Age‐related memory vulnerability to interfering stimuli is caused by gradual loss of MAPK‐dependent protection in Drosophila

Age‐related memory impairment (AMI) is a common phenomenon across species. Vulnerability to interfering stimuli has been proposed to be an important cause of AMI. However, the molecular mechanisms underlying this vulnerability‐related AMI remain unknown. Here we show that learning‐activated MAPK signals are gradually lost with age, leading to vulnerability‐related AMI in Drosophila. Young flies (2‐ or 3‐day‐old) exhibited a significant increase in phosphorylated MAPK levels within 15 min after learning, whereas aged flies (25‐day‐old) did not. Compared to 3‐day‐old flies, significant 1 h memory impairments were observed in 15‐, 20‐, and 30‐day‐old flies, but not in 10‐day‐old flies. However, with post‐learning interfering stimuli such as cooling or electric stimuli, 10‐day‐old flies had worse memory performance at 1 h than 3‐day‐old flies, showing a premature AMI phenomenon. Increasing learning‐activated MAPK signals through acute transgene expression in mushroom body (MB) neurons restored physiological trace of 1 h memory in a pair of MB output neurons in aged flies. Decreasing such signals in young flies mimicked the impairment of 1 h memory trace in aged flies. Restoring learning‐activated MAPK signals in MB neurons in aged flies significantly suppressed AMI even with interfering stimuli. Thus, our data suggest that age‐related loss of learning‐activated neuronal MAPK signals causes memory vulnerability to interfering stimuli, thereby leading to AMI.     

夜间变暖提高荫香叶片的光合能力

研究了不同氮供应的条件下夜间变暖对荫香叶片光合能力的影响。当植株生长在相同的日间温度(25℃),而夜间温度从18℃增至20℃时,叶片的光合速率增高(p<0.05)。高氮供应的植株,夜间变暖下其叶片光合速率较低氮供应的高,氮供应增高能促进夜间变暖提高叶片光合速率的效应。在低氮供给和夜间变暖下,植株叶片的光下呼吸和暗呼吸的增高显著(p<0.05)。无论在高氮或低氮供应下,生长在夜间变暖下的植物,其叶片的R ub isco最大羧化速率(Vcm ax)和光合电子传递最大速率(Jm ax)增高(p<0.05),氮供应能增强夜间变暖对Vcm ax和Jm ax的正向效应。夜间变暖降低植株叶片的比叶重,而增加单位叶干重的氮含量(Nm),单位叶面积的氮含量(Na)没发生明显变化。随着全球气候变化,夜间趋暖将有利于树木叶片光合能力的提高,结合高氮供给将会明显地增高植物的碳固定。     

Quantitative regulation of the thermal stability of enveloped virus vaccines by surface charge engineering to prevent the self-aggregation of attachment glycoproteins

The development of thermostable vaccines can relieve the bottleneck of existing vaccines caused by thermal instability and subsequent poor efficacy, which is one of the predominant reasons for the millions of deaths caused by vaccine-preventable diseases. Research into the mechanism of viral thermostability may provide strategies for developing thermostable vaccines. Using Newcastle disease virus (NDV) as model, we identified the negative surface charge of attachment glycoprotein as a novel determinant of viral thermostability. It prevented the temperature-induced aggregation of glycoprotein and subsequent detachment from virion surface. Then structural stability of virion surface was improved and virus could bind to and infect cells efficiently after heat-treatment. Employing the approach of surface charge engineering, thermal stability of NDV and influenza A virus (IAV) vaccines was successfully improved. The increase in the level of vaccine thermal stability was determined by the value-added in the negative surface charge of the attachment glycoprotein. The engineered live and inactivated vaccines could be used efficiently after storage at 37°C for at least 10 and 60 days, respectively. Thus, our results revealed a novel surface-charge-mediated link between HN protein and NDV thermostability, which could be used to design thermal stable NDV and IAV vaccines rationally.     

抑郁症易感基因和抗抑郁药物靶点相关[]神经细胞类型及相互作用网络分析

基于抑郁症的全基因组关联分析研究(GWAS),对于获得的单核苷酸多态性位点(SNP)使用Haploreg软件进行基因注释,得到SNP注释的102个易感基因.。使用MAGMA软件对GWAS的汇总统计数据做基因水平的分析,获得了270个校正之后显著的基因,两者合并共得到320个抑郁症易感基因。通过药物数据库Drugbank获取133个抗抑郁药物靶点基因。使用EWCE包对抑郁症易感基因和抗抑郁药物靶点在三套脑组织单细胞测序数据中,分别进行神经细胞类型富集分析。结果发现大脑皮质的GABA神经元(抑制性神经元)和谷氨酸能神经元(兴奋性神经元)是抑郁症易感基因和抗抑郁药物靶点共同的神经元。这两种类型的神经细胞可能是抗抑郁药物与抑郁症易感基因相互作用的神经细胞,另外少突胶质前体细胞可能是抑郁症特有的易感神经细胞。使用Network Calculator软件构建网络并进行进行网络拓扑学参数分析。结果表明抑郁症易感基因与抗抑郁药物靶点组成了一个具有显著的相互连接的网络。本研究从单细胞层面揭示抑郁症的遗传机制,在网络层面为寻找新的抗抑郁药物靶点提供了一定的启示。     

DLGCN:基于图卷积网络的药物-lncRNA[]关联预测

为实现高通量识别新的药物-长链非编码RNA(Long non-coding RNA, lncRNA)关联,本文提出了一种基于图卷积网络模型来识别潜在药物-lncRNA关联的方法DLGCN(Drug-LncRNA graph convolution network)。首先,基于药物的结构信息和lncRNA的序列信息分别构建了药物-药物和lncRNA-lncRNA相似性网络,并整合实验证实的药物-lncRNA关联构建了药物-lncRNA异质性网络。然后,将注意力机制和图卷积运算应用于该网络中,学习药物和lncRNA的低维特征,基于整合的低维特征预测新的药物-lncRNA关联。通过效能评估,DLGCN的受试者工作特性曲线下面积(Area under receiver operating characteristic, AUROC)达到0.843 1,优于经典的机器学习方法和常见的深度学习方法。此外,DLGCN预测到姜黄素能够调控lncRNA MALAT1的表达,已被最近的研究证实。DLGCN能够有效预测药物-lncRNA关联,为肿瘤治疗新靶点的识别和抗癌药物的筛选提供了重要参考。     

Hemin with Peroxidase Activity Can Inhibit the Oxidative Damage Induced by Ultraviolet A

Excessive reactive oxygen species (ROS), a highly reactive substance that contains oxygen, induced by ultraviolet A (UVA) cause oxidative damage to skin. We confirmed that hemin can catalyze the reaction of tyrosine (Tyr) and hydrogen peroxide (H₂O₂). Catalysis was found to effectively reduce or eliminate oxidative damage to cells induced by H₂O₂ or UVA. The scavenging effects of hemin for other free-radical ROS were also evaluated through pyrogallol autoxidation, 1,1-diphenyl-2-picrylhydrazyl radical (DPPH·)-scavenging assays, and phenanthroline–Fe²⁺ assays. The results show that a mixture of hemin and tyrosine exhibits strong scavenging activities for H₂O₂, superoxide anion (O₂⁻·), DPPH·, and the hydroxyl radical (·OH). Furthermore, the inhibition of oxidative damage to human skin keratinocyte (HaCaT) cells induced by H₂O₂ or UVA was evaluated. The results show that catalysis can significantly reduce the ratio of cell apoptosis and death and inhibit the release of lactate dehydrogenase (LDH), as well as accumulation of malondialdehyde (MDA). Furthermore, the resistance to apoptosis was found to be enhanced. These results show that the mixture of hemin and tyrosine has a significantly protective effect against oxidative damage to HaCaT cells caused by UVA, suggesting it as a protective agent for combating UVA damage.     

高寒山区植物根抗氧化酶系统的季节变化与抗冷冻关系

在高寒山区（海拔2900m）和选取4种多年生草本植物,即无芒雀麦（Bromus inermis）、草地早熟禾（Poa sphyondylodes）、花誉麦（Bromus sinensis）和垂重申披碱草（Elymus nutans）,测定了秋末、冬初、冬季、春季气温变化过程中其根中丙二醛（MDA）含量和抗氧酶活力（过氧化氢酶（CAT）、过氧化物酶（POD）、超氧物歧化酶（SOD））和抗坏血酸氧化酶（APX）变化,分析了抗氧酶系统在根抗冷适应中的作用,结果表明,随秋末降温植物根中MDA含量增加,尔后下降,在冬季和翌年春季保持相对稳定。从9月初到10月下旬,4种植物根中SOD、CAT、POD活力平均增加170％、130％和56％。在冬季下降,但仍远高于9月,在春季气温上升过程中酶活力上升。根能在组织结冰状况下生存与其具备完善的保护酶系统,能及时清除氧自由基抑制膜脂过氧化维持膜完整性有关,据降温过程中MDA含量和抗氧酶活力变化,可将根冷适应分为两个阶段,即第1阶段平均气温在0℃以上,抗氧酶活力增强,MDA增加阶段,第2阶段平均气温降至0℃以下,最低气温降到－15℃以下,抗氧酶活力下降,MDA无明显变化阶段。     

