超连续谱激光可见谱段致人眼眩目效应研究

本文采用超连续谱激光光源滤除其红外部分仅输出可见谱段部分,在不超过国家安全标准允许的最大辐照量条件下,以正入射方式照射人眼后,记录并分析在明、暗适应条件下中心极限视力恢复时间、中心近极限视力恢复时间和视觉后像持续时间,明确超连续谱激光可见谱段对人眼的眩目效果。明适应下激光照射0.1 s导致人眼中心极限视力恢复时间为31~119 s,中心近极限视力恢复时间为19~76 s;暗适应下激光照射0.1 s导致人眼中心极限视力恢复时间为26~223 s,中心近极