Selective incorporation of 5-hydroxytryptophan blocks long range electron transfer in oxalate decarboxylase

Oxalate decarboxylase from Bacillus subtilis is a binuclear Mn-dependent acid stress response enzyme that converts the mono-anion of oxalic acid into formate and carbon dioxide in a redox neutral unimolecular disproportionation reaction. A π-stacked tryptophan dimer, W96 and W274, at the interface between two monomer subunits facilitates long-range electron transfer between the two Mn ions and plays an important role in the catalytic mechanism. Substitution of W96 with the unnatural amino acid 5-hydroxytryptophan leads to a persistent EPR signal which can be traced back to the neutral radical of 5-hydroxytryptophan with its hydroxyl proton removed. 5-Hydroxytryptophan acts as a hole sink preventing the formation of Mn(III) at the N-terminal active site and strongly suppresses enzymatic activity. The lower boundary of the standard reduction potential for the active site Mn(II)/Mn(III) couple can therefore be estimated as 740 mV against the normal hydrogen electrode at pH 4, the pH of maximum catalytic efficiency. Our results support the catalytic importance of long-range electron transfer in oxalate decarboxylase while at the same time highlighting the utility of unnatural amino acid incorporation and specifically the use of 5-hydroxytryptophan as an energetic sink for hole hopping to probe electron transfer in redox proteins.     

Latent group detection in functional partially linear regression models

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. We develop an algorithm in the spirit of the K-means clustering to identify latent groups of the subjects under study. We establish the consistency of the proposed estimator, derive the convergence rate and the asymptotic distribution, and develop inference procedures. We show by simulation studies that the proposed method has higher accuracy for recovering latent groups and for estimating the functional coefficients than existing methods. The analysis of the barley data shows that the proposed method can help identify groups of barley families with different salinity tolerant abilities.     

Variable selection in nonlinear function-on-scalar regression

We develop a new method for variable selection in a nonlinear additive function-on-scalar regression (FOSR) model. Existing methods for variable selection in FOSR have focused on the linear effects of scalar predictors, which can be a restrictive assumption in the presence of multiple continuously measured covariates. We propose a computationally efficient approach for variable selection in existing linear FOSR using functional principal component scores of the functional response and extend this framework to a nonlinear additive function-on-scalar model. The proposed method provides a unified and flexible framework for variable selection in FOSR, allowing nonlinear effects of the covariates. Numerical analysis using simulation study illustrates the advantages of the proposed method over existing variable selection methods in FOSR even when the underlying covariate effects are all linear. The proposed procedure is demonstrated on accelerometer data from the 2003–2004 cohorts of the National Health and Nutrition Examination Survey (NHANES) in understanding the association between diurnal patterns of physical activity and demographic, lifestyle, and health characteristics of the participants.     

Functional data analysis with covariate-dependent mean and covariance structures

Functional data analysis has emerged as a powerful tool in response to the ever-increasing resources and efforts devoted to collecting information about response curves or anything that varies over a continuum. However, limited progress has been made with regard to linking the covariance structures of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate-dependent mean and covariance structures. Particularly, by allowing variances of random scores to be covariate-dependent, we identify eigenfunctions for each individual from the set of eigenfunctions that govern the variation patterns across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi-likelihood procedure that combines regularization and B-spline smoothing for model selection and estimation and establish the convergence rate and asymptotic normality of the proposed estimators. The utility of the developed method is demonstrated via simulations, as well as an analysis of the Avon Longitudinal Study of Parents and Children concerning parental effects on the growth curves of their offspring, which yields biologically interesting results.     

