甘肃省经济增长与环境压力关系动态变化的结构分解分析

基于宏观环境经济学思想,建立了以污染物排放为表征的环境压力函数,并运用结构分解分析（SDA）模型,结合“修正后的Laspeyres方法”,构建了用于分析和解释“经济增长-环境压力”关系动态变化的驱动因子及其影响程度的方法,并分析了1990-2005年甘肃省经济增长与环境压力之间时序关系的变化趋势以及各驱动因素对时序关系变化的影响程度.结果表明：研究期间,甘肃省由污染物排放所产生的环境压力主要是由经济增长过程中产生的废气和工业固体废弃物所致,且环境压力在后期呈现出较快的增长趋势;人口因素对甘肃省环境压力变化的影响不大,经济增长因素对环境压力增大具有明显的正向效应,而技术因素则相对表现出抑制效应,但不足以抵消经济增长带来的正向效应,且经济增长和技术因素对环境压力的影响程度视不同类型污染物而有所差异.     

A structural analysis of G-quadruplex/ligand interactions

This focused review article discusses in detail, all available high-resolution small molecule ligand/G-quadruplex structural data derived from crystallographic and NMR based techniques, in an attempt to understand key factors in ligand binding and to highlight the biological importance of these complexes. In contrast to duplex DNA, G-quadruplexes are four-stranded nucleic acid structures folded from guanine rich repeat sequences stabilized by the stacking of guanine G-quartets and extensive Watson-Crick/Hoogsteen hydrogen bonding. Thermally stable, these topologies can play a role in telomere regulation and gene expression. The core structures of G-quadruplexes form stable scaffolds while the loops have been shown, by the addition of small molecule ligands, to be sufficiently adaptable to generate new and extended binding platforms for ligands to associate, either by extending G-quartet surfaces or by forming additional planar dinucleotide pairings. Many of these structurally characterised loop rearrangements were totally unexpected opening up new opportunities for the design of selective ligands. However these rearrangements do significantly complicate attempts to rationally design ligands against well defined but unbound topologies, as seen for the series of napthalene diimides complexes. Drawing together previous findings and with the introduction of two new crystallographic quadruplex/ligand structures we aim to expand the understanding of possible structural adaptations available to quadruplexes in the presence of ligands, thereby aiding in the design of new selective entities.     

Bioinformatic analysis of structural proteins of paramyxovirus Tianjin strain

The amino acid sequences of the NP,P, M, F,HN and L proteins of the paramyxovirus Tianjin strain were analyzed by using the bioinformatics methods. Phylogenetic analysis based on 6 structural proteins among the Tianjin strain and 25 paramyxoviruses showed that the Tianjin strain belonged to the genus Respirovirus, in the subfamily Paramyxovirinae, and was most closely related to Sendal virus (SeV). Phylogenetic analysis with 14 known SeVs showed that Tianjin strain represented a new evolutionary lineage. Similarities comparisons indicated that Tianjin strain P protein was poorly conserved, sharing only 78.7%-91.9% amino acid identity with the known SeVs, while the L protein was the most conserved, having 96.0%-98.0% amino acid identity with the known SeVs. Alignments of amino acid sequences of 6 structural proteins clearly showed that Tianjin strain possessed many unique amino acid substitutions in their protein sequences, 15 in NP, 29 in P, 6 in M, 13 in F, 18 in HN, and 29 in L. These results revealed that Tianjin strain was most likely a new genotype of SeV. The presence of unique amino acid substitutions suggests that Tianjin strain maybe has a significant difference in biological, pathological, immunological, or epidemiological characteristics from the known SeVs.     

