呼肠病毒BYD株吸附蛋白σ1的原核表达及其抗原性鉴定

将呼肠病毒BYD株S1片段编码的细胞吸附蛋白基因连接至pET-28a( ),构建表达载体pET-28a( )-S1,转化表达宿主菌E.coli BL21(DE3),分析表达载体能否表达预期大小的重组σ1,并进一步鉴定重组σ1的抗原性。SDS-PAGE实验表明,经IPTG诱导后,表达载体能表达53kD左右蛋白质,与重组σ1的预期大小相符;免疫印迹分析表明重组σ1有较好的抗原性和特异性,可用于呼肠病毒诊断试剂的制备。     

农田小麦在土壤湿润条件下的气孔活动

1984年在北京大屯农业生态系统试验站用MK 3型自动气孔计对土壤湿润、睛朗天气条件下冬小麦气孔传导力的日变化,季节变化、以及叶龄和梯度变化进行了观测。发现叶片传导力(gl)的日变化为双峰曲线,正午gl的降低可能是强光和高的饱和差作用的结果,从而限制了光合潜力的发挥。近轴面传导力(gd)和远轴面传导力(gb)的比(α)不是一个常数,这是因为两面气孔对环境条件的反应不同。gl和冠层传导力(g(?))都以孕穗期为最高。灌浆时期gl和gc有所降低,反映了叶片的过早衰老。这是影响本地区小麦产量的重要因素之一,其原因不仅与土壤水分有关,还与大气条件和病虫害有关。本文还讨论了gl随时龄的变化。观测表明,气孔计可以迅速准确地掌握作物群体的生理动态,有可能用于指导农田灌灌和管理。     

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

Background:The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.Methods:We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ground-level ozone (O₃), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.Results:Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM_2.5 (1.70 μg/m³), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO₂. We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O₃ for hospital admission, ICU admission and death, respectively.Interpretation:Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O₃.

By November 2021, COVID-19 had caused more than 5 million deaths globally¹ and more than 29 400 in Canada.² The clinical manifestations of SARS-CoV-2 infection range from being asymptomatic to multiple organ failure and death. Identifying risk factors for COVID-19 severity is important to better understand etiological mechanisms and identify populations to prioritize for screening, vaccination and medical treatment. Risk factors for severity of COVID-19 include male sex, older age, pre-existing medical conditions and being from racialized communities.^3–5 More recently, ambient air pollution has been implicated as a potential driver of COVID-19 severity.^6–10Long-term exposure to ambient air pollution, a major contributor to global disease burden,¹¹ could increase the risk of severe COVID-19 outcomes by several mechanisms. Air pollutants can reduce individuals’ pulmonary immune responses and antimicrobial activities, boosting viral loads.⁸ Air pollution can also induce chronic inflammation and overexpression of the alveolar angiotensin-converting enzyme 2 (ACE) receptor,⁷ the key receptor that facilitates SARS-CoV-2 entry into cells.^12,13 Exposure to air pollution contributes to chronic conditions, such as cardiovascular disease, that are associated with unfavourable COVID-19 prognosis, possibly owing to persistent immune activation and excessive amplification of cytokine development.¹⁰ Thus, greater exposure to long-term air pollution may lead to severe COVID-19 outcomes.Reports exist of positive associations between long-term exposure to particulate matter with diameters equal to or smaller than 2.5 or 10 μm (PM_2.5 and PM₁₀), ground-level ozone (O₃) and nitrogen dioxide (NO₂), and metrics of COVID-19 severity (e.g., mortality and case fatality rate).^8–10 However, most studies to date have used ecological and cross-sectional designs, owing to limited access to individual data, which leads to ambiguity in interpreting the results, thus hindering their influence on policy. ^6,14 Ecological designs do not allow for disentangling the relative impacts of air pollution on individual susceptibility to infection and disease severity.¹⁴ Residual confounding by factors such as population mobility and social interactions is also problematic. Therefore, a cohort study with data on individuals with SARS-CoV-2 is a more appropriate design.^6,14 Studies that have used individual data were conducted in specific subpopulations^15,16 or populations with few severe cases,¹⁷ or had limited data on individual exposure to air pollutants.¹⁸ In Canada, 1 ecological study found a positive association between long-term exposure to PM_2.5 and COVID-19 incidence,¹⁹ but no published study has explored the association between air pollution and COVID-19 severity.We aimed to examine the associations between long-term exposure to 3 common air pollutants (PM_2.5, NO₂ and O₃) and key indicators of COVID-19 severity, including hospital admission, intensive care unit (ICU) admission and death, using a large prospective cohort of people with confirmed SARS-CoV-2 infection in Ontario, Canada, in 2020. The air contaminants PM_2.5, NO₂ and O₃ are regularly monitored by the Canadian government, and are key pollutants that are considered when setting air-quality policies. They originate from varying sources (NO₂ is primarily emitted during combustion of fuel, O₃ is primarily formed in air by chemical reactions of nitrogen oxides and volatile organic compounds, and PM_2.5 can be emitted during combustion or formed by reactions of chemicals like sulphur dioxide and nitrogen oxides in air) and they may affect human health differently.^20,21,22     

