scholarly journals Real-time geospatial surveillance of localized emotional stress responses to COVID-19: a proof of concept analysis

2021 ◽  
pp. 102598
Author(s):  
Tamar Edry ◽  
Nason Maani ◽  
Martin Sykora ◽  
Suzanne Elayan ◽  
Yulin Hswen ◽  
...  
Keyword(s):  
Real Time ◽  
Emotional Stress ◽  
Stress Responses ◽  
Concept Analysis ◽  
Proof Of Concept

scholarly journals Real-time prediction of intradialytic relative blood volume: a proof-of-concept for integrated cloud computing infrastructure

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sheetal Chaudhuri ◽  
Hao Han ◽  
Caitlin Monaghan ◽  
John Larkin ◽  
Peter Waguespack ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Blood Volume ◽  
Concept Analysis ◽  
Receiver Operating Curve ◽  
Proof Of Concept ◽  
Dialysis Treatment ◽  
Treatment Data ◽  
Relative Blood Volume ◽  
Intradialytic Symptoms

Abstract Background Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals. Method We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient’s relative blood volume (RBV) decreases at a rate of at least − 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records. Results Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data. Conclusions The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis.

scholarly journals Use of Oxidative Stress Responses to Determine the Efficacy of Inactivation Treatments on Cryptosporidium Oocysts

2021 ◽  
Vol 9 (7) ◽  
pp. 1463
Author(s):  
Tamirat Tefera Temesgen ◽  
Kristoffer Relling Tysnes ◽  
Lucy Jane Robertson
Keyword(s):  
Oxidative Stress ◽  
Stress Responses ◽  
Target Genes ◽  
Cryptosporidium Oocyst ◽  
Drinking Water Treatment ◽  
Proof Of Concept ◽  
Environmental Matrices ◽  
Oocyst Wall ◽  
Novel Approach ◽  
Cryptosporidium Oocysts

Cryptosporidium oocysts are known for being very robust, and their prolonged survival in the environment has resulted in outbreaks of cryptosporidiosis associated with the consumption of contaminated water or food. Although inactivation methods used for drinking water treatment, such as UV irradiation, can inactivate Cryptosporidium oocysts, they are not necessarily suitable for use with other environmental matrices, such as food. In order to identify alternative ways to inactivate Cryptosporidium oocysts, improved methods for viability assessment are needed. Here we describe a proof of concept for a novel approach for determining how effective inactivation treatments are at killing pathogens, such as the parasite Cryptosporidium. RNA sequencing was used to identify potential up-regulated target genes induced by oxidative stress, and a reverse transcription quantitative PCR (RT-qPCR) protocol was developed to assess their up-regulation following exposure to different induction treatments. Accordingly, RT-qPCR protocols targeting thioredoxin and Cryptosporidium oocyst wall protein 7 (COWP7) genes were evaluated on mixtures of viable and inactivated oocysts, and on oocysts subjected to various potential inactivation treatments such as freezing and chlorination. The results from the present proof-of-concept experiments indicate that this could be a useful tool in efforts towards assessing potential technologies for inactivating Cryptosporidium in different environmental matrices. Furthermore, this approach could also be used for similar investigations with other pathogens.

scholarly journals Real-time SARS-CoV-2 diagnostic and variants tracking over multiple candidates using nanopore DNA sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
François Stüder ◽  
Jean-Louis Petit ◽  
Stefan Engelen ◽  
Marco Antonio Mendoza-Parra
Keyword(s):  
Real Time ◽  
Optimal Solution ◽  
Proof Of Concept ◽  
Gene Encoding ◽  
Spike Gene ◽  
Long Period ◽  
The World ◽  
Receptor Recognition ◽  
Nanopore Dna Sequencing ◽  
Novel Coronavirus

