Testing a Theoretical Model Predicting Uncertainty and Depression in Patients Undergoing Renal Replacement Therapy in Korea

PurposeThe purpose of this study was to test hypothesized relationships among experiences of uncertainty, depression, and social support in a sample of subjects undergoing renal replacement therapy in Korea.MethodsPath analysis was used in the sample to examine the relationships among depression and experiences of uncertainty, direct social support, indirect social support, and demographic variables. The size of the sample was 104 patients. Patients received either hemodialysis at one of three clinics or continuous ambulatory peritoneal dialysis.ResultsOne hundred and four subjects participated in the study. It was found that 6.2% of variance in uncertainty was predicted by direct social support (β =− .267), and 46.2% of variance in depression was predicted by three variables: direct social support (β =− .517), economic status (β = .299), and number of admissions (β = .275). Unlike the theoretical model, experiences of uncertainty could not predict depression.ConclusionThe effectiveness of social support in relieving experiences of uncertainty and consequently depression was shown in this study. Moreover, depression in this population could be predicted by direct social support, economic status, and frequency of admission. The study was needed to investigate the relationship between depression and experiences of uncertainty with time covariates, as well as to find the factors that influence depression in patients with chronic renal failure

Toward Data-Driven Digital Therapeutics Analytics: Literature Review and Research Directions

With the advent of Digital Therapeutics (DTx), the development of software as a medical device (SaMD) for mobile and wearable devices has gained significant attention in recent years. Existing DTx evaluations, such as randomized clinical trials, mostly focus on verifying the effectiveness of DTx products. To acquire a deeper understanding of DTx engagement and behavioral adherence, beyond efficacy, a large amount of contextual and interaction data from mobile and wearable devices during field deployment would be required for analysis. In this work, the overall flow of the data-driven DTx analytics is reviewed to help researchers and practitioners to explore DTx datasets, to investigate contextual patterns associated with DTx usage, and to establish the (causal) relationship of DTx engagement and behavioral adherence. This review of the key components of data-driven analytics provides novel research directions in the analysis of mobile sensor and interaction datasets, which helps to iteratively improve the receptivity of existing DTx.Comment: This paper has been accepted by the IEEE/CAA Journal of Automatica Sinic

Locally Activating TrkB Receptor Generates Actin Waves and Specifies Axonal Fate

Actin waves are filamentous actin (F-actin)-rich structures that initiate in the somato-neuritic area and move toward neurite ends. The upstream cues that initiate actin waves are poorly understood. Here, using an optogenetic approach (Opto-cytTrkB), we found that local activation of the TrkB receptor around the neurite end initiates actin waves and triggers neurite elongation. During actin wave generation, locally activated TrkB signaling in the distal neurite was functionally connected with preferentially localized Rac1 and its signaling pathways in the proximal region. Moreover, TrkB activity changed the location of ankyrinG––the master organizer of the axonal initial segment-and initiated the stimulated neurite to acquire axonal characteristics. Taken together, these findings suggest that local Opto-cytTrkB activation switches the fate from minor to major axonal neurite during neuronal polarization by generating actin waves.C. 2019 Elsevier Ltd.11Nsciescopu

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

Considerations on the Endpoint for Future Internet Categories and Subject Descriptors General Terms Design and Mechanism Discussion Keywords

ABSTRACT Where to put the endpoint is a big issue in Future Internet because many problems of the Internet come from the fact that it uses NAP (Network Attachment Point) as the endpoint of the end-toend communication. This paper briefly reviews related works regarding the definition and location of endpoint, propose NID (Network Interface Device) as the appropriate endpoint for Future Internet and argue that NID could be the advisable point from the two essential aspects of the Internet-scalability and functionality. This paper also describes the basic model for the NID-based communication

Clinical Feature of Unilateral Ptosis with Positive Result in Phenylephrine Test (.pdf)

To investigate the etiology and clinical feature of unilateral ptosis in patients with positive result in phenylephrine test (PE)

Enhanced flux of chemically induced hot electrons on a Pt nanowire/Si nanodiode during decomposition of hydrogen peroxide

Identifying the charge transfer at metal-semiconductor interfaces by detecting hot electrons is crucial for understanding the mechanism of catalytic reactions and the development of an engineered catalyst structure. Over the last two decades, the development of catalytic nanodiodes has enabled us to directly measure chemically induced hot electron flux and relate it to catalytic activity. A crucial question is the role of interfacial sites at metal-oxide interfaces in determining catalytic activity and hot electron flux. To address this issue, a new design of catalytic nanodiodes employs nanoscale Pt wires and a semiconducting substrate. Here, we fabricated a novel Schottky nanodiode, a platinum nanowire (Pt NW) deposited Si catalytic nanodiode (Pt NW/Si) that exhibits an increased number of metal-semiconductor interfacial sites (Pt/Si) compared with a Pt film-based Si nanodiode (Pt film/Si). Two types of Pt/Si catalytic nanodiodes were utilized to investigate the electronic properties of the Pt/Si interface by detecting hot electrons and observing reactivity during the H2O2 decomposition reaction in the liquid-solid system. We show that the Pt NWs had higher catalytic activity because of the surface defect sites on the Pt NW surface. We observed a higher chemicurrent yield on the Pt NW/Si nanodiode compared with the Pt film/Si nanodiode, which is associated with the shortened travel length for the hot electrons at the edge of the Pt nanowires and results in a higher transmission probability for hot electron transport through metal-oxide interfaces. This journal i11Nsciescopu