Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China.

Sharing of genetic elements among different pathogens and commensals inhabiting same hosts and environments has significant implications for antimicrobial resistance (AMR), especially in settings with high antimicrobial exposure. We analysed 661 Escherichia coli and Salmonella enterica isolates collected within and across hosts and environments, in 10 Chinese chicken farms over 2.5 years using data-mining methods. Most isolates within same hosts possessed the same clinically relevant AMR-carrying mobile genetic elements (plasmids: 70.6%, transposons: 78%), which also showed recent common evolution. Supervised machine learning classifiers revealed known and novel AMR-associated mutations and genes underlying resistance to 28 antimicrobials, primarily associated with resistance in E. coli and susceptibility in S. enterica. Many were essential and affected same metabolic processes in both species, albeit with varying degrees of phylogenetic penetration. Multi-modal strategies are crucial to investigate the interplay of mobilome, resistance and metabolism in cohabiting bacteria, especially in ecological settings where community-driven resistance selection occurs.

Machine learning and metagenomics reveal shared antimicrobial resistance profiles across multiple chicken farms and abattoirs in China.

China is the largest global consumer of antimicrobials and improving surveillance methods could help to reduce antimicrobial resistance (AMR) spread. Here we report the surveillance of ten large-scale chicken farms and four connected abattoirs in three Chinese provinces over 2.5 years. Using a data mining approach based on machine learning, we analysed 461 microbiomes from birds, carcasses and environments, identifying 145 potentially mobile antibiotic resistance genes (ARGs) shared between chickens and environments across all farms. A core set of 233 ARGs and 186 microbial species extracted from the chicken gut microbiome correlated with the AMR profiles of Escherichia coli colonizing the same gut, including Arcobacter, Acinetobacter and Sphingobacterium, clinically relevant for humans, and 38 clinically relevant ARGs. Temperature and humidity in the barns were also correlated with ARG presence. We reveal an intricate network of correlations between environments, microbial communities and AMR, suggesting multiple routes to improving AMR surveillance in livestock production.

On-machine surface defect detection using light scattering and deep learning.

This paper presents an on-machine surface defect detection system using light scattering and deep learning. A supervised deep learning model is used to mine the information related to defects from light scattering patterns. A convolutional neural network is trained on a large dataset of scattering patterns that are predicted by a rigorous forward scattering model. The model is valid for any surface topography with homogeneous materials and has been verified by comparing with experimental data. Once the neural network is trained, it allows for fast, accurate, and robust defect detection. The system capability is validated on microstructured surfaces produced by ultraprecision diamond machining.

Multi-view fringe projection system for surface topography measurement during metal powder bed fusion.

Metal powder bed fusion (PBF) methods need in-process measurement methods to increase user confidence and encourage further adoption in high-value manufacturing sectors. In this paper, a novel measurement method for PBF systems is proposed that uses multi-view fringe projection to acquire high-resolution surface topography information of the powder bed. Measurements were made using a mock-up of a commercial PBF system to assess the system's accuracy and precision in comparison to conventional single-view fringe projection techniques for the same application. Results show that the multi-view system is more accurate, but less precise, than single-view fringe projection on a point-by-point basis. The multi-view system also achieves a high degree of surface coverage by using alternate views to access areas not measured by a single camera.

Combined Inkjet Printing and Infrared Sintering of Silver Nanoparticles using a Swathe-by-Swathe and Layer-by-Layer Approach for 3-Dimensional Structures.

Despite the advancement of additive manufacturing (AM)/3-dimensional (3D) printing, single-step fabrication of multifunctional parts using AM is limited. With the view of enabling multifunctional AM (MFAM), in this study, sintering of metal nanoparticles was performed to obtain conductivity for continuous line inkjet printing of electronics. This was achieved using a bespoke three-dimensional (3D) inkjet-printing machine, JETx, capable of printing a range of materials and utilizing different post processing procedures to print multilayered 3D structures in a single manufacturing step. Multiple layers of silver were printed from an ink containing silver nanoparticles (AgNPs) and infrared sintered using a swathe-by-swathe (SS) and layer-by-layer sintering (LS) regime. The differences in the heat profile for the SS and LS was observed to influence the coalescence of the AgNPs. Void percentage of both SS and LS samples was higher toward the top layer than the bottom layer due to relatively less IR exposure in the top than the bottom. The results depicted a homogeneous microstructure for LS of AgNPs and showed less deformation compared to the SS. Electrical resistivity of the LS tracks (13.6 ± 1 µΩ cm) was lower than the SS tracks (22.5 ± 1 µΩ cm). This study recommends the use of LS method to sinter the AgNPs to obtain a conductive track in 25% less time than SS method for MFAM.

CluGene: A Bioinformatics Framework for the Identification of Co-Localized, Co-Expressed and Co-Regulated Genes Aimed at the Investigation of Transcriptional Regulatory Networks from High-Throughput Expression Data.

The full understanding of the mechanisms underlying transcriptional regulatory networks requires unravelling of complex causal relationships. Genome high-throughput technologies produce a huge amount of information pertaining gene expression and regulation; however, the complexity of the available data is often overwhelming and tools are needed to extract and organize the relevant information. This work starts from the assumption that the observation of co-occurrent events (in particular co-localization, co-expression and co-regulation) may provide a powerful starting point to begin unravelling transcriptional regulatory networks. Co-expressed genes often imply shared functional pathways; co-expressed and functionally related genes are often co-localized, too; moreover, co-expressed and co-localized genes are also potential targets for co-regulation; finally, co-regulation seems more frequent for genes mapped to proximal chromosome regions. Despite the recognized importance of analysing co-occurrent events, no bioinformatics solution allowing the simultaneous analysis of co-expression, co-localization and co-regulation is currently available. Our work resulted in developing and valuating CluGene, a software providing tools to analyze multiple types of co-occurrences within a single interactive environment allowing the interactive investigation of combined co-expression, co-localization and co-regulation of genes. The use of CluGene will enhance the power of testing hypothesis and experimental approaches aimed at unravelling transcriptional regulatory networks. The software is freely available at http://bioinfolab.unipg.it/.

