Morphology,biomass and nutrient status of fine roots of Scots pine (<Emphasis Type="Italic">Pinus sylvestris</Emphasis>) as influenced by seasonal fluctuations in soil moisture and soil solution chemistry

A field monitoring study was carried out to follow the changes of fine root morphology, biomass and nutrient status in relation to seasonal changes in soil solution chemistry and moisture regime in a mature Scots pine stand on acid soil. Seasonal and yearly fluctuations in soil moisture and soil solution chemistry have been observed. Changes in soil moisture accounted for some of the changes in the soil solution chemistry. The results showed that when natural acidification in the soil occurs with low pH (3.5–4.2) and high aluminium concentration in the soil solution (>3–10 mg l^–1), fine root longevity and distribution could be affected. However, fine root growth of Scots pine may not be negatively influenced by adverse soil chemical conditions if soil moisture is not a limiting factor for root growth. In contrast, dry soil conditions increase Scots pine susceptibility to soil acidification and this could significantly reduce fine root growth and increase root mortality. It is therefore important to study seasonal fluctuations of the environmental variables when investigating and modelling cause-effect relationships.     

Modeling the oscillation dynamics of activated airway smooth muscle strips

When strips of activated airway smooth muscle are stretched cyclically, they exhibit force-length loops that vary substantially in both position and shape with the amplitude and frequency of the stretch. This behavior has recently been ascribed to a dynamic interaction between the imposed stretch and the number of actin-myosin interactions in the muscle. However, it is well known that the passive rheological properties of smooth muscle have a major influence on its mechanical properties. We therefore hypothesized that these rheological properties play a significant role in the force-length dynamics of activated smooth muscle. To test the plausibility of this hypothesis, we developed a model of the smooth muscle strip consisting of a force generator in series with an elastic component. Realistic steady-state force-length loops are predicted by the model when the force generator obeys a hyperbolic force-velocity relationship, the series elastic component is highly nonlinear, and both elastic stiffness and force generation are adjusted so that peak loop force equals isometric force. We conclude that the dynamic behavior of airway smooth muscle can be ascribed in large part to an interaction between connective tissue rheology and the force-velocity behavior of contractile proteins.     

Loss of Gadd45a does not modify the pulmonary response to oxidative stress

It is well established that exposure to high levels of oxygen (hyperoxia) injures and kills microvascular endothelial and alveolar type I epithelial cells. In contrast, significant death of airway and type II epithelial cells is not observed at mortality, suggesting that these cell types may express genes that protect against oxidative stress and damage. During a search for genes induced by hyperoxia, we previously reported that airway and alveolar type II epithelial cells uniquely express the growth arrest and DNA damage (Gadd)45a gene. Because Gadd45a has been implicated in protection against genotoxic stress, adult Gadd45a (+/+) and Gadd45a (-/-) mice were exposed to hyperoxia to investigate whether it protected epithelial cells against oxidative stress. During hyperoxia, Gadd45a deficiency did not affect loss of airway epithelial expression of Clara cell secretory protein or type II epithelial cell expression of pro-surfactant protein C. Likewise, Gadd45a deficiency did not alter recruitment of inflammatory cells, edema, or overall mortality. Consistent with Gadd45a not affecting the oxidative stress response, p21(Cip1/WAF1) and heme oxygenase-1 were comparably induced in Gadd45a (+/+) and Gadd45a (-/-) mice. Additionally, Gadd45a deficiency did not affect oxidative DNA damage or apoptosis as assessed by oxidized guanine and terminal deoxyneucleotidyl transferase-mediated dUTP nick-end labeling staining. Overexpression of Gadd45a in human lung adenocarcinoma cells did not affect viability or survival during exposure, whereas it was protective against UV-radiation. We conclude that increased tolerance of airway and type II epithelial cells to hyperoxia is not attributed solely to expression of Gadd45a.     

Using a logarithmic regression to identify the heart-rate threshold in cyclists

The purpose of this study was to establish an objective method for identifying the heart-rate threshold (HRT) in cyclists. Fifty-six male cyclists were tested on a cycle ergometer to volitional fatigue. Identification of the HRT used a heart-rate increase above a logarithmic regression line of best fit, coupled with the crossover of a linear regression line of best fit. The measures of Vco(2) and blood lactate for ventilatory threshold (VT) and lactate threshold (HLaT), respectively, were used as criterion measures to validate the HRT. Comparison of HRT with VT and HLaT showed significant associations (r = 0.98). Statistical variance between HRT, VT, and HLaT indicated no difference. From these findings, the logarithmic regression method provides an objective means to determine the HRT. Through this method, cyclists may obtain information for establishing accurate training levels and protocols.     

