Solar wind interaction with comet 67P: impacts of corotating interaction regions

International audienceWe present observations from the Rosetta Plasma Consortium of the effects of stormy solar wind on comet 67P/Churyumov-Gerasimenko. Four corotating interaction regions (CIRs), where the first event has possibly merged with a coronal mass ejection, are traced from Earth via Mars (using Mars Express and Mars Atmosphere and Volatile EvolutioN mission) to comet 67P from October to December 2014. When the comet is 3.1–2.7 AU from the Sun and the neutral outgassing rate ∼1025–1026 s−1, the CIRs significantly influence the cometary plasma environment at altitudes down to 10–30 km. The ionospheric low-energy (∼5 eV) plasma density increases significantly in all events, by a factor of >2 in events 1 and 2 but less in events 3 and 4. The spacecraft potential drops below −20 V upon impact when the flux of electrons increases. The increased density is likely caused by compression of the plasma environment, increased particle impact ionization, and possibly charge exchange processes and acceleration of mass-loaded plasma back to the comet ionosphere. During all events, the fluxes of suprathermal (∼10–100 eV) electrons increase significantly, suggesting that the heating mechanism of these electrons is coupled to the solar wind energy input. At impact the magnetic field strength in the coma increases by a factor of 2–5 as more interplanetary magnetic field piles up around the comet. During two CIR impact events, we observe possible plasma boundaries forming, or moving past Rosetta, as the strong solar wind compresses the cometary plasma environment. We also discuss the possibility of seeing some signatures of the ionospheric response to tail disconnection events

Investigating short-time-scale variations in cometary ions around comet 67P

The highly varying plasma environment around comet 67P/Churyumov–Gerasimenko inspired an upgrade of the ion mass spectrometer (Rosetta Plasma Consortium Ion Composition Analyzer) with new operation modes, to enable high time resolution measurements of cometary ions. Two modes were implemented, one having a 4 s time resolution in the energy range 0.3–82 eV/q and the other featuring a 1 s time resolution in the energy range 13–50 eV/q. Comparing measurements made with the two modes, it was concluded that 4 s time resolution is enough to capture most of the fast changes of the cometary ion environment. The 1462 h of observations done with the 4 s mode were divided into hour-long sequences. It is possible to sort 84 per cent of these sequences into one of five categories, depending on their appearance in an energy–time spectrogram. The ion environment is generally highly dynamic, and variations in ion fluxes and energies are seen on time-scales of 10 s to several minutes

Evidence for the classical integrability of the complete AdS(4) x CP(3) superstring

We construct a zero-curvature Lax connection in a sub-sector of the superstring theory on AdS(4) x CP(3) which is not described by the OSp(6|4)/U(3) x SO(1,3) supercoset sigma-model. In this sub-sector worldsheet fermions associated to eight broken supersymmetries of the type IIA background are physical fields. As such, the prescription for the construction of the Lax connection based on the Z_4-automorphism of the isometry superalgebra OSp(6|4) does not do the job. So, to construct the Lax connection we have used an alternative method which nevertheless relies on the isometry of the target superspace and kappa-symmetry of the Green-Schwarz superstring.Comment: 1+26 pages; v2: minor typos corrected, acknowledgements adde

Classification of heterogeneous microarray data by maximum entropy kernel

<p>Abstract</p> <p>Background</p> <p>There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are commonly used in microarray analyses with support vector machines (SVMs) to approach a wide range of classification problems. However, the standard vectorial data kernel family (linear, RBF, etc.) that takes vectorial data as input, often fails in prediction if the data come from different platforms or laboratories, due to the low gene overlaps or consistencies between the different datasets.</p> <p>Results</p> <p>We introduce a new type of kernel called maximum entropy (ME) kernel, which has no pre-defined function but is generated by kernel entropy maximization with sample distance matrices as constraints, into the field of SVM classification of microarray data. We assessed the performance of the ME kernel with three different data: heterogeneous kidney carcinoma, noise-introduced leukemia, and heterogeneous oral cavity carcinoma metastasis data. The results clearly show that the ME kernel is very robust for heterogeneous data containing missing values and high-noise, and gives higher prediction accuracies than the standard kernels, namely, linear, polynomial and RBF.</p> <p>Conclusion</p> <p>The results demonstrate its utility in effectively analyzing promiscuous microarray data of rare specimens, e.g., minor diseases or species, that present difficulty in compiling homogeneous data in a single laboratory.</p

