What have transgenic and knockout animals taught us about respiratory disease?

Over the past decade there has been a significant shift to the use of murine models for investigations into the molecular basis of respiratory diseases, including asthma and chronic obstructive pulmonary disease. These models offer the exciting prospect of dissecting the complex interaction between cytokines, chemokines and growth related peptides in disease pathogenesis. Furthermore, the receptors and the intracellular signalling pathways that are subsequently activated are amenable for study because of the availability of monoclonal antibodies and techniques for targeted gene disruption and gene incorporation for individual mediators, receptors and proteins. However, it is clear that extrapolation from these models to the human condition is not straightforward, as reflected by some recent clinical disappointments. This is not necessarily a problem with the use of mice itself, but results from our continued ignorance of the disease process and how to improve the modelling of complex interactions between different inflammatory mediators that underlie clinical pathology. This review highlights some of the strengths and weaknesses of murine models of respiratory disease

The application of physiologically based pharmacokinetic modelling to assess the impact of antiretroviral-mediated drug-drug interactions on piperaquine antimalarial therapy during pregnancy

Antimalarial therapy during pregnancy poses important safety concerns due to potential teratogenicity and maternal physiological and biochemical changes during gestation. Piperaquine (PQ) has gained interest for use in pregnancy in response to increasing resistance towards sulfadoxine-pyrimethamine in sub-Saharan Africa. Coinfection with HIV is common in many developing countries, however, little is known about the impact of antiretroviral (ARV) mediated drug-drug interaction (DDI) on piperaquine pharmacokinetics during pregnancy. This study applied mechanistic pharmacokinetic modelling to predict pharmacokinetics in non-pregnant and pregnant patients, which was validated in distinct customised population groups from Thailand, Sudan and Papua New Guinea. In each population group, no significant differences in day 7 concentrations were observed during different gestational weeks (GW) (weeks 10-40), supporting the notion that piperaquine is safe throughout pregnancy with consistent pharmacokinetics, although possible teratogenicity may limit this. Antiretroviral-mediated DDIs (efavirenz and ritonavir) had moderate effects on piperaquine during different gestational weeks with a predicted AUCratioin the range 0.56-0.8 and 1.64-1.79 for efavirenz and ritonavir, respectively, over GW 10-40, with a reduction in circulating human serum albumin significantly reducing the number of subjects attaining the day 7 (post-dose) therapeutic efficacy concentrations under both efavirenz and ritonavir DDIs. This present model successfully mechanistically predicted the pharmacokinetics of piperaquine in pregnancy to be unchanged with respect to non-pregnant women, in the light of factors such as malaria/HIV co-infection. However, antiretroviral-mediated DDIs could significantly alter piperaquine pharmacokinetics. Further model refinement will include collation of relevant physiological and biochemical alterations common to HIV/malaria patients

Challenges for automatically extracting molecular interactions from full-text articles

<p>Abstract</p> <p>Background</p> <p>The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles.</p> <p>Results</p> <p>We manually annotated passages from full-text articles that describe interactions summarised in a Molecular Interaction Map (MIM). Our corpus tracks the process of identifying facts to form the MIM summaries and captures any factual dependencies that must be resolved to extract the fact completely. For example, a fact in the results section may require a synonym defined in the introduction. The passages are also annotated with negated and coreference expressions that must be resolved.</p> <p>We describe the guidelines for identifying relevant passages and possible dependencies. The corpus includes 2162 sentences from 78 full-text articles. Our corpus analysis demonstrates the necessity of full-text processing; identifies the article sections where interactions are most commonly stated; and quantifies the proportion of interaction statements requiring coherent dependencies. Further, it allows us to report on the relative importance of identifying synonyms and resolving negated expressions. We also experiment with an oracle sentence retrieval system using the corpus as a gold-standard evaluation set.</p> <p>Conclusion</p> <p>We introduce the MIM corpus, a unique resource that maps interaction facts in a MIM to annotated passages within full-text articles. It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.</p

Ybp2 Associates with the Central Kinetochore of Saccharomyces cerevisiae and Mediates Proper Mitotic Progression

The spindle checkpoint ensures the accurate segregation of chromosomes by monitoring the status of kinetochore attachment to microtubules. Simultaneous mutations in one of several kinetochore and cohesion genes and a spindle checkpoint gene cause a synthetic-lethal or synthetic-sick phenotype. A synthetic genetic array (SGA) analysis using a mad2Δ query mutant strain of yeast identified YBP2, a gene whose product shares sequence similarity with the product of YBP1, which is required for H2O2-induced oxidation of the transcription factor Yap1. ybp2Δ was sensitive to benomyl and accumulated at the mitotic stage of the cell cycle. Ybp2 physically associates with proteins of the COMA complex (Ctf19, Okp1, Mcm21, and Ame1) and 3 components of the Ndc80 complex (Ndc80, Nuf2, and Spc25 but not Spc24) in the central kinetochore and with Cse4 (the centromeric histone and CENP-A homolog). Chromatin-immunoprecipitation analyses revealed that Ybp2 associates specifically with CEN DNA. Furthermore, ybp2Δ showed synthetic-sick interactions with mutants of the genes that encode the COMA complex components. Ybp2 seems to be part of a macromolecular kinetochore complex and appears to contribute to the proper associations among the central kinetochore subcomplexes and the kinetochore-specific nucleosome

