A computational model of invasive aspergillosis in the lung and the role of iron

BACKGROUND: Invasive aspergillosis is a severe infection of immunocompromised hosts, caused by the inhalation of the spores of the ubiquitous environmental molds of the Aspergillus genus. The innate immune response in this infection entails a series of complex and inter-related interactions between multiple recruited and resident cell populations with each other and with the fungal cell; in particular, iron is critical for fungal growth. RESULTS: A computational model of invasive aspergillosis is presented here; the model can be used as a rational hypothesis-generating tool to investigate host responses to this infection. Using a combination of laboratory data and published literature, an in silico model of a section of lung tissue was generated that includes an alveolar duct, adjacent capillaries, and surrounding lung parenchyma. The three-dimensional agent-based model integrates temporal events in fungal cells, epithelial cells, monocytes, and neutrophils after inhalation of spores with cellular dynamics at the tissue level, comprising part of the innate immune response. Iron levels in the blood and tissue play a key role in the fungus’ ability to grow, and the model includes iron recruitment and consumption by the different types of cells included. Parameter sensitivity analysis suggests the model is robust with respect to unvalidated parameters, and thus is a viable tool for an in silico investigation of invasive aspergillosis. CONCLUSIONS: Using laboratory data from a mouse model of invasive aspergillosis in the context of transient neutropenia as validation, the model predicted qualitatively similar time course changes in fungal burden, monocyte and neutrophil populations, and tissue iron levels. This model lays the groundwork for a multi-scale dynamic mathematical model of the immune response to Aspergillus species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0275-2) contains supplementary material, which is available to authorized users

Global gene expression profiling of myeloid immune cell subsets in response to in vitro challenge with porcine circovirus 2b

Compelling evidence suggests that the early interaction between porcine circovirus 2 (PCV-2) and the innate immune system is the key event in the pathogenesis of Post-Weaning Multisystemic Wasting Syndrome (PMWS). Furthermore, PCV2 has been detected in bone-marrow samples, potentially enabling an easy spread and reservoir for the virus. To assess the gene-expression differences induced by an in-vitro PCV2b infection in different three different myeloid innate immune cell subsets generated from the same animal, we used the Agilent Porcine Gene Expression Microarray (V2). Alveolar macrophages (AMØs), monocyte-derived dendritic cells (MoDCs) and bone-marrow cells (BMCs) were generated from each animal, and challenged with a UK-isolate of a PCV2 genotype b-strain at a MOI of 0.5. Remarkably, analysis showed a highly distinct and cell-type dependent response to PCV2b challenge. Overall, MoDCs showed the most marked response to PCV2b challenge in vitro and revealed a key role for TNF in the interaction with PCV2b, whereas only few genes were affected in BMCs and AMØs. These observations were further supported by an enrichment of genes in the downstream NF-κB Signalling pathway as well as an up regulation of genes with pro-apoptotic functions post-challenge. PCV2b challenge increases the expression of a large number of immune-related and pro-apoptotic genes mainly in MoDC, which possibly explain the increased inflammation, granulomatous inflammation and lymphocyte depletion seen in PMWS-affected pigs

Interplay of lncRNA H19/miR‐675 and lncRNA NEAT1/miR‐204 in breast cancer

Long noncoding RNAs (lncRNAs) are frequently precursor RNAs of microRNAs (miRNAs) or act as competing endogenous RNAs (ceRNAs) to interact with miRNAs. To better understand the shared impact of lncRNAs and miRNAs in the regulatory post‐transcriptional network, we focused here on the relationships between (a) lncRNA H19 and miR‐675, (b) NEAT1 and miR‐204, and (c) HOTAIR and miR‐331 in plasma of early breast cancer (BC) patients. We quantified each RNA in plasma samples of 63 BC patients and 10 healthy women by quantitative real‐time PCR. In cell culture experiments, the influence of these noncoding RNAs (ncRNAs) on proliferation and apoptosis of BC cell line MCF‐7 was examined. Plasma levels of H19 (P = 0.030), NEAT1 (P = 0.030), and miR‐331 (P = 0.012) were deregulated in BC patients compared with healthy women. In both cohorts, the concentrations of H19 correlated with those of miR‐675 (P = 0.0001). Higher H19 (P = 0.001) along with lower miR‐675 (P = 0.007) levels and higher miR‐204 (P = 0.017) along with lower NEAT1 (P = 0.030) levels were detected in plasma of HER2‐positive patients compared with the other BC subgroups. Whereas the expression of HOTAIR was below the detection level, miR‐331 levels correlated with nodal status (P = 0.002) and recurrence (P = 0.012). In cell culture experiments, a competitive impact on cell proliferation and apoptosis by these ncRNAs was also documented. Our findings describe a relationship of the plasma levels of H19/miR‐675 and NEAT1/miR‐204 in the different BC subtypes; in addition, they reveal an interplay between these lncRNAs and miRNAs in the regulatory network in MCF‐7 cells, which should also be considered in the search for new diagnostic and therapeutic markers