Mesenchymal Stromal Cells Engage Complement and Complement Receptor Bearing Innate Effector Cells to Modulate Immune Responses

Infusion of human third-party mesenchymal stromal cells (MSCs) appears to be a promising therapy for acute graft-versus-host disease (aGvHD). To date, little is known about how MSCs interact with the body's innate immune system after clinical infusion. This study shows, that exposure of MSCs to blood type ABO-matched human blood activates the complement system, which triggers complement-mediated lymphoid and myeloid effector cell activation in blood. We found deposition of complement component C3-derived fragments iC3b and C3dg on MSCs and fluid-phase generation of the chemotactic anaphylatoxins C3a and C5a. MSCs bound low amounts of immunoglobulins and lacked expression of complement regulatory proteins MCP (CD46) and DAF (CD55), but were protected from complement lysis via expression of protectin (CD59). Cell-surface-opsonization and anaphylatoxin-formation triggered complement receptor 3 (CD11b/CD18)-mediated effector cell activation in blood. The complement-activating properties of individual MSCs were furthermore correlated with their potency to inhibit PBMC-proliferation in vitro, and both effector cell activation and the immunosuppressive effect could be blocked either by using complement inhibitor Compstatin or by depletion of CD14/CD11b-high myeloid effector cells from mixed lymphocyte reactions. Our study demonstrates for the first time a major role of the complement system in governing the immunomodulatory activity of MSCs and elucidates how complement activation mediates the interaction with other immune cells

Computational Biology in Costa Rica: The Role of a Small Country in the Global Context of Bioinformatics

Introduction: The successful development of high throughput methods for DNA sequencing, transcriptomics, proteomics, and other –omics, has contributed to the emergence of novel possibilities for the examination of complex biological systems through computational analysis. These fields have witnessed unprecedented advances in high income countries. Nevertheless, the role of other nations needs to be examined in order to delineate their contribution within the global context of bioinformatics. Previous articles have focused on the expansion of Computational Biology in Brazil and Mexico [1],[2], two of the largest Latin American countries, and which have shown political commitment to foster their scientific development. Costa Rica is a small Central American country with a population of 4 million, with its territory 164 and 38 times smaller than Brazil and Mexico, respectively. Thus, it is interesting to visualize the possibilities and challenges of this low-income country in the context of the global bioinformatics endeavor.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Instituto Clodomiro Picado (ICP

Nature and Distribution of Stable Subsurface Oxygen in Copper Electrodes During Electrochemical CO₂ Reduction

Oxide-derived copper (OD-Cu) electrodes exhibit higher activity than pristine copper during the carbon dioxide reduction reaction (CO₂RR) and higher selectivity toward ethylene. The presence of residual subsurface oxygen in OD-Cu has been proposed to be responsible for such improvements, although its stability under the reductive CO₂RR conditions remains unclear. This work sheds light on the nature and stability of subsurface oxygen. Our spectroscopic results show that oxygen is primarily concentrated in an amorphous 1–2 nm thick layer within the Cu subsurface, confirming that subsurface oxygen is stable during CO₂RR for up to 1 h at −1.15 V vs RHE. Besides, it is associated with a high density of defects in the OD-Cu structure. We propose that both low coordination of the amorphous OD-Cu surface and the presence of subsurface oxygen that withdraws charge from the copper sp- and d-bands might selectively enhance the binding energy of CO

In Silico Prediction of Estrogen Receptor Subtype Binding Affinity and Selectivity Using Statistical Methods and Molecular Docking with 2-Arylnaphthalenes and 2-Arylquinolines

