非洲猪瘟病毒(ASFV)是一种致命的病原体，对全球养猪业造成灾难性的社会经济影响。到目前为止，还没有获得许可的预防性疫苗。目前对非洲猪瘟病毒主要免疫原和关键抗原表位图谱的了解有限。因此，功能性单克隆抗体(mAb)和表位图谱的研究对我们理解免疫反应和设计改进的疫苗、治疗和诊断至关重要。本研究基于自然感染ASFV的康复期PBMCs构建的ASFV抗体噬菌体展示文库，筛选出一株抗ASFV主要衣壳蛋白(p72)单链抗体，并与IgG Fc片段融合(scFv-83-Fc)，可以特异性识别ASFV Pig/HLJ/2018毒株。进一步，使用scFv-83-Fc单克隆抗体为靶点，我们从M13噬菌体展示随机肽库中鉴定到p72的一段保守表位肽（²²¹MTGYKH²²⁶）。此外，流式细胞术和细胞摄取实验表明，该表位肽在体外能显著促进BMDC成熟，并能被DC细胞有效摄取，这可能意味着其在疫苗和诊断试剂开发中的潜在应用前景。总之，本研究为确定ASFV疫苗开发的靶点提供了一个有价值的平台，并有助于亚单位疫苗和诊断试剂的优化设计。

龟纹瓢虫（鞘翅目：瓢虫科）在中国是一种自然天敌昆虫，捕食范围广泛，常用于害虫治理。然而其在中国区域内遗传模式（遗传变异、种群结构和历史动态）还不清楚，从而阻碍了害虫生物防治的发展进程。种群遗传数据对于天敌生防过程中不同阶段策略的优化具有很大潜力。本研究通过收集中国区域内30个采样区域的462头龟纹瓢虫样本，采用23对微卫星和线粒体COI分子标记，开展了该种的群体遗传工作。微卫星数据显示龟纹瓢虫具有中等水平的遗传多样性，线粒体基因则显示出高水平的遗传多样性。与长江流域种群相比，黄河流域种群具有更高的遗传分歧。龟纹瓢虫中国种群未形成显著的地理种群结构，但存在群体分化的迹象，这可能与种群间频繁的基因交流有关。种群经历瓶颈后出现扩张，寄主植物——害虫——天敌之间的三级营养关系是种群扩张的重要因素。种群遗传研究在害虫生物防治过程中发挥着重要作用，本研究通过估测种群遗传多样性、种群遗传差异和推测种群历史动态，为有效利用天敌昆虫提供重要的遗传信息。

盐害严重威胁着植物的生长和发育。因此，识别和筛选盐胁迫响应的关键基因并解析其作用机制对提高植物的耐盐性至关重要。本研究运用磷酸化蛋白质组技术对盐胁迫处理前后的谷子样品进行检测分析，共鉴定出4000个磷酸化多肽，其中123个显著差异。非冗余蛋白质数据库（NR）功能注释显示，有23个转录因子表达差异显著，如SiRAV1转录因子。亚细胞定位分析显示SiRAV1位于细胞核中。表型和生理分析证实，SiRAV1的过表达能够提高谷子对盐胁迫的耐受性，且这一作用是通过抑制盐诱导的H₂O₂积累、丙二醛含量和电解质渗漏率的增加等方式实现的。进一步的研究表明，SiRAV1能够直接结合SiCAT启动子以激活SiCAT的表达，从而提高CAT酶的活性。本研究还发现，SiRAV1蛋白的Ser31位点磷酸化可以通过增强其与SiCAT启动子的结合能力来正向调节谷子的耐盐性。综上所述，本研究首次解析了SiRAV1在谷子盐响应中的作用机制：盐胁迫通过诱导SiRAV1蛋白的Ser31位点磷酸化，进而增强了其与SiCAT启动子的结合能力，激活了SiCAT的表达，从而提高谷子对盐胁迫的耐受性。

甜樱桃是世界最受欢迎的水果之一。早先，我们发现了一种黑色暗格真菌S16，它能够促进樱桃砧木吉塞拉5号的生长。然而，关于它们之间作用的分子机制还不甚了解。在本次研究中，我们分析了与S16共生的樱桃根部的生理指标以及转录组本，初步阐释了S16促樱桃生长的分子机制。与S16共生后，樱桃幼苗的活力更强。而且，与对照相比，S16共生根部共鉴定到4249个差异表达基因。这些基因涉及到与植物代谢、激素相关的生长过程。而且，与氮调控相关的基因高度富集。生理指标测定表明，S16能够促进樱桃幼苗利用NO₃^-转运蛋白来吸收氮源。因此，此次RNA测序数据库可以更加深入了从分子机制层面解析黑色暗格真菌促樱桃的生长过程。

