An Internet of Things based bed-egress alerting paradigm using wearable sensors in elderly care environment

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below 1 10 th of a second

Emerging histopathologic markers in early-stage oral tongue cancer : A systematic review and meta-analysis

Although there are many histopathologic prognosticators, grading of early oral tongue squamous cell carcinoma (OTSCC) is still based on morphological cell differentiation which has low prognostic value. Here we summarize the emerging histopathological markers showing powerful prognostic value, but are not included in pathology reports. Using PubMed, Scopus, Ovid Medline, and Web of Science databases, a systematic literature search was preformed to identify early OTSCC studies that investigated the prognostic significance of hematoxylin-eosin-based histopathologic markers. Our meta-analysis showed that tumor budding was associated with overall survival (hazard ratio [HR] 2.32; 95% CI 1.40-3.84; p < 0.01) and disease-specific survival (DSS) (1.89; 95% CI 1.13-3.15; p = 0.02). Worst pattern of invasion was associated with disease-free survival (DFS) (1.95; 95% CI 1.04-3.64; p = 0.04). Tumor-stroma ratio was also associated with DFS (1.75, 95% CI 1.24-2.48; p < 0.01) and DSS (1.69; 95% CI 1.19-2.42; p < 0.01). Tumor budding, worst pattern of invasion, and tumor-stroma ratio have a promising prognostic value in early OTSCC. The evaluation and reporting of these markers is cost-effective and can be incorporated in daily practice.Peer reviewe

MESSAGEix workshop

The aim of the workshop is to help new users of the MESSAGEix modelling framework to get started with their modeling work. The main features of the “framework” are introduced, and the use cases of some features are shown. The user can learn how to build an energy model and how to represent some policy constraints in their energy scenarios. For information about the model, its structure, mathematical formulation and much more, please see the documentation at: https://docs.messageix.org. The different lectures contain the workshop slides, videos as well as tutorials for hands-on examples

Synthesis, in vitro evaluation, and radiolabeling of fluorinated puromycin analogues: potential candidates for PET imaging of protein synthesis

There is currently no ideal radiotracer for imaging protein synthesis rate (PSR) by positron emission tomography (PET). Existing fluorine-18 labelled amino acid-based radiotracers predominantly visualize amino acid transporter processes, and in many cases they are not incorporated into nascent proteins at all. Others are radiolabelled with the short half-life positron emitter carbon-11 which is rather impractical for many PET centers. Based on the puromycin (6) structural manifold, a series of 10 novel derivatives of 6 was prepared via Williamson ether synthesis from a common intermediate. A bioluminescence assay was employed to study their inhibitory action on protein synthesis which identified fluoroethyl analogue (7b) as a lead compound. The fluorine-18 analogue was prepared via nucleophilic substitution of the corresponding tosylate precursor in modest radiochemical yield 2±0.6% and excellent radiochemical purity (>99%) and showed complete stability over 3 h at ambient temperature

Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training

OBJECTIVES Diagnostic accuracy of artificial intelligence (AI) pneumothorax (PTX) detection in chest radiographs (CXR) is limited by the noisy annotation quality of public training data and confounding thoracic tubes (TT). We hypothesize that in-image annotations of the dehiscent visceral pleura for algorithm training boosts algorithm's performance and suppresses confounders. METHODS Our single-center evaluation cohort of 3062 supine CXRs includes 760 PTX-positive cases with radiological annotations of PTX size and inserted TTs. Three step-by-step improved algorithms (differing in algorithm architecture, training data from public datasets/clinical sites, and in-image annotations included in algorithm training) were characterized by area under the receiver operating characteristics (AUROC) in detailed subgroup analyses and referenced to the well-established \textquotedblCheXNet\textquotedbl algorithm. RESULTS Performances of established algorithms exclusively trained on publicly available data without in-image annotations are limited to AUROCs of 0.778 and strongly biased towards TTs that can completely eliminate algorithm's discriminative power in individual subgroups. Contrarily, our final \textquotedblalgorithm 2\textquotedbl which was trained on a lower number of images but additionally with in-image annotations of the dehiscent pleura achieved an overall AUROC of 0.877 for unilateral PTX detection with a significantly reduced TT-related confounding bias. CONCLUSIONS We demonstrated strong limitations of an established PTX-detecting AI algorithm that can be significantly reduced by designing an AI system capable of learning to both classify and localize PTX. Our results are aimed at drawing attention to the necessity of high-quality in-image localization in training data to reduce the risks of unintentionally biasing the training process of pathology-detecting AI algorithms. KEY POINTS • Established pneumothorax-detecting artificial intelligence algorithms trained on public training data are strongly limited and biased by confounding thoracic tubes. • We used high-quality in-image annotated training data to effectively boost algorithm performance and suppress the impact of confounding thoracic tubes. • Based on our results, we hypothesize that even hidden confounders might be effectively addressed by in-image annotations of pathology-related image features