Self-efficacy difference among patients with cancer with different socioeconomic status: Application of latent class analysis and standardization and decomposition analysis

IntroductionAlthough the relationship between partial socioeconomic status (SES) and self-efficacy has been studied in previous studies, few research have examined self-efficacy difference among patients with cancer with different SES.MethodsA cross-sectional survey involving 764 patients with cancer was completed. Latent class analysis (LCA) was applied to identify distinct groups of patients with cancer using four SES indicators (education, income, employment status and health insurance status). Standardization and decomposition analysis (SDA) was then used to examine differences in patients’ self-efficacy among SES groups and the components of the differences attributed to confounding factors, such as gender, age, anxiety, depression and social support.ResultsParticipants were classified into four distinctive SES groups via using LCA method, and the observed self-efficacy level significantly varied by SES groups; as theorized, higher self-efficacy was associated with higher SES. The self-efficacy differences by SES groups were decomposed into “real” group differences and factor component effects that are attributed to group differences in confounding factor compositions.ConclusionSelf-efficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer.     

MUNIN: Application of three-way decomposition to the analysis of heteronuclear NMR relaxation data**

MUNIN (Multidimensional NMR Spectra Interpretation), a recently introduced approach exploiting the mathematical concept of three-way decomposition, is proposed for separation and quantitative relaxation measurements of strongly overlapped resonances in sets of heteronuclear two-dimensional spectra that result from typical relaxation experiments. The approach is general and may also be applied to sets of two-dimensional spectra with arbitrary modulation along the third dimension (e.g., J-coupling, diffusion). Here, the method is applied for the analysis of ¹⁵N rotating frame relaxation data.     

The gender health gap in China: A decomposition analysis

Around the world, and in spite of their higher life expectancy, women tend to report worse health than men until old age. Explanations for this gender gap in self-perceived health may be different in China than in other countries due to the traditional phenomenon of son preference. We examine several possible reasons for the gap using the Chinese SAGE data. We first rule out differential reporting by gender as a possible explanation, exploiting information on anchoring vignettes in eight domains of health functioning. Decomposing the gap in general self-assessed health, we find that about 31% can be explained by socio-demographic factors, most of all by discrimination against women in education in the 20th century. A more complete specification including chronic conditions and health functioning fully explains the remainder of the gap (about 69%). Adding chronic conditions and health functioning also explains at least two thirds of the education contribution, suggesting how education may affect health. In particular, women's higher rates of arthritis, angina and eye diseases make the largest contributions to the gender health gap, by limiting mobility, increasing pain and discomfort, and causing sleep problems and a feeling of low energy.     

The protein fluorescence and structural toolkit: Database and programs for the analysis of protein fluorescence and structural data

Protein fluorescence is a powerful tool for studying protein structure and dynamics if we have a means to interpret the spectral data in terms of protein structural properties. Our previous research successfully provided this support through the development of individual software modules implementing the algorithms for fluorescence and structural analyses. Now we have integrated the developed software modules, introduced a new program for the assignment of tryptophan residues to spectral-structural classes, and created a web-based toolkit PFAST: protein fluorescence and structural toolkit: http://pfast.phys.uri.edu/. PFAST contains three modules: (1) FCAT is a fluorescence-correlation analysis tool, which decomposes protein fluorescence spectra to reveal the spectral components of individual tryptophan residues or groups of tryptophan residues located close to each other, and assigns spectral components to one of five previously established spectral-structural classes. (2) SCAT is a structural-correlation analysis tool for the calculation of the structural parameters of the environment of tryptophan residues from the atomic structures of the proteins from the Protein Data Bank (PDB), and for the assignment of tryptophan residues to one of five spectral-structural classes. (3) The last module is a PFAST database that contains protein fluorescence and structural data obtained from results of the FCAT and SCAT analyses.     

An algorithm for a decomposition of weighted digraphs: with applications to life cycle analysis in ecology

In the analysis of organism life cycles in ecology, comparisons of life cycles between species or between different types of life cycles within species are frequently conducted. In matrix population models, partitioning of the elasticity matrix is used to quantify the separate contributions of different life cycles to the population growth rate. Such partition is equivalent to a decomposition of the life cycle graph of the population. A graph theoretic spanning tree method to carry out the decomposition was formalized by Wardle [Ecology 79(7), 2539–2549 (1998)]. However there are difficulties in realizing a suitable decomposition for complex life histories using the spanning-tree method. One of the problems is the occurrence of life cycles that contain contradictory directions that defy biological interpretation. We propose an algorithmic approach for decomposing a directed, weighted graph. The graph is to be decomposed into two parts. The first part is a set of simple cycles that contain no contradictory directions and that consist of edges of equal weight. The second part of the decomposition is a subgraph in which no such simple cycles are obtainable. When applied to life cycle analysis in ecology, the proposed method will guarantee a complete decomposition of the life cycle graph into individual life cycles containing no contradictory directions. Although the research described in this article has been funded in part by the United States Environmental Protection Agency through STAR cooperative agreement R-82940201-0 to the University of Chicago, it has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Finite element analysis and computed tomography based structural rigidity analysis of rat tibia with simulated lytic defects