Regulation of Anopheles gambiae male accessory gland genes influences postmating response in female.

In Drosophila, the accessory gland proteins (Acps) secreted from the male accessory glands (MAGs) and transferred along with sperm into the female reproductive tract have been implicated in triggering postmating behavioral changes, including refractoriness to subsequent mating and propensity to egg laying. Recently, Acps have been found also in Anopheles, suggesting similar functions. Understanding the mechanisms underlying transcriptional regulation of Acps and their functional role in modulating Anopheles postmating behavior may lead to the identification of novel vector control strategies to reduce mosquito populations. We identified heat-shock factor (HSF) binding sites within the Acp promoters of male Anopheles gambiae and discovered three distinct Hsf isoforms; one being significantly up-regulated in the MAGs after mating. Through genome-wide transcription analysis of Hsf-silenced males, we observed significant down-regulation in 50% of the Acp genes if compared to control males treated with a construct directed against an unrelated bacterial sequence. Treated males retained normal life span and reproductive behavior compared to control males. However, mated wild-type females showed a ∼46% reduction of egg deposition rate and a ∼23% reduction of hatching rate (∼58% combined reduction of progeny). Our results highlight an unsuspected role of HSF in regulating Acp transcription in A. gambiae and provide evidence that Acp down-regulation in males leads a significant reduction of progeny, thus opening new avenues toward the development of novel vector control strategies.

Serum IgE reactivity profiling in an asthma affected cohort.

BACKGROUND: Epidemiological evidence indicates that atopic asthma correlates with high serum IgE levels though the contribution of allergen specific IgE to the pathogenesis and the severity of the disease is still unclear. METHODS: We developed a microarray immunoassay containing 103 allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals belonging to families whose members have a documented history of asthma and atopy. We employed k-means clustering, to investigate whether a particular IgE reactivity profile correlated with asthma and other atopic conditions such as rhinitis, conjunctivitis and eczema. RESULTS: Both case-control and parent-to-siblings analyses demonstrated that while the presence of specific IgE against individual allergens correlated poorly with pathological conditions, particular reactivity profiles were significantly associated with asthma (p<10E-09). An artificial neural network (ANN)-based algorithm, calibrated with the profile reactivity data, correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Multivariate statistical analysis demonstrated that the familiar relationships of the study population did not affect the observed correlations. CONCLUSIONS: These findings indicate that asthma is a higher-order phenomenon related to patterns of IgE reactivity rather than to single antibody reactions. This notion sheds new light on the pathogenesis of the disease and can be readily employed to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile.

Gepoclu: a software tool for identifying and analyzing gene positional clusters in large-scale gene expression analysis.

BACKGROUND: The notion that genes are non-randomly organized within the chromosomes of eukaryotic organisms has recently received strong experimental support. Clusters of co-expressed and co-localized genes have been recognized as playing key roles in a number of functional pathways and adaptive responses including organism development, differentiation, disease states and aging. The identification of genes arranged in close proximity with each other within a particular temporal and spatial transcriptional program is anticipated to unravel possible functional links and reciprocal interactions. RESULTS: We developed a novel software tool Gepoclu (Gene Positional Clustering) that automatically selects genes based on expression values from multiple sources, including microarray, EST and qRT-PCR, and performs positional clustering. Gepoclu provides expression-based gene selection from multiple experimental sources, position-based gene clustering and cluster visualization functionalities, all as parts of the same fully integrated, and interactive, package. This means rapid iterations while exploring for emergent behavior, and full programmability of the filtering and clustering steps. CONCLUSIONS: Gepoclu is a useful data-mining tool for exploring relationships among transcriptional data deriving form different sources. It provides an easy interactive environment for analyzing positional clustering behavior of co-expressed genes, and at the same time it is fully programmable, so that it can be customized and extended to support specific analysis needs.

Three-dimensional surface topography acquisition and analysis for firearm identification.

In the last decade, computer-based systems for the comparison of microscopic firearms evidence have been the subject of considerable research work because of their expected capability of supporting the firearms examiner through the automated analysis of large amounts of evidence. The Integrated Ballistics Identification System, which is based on a two-dimensional representation of the specimen surface, has been widely adopted in forensic laboratories worldwide. More recently, some attempts to develop systems based on three-dimensional (3D) representations of the specimen surface have been made, both in the literature and as industrial products, such as BulletTRAX-3D, but fundamental limitations in achieving fully automated identification remain. This work analyzes the advantages and disadvantages of a 3D-based approach by proposing an approach and a prototype system for firearms evidence comparison that is based on the acquisition and analysis of the 3D surface topography of specimens, with particular reference to cartridge cases. The concept of 3D virtual comparison microscope is introduced, whose purpose is not to provide fully automated identification, but to show how the availability of 3D shape information can provide a whole new set of verification means, some of them being described and discussed in this work, specifically, visual enhancement tools and quantitative measurement of shape properties, for supporting, not replacing, the firearm examiner in reaching the final decision.