Following rapid social and economic development over the past several decades, soil pollution by heavy metals (HMs) has been both serious and widespread in China.  The Soil Environmental Quality Standards (SEQSs) in China (GB 15618-1995) have been introduced to encourage and enforce sustainable soil HM management.  However, in recent years, HM contents in soils have frequently been found to exceed their associated standard values, while the crops growing on them might still meet regulatory standards, and vice versa.  There is thus growing awareness that GB 15618-1995 does not effectively regulate current soil HM pollution, as it has encountered bottlenecks, and disappointing outcomes caused by poor execution along with deficiencies and gaps in the policies.  However, due to the deficiency of scientific research about relationships between soil HM concentrations and their ecological or human health effects, the development of SEQSs in China is still greatly restricted.  This paper discusses international SEQSs of HMs as well their development in China over time, then examines current Chinese SEQSs to demonstrate their potential regulatory deficiencies by referring to international SEQSs.  The corresponding legislative policies are described, and scientific information or responses are outlined for maintaining soil environmental quality.  China’s experience has shown that policy and science can be linked to work in tandem to better understand and manage soil quality issues.

Mitogen-activated protein kinase (MAPK) cascades play an important role in extracellular signal transduction and are involved in the pathogenicity of fungal pathogens to host plants.  In Curvularia lunata, the roles of two MAPK genes, Clk1 and Clm1, have already been studied.  Clk1 is involved in conidia formation and pathogenicity, and Clm1 is closely related to pathogen cell wall formation and pathogenicity to maize leaves.  In this study, a third C. lunata MAPK gene, Clh1, which is homologous to hog1, was successfully cloned.  We found that a Clh1 deletion mutant had lower intracellular glycerol accumulation than the wild-type stain and was unable to grow normally under osmotic stress conditions.  Furthermore, the deletion mutants of three C. lunata MAPK genes (Clk1, Clm1 and Clh1) had lower levels of acetyl-CoA, which is an important intermediate product in the synthesis of melanin and furan toxin, and down-regulated expression of pathogenicity-associated genes.  Furthermore, pathogenicity and the ability to produce toxin were restored after adding acetyl-CoA to the culture medium, suggesting that acetyl-CoA is closely involved in the pathogen MAPK signaling pathway. 

    Lead (Pb) contamination has often been recorded in Chinese field soils. In recent years, efforts have been made to investigate Pb toxicity thresholds in soils with plant growth and microbial assays. However, the influence of soil properties on Pb toxicity impacts on soil microbial processes is poorly understood. In this study ten soils with different properties were collected in China to investigate the relationships between thresholds of Pb toxicity to soil microbes and soil properties. The effect of soil leaching on Pb toxicity was also investigated to determine the possible influence of added anions on Pb toxicity during dose-response tests. Toxicity was inferred by measuring substrate-induced nitrification in leached and non-leached soils after Pb addition. We found that soil microbe Pb toxicity thresholds (EC_x, x=10, 50) differed significantly between the soils; the 10% inhibition ratio values (EC₁₀) ranged from 86 to 218 mg kg^–1 in non-leached soils and from 101 to 313 mg kg^–1 in leached soils. The 50% inhibition ratio values (EC₅₀) ranged from 403 to 969 mg kg^–1 in non-leached soils and from 494 to 1 603 mg kg^–1 in leached soils. Soil leaching increased EC10 and EC50 values by an average leaching factor (LF) of 1.46 and 1.33, respectively. Stepwise multiple regression models predicting Pb toxicity to soil microbes were developed based on EC_x and soil properties. Based on these models, soil pH and organic carbon are the most important soil properties affecting Pb toxicity thresholds (R₂>0.60). The quantitative relationship between Pb toxicity and soil properties will be helpful for developing soil-specific guidance on Pb toxicity thresholds in Chinese field soils.

Curvularia leaf spot, caused mainly by Curvularia lunata, is a widespread plant disease in China.  In the recent years, directional host selection by the pathogen, which likely results in the virulence differentiation in pathogens, is widely reported.  Among the hallmarks potentially associated to pathogen variation in virulence, superoxide dismutase gene Sod has been found to be closely related to the enhancement of virulence.  In the present study, the full-length of Sod was obtained via Blastn alignment against GenBank and the whole genome of C. lunata.  In order to understand the role of Sod in the virulence variation in C. lunata, targeted gene disruption was performed to construct Sod mutants.  The cell wall degrading enzyme (CWDE) activities and toxin production of ΔSod were not distinctly different from wild-type strain CX-3 and its complon.  However, at an early stage of infection, ΔSod virulence appeared to be lower than CX-3 and the complon, while at a later stage, its virulence gradually returned to the level of CX-3 and the complon.  Furthermore, the melanin production of ΔSod was significantly reduced compared to CX-3 and the complon, suggesting that Sod gene influences the virulence by regulating melanin production at an early stage of infection but is not essential for pathogenicity.  However, the disruption of Sod did not significantly affect the transcriptional expression of the melanin biosynthesis-associated genes, brn1 and scd.  Therefore, we infer that Sod in C. lunata are involved, to some extent, with the virulence in maize leaf, but still needs further studies to have a clear understanding of its mechanism.

