国家种质库部分作物种子生活力监测结果与分析

对国家种质库中23种作物1.8万多份种子进行了生活力监测,结果表明,贮存10～12年后,96%以上的被监测种子发芽率仍保持在85%以上,但有95份种子(占被监测份数的0.51%)出现了明显的下降(发芽率从80%以上降至70%以下).胡萝卜、莴苣、棉花、胡麻、蓖麻等5种作物种子整体监测发芽率平均值都出现了显著下降,而胡萝卜、莴苣这二种作物的监测发芽率下降更为显著.不同起始发芽率水平及贮存前所处环境条件对贮存种子的生活力下降有一定影响.     

DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.     

Engineering challenges in high density cell culture systems

High density cell culture systems offer the advantage of production of bio-pharmaceuticals in compact bioreactors with high volumetric production rates; however, these systems are difficult to design and operate. First of all, the cells have to be retained in the bioreactor by physical means during perfusion. The design of the cell retention is the key to performance of high density cell culture systems. Oxygenation and media design are also important for maximizing the cell number. In high density perfusion reactors, variable cell density, and hence the metabolic demand, require constant adjustment of perfusion rates. The use of cell specific perfusion rate (CSPR) control provides a constant environment to the cells resulting in consistent production. On-line measurement of cell density and metabolic activities can be used for the estimation of cell densities and the control of CSPR. Issues related to mass transfer and mixing become more important at high cell densities. Due to the difference in mass transfer coefficients for oxygen and CO₂, a significant accumulation of dissolved CO₂ is experienced with silicone tubing aeration. Also, mixing is observed to decrease at high densities. Base addition, if not properly done, could result in localized cell lysis and poor culture performance. Non-uniform mixing in reactors promotes the heterogeneity of the culture. Cell aggregation results in segregation of the cells within different mixing zones. This paper discusses these issues and makes recommendations for further development of high density cell culture bioreactors.     

Fungal population in the atmosphere of Ismailia City

Fungal spore populations in the outdoor and indoor atmosphere of Ismailia have been studied during the period from March 1992 to May 1993. A total of 23 350 cfu and 73 species were recorded,Cladosporium cladosporioides, Aureobasidium pullulans andAspergillus flavus were the most abundant. The indoor and outdoor mycoflora showed marked quantitative and qualitative differences. In view of count, recorded species could be categorized into three groups as follows: (a) species showing higher counts in out- than indoor, (b) species showing the opposite trend i.e. lower counts in out-door than indoor, (c) species showing approximately equal counts in out- and indoor. Regarding seasonal periodicity, March and either September or October showed the highest count for both normal fungal flora (NFF) and opportunistic fungal flora (OFF). While January and July showed the lowest count of them both, May but not July was the lowest as for outdoor NFF.     

植被综合生态质量时空变化动态监测评价模型

为了能掌握全国植被综合生态质量的高低及其时空变化,构建了既能反映植被生产力又能反映植被覆盖度的植被综合生态质量指数,建立了植被综合生态质量指数年际对比和多年变化趋势评价模型。利用构建的指数和评价模型,以2017年作为监测评价的当年,以2000—2017年作为评价的多年时段,对全国植被综合生态质量时空变化进行了监测评价。结果表明：（1）2017年全国大部地区植被综合生态质量指数高于2000—2016年多年平均值,生态质量偏好;2017年福建、广西、海南、广东、云南植被综合生态质量位居全国前五位,构建的植被综合生态质量指数及其年际对比模型可以定量反映全国植被综合生态质量的空间差异和年际差异。（2）全国有90.7%的区域2000—2017年植被综合生态质量指数呈提高趋势,东北地区西部、内蒙古东部、华北大部、西北地区东部、西南地区东部、华南西部等地生态质量指数提升明显,构建的植被综合生态质量指数多年变化趋势评价模型可以定量反映植被生态质量的多年变化趋势和幅度。（3）南方大部地区2000—2017年平均年植被综合生态质量指数在50.0以上,北方大部地区在50.0以下;我国中东部大部地区在20.0以上,西部大部地区在20.0以下,表明南方大部地区年植被生态质量好于北方、中东大部好于西部。可见,构建的植被综合生态质量指数及其年际对比和多年变化趋势评价模型,能够监测评价当年和多年全国植被综合生态质量的时空变化,可为掌握全国植被生态质量动态提供模型和方法。     