Real-time Ethernet Residual Bus Simulation

The increasing complexity of automotive networks, their challenging timing constraints and their high bandwidth demands require new concepts for future in-car communication. Real-time Ethernet is meant to be a suitable candidate for the next-generation in-car interconnection. However, model-based testing capabilities must be available as well. Applications must be validated prior the first assembly, due to the distributed development process. Methods like residual bus simulation are of particular interest to allow for testing systems in early development stages by emulating unfinished or not available parts of the system. In this paper, we present a methodology and a feasibility study of a residual bus simulation in automotive real-time Ethernet systems. The challenges of applying this testing method in real-time Ethernet based networks with parallel packet transmission are outlined and compared to today's automotive bus system simulation approaches. Furthermore, the combination of different model-based testing techniques, that are not used in state-of-the-art commercial tools, are applied for the validation of non-functional timing requirements. An extension to an existing abstract test case model is proposed, which allows modelling temporal attributes. It is simultaneously used as simulation model to drive the residual bus simulation. We demonstrate the approach's feasibility by implementing a prototype residual bus simulator for real-time Ethernet networks and applying it to an example application.Unknow

Antimicrobial Efficacy and Spectrum of Phosphorous-Fluorine Co-Doped TiO2 Nanoparticles on the Foodborne Pathogenic Bacteria Campylobacter jejuni, Salmonella Typhimurium, Enterohaemorrhagic E. coli, Yersinia enterocolitica, Shewanella putrefaciens, Listeria monocytogenes and Staphylococcus aureus

Contamination of meats and meat products with foodborne pathogenic bacteria raises serious safety issues in the food industry. The antibacterial activities of phosphorous-fluorine co-doped TiO2 nanoparticles (PF-TiO2) were investigated against seven foodborne pathogenic bacteria: Campylobacter jejuni, Salmonella Typhimurium, Enterohaemorrhagic E. coli, Yersinia enterocolitica, Shewanella putrefaciens, Listeria monocytogenes and Staphylococcus aureus. PF-TiO2 NPs were synthesized hydrothermally at 250 °C for 1, 3, 6 or 12 h, and then tested at three different concentrations (500 μg/mL, 100 μg/mL, 20 μg/mL) for the inactivation of foodborne bacteria under UVA irradiation, daylight exposure or dark conditions. The antibacterial efficacies were compared after 30 min of exposure to light. Distinct differences in the antibacterial activities of the PF-TiO2 NPs, and the susceptibilities of tested foodborne pathogenic bacterium species were found. PF-TiO2/3 h and PF-TiO2/6 h showed the highest antibacterial activity by decreasing the living bacterial cell number from ~106 by ~5 log (L. monocytogenes), ~4 log (EHEC), ~3 log (Y. enterolcolitca, S. putrefaciens) and ~2.5 log (S. aureus), along with complete eradication of C. jejuni and S. Typhimurium. Efficacy of PF-TiO2/1 h and PF-TiO2/12 h NPs was lower, typically causing a ~2–4 log decrease in colony forming units depending on the tested bacterium while the effect of PF-TiO2/0 h was comparable to P25 TiO2, a commercial TiO2 with high photocatalytic activity. Our results show that PF-co-doping of TiO2 NPs enhanced the antibacterial action against foodborne pathogenic bacteria and are potential candidates for use in the food industry as active surface components, potentially contributing to the production of meats that are safe for consumption

Fatal West Nile Virus Infection in Horse Returning to United Kingdom from Spain, 2022

We report fatal West Nile virus (WNV) infection in a 7-year-old mare returning to the United Kingdom from Spain. Case timeline and clustering of virus sequence with recent WNV isolates suggest that transmission occurred in Andalusía, Spain. Our findings highlight the importance of vaccination for horses traveling to WNV-endemic regions

Human tear fluid proteome dataset for usage as a spectral library and for protein modeling

This article provides a detailed dataset of human tear fluid proteins. Samples were fractionated by sodium dodecyl sulfate (SDS) gel electrophoresis resulting in 48 fractions that were spiked with an indexed retention time (iRT) peptide standard. These data are based on a data-dependent acquisition (DDA) mass spectrometric approach and can be used for example as a spectral library for tear fluid proteome analysis by data-independent acquisition (DIA). Moreover, the provided data set can be used with optimized HPLC and mass spectrometric settings for proteins/peptides of interest. Besides these aspects, this dataset can serve as a protein overview for gene ontology enrichment analysis and for modeling and benchmarking of multiple signaling pathways associated with the ocular surface in healthy or disease stages. The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075

A method for model-free partial volume correction in oncological PET

BACKGROUND: As is well known, limited spatial resolution leads to partial volume effects (PVE) and consequently to limited signal recovery. Determination of the mean activity concentration of a target structure is thus compromised even at target sizes much larger than the reconstructed spatial resolution. This leads to serious size-dependent underestimates of true signal intensity in hot spot imaging. For quantitative PET in general and in the context of therapy assessment in particular it is, therefore, mandatory to perform an adequate partial volume correction (PVC). The goal of our work was to develop and to validate a model-free PVC algorithm for hot spot imaging. METHODS: The algorithm proceeds in two automated steps. Step 1: estimation of the actual object boundary with a threshold based method and determination of the total activity A measured within the enclosed volume V. Step 2: determination of the activity fraction B, which is measured outside the object due to the partial volume effect (spill-out). The PVE corrected mean value is then given by C(mean) = (A+B)/V. For validation simulated tumours were used which were derived from real patient data (liver metastases of a colorectal carcinoma and head and neck cancer, respectively). The simulated tumours have characteristics (regarding tumour shape, contrast, noise, etc.) which are very similar to those of the underlying patient data, but the boundaries and tracer accumulation are exactly known. The PVE corrected mean values of 37 simulated tumours were determined and compared with the true mean values. RESULTS: For the investigated simulated data the proposed approach yields PVE corrected mean values which agree very well with the true values (mean deviation (± s.d.): (−0.8±2.5)%). CONCLUSIONS: The described method enables accurate quantitative partial volume correction in oncological hot spot imaging