Finite element analysis (FEA), CT based structural rigidity analysis (CTRA) and mechanical testing is performed to assess the compressive failure load of rat tibia with simulated lytic defects.     

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.     

农田土壤枯枝落叶分解代谢的灰色分析

研究了农田土壤枯枝落叶分解代谢过程的影响因素。结果表明 ,农田土壤枯枝落叶分解速率有明显的季节变化 ;分解速率的高峰值主要是在 7,8月份。通过灰色关联分析表明 ,影响土壤枯枝落叶分解速率的主要因素是弹尾类动物、线虫类动物、无机磷转化作用和土壤含水量。建立了灰色数学模型     

Protein psychrophilicity: role of residual structural properties in adaptation of proteins to low temperatures

In order to investigate the structural distribution responsible for protein psychrophilicity, a systematic comparative analysis of 13 pairs of psychrophilic and mesophilic proteins is reported. Three kinds of residue structural states such as exposed, intermediate and buried were considered for analyzing the structural patterns of single amino acids and amino acids in different groups. The statistical test revealed that higher frequency in exposed state of Ala, higher frequency in intermediate state of His, lower frequency in buried state of Lys, lower frequency in exposed state of Gln, higher frequency in exposed state and in intermediate state of Thr, higher frequency in exposed and intermediate state of tiny and small amino acids groups could be critical factors related with protein psychrophilicity. Such structure-based differences of residual properties would help to develop a strategy for designing psychrophilic proteins.     

Winter climate change implications for decomposition in northeastern forests: comparisons of sugar maple litter with herbivore fecal inputs

Forests in northeastern North America are influenced by varying climatic and biotic factors; however, there is concern that rapid changes in these factors may lead to important changes in ecosystem processes such as decomposition. Climate change (especially warming) is predicted to increase rates of decomposition in northern latitudes. Warming in winter may result in complex effects including decreased levels of snow cover and an increased incidence of soil freezing that will effect decomposition. Along with these changes in climate, moose densities have also been increasing in this region, likely affecting nutrient dynamics. We measured decomposition and N release from ¹⁵N‐labeled sugar maple leaf litter and moose feces over 20 months in reference and snow removal treatment (to induce soil freezing) plots in two separate experiments at the Hubbard Brook Experimental Forest in New Hampshire, USA. Snow removal/soil freezing decreased decomposition of maple litter, but stimulated N transfer to soil and microbial biomass. Feces decomposed more rapidly than maple litter, and feces N moved into the mineral soil more than N derived from litter, likely due to the lower C : N ratio of feces. Feces decomposition was not affected by the snow removal treatment. Total microbial biomass (measured as microbial N and C) was not significantly affected by the treatments in either the litter or feces plots. These results suggest that increases in soil freezing and/or large herbivore populations, increase the transfer rate of N from plant detritus or digested plants into the mineral soil. Such changes suggest that altering the spatial and temporal patterns of soil freezing and moose density have important implications for ecosystem N cycling.     