Kidney proteome responses in the teleost fish Paralichthys olivaceus indicate a putative immune response against Streptococcus parauberis

The proteomic response to bacterial infection in a teleost fish (Paralichthys olivaceus) infected with Streptococcus parauberis was analyzed using label-free protein quantitation coupled with LC-MS(E) tandem mass spectrometry. A total of 82 proteins from whole kidney, a major lymphoid organ in this fish, were found to be differentially expressed between healthy and diseased fish analyzed 6, 24, 72 and 120 h post-infection. Among the differentially expressed proteins, those involved in mediating immune responses (e.g., heat shock proteins, cathepsins, goose-type lysozyme and complement components) were most significantly up-regulated by infection. In addition, cell division cycle 48 (CDC48) and calreticulin, which are associated with cellular recovery and glycoprotein synthesis, were up-regulated in the universal protein group, whereas the other proteins in that group were down-regulated. There was continuous activation of expression of immune-associated proteins during infection, but there was also loss of expression of proteins not involved in immune function. We expect that our findings regarding immune response at the protein level would offer new insight into the systemic response to bacterial infection of a major immune organ in teleost fish.     

Cobalt determination in serum and urine by electrothermal atomic absorption spectrometry

Cobalt determinations in biological fluids are of great interest in biological or toxicological research programs. Cobalturia is often chosen as an indicator for a biological monitoring program in occupational exposure to cobalt dusts. The method described here derives from the IUPAC reference method for nickel determination. It enables cobaltemia and cobalturia to be measured in small samples (1 mL). The mean usual values for cobalt in biological fluids are very low (2.7 nmol L⁻¹ for serum and 6.7 nmol L⁻¹ for urine), and therefore, thus require an analytical procedure with preconcentration and extraction. The sample is mineralized by wet acid digestion. After digestion, inorganic cobalt is extracted in form of ammonium pyrrolidine dithiocarbamate complex into isobutyl methyl ketone and measured in the organic layer by electrothermal atomic absorption spectrometry. The analytical parameters are described in detail. The extraction output is about 99%. The detection limits are 1.93 and 1.89 nmol L⁻¹ for serum and urine, respectively. Sensitivity (expressed as the concentration that gives a 0.044 absorbance) is 3.4 nmol L⁻¹ for serum and 3.3 nmol L⁻¹ for urine. Within-run precision ranged between 3.9 and 2.5% (coefficients of variation) for serum and 4.2 and 1.1% for urine, at 87 and 136 nmol L⁻¹ levels, respectively. Between-run precision ranged between 4.3 and 3.3% (coefficients of variation) for serum and 4.2 and 2.3% for urine, at 87 and 136 nmol L⁻¹ levels, respectively. At very low concentration, 5.7 nmol L⁻¹ for serum and 2.5 nmol L⁻¹ for urine, the between-run precision is, respectively, 19.5 and 28%. Linearity is effective between 0 and 272 nmol L⁻¹. Interferences and matrix effects are negligible for urine, serum, or plasma samples without hemoglobin. The method is easily applicable for routine determinations.     

Indicators of restoration success in riparian tropical forests using multiple reference ecosystems

Forest restoration by planting trees often accelerates succession, but the trajectories toward reference ecosystems have rarely been evaluated. Using a chronosequence (4–53 years) of 26 riparian forest undergoing restoration in the Brazilian Atlantic Forest, we modeled how the variables representing forest structure, tree species richness and composition, and the proportion of plant functional guilds change through time. We also estimated the time required for these variables to reach different types of reference ecosystems: old‐growth forest (OGF), degraded forest, and secondary forest. Among the attributes which follow a predictable trajectory over time are: the basal area, canopy cover, density and tree species richness, as well as proportions of shade tolerant and slow growing species or individuals. Most of the variation in density of pteridophythes, lianas, shrubs and phorophythes, proportion of animal‐dispersed individuals, rarefied richness and floristic similarity with reference ecosystems remain unexplained. Estimated time to reach the reference ecosystems is, in general, shorter for structural attributes than for species composition or proportion of functional guilds. The length of this time varies among the three types of reference ecosystems for most attributes. For instance, tree species richness and proportion of shade tolerant or slow growing individuals become similar to secondary forests in about 40 years, but is estimated to take 70 years or more to reach the OGF. Of all the variables considered, canopy cover, basal area, density, and richness of the understory—by their ecological relevance and predictability—are recommended as ecological indicators for monitoring tropical forest restoration success.