A meta-analysis on morphological,physiological and biochemical responses of plants with PGPR inoculation under drought stress

Plant growth-promoting rhizobacteria (PGPR) can help plants to resist drought stress. However, the mechanisms of how PGPR inoculation affect plant status under drought remain incompletely understood. We performed a meta-analysis of plant response to PGPR inoculation by compiling data from 57 PGPR-inoculation studies, including 2, 387 paired observations on morphological, physiological and biochemical parameters under drought and well-watered conditions. We compare the PGPR effect on plants performances among different groups of controls and treatments. Our results reveal that PGPR enables plants to restore themselves from drought-stressed to near a well-watered state, and that C4 plants recover better from drought stress than C3 plants. Furthermore, PGPR is more effective underdrought than well-watered conditions in increasing plant biomass, enhancing photosynthesis and inhibiting oxidant damage, and the responses of C4 plants to the PGPR effect was stronger than that of C3 plants under drought conditions. Additionally, PGPR belonging to different taxa and PGPR with different functional traits have varying degrees of drought-resistance effects on plants. These results are important to improve our understanding of the PGPR beneficial effects on enhanced drought-resistance of plants.     

食源性致病菌激活NLRP3炎症小体及食源性功能物质的抑制机理研究进展

食源性致病菌感染是引起食源性疾病的首要因素,严重影响人类健康。炎症小体通过识别受体感知入侵宿主的危险信号进而组装形成多聚蛋白复合物,从而诱导炎症反应,是先天免疫系统中识别食源性病原菌感染和清除病原体的重要防线。NLRP3炎症小体是位于胞内的炎症反应平台,可以感知多种病原微生物的侵袭,在先天性免疫反应中起着至关重要的作用。食源性致病菌感染常引起NLRP3炎症小体的异常激活,介导多种炎症性疾病的发生和发展,因此,许多抗炎研究中常常以NLRP3炎症小体作为靶点。本文总结了食源性致病菌及其代谢产物激活NLRP3炎症小体的分子机制,以及天然产物和膳食功能物质抑制NLRP3炎症小体激活的机理,为治疗炎症性疾病、开发缓解致病菌诱导的炎症反应的功能化合物提供新的思路。     

偏头痛患者体感刺激下脑电信号的功能连接（英文）

目的 偏头痛是一种复杂的脑功能障碍性疾病,全球范围内患病率为14.4%。功能连接测量两个神经信号之间的统计学相互依赖性,不同的功能连接反映了大脑区域协同工作的不同模式。因此,研究不同脑区的功能连接对于理解偏头痛的病理生理机制具有十分重要的意义。以往基于脑电图对偏头痛患者脑功能连接的分析主要集中在视觉和疼痛刺激。本文尝试研究偏头痛患者在发作间期对体感刺激的皮质反应,以进一步了解偏头痛的神经功能障碍,为偏头痛的预防和治疗提供线索。方法 招募23例无先兆偏头痛患者,10例有先兆偏头痛患者,28名健康对照者。所有受试者均进行详细的基本资料和病史采集,完善量表评估,在正中神经体感刺激下进行脑电图记录。计算68个脑区的相干性作为功能连接,并评估功能连接与临床参数的相关性。结果 在正中神经体感刺激下,无先兆偏头痛和有先兆偏头痛患者的脑电功能连接与对照组相比存在差异,异常的脑电功能连接主要位于感觉辨别、疼痛调节、情绪认知和视觉处理等区域。无先兆偏头痛和有先兆偏头痛患者的大脑皮层对体感刺激可能具有相同的反应方式。偏头痛患者的功能连接异常与临床特征之间存在相关性,可以部分反映偏头痛的严重程度。结论 本研究...     

