Abnormal phase transitions for tetragonal (1-x)Pb(Mg[sub ⅓]Nb[sub ⅔])O₃-xPbTiO₃ single crystals at low temperature

2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Public health responses to influenza in care homes: a questionnaire-based study of local Health Protection Units.

BACKGROUND: Influenza virus infection poses a major threat to the elderly people in residential care. We sought to describe the extent to which local public health services in England were positioned to detect and respond effectively to influenza-like illness (ILI) in nursing homes. METHODS: A questionnaire-based survey was conducted in all 34 Health Protection Units (HPUs) regarding the 2004-05 influenza season. RESULTS: Of the 20 responses, half reported 24 outbreaks of ILI in care homes. The mean resident population attack rate was 41% (range 15-79) with 31 deaths. Staff ILI occurred in 23 of 24 outbreaks. Seven of 20 HPUs stated that a local policy for the management of ILI in nursing homes was in place, with only four specifying the use of neuraminidase inhibitors (NI) for treatment of cases and prophylaxis of residents. In the outbreaks reported, NIs were used for treatment and prophylaxis, respectively, in only 46 and 54% of instances. CONCLUSIONS: Given the availability of effective interventions for treatment and prophylaxis, there is potential to prevent substantial morbidity and mortality from influenza in at-risk populations. This study suggests that challenges remain in the effective response to influenza outbreaks in care homes and that there are wide variations in practice at local level

Rewarding Subjective Effects of the NMDAR Antagonist Nitrous Oxide (Laughing Gas) Are Moderated by Impulsivity and Depressive Symptoms in Healthy Volunteers

BACKGROUND: Nitrous oxide (N2O) is an anaesthetic gas with both therapeutic and abuse potential. As an NMDAR antagonist, its effects are expected to resemble those of the prototypical NMDAR antagonist, ketamine. Here, we examine the subjective rewarding effects of N2O using measures previously employed in studies of ketamine. We also test for moderation of these effects by bipolar phenotype, depressive symptoms, and impulsivity. METHODS: Healthy volunteers were randomised to either 50% N2O (n=40) or medical air (n=40). Self-reported rewarding (liking and wanting), and alcohol-like effects were assessed pre-, peri- and post-inhalation. RESULTS: Effect sizes for the various rewarding/alcohol-like effects of N2O were generally similar to those reported in studies of moderate-dose ketamine. Impulsivity moderated the subjective reinforcing (liking) effects of inhaled gas, while depressive symptoms moderated motivational (wanting [more]) effects. However, depression and impulsivity had opposite directional influences, such that higher impulsivity was associated with higher N2O-liking, and higher depression, with lower N2O-wanting. CONCLUSIONS: To the extent that static (versus longitudinal) subjective rewarding effects are a reliable indicator of future problematic drug use, our findings suggests that impulsivity and depression may respectively predispose and protect against N2O abuse. Future studies should examine if these moderators are relevant for other NMDAR antagonists, including ketamine, and novel ketamine-like therapeutics and recreational drugs. Similarities between moderate-dose N2O and moderate-dose ketamine in the intensity of certain subjective effects suggest that N2O may, at least partially, substitute for ketamine as a safe and easily-implemented experimental tool for probing reward-related NMDAR function and dysfunction in humans

Numerical Modeling of Fluid Flow in Solid Tumors

A mathematical model of interstitial fluid flow is developed, based on the application of the governing equations for fluid flow, i.e., the conservation laws for mass and momentum, to physiological systems containing solid tumors. The discretized form of the governing equations, with appropriate boundary conditions, is developed for a predefined tumor geometry. The interstitial fluid pressure and velocity are calculated using a numerical method, element based finite volume. Simulations of interstitial fluid transport in a homogeneous solid tumor demonstrate that, in a uniformly perfused tumor, i.e., one with no necrotic region, because of the interstitial pressure distribution, the distribution of drug particles is non-uniform. Pressure distribution for different values of necrotic radii is examined and two new parameters, the critical tumor radius and critical necrotic radius, are defined. Simulation results show that: 1) tumor radii have a critical size. Below this size, the maximum interstitial fluid pressure is less than what is generally considered to be effective pressure (a parameter determined by vascular pressure, plasma osmotic pressure, and interstitial osmotic pressure). Above this size, the maximum interstitial fluid pressure is equal to effective pressure. As a consequence, drugs transport to the center of smaller tumors is much easier than transport to the center of a tumor whose radius is greater than the critical tumor radius; 2) there is a critical necrotic radius, below which the interstitial fluid pressure at the tumor center is at its maximum value. If the tumor radius is greater than the critical tumor radius, this maximum pressure is equal to effective pressure. Above this critical necrotic radius, the interstitial fluid pressure at the tumor center is below effective pressure. In specific ranges of these critical sizes, drug amount and therefore therapeutic effects are higher because the opposing force, interstitial fluid pressure, is low in these ranges