Fast classification and compositional analysis of cornstover fractions using Fourier transform near-infrared techniques

The objectives of this research were to determine the variation of chemical composition across botanical fractions of cornstover, and to probe the potential of Fourier transform near-infrared (FT-NIR) techniques in qualitatively classifying separated cornstover fractions and in quantitatively analyzing chemical compositions of cornstover by developing calibration models to predict chemical compositions of cornstover based on FT-NIR spectra. Large variations of cornstover chemical composition for wide calibration ranges, which is required by a reliable calibration model, were achieved by manually separating the cornstover samples into six botanical fractions, and their chemical compositions were determined by conventional wet chemical analyses, which proved that chemical composition varies significantly among different botanical fractions of cornstover. Different botanic fractions, having total saccharide content in descending order, are husk, sheath, pith, rind, leaf, and node. Based on FT-NIR spectra acquired on the biomass, classification by Soft Independent Modeling of Class Analogy (SIMCA) was employed to conduct qualitative classification of cornstover fractions, and partial least square (PLS) regression was used for quantitative chemical composition analysis. SIMCA was successfully demonstrated in classifying botanical fractions of cornstover. The developed PLS model yielded root mean square error of prediction (RMSEP %w/w) of 0.92, 1.03, 0.17, 0.27, 0.21, 1.12, and 0.57 for glucan, xylan, galactan, arabinan, mannan, lignin, and ash, respectively. The results showed the potential of FT-NIR techniques in combination with multivariate analysis to be utilized by biomass feedstock suppliers, bioethanol manufacturers, and bio-power producers in order to better manage bioenergy feedstocks and enhance bioconversion.     

副溶血性弧菌免疫逃逸及其可能机制的研究进展

副溶血性弧菌是全球范围内威胁人体健康和食品安全的食源性致病菌。在感染人体的过程中,副溶血性弧菌通过将其效应蛋白直接注射至宿主细胞中操纵宿主,介导毒力的发挥,并进化出了一套完美的免疫逃逸策略,成功躲避免疫系统的攻击,引起急性肠胃炎、败血症和坏死性筋膜炎等疾病。副溶血性弧菌入侵上皮细胞,使胞内囊泡酸化,在与溶酶体融合之前逃逸到细胞质中,并且限制活性氧的产生,促进其在胞内生存。副溶血性弧菌可以诱导自噬,抑制NLRC4炎症小体介导的caspase-1的激活,还可以通过抑制TAK1激酶,阻止MAPK和NF-κB信号通路的激活,干扰免疫系统激活,借助多种手段共同协作从而达到免疫逃逸。本文系统总结了副溶血性弧菌现已研究的免疫逃逸机制,并对其可能存在的免疫逃逸机制提供了新的见解和方向,对深入了解副溶血性弧菌的致病机理和防控药物靶向位点的选择及研发具有重要意义。     

黄河三角洲垦利县夏季土壤水盐空间变异及土壤盐分微域特征

黄河三角洲作为我国重要的后备土地资源区,土壤盐渍化问题突出,切实掌握季节性土壤水盐状况及其微域特征是该区土壤盐渍化防控和土地资源高效利用的重要基础。选择黄河三角洲垦利县,通过野外调查实测与室内化验分析获取土壤水盐含量数据,利用统计分析、GIS空间插值、实地观测与数据分析对比等方法,分析了研究区夏季土壤水盐状况及其微域变异规律。结果显示:研究区夏季土壤水盐含量总体较高,含盐量以中度盐渍化为主,随着土层深度的增加含盐量呈上升趋势,且各层土壤含盐量呈显著正相关性;含盐量较高的地区主要分布在该区东北部和中东部,含盐量较低的地区主要分布在西南部和中部;土壤含盐量从大到小的植被类型依次为光板地→碱蓬→高粱→芦苇→茅草→水稻→棉花→玉米;土壤盐分微域变化特征明显,含盐量受距路边远近、不同耕作措施、地形部位、植被群落等因素影响较大,表现出微域规律性和复杂性。该研究基本摸清了研究区夏季时相的土壤水盐状况及其微域特征,为黄河三角洲农作物栽培管理及土壤资源可持续利用提供了科学依据。