Global Gene Expression Profiling Of Human Pleural Mesotheliomas: Identification of Matrix Metalloproteinase 14 (MMP-14) as Potential Tumour Target

BACKGROUND:The goal of our study was to molecularly dissect mesothelioma tumour pathways by mean of microarray technologies in order to identify new tumour biomarkers that could be used as early diagnostic markers and possibly as specific molecular therapeutic targets. METHODOLOGY:We performed Affymetrix HGU133A plus 2.0 microarray analysis, containing probes for about 39,000 human transcripts, comparing 9 human pleural mesotheliomas with 4 normal pleural specimens. Stringent statistical feature selection detected a set of differentially expressed genes that have been further evaluated to identify potential biomarkers to be used in early diagnostics. Selected genes were confirmed by RT-PCR. As reported by other mesothelioma profiling studies, most of genes are involved in G2/M transition. Our list contains several genes previously described as prognostic classifier. Furthermore, we found novel genes, never associated before to mesotheliom that could be involved in tumour progression. Notable is the identification of MMP-14, a member of matrix metalloproteinase family. In a cohort of 70 mesothelioma patients, we found by a multivariate Cox regression analysis, that the only parameter influencing overall survival was expression of MMP14. The calculated relative risk of death in MM patients with low MMP14 expression was significantly lower than patients with high MMp14 expression (P = 0.002). CONCLUSIONS:Based on the results provided, this molecule could be viewed as a new and effective therapeutic target to test for the cure of mesothelioma

Role of SPI-1 Secreted Effectors in Acute Bovine Response to Salmonella enterica Serovar Typhimurium: A Systems Biology Analysis Approach

Salmonella enterica Serovar Typhimurium (S. Typhimurium) causes enterocolitis with diarrhea and polymorphonuclear cell (PMN) influx into the intestinal mucosa in humans and calves. The Salmonella Type III Secretion System (T3SS) encoded at Pathogenicity Island I translocates Salmonella effector proteins SipA, SopA, SopB, SopD, and SopE2 into epithelial cells and is required for induction of diarrhea. These effector proteins act together to induce intestinal fluid secretion and transcription of C-X-C chemokines, recruiting PMNs to the infection site. While individual molecular interactions of the effectors with cultured host cells have been characterized, their combined role in intestinal fluid secretion and inflammation is less understood. We hypothesized that comparison of the bovine intestinal mucosal response to wild type Salmonella and a SipA, SopABDE2 effector mutant relative to uninfected bovine ileum would reveal heretofore unidentified diarrhea-associated host cellular pathways. To determine the coordinated effects of these virulence factors, a bovine ligated ileal loop model was used to measure responses to wild type S. Typhimurium (WT) and a ΔsipA, sopABDE2 mutant (MUT) across 12 hours of infection using a bovine microarray. Data were analyzed using standard microarray analysis and a dynamic Bayesian network modeling approach (DBN). Both analytical methods confirmed increased expression of immune response genes to Salmonella infection and novel gene expression. Gene expression changes mapped to 219 molecular interaction pathways and 1620 gene ontology groups. Bayesian network modeling identified effects of infection on several interrelated signaling pathways including MAPK, Phosphatidylinositol, mTOR, Calcium, Toll-like Receptor, CCR3, Wnt, TGF-β, and Regulation of Actin Cytoskeleton and Apoptosis that were used to model of host-pathogen interactions. Comparison of WT and MUT demonstrated significantly different patterns of host response at early time points of infection (15 minutes, 30 minutes and one hour) within phosphatidylinositol, CCR3, Wnt, and TGF-β signaling pathways and the regulation of actin cytoskeleton pathway

Euclid: Validation of the MontePython forecasting tools

Context. The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. Aims. We expand and adjust the mock Euclid likelihoods of the MontePython software in order to match the exact recipes used in previous Euclid Fisher matrix forecasts for several probes: weak lensing cosmic shear, photometric galaxy clustering, the crosscorrelation between the latter observables, and spectroscopic galaxy clustering.We also establish which precision settings are required when running the Einstein-Boltzmann solvers CLASS and CAMB in the context of Euclid. Methods. For the minimal cosmological model, extended to include dynamical dark energy, we perform Fisher matrix forecasts based directly on a numerical evaluation of second derivatives of the likelihood with respect to model parameters. We compare our results with those of previously validated Fisher codes using an independent method based on first derivatives of the Euclid observables. Results. We show that such MontePython forecasts agree very well with previous Fisher forecasts published by the Euclid Collaboration, and also, with new forecasts produced by the CosmicFish code, now interfaced directly with the two Einstein-Boltzmann solvers CAMB and CLASS. Moreover, to establish the validity of the Gaussian approximation, we show that the Fisher matrix marginal error contours coincide with the credible regions obtained when running Monte Carlo Markov chains with MontePython while using the exact same mock likelihoods. Conclusions. The new Euclid forecast pipelines presented here are ready for use with additional cosmological parameters, in order to explore extended cosmological models

Breaking Functional Connectivity into Components: A Novel Approach Using an Individual-Based Model, and First Outcomes

