LOX-1过表达诱发H9C2心肌细胞肥大

目的:构建携带过表达大鼠凝集素样氧化低密度脂蛋白受体-1(LOX-1)基因的慢病毒载体,研究LOX-1与心肌细胞肥大的关系。方法:构建大鼠LOX-1基因pHIV-LOX-1过表达质粒,与包装质粒psPAX2、pMD2G共转染293T细胞,检测其侵染效率。包装慢病毒并侵染H9C2心肌细胞,72 h后观察其侵染效率。qPCR法检测细胞LOX-1表达。检测过表达LOX-1后心肌细胞面积及其蛋白含量变化。结果:成功构建过表达LOX-1 H9C2心肌细胞。过表达LOX-1组(Lv.LOX-1+)心肌细胞面积(16691.890±1022.368μm2)较对照组(Lv.NC)(3459.865±343.175μm2)显著增加(P0.001)。Lv.LOX-1+组心肌细胞蛋白含量(132.457±8.188 pg/cell)较Lv.NC组(45.095±1.655 pg/cell)显著增加(P0.001)。结论:LOX-1过表达能诱导H9C2心肌细胞肥大。     

Effects of global warming on mosquitoes & mosquito‐borne diseases and the new strategies for mosquito control

Global warming has shortened mosquitoes’ lifecycle period and increased the disease transmission rates by mosquito vectors. We reviewed only three mosquito‐borne diseases: malaria, dengue fever, and the Japanese encephalitis. Billions of people get infected with those diseases and millions of people die every year. Although we struggle to find the most effective way to control mosquitoes using various methods (including pesticides), mosquito‐borne diseases are still among the most serious problems being faced. This paper, therefore, reviews the strategies for controlling mosquitoes. The use of pesticides to control mosquitoes might have more negative effects on humans and environments than benefits. Although the development of genetically modified (GM) mosquitoes raises new hopes for effective mosquito control, it will take longer to assess the risks to humans and environments. Furthermore, there has been concern about the possible adverse effects from the release of GM mosquitoes into the environment. The various mosquito traps may not be as effective at controlling only female mosquito populations. Therefore, new strategies for the control of mosquitoes are vital. The smart mosquito counter device was developed by Korean Centre for Disease Control (KCDC) in 2013. The mosquito pest control office is able to set up the appropriate mosquito control strategies by using quantitative mosquito information. The smart device will bring mosquito control in line with modern smart generation technology and the device will also soon be able to identify different mosquito species. This new strategy will change the methods of mosquito control and will provide beneficial effects toward sustainable nature and human health.     

Searching for a successful HDL-based treatment strategy

Despite strong evidence that HDL-cholesterol levels predict atherosclerotic events in a population, attempts at using an HDL-based treatment strategy have not yet been successful. Most of the efforts to date have focused on raising plasma HDL-cholesterol levels. This brief review focuses on a different strategy, which is based on the use of 18-amino acid apoA-I mimetic peptides. The story of these peptides spans decades and illustrates the remarkable complexity of HDL-based treatment strategies, but suggests that such a strategy may still be successful.     

Using a resource selection approach to predict the suitability of alpine habitats for a common herbivore

Climate change models predict that Australia's alpine areas will experience major declines in snow cover, which, in turn, may provide suitable habitat for species presently restricted to lower altitudes. As a result, there are concerns among land managers that many species will invade alpine areas and have a detrimental impact on fragile alpine ecosystems. However, species survival in such areas, irrespective of snow cover, is greatly dependent on the availability of suitable resources. This study investigated the selection of resources by common wombats Vombatus ursinus, which are currently restricted to, but widespread throughout, the subalpine zone of the Snowy Mountains. Our objectives were to identify habitat choices, and build a model of habitat suitability over the broader landscape, to investigate the likelihood of this common herbivore inhabiting the alpine zone. Global positioning system data were obtained from collared wombats, which were tracked for up to a year, to examine resource selection. Resource selection within the home range of individual wombats revealed that topographic position, vegetation cover, drainage, past fire disturbance, and roads were important predictors of locations. A global model showed that wombats selected locations with mid‐elevations, moderate slopes, closer to water courses and roads, and with a lower proportion of grassland, which are discussed in relation to foraging and burrowing requirements. Mapping of the global model illustrated that alpine areas had a low relative probability of use by this species. Consequently, wombats are unlikely to inhabit alpine areas under given climate change scenarios of less snow cover, because the area (presently) does not contain suitable resources necessary for a wombat to maintain a home range. Researchers and managers need to be mindful of how the spatial distribution of resources, in addition to species climatic tolerances, will influence potential range shifts.     