晋北典型针叶人工林叶功能性状特征及其与土壤因子的关系

为了解释植物叶片的资源分配特征及其与土壤因子间的适应策略,该研究以黄土高原东北缘山西省大同市新荣区油松、樟子松人工纯林及其柠条混交林为对象,采用样方法采集样木树冠中部生长良好的轮生枝中东西南北4个方向的枝条,并在每个枝条上选择里、中、外3处有代表性的当年生叶和多年生叶;采用 “S”形采样法在每个样方内选取9个取样点,用土钻采集各样点0～20 cm土壤样品;测定分析不同造林模式下油松、樟子松异龄叶功能性状特征、土壤理化性质以及二者的关系,为人工林培育及经营提供理论支撑。结果表明：(1)不同造林模式下油松及樟子松叶功能性状的差异集中在化学计量之间;随着叶龄增长,油松、樟子松均表现出干物质含量上升,氮磷含量下降的特征。(2)土壤全磷、全氮含量分别是油松当年及多年生叶的主要解释因子,土壤全磷与当年生叶碳氮比、有机碳、碳磷比均呈显著正相关关系,与全氮、叶面积及叶干物质含量呈显著负相关关系,土壤全氮与多年生叶全磷含量呈正相关关系,与叶有机碳、碳磷比、碳氮比则呈显著负相关关系。(3)樟子松当年生叶功能性状的关键土壤因子是土壤容重、全磷含量,其与叶碳氮磷的比值、干物质含量、碳含量呈正相关关系,而与氮磷含量呈负相关关系;多年生叶功能性状的关键土壤因子是土壤容重、含水量、pH,其与叶氮磷含量呈正相关关系,与碳含量、干物质含量、比叶面积等呈负相关关系。(4)油松及樟子松纯林的叶功能性状更易向关键土壤因子含量更高的方向偏移,说明与柠条混交可有效分异叶片生长对主要土壤因子的集中需求,但混交造林模式下林木长势有所衰弱;结合研究区资源匮乏现状,林木种植密度较大,竞争加剧了生存压力导致林木生长受限。     

寄主植物对桑寄生植物叶片功能性状的影响

为了解寄生植物叶片功能性状的差异及其影响因素,研究了西双版纳地区寄主植物对3种桑寄生植物叶片功能性状的影响,并分析了桑寄生植物与寄主植物叶片功能性状的相关性。结果表明,不同寄主植物的相同寄生植物叶片功能性状存在显著差异,来自7种寄主植物的五蕊寄生(Dendrophthoe pentandra)的叶片含水量(61.2%～70.1%)、氮含量(9.6～16.0 g/kg)、碳氮比(30.8～48.5)以及缩合单宁含量(3.3%～11.0%)等性状的差异较大;从4种寄主植物上获取的澜沧江寄生(Scurrula chingii var.yunnanensis)的叶片含水量(60.0%～71.7%)、碳含量(431.3～502.3 g/kg)和缩合单宁含量(3.8%～9.9%)等性状也呈现较大种间差异,而在2种寄主植物上的离瓣寄生(Helixanthera parasitica)的叶片功能性状没有显著差异。桑寄生植物与寄主植物的叶片含水量、总碳含量、总氮含量、碳氮比和缩合单宁含量呈显著的正相关。寄主植物作为桑寄生植物营养物质的主要来源,会影响桑寄生植物叶片的相应功能性状。桑寄生植物能从寄主植物获...     

TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample

Genetic studies on attention have mainly focused on children with attention-deficit/hyperactivity disorder (ADHD), so little systematic research has been conducted on genetic correlates of attention performance and their potential brain mechanisms among healthy individuals. The current study included a genome-wide association study (GWAS, N = 1145 healthy young adults) aimed to identify genes associated with sustained attention and an imaging genetics study (an independent sample of 483 healthy young adults) to examine any identified genes' influences on brain function. The GWAS found that TTLL11 showed genome-wide significant associations with sustained attention, with rs13298112 as the most significant SNP and the GG homozygotes showing more impulsive but also more focused responses than the A allele carriers. A retrospective examination of previously published ADHD GWAS results confirmed an un-reported, small but statistically significant effect of TTLL11 on ADHD. The imaging genetics study replicated this association and showed that the TTLL11 gene was associated with resting state activity and connectivity of the somatomoter network, and can be predicted by dorsal attention network connectivity. Specifically, the GG homozygotes showed lower brain activity, weaker brain network connectivity, and non-significant brain-attention association compared to the A allele carriers. Expression database showed that expression of this gene is enriched in the brain and that the G allele is associated with lower expression level than the A allele. These results suggest that TTLL11 may play a major role in healthy individuals' attention performance and may also contribute to the etiology of ADHD.