Therapeutic capsule endoscopy: Opportunities and challenges

10.1260/2040-2295.2.4.459Journal of Healthcare Engineering24459-47

Sugar beet (Beta vulgaris) guard cells responses to salinity stress: a proteomic analysis

Soil salinity is a major environmental constraint affecting crop growth and threatening global food security. Plants adapt to salinity by optimizing the performance of stomata. Stomata are formed by two guard cells (GCs) that are morphologically and functionally distinct from the other leaf cells. These microscopic sphincters inserted into the wax-covered epidermis of the shoot balance CO2 intake for photosynthetic carbon gain and concomitant water loss. In order to better understand the molecular mechanisms underlying stomatal function under saline conditions, we used proteomics approach to study isolated GCs from the salt-tolerant sugar beet species. Of the 2088 proteins identified in sugar beet GCs, 82 were differentially regulated by salt treatment. According to bioinformatics analysis (GO enrichment analysis and protein classification), these proteins were involved in lipid metabolism, cell wall modification, ATP biosynthesis, and signaling. Among the significant differentially abundant proteins, several proteins classified as “stress proteins” were upregulated, including non-specific lipid transfer protein, chaperone proteins, heat shock proteins, inorganic pyrophosphatase 2, responsible for energized vacuole membrane for ion transportation. Moreover, several antioxidant enzymes (peroxide, superoxidase dismutase) were highly upregulated. Furthermore, cell wall proteins detected in GCs provided some evidence that GC walls were more flexible in response to salt stress. Proteins such as L-ascorbate oxidase that were constitutively high under both control and high salinity conditions may contribute to the ability of sugar beet GCs to adapt to salinity by mitigating salinity-induced oxidative stress

A population biological model with a singular nonlinearity

summary:We consider the existence of positive solutions of the singular nonlinear semipositone problem of the form $$\begin {cases} -{\rm div}(|x|^{-\alpha p}|\nabla u|^{p-2}\nabla u)=|x|^{-(\alpha +1)p+\beta } \Big (a u^{p-1}-f(u)-\dfrac {c}{u^{\gamma }}\Big ), \quad x\in \Omega ,\\ u=0, \quad x\in \partial \Omega , \end {cases}$$ where $\Omega$ is a bounded smooth domain of ${\mathbb R}^N$ with $0\in \Omega$, $1<p<N$, $0\leq \alpha < {(N-p)}/{p}$, $\gamma \in (0,1)$, and $a$, $\beta$, $c$ and $\lambda$ are positive parameters. Here $f\colon [0,\infty )\to {\mathbb R}$ is a continuous function. This model arises in the studies of population biology of one species with $u$ representing the concentration of the species. We discuss the existence of a positive solution when $f$ satisfies certain additional conditions. We use the method of sub-supersolutions to establish our results

Therapeutic targeting in pediatric acute myeloid leukemia with aberrant HOX/MEIS1 expression

Despite advances in the clinical management of childhood acute myeloid leukemia (AML) during the last decades, outcome remains fatal in approximately one third of patients. Primary chemoresistance, relapse and acute and long-term toxicities to conventional myelosuppressive therapies still constitute significant challenges and emphasize the unmet need for effective targeted therapies. Years of scientific efforts have translated into extensive insights on the heterogeneous spectrum of genetics and oncogenic signaling pathways of AML and identified a subset of patients characterized by upregulation of HOXA and HOXB homeobox genes and myeloid ecotropic virus insertion site 1 (MEIS1). Aberrant HOXA/MEIS1 expression is associated with genotypes such as rearrangements in Histone-lysine N-methyltransferase 2A (KMT2A-r), nucleoporin 98 (NUP98-r) and mutated nucleophosmin (NPM1c) that are found in approximately one third of children with AML. AML with upregulated HOXA/MEIS1 shares a number of molecular vulnerabilities amenable to recently developed molecules targeting the assembly of protein complexes or transcriptional regulators. The interaction between the nuclear scaffold protein menin and KMT2A has gained particular interest and constitutes a molecular dependency for maintenance of the HOXA/MEIS1 transcription program. Menin inhibitors disrupt the menin-KMT2A complex in preclinical models of KMT2A-r, NUP98-r and NPM1c acute leukemias and its occupancy at target genes leading to leukemic cell differentiation and apoptosis. Early-phase clinical trials are either ongoing or in development and preliminary data suggests tolerable toxicities and encouraging efficacy of menin inhibitors in adults with relapsed or refractory KMT2A-r and NPM1c AML. The Pediatric Acute Leukemia/European Pediatric Acute Leukemia (PedAL/EUPAL) project is focused to advance and coordinate informative clinical trials with new agents and constitute an ideal framework for testing of menin inhibitors in pediatric study populations. Menin inhibitors in combination with standard chemotherapy or other targeting agents may enhance anti-leukemic effects and constitute rational treatment strategies for select genotypes of childhood AML, and provide enhanced safety to avoid differentiation syndrome. In this review, we discuss the pathophysiological mechanisms in KMT2A-r, NUP98-r and NPM1c AML, emerging molecules targeting the HOXA/MEIS1 transcription program with menin inhibitors as the most prominent examples and future therapeutic implications of these agents in childhood AML.</p