Population genetic structure of the western cherry fruit fly Rhagoletis indifferens (Diptera: Tephritidae) in British Columbia,Canada

相似文献   

Seagrass rehabilitation off metropolitan Adelaide: a case study of loss,action, failure and success

Heavy losses of 6200 ha of seagrass off the Adelaide metropolitan coast since 1949 have had substantial implications for beach management, fisheries and biodiversity. Here, we describe for managers some promising initial trials to develop a cost‐effective method to rehabilitate some of these lost seagrasses.     

The gliding speed of migrating birds: slow and safe or fast and risky?

Aerodynamic theory postulates that gliding airspeed, a major flight performance component for soaring avian migrants, scales with bird size and wing morphology. We tested this prediction, and the role of gliding altitude and soaring conditions, using atmospheric simulations and radar tracks of 1346 birds from 12 species. Gliding airspeed did not scale with bird size and wing morphology, and unexpectedly converged to a narrow range. To explain this discrepancy, we propose that soaring‐gliding birds adjust their gliding airspeed according to the risk of grounding or switching to costly flapping flight. Introducing the Risk Aversion Flight Index (RAFI, the ratio of actual to theoretical risk‐averse gliding airspeed), we found that inter‐ and intraspecific variation in RAFI positively correlated with wing loading, and negatively correlated with convective thermal conditions and gliding altitude, respectively. We propose that risk‐sensitive behaviour modulates the evolution (morphology) and ecology (response to environmental conditions) of bird soaring flight.     

The Tomato spotted wilt virus cell‐to‐cell movement protein (NSM) triggers a hypersensitive response in Sw‐5‐containing resistant tomato lines and in Nicotiana benthamiana transformed with the functional Sw‐5b resistance gene copy

Although the Sw‐5 gene cluster has been cloned, and Sw‐5b has been identified as the functional gene copy that confers resistance to Tomato spotted wilt virus (TSWV), its avirulence (Avr) determinant has not been identified to date. Nicotiana tabacum ‘SR1‘ plants transformed with a copy of the Sw‐5b gene are immune without producing a clear visual response on challenge with TSWV, whereas it is shown here that N. benthamiana transformed with Sw‐5b gives a rapid and conspicuous hypersensitive response (HR). Using these plants, from all structural and non‐structural TSWV proteins tested, the TSWV cell‐to‐cell movement protein (NS_M) was confirmed as the Avr determinant using a Potato virus X (PVX) replicon or a non‐replicative pEAQ‐HT expression vector system. HR was induced in Sw‐5b‐transgenic N. benthamiana as well as in resistant near‐isogenic tomato lines after agroinfiltration with a functional cell‐to‐cell movement protein (NS_M) from a resistance‐inducing (RI) TSWV strain (BR‐01), but not with NS_M from a Sw‐5 resistance‐breaking (RB) strain (GRAU). This is the first biological demonstration that Sw‐5‐mediated resistance is triggered by the TSWV NS_M cell‐to‐cell movement protein.     

Metabolic network prediction through pairwise rational kernels

Background

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations.

Results

We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy values have been improved, while maintaining lower construction and execution times.

Conclusions

The power of using kernels is that almost any sort of data can be represented using kernels. Therefore, completely disparate types of data can be combined to add power to kernel-based machine learning methods. When we compared our proposal using PRKs with other similar kernel, the execution times were decreased, with no compromise of accuracy. We also proved that by combining PRKs with other kernels that include evolutionary information, the accuracy can also also be improved. As our proposal can use any type of sequence data, genes do not need to be properly annotated, avoiding accumulation errors because of incorrect previous annotations.