谭清苏铁性别相关的RAPD标记研究

以谭清苏铁(Cycas tanqingii D.Y.Wang)雌雄植株半年生羽叶为材料,用优化的CTAB法分别提取其全基因组DNA,进行RAPD单因子梯度实验和正交实验以优化扩增条件。应用160个RAPD随机引物检测基因组DNA,雌雄植株均扩增出1450多条带,其中引物S0465扩增出与谭清苏铁雌株高度相关的RAPD标记,其大小约为500bp,该标记与雄株没有关联。     

甲基对硫磷水解酶基因的高效表达及酶活性分析

假单胞菌WBC 3的甲基对硫磷水解酶基因mph在大肠杆菌系统AD494(DE3) pET32a ( + )中实现了高效可溶性融合表达。表达的重组酶能够有效地被亲合层析纯化。酶学性质分析表明 ,重组酶对底物乙基对硫磷水解能力较野生酶相比有近 4倍的提高 ,对甲基对硫磷和杀螟松的水解活力无明显变化。以融合蛋白形式存在的重组酶在室温及 4℃下的贮存稳定性明显优于野生型酶。     

Alterations and Mechanism of Gut Microbiota in Graves’ Disease and Hashimoto’s Thyroiditis

To explore the role of gut microbiota in Graves’ disease (GD) and Hashimoto’s thyroiditis (HT). Seventy fecal samples were collected, including 27 patients with GD, 27 with HT, and 16 samples from healthy volunteers. Chemiluminescence was used to detect thyroid function and autoantibodies (FT3, FT4, TSH, TRAb, TGAb, and TPOAb); thyroid ultrasound and 16S sequencing were used to analyze the bacteria in fecal samples; KEGG (Kyoto Encyclopedia of Genes and Genomes) and COG (Clusters of Orthologous Groups) were used to analyze the functional prediction and pathogenesis. The overall structure of gut microbiota in the GD and HT groups was significantly different from the healthy control group. Proteobacteria and Actinobacteria contents were the highest in the HT group. Compared to the control group, the GD and HT groups had a higher abundance of Erysipelotrichia, Cyanobacteria, and Ruminococcus_2 and lower levels of Bacillaceae and Megamonas. Further analysis of KEGG found that the “ABC transporter” metabolic pathway was highly correlated with the occurrence of GD and HT. COG analysis showed that the GD and HT groups were enriched in carbohydrate transport and metabolism compared to the healthy control group but not in amino acid transport and metabolism. Our data suggested that Bacillus, Blautia, and Ornithinimicrobium could be used as potential markers to distinguish GD and HT from the healthy population and that “ABC transporter” metabolic pathway may be involved in the pathogenesis of GD and HT.     

使用冷冻方法防治昆虫标本虫害

皮蠹幼虫对昆虫标本的蛀蚀是我国北方地区标本保藏时需要注意的首要问题。经12次的试验观察表明,花斑皮蠹幼虫TrogodermavariabileBallion在冰柜中放置位置不同其冷冻致死率亦不相同置于冰柜表层的,死亡率介于0～50%;上层的死亡率为95%～100%;中上层及中层死亡率达100%。放置在表层及上层的皮蠹幼虫,在经2d以上的冷冻处理后部分个体出现复活。因此,对那些原先放置上层及表层的标本,第1次冷冻结束后,间隔数天应再进行第2次冷冻,以提高和巩固冷冻杀虫效果。经3年的实践证明,采用冷冻方法治理皮蠹幼虫为害效果明显,可以推广普及。     

Noggin and bFGF cooperate to maintain the pluripotency of human embryonic stem cells in the absence of feeder layers

Human embryonic stem (hES) cells are typically maintained on mouse embryonic fibroblast (MEF) feeders or with MEF-conditioned medium. However, these xenosupport systems greatly limit the therapeutic applications of hES cells because of the risk of cross-transfer of animal pathogens. Here we showed that the bone morphogenetic protein antagonist noggin is critical in preventing differentiation of hES cells in culture. Furthermore, we found that the combination of noggin and basic fibroblast growth factor (bFGF) was sufficient to maintain the prolonged growth of hES cells while retaining all hES cell features. Since both noggin and bFGF are expressed in MEF, our findings suggest that they may be important factors secreted by MEF for maintaining undifferentiated pluripotent hES cells. Our data provide new insight into the mechanism how hES cell self-renewal is regulated. The newly developed feeder-free culture system will provide a more reliable alternative for future therapeutic applications of hES cells.     

蜘蛛杀虫肽基因的合成及其在植物中表达质粒的构建

近年来用生物制剂防治害虫,虽然可以避免环境污染,但效果往往不稳定,而用基因工程方法,将抗虫基因导入植物的基因组中,让植物自身产生抗虫物质,将是一种理想的途径［１,２］。抗虫的植物基因工程主要是利用苏云金杆菌的内毒素蛋白,转化此基因的烟草和番茄显示了对虫的抗性［３—６］。澳大利亚Ｄｅａｋｉｎ大学从一种蜘蛛毒液中分离纯化到一种只有３７个氨基酸的小肽,体外实验发现其能杀死多种对农业生产有害的昆虫,但对哺乳动物没有毒害作用［７］。我们根据此肽的氨基酸序列,采用植物偏爱的密码子,人工合成并克隆了此肽的基因…     

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.