Surveillance of Ruminant Diseases in the Nordic Countries

<p/> <p>All the Nordic countries have a basis for their surveillance and disease control in ruminants in national legislation and regulations listing notifiable diseases of concern to the countries. The Nordic countries are a disease-free zone comparing to other parts of the world and the aim of the surveillance is to keep that status and be able to document it. Following is a short summary from each country.</p

Distribution of motor unit potential velocities in short static and prolonged dynamic contractions at low forces: use of the within-subject’s skewness and standard deviation variables

Behaviour of motor unit potential (MUP) velocities in relation to (low) force and duration was investigated in biceps brachii muscle using a surface electrode array. Short static tests of 3.8 s (41 subjects) and prolonged dynamic tests (prolonged tests) of 4 min (30 subjects) were performed as position tasks, applying forces up to 20% of maximal voluntary contraction (MVC). Four variables, derived from the inter-peak latency technique, were used to describe changes in the surface electromyography signal: the mean muscle fibre conduction velocity (CV), the proportion between slow and fast MUPs expressed as the within-subject skewness of MUP velocities, the within-subject standard deviation of MUP velocities [SD-peak velocity (PV)], and the amount of MUPs per second (peak frequency = PF). In short static tests and the initial phase of prolonged tests, larger forces induced an increase of the CV and PF, accompanied with the shift of MUP velocities towards higher values, whereas the SD-PV did not change. During the first 1.5–2 min of the prolonged lower force levels tests (unloaded, and loaded 5 and 10% MVC) the CV and SD-PV slightly decreased and the MUP velocities shifted towards lower values; then the three variables stabilized. The PF values did not change in these tests. However, during the prolonged higher force (20% MVC) test, the CV decreased and MUP velocities shifted towards lower values without stabilization, while the SD-PV broadened and the PF decreased progressively. It is argued that these combined results reflect changes in both neural regulatory strategies and muscle membrane state

International BEAT-PCD consensus statement for infection prevention and control for primary ciliary dyskinesia in collaboration with ERN-LUNG PCD Core Network and patient representatives.

Introduction In primary ciliary dyskinesia (PCD) impaired mucociliary clearance leads to recurrent airway infections and progressive lung destruction, and concern over chronic airway infection and patient-to-patient transmission is considerable. So far, there has been no defined consensus on how to control infection across centres caring for patients with PCD. Within the BEAT-PCD network, COST Action and ERS CRC together with the ERN-Lung PCD core a first initiative has now been taken towards creating such a consensus statement. Methods A multidisciplinary international PCD expert panel was set up to create a consensus statement for infection prevention and control (IP&C) for PCD, covering diagnostic microbiology, infection prevention for specific pathogens considered indicated for treatment and segregation aspects. Using a modified Delphi process, consensus to a statement demanded at least 80% agreement within the PCD expert panel group. Patient organisation representatives were involved throughout the process. Results We present a consensus statement on 20 IP&C statements for PCD including suggested actions for microbiological identification, indications for treatment of Pseudomonas aeruginosa, Burkholderia cepacia and nontuberculous mycobacteria and suggested segregation aspects aimed to minimise patient-to-patient transmission of infections whether in-hospital, in PCD clinics or wards, or out of hospital at meetings between people with PCD. The statement also includes segregation aspects adapted to the current coronavirus disease 2019 (COVID-19) pandemic. Conclusion The first ever international consensus statement on IP&C intended specifically for PCD is presented and is targeted at clinicians managing paediatric and adult patients with PCD, microbiologists, patient organisations and not least the patients and their families

Evolutionary Sequence Modeling for Discovery of Peptide Hormones

There are currently a large number of “orphan” G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these peptide hormones is a difficult and important problem. We describe a computational framework that models spatial structure along the genomic sequence simultaneously with the temporal evolutionary path structure across species and show how such models can be used to discover new functional molecules, in particular peptide hormones, via cross-genomic sequence comparisons. The computational framework incorporates a priori high-level knowledge of structural and evolutionary constraints into a hierarchical grammar of evolutionary probabilistic models. This computational method was used for identifying novel prohormones and the processed peptide sites by producing sequence alignments across many species at the functional-element level. Experimental results with an initial implementation of the algorithm were used to identify potential prohormones by comparing the human and non-human proteins in the Swiss-Prot database of known annotated proteins. In this proof of concept, we identified 45 out of 54 prohormones with only 44 false positives. The comparison of known and hypothetical human and mouse proteins resulted in the identification of a novel putative prohormone with at least four potential neuropeptides. Finally, in order to validate the computational methodology, we present the basic molecular biological characterization of the novel putative peptide hormone, including its identification and regional localization in the brain. This species comparison, HMM-based computational approach succeeded in identifying a previously undiscovered neuropeptide from whole genome protein sequences. This novel putative peptide hormone is found in discreet brain regions as well as other organs. The success of this approach will have a great impact on our understanding of GPCRs and associated pathways and help to identify new targets for drug development

An FPT Approach for Predicting Protein Localization from Yeast Genomic Data

Accurately predicting the localization of proteins is of paramount importance in the quest to determine their respective functions within the cellular compartment. Because of the continuous and rapid progress in the fields of genomics and proteomics, more data are available now than ever before. Coincidentally, data mining methods been developed and refined in order to handle this experimental windfall, thus allowing the scientific community to quantitatively address long-standing questions such as that of protein localization. Here, we develop a frequent pattern tree (FPT) approach to generate a minimum set of rules (mFPT) for predicting protein localization. We acquire a series of rules according to the features of yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regression under various statistical measures. Our results show that mFPT gave better performance than other approaches in predicting protein localization. Meanwhile, setting 0.65 as the minimum hit-rate, we obtained 138 proteins that mFPT predicted differently than the simple naive bayesian method (SNB). In our analysis of these 138 proteins, we present novel predictions for the location for 17 proteins, which currently do not have any defined localization. These predictions can serve as putative annotations and should provide preliminary clues for experimentalists. We also compared our predictions against the eukaryotic subcellular localization database and related predictions by others on protein localization. Our method is quite generalized and can thus be applied to discover the underlying rules for protein-protein interactions, genomic interactions, and structure-function relationships, as well as those of other fields of research