AbstractSince December 2019, a novel coronavirus responsible for a severe acute respiratory syndrome (SARS-CoV-2) is accountable for a major pandemic situation. The emergence of the B.1.1.7 strain, as a highly transmissible variant has accelerated the world-wide interest in tracking SARS-CoV-2 variants’ occurrence. Similarly, other extremely infectious variants, were described and further others are expected to be discovered due to the long period of time on which the pandemic situation is lasting. All described SARS-CoV-2 variants present several mutations within the gene encoding the Spike protein, involved in host receptor recognition and entry into the cell. Hence, instead of sequencing the whole viral genome for variants’ tracking, herein we propose to focus on the SPIKE region to increase the number of candidate samples to screen at once; an essential aspect to accelerate diagnostics, but also variants’ emergence/progression surveillance. This proof of concept study accomplishes both at once, population-scale diagnostics and variants' tracking. This strategy relies on (1) the use of the portable MinION DNA sequencer; (2) a DNA barcoding and a SPIKE gene-centered variant’s tracking, increasing the number of candidates per assay; and (3) a real-time diagnostics and variant’s tracking monitoring thanks to our software RETIVAD. This strategy represents an optimal solution for addressing the current needs on SARS-CoV-2 progression surveillance, notably due to its affordable implementation, allowing its implantation even in remote places over the world.

scholarly journals Characterisation of Textile Embedded Electrodes for Use in a Neonatal Smart Mattress Electrocardiography System

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 999
Author(s):  
Henry Dore ◽  
Rodrigo Aviles-Espinosa ◽  
Zhenhua Luo ◽  
Oana Anton ◽  
Heike Rabe ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Heart Rate ◽  
Intensive Care ◽  
High Resolution ◽  
Neonatal Intensive Care Unit ◽  
Real Time ◽  
Neonatal Intensive Care ◽  
Delivery Room ◽  
Proof Of Concept ◽  
Heart Rate Monitoring

Heart rate monitoring is the predominant quantitative health indicator of a newborn in the delivery room. A rapid and accurate heart rate measurement is vital during the first minutes after birth. Clinical recommendations suggest that electrocardiogram (ECG) monitoring should be widely adopted in the neonatal intensive care unit to reduce infant mortality and improve long term health outcomes in births that require intervention. Novel non-contact electrocardiogram sensors can reduce the time from birth to heart rate reading as well as providing unobtrusive and continuous monitoring during intervention. In this work we report the design and development of a solution to provide high resolution, real time electrocardiogram data to the clinicians within the delivery room using non-contact electric potential sensors embedded in a neonatal intensive care unit mattress. A real-time high-resolution electrocardiogram acquisition solution based on a low power embedded system was developed and textile embedded electrodes were fabricated and characterised. Proof of concept tests were carried out on simulated and human cardiac signals, producing electrocardiograms suitable for the calculation of heart rate having an accuracy within ±1 beat per minute using a test ECG signal, ECG recordings from a human volunteer with a correlation coefficient of ~ 87% proved accurate beat to beat morphology reproduction of the waveform without morphological alterations and a time from application to heart rate display below 6 s. This provides evidence that flexible non-contact textile-based electrodes can be embedded in wearable devices for assisting births through heart rate monitoring and serves as a proof of concept for a complete neonate electrocardiogram monitoring system.

scholarly journals Four-dimensional modelling of the mitral valve by real-time 3D transoesophageal echocardiography: proof of concept

2014 ◽  
Vol 20 (2) ◽  
pp. 200-208 ◽  
Author(s):  
Thilo Noack ◽  
Chirojit Mukherjee ◽  
Philipp Kiefer ◽  
Fabian Emrich ◽  
Marcel Vollroth ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Real Time ◽  
Transoesophageal Echocardiography ◽  
Proof Of Concept

Abstract WP239: Real Time Prospective Measurement of aPTT Predicts Paradoxical Embolism in Cryptogenic Stroke

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Bo Song ◽  
Wenjun Deng ◽  
Lindsay Fisher ◽  
I-ying Chou ◽  
Max Oyer ◽  
...  
Keyword(s):  
Real Time ◽  
Protein C ◽  
Cryptogenic Stroke ◽  
Protein S ◽  
Paradoxical Embolism ◽  
Proof Of Concept ◽  
Stroke Patients ◽  
Neurologic Diseases ◽  
Coagulation Testing ◽  
Coagulation Status

