Individual aerosol particles from biomass burning in southern Africa: 2. Compositions and aging of inorganic particles

Individual aerosol particles collected over southern Africa during the SAFARI 2000 field study were studied using transmission electron microscopy and field- emission scanning electron microscopy. The sizes, shapes, compositions, mixing states, surface coatings, and relative abundances of aerosol particles from biomass burning, in boundary layer hazes, and in the free troposphere were compared, with emphasis on aging and reactions of inorganic smoke particles. Potassium salts and organic particles were the predominant species in the smoke, and most were internally mixed. More KCl particles occur in young smoke, whereas more K2SO4 and KNO3 particles were present in aged smoke. This change indicates that with the aging of the smoke, KCl particles from the fires were converted to K2SO4 and KNO3 through reactions with sulfur- and nitrogen-bearing species from biomass burning as well as other sources. More soot was present in smoke from flaming grass fires than bush and wood fires, probably due to the predominance of flaming combustion in grass fires. The high abundance of organic particles and soluble salts can affect the hygroscopic properties of biomass- burning aerosols and therefore influence their role as cloud condensation nuclei. Particles from biomass burning were important constituents of the regional hazes

Estimation of soil and vegetation temperatures with multiangular thermal infrared observations: IMGRASS, HEIFE, and SGP 1997 experiments

The potential of directional observations in the thermal infrared region for land surface studies is a largely uncharted area of research. The availability of the dual-view Along Track Scanning Radiometer (ATSR) observations led to explore new opportunities in this direction. In the context of studies on heat transfer at heterogeneous land surfaces, multiangular thermal infrared (TIR) observations offer the opportunity of overcoming fundamental difficulties in modeling sparse canopies. Three case studies were performed on the estimation of the component temperatures of foliage and soil. The first one included the use of multi-temporal field measurements at view angles of 0°, 23° and 52°. The second and third one were done with directional ATSR observations at view angles of 0° and 53° only. The first one was a contribution to the Inner-Mongolia Grassland Atmosphere Surface Study (IMGRASS) experiment in China, the second to the Hei He International Field Experiment (HEIFE) in China and the third one to the Southern Great Plains 1997 (SGP 1997) experiment in Oklahoma, United States. The IMGRASS experiment provided useful insights on the applicability of a simple linear mixture model to the analysis of observed radiance. The HEIFE case study was focused on the large oasis of Zhang-Ye and led to useful estimates of soil and vegetation temperatures. The SGP 1997 contributed a better understanding of the impact of spatial heterogeneity on the accuracy of retrieved foliage and soil temperatures. Limitations in the approach due to varying radiative and boundary layer forcing and to the difference in spatial resolution between the forward and the nadir view are evaluated through a combination of modeling studies and analysis of field data

Biology of the microbiome 2: metabolic role

The human microbiome is a new frontier in biology and one that is helping to define what it is to be human. Recently, we have begun to understand that the "communication" between the host and its microbiome is via a metabolic superhighway. By interrogating and understanding the molecules involved we may start to know who the main players are, and how we can modulate them and the mechanisms of health and disease.</p

Improved Noisy Student Training for Automatic Speech Recognition

Recently, a semi-supervised learning method known as "noisy student training" has been shown to improve image classification performance of deep networks significantly. Noisy student training is an iterative self-training method that leverages augmentation to improve network performance. In this work, we adapt and improve noisy student training for automatic speech recognition, employing (adaptive) SpecAugment as the augmentation method. We find effective methods to filter, balance and augment the data generated in between self-training iterations. By doing so, we are able to obtain word error rates (WERs) 4.2%/8.6% on the clean/noisy LibriSpeech test sets by only using the clean 100h subset of LibriSpeech as the supervised set and the rest (860h) as the unlabeled set. Furthermore, we are able to achieve WERs 1.7%/3.4% on the clean/noisy LibriSpeech test sets by using the unlab-60k subset of LibriLight as the unlabeled set for LibriSpeech 960h. We are thus able to improve upon the previous state-of-the-art clean/noisy test WERs achieved on LibriSpeech 100h (4.74%/12.20%) and LibriSpeech (1.9%/4.1%).Comment: 5 pages, 5 figures, 4 tables; v2: minor revisions, reference adde

Growth Factors and Feeder Cells Promote Differentiation of Human Embryonic Stem Cells into Dopaminergic Neurons: A Novel Role for Fibroblast Growth Factor-20

Human embryonic stem cells (hESCs) are a potential source of dopaminergic neurons for treatment of patients with Parkinson's disease (PD). Dopaminergic neurons can be derived from hESCs and display a characteristic midbrain phenotype. Once transplanted, they can induce partial behavioral recovery in animal models of PD. However, the potential research field faces several challenges that need to be overcome before clinical application of hESCs in a transplantation therapy in PD can be considered. These include low survival of the hESC-derived, grafted dopaminergic neurons after transplantation; unclear functional integration of the grafted neurons in the host brain; and, the risk of teratoma/tumor formation from the transplanted cells. This review is focused on our recent efforts to improve the survival of hESC-dervied dopaminergic neurons. In a recent study, we examined the effect of fibroblast growth factor (FGF)-20 in the differentiation of hESCs into dopaminergic neurons. We supplemented cultures of hESCs with FGF-20 during differentiation on PA6 mouse stromal cells for 3 weeks. When we added FGF-20 the yield of neurons expressing tyrosine hydroxylase increased. We demonstrated that at least part of the effect is contributed by enhanced cell differentiation towards the dopaminergic phenotype as well as reduced cell death. We compare our results with those obtained in other published protocols using different sets of growth factors. Taken together, our data indicate that FGF-20 has potent effects to generate large number of dopaminergic neurons derived from hESCs, which may be useful for hESC-based therapy in PD

OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs

The concept of orthology provides a foundation for formulating hypotheses on gene and genome evolution, and thus forms the cornerstone of comparative genomics, phylogenomics and metagenomics. We present the update of OrthoDB—the hierarchical catalog of orthologs (http://www.orthodb.org). From its conception, OrthoDB promoted delineation of orthologs at varying resolution by explicitly referring to the hierarchy of species radiations, now also adopted by other resources. The current release provides comprehensive coverage of animals and fungi representing 252 eukaryotic species, and is now extended to prokaryotes with the inclusion of 1115 bacteria. Functional annotations of orthologous groups are provided through mapping to InterPro, GO, OMIM and model organism phenotypes, with cross-references to major resources including UniProt, NCBI and FlyBase. Uniquely, OrthoDB provides computed evolutionary traits of orthologs, such as gene duplicability and loss profiles, divergence rates, sibling groups, and now extended with exon-intron architectures, syntenic orthologs and parent-child trees. The interactive web interface allows navigation along the species phylogenies, complex queries with various identifiers, annotation keywords and phrases, as well as with gene copy-number profiles and sequence homology searches. With the explosive growth of available data, OrthoDB also provides mapping of newly sequenced genomes and transcriptomes to the current orthologous group

OrthoDB: the hierarchical catalog of eukaryotic orthologs in 2011

The concept of homology drives speculation on a gene's function in any given species when its biological roles in other species are characterized. With reference to a specific species radiation homologous relations define orthologs, i.e. descendants from a single gene of the ancestor. The large-scale delineation of gene genealogies is a challenging task, and the numerous approaches to the problem reflect the importance of the concept of orthology as a cornerstone for comparative studies. Here, we present the updated OrthoDB catalog of eukaryotic orthologs delineated at each radiation of the species phylogeny in an explicitly hierarchical manner of over 100 species of vertebrates, arthropods and fungi (including the metazoa level). New database features include functional annotations, and quantification of evolutionary divergence and relations among orthologous groups. The interface features extended phyletic profile querying and enhanced text-based searches. The ever-increasing sampling of sequenced eukaryotic genomes brings a clearer account of the majority of gene genealogies that will facilitate informed hypotheses of gene function in newly sequenced genomes. Furthermore, uniform analysis across lineages as different as vertebrates, arthropods and fungi with divergence levels varying from several to hundreds of millions of years will provide essential data for uncovering and quantifying long-term trends of gene evolution. OrthoDB is freely accessible from http://cegg.unige.ch/orthod

Chemometric analysis of biofluids from mice experimentally infected with Schistosoma mansoni

BACKGROUND: The urinary metabolic fingerprint of a patent Schistosoma mansoni infection in the mouse has been characterized using spectroscopic methods. However, the temporal dynamics of metabolic alterations have not been studied at the systems level. Here, we investigated the systems metabolic changes in the mouse upon S. mansoni infection by modeling the sequence of metabolic events in urine, plasma and faecal water. METHODS: Ten female NMRI mice, aged 5 weeks, were infected with 80 S. mansoni cercariae each. Ten age- and sex-matched mice remained uninfected and served as a control group. Urine, plasma and faecal samples were collected 1 day before, and on eight time points until day 73 post-infection. Biofluid samples were subjected to 1H nuclear magnetic resonance (NMR) spectroscopy and multivariate statistical analyses. RESULTS: Differences between S. mansoni-infected and uninfected control mice were found from day 41 onwards. One of the key metabolic signatures in urine and faecal extracts was an alteration in several gut bacteria-related metabolites, whereas the plasma reflected S. mansoni infection by changes in metabolites related to energy homeostasis, such as relatively higher levels of lipids and decreased levels of glucose. We identified 12 urinary biomarkers of S. mansoni infection, among which hippurate, phenylacetylglycine (PAG) and 2-oxoadipate were particularly robust with regard to disease progression. Thirteen plasma metabolites were found to differentiate infected from control mice, with the lipid components, D-3-hydroxybutyrate and glycerophosphorylcholine showing greatest consistency. Faecal extracts were highly variable in chemical composition and therefore only five metabolites were found discriminatory of infected mice, of which 5-aminovalerate was the most stable and showed a positive correlation with urinary PAG. CONCLUSIONS: The composite metabolic signature of S. mansoni in the mouse derived from perturbations in urina faecal and plasma composition showed a coherent response in altered energy metabolism and in gut microbial activity. Our findings provide new mechanistic insight into host-parasite interactions across different compartments and identified a set of temporally robust biomarkers of S. mansoni infection, which might assist in derivation of diagnostic assays or metrics for monitoring therapeutic respons

Fractal analysis in particle dissolution: a review

Fractal is a geometric language to describe the objects, the systems, and the phenomenon spatially and temporally. This paper reviews the literature on fractal models developed to describe the dissolution of particles. Dissolution, the process by which a solid forms a homogeneous mixture with a solution, is the behavior of a population of particles rather than a single one in most of the cases. The fractal models developed for the particle population are reviewed on the basis of two key particle surface properties, namely, the surface fractal nature and the chemical reactivity of particle surfaces. In terms of the surface fractal nature, fractals have been used to describe the change in the superficial roughness of particles, surface area-particle size relation, and particle size distribution (PSD). In terms of the reactive fractal dimensions, the models that describe the dissolution process have been developed to obtain the empirical noninteger exponent, the reactive fractal dimension that can dictate the chemical reactivity of a solid surface. The comparison between the surface fractal dimension and the reactive fractal dimension provides the dissolution mechanisms in many aspects of surface morphology. Further research is necessary to modify the current models to coincide with the real industrial processes and production and to develop the specific models for a better understanding of many processes involving the dissolution of particles encountered in many areas, including pharmaceutical and chemical applications and hydrometallurgy