Landscape connectivity is a key factor determining the viability of populations in fragmented landscapes. Predicting ‘functional connectivity’, namely whether a patch or a landscape functions as connected from the perspective of a focal species, poses various challenges. First, empirical data on the movement behaviour of species is often scarce. Second, animal-landscape interactions are bound to yield complex patterns. Lastly, functional connectivity involves various components that are rarely assessed separately. We introduce the spatially explicit, individual-based model FunCon as means to distinguish between components of functional connectivity and to assess how each of them affects the sensitivity of species and communities to landscape structures. We then present the results of exploratory simulations over six landscapes of different fragmentation levels and across a range of hypothetical bird species that differ in their response to habitat edges. i) Our results demonstrate that estimations of functional connectivity depend not only on the response of species to edges (avoidance versus penetration into the matrix), the movement mode investigated (home range movements versus dispersal), and the way in which the matrix is being crossed (random walk versus gap crossing), but also on the choice of connectivity measure (in this case, the model output examined). ii) We further show a strong effect of the mortality scenario applied, indicating that movement decisions that do not fully match the mortality risks are likely to reduce connectivity and enhance sensitivity to fragmentation. iii) Despite these complexities, some consistent patterns emerged. For instance, the ranking order of landscapes in terms of functional connectivity was mostly consistent across the entire range of hypothetical species, indicating that simple landscape indices can potentially serve as valuable surrogates for functional connectivity. Yet such simplifications must be carefully evaluated in terms of the components of functional connectivity they actually predict

Euclid preparation: LIV. Sensitivity to neutrino parameters

\ua9 The Authors 2024.Context. The Euclid mission of the European Space Agency will deliver weak gravitational lensing and galaxy clustering surveys that can be used to constrain the standard cosmological model and extensions thereof. Aims. We present forecasts from the combination of the Euclid photometric galaxy surveys (weak lensing, galaxy clustering, and their cross-correlations) and its spectroscopic redshift survey with respect to their sensitivity to cosmological parameters. We include the summed neutrino mass, Σmν, and the effective number of relativistic species, Neff, in the standard Λ CDM scenario and in the dynamical dark energy (w0waCDM) scenario. Methods. We compared the accuracy of different algorithms predicting the non-linear matter power spectrum for such models. We then validated several pipelines for Fisher matrix and Markov chain Monte Carlo (MCMC) forecasts, using different theory codes, algorithms for numerical derivatives, and assumptions on the non-linear cut-off scale. Results. The Euclid primary probes alone will reach a sensitivity of σ (Σmν = 60 meV) = 56 meV in the Λ CDM+Σmν model, whereas the combination with cosmic microwave background (CMB) data from Planck is expected to achieve σ (Σmν) = 23 meV, offering evidence of a non-zero neutrino mass to at least the 2.6 σ level. This could be pushed to a 4 σ detection if future CMB data from LiteBIRD and CMB Stage-IV were included. In combination with Planck, Euclid will also deliver tight constraints on Δ Neff < 0.144 (95%CL) in the Λ CDM+Σmν+Neff model or even Δ Neff < 0.063 when future CMB data are included. When floating the dark energy parameters, we find that the sensitivity to Neff remains stable, but for Σmν, it gets degraded by up to a factor of 2, at most. Conclusions. This work illustrates the complementarity among the Euclid spectroscopic and photometric surveys and among Euclid and CMB constraints. Euclid will offer great potential in measuring the neutrino mass and excluding well-motivated scenarios with additional relativistic particles

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Assimilation of alternative sulfur sources in fungi

Fungi are well known for their metabolic versatility, whether it is the degradation of complex organic substrates or the biosynthesis of intricate secondary metabolites. The vast majority of studies concerning fungal metabolic pathways for sulfur assimilation have focused on conventional sources of sulfur such as inorganic sulfur ions and sulfur-containing biomolecules. Less is known about the metabolic pathways involved in the assimilation of so-called “alternative” sulfur sources such as sulfides, sulfoxides, sulfones, sulfonates, sulfate esters and sulfamates. This review summarizes our current knowledge regarding the structural diversity of sulfur compounds assimilated by fungi as well as the biochemistry and genetics of metabolic pathways involved in this process. Shared sequence homology between bacterial and fungal sulfur assimilation genes have lead to the identification of several candidate genes in fungi while other enzyme activities and pathways so far appear to be specific to the fungal kingdom. Increased knowledge of how fungi catabolize this group of compounds will ultimately contribute to a more complete understanding of sulfur cycling in nature as well as the environmental fate of sulfur-containing xenobiotics

Parkinson's Disease: Basic Pathomechanisms and a Clinical Overview

PD is a common and a debilitating degenerative movement disorder. The number of patients is increasing worldwide and as yet there is no cure for the disease. The majority of existing treatments target motor symptom control. Over the last two decades the impact of the genetic contribution to PD has been appreciated. Significant discoveries have been made, which have advanced our understanding of the pathophysiological and molecular basis of PD. In this chapter we outline current knowledge of the clinical aspects of PD and the basic mechanistic understanding