance. However, the integration into clinical workflows is crucial for further routine use. TRIAL REGISTRATION ClinicalTrials.gov NCT04128943

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

Evaluation of a prostate cancer e-health-tutorial

Hintergrund: Angesichts verschiedener Behandlungsoptionen ist die Information und Therapieentscheidung beim lokalisierten Prostatakarzinom eine Herausforderung. Die digitale Informationstechnologie bietet im Vergleich zu gedruckten Informationen mehr Möglichkeiten, die Information und die Patientenkommunikation bedarfsgerecht zu gestalten. Ziele: Zur Unterstützung der Therapieentscheidung und der Kommunikation mit Patienten ist in der deutschsprachigen Schweiz ein Online-Tutorial in einem systematischen Prozess entwickelt und in einer Pilotstudie getestet worden. In der Evaluation interessierten die Nutzerzufriedenheit, die Erfüllung der Informationsbedürfnisse, die Vorbereitung auf die Therapieentscheidung und deren subjektive Qualität. Material und Methoden: Die Plattform wurde in einem iterativen Prozess mittels Fokusgruppen mit Ärzten und Patienten auf der Grundlage von Informationen aus bestehenden Broschüren entwickelt. Für den Test der Plattform wurden in 8 urologischen Kliniken 87 Patienten zur Teilnahme eingeladen. Die 56 Nutzer wurden 4 Wochen nach dem Login und 3 Monate nach dem Therapieentscheid online befragt, 48 Nutzer füllten beide Befragungen aus. Eingesetzte Instrumente waren die Preparation for Decision Making Scale (PDMS), die Decisional Conflict Scale (DCS) und die Decisional Regret Scale (DRS). Ergebnisse und Diskussion: Die Nutzenden sind mit der Plattform sehr zufrieden und finden ihre Informationsbedürfnisse gut erfüllt. Sie zeigen 3 Monate nach dem Entscheid eine gute Vorbereitung auf die Entscheidung (MW PDMS 75, SD 23) und berichten über niedrigen Entscheidungskonflikt (MW DCS 9.6, SD 11) und kaum Bedauern über die Entscheidung (MW DRS 6.4, SD 9.6). Basierend auf diesen Erkenntnissen kann die Plattform zur weiteren Nutzung empfohlen werden.Background: Due to the multitude of therapy options the treatment decision after diagnosis of a localised prostate cancer is challenging. Compared to printed booklets, web based information technology offers more possibilities to tailor information to patients’ individual needs. Objectives: To support the decision making process as well as the communication with patients we developed an online tutorial in a systematic process in the German speaking part of Switzerland and then tested it in a pilot study. The study investigated users’ satisfaction, the coverage of information needs, the preparation for decision making and the subjective quality of the decision. Materials and methods: Based on already existing information material the online tutorial was developed in an iterative process using focus groups with patients and urologists. For the following evaluation in eight clinics a total of 87 patients were invited to access the platform and participate in the study. From these patients 56 used the tutorial and 48 answered both surveys (the first one 4 weeks after the first login and the second one 3 months after treatment decision). The surveys used the Preparation for Decision Making Scale (PDMS), the Decisional Conflict Scale (DCS), and the Decisional Regret Scale (DRS). Results and Conclusion: Satisfaction with the tutorial is very high among patients with newly diagnosed localized prostate cancer. Users find their information needs sufficiently covered. Three months after the decision they felt that they were well prepared for the decision making (Mean PDMS 75, SD 23), they had low decisional conflict (Mean DCS 9.6, SD 11) and almost no decisional regret (Mean DRS 6.4, SD 9.6). Based on these findings the further use of the tutorial can be recommended

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.</p

A New Soldier-Producing Aphid Species, Pseudoregma baenzigeri, sp. nov., from Northern Thailand

Pseudoregma baenzigeri, sp. nov., is described from northern Thailand. This species forms dense, huge colonies on shoots of the bamboo Dendrocalamus sp., and produces many first-instar, pseudoscorpion-like soldiers. Alate sexuparae were found from the end of September to mid October. Two syrphids, Eupeodes sp. A (allied to E. confrater) and Dideoides chrysotoxoides, and the pyralid Dipha aphidivora were recorded as predators of P. baenzigeri. The aphids were also likely to be eaten by some rodents. The apterous adult, nymphs, soldier and alate sexupara of P. baenzigeri can be distinguished from those of the other congeners by the longer, conical ultimate rostral segment. A tentative key to the species of Pseudoregma living on bamboo is provided

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK

Emotional ratings and skin conductance response to visual, auditory and haptic stimuli

The human emotional reactions to stimuli delivered by different sensory modalities is a topic of interest for many disciplines, from Human-Computer-Interaction to cognitive sciences. Different databases of stimuli eliciting emotional reaction are available, tested on a high number of participants. Interestingly, stimuli within one database are always of the same type. In other words, to date, no data was obtained and compared from distinct types of emotion-eliciting stimuli from the same participant. This makes it difficult to use different databases within the same experiment, limiting the complexity of experiments investigating emotional reactions. Moreover, whereas the stimuli and the participants’ rating to the stimuli are available, physiological reactions of participants to the emotional stimuli are often recorded but not shared. Here, we test stimuli delivered either through a visual, auditory, or haptic modality in a within participant experimental design. We provide the results of our study in the form of a MATLAB structure including basic demographics on the participants, the participant’s self-assessment of his/her emotional state, and his/her physiological reactions (i.e., skin conductance)

Enhanced multiclass SVM with thresholding fusion for speech-based emotion classification

As an essential approach to understanding human interactions, emotion classification is a vital component of behavioral studies as well as being important in the design of context-aware systems. Recent studies have shown that speech contains rich information about emotion, and numerous speech-based emotion classification methods have been proposed. However, the classification performance is still short of what is desired for the algorithms to be used in real systems. We present an emotion classification system using several one-against-all support vector machines with a thresholding fusion mechanism to combine the individual outputs, which provides the functionality to effectively increase the emotion classification accuracy at the expense of rejecting some samples as unclassified. Results show that the proposed system outperforms three state-of-the-art methods and that the thresholding fusion mechanism can effectively improve the emotion classification, which is important for applications that require very high accuracy but do not require that all samples be classified. We evaluate the system performance for several challenging scenarios including speaker-independent tests, tests on noisy speech signals, and tests using non-professional acted recordings, in order to demonstrate the performance of the system and the effectiveness of the thresholding fusion mechanism in real scenarios.Peer ReviewedPreprin

UBe13: An Unconventional Actinide Superconductor

Electrical-resistivity, magnetic-susceptibility, and specific-heat data reveal that UBe13 is superconducting below 0.85 K. Highly anomalous low-temperature electronic properties in both the normal and superconducting states result in an enormous electronic specific-heat coefficient γ=1.1 J/mole K2 and a corresponding magnetic susceptibility χ=1.5×10-2 emu/mole. The superconducting state appears to be extremely stable with an initial slope of the temperature derivative of the critical field (Hc2T)Tc=-257 kOe/K. © 1983 The American Physical Society