Microsecond Dynamics During the Binding-induced Folding of an Intrinsically Disordered Protein

Tau is an intrinsically disordered protein implicated in many neurodegenerative diseases. The repeat domain fragment of tau, tau-K18, is known to undergo a disorder to order transition in the presence of lipid micelles and vesicles, in which helices form in each of the repeat domains. Here, the mechanism of helical structure formation, induced by a phospholipid mimetic, sodium dodecyl sulfate (SDS) at sub-micellar concentrations, has been studied using multiple biophysical probes. A study of the conformational dynamics of the disordered state, using photoinduced electron transfer coupled to fluorescence correlation spectroscopy (PET-FCS) has indicated the presence of an intermediate state, I, in equilibrium with the unfolded state, U. The cooperative binding of the ligand (L), SDS, to I has been shown to induce the formation of a compact, helical intermediate (IL₅) within the dead time (∼37 µs) of a continuous flow mixer. Quantitative analysis of the PET-FCS data and the ensemble microsecond kinetic data, suggests that the mechanism of induction of helical structure can be described by a U ↔ I ↔ IL₅ ↔ FL₅ mechanism, in which the final helical state, FL₅, forms from IL₅ with a time constant of 50–200 µs. Finally, it has been shown that the helical conformation is an aggregation-competent state that can directly form amyloid fibrils.     

Dispersion population models discrete in time and continuous in space

We analyze a discrete-time model of populations that grow and disperse in separate phases. The growth phase is a nonlinear process that allows for the effects of local crowding. The dispersion phase is a linear process that distributes the population throughout its spatial habitat. Our study quantifies the issues of survival and extinction, the existence and stability of nontrivial steady states, and the comparison of various dispersion strategies. Our results show that all of these issues are tied to the global nature of various model parameters. The extreme strategies of staying-in place and going-everywhere-uniformly are compared numerically to diffusion strategies in various contexts. We approach the mathematical analysis of our model from a functional analysis and an operator theory point of view. We use recent results from the theory of positive operators in Banach lattices.     

Phosphorus efficiency of plants

Föhse et al. (1988) have shown that P influx per unit root length in seven plant species growing in a low-P soil varied from 0.6×10^-14 to 4.8×10^-14 mol cm^-1s^-1. The objective of this work was to investigate the reasons for these differences. No correlation was found between P influx and root radius, root hairs, cation-anion balance and Ca uptake. However, when root hairs were included in mathematical model calculations, the differences of P influx could be accounted for. These calculations have shown that in soils low in available P, contribution to P uptake by root hairs was up to 90% of total uptake. The large contribution of root hairs to P uptake was partly due to their surface area, which was similar to that of the root cylinder. However, the main reason for the high P uptake efficiency of root hairs was their small radius (approx. 5×10^-4 cm) and their perpendicular growth into the soil from the root axis. Because of the small radius compared to root axes, P concentration at root hair surfaces decreased at a slower pace and therefore P influx remained higher. Under these conditions higher I_max (maximum influx) or smaller K_m values (Michaelis constant) increased P influx. The main reasons for differences found in P influx among species were the size of I_max and the number and length of root hairs. In a soil low in available P, plant species having more root hairs were able to satisfy a higher proportion of their P demand required for maximum growth.     

具有节点偏置的高阶神经网络模型

在汪涛文献基础上提出了一个具有节点偏置的高阶神经网络模型、给出了模型的哈密顿量和学习算法,证明了学习算法的收敛性,该模型能对每一神经元自动引入一个节点偏置使得网络能够存储所有学习图样包括相关图样,其存储容量远高于Hebb—rule—like学习算法下的高阶神经网络模型.对由30个神经元组成的二阶神经网络进行了计算机仿真,结果证实了上述结论.此外,对初始突触强度对学习效果的影响和不同存储图样数目下的平均吸引半径进行了仿真计算并分析了所得结果.新模型的特点使其具有良好的应用前景     

中医正骨手法改善桡骨远端伸直型骨折患者腕关节功能的临床研究及疗效的影响因素分析

摘要 目的：观察中医正骨手法在桡骨远端伸直型骨折中的临床应用价值,并分析疗效的影响因素。方法：选择四川省骨科医院2020年1月~2022年1月期间收治的桡骨远端伸直型骨折患者152例,按照治疗方式的不同将患者分为对照组（给予石膏固定）和研究组（应用中医正骨手法治疗）,例数分别为77例和75例。对比两组优良率、临床指标、腕关节活动度和X线相关影像学指标。同时采用多因素Logistic回归分析影响研究组腕关节功能疗效的相关因素。结果：治疗后,研究组的优良率明显高于对照组（P<0.05）。研究组手背消肿时间、疼痛缓解时间、骨折愈合时间均短于对照组（P<0.05）。两组治疗后12周掌屈、背伸、桡偏、尺偏、旋前、旋后活动度均扩大,且研究组均大于对照组（P<0.05）。两组治疗后12周掌倾角、尺偏角、桡骨高度均增加,且研究组均大于对照组（P<0.05）。单因素分析显示,研究组腕关节功能优良率与年龄、性别、骨质疏松、功能锻炼、掌倾角、尺偏角、桡骨高度、骨折端稳定性、受伤能量、利手情况有关（P<0.05）,而与体质量指数、就诊时间、基础疾病、骨折类型、固定时间无关（P>0.05）。多因素Logistic回归分析显示：性别为女、骨质疏松、无功能锻炼、掌倾角偏小、桡骨高度偏短、骨折端不稳定、受伤能量为高能量、利手是影响腕关节功能优良率的危险因素（P<0.05）。结论：中医正骨手法可有效改善桡骨远端伸直型骨折患者腕关节功能,减少骨折愈合及疼痛缓解时间。此外,患者腕关节功能的优良率还受到性别、骨质疏松、功能锻炼、掌倾角、桡骨高度、骨折端稳定性、受伤能量、利手情况的影响,值得引起临床重视。     