Patent foramen ovale (PFO) is an important underlying source of cryptogenic stroke (CS) associated with hematologic procoagulability. However, the association of genetically identified hyperocagulability and paradoxical embolism has been difficult to establish due to retrospective analysis and the limited numbers of of known genetically identified hypercoagulable conditions. In this study, we explored the utility of conventional coagulation status in PFO related stroke, as the patients may harbor genetically unidentified hyperocoagulable conditions. Method: Eligible pts were prospectively recruited in accordance with IRB, and underwent conventional coagulation testing (PT/PTT) testing within 12 hours of stroke. All patients underwent full cryptogenic workup such as MRI/MRA, mobile cardiac outpatient telemetry (>30 days), cardiac echo, and hypercoagulable testing. Results: We screened 4,831 pts admitted with acute neurologic diseases, and recruited 358 eligible acute ischemic stroke pts. 54 (15.1%) pts had CS and 32 pts had PFO related stroke. While there is no difference between PFO-related CS and PFO-unrelated CS on full hypercaogulable screen (protein S, protein C, FVL, PTGM, ATIII, APLAb, LA, hcy), aPTT was statistically significantly shortened in PFO-related stroke patients (PFO CS vs. non-PFO CS: aPTT 27.2±4.1s vs. 29.9±2.3s). ROC curve indicates early shortened aPTT can predict PFO related stroke (sensitivity 70%, specificity 81.5%, p=0.017) (see Figure). Conclusion: We found real time aPTT to be significantly shortened in patients eventually diagnosed with paradoxical embolism related to PFO. While studies in larger pt cohorts accounting for other potential confounders are underway, this proof-of-concept study demonstrates the importance and utility of early conventional coagulation testing in identifying paradoxical embolism. Pts with shortened aPTT may need additional workup for other underlying hypercoagulable conditions.

Establishing a mesh communication backbone for disaster management: proof of concept

2019 ◽  
Author(s):  
Chamnan Kumsap ◽  
Somsarit Sinnung ◽  
Suriyawate Boonthalarath
Keyword(s):  
Data Management ◽  
Real Time ◽  
Disaster Management ◽  
Database Management System ◽  
Proof Of Concept ◽  
Incident Command ◽  
Response Unit ◽  
Disaster Data ◽  
Military Unit ◽  
Quantitative Statistics

"This article addresses the establishment of a mesh communication backbone to facilitate a near real-time and seamless communications channel for disaster data management at its proof of concept stage. A complete function of the data communications is aimed at the input in near real-time of texts, photos, live HD videos of the incident to originate the disaster data management of a military unit responsible for prevention and solving disaster problems and in need of a communication backbone that links data from a Response Unit to an Incident Command Station. The functions of data flow were tested in lab and at fields. Texts encompassing registered name, latitude, longitude, sent time were sent from concurrent 6 responders. Photos and full HD live videos were successfully sent to a laptop Incident Command Station. However, a disaster database management system was needed to store data sent by the Response Unit. Quantitative statistics were suggested for a more substantial proof of concept and subject to further studies."

scholarly journals Ecological mechanisms in cognitive science

2019 ◽  
Vol 29 (5) ◽  
pp. 676-696 ◽  
Author(s):  
Sabrina Golonka ◽  
Andrew D. Wilson
Keyword(s):  
Simple Model ◽  
Circadian Rhythms ◽  
Cognitive Science ◽  
Real Time ◽  
Mechanistic Model ◽  
Mechanistic Explanation ◽  
Perceptual Information ◽  
Proof Of Concept ◽  
Time Interaction ◽  
Ecological Mechanisms

In 2010, Bechtel and Abrahamsen defined and described what it means to be a dynamic causal mechanistic explanatory model. They discussed the development of a mechanistic explanation of circadian rhythms as an exemplar of the process and challenged cognitive science to follow this example. This article takes on that challenge. A mechanistic model is one that accurately represents the real parts and operations of the mechanism being studied. These real components must be identified by an empirical programme that decomposes the system at the correct scale and localises the components in space and time. Psychological behaviour emerges from the nature of our real-time interaction with our environments—here we show that the correct scale to guide decomposition is picked out by the ecological perceptual information that enables that interaction. As proof of concept, we show that a simple model of coordinated rhythmic movement, grounded in information, is a genuine dynamical mechanistic explanation of many key coordination phenomena.

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