Computational Comparative Study of Tuberculosis Proteomes Using a Model Learned from Signal Peptide Structures

Secretome analysis is important in pathogen studies. A fundamental and convenient way to identify secreted proteins is to first predict signal peptides, which are essential for protein secretion. However, signal peptides are highly complex functional sequences that are easily confused with transmembrane domains. Such confusion would obviously affect the discovery of secreted proteins. Transmembrane proteins are important drug targets, but very few transmembrane protein structures have been determined experimentally; hence, prediction of the structures is essential. In the field of structure prediction, researchers do not make assumptions about organisms, so there is a need for a general signal peptide predictor

Differential Inductive Signaling of CD90+ Prostate Cancer-Associated Fibroblasts Compared to Normal Tissue Stromal Mesenchyme Cells

Prostate carcinomas are surrounded by a layer of stromal fibroblastic cells that are characterized by increased expression of CD90. These CD90+ cancer-associated stromal fibroblastic cells differ in gene expression from their normal counterpart, CD49a+CD90lo stromal smooth muscle cells; and were postulated to represent a less differentiated cell type with altered inductive properties. CD90+ stromal cells were isolated from tumor tissue specimens and co-cultured with the pluripotent embryonal carcinoma cell line NCCIT in order to elucidate the impact of tumor-associated stroma on stem cells, and the ‘cancer stem cell.’ Transcriptome analysis identified a notable decreased induction of smooth muscle and prostate stromal genes such as PENK, BMP2 and ChGn compared to previously determined NCCIT response to normal prostate stromal cell induction. CD90+ stromal cell secreted factors induced an increased expression of CD90 and differential induction of genes involved in extracellular matrix remodeling and the RECK pathway in NCCIT. These results suggest that, compared to normal tissue stromal cells, signaling from cancer-associated stromal cells has a markedly different effect on stem cells as represented by NCCIT. Given that stromal cells are important in directing organ-specific differentiation, stromal cells in tumors appear to be defective in this function, which may contribute to abnormal differentiation found in diseases such as cancer

Formin homology 2 domains occur in multiple contexts in angiosperms

BACKGROUND: Involvement of conservative molecular modules and cellular mechanisms in the widely diversified processes of eukaryotic cell morphogenesis leads to the intriguing question: how do similar proteins contribute to dissimilar morphogenetic outputs. Formins (FH2 proteins) play a central part in the control of actin organization and dynamics, providing a good example of evolutionarily versatile use of a conserved protein domain in the context of a variety of lineage-specific structural and signalling interactions. RESULTS: In order to identify possible plant-specific sequence features within the FH2 protein family, we performed a detailed analysis of angiosperm formin-related sequences available in public databases, with particular focus on the complete Arabidopsis genome and the nearly finished rice genome sequence. This has led to revision of the current annotation of half of the 22 Arabidopsis formin-related genes. Comparative analysis of the two plant genomes revealed a good conservation of the previously described two subfamilies of plant formins (Class I and Class II), as well as several subfamilies within them that appear to predate the separation of monocot and dicot plants. Moreover, a number of plant Class II formins share an additional conserved domain, related to the protein phosphatase/tensin/auxilin fold. However, considerable inter-species variability sets limits to generalization of any functional conclusions reached on a single species such as Arabidopsis. CONCLUSIONS: The plant-specific domain context of the conserved FH2 domain, as well as plant-specific features of the domain itself, may reflect distinct functional requirements in plant cells. The variability of formin structures found in plants far exceeds that known from both fungi and metazoans, suggesting a possible contribution of FH2 proteins in the evolution of the plant type of multicellularity

Whole-Genome Immunoinformatic Analysis of F. tularensis: Predicted CTL Epitopes Clustered in Hotspots Are Prone to Elicit a T-Cell Response

The cellular arm of the immune response plays a central role in the defense against intracellular pathogens, such as F. tularensis. To date, whole genome immunoinformatic analyses were limited either to relatively small genomes (e.g. viral) or to preselected subsets of proteins in complex pathogens. Here we present, for the first time, an unbiased bacterial global immunoinformatic screen of the 1740 proteins of F. tularensis subs. holarctica (LVS), aiming at identification of immunogenic peptides eliciting a CTL response. The very large number of predicted MHC class I binders (about 100,000, IC50 of 1000 nM or less) required the design of a strategy for further down selection of CTL candidates. The approach developed focused on mapping clusters rich in overlapping predicted epitopes, and ranking these “hotspot” regions according to the density of putative binding epitopes. Limited by the experimental load, we selected to screen a library of 1240 putative MHC binders derived from 104 top-ranking highly dense clusters. Peptides were tested for their ability to stimulate IFNγ secretion from splenocytes isolated from LVS vaccinated C57BL/6 mice. The majority of the clusters contained one or more CTL responder peptides and altogether 127 novel epitopes were identified, of which 82 are non-redundant. Accordingly, the level of success in identification of positive CTL responders was 17–25 fold higher than that found for a randomly selected library of 500 predicted MHC binders (IC50 of 500 nM or less). Most proteins (ca. 2/3) harboring the highly dense hotspots are membrane-associated. The approach for enrichment of true positive CTL epitopes described in this study, which allowed for over 50% increase in the dataset of known T-cell epitopes of F. tularensis, could be applied in immunoinformatic analyses of many other complex pathogen genomes