Neurotoxic shellfish poisoning

This is the final version of the article. Available from MDPI via the DOI in this recordNeurotoxic shellfish poisoning (NSP) is caused by consumption of molluscan shellfish contaminated with brevetoxins primarily produced by the dinoflagellate, Karenia brevis. Blooms of K. brevis, called Florida red tide, occur frequently along the Gulf of Mexico. Many shellfish beds in the US (and other nations) are routinely monitored for presence of K. brevis and other brevetoxin-producing organisms. As a result, few NSP cases are reported annually from the US. However, infrequent larger outbreaks do occur. Cases are usually associated with recreationally-harvested shellfish collected during or post red tide blooms. Brevetoxins are neurotoxins which activate voltage-sensitive sodium channels causing sodium influx and nerve membrane depolarization. No fatalities have been reported, but hospitalizations occur. NSP involves a cluster of gastrointestinal and neurological symptoms: nausea and vomiting, paresthesias of the mouth, lips and tongue as well as distal paresthesias, ataxia, slurred speech and dizziness. Neurological symptoms can progress to partial paralysis; respiratory distress has been recorded. Recent research has implicated new species of harmful algal bloom organisms which produce brevetoxins, identified additional marine species which accumulate brevetoxins, and has provided additional information on the toxicity and analysis of brevetoxins. A review of the known epidemiology and recommendations for improved NSP prevention are presented.The funding for this study was provided by the Florida Department of Health and the Centers for Disease Control and Prevention (CDC), as well as the National Science Foundation and National Institute of Environmental Health Sciences Oceans and Human Health Center at the University of Miami Rosenstiel School (NSF 0CE0432368; NIEHS 1 P50 ES12736) and the National Institute of Environmental Health Sciences Red Tide POI (P01 ES 10594)

Geographic Trends of Tobacco-Related Cancers in Cyprus

BACKGROUND: Causal relationships have been previously established between smoking and various cancers. In Cyprus, 39 % of men and 14 % of women reported daily smoking in 2008. The objective of this study was to compare the incidence of tobacco-related cancers to all other cancers by district and rural-urban classification to understand the impact of tobacco in Cyprus. METHODS: Data on lung, urinary bladder, oral, pharyngeal, head/neck, and laryngeal cancers were obtained from the Cyprus Cancer Registry (1998-2008). There were 3,635 patients with tobacco-related cancers and 18,780 with non-tobacco cancers. Univariate analysis comparing tobacco-related cancers and all other cancers were conducted with regards to age at diagnosis, age groups, sex, smoking status, disease stage, and rural/urban status, with a p-value of 0.05 considered significant. Smoking prevalence, lung cancer, and bladder cancer rates of Cyprus were also compared to a number of other European countries. RESULTS: Patients with tobacco-related cancers were older than those with non-tobacco cancers (mean age 67.2 ± 12.4 vs. 62.4 ± 17.1, p \u3c 0.0001). Among those with tobacco-related cancers, 80.1 % were male compared to 45.4 % males with other cancer types. The proportion of ever smokers was higher among males compared to females in urban and rural districts. Sub-districts 41 (Age Adjusted Rate (AAR) 41.9, 95 % CI: 35.7-48.1), 60 (AAR 40.3, 95 % CI: 35.2-45.3), and 50 (AAR 36.3, 95 % CI: 33.8-38.7) had the highest rates of tobacco-related cancers. The overall tobacco-related cancer rate was the highest among males in urban districts (AAR 60.8, 95 % CI: 58.2-63.5). Among tobacco-related cancers, lung cancer had the highest overall AAR (17.9 per 100,000) while head and neck cancer had the lowest overall AAR (5.3 per 100,000). Additionally, even though Cypriot males aged 65-69 years old exhibited higher smoking prevalence than other European countries, the overall lung and bladder cancer rates were lower in Cyprus. CONCLUSION: Despite the high proportion of smokers in Cyprus, cancer rates are low compared to other countries. Future in-depth measurements of relevant risk factors and smoking exposure can help understand this phenomenon and provide insights for cancer prevention