Predicting Body Height in a Pediatric Intensive Care Unit Using Ulnar Length

Objective: To determine if ulnar length obtained by the bedside nurse can be used to estimate patient length. To compare our findings to previous predictive equations of height and ulnar length. To evaluate the performance of predictive equations for height and ulnar length on patients with syndromes that affect height.Design: Retrospective observational study of prospectively collected data.Settings: Multidisciplinary Pediatric Intensive Care Unit in a university teaching hospital.Patients: 1,177 patients, ages 1 month to 23 years. Mean age was 79.7 months (1,3 IQR 19.5, 164.5 months) and 55.4% male.Measurements: Ulnar length was obtained using digital calipers by bedside nurses in PICU as well as height and weight. The electronic health care record was used to extract patient information.Main Results: The predictive equation for height for the entire group is: height (cm) = 0.59*ulnar length (mm) + 13.1 (r2 = 0.93). Bland Altman analysis of the derivation formula applied to the testing group did not show any systematic bias.Conclusions: Our study shows that ulnar length measurements can be used to predict height with a simple linear formula in a PICU setting. Not having specific individuals or specific training for ulnar measurement did not seem to alter the accuracy (r2 = 0.93). The robust nature of the measurement and ease of use may make this an unconventional but reasonable alternative to obtaining height when that cannot be measured directly

DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to SAE Level-3. In this paper, we introduce the Driver Monitoring Dataset (DMD), an extensive dataset which includes real and simulated driving scenarios: distraction, gaze allocation, drowsiness, hands-wheel interaction and context data, in 41 hours of RGB, depth and IR videos from 3 cameras capturing face, body and hands of 37 drivers. A comparison with existing similar datasets is included, which shows the DMD is more extensive, diverse, and multi-purpose. The usage of the DMD is illustrated by extracting a subset of it, the dBehaviourMD dataset, containing 13 distraction activities, prepared to be used in DL training processes. Furthermore, we propose a robust and real-time driver behaviour recognition system targeting a real-world application that can run on cost-efficient CPU-only platforms, based on the dBehaviourMD. Its performance is evaluated with different types of fusion strategies, which all reach enhanced accuracy still providing real-time response.Comment: Accepted to ECCV 2020 workshop - Assistive Computer Vision and Robotic

Relationships between consecutive long-term and mid-term mobility decisions over the life course: a bayesian network approach

Long-term and mid-term mobility decision processes in different life trajectories generate complex dynamics, in which consecutive life events are interrelated and time dependent. This study uses the Bayesian network approach to study the dynamic relationships among residential events, household structure events, employment/education events, and car ownership events. Using retrospective data obtained from a web-based survey in Beijing, China, first structure learning is used to discover the direct and indirect relationships between these mobility decisions. Parameter learning is then applied to describe the conditional probabilities and predict the direct and indirect effects of actions and policies in the resulting network. The results confirm the interdependencies between these long-term and mid-term mobility decisions, and evidence the reactive and proactive behavior of individuals and households in the context of various life events over the course of their lives. In this regard, it is important to note that an increase in household size has a contemporaneous effect on car acquisition in the future; while residential events have a synergic relationship with employment/education events. Moreover, if people’s residential location or workplace/study location will move from an urban district to a suburban or outer suburban district, it has both lagged and concurrent effects on car acquisition

Primary recovery factor as a function of production rate: implications for conventional reservoirs with different drive mechanisms

This study evaluates the dependency of production rate on the recovery of hydrocarbon from conventional reservoirs using MBAL simulator. The results indicated that the recoveries are sensitive to the production rate in almost all hydrocarbon reservoirs. It was also found that the recovery of volumetric gas drive reservoirs is not impacted by the production rate. In fact, any increase in the production rate improves gas recovery in weak and strong water drive reservoirs. Moreover, increasing the production rate in oil reservoirs decreases the recovery with a significant effect observed in the weak water drive reservoirs. The results of this study demonstrate the need for implementing an effective reservoir management in order to obtain a maximum recovery

An evaluation model for the implementation of hospital information system in public hospitals using multi-criteria-decision-making (MCDM) approaches

Background: Hospital Information System (HIS) is implemented to provide high-quality patient care. The aim of this study is to identify significant dimensional factors that influence the hospital decision in adopting the HIS. Methods: This study designs the initial integrated model by taking the three main dimensions in adopting HIS technology. Accordingly, DEMATEL was utilized to test the strength of interdependencies among the dimensions and variables. Then ANP approach is adapted to determining how the factors are weighted and prioritized by professionals and main users working in the Iranian public hospitals, in-volved with the HIS system. Results: The results indicated that "Perceived Technical Competence" is a key factor in the Human dimension. The respondents also believed that "Relative Advantage," "Compatibility" and "Security Concern" of Technology dimension should be further assessed in relation to other factors. With respect to Organization dimension, "Top Management Support" and "Vendor Support" are considered more important than others. Conclusion: Applying the TOE and HOT-fit models as the pillar of our developed model with significant findings add to the growing literature on the factors associated with the adoption of HIS and also shed some light for managers of public hospitals in Iran to success-fully adopt the HIS. © 2018 Ali Aliakbar Esfahani et al