A microprocedure for extracting tissue nucleotides for analysis by high-performance liquid chromatography.

A method is described for the preparation of concentrated tissue extracts for nucleotideanalysis by high-performance liquid chromatography (hplc). Ten to one hundred milligrams of tissue was extracted in a combined weighing-homogenizing-centrifuge tube using a trichloracetic acid (TCA)-methanol extractant containing a radioactive internal standard. This extractant eliminated nucleotide interconversion which was found to occur when TCA alone was employed. High ATP/ADP and ATP/AMP ratios were observed and recoveries of greater than 97% were obtained with exogenous radioactive nucleotides. The method has been applied successfully in studies on muscle, heart, liver, kidney, lung, brain, and subcellular fractions.     

Exploration research on the fusion of multimodal spectrum technology to improve performance of rapid diagnosis scheme for thyroid dysfunction

The spectral fusion by Raman spectroscopy and Fourier infrared spectroscopy combined with pattern recognition algorithms is utilized to diagnose thyroid dysfunction serum, and finds the spectral segment with the highest sensitivity to further advance diagnosis speed. Compared with the single infrared spectroscopy or Raman spectroscopy, the proposal can improve the detection accuracy, and can obtain more spectral features, indicating greater differences between thyroid dysfunction and normal serum samples. For discriminating different samples, principal component analysis (PCA) was first used for feature extraction to reduce the dimension of high‐dimension spectral data and spectral fusion. Then, support vector machine (SVM), back propagation neural network, extreme learning machine and learning vector quantization algorithms were employed to establish the discriminant diagnostic models. The accuracy of spectral fusion of the best analytical model PCA‐SVM, single Raman spectral accuracy and single infrared spectral accuracy is 83.48%, 78.26% and 80%, respectively. The accuracy of spectral fusion is higher than the accuracy of single spectrum in five classifiers. And the diagnostic accuracy of spectral fusion in the range of 2000 to 2500 cm^?1 is 81.74%, which greatly improves the sample measure speed and data analysis speed than analysis of full spectra. The results from our study demonstrate that the serum spectral fusion technique combined with multivariate statistical methods have great potential for the screening of thyroid dysfunction.     

Functional traits,convergent evolution,and periodic tables of niches

Ecology is often said to lack general theories sufficiently predictive for applications. Here, we examine the concept of a periodic table of niches and feasibility of niche classification schemes from functional trait and performance data. Niche differences and their influence on ecological patterns and processes could be revealed effectively by first performing data reduction/ordination analyses separately on matrices of trait and performance data compiled according to logical associations with five basic niche ‘dimensions’, or aspects: habitat, life history, trophic, defence and metabolic. Resultant patterns then are integrated to produce interpretable niche gradients, ordinations and classifications. Degree of scheme periodicity would depend on degrees of niche conservatism and convergence causing species clustering across multiple niche dimensions. We analysed a sample data set containing trait and performance data to contrast two approaches for producing niche schemes: species ordination within niche gradient space, and niche categorisation according to trait‐value thresholds. Creation of niche schemes useful for advancing ecological knowledge and its applications will depend on research that produces functional trait and performance datasets directly related to niche dimensions along with criteria for data standardisation and quality. As larger databases are compiled, opportunities will emerge to explore new methods for data reduction, ordination and classification.     

Unraveling the efficiency of RAPD and SSR markers in diversity analysis and population structure estimation in common bean

Increase in food production viz-a-viz quality of food is important to feed the growing human population to attain food as well as nutritional security. The availability of diverse germplasm of any crop is an important genetic resource to mine the genes that may assist in attaining food as well as nutritional security. Here we used 15 RAPD and 23 SSR markers to elucidate diversity among 51 common bean genotypes mostly landraces collected from the Himalayan region of Jammu and Kashmir, India. We observed that both the markers are highly polymorphic. The discriminatory power of these markers was determined using various parameters like; percent polymorphism, PIC, resolving power and marker index. 15 RAPDs produced 171 polymorphic bands, while 23 SSRs produced 268 polymorphic bands. SSRs showed a higher PIC value (0.300) compared to RAPDs (0.243). Further the resolving power of SSRs was 5.241 compared to 3.86 for RAPDs. However, RAPDs showed a higher marker index (2.69) compared to SSRs (1.279) that may be attributed to their higher multiplex ratio. The dendrograms generated with hierarchical UPGMA cluster analysis grouped genotypes into two main clusters with various degrees of sub clustering within the cluster. Here we observed that both the marker systems showed comparable accuracy in grouping genotypes of common bean according to their area of cultivation. The model based STRUCTURE analysis using 15 RAPD and 23 SSR markers identified a population with 3 sub-populations which corresponds to distance based groupings. High level of genetic diversity was observed within the population. These findings have further implications in common bean breeding as well as conservation programs.     

Gap regeneration in primary evergreen broad-leaved forests with or without a major canopy tree,Distylium racemosum,southwestern Japan: A comparative analysis

Gap regeneration was studied in a typical primary evergreen broad-leaved forest withoutDistylium racemosum, at the Kasugayama Forest Reserve, southwestern Japan and the results were compared with those from other primary evergreen broad-leaved forests in southwestern Japan, whereD. racemosum was the dominant species. Several common types of gap regeneration behavior were recognized among the major tree species and forests with or withoutD. racemosum consisted of three typical regeneration guilds which could be detected in the principal component analysis.Castanopsis cuspidata frequently regenerated in gaps from saplings recruited before gap formation in the forest withoutD. racemosum, although elsewhere, in forests withD. racemosum, it lacked advanced regeneration and regenerated in gaps from saplings recruited after gap formation. Some evergreenQuercus had their regenerations in gaps of the forest withoutD. racemosum, although elsewhere, in forests withD. racemosum, evergreenQuercus might not regenerate. The results indicate that tree species may change their regeneration behavior depending on the presence or absence of another key dominant species. This suggests that the presence and the dominance of a potential competitor induces shifts in the regeneration niche of other coexisting tree species.     

Environmental diversity: on the best-possible use of surrogate data for assessing the relative biodiversity of sets of areas

The conservation goal of representation of biodiversity (in the broad sense of all species) in protected areas requires best-possible use of available surrogate information. One standard approach is based on indicator groups of taxa. A minimum set of areas having at least one representation of each indicator species is taken to be representative of other organisms. This same minimum-set approach is adapted to other attributes of biodiversity, for example, derived environmental clusters. A weakness of these approaches is that useful information is lost; for example, for environmental clusters, there is no distinction made either among or within clusters. A more powerful surrogate approach can use some expression of environmental and/or biotic pattern so that variation among areas is seen as part of a continuum rather than partitioned into arbitrary clusters/attributes. The challenge in using pattern effectively is to adopt a robust model for the relationship between pattern and the underlying units of biodiversity, i.e. species. An environmental space (a continuum or ordination pattern), combined with the standard ecological continuum model relating species to environmental space, has advantages over other patterns based on hierarchy or distance matrices. Because an environmental space can be estimated either directly (observed environmental data) or indirectly (data on indicator groups), the corresponding surrogate-measure of biodiversity, environmental diversity (ED) makes best-possible use of either kind of data. We conclude that the arbitrariness of the attribute approach can be replaced by a robust surrogate pattern approach that is flexible and avoids unwarranted assumptions.     

Muscle RING-finger protein-1 (MuRF1) as a connector of muscle energy metabolism and protein synthesis

During pathophysiological muscle wasting, a family of ubiquitin ligases, including muscle RING-finger protein-1 (MuRF1), has been proposed to trigger muscle protein degradation via ubiquitination. Here, we characterized skeletal muscles from wild-type (WT) and MuRF1 knockout (KO) mice under amino acid (AA) deprivation as a model for physiological protein degradation, where skeletal muscles altruistically waste themselves to provide AAs to other organs. When WT and MuRF1 KO mice were fed a diet lacking AA, MuRF1 KO mice were less susceptible to muscle wasting, for both myocardium and skeletal muscles. Under AA depletion, WT mice had reduced muscle protein synthesis, while MuRF1 KO mice maintained nonphysiologically elevated levels of skeletal muscle protein de novo synthesis. Consistent with a role of MuRF1 for muscle protein turnover during starvation, the concentrations of essential AAs, especially branched-chain AAs, in the blood plasma significantly decreased in MuRF1 KO mice under AA deprivation. To clarify the molecular roles of MuRF1 for muscle metabolism during wasting, we searched for MuRF1-associated proteins using pull-down assays and mass spectrometry. Muscle-type creatine kinase (M-CK), an essential enzyme for energy metabolism, was identified among the interacting proteins. Coexpression studies revealed that M-CK interacts with the central regions of MuRF1 including its B-box domain and that MuRF1 ubiquitinates M-CK, which triggers the degradation of M-CK via proteasomes. Consistent with MuRF1's role of adjusting CK activities in skeletal muscles by regulating its turnover in vivo, we found that CK levels were significantly higher in the MuRF1 KO mice than in WT mice. Glucocorticoid modulatory element binding protein-1 and 3-hydroxyisobutyrate dehydrogenase, previously identified as potential MuRF1-interacting proteins, were also ubiquitinated MuRF1-dependently. Taken together, these data suggest that, in a multifaceted manner, MuRF1 participates in the regulation of AA metabolism, including the control of free AAs and their supply to other organs under catabolic conditions, and in the regulation of ATP synthesis under metabolic-stress conditions where MuRF1 expression is induced.     

A problem in multivariate analysis of codon usage data and a possible solution

Multivariate analyses are often used to identify major trends of variation in synonymous codon usage among genes. These analyses need to be performed on properly normalized codon usage data to avoid biases masking this synonymous variation, i.e., gene length, amino acid usage, and codon degeneracy; however, previous studies have failed to do so. In this paper, we demonstrate that the use of alternative normalized data (called 'relative adaptiveness' in the literature) can avoid all these biases and furthermore, can identify more trends of variation among genes, including GC-ending codon usage, GT-ending codon usage, and gene expression level.     

辽东山区天然次生林的数量分类

结合DCA排序和TW IN SPAN分类结果,将辽东山区天然次生林划分为5个群落类型:花曲柳林、蒙古栎林、阔叶混交林、水曲柳林、胡桃楸林。DCA排序与TW IN SPAN分类产生了较一致的分类结果。DCA第一轴代表的环境意义为坡向。花曲柳林多分布于阳坡的中坡及中上坡,蒙古栎林多分布在中上坡。花曲柳与蒙古栎常混生在一起,随着坡位上升,花曲柳优势度下降,而蒙古栎优势度增加。阔叶混交林多位于阴坡,乔木层没有稳定和绝对优势种,多以假色槭、风桦、色木槭为优势种,但假色槭分布于乔木层第2亚层。水曲柳林多分布在中下坡。胡桃楸分布在山下部,喜潮湿生境。色木槭在辽东山区分布广泛,重要值较高,且更新良好,很可能是群落演替顶级物种。辽东山区天然次生林林下藤本植株数量多,以五味子、软枣猕猴桃、狗枣猕猴桃为主。