应用生态网络分析方法评价中国经济系统的可持续性

将生态网络分析方法应用于中国经济系统的可持续性分析。依据1987—2010年的投入产出数据,构建中国经济系统的货币网络流,用生态网络指标量化经济系统的网络特征和变化情况,探讨中国经济系统中增长与发展的变化及其可持续性。主要结论有:(1)1987—2010年间中国经济系统的总吞吐量呈指数增长趋势,网络规模不断增长。(2)1987—2010年间中国经济的系统效率在波动中呈增加趋势,但增长幅度较小。从长期阶段看,1997—2010年间的系统效率和组织能力比1987—1995年间有明显提高,表明经济系统在后期获得了一定程度的发展。但系统效率在2002年达到高点后呈现下降趋势。(3)1987—2010年间中国经济系统的上升性和发展能力都在持续提高,但主要来自规模增长。增长和发展的量化结果表明,1987—2010年间中国经济系统上升性的提高,90%来自总吞吐量(增长),只有10%来自效率改进(发展)。(4)1987—2010年间的中国经济系统的α平均值为0.138,远小于0.37或0.33的可持续性最优平衡点,系统处于缺乏效率的不可持续的状态。要提高经济系统的可持续性,需要提高经济系统的效率(结构)和组织能力。     

The structural analysis of protein–protein interactions by NMR spectroscopy

A comprehensive understanding of protein–protein interactions is an important next step in our quest to understand how the information contained in a genome is put into action. Although a number of experimental techniques can report on the existence of a protein– protein interaction, very few can provide detailed structural information. NMR spectroscopy is one of these, and in recent years several complementary NMR approaches, including residual dipolar couplings and the use of paramagnetic effects, have been developed that can provide insight into the structure of protein–protein complexes. In this article, we review these approaches and comment on their strengths and weaknesses.     

A biochemical and structural analysis of genetic diversity within the HLA-A*11 subtype

The HLA-A*11 subtype includes 17 naturally occurring variants (-A*1101 to -A*1117) distributed among different ethnic groups worldwide. At present, only HLA-A*1101 has been characterized at the molecular, structural, and immunological level. Developing similar knowledge on other HLA-A*11 alleles is highly important for bone marrow and graft transplantation. This is also important to better understand disease linkages within the HLA-A*11 subtype given that HLA-A*11 molecules are associated with resistance to acquisition of HIV-1 infection and various autoimmune diseases. To broaden our understanding of HLA-A*11 molecules, we have determined the impact of natural polymorphism on the peptide-binding properties of several HLA-A*11 molecules: -A*1103, -A*1106, -A*1108, -A*1110, -A*1111, and -A*1114. We used an approach that combines data from thermal stability studies of recombinant, soluble forms of these molecules in complex with HIV-1 peptides, together with a detailed structural analysis of the resulting HLA-A*11 molecule/peptide complexes based on crystal and molecular model structures. Our analysis shows that natural polymorphism within the HLA-A*11 subtype is distributed along the 1 and 2 helices of the peptide-binding groove, in marked contrast to the pattern of polymorphism in HLA-A*2 and HLA-B*27 subtypes. Natural polymorphism greatly altered the abilities of individual -A*11 molecules to form stable complexes with HIV-1 peptides. In comparison to -A*1101, natural polymorphism altered the peptide-presenting properties of -A*1103, -A*1108, and -A*1114 and has the potential to affect the peptide-selecting properties of -A*1106, -A*1110, and -A*1111 as well. Overall, our findings suggest that HLA-A*11 molecules may stimulate alloreactive CD8+ cytotoxic T-cell responses.     

基于能源代谢分析的南昌市能源消费碳排放综合生态效率研究

有关能源消费的代谢机理及生态效率研究是当前生态经济研究领域中的重点和难点,也是政府决策部门、相关行业及人群关注的热点。基于能源代谢分析理念,构建了基于相对变量的城市能源消费碳排放综合生态效率度量模型,对2000—2013年南昌市能源消费结构、碳排放量及其生态效率进行了测算与分析。结果表明:(1)南昌市在2000—2013年,能源消费量和碳排放量整体上呈"N"型曲线上升的一致性变化特征,主要经历了快速增长、短暂下降、恢复平稳增长3个阶段,且煤炭是南昌市能源消费和碳排放的主要来源,短时期内难以改变;(2)南昌市的能源消费效率和碳排放效率整体上在不断优化;(3)南昌市能源消费碳排放综合生态效率经历了较大的波动变化,整体上的生态效率分值并不高;仍需要加大节能减排力度,全面优化南昌市能源消费结构。