The combined effect of water deficit stress and TiO2 nanoparticles on cell membrane and antioxidant enzymes in Helianthus annuus L.

Nanotechnology has become one of the several approaches attempting to ameliorate the severe effect of drought on plant''s production and to increase the plants tolerance against water deficit for the water economy. In this research, the effect of foliar application of TiO₂, nanoparticles or ordinary TiO₂, on Helianthus annuus subjected to different levels of water deficit was studied. Cell membrane injury increased by increasing the level of water deficit and TiO₂ concentration, and both types of TiO₂ affected the leaves in analogous manner. Ord-TiO₂ increased H₂O₂ generation by 67–240% and lipid peroxidation by 4–67% in leaves. These increases were more than that induced by Nano-TiO₂ and the effect was concentration dependent. Proline significantly increased in leaves by water deficit stress, reaching at 25% field capacity (FC) to more than fivefold compared to that in plants grown on full FC. Spraying plants with water significantly decreased the activities of enzymes in the water deficit stressed roots. The water deficit stress exerted the highest magnitude of effect on the changes of cell membrane injury, MDA, proline content, and activities of CAT and GPX. Nano-TiO₂ was having the highest effect on contents of H₂O₂ and GPX activity. In roots, the level of water deficit causes highest effect on enzyme activities, but TiO₂ influenced more on the changes of MDA and H₂O₂ contents. GPX activity increased by 283% in leaves of plants treated with 50 and 150 ppm Nano-TiO₂, while increased by 170% in those treated with Ord-TiO₂, but APX and CAT activities increased by 17–197%, in average, with Ord-TiO₂. This study concluded that Nano-TiO₂ didn’t ameliorate the effects of drought stress on H. annuus but additively increased the stress, so its use in nano-phytotechnology mustn’t be expanded without extensive studies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-022-01153-z.     

Pyroptosis in glioblastoma: A crucial regulator of the tumour immune microenvironment and a predictor of prognosis

Recent studies have shown that pyroptosis, an inflammatory form of cell death, has a dual role in tumorigenesis and tumour progression and affects the prognosis of patients; however, the role of pyroptosis in glioblastoma (GBM) is still unclear. In this study, based on GBM patients'' data from two independent cohorts, we performed a comprehensive analysis of the expression and prognostic value of 33 pyroptosis‐associated genes (PAGs) in GBM, as well as their role in the tumour immune microenvironment (TIME) of GBM. We identified 29 PAGs that were differentially expressed between GBM and normal brain tissue, 18 of which were upregulated in GBM tissue. Most of the 33 PAGs were strongly correlated with the levels of immune cell infiltration. Based on the 33 PAGs, the GBM samples can be divided into two clusters (C1‐C2), with C1 having a ‘hot’ but immunosuppressive TIME and C2 having a ‘cold’ TIME, suggesting different immunotherapeutic responses in the two clusters. In addition, we identified four PAGs that were strongly associated with GBM prognosis and constructed a risk model based on these four PAGs. This risk model is an independent prognostic factor for GBM patients, and there is a different immune status between high‐ and low‐risk groups. In conclusion, this study demonstrates that pyroptosis is closely associated with the prognosis and TIME of GBM and provides an important basis for further studies on the relationship between pyroptosis and GBM.     

亚热带河口养殖塘沉积物有机碳矿化及其影响因子

亚热带河口的养殖塘是温室气体二氧化碳(CO2)的重要排放源,但其沉积物有机碳矿化动力学特征目前尚未厘清.以我国东南沿海亚热带闽江、木兰溪以及九龙江河口区的6个凡纳滨对虾(Penaeus vannamei)养殖塘为研究对象,对沉积物取样,并进行为期60 d的室内厌氧培养,对养殖塘沉积物CO2累积产量曲线利用一阶动力学模型...     

基于三温模型的南宁市蒸散量估算及其影响因素

蒸散发是水文能量循环和气候系统的关键要素.研究蒸散发的时空变化特征及其响应气候、土地利用的变化规律,对理解城市流域水循环和生态过程效应具有重要意义.本研究基于三温模型和MODIS影像,估算并分析2001-2018年南宁市的蒸散量时空演变特征,并探讨了主要气候要素、土地利用类型对蒸散量的影响规律和驱动模式.结果表明:20...     