An analytical model for chemical diffusion in layered contaminated sediment systems with bioreactive caps

An analytical model for contaminant transport in multilayered capped contaminated sediments including the degradation of organic contaminant is presented. The effect of benthic boundary layer was treated as a Robin‐type boundary condition. The results of the proposed analytical model agree well with experimental data. The biodegradation of contaminant in bioturbation layer shows a significant influence on the flux at the surface of system. The maximum flux for the case with t1/2,bio = 0.07 year can be 4.5 times less than that of the case without considering the effect of biodegradation. The thickness of bioturbation layer has a significant effect on the performance of the capped contaminated sediment. The maximum flux for the case with lbio = 15 cm can be 17 times larger than that of the case without bioturbation layer. This may be because the effective diffusion coefficient of sand cap can be 28 times lower than Dbio. The mass transfer coefficient should be considered for the design of the capping system as the contaminant concentration at the top of system for the case with kbl = 2.5 × 10−5 cm/s can be 13 times greater than that of the case with kbl = 10−4 cm/s. The proposed analytical model can be used for verification of complicated numerical methods, evaluation of experimental data, and design of the capping contaminated sediment systems with reactive cap layers

Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers.

Objective: This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis. Method: We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity. Results: The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04). Conclusion: The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592

MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response

Predicting clinical outcome is remarkably important but challenging. Research efforts have been paid on seeking significant biomarkers associated with the therapy response or/and patient survival. However, these biomarkers are generally costly and invasive, and possibly dissatifactory for novel therapy. On the other hand, multi-modal, heterogeneous, unaligned temporal data is continuously generated in clinical practice. This paper aims at a unified deep learning approach to predict patient prognosis and therapy response, with easily accessible data, e.g., radiographics, laboratory and clinical information. Prior arts focus on modeling single data modality, or ignore the temporal changes. Importantly, the clinical time series is asynchronous in practice, i.e., recorded with irregular intervals. In this study, we formalize the prognosis modeling as a multi-modal asynchronous time series classification task, and propose a MIA-Prognosis framework with Measurement, Intervention and Assessment (MIA) information to predict therapy response, where a Simple Temporal Attention (SimTA) module is developed to process the asynchronous time series. Experiments on synthetic dataset validate the superiory of SimTA over standard RNN-based approaches. Furthermore, we experiment the proposed method on an in-house, retrospective dataset of real-world non-small cell lung cancer patients under anti-PD-1 immunotherapy. The proposed method achieves promising performance on predicting the immunotherapy response. Notably, our predictive model could further stratify low-risk and high-risk patients in terms of long-term survival.Comment: MICCAI 2020 (Early Accepted; Student Travel Award

A Novel Xenograft Model in Zebrafish for High-Resolution Investigating Dynamics of Neovascularization in Tumors

Tumor neovascularization is a highly complex process including multiple steps. Understanding this process, especially the initial stage, has been limited by the difficulties of real-time visualizing the neovascularization embedded in tumor tissues in living animal models. In the present study, we have established a xenograft model in zebrafish by implanting mammalian tumor cells into the perivitelline space of 48 hours old Tg(Flk1:EGFP) transgenic zebrafish embryos. With this model, we dynamically visualized the process of tumor neovascularization, with unprecedented high-resolution, including new sprouts from the host vessels and the origination from VEGFR2+ individual endothelial cells. Moreover, we quantified their contributions during the formation of vascular network in tumor. Real-time observations revealed that angiogenic sprouts in tumors preferred to connect each other to form endothelial loops, and more and more endothelial loops accumulated into the irregular and chaotic vascular network. The over-expression of VEGF165 in tumor cells significantly affected the vascularization in xenografts, not only the number and size of neo-vessels but the abnormalities of tumor vascular architecture. The specific inhibitor of VEGFR2, SU5416, significantly inhibited the vascularization and the growth of melanoma xenografts, but had little affects to normal vessels in zebrafish. Thus, this zebrafish/tumor xenograft model not only provides a unique window to investigate the earliest events of tumoral neoangiogenesis, but is sensitive to be used as an experimental platform to rapidly and visually evaluate functions of angiogenic-related genes. Finally, it also offers an efficient and cost-effective means for the rapid evaluation of anti-angiogenic chemicals

A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard