林隙对香樟和枫香幼苗早期生长阶段功能性状的影响

探究林隙对不同需光性树种早期生长特征和功能性状的影响,对揭示林隙微生境影响次生林内幼苗更新机制具有重要意义。以亚热带次生林中耐荫常绿树种香樟和阳性落叶树种枫香幼苗为试验对象,研究大林隙(D/H介于1.5—2.0)、中林隙(D/H介于1.0—1.5)和小林隙(D/H介于0.5—1.0)对不同需光树种幼苗早期(1—3年生)生长特征和功能性状的影响。结果表明：(1)林隙大小对两种幼苗的生长均有显著影响。其中,中林隙可显著促进香樟2—3年生幼苗的生长,大林隙对枫香1—3年生幼苗的生长均具有显著促进作用。(2)对林隙环境因子与幼苗功能性状的关系进行冗余分析表明,香樟幼苗功能性状的变化与林隙土壤有机质含量、水解性氮含量、酸碱度和有效磷含量密切相关,而枫香幼苗功能性状则主要受林隙土壤酸碱度、有机质含量、水解性氮含量、土壤含水率、冠层透光率和土壤有效磷含量的影响。(3)维持较高的根重比、细根比根长、叶碳氮比和叶碳磷比是幼苗应对林隙环境影响的重要生理生态调节机制。     

荒漠植物不同功能群性状特征及其与土壤环境的关系

研究不同功能群植物性状差异及其与土壤环境关系对于充分掌握植物的环境适应策略至关重要。以艾比湖流域为研究区,利用荒漠植物的植物高度、叶片碳、氮、磷、硫、钾、钙、钠、镁含量等9个性状,将高、低土壤水盐环境下的植物划分为5个功能群,分析不同功能群的植物组成、性状差异及其与土壤环境的关系。结果表明：(1)不同土壤水盐环境下,其植物功能群组成不同;其中白刺、胡杨和罗布麻在两个土壤水盐环境下的功能群中均存在。(2)植物的功能性状在不同土壤水盐环境下也发生了适应性的变化。高土壤水盐环境下3个功能群的植物高度、叶片碳、氮、磷和钙含量显著高于低土壤水盐环境功能群(P<0.05);低土壤水盐环境下2个功能群的植物叶片硫、钠和镁含量高于高土壤水盐环境功能群。(3)土壤含水量(SVWC)、电导率(EC)、pH以及土壤磷含量对荒漠植物功能性状影响较大。在高土壤水盐环境下,EC、pH与植物高度,叶片钾、钙含量正相关,与叶片硫含量负相关;在低土壤水盐环境下,SVWC、EC与植物高度呈显著正相关(P<0.05)。研究有助于理解荒漠植物对极端环境的适应对策,为保护荒漠地区生物多样性提供理论依据。     

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。     

基于叶绿体基因组数据的芸香科属间系统发育初步分析（专题约稿）

该研究在人工控制水分条件下,设置3个干旱胁迫处理,选用3个主栽油菜品种‘陇油10号’、‘陇油2号’、‘青杂5号’幼苗进行盆栽试验,测定干旱胁迫条件下叶片相对含水量、叶绿素含量、光合气体交换参数及叶绿素荧光参数等指标,考察各指标在干旱胁迫过程中的变化特征,并通过主成分分析(PCA)和隶属函数法评价品种的抗旱性及其主要响应因子,以揭示西北地区油菜幼苗响应干旱胁迫的光合调控机制。结果表明：(1)各品种油菜幼苗的叶片相对含水量(RWC)均随干旱胁迫程度的递增而逐渐降低,最大水分亏缺(WSD)却逐渐上升。(2)各品种油菜幼苗叶片的叶绿素a含量、叶绿素总含量随着干旱胁迫程度的递增而先增加后递减,且同一种幼苗在不同处理间差异显著。(3)各品种油菜幼苗叶片的净光合速率(P_n)、水分利用效率(WUE)、单株生物量、气孔导度(G_s)、胞间CO₂浓度(C_i)均在受到干旱胁迫时迅速降低,且同一品种幼苗在不同处理间差异显著,而其叶片蒸腾速率(T_r)在干旱胁迫下无显著变化。(4)各品种油菜幼苗叶片光化学猝灭系数(qP)和非光化学猝灭系数(NPQ)随着干旱胁迫程度的递增先增加后递减,最大光化学效率(F_v/F_m)和电子传递速率(ETR)在受到干旱胁迫时迅速降低,且同一品种幼苗在不同处理间差异显著。(5)主成分分析结果表明,在油菜幼苗受到干旱胁迫时RWC、C_i、G_s、P_n、WUE、叶绿素总含量、叶绿素a含量和NPQ起主要调控作用;隶属函数法综合评价表明,3个品种油菜幼苗耐旱能力由高到低依次为‘陇油10号’＞‘陇油2号’＞‘青杂5号’。     

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...