This study investigated the effects of the degree of unsaturation (unsaturity) of long-chain fatty acids on microbial protein content and the activities of transaminases and dehydrogenase in vitro using goat rumen fluid as the cultural medium. Six types of fatty acids, stearic acid (C18:0, group A, control group), oleic acid (C18:1, n-9, group B), linoleic acid (C18:2, n-6, group C), α-linolenic acid (C18:3, n-3, group D), arachidonic acid (C20:4, n-6, group E), and eicosapentaenoic acid (C20:5, n-3, group F), were tested, and the inclusion ratio of each fatty acid was 3% (w/w) in total of culture substrate. Samples were taken at 0, 3, 6, 9, 12, 18 and 24 h, respectively, during culture for analyses. Compared with stearic acid, linoleic acid, α-linolenic acid, and arachidonic acid increased the bacterial protein content, while oleic acid and eicosapentaenoic acid had no significant effects; the protozoal protein content was reduced for all the unsaturated fatty acids, and the magnitude of the reduction appeared to be associated with the degree of unsaturity of fatty acids. The total microbial protein content was dominantly accounted by the protozoal protein content (about 4–9 folds of the bacterial protein), and only increased by linoleic acid, but reduced by oleic acid, arachidonic acid and eicosapentaenoic acid. There were no significant effects in the activities of both glutamic oxaloacetic transaminase (GOT) and glutamic-pyruvic transaminase (GPT) for all the other fatty acids, except for arachidonic acid which enhanced GOT activity and oleic acid which enhanced GPT activity. The total dehydrogenase activity was positively correlated with the degree of unsaturation of fatty acids. In conclusion, the inclusion of 3% of long-chain unsaturated fatty acids increased bacterial protein content, whereas reduced protozoal protein content and enhanced dehydrogenase activity. The fatty acids with more than three double bonds had detrimental effects on the microbial protein content. This work demonstrates for the first time the effect rule of the unsaturation degree of long-chain fatty acids on the rumen microbial protein in vitro.

    This study investigated the impacts of the degree of unsaturation (unsaturity) of long-chain fatty acids on volatile fatty acid (VFA) profiles of rumen fermentation in vitro. Six types of long-chain fatty acids, including stearic acid (C18:0, control group), oleic acid (C18:1, n-9), linoleic acid (C18:2, n-6), α-linolenic acid (C18:3, n-3), arachidonic acid (C20:4, n-6) and eicosapentaenoic acid (C20:5, n-3), were tested. Rumen fluid from three goats fitted with ruminal fistulae was used as inoculum and the inclusion rate of long-chain fatty acid was at 3% (w/w) of substrate. Samples were taken for VFA analysis at 0, 3, 6, 9, 12, 18 and 24 h of incubation, respectively. The analysis showed that there were significant differences in the total VFA among treatments, sampling time points, and treatment×time point interactions (P<0.01). α-Linolenic acid had the highest total VFA (P<0.01) among different long-chain fatty acids tested. The molar proportion of acetate in total VFA significantly differed among treatments (P<0.01) and sampling time points (P<0.01), but not treatment×time point interactions (P>0.05). In contrast, the molar proportion of propionate did not differ among treatments during the whole incubation (P>0.05). However, for butyrate molar proportions, significant differences were found not only among sampling time points but also among treatments and treatment×time point interactions (P<0.01), with eicosapentaenoic acid having the highest value (P<0.01). Additionally, no statistically significant differences were found in the acetate to propionate ratios among treatments groups (P>0.05), even the treatments stearic acid and α-linolenic acid were numerically higher than the others. The inclusion of 3% long-chain unsaturated fatty acids differing in the degree of unsaturation brought out a significant quadratic regression relation between the total VFA concentration and the double bond number of fatty acid. In conclusion, the α-linolenic acid with 3 double bonds appeared better for improving rumen microbial fermentation and the total VFA concentration.

Early crop yield forecasting is important for food safety as well as large-scale food related planning. The phenology-adjusted spectral indices derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to develop liner regression models with the county-level corn yield data in Northeast China. We also compared the different spectral indices in predicting yield. The results showed that, using Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Land Surface Water Index (LSWI), the best time to predict corn yields was 55-60 days after green-up date. LSWI showed the strongest correlation (R2=0.568), followed by EVI (R2=0.497) and NDWI (R2=0.495). The peak correlation between Wide Dynamic Range Vegetation Index (WDRVI) and yield was detected 85 days after green-up date (R2=0.506). The correlation was generally low for Normalized Difference Vegetation Index (NDVI) (R2=0.385) and no obvious peak correlation existed for NDVI. The coefficients of determination of the different spectral indices varied from year to year, which were greater in 2001 and 2004 than in other years. Leave-one-year-out approach was used to test the performance of the model. Normalized root mean square error (NRMSE) ranged from 7.3 to 16.9% for different spectral indices. Overall, our results showed that crop phenology-tuned spectral indices were feasible and helpful for regional corn yield forecasting.