Evaluation of harmful algal bloom outreach activities

This is the final version of the article. Available from MDPI via the link in this record.With an apparent increase of harmful algal blooms (HABs) worldwide, healthcare providers, public health personnel and coastal managers are struggling to provide scientifically-based appropriately-targeted HAB outreach and education. Since 1998, the Florida Poison Information Center-Miami, with its 24 hour/365 day/year free Aquatic Toxins Hotline (1-888-232-8635) available in several languages, has received over 25,000 HAB-related calls. As part of HAB surveillance, all possible cases of HAB-related illness among callers are reported to the Florida Health Department. This pilot study evaluated an automated call processing menu system that allows callers to access bilingual HAB information, and to speak directly with a trained Poison Information Specialist. The majority (68%) of callers reported satisfaction with the information, and many provided specific suggestions for improvement. This pilot study, the first known evaluation of use and satisfaction with HAB educational outreach materials, demonstrated that the automated system provided useful HAB-related information for the majority of callers, and decreased the routine informational call workload for the Poison Information Specialists, allowing them to focus on callers needing immediate assistance and their healthcare providers. These results will lead to improvement of this valuable HAB outreach, education and surveillance tool. Formal evaluation is recommended for future HAB outreach and educational materials.The funding for this study was provided by the Florida Department of Health and the Centers for Disease Control and Prevention (CDC) and Florida Harmful Algal Bloom Taskforce, as well as the National Science Foundation and National Institute of Environmental Health Sciences Oceans and Human Health Center at the University of Miami Rosenstiel School (NSF 0CE0432368; NIEHS 1 P50 ES12736), the former National Institute of Environmental Health Sciences Marine and Freshwater Biomedical Sciences Center at the University of Miami Rosenstiel School (NIEHS P30ES05705), and the National Institute of Environmental Health Sciences Red Tide POI (P01 ES 10594)

Post-Lie Algebras, Factorization Theorems and Isospectral-Flows

In these notes we review and further explore the Lie enveloping algebra of a post-Lie algebra. From a Hopf algebra point of view, one of the central results, which will be recalled in detail, is the existence of a second Hopf algebra structure. By comparing group-like elements in suitable completions of these two Hopf algebras, we derive a particular map which we dub post-Lie Magnus expansion. These results are then considered in the case of Semenov-Tian-Shansky's double Lie algebra, where a post-Lie algebra is defined in terms of solutions of modified classical Yang-Baxter equation. In this context, we prove a factorization theorem for group-like elements. An explicit exponential solution of the corresponding Lie bracket flow is presented, which is based on the aforementioned post-Lie Magnus expansion.Comment: 49 pages, no-figures, review articl

Probabilistic inference for determining options in reinforcement learning

Tasks that require many sequential decisions or complex solutions are hard to solve using conventional reinforcement learning algorithms. Based on the semi Markov decision process setting (SMDP) and the option framework, we propose a model which aims to alleviate these concerns. Instead of learning a single monolithic policy, the agent learns a set of simpler sub-policies as well as the initiation and termination probabilities for each of those sub-policies. While existing option learning algorithms frequently require manual specification of components such as the sub-policies, we present an algorithm which infers all relevant components of the option framework from data. Furthermore, the proposed approach is based on parametric option representations and works well in combination with current policy search methods, which are particularly well suited for continuous real-world tasks. We present results on SMDPs with discrete as well as continuous state-action spaces. The results show that the presented algorithm can combine simple sub-policies to solve complex tasks and can improve learning performance on simpler tasks

Determining the Cosmic Distance Scale from Interferometric Measurements of the Sunyaev-Zel'dovich Effect

We determine the distances to 18 galaxy clusters with redshifts ranging from z~0.14 to z~0.78 from a maximum likelihood joint analysis of 30 GHz interferometric Sunyaev-Zel'dovich effect (SZE) and X-ray observations. We model the intracluster medium (ICM) using a spherical isothermal beta model. We quantify the statistical and systematic uncertainties inherent to these direct distance measurements, and we determine constraints on the Hubble parameter for three different cosmologies. These distances imply a Hubble constant of 60 (+4, -4) (+13, -18) km s-1 Mpc-1 for an Omega_M = 0.3, Omega_Lambda = 0.7 cosmology, where the uncertainties correspond to statistical followed by systematic at 68% confidence. With a sample of 18 clusters, systematic uncertainties clearly dominate. The systematics are observationally approachable and will be addressed in the coming years through the current generation of X-ray satellites (Chandra & XMM-Newton) and radio observatories (OVRO, BIMA, & VLA). Analysis of high redshift clusters detected in future SZE and X-ray surveys will allow a determination of the geometry of the universe from SZE determined distances.Comment: ApJ Submitted; 40 pages, 9 figures (fig 3 B&W for size constraint), 13 tables, uses emulateapj5 styl

Bidirectional Psychoneuroimmune Interactions in the Early Postpartum Period Influence Risk of Postpartum Depression