Effect of potentiation and stretching on maximal force, rate of force development, and range of motion

The purpose of this investigation was to compare the effects of stretching vs. potentiation on subsequent maximal force and rate of force development capabilities of subjects in an isometric squat. Ten male collegiate athletes participated as subjects in this study. Subjects were tested during 3 separate sessions that involved joint range of motion (ROM) measurements of the lower body and isometric squat trials on a force plate to determine peak force (PF) and rate of force development (RFD) values. One testing session was preceded by 10 minutes of quiet sitting (C), 1 by a 30-minute lower-body stretching protocol (S), and 1 by 3 sets of a leg press exercise using 90% of the subjects' previously determined 1 repetition maximum (P). Three repetitions were performed for each set of the leg press, with a 3-minute rest period between each set. PF during the isometric squat was not significantly different following any of the 3 conditions (C: 100.0 +/- 0.0%, S: 101.2 +/- 6.5%, P: 98.6 +/- 6.2%). However, RFD was significantly lower in P (87.5 +/- 12.8%) compared with both C (100.0 +/- 0.0%) and S (102.6 +/- 18.5%). Significant improvement in ROM occurred only following P. It appears the potentiation protocol used in the current investigation may actually have had fatiguing effects instead of potentiating effects, but it did result in significant increases in ROM.     

Combined static and dynamic analysis for determining the quality of time-series expression profiles

Expression profiling of time-series experiments is widely used to study biological systems. However, determining the quality of the resulting profiles remains a fundamental problem. Because of inadequate sampling rates, the effect of arrest-and-release methods and loss of synchronization, the measurements obtained from a series of time points may not accurately represent the underlying expression profiles. To solve this, we propose an approach that combines time-series and static (average) expression data analysis--for each gene, we determine whether its temporal expression profile can be reconciled with its static expression levels. We show that by combining synchronized and unsynchronized human cell cycle data, we can identify many cycling genes that are missed when using only time-series data. The algorithm also correctly distinguishes cycling genes from genes that specifically react to an environmental stimulus even if they share similar temporal expression profiles. Experimental validation of these results shows the utility of this analytical approach for determining the accuracy of gene expression patterns.     

Natural killer T cells: rapid responders controlling immunity and disease

Natural killer T (NKT) cells are a subset of T cells that share properties of natural killer cells and conventional T cells. They are involved in immediate immune responses, tumor rejection, immune surveillance and control of autoimmune diseases. Most NKT cells express both an invariant T cell antigen receptor and the NK cell receptor NK1.1, and are referred to as invariant NKT cells. This invariant T cell receptor is restricted to interactions with glycolipids presented by the non-classical MHC, CD1d. These NKT cells rapidly produce high levels of interleukin (IL)-2, IFN-gamma, TNF-alpha, and IL-4 upon stimulation through their TCR. Most also have cytotoxic activity similar to NK cells. NKT cells are involved in a number of pathological conditions, and have been shown to regulate viral infections in vivo, and control tumor growth. They may also play both protective and harmful roles in the progression of certain autoimmune diseases, such as diabetes, lupus, atherosclerosis, and allergen-induced asthma.     

SpecAlign--processing and alignment of mass spectra datasets

SUMMARY: Pre-processing of chromatographic profile or mass spectral data is an important aspect of many types of proteomics and biomarker discovery experiments. Here we present a graphical computational tool, SpecAlign, that enables simultaneous visualization and manipulation of multiple datasets. SpecAlign not only provides all common processing functions, but also uniquely implements an algorithm that enables the complete alignment of each mass spectrum within a loaded dataset. We demonstrate its utility by aligning two datasets each containing six spectra; one set was acquired prior to instrument calibration and the other following calibration. AVAILABILITY: The software is free of charge and available for download from http://ptcl.chem.ox.ac.uk/~jwong/specalign. Supports Windows operating systems including Windows 9X/NT/2000/XP.     

Semi-supervised protein classification using cluster kernels

MOTIVATION: Building an accurate protein classification system depends critically upon choosing a good representation of the input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art classification performance. However, such representations are based only on labeled data--examples with known 3D structures, organized into structural classes--whereas in practice, unlabeled data are far more plentiful. RESULTS: In this work, we develop simple and scalable cluster kernel techniques for incorporating unlabeled data into the representation of protein sequences. We show that our methods greatly improve the classification performance of string kernels and outperform standard approaches for using unlabeled data, such as adding close homologs of the positive examples to the training data. We achieve equal or superior performance to previously presented cluster kernel methods and at the same time achieving far greater computational efficiency. AVAILABILITY: Source code is available at www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot. The Spider matlab package is available at www.kyb.tuebingen.mpg.de/bs/people/spider. SUPPLEMENTARY INFORMATION: www.kyb.tuebingen.mpg.de/bs/people/weston/semiprot.