热带普通小球藻培养模式的筛选及其培养基的优化

【背景】从海南热带海区中分离得到一株微藻,其生长速度快、适应力强,经鉴定该微藻为普通小球藻。【目的】提高热带普通小球藻的生长速率。【方法】以"宁波大学3#微藻培养液配方"为基础培养液,分别添加有机碳(C6H12O6和CH3COONa)对热带普通小球藻进行自养、兼养及异养培养,获得促进热带普通小球藻快速生长的培养方式。在"宁波大学3#微藻培养液配方"的基础上对热带普通小球藻的兼养培养基配方进行优化,并用优化兼养培养基与"宁波大学3#微藻培养基"对比培养热带普通小球藻。【结果】添加6 g/L CH3COONa的兼养模式促进热带普通小球藻生长效果最好;优化的兼养培养基配方为:6 g/L CH3COONa,20 mg/L(NH4)2SO4-N,5 mg/L Na H2PO4-P,3 mg/L Fe SO4-Fe,1 mg/L Vitamin B1和0.000 5 mg/L Vitamin B12。对比培养实验结果显示,培养第6天,兼养培养液收获的生物量(细胞密度)达4.20×107 cells/m L,是"宁波大学3#配方微藻培养液"的2.30倍。【结论】兼养培养模式为热带普通小球藻的最佳培养模式,优化的兼养培养基极显著地提高了热带普通小球藻的生物量(P0.01)。     

塔拉多糖的脱色工艺化研究

塔拉多糖是一种半乳甘露聚糖胶,对于我们具有非常重要的应用价值。本实验主要对塔拉提取物中的塔拉多糖进行脱色工艺化研究;在单因素实验的基础上,对活性炭颗粒质量、脱色时间、脱色温度以及脱色次数这四种因素进行正交优化实验,其最佳脱色实验参数为：活性炭颗粒0.6 g,脱色45 min,脱色温度45℃脱色次数3次,脱色率可以达到50.21%,同时多糖类保留率为90.39%。     

Environmental DNA analysis shows high potential as a tool for estimating intraspecific genetic diversity in a wild fish population

Environmental DNA (eDNA) analysis has recently been used as a new tool for estimating intraspecific diversity. However, whether known haplotypes contained in a sample can be detected correctly using eDNA‐based methods has been examined only by an aquarium experiment. Here, we tested whether the haplotypes of Ayu fish (Plecoglossus altivelis altivelis) detected in a capture survey could also be detected from an eDNA sample derived from the field that contained various haplotypes with low concentrations and foreign substances. A water sample and Ayu specimens collected from a river on the same day were analysed by eDNA analysis and Sanger sequencing, respectively. The 10 L water sample was divided into 20 filters for each of which 15 PCR replications were performed. After high‐throughput sequencing, denoising was performed using two of the most widely used denoising packages, unoise3 and dada2 . Of the 42 haplotypes obtained from the Sanger sequencing of 96 specimens, 38 (unoise3 ) and 41 (dada2 ) haplotypes were detected by eDNA analysis. When dada2 was used, except for one haplotype, haplotypes owned by at least two specimens were detected from all the filter replications. Accordingly, although it is important to note that eDNA‐based method has some limitations and some risk of false positive and false negative, this study showed that the eDNA analysis for evaluating intraspecific genetic diversity provides comparable results for large‐scale capture‐based conventional methods. Our results suggest that eDNA‐based methods could become a more efficient survey method for investigating intraspecific genetic diversity in the field.     

A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method

China's high‐speed economic development and reliance on overconsumption of natural resources have led to serious environmental pollution. Environmental taxation is seen as an effective economic tool to help mitigate air pollution. In order to assess the effects of different scenarios of environmental taxation policies, we propose a frontier‐based environmentally extended input–output optimization model with explicit emission abatement sectors to reflect the inputs and benefits of abatement. Frontier analysis ensures policy scenarios are assessed under the same technical efficiency benchmark, while input–output analysis depicts the wide range of economic transactions among sectors of an economy. Four scenarios are considered in this study, which are increasing specific tax rates of SO₂, NO_x, and soot and dust separately and increasing all three tax rates simultaneously. Our estimation results show that: raising tax rates of SO₂, NO_x, and soot and dust simultaneously would have the highest emission reduction effects, with the SO₂ tax rate making the greatest contribution to emission reduction. Raising the soot and dust tax rate is the most environmentally friendly strategy due to its highest abatement to welfare through avoided health costs. The combination of frontier analysis and input–output analysis provides policy makers a comprehensive and sectoral approach to assess costs and benefits of environmental taxation.     