对分子置换法中积分半径选取方法的探讨

通过对晶胞中帕特逊向量的统计分布的研究,从理论上阐述了根据模型结构单元的线度确定旋转函数的积分半径这种作法的合理性,并且指出了估算积分半径取值范围的具体方法,以及自身旋转函数与交叉旋转函数的积分半径取值范围的区别。经过我们将此方法应用于酚胰岛素Ｂ链羰端六肽胰岛素的旋转函数求解,计算结果证实了这种积分半径的估算方法的可靠性。     

Author index

Using dynamic light scattering we have been able to determine precisely the hydrodynamic radius of l-α-dimyristoylphosphatidylcholine (DMPC) vesicles as a function of temperature. We have detected a sharp, thermally reversible change in the vesicle radius at a phase transition temperature 24°C, corresponding to an approximate 11% increase in surface are. In the range 10–20°C, the change in radius is less than 1%.     

Dynamic structure of metallothionein

Molecular sieve chromatography of rabbit liver metallothionein at different electrolyte concentrations revealed that this protein undergoes an increase in Stokes radius from 1.50 to 1.78 nm when the ionic strength is lowered from 0.5 to 0.015 indicating a change in molecular shape and/or hydration. The variation in ionic strength also affects the far-UV circular dichroism of metallothionein reflecting a conformational transition in the protein. The effects are attributed to changes in intramolecular repulsion between the strongly negatively charged metal-thiolate clusters of the protein. It is suggested that metallothionein exists in at least two interchangeable conformational states which differ in hydrodynamic properties and whose equilibrium concentrations are determined by the electrostatic free energy of the system.     

Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data

Relatively simple foraging radius models have the potential to generate predictive distributions for a large number of species rapidly, thus providing a cost-effective alternative to large-scale surveys or complex modelling approaches. Their effectiveness, however, remains largely untested. Here we compare foraging radius distribution models for all breeding seabirds in Ireland, to distributions of empirical data collected from tracking studies and aerial surveys. At the local/colony level, we compared foraging radius distributions to GPS tracking data from seabirds with short (Atlantic puffin Fratercula arctica, and razorbill Alca torda) and long (Manx shearwater Puffinus puffinus, and European storm-petrel Hydrobates pelagicus) foraging ranges. At the regional/national level, we compared foraging radius distributions to extensive aerial surveys conducted over a two-year period. Foraging radius distributions were significantly positively correlated with tracking data for all species except Manx shearwater. Correlations between foraging radius distributions and aerial survey data were also significant, but generally weaker than those for tracking data. Correlations between foraging radius distributions and aerial survey data were benchmarked against generalised additive models (GAMs) of the aerial survey data that included a range of environmental covariates. While GAM distributions had slightly higher correlations with aerial survey data, the results highlight that the foraging radius approach can be a useful and pragmatic approach for assessing breeding distributions for many seabird species. The approach is likely to have acceptable utility in complex, temporally variable ecosystems and when logistic and financial resources are limited.     

The pulse of the tree is under genetic control: eucalyptus as a case study

The pulse of the tree (diurnal cycle of stem radius fluctuations) has been widely studied as a way of analyzing tree responses to the environment, including the phenotypic plasticity of tree–water relationships in particular. However, the genetic basis of this daily phenotype and its interplay with the environment remain largely unexplored. We characterized the genetic and environmental determinants of this response, by monitoring daily stem radius fluctuation (dSRF) on 210 trees from a Eucalyptus urophylla × E. grandis full‐sib family over 2 years. The dSRF signal was broken down into hydraulic capacitance, assessed as the daily amplitude of shrinkage (DA), and net growth, estimated as the change in maximum radius between two consecutive days (ΔR). The environmental determinants of these two traits were clearly different: DA was positively correlated with atmospheric variables relating to water demand, while ΔR was associated with soil water content. The heritability for these two traits ranged from low to moderate over time, revealing a time‐dependent or environment‐dependent complex genetic determinism. We identified 686 and 384 daily quantitative trait loci (QTL) representing 32 and 31 QTL regions for DA and ΔR, respectively. The identification of gene networks underlying the 27 major genomics regions for both traits generated additional hypotheses concerning the biological mechanisms involved in response to water demand and supply. This study highlights that environmentally induced changes in daily stem radius fluctuation are genetically controlled in trees and suggests that these daily responses integrated over time shape the genetic architecture of mature traits.