Influence of the Degree of Aeration on Halotolerance of Yeasts of the Genera Candida,Rhodotorula, and Malassezia

The biochemical mechanisms were studied that determine different reactions of yeasts of different genera to two simultaneously imposed stressors, hypoxia and osmotic shock. For Candida lipolytica, these two stressors were antagonistic, which resulted in stimulation (and not suppression) of the growth of this yeast by NaCl (in a wide range of concentrations) under microaerobic conditions. The reaction of Malasseziasp. was different: the degree of halotolerance of this microorganism was lower under microaerobic conditions. An intervening reaction pattern was characteristic of Rhodotorula aurantiaca.These differences were found to be determined, above all, by the induction of a salt-resistant respiratory system (oxidase) in C. lipolytica, which could not be induced in Malassezia sp. In addition, the synthesis of catalase was enhanced in C. lipolytica, which provided for neutralization of the active forms of oxygen accumulating as a result of inhibition of other protective enzymes by salt.     

铁皮石斛腋芽的快速繁殖

目的利用组织培养技术建立铁皮石斛的高效快繁体系,克隆繁殖种苗,为野生居群的恢复提供材料。方法以铁皮石斛腋芽为外植体,研究不同浓度和配比的基本培养基、激素以及天然提取物对腋芽萌发生长,丛生芽的诱导增殖以及壮苗生根的影响,比较不同培养阶段的增殖倍数,筛选各时期的最适培养基。并对试管苗的形态学特征进行了调查。结果1/2MS+NAA 0.2 mg/L+BA 1 mg/L适合腋芽的成活生长。BA与香蕉汁组合有利于丛生芽的诱导增殖,其最适比例为1/2MS+NAA 0.5 mg/L+BA 2.0 mg/L+香蕉汁100 g/L,增殖倍数最大可达14.0,平均增殖倍数为6.4。培养基中添加100 g/L香蕉汁或200 g/L马铃薯汁均有利于壮苗生根。结论铁皮石斛通过腋芽形成丛生芽途径建立高效的快繁技术体系获得优质种苗是可行的。     

Relationship between multiple sequence alignments and quality of protein comparative models

Comparative modeling is the method of choice, whenever applicable, for protein structure prediction, not only because of its higher accuracy compared to alternative methods, but also because it is possible to estimate a priori the quality of the models that it can produce, thereby allowing the usefulness of a model for a given application to be assessed beforehand. By and large, the quality of a comparative model depends on two factors: the extent of structural divergence between the target and the template and the quality of the sequence alignment between the two protein sequences. The latter is usually derived from a multiple sequence alignment (MSA) of as many proteins of the family as possible, and its accuracy depends on the number and similarity distribution of the sequences of the protein family. Here we describe a method to evaluate the expected difficulty, and by extension accuracy, of a comparative model on the basis of the MSA used to build it. The parameter that we derive is used to compare the results obtained in the last two editions of the Critical Assessment of Methods for Structure Prediction (CASP) experiment as a function of the difficulty of the modeling exercise. Our analysis demonstrates that the improvement in the scope and quality of comparative models between the two experiments is largely due to the increased number of available protein sequences and to the consequent increased chance that a large and appropriately spaced set of protein sequences homologous to the proteins of interest is available.     

BAFF inhibition: a new class of drugs for the treatment of autoimmunity

BAFF (BLyS) and APRIL are TNF-like cytokines that support survival and differentiation of B cells. Recent studies have discovered a role for BAFF in augmenting both innate and adaptive immune responses as well as in collaborating with other inflammatory cytokines to promote the activation and differentiation of effector immune cells. BAFF is an important pathogenic factor in lupus mouse models and BAFF inhibition successfully delays disease onset in these mice, although the responsiveness to BAFF inhibition varies among different strains. These results have led to the development of inhibitors targeting BAFF and APRIL in humans. An anti-BAFF antibody has shown significant but modest efficacy in two Phase III clinical trials for moderately active SLE and other inhibitors are being developed or at early stages of clinical testing.     

Shrinkage Estimation Method for Mapping Multiple Quantitative Trait Loci

In this article, shrinkage estimation method for multiple-marker analysis and for mapping multiple quantitative trait loci (QTL) was reviewed. For multiple-marker analysis, Xu (Genetics, 2003, 163:789-801) developed a Bayesian shrinkage estimation (BSE) method. The key to the success of this method is to allow each marker effect have its own variance parameter, which in turn has its own prior distribution so that the variance can be estimated from the data. Under this hierarchical model, a large number of markers can be handled although most of them may have negligible effects. Under epistatic genetic model, however, the running time is very long. To overcome this problem, a novel method of incorporating the idea described above into maximum likelihood, known as penalized likelihood method, was proposed. A simulated study showed that this method can handle a model with multiple effects, which are ten times larger than the sample size. For multiple QTL analysis, two modified versions for the BSE method were introduced: one is the fixed-interval method and another is the variable-interval method. The former deals with markers with intermediate density, and the latter can handle markers with extremely high density as well as model with epistatic effects. For the detection of epistatic effects, penalized likelihood method and the variable-interval approach of the BSE method are available.     

基于多目标灰色局势决策的三峡库区防护林类型空间优化配置

基于2007年Landsat TM遥感影像和影响防护林的主导环境因子,对三峡库区的森林立地进行分类,并通过选取水源涵养量、生物量和林分生产力3个指标,利用多目标灰色局势决策模型对库区现有的针叶林、阔叶林、针阔混交林和灌木林4种防护林类型进行空间优化配置.结果表明： 2007年,三峡库区森林立地可划分为40种类型;空间配置优化后,研究区针叶林、阔叶林、针阔混交林和灌木林的面积比例分别为32.55%、29.43%、34.95%和3.07%.与优化前相比,优化后针叶林和灌木林的面积比例分别减少了8.79%和28.55%,阔叶林和针阔混交林分别增加了10.23%和27.11%.通过防护林类型的空间优化,三峡库区整体的水源涵养能力、生物量和林分生产力分别增加14.09×10⁸ m³、0.35×10⁸ t和1.08×10⁶ t.     

MONITORING THE TREND OF HARBOR SEALS IN PRINCE WILLIAM SOUND,ALASKA, AFTER THE EXXON VALDEZ OIL SPILL

We used aerial counts to monitor the trend in numbers of harbor seals, Phoca vitulina richardsi, in Prince William Sound, Alaska, following the 1989 Exxon Valdez oil spill. Repetitive counts were made at 25 haul-out sites during the annual molt period each year from 1990 through 1997. A generalized linear model indicated that time of day, date, and time relative to low tide significantly affected seal counts. When Poisson regression was used to adjust counts to a standardized set of survey conditions, results showed a highly significant decline of 4.6% per year. Unadjusted counts indicated a slight, but not statistically significant, decline in the number of seals. The number of harbor seals on the trend-count route in eastern and central PWS has been declining since at least 1984, with an overall population reduction of 63% through 1997. Programs to monitor long-term changes in animal population sizes should account for factors that can cause short-term variations in indices of abundance. The inclusion of such factors as covariates in models can improve the accuracy of monitoring programs.     

Predicting walnut (Juglans spp.) crop yield using meteorological and airborne pollen data

Crop yield determines economy by influencing prices on the trade market, and so accurate forecasts of the yield are important for planning various aspects of agricultural production. The main aim of this study is to construct a model for predicting walnut yield in an important walnut production area (the region of Novi Sad in Northern Serbia). Relationships between the amount of walnuts produced annually (2000–2011) and abiotic (e.g. meteorological) and biotic (e.g. airborne pollen data) factors were examined using Pearson correlation analysis. Walnut yield data were then entered into linear regression models with variables that had the highest correlations. The models were constructed using 10 years of data, and tested using 2 years of data not included in constructing the model. This paper has shown that walnut yield is greatly dependent on weather conditions, particularly during fertilisation and seed growth, but the amount of available airborne pollen also plays an important role. The introduction of the seasonal pollen index, as a proxy for the amount of pollen available for fertilisation, improved the performance of models predicting walnut yield.     

Statistical method for prediction of gait kinematics with Gaussian process regression

We propose a novel methodology for predicting human gait pattern kinematics based on a statistical and stochastic approach using a method called Gaussian process regression (GPR). We selected 14 body parameters that significantly affect the gait pattern and 14 joint motions that represent gait kinematics. The body parameter and gait kinematics data were recorded from 113 subjects by anthropometric measurements and a motion capture system. We generated a regression model with GPR for gait pattern prediction and built a stochastic function mapping from body parameters to gait kinematics based on the database and GPR, and validated the model with a cross validation method. The function can not only produce trajectories for the joint motions associated with gait kinematics, but can also estimate the associated uncertainties. Our approach results in a novel, low-cost and subject-specific method for predicting gait kinematics with only the subject's body parameters as the necessary input, and also enables a comprehensive understanding of the correlation and uncertainty between body parameters and gait kinematics.