Long smut in pearl millet - a new record from Eritrea

Long smut (Tolyposporium ehrenbergii) was observed on pearl millet (Pennisetum glaucum) panicles during the rainy season in the Anseba zone, Eritrea in 2000. The sorus was 3-4 times larger than a normal grain of pearl millet and was cylindrical, sometimes with a slight curve in the middle or at the tip, and contained a black mass of spores covered by a whitish to dull yellow, fairly thick membrane. This is believed to be the first documented record of this fungus on pearl millet

Prevalence of pearl millet downy mildew in Eritrea

A systematic survey of the prevalence and severity of downy mildew (Sclerospora graminicola) on pearl millet (Pennisetum glaucum) was conducted in 32 fields sown with pearl millet landraces and 7 fields sown with an improved ICRISAT variety (ICMV 221) in 8 subzones of Eritrea in 2000. Downy mildew incidence (%) was calculated from the ratio of diseased to total plants in 1 m2 subplots and 27 diseased leaf samples collected to assess variations in pathogenicity. Data on total rainfall and number of rainy days from sowing to soft dough were also collected. Downy mildew was present in most fields, but its incidence varied with location (40-78% incidence in the Keren subzone, but less than 1% in Mogolo and Dghe), and even the improved, resistant cultivar ICMV 221 had between <1-28% disease incidence. The variation in downy mildew incidence did not directly relate to variation in total rainfall or to the number of rainy days, but was probably related instead to variation in pathogen virulence within the region. There was also no consistent effect of rotational cropping sequence on disease incidence

The development of a knowledge base for basic active structures: an example case of dopamine agonists

<p>Abstract</p> <p>Background</p> <p>Chemical compounds affecting a bioactivity can usually be classified into several groups, each of which shares a characteristic substructure. We call these substructures "basic active structures" or BASs. The extraction of BASs is challenging when the database of compounds contains a variety of skeletons. Data mining technology, associated with the work of chemists, has enabled the systematic elaboration of BASs.</p> <p>Results</p> <p>This paper presents a BAS knowledge base, BASiC, which currently covers 46 activities and is available on the Internet. We use the dopamine agonists D1, D2, and Dauto as examples and illustrate the process of BAS extraction. The resulting BASs were reasonably interpreted after proposing a few template structures.</p> <p>Conclusions</p> <p>The knowledge base is useful for drug design. Proposed BASs and their supporting structures in the knowledge base will facilitate the development of new template structures for other activities, and will be useful in the design of new lead compounds via reasonable interpretations of active structures.</p

Transcriptional Response of Zebrafish Embryos Exposed to Neurotoxic Compounds Reveals a Muscle Activity Dependent hspb11 Expression

Acetylcholinesterase (AChE) inhibitors are widely used as pesticides and drugs. Their primary effect is the overstimulation of cholinergic receptors which results in an improper muscular function. During vertebrate embryonic development nerve activity and intracellular downstream events are critical for the regulation of muscle fiber formation. Whether AChE inhibitors and related neurotoxic compounds also provoke specific changes in gene transcription patterns during vertebrate development that allow them to establish a mechanistic link useful for identification of developmental toxicity pathways has, however, yet not been investigated. Therefore we examined the transcriptomic response of a known AChE inhibitor, the organophosphate azinphos-methyl (APM), in zebrafish embryos and compared the response with two non-AChE inhibiting unspecific control compounds, 1,4-dimethoxybenzene (DMB) and 2,4-dinitrophenol (DNP). A highly specific cluster of APM induced gene transcripts was identified and a subset of strongly regulated genes was analyzed in more detail. The small heat shock protein hspb11 was found to be the most sensitive induced gene in response to AChE inhibitors. Comparison of expression in wildtype, ache and sopfixe mutant embryos revealed that hspb11 expression was dependent on the nicotinic acetylcholine receptor (nAChR) activity. Furthermore, modulators of intracellular calcium levels within the whole embryo led to a transcriptional up-regulation of hspb11 which suggests that elevated intracellular calcium levels may regulate the expression of this gene. During early zebrafish development, hspb11 was specifically expressed in muscle pioneer cells and Hspb11 morpholino-knockdown resulted in effects on slow muscle myosin organization. Our findings imply that a comparative toxicogenomic approach and functional analysis can lead to the identification of molecular mechanisms and specific marker genes for potential neurotoxic compounds

Burn Injury Reduces Neutrophil Directional Migration Speed in Microfluidic Devices

Thermal injury triggers a fulminant inflammatory cascade that heralds shock, end-organ failure, and ultimately sepsis and death. Emerging evidence points to a critical role for the innate immune system, and several studies had documented concurrent impairment in neutrophil chemotaxis with these post-burn inflammatory changes. While a few studies suggest that a link between neutrophil motility and patient mortality might exist, so far, cumbersome assays have prohibited exploration of the prognostic and diagnostic significance of chemotaxis after burn injury. To address this need, we developed a microfluidic device that is simple to operate and allows for precise and robust measurements of chemotaxis speed and persistence characteristics at single-cell resolution. Using this assay, we established a reference set of migration speed values for neutrophils from healthy subjects. Comparisons with samples from burn patients revealed impaired directional migration speed starting as early as 24 hours after burn injury, reaching a minimum at 72–120 hours, correlated to the size of the burn injury and potentially serving as an early indicator for concurrent infections. Further characterization of neutrophil chemotaxis using this new assay may have important diagnostic implications not only for burn patients but also for patients afflicted by other diseases that compromise neutrophil functions

Cholesterol and Lipoprotein Dynamics in a Hibernating Mammal

Hibernating mammals cease feeding during the winter and rely primarily on stored lipids to fuel alternating periods of torpor and arousal. How hibernators manage large fluxes of lipids and sterols over the annual hibernation cycle is poorly understood. The aim of this study was to investigate lipid and cholesterol transport and storage in ground squirrels studied in spring, summer, and several hibernation states. Cholesterol levels in total plasma, HDL and LDL particles were elevated in hibernators compared with spring or summer squirrels. Hibernation increased plasma apolipoprotein A-I expression and HDL particle size. Expression of cholesterol 7 alpha-hydroxylase was 13-fold lower in hibernators than in active season squirrels. Plasma triglycerides were reduced by fasting in spring but not summer squirrels. In hibernators plasma β-hydroxybutyrate was elevated during torpor whereas triglycerides were low relative to normothermic states. We conclude that the switch to a lipid-based metabolism during winter, coupled with reduced capacity to excrete cholesterol creates a closed system in which efficient use of lipoproteins is essential for survival

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Utilising stream reasoning techniques to underpin an autonomous framework for cloud application platforms

As cloud application platforms (CAPs) are reaching the stage where the human effort required to maintain them at an operational level is unsupportable, one of the major challenges faced by the cloud providers is to develop appropriate mechanisms for run-time monitoring and adaptation, to prevent cloud application platforms from quickly dissolving into a non-reliable environment. In this context, the application of intelligent approaches to Autonomic Clouds may offer promising opportunities. In this paper we present an approach to providing cloud platforms with autonomic capabilities, utilising techniques from the Semantic Web and Stream Reasoning research fields. The main idea of this approach is to encode values, monitored within cloud application platforms, using Semantic Web languages, which then allows us to integrate semantically-enriched observation streams with static ontological knowledge and apply intelligent reasoning. Using such run-time reasoning capabilities, we have developed a conceptual architecture for an autonomous framework and describe a prototype solution we have constructed which implements this architecture. Our prototype is able to perform analysis and failure diagnosis, and suggest further adaptation actions. We report our experience in utilising the Stream Reasoning technique in this context as well as further challenges that arise out of our work