Nonparametric Bayesian grouping methods for spatial time-series data

We describe an approach for identifying groups of dynamically similar locations in spatial time-series data based on a simple Markov transition model. We give maximum-likelihood, empirical Bayes, and fully Bayesian formulations of the model, and describe exhaustive, greedy, and MCMC-based inference methods. The approach has been employed successfully in several studies to reveal meaningful relationships between environmental patterns and disease dynamics.Comment: 11 pages, no figure

Data mining approach to estimate the duration of drug therapy from longitudinal electronic medical records

Background: Electronic Medical Records (EMRs) from primary/ ambulatory care systems present a new and promising source of information for conducting clinical and translational research. Objectives: To address the methodological and computational challenges in order to extract reliable medication information from raw data which is often complex, incomplete and erroneous. To assess whether the use of specific chaining fields of medication information may additionally improve the data quality. Methods: Guided by a range of challenges associated with missing and internally inconsistent data, we introduce two methods for the robust extraction of patient-level medication data. First method relies on chaining fields to estimate duration of treatment (“chaining”), while second disregards chaining fields and relies on the chronology of records (“continuous”). Centricity EMR database was used to estimate treatment duration with both methods for two widely prescribed drugs among type 2 diabetes patients: insulin and glucagon-like peptide-1 receptor agonists. Results: At individual patient level the “chaining” approach could identify the treatment alterations longitudinally and produced more robust estimates of treatment duration for individual drugs, while the “continuous” method was unable to capture that dynamics. At population level, both methods produced similar estimates of average treatment duration, however, notable differences were observed at individual-patient level. Conclusion: The proposed algorithms explicitly identify and handle longitudinal erroneous or missing entries and estimate treatment duration with specific drug(s) of interest, which makes them a valuable tool for future EMR based clinical and pharmaco-epidemiological studies. To improve accuracy of real-world based studies, implementing chaining fields of medication information is recommended.Publisher PDFPeer reviewe

The GEOTRACES Intermediate Data Product 2014

The GEOTRACES Intermediate Data Product 2014 (IDP2014) is the first publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2013. It consists of two parts: (1) a compilation of digital data for more than 200 trace elements and isotopes (TEls) as well as classical hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing a strongly inter-linked on-line atlas including more than 300 section plots and 90 animated 3D scenes. The IDP2014 covers the Atlantic, Arctic, and Indian oceans, exhibiting highest data density in the Atlantic. The TEI data in the IDP2014 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at cross-over stations. The digital data are provided in several formats, including ASCII spreadsheet, Excel spreadsheet, netCDF, and Ocean Data View collection. In addition to the actual data values the IDP2014 also contains data quality flags and 1-sigma data error values where available. Quality flags and error values are useful for data filtering. Metadata about data originators, analytical methods and original publications related to the data are linked to the data in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2014 data providing section plots and a new kind of animated 3D scenes. The basin-wide 3D scenes allow for viewing of data from many cruises at the same time, thereby providing quick overviews of large-scale tracer distributions. In addition, the 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of observed tracer plumes, as well as for making inferences about controlling processes

\u3cem\u3eIn Situ\u3c/em\u3e Nanomechanical Testing in Focused Ion Beam and Scanning Electron Microscopes

The recent interest in size-dependent deformation of micro- and nanoscale materials has paralleled both technological miniaturization and advancements in imaging and small-scale mechanical testing methods. Here we describe a quantitative in situ nanomechanical testing approach adapted to a dualbeam focused ion beam and scanning electron microscope. A transducer based on a three-plate capacitor system is used for high-fidelity force and displacement measurements. Specimen manipulation, transfer, and alignment are performed using a manipulator, independently controlled positioners, and the focused ion beam. Gripping of specimens is achieved using electron-beam assisted Pt-organic deposition. Local strain measurements are obtained using digital image correlation of electron images taken during testing. Examples showing results for tensile testing of single-crystalline metallic nanowires and compression of nanoporous Au pillars will be presented in the context of size effects on mechanical behavior and highlight some of the challenges of conducting nanomechanical testing in vacuum environments

Assessing long term effects of compost fertilization on soil fertility and nitrogen mineralization rate

Background: Fertilization with organic waste compost can close the nutrient cycles between urban and rural environments. However, its effect on yield and soil fertility must be investigated. Aim: This study investigated the long-term effect of compost on soil nutrient and potentially toxic elements (PTEs) concentration, nutrient budgets, and nitrogen (N) mineralization and efficiency. Methods: After 21 years of annual compost application (100/400 kg N ha–1 year–1 [100BC/400BC]) alone and combined with mineral fertilization, soil was analyzed for pH, organic carbon (SOC), nutrient (total N and P, Nmin, extractable CAL-P, CAL-K, and Mg), and PTE (Cu, Ni, Zn) concentrations. Yields were recorded and nutrient/PTE budgets and apparent netmineralization (ANM, only 2019) were calculated. Results:Nefficiency was the highest in maize and formineral fertilization. Compost application led to lower N efficiencies, but increased ANM, SOC, pH, and soil N, and surpluses of N, P, and all PTEs. Higher PTE concentrations were only found in 400BC for Cu. Nutrient budgets correlatedwith soil nutrient concentration. A surplus of 16.1 kg P ha–1 year–1 and 19.5 kgKha–1 year–1 resulted in 1mg kg–1 increase in CAL-P and CAL-K over 21 years. Conclusion: Compost application supplies nutrients to crops with a minor risk of soilaccumulation of PTEs. However, the nutrient stoichiometry provided by compost does not match crop offtakes causing imbalances. Synchronization of compost N mineralization and plant N demand does not match and limits the yield effect. In winter wheat only 65–70% of Nmineralization occurred during the growth period