More than 500,000 U.S. women develop postpartum depression (PPD) annually. Although psychosocial risks are known, the underlying biology remains unclear. Dysregulation of the immune inflammatory response and the hypothalamic–pituitary–adrenal (HPA) axis are associated with depression in other populations. While significant research on the contribution of these systems to the development of PPD has been conducted, results have been inconclusive. This is partly because few studies have focused on whether disruption in the bidirectional and dynamic interaction between the inflammatory response and the HPA axis together influence PPD. In this study, we tested the hypothesis that disruption in the inflammatory-HPA axis bidirectional relationship would increase the risk of PPD. Plasma pro- and anti-inflammatory cytokines were measured in women during the 3rd trimester of pregnancy and on Days 7 and 14, and Months 1, 2, 3, and 6 after childbirth. Saliva was collected 5 times the day preceding blood draws for determination of cortisol area under the curve (AUC) and depressive symptoms were measured using the Edinburgh Postpartum Depression Survey (EPDS). Of the 152 women who completed the EPDS, 18% were depressed according to EDPS criteria within the 6 months postpartum. Cortisol AUC was higher in symptomatic women on Day 14 (p = .017). To consider the combined effects of cytokines and cortisol on predicting symptoms of PPD, a multiple logistic regression model was developed that included predictors identified in bivariate analyses to have an effect on depressive symptoms. Results indicated that family history of depression, day 14 cortisol AUC, and the day 14 IL8/IL10 ratio were significant predictors of PPD symptoms. One unit increase each in the IL8/IL10 ratio and cortisol AUC resulted in 1.50 (p = 0.06) and 2.16 (p = 0.02) fold increases respectively in the development of PPD. Overall, this model correctly classified 84.2% of individuals in their respective groups. Findings suggest that variability in the complex interaction between the inflammatory response and the HPA axis influence the risk of PPD

Disease surveillance using a hidden Markov model

<p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

Attitudes About COVID-19 and Health (ATTACH): Online Survey and Mixed Methods Study

Background: Behavioral mitigation strategies to slow the spread of COVID-19 have resulted in sweeping lifestyle changes, with short- and long-term psychological, well-being, and quality of life implications. The Attitudes About COVID-19 and Health (ATTACH) study focuses on understanding attitudes and beliefs while considering the impact on mental and physical health and the influence of broader demographic and geographic factors on attitudes, beliefs, and mental health burden. / Objective: In this assessment of our first wave of data collection, we provide baseline cohort description of the ATTACH study participants in the United Kingdom, the United States, and Mexico. Additionally, we assess responses to daily poll questions related to COVID-19 and conduct a cross-sectional analysis of baseline assessments collected in the UK between June 26 and October 31, 2020. / Methods: The ATTACH study uses smartphone app technology and online survey data collection. Participants completed poll questions related to COVID-19 2 times daily and a monthly survey assessing mental health, social isolation, physical health, and quality of life. Poll question responses were graphed using 95% Clopper–Pearson (exact) tests with 95% CIs. Pearson correlations, hierarchical linear regression analyses, and generalized linear models assessed relationships, predictors of self-reported outcomes, and group differences, respectively. / Results: By October 31, 2020, 1405, 80, and 90 participants had consented to participate in the UK, United States, and Mexico, respectively. Descriptive data for the UK daily poll questions indicated that participants generally followed social distancing measures, but worry and negative impacts on families increased as the pandemic progressed. Although participants generally reported feeling that the reasons for current measures had been made clear, there was low trust that the government was doing everything in its power to meet public needs. In the UK, 1282 participants also completed a monthly survey (94.99% [1326/1396] White, 72.22% [1014/1404] female, and 20.12% [277/1377] key or essential workers); 18.88% (242/1282) of UK participants reported a preexisting mental health disorder, 31.36% (402/1282) reported a preexisting chronic medical illness, and 35.11% (493/1404) were aged over 65; 57.72% (740/1282) of participants reported being more sedentary since the pandemic began, and 41.89% (537/1282) reported reduced access to medical care. Those with poorer mental health outcomes lived in more deprived neighborhoods, in larger households (Ps<.05), had more preexisting mental health disorders and medical conditions, and were younger than 65 years (all Ps<.001). / Conclusions: Communities who have been exposed to additional harm during the COVID-19 pandemic were experiencing worse mental outcomes. Factors including having a medical condition, or living in a deprived neighborhood or larger household were associated with heightened risk. Future longitudinal studies should investigate the link between COVID-19 exposure, mental health, and sociodemographic and residential characteristics