Genetic parameters for growth traits in pigs estimated using third degree polynomial functions

Selostus: Sian kasvuominaisuuksien perinnölliset tunnusluvut arvioituna kolmannen asteen polynomifunktion avulla

Cloning and characterization of Helicobacter pylori succinyl CoA:acetoacetate CoA-transferase, a novel prokaryotic member of the CoA-transferase family.

Sequencing of a fragment of Helicobacter pylori genome led to the identification of two open reading frames showing striking homology with Coenzyme A (CoA) transferases, enzymes catalyzing the reversible transfer of CoA from one carboxylic acid to another. The genes were present in all H. pylori strains tested by polymerase chain reaction or slot blotting but not in Campylobacter jejuni. Genes for the putative A and B subunits of H. pylori CoA-transferase were introduced into the bacterial expression vector pKK223-3 and expressed in Escherichia coli JM105 cells. Amino acid sequence comparisons, combined with measurements of enzyme activities using different CoA donors and acceptors, identified the H. pylori CoA-transferase as a succinyl CoA:acetoacetate CoA-transferase. This activity was consistently observed in different H. pylori strains. Antibodies raised against either recombinant A or B subunits recognized two distinct subunits of Mr approximately 26,000 and 24, 000 that are both necessary for H. pylori CoA-transferase function. The lack of alpha-ketoglutarate dehydrogenase and of succinyl CoA synthetase activities indicates that the generation of succinyl CoA is not mediated by the tricarboxylic acid cycle in H. pylori. We postulate the existence of an alternative pathway where the CoA-transferase is essential for energy metabolism.

Reversible major histocompatibility complex I-peptide multimers containing Ni(2+)-nitrilotriacetic acid peptides and histidine tags improve analysis and sorting of CD8(+) T cells.

MHC-peptide multimers containing biotinylated MHC-peptide complexes bound to phycoerythrin (PE) streptavidin (SA) are widely used for analyzing and sorting antigen-specific T cells. Here we describe alternative T cell-staining reagents that are superior to conventional reagents. They are built on reversible chelate complexes of Ni(2+)-nitrilotriacetic acid (NTA) with oligohistidines. We synthesized biotinylated linear mono-, di-, and tetra-NTA compounds using conventional solid phase peptide chemistry and studied their interaction with HLA-A*0201-peptide complexes containing a His(6), His(12), or 2×His(6) tag by surface plasmon resonance on SA-coated sensor chips and equilibrium dialysis. The binding avidity increased in the order His(6) < His(12) < 2×His(6) and NTA(1) < NTA(2) < NTA(4), respectively, depending on the configuration of the NTA moieties and increased to picomolar K(D) for the combination of a 2×His(6) tag and a 2×Ni(2+)-NTA(2). We demonstrate that HLA-A2-2×His(6)-peptide multimers containing either Ni(2+)-NTA(4)-biotin and PE-SA- or PE-NTA(4)-stained influenza and Melan A-specific CD8+ T cells equal or better than conventional multimers. Although these complexes were highly stable, they very rapidly dissociated in the presence of imidazole, which allowed sorting of bona fide antigen-specific CD8+ T cells without inducing T cell death as well as assessment of HLA-A2-peptide monomer dissociation kinetics on CD8+ T cells.

Reversible ferromagnetic switching in ZnO:(Co,Mn) powders

We report here on the magnetic properties of ZnO:Mn- and ZnO:Co-doped nanoparticles. We have found that the ferromagnetism of ZnO:Mn can be switched on and off by consecutive low-temperature annealings in O2 and N2, respectively, while the opposite phenomenology was observed for ZnO:Co. These results suggest that different defects (presumably n-type for ZnO:Co and p-type for ZnO:Mn) are required to induce a ferromagnetic coupling in each case. We will argue that ferromagnetism is likely to be restricted to a very thin, nanometric layer at the grain surface. These findings reveal and give insight into the dramatic relevance of surface effects to the occurrence of ferromagnetism in ZnO-doped oxides.

Use of human MAR elements to improve retroviral vector production.

Retroviral vectors have many favorable properties for gene therapies, but their use remains limited by safety concerns and/or by relatively lower titers for some of the safer self-inactivating (SIN) derivatives. In this study, we evaluated whether increased production of SIN retroviral vectors can be achieved from the use of matrix attachment region (MAR) epigenetic regulators. Two MAR elements of human origin were found to increase and to stabilize the expression of the green fluorescent protein transgene in stably transfected HEK-293 packaging cells. Introduction of one of these MAR elements in retroviral vector-producing plasmids yielded higher expression of the viral vector RNA. Consistently, viral titers obtained from transient transfection of MAR-containing plasmids were increased up to sixfold as compared with the parental construct, when evaluated in different packaging cell systems and transfection conditions. Thus, use of MAR elements opens new perspectives for the efficient generation of gene therapy vectors.

An adenovirus-based fluorescent reporter vector to identify and isolate HIV-infected cells.

A procedure is described that allows the simple identification and sorting of live human cells that transcribe actively the HIV virus, based on the detection of GFP fluorescence in cells. Using adenoviral vectors for gene transfer, an expression cassette including the HIV-1 LTR driving the reporter gene GFP was introduced into cells that expressed stably either the Tat transcriptional activator, or an inactive mutant of Tat. Both northern and fluorescence-activated cell sorting (FACS) analysis indicate that cells containing the functional Tat protein presented levels of GFP mRNA and GFP fluorescence several orders of magnitude higher than control cells. Correspondingly, cells infected with HIV-1 showed similar enhanced reporter gene activation. HIV-1-infected cells of the lymphocytic line Jurkat were easily identified by fluorescence-activated cell sorting (FACS) as they displayed a much higher green fluorescence after transduction with the reporter adenoviral vector. This procedure could also be applied on primary human cells as blood monocyte-derived macrophages exposed to the adenoviral LTR-GFP reporter presented a much higher fluorescence when infected with HIV-1 compared with HIV-uninfected cells. The vector described has the advantages of labelling cells independently of their proliferation status and that analysis can be carried on intact cells which can be isolated subsequently by fluorescence-activated cell sorting (FACS) for further culture. This work suggests that adenoviral vectors carrying a virus-specific transcriptional control element controlling the expressions of a fluorescent protein will be useful in the identification and isolation of cells transcribing actively the viral template, and to be of use for drug screening and susceptibility assays.

Geomodelling of a fluvial system with semi-supervised support vector regression

Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

Current-density-functional approach to large quantum dots in intense magnetic fields

Within current-density-functional theory, we have studied a quantum dot made of 210 electrons confined in a disk geometry. The ground state of this large dot exhibits some features as a function of the magnetic field (Beta) that can be attributed in a clear way to the formation of compressible and incompressible states of the system. The orbital and spin angular momenta, the total energy, ionization and electron chemical potentials of the ground state, as well as the frequencies of far-infrared edge modes are calculated as a function of Beta, and compared with available experimental and theoretical results.

Wave-vector dependence of spin and density multipole excitations in quantum dots

We have employed time-dependent local-spin density-functional theory to analyze the multipole spin and charge density excitations in GaAs-AlxGa1-xAs quantum dots. The on-plane transferred momentum degree of freedom has been taken into account, and the wave-vector dependence of the excitations is discussed. In agreement with previous experiments, we have found that the energies of these modes do not depend on the transferred wave vector, although their intensities do. Comparison with a recent resonant Raman scattering experiment [C. Schüller et al., Phys. Rev. Lett. 80, 2673 (1998)] is made. This allows us to identify the angular momentum of several of the observed modes as well as to reproduce their energies