The Importance of Bottom-Up Approaches to International Cooperation in Ocean Science: The Iron Story

In the past decade, several international efforts developed to address urgent societal issues have been identified through, for example, the United Nations 2030 Agenda for Sustainable Development and its associated 17 Sustainable Development Goals and the United Nations Decade of Ocean Science for Sustainable Development (2021–2030). These worthy efforts will bring ocean science research to bear on problems that need attention in the short term. Yet, there is also a continuing need at the international level to support fundamental ocean science and solve methodological issues over the long term. While knowledge needs to be created before it can be applied, national and international science strategy documents often do not mention the need to maintain the health of the basic science enterprise. We argue that international organizations designed to create knowledge must be maintained and strengthened to inform decisions on how to allocate funding for generating knowledge about the ocean versus solving ocean problems. We use the ocean iron cycle as an example of the benefits of using such a “bottom-up” approach to knowledge generation

A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is however critical both for basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brain-wide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brain-wide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open access data repository; compatibility with existing resources, and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.Comment: 41 page

Fogarty International Center collaborative networks in infectious disease modeling:Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the ‘big data’ revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications. Keywords: Infectious diseases, Transmission models, Computational models, Pathogen evolution, Capacity building, Emerging disease threats, Influenza, Control, Polic

Analysis of meniscal degeneration and meniscal gene expression

<p>Abstract</p> <p>Background</p> <p>Menisci play a vital role in load transmission, shock absorption and joint stability. There is increasing evidence suggesting that OA menisci may not merely be bystanders in the disease process of OA. This study sought: 1) to determine the prevalence of meniscal degeneration in OA patients, and 2) to examine gene expression in OA meniscal cells compared to normal meniscal cells.</p> <p>Methods</p> <p>Studies were approved by our human subjects Institutional Review Board. Menisci and articular cartilage were collected during joint replacement surgery for OA patients and lower limb amputation surgery for osteosarcoma patients (normal control specimens), and graded. Meniscal cells were prepared from these meniscal tissues and expanded in monolayer culture. Differential gene expression in OA meniscal cells and normal meniscal cells was examined using Affymetrix microarray and real time RT-PCR.</p> <p>Results</p> <p>The grades of meniscal degeneration correlated with the grades of articular cartilage degeneration (r = 0.672; P < 0.0001). Many of the genes classified in the biological processes of immune response, inflammatory response, biomineral formation and cell proliferation, including major histocompatibility complex, class II, DP alpha 1 (<it>HLA-DPA1</it>), integrin, beta 2 (<it>ITGB2</it>), ectonucleotide pyrophosphatase/phosphodiesterase 1 (<it>ENPP1</it>), ankylosis, progressive homolog (<it>ANKH</it>) and fibroblast growth factor 7 (<it>FGF7</it>), were expressed at significantly higher levels in OA meniscal cells compared to normal meniscal cells. Importantly, many of the genes that have been shown to be differentially expressed in other OA cell types/tissues, including ADAM metallopeptidase with thrombospondin type 1 motif 5 (<it>ADAMTS5</it>) and prostaglandin E synthase (<it>PTGES</it>), were found to be expressed at significantly higher levels in OA meniscal cells. This consistency suggests that many of the genes detected in our study are disease-specific.</p> <p>Conclusion</p> <p>Our findings suggest that OA is a whole joint disease. Meniscal cells may play an active role in the development of OA. Investigation of the gene expression profiles of OA meniscal cells may reveal new therapeutic targets for OA therapy and also may uncover novel disease markers for early diagnosis of OA.</p

Platelets Alter Gene Expression Profile in Human Brain Endothelial Cells in an In Vitro Model of Cerebral Malaria

Platelet adhesion to the brain microvasculature has been associated with cerebral malaria (CM) in humans, suggesting that platelets play a role in the pathogenesis of this syndrome. In vitro co-cultures have shown that platelets can act as a bridge between Plasmodium falciparum-infected red blood cells (pRBC) and human brain microvascular endothelial cells (HBEC) and potentiate HBEC apoptosis. Using cDNA microarray technology, we analyzed transcriptional changes of HBEC in response to platelets in the presence or the absence of tumor necrosis factor (TNF) and pRBC, which have been reported to alter gene expression in endothelial cells. Using a rigorous statistical approach with multiple test corrections, we showed a significant effect of platelets on gene expression in HBEC. We also detected a strong effect of TNF, whereas there was no transcriptional change induced specifically by pRBC. Nevertheless, a global ANOVA and a two-way ANOVA suggested that pRBC acted in interaction with platelets and TNF to alter gene expression in HBEC. The expression of selected genes was validated by RT-qPCR. The analysis of gene functional annotation indicated that platelets induce the expression of genes involved in inflammation and apoptosis, such as genes involved in chemokine-, TREM1-, cytokine-, IL10-, TGFβ-, death-receptor-, and apoptosis-signaling. Overall, our results support the hypothesis that platelets play a pathogenic role in CM