Over the years development of selective estrogen receptor (ER) ligands has been of great concern to researchers involved in the chemistry and pharmacology of anticancer drugs, resulting in numerous synthesized selective ER subtype inhibitors. In this work, a data set of 82 ER ligands with ERα and ERβ inhibitory activities was built, and quantitative structure-activity relationship (QSAR) methods based on the two linear (multiple linear regression, MLR, partial least squares regression, PLSR) and a nonlinear statistical method (Bayesian regularized neural network, BRNN) were applied to investigate the potential relationship of molecular structural features related to the activity and selectivity of these ligands. For ERα and ERβ, the performances of the MLR and PLSR models are superior to the BRNN model, giving more reasonable statistical properties (ERα: for MLR, Rtr2 = 0.72, Qte2 = 0.63; for PLSR, Rtr2 = 0.92, Qte2 = 0.84. ERβ: for MLR, Rtr2 = 0.75, Qte2 = 0.75; for PLSR, Rtr2 = 0.98, Qte2 = 0.80). The MLR method is also more powerful than other two methods for generating the subtype selectivity models, resulting in Rtr2 = 0.74 and Qte2 = 0.80. In addition, the molecular docking method was also used to explore the possible binding modes of the ligands and a relationship between the 3D-binding modes and the 2D-molecular structural features of ligands was further explored. The results show that the binding affinity strength for both ERα and ERβ is more correlated with the atom fragment type, polarity, electronegativites and hydrophobicity. The substitutent in position 8 of the naphthalene or the quinoline plane and the space orientation of these two planes contribute the most to the subtype selectivity on the basis of similar hydrogen bond interactions between binding ligands and both ER subtypes. The QSAR models built together with the docking procedure should be of great advantage for screening and designing ER ligands with improved affinity and subtype selectivity property

The Artelon CMC spacer compared with tendon interposition arthroplasty: A randomized, controlled, multicenter study of 109 patients with osteoarthritis followed for 1 year

Background and purpose The Artelon CMC spacer is designed for surgical treatment of osteoarthritis (OA) in the carpometacarpal joint of the thumb (CMC-I). Good results using this degradable device were previously presented in a pilot study. We now present results from a larger randomized, controlled, multicenter study

Molecular Characterisation of Trimethoprim Resistance in Escherichia coli and Klebsiella pneumoniae during a Two Year Intervention on Trimethoprim Use

BACKGROUND: Trimethoprim resistance is increasing in Enterobacteriaceae. In 2004-2006 an intervention on trimethoprim use was conducted in Kronoberg County, Sweden, resulting in 85% reduction in trimethoprim prescriptions. We investigated the distribution of dihydrofolate reductase (dfr)-genes and integrons in Escherichia coli and Klebsiella pneumoniae and the effect of the intervention on this distribution. METHODOLOGY/PRINCIPAL FINDINGS: Consecutively isolated E. coli (n = 320) and K. pneumoniae (n = 54) isolates phenotypically resistant to trimethoprim were studied. All were investigated for the presence of dfrA1, dfrA5, dfrA7, dfrA8, dfrA12, dfrA14, dfrA17 and integrons class I and II. Isolates negative for the seven dfr-genes (n = 12) were also screened for dfr2d, dfrA3, dfrA9, dfrA10, dfrA24 and dfrA26. These genes accounted for 96% of trimethoprim resistance in E. coli and 69% in K. pneumoniae. The most prevalent was dfrA1 in both species. This was followed by dfrA17 in E. coli which was only found in one K. pneumoniae isolate. Class I and II Integrons were more common in E. coli (85%) than in K. pneumoniae (57%). The distribution of dfr-genes did not change during the course of the 2-year intervention. CONCLUSIONS/SIGNIFICANCE: The differences observed between the studied species in terms of dfr-gene and integron prevalence indicated a low rate of dfr-gene transfer between these two species and highlighted the possible role of narrow host range plasmids in the spread of trimethoprim resistance. The stability of dfr-genes, despite large changes in the selective pressure, indirectly suggests a low fitness cost of dfr-gene carriage