The Berkeley sample of Type II supernovae: BVRI light curves and spectroscopy of 55 SNe II

In this work, BVRI light curves of 55 Type II supernovae (SNe II) from the Lick Observatory Supernova Search programme obtained with the Katzman Automatic Imaging Telescope and the 1 m Nickel telescope from 2006 to 2018 are presented. Additionally, more than 150 spectra gathered with the 3 m Shane telescope are published. We conduct an analyse of the peak absolute magnitudes, decline rates, and time durations of different phases of the light and colour curves. Typically, our light curves are sampled with a median cadence of 5.5 d for a total of 5093 photometric points. In average, V-band plateau declines with a rate of 1.29 mag (100 d)−1, which is consistent with previously published samples. For each band, the plateau slope correlates with the plateau length and the absolute peak magnitude: SNe II with steeper decline have shorter plateau duration and are brighter. A time-evolution analysis of spectral lines in term of velocities and pseudo-equivalent widths is also presented in this paper. Our spectroscopic sample ranges between 1 and 200 d post-explosion and has a median ejecta expansion velocity at 50 d post-explosion of 6500 km s−1 (H α line) and a standard dispersion of 2000 km s−1. Nebular spectra are in good agreement with theoretical models using a progenitor star having a mass <16M⊙. All the data are available to the community and will help to understand SN II diversity better, and therefore to improve their utility as cosmological distance indicators

Magnesium Limitation Is an Environmental Trigger of the Pseudomonas aeruginosa Biofilm Lifestyle

Biofilm formation is a conserved strategy for long-term bacterial survival in nature and during infections. Biofilms are multicellular aggregates of cells enmeshed in an extracellular matrix. The RetS, GacS and LadS sensors control the switch from a planktonic to a biofilm mode of growth in Pseudomonas aeruginosa. Here we detail our approach to identify environmental triggers of biofilm formation by investigating environmental conditions that repress expression of the biofilm repressor RetS. Mg2+ limitation repressed the expression of retS leading to increased aggregation, exopolysaccharide (EPS) production and biofilm formation. Repression of retS expression under Mg2+ limitation corresponded with induced expression of the GacA-controlled small regulatory RNAs rsmZ and rsmY and the EPS biosynthesis operons pel and psl. We recently demonstrated that extracellular DNA sequesters Mg2+ cations and activates the cation-sensing PhoPQ two-component system, which leads to increased antimicrobial peptide resistance in biofilms. Here we show that exogenous DNA and EDTA, through their ability to chelate Mg2+, promoted biofilm formation. The repression of retS in low Mg2+ was directly controlled by PhoPQ. PhoP also directly controlled expression of rsmZ but not rsmY suggesting that PhoPQ controls the equilibrium of the small regulatory RNAs and thus fine-tunes the expression of genes in the RetS pathway. In summary, Mg2+ limitation is a biologically relevant environmental condition and the first bonafide environmental signal identified that results in transcriptional repression of retS and promotes P. aeruginosa biofilm formation

Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine

Erratum to: Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5).

[This corrects the article DOI: 10.1186/s13601-016-0116-9.]

Erratum to: Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5).

[This corrects the article DOI: 10.1186/s13601-016-0116-9.]

Positioning the principles of precision medicine in care pathways for allergic rhinitis and chronic rhinosinusitis - A EUFOREA-ARIA-EPOS-AIRWAYS ICP statement.

Precision medicine (PM) is increasingly recognized as the way forward for optimizing patient care. Introduced in the field of oncology, it is now considered of major interest in other medical domains like allergy and chronic airway diseases, which face an urgent need to improve the level of disease control, enhance patient satisfaction and increase effectiveness of preventive interventions. The combination of personalized care, prediction of treatment success, prevention of disease and patient participation in the elaboration of the treatment plan is expected to substantially improve the therapeutic approach for individuals suffering from chronic disabling conditions. Given the emerging data on the impact of patient stratification on treatment outcomes, European and American regulatory bodies support the principles of PM and its potential advantage over current treatment strategies. The aim of the current document was to propose a consensus on the position and gradual implementation of the principles of PM within existing adult treatment algorithms for allergic rhinitis (AR) and chronic rhinosinusitis (CRS). At the time of diagnosis, prediction of success of the initiated treatment and patient participation in the decision of the treatment plan can be implemented. The second-level approach ideally involves strategies to prevent progression of disease, in addition to prediction of success of therapy, and patient participation in the long-term therapeutic strategy. Endotype-driven treatment is part of a personalized approach and should be positioned at the tertiary level of care, given the efforts needed for its implementation and the high cost of molecular diagnosis and biological treatment