Mapping DNA damage‐dependent genetic interactions in yeast via party mating and barcode fusion genetics

Condition‐dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State‐of‐the‐art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double‐mutant strains, does not scale readily to multi‐condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG‐GI), by which double‐mutant strains generated via en masse “party” mating can also be monitored en masse for growth to detect genetic interactions. By using site‐specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG‐GI enables multiplexed quantitative tracking of double mutants via next‐generation sequencing. We applied BFG‐GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4‐nitroquinoline 1‐oxide (4NQO), bleomycin, zeocin, and three other DNA‐damaging environments. BFG‐GI recapitulated known genetic interactions and yielded new condition‐dependent genetic interactions. We validated and further explored a subnetwork of condition‐dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53.     

Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks

In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS²Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS²O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS²O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS²O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.     

Can dominance genetic variance be ignored in evolutionary quantitative genetic analyses of wild populations?

Accurately estimating genetic variance components is important for studying evolution in the wild. Empirical work on domesticated and wild outbred populations suggests that dominance genetic variance represents a substantial part of genetic variance, and theoretical work predicts that ignoring dominance can inflate estimates of additive genetic variance. Whether this issue is pervasive in natural systems is unknown, because we lack estimates of dominance variance in wild populations obtained in situ. Here, we estimate dominance and additive genetic variance, maternal variance, and other sources of nongenetic variance in eight traits measured in over 9000 wild nestlings linked through a genetically resolved pedigree. We find that dominance variance, when estimable, does not statistically differ from zero and represents a modest amount (2-36%) of genetic variance. Simulations show that (1) inferences of all variance components for an average trait are unbiased; (2) the power to detect dominance variance is low; (3) ignoring dominance can mildly inflate additive genetic variance and heritability estimates but such inflation becomes substantial when maternal effects are also ignored. These findings hence suggest that dominance is a small source of phenotypic variance in the wild and highlight the importance of proper model construction for accurately estimating evolutionary potential.     

Phenotypic and genetic differentiation between diadromous and landlocked puyen Galaxias maculatus

This study reports the phenotypic and genetic differences between individuals of puyen Galaxias maculatus from two sites in the same river basin in Tierra del Fuego National Park, southern South America. Individuals from the two sampling sites presented morphometric and genetic differences. The morphometric differences indicated that individuals from Laguna Negra (LN) were short and more robust and had large eyes, whereas those from Arroyo Negro (AN) were thin and elongated and had small eyes. Genetic differences showed that AN individuals had a greater genetic structuration and an older demographic history than LN individuals. The results of this study affirmed that the individuals from the two sampling sites belong to different populations with a high degree of isolation. The demographic history could indicate that the individuals of G. maculatus which migrated to northern areas during the last glaciation settled in the Beagle Channel after its formation. The LN population could have originated after the retreat of the glaciers, migrating from AN.     

The survivin molecule as a double-edged sword in cellular physiologic and pathologic conditions and its role as a potential biomarker and therapeutic target in cancer

Survivin is a member of the family of apoptosis inhibitory proteins with increased expression level in most cancerous tissues. Evidence shows that survivin plays regulatory roles in proliferation or survival of normal adult cells, principally vascular endothelial cells, T lymphocytes, primitive hematopoietic cells, and polymorphonuclear neutrophils. Survivin antiapoptotic role is, directly and indirectly, related to caspase proteins and shows its role in cell division through the chromosomal passenger complex. Survivin contains many genetic polymorphisms that the role of some variations has been proven in several cancers. The −31G/C polymorphism is one of the most important survivin mutations which is located in the promoter region on a CDE/CHR motif. This polymorphism can upregulate the survivin messenger RNA. In addition, its allele C can increase the risk of cancers in 1.27-fold than allele G. Considering the fundamental role of survivin in different cancers, this protein could be considered as a new therapeutic target in cancer treatment. For this purpose, various strategies have been designed including the prevention of survivin expression through inhibition of mRNA translation using antagonistic molecules, inhibition of survivin gene function through small inhibitory molecules, gene therapy, and immunotherapy. In this study, we describe the structure, played roles in physiological and pathological states and genetic polymorphisms of survivin. Finally, the role of survivin as a potential target in cancer therapy given challenges ahead has been discussed.