Modifying the microstructure and morphology of film surface layers by manipulating chemical vapor deposition reactor conditions

Two spatial dimension front tracking simulations have been performed to study the growth of polycrystalline, faceted films from randomly oriented nuclei. We present strategies to optimize the microstructure, morphology, and texture of thin films during chemical vapor deposition. In particular, we examine how changes in reactor conditions can be used to modify the mean grain size, surface roughness, crystallographic texture, and growth zones. Changing growth conditions once the target bulk film structure is established can be used to establish a thin surface region with much different structural characteristics. Analytical models are provided to aid in choosing the appropriate changes in reactor conditions and surface layer thickness to achieve optimal properties. © 2001 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70359/2/JAPIAU-89-9-4857-1.pd

Spatio-Temporal Magnitude and Direction of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The number of outbreaks of HPAI-H5N1 reported by Bangladesh from 2007 through 2011 placed the country among the highest reported numbers worldwide. However, so far, the understanding of the epidemic progression, direction, intensity, persistence and risk variation of HPAI-H5N1 outbreaks over space and time in Bangladesh remains limited. METHODOLOGY/PRINCIPAL FINDINGS: To determine the magnitude and spatial pattern of the highly pathogenic avian influenza A subtype H5N1 virus outbreaks over space and time in poultry from 2007 to 2009 in Bangladesh, we applied descriptive and analytical spatial statistics. Temporal distribution of the outbreaks revealed three independent waves of outbreaks that were clustered during winter and spring. The descriptive analyses revealed that the magnitude of the second wave was the highest as compared to the first and third waves. Exploratory mapping of the infected flocks revealed that the highest intensity and magnitude of the outbreaks was systematic and persistent in an oblique line that connects south-east to north-west through the central part of the country. The line follows the Brahmaputra-Meghna river system, the junction between Central Asian and East Asian flyways, and the major poultry trading route in Bangladesh. Moreover, several important migratory bird areas were identified along the line. Geostatistical analysis revealed significant latitudinal directions of outbreak progressions that have similarity to the detected line of intensity and magnitude. CONCLUSION/SIGNIFICANCE: The line of magnitude and direction indicate the necessity of mobilizing maximum resources on this line to strengthen the existing surveillance

Involvement of mTOR in CXCL12 Mediated T Cell Signaling and Migration

CXCL12 is a pleiotropic chemokine involved in multiple different processes such as immune regulation, inflammatory responses, and cancer development. CXCL12 is also a potent chemokine involved in chemoattraction of T cells to the site of infection or inflammation. Mammalian target of rapamycin (mTOR) is a serine-threonine kinase that modulates different cellular processes, such as metabolism, nutrient sensing, protein translation, and cell growth. The role of mTOR in CXCL12-mediated resting T cell migration has yet to be elucidated.Rapamycin, an inhibitor of mTOR, significantly inhibits CXCL12 mediated migration of both primary human resting T cells and human T cell leukemia cell line CEM. p70(S6K1), an effector molecule of mTOR signaling pathway, was knocked down by shRNA in CEM cells using a lentiviral gene transfer system. Using p70(S6K1) knock down cells, we demonstrate the role of mTOR signaling in T cell migration both in vitro and in vivo.Our data demonstrate a new role for mTOR in CXCL12-induced T cell migration, and enrich the current knowledge regarding the clinical use of rapamycin

Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

BACKGROUND: The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. METHODOLOGY/PRINCIPAL FINDINGS: An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007-2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. CONCLUSIONS/SIGNIFICANCE: The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh

Prevalence and Characterization of Motile Salmonella in Commercial Layer Poultry Farms in Bangladesh

Salmonella is a globally widespread food-borne pathogen having major impact on public health. All motile serovars of Salmonella enterica of poultry origin are zoonotic, and contaminated meat and raw eggs are an important source to human infections. Information on the prevalence of Salmonella at farm/holding level, and the zoonotic serovars circulating in layer poultry in the South and South-East Asian countries including Bangladesh, where small-scale commercial farms are predominant, is limited. To investigate the prevalence of Salmonella at layer farm level, and to identify the prevalent serovars we conducted a cross-sectional survey by randomly selecting 500 commercial layer poultry farms in Bangladesh. Faecal samples from the selected farms were collected following standard procedure, and examined for the presence of Salmonella using conventional bacteriological procedures. Thirty isolates were randomly selected, from the ninety obtained from the survey, for serotyping and characterized further by plasmid profiling and pulsed-field gel electrophoresis (PFGE). Results of the survey showed that the prevalence of motile Salmonella at layer farm level was 18% (95% confidence interval 15–21%), and Salmonella Kentucky was identified to be the only serovar circulating in the study population. Plasmid analysis of the S. Kentucky and non-serotyped isolates revealed two distinct profiles with a variation of two different sizes (2.7 and 4.8 kb). PFGE of the 30 S. Kentucky and 30 non-serotyped isolates showed that all of them were clonally related because only one genotype and three subtypes were determined based on the variation in two or three bands. This is also the first report on the presence of any specific serovar of Salmonella enterica in poultry in Bangladesh

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495

A multi-criteria sustainability assessment framework: development and application in comparing two food waste management options using a UK region as a case study

This is a post-peer-review, pre-copyedit version of an article published in Environmental Science and Pollution Research. The final authenticated version is available online at: https://doi.org/10.1007/s11356-018-2479-