Buttressing staples with cholecyst-derived extracellular matrix (CEM) reinforces staple lines in an ex vivo peristaltic inflation model

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ Springer Science + Business Media, LLC 2008Background - Staple line leakage and bleeding are the most common problems associated with the use of surgical staplers for gastrointestinal resection and anastomotic procedures. These complications can be reduced by reinforcing the staple lines with buttressing materials. The current study reports the potential use of cholecyst-derived extracellular matrix (CEM) in non-crosslinked (NCEM) and crosslinked (XCEM) forms, and compares their mechanical performance with clinically available buttress materials [small intestinal submucosa (SIS) and bovine pericardium (BP)] in an ex vivo small intestine model. Methods - Three crosslinked CEM variants (XCEM0005, XCEM001, and XCEM0033) with different degree of crosslinking were produced. An ex vivo peristaltic inflation model was established. Porcine small intestine segments were stapled on one end, using buttressed or non-buttressed surgical staplers. The opened, non-stapled ends were connected to a peristaltic pump and pressure transducer and sealed. The staple lines were then exposed to increased intraluminal pressure in a peristaltic manner. Both the leak and burst pressures of the test specimens were recorded. Results - The leak pressures observed for non-crosslinked NCEM (137.8 ± 22.3 mmHg), crosslinked XCEM0005 (109.1 ± 14.1 mmHg), XCEM001 (150.1 ± 16.0 mmHg), XCEM0033 (98.8 ± 10.5 mmHg) reinforced staple lines were significantly higher when compared to non-buttressed control (28.3 ± 10.8 mmHg) and SIS (one and four layers) (62.6 ± 11.8 and 57.6 ± 12.3 mmHg, respectively) buttressed staple lines. NCEM and XCEM were comparable to that observed for BP buttressed staple lines (138.8 ± 3.6 mmHg). Only specimens with reinforced staple lines were able to achieve high intraluminal pressures (ruptured at the intestinal mesentery), indicating that buttress reinforcements were able to withstand pressure higher than that of natural tissue (physiological failure). Conclusions - These findings suggest that the use of CEM and XCEM as buttressing materials is associated with reinforced staple lines and increased leak pressures when compared to non-buttressed staple lines. CEM and XCEM were found to perform comparably with clinically available buttress materials in this ex vivo model.Enterprise Irelan

The role of multi-sector climate impacts in achieving water, energy, and land SDGs

IIASA’s Integrated Assessment Model (IAM), MESSAGEix-GLOBIOM is used in various assessments to understand scenarios of socio-economic development within the energy and land systems across scales (global, country, basin). However, the representation of climate impacts and water systems within IAMs until now has been limited. The study goes a step forward on improving the representation of climate impacts and the capability to analyze interactions between population, economic growth, energy, land, and water resources in a dynamic system simultaneously. It uses spatially resolved representation of water systems to retain hydrological information without compromising computational complexity, and simplified water availability and key infrastructure assumptions mapped with the energy and land systems. The results from this study inform the required regional and sectoral investments pathways across mitigation and non-mitigation pathways. The results also highlight the importance of water as a constraint in energy and land-use decisions and implications of global responses to the limited water availability from water resources – renewable water, non-renewable groundwater, desalinated water