Impaired clearance and enhanced pulmonary inflammatory/fibrotic response to carbon nanotubes in myeloperoxidase-deficient mice

Advancement of biomedical applications of carbonaceous nanomaterials is hampered by their biopersistence and pro-inflammatory action in vivo. Here, we used myeloperoxidase knockout B6.129X1-MPO (MPO k/o) mice and showed that oxidation and clearance of single walled carbon nanotubes (SWCNT) from the lungs of these animals after pharyngeal aspiration was markedly less effective whereas the inflammatory response was more robust than in wild-type C57Bl/6 mice. Our results provide direct evidence for the participation of MPO - one of the key-orchestrators of inflammatory response - in the in vivo pulmonary oxidative biodegradation of SWCNT and suggest new ways to control the biopersistence of nanomaterials through genetic or pharmacological manipulations.     

Looking deeper into vertebrate development

Magnetic resonance imaging (MRI) is a non-invasive imaging method that provides three-dimensional (3-D) images of the internal structure of opaque objects, such as humans and mice. In optimal situations, spatial resolution can approach the micron level. Arbitrarily oriented single-slice images can be obtained in seconds, with full 3-D volume images taking tens of minutes to collect. The exquisite sensitivity of MRI to the local physical and chemical environment provides a wide range of mechanisms giving rise to intrinsic contrast in the MR experiment, thus providing images with dramatic differences between different tissue types (e.g. white vs grey matter, myelinated vs unmyelinated fibres, and brain parenchyma vs ventricles). The recent advent of physiologically sensitive MRI contrast agents opens up a wealth of new avenues of study, even including the in vivo imaging of gene expression.     

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon--known as heterotachy--can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.     

Profiling killers; unravelling the pathways of human natural killer cell function

Natural killer (NK) cells are lymphocytes with an innate abilityto recognize and kill infected cells and tumour cells. UnlikeB and T cells, NK cells do not express an antigen receptor.Instead, NK cells detect changes in the phenotype of the targetcell surface; malignant transformation or infection resultingin the loss or gain of particular molecules that are detectedby inhibitory or activating receptors on the NK cell surface.The identification and characterization of NK cells and theirreceptors was made possible by monoclonal antibody technology.The ease with which genes and gene products can now be identifiedand manipulated has accelerated our understanding of NK cellfunction. Furthermore, gene and protein profiling studies arebeginning to refine our understanding of NK cells, their interactionswith other cells and their effector mechanisms. This reviewillustrates some of the basic features of NK cell biology andhighlights the contribution made by post-genomic technologyin defining the molecular mechanisms by which NK cells identifyand kill susceptible targets.      

Phylogenetic mixture models can reduce node-density artifacts

We investigate the performance of phylogenetic mixture models in reducing a well-known and pervasive artifact of phylogenetic inference known as the node-density effect, comparing them to partitioned analyses of the same data. The node-density effect refers to the tendency for the amount of evolutionary change in longer branches of phylogenies to be underestimated compared to that in regions of the tree where there are more nodes and thus branches are typically shorter. Mixture models allow more than one model of sequence evolution to describe the sites in an alignment without prior knowledge of the evolutionary processes that characterize the data or how they correspond to different sites. If multiple evolutionary patterns are common in sequence evolution, mixture models may be capable of reducing node-density effects by characterizing the evolutionary processes more accurately. In gene-sequence alignments simulated to have heterogeneous patterns of evolution, we find that mixture models can reduce node-density effects to negligible levels or remove them altogether, performing as well as partitioned analyses based on the known simulated patterns. The mixture models achieve this without knowledge of the patterns that generated the data and even in some cases without specifying the full or true model of sequence evolution known to underlie the data. The latter result is especially important in real applications, as the true model of evolution is seldom known. We find the same patterns of results for two real data sets with evidence of complex patterns of sequence evolution: mixture models substantially reduced node-density effects and returned better likelihoods compared to partitioning models specifically fitted to these data. We suggest that the presence of more than one pattern of evolution in the data is a common source of error in phylogenetic inference and that mixture models can often detect these patterns even without prior knowledge of their presence in the data. Routine use of mixture models alongside other approaches to phylogenetic inference may often reveal hidden or unexpected patterns of sequence evolution and can improve phylogenetic inference.     

Differences in three kinetic parameters underpin the unique catalytic profiles of nitric-oxide synthases I, II, and III.

We previously reported the existence of a special auto-regulation property of neuronal nitric-oxide synthase (NOS) based on NO near-geminate combination and partial trapping of neuronal NOS (nNOS) through a futile regenerating pathway. On this basis, we developed a kinetic simulation model that was proven to predict nNOS catalytic specificities and mutations effects (Santolini, J., Adak, S., Curran, C. M., and Stuehr, D. J. (2001) J. Biol. Chem. 276, 1233-1243; Adak, S., Santolini, J., Tikunova, S., Wang, Q., Johnson, J. D., and Stuehr, D. J. (2001) J. Biol. Chem. 276, 1244-1252). Here we show that the same model simulates and explains the distinct catalytic behaviors of inducible and endothelial NOS (iNOS and eNOS). Their marked differences were linked to variations in three basic parameters (rates of ferric heme reduction, ferric heme.NO dissociation, and ferrous heme.NO oxidation) that together control partitioning between futile and productive pathways and their relative rates. We also incorporated feedback inhibition into the kinetic model to account for potential rebinding of accumulated solution NO. The model accurately simulated the different relative impacts of both NOS.NO interactions (near-geminate combination of NO versus rebinding of solution NO) on catalytic behavior of each NOS isoform, including their speed and extent of heme.NO complex accumulation, K(m) for O(2), and propensity to transform NO into a higher oxide. Thus, individual catalytic behavior of any NOS can be understood through a single unified kinetic model. Because the model defines how different settings of individual kinetic parameters control regulation by two distinct NOS.NO interactions, it sheds light on mechanisms, structural features, and scope of NOS regulation and its physiologic impact.     

Selective haematological parameters in steelhead trout, Salmo gairdneri Richardson

Fifteen steelhead trout, Salmo gairdneri , were assayed for selective blood parameters. The trout were reared under flow-through conditions at the salmonid aquaculture facility at the University of Rhode Island. The means of the measured haematological parameters were: pH, 7·59 ± 0·05; pCO₂, 8·5 ± 1·05 mmHg; HCO₃-, 11·9 ± 1·9 meq/1; Ferri-Hb, 21·7 ± 2·0%; C1-, 147 ± 17·8 meq/1; Hct, 30·7 ± 4·8%.     

"Right" stay in hospital after sugery: randomised controlled trial.

A randomised controlled trial was carried out on 100 patients to compare the effects of discharge after certain pre-specified clinical criteria had been fulfilled--"right" stay--with those of discharge at an arbitrary 10 days after surgery--"fixed" stay. The operations concerned (cholecystectomy and vagotomy) were more hazardous than those previously included in studies of early discharge. Patients in the right-stay group were discharged, on average, 7-6 days after operation--that is, two days earlier than those in the fixed-stay group. In terms of clinical progress, social factors such as return to work, and the acceptability to patients and relatives of the implications of right stay, patients in this group fared as well as those in the fixed-stay group, and in some respects slightly better. Right stay entailed the transfer of some work from hospital to community medical and nursing staff, but this also was acceptable. The concept and use of the right-stay principle is of value in planning the postoperative discharge of suitable patients.