皮质酮诱导的PC12细胞梯度应激损伤模型的构建及评价

目的:建立皮质酮诱导的PC12细胞梯度应激损伤模型,为细胞应激水平的评估和细胞应激损伤调控研究提供实验基础和对象。方法:通过检测不同浓度皮质酮(0～1 000μmol/L)在经过不同干预时间(8～48 h)后PC12细胞活力,观察皮质酮对细胞活力的影响,筛选最佳干预条件的细胞模型。分光光度法和微量法检测细胞模型的关键应激指标(MDA、SOD、NADH、LDH),对模型进行评价。结果:当皮质酮浓度在200μmol/L以下且干预时间为12 h时,细胞活力在半数失活率以下,可减少各组由于细胞活力下降而产生的混杂因素。与空白对照组比较,皮质酮浓度依赖性地升高模型组的MDA、NADH和LDH水平,降低SOD水平(P<0.01),符合梯度应激模型的构建要求。结论:成功建立了PC12细胞梯度应激损伤模型,在干预时间为12 h的情况下,干预浓度为0μmol/L、25μmol/L、50μmol/L、100μmol/L、150μmol/L、200μmol/L,使得细胞模型应激损伤程度梯度增加,可作为开展细胞应激损伤评估及调控实验的基础和对象。     

The modulation of neuroinflammation by inducible nitric oxide synthase

The accumulation and propagation of misfolded proteins in the brain is a pathological hallmark shared by many neurodegenerative diseases, such as the depositions of β-amyloid and hyperphosphorylated tau proteins in Alzheimer''s disease. Initial evidence shows the role of nitric oxide synthases in the development of neurodegenerative diseases. A recent, in an exciting paper (Bourgognon et al. in Proc Natl Acad Sci USA 118, 1–11, 2021. 10.1073/pnas.2009579118) it was shown that the inducible nitric oxide synthase plays an important role in promoting oxidative and nitrergic stress leading to neuroinflammation and consequently neuronal function impairments and decline in synaptic strength in mouse prion disease. In this context, we reviewed the possible mechanisms of nitric oxide synthase in the generation of neurodegenerative diseases.     

基于过程模型CROBAS的全局灵敏度分析方法比较

过程机理模型在开发过程中常受限于生理学参数无法直接或准确测量.全局灵敏度分析可以评估模型预测结果对于生理学参数变化的响应,为模型结构改进、数据收集和参数校准提供参考.本研究基于过程模型CROBAS,以华山松为例,选取模型中描述树木结构关系的10个参数,以树高和各器官生物量的Nash-Sutcliffe效率(NSE)为目...     

Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.     

The Usefulness of Various Numerical Methods for Assessing the Specific Effects of Pollution on Aquatic Biota

The data obtained during an extensive multidisciplinary investigation of a polluted harbor basin in Hamburg were analyzed in various ways in order to determine which statistical methods are easiest to interpret and permit the most accurate evaluations. The methods analyzed include the species deficit, index of species similarity, and saprobity index, as well as the more complex cluster and gradient analyses, which revealed a variety of relationships among the biotic communities at the various sampling sites and some ecological tolerance limits of various species. The shortcomings of numerical indices for characterizing water bodies are discussed. It is suggested that biostatistical methods are much more valuable for the empirical evaluation of data than for artificially classifying ecosystems.     

数字细胞模型的研究及应用

组学分析技术的发展推动生物学逐渐成为一门以数据分析为中心的科学。依托生物数据在细胞整体系统水平建立数字细胞模型,对于理解细胞系统组织原理和生命产生进化规律,预测各种环境和基因扰动对细胞功能的影响并指导设计人工生命具有重要意义,因此数字细胞的构建模拟设计已成为合成生物学的核心研究内容与底层支撑技术。本文重点对天津工业生物技术研究所创立十年来在数字细胞研究方面的进展进行回顾介绍,重点包括基因组尺度代谢网络模型的构建、质控以及其在途径设计和指导菌种代谢工程改造方面的应用,进一步结合近年来细胞模型研究的前沿趋势,对整合多种约束的模型的构建和分析研究方面的最新成果进行了介绍,最后对数字细胞研究的未来发展方向进行展望。数字细胞技术将与基因组测序、合成和编辑等合成生物学前沿技术一起提升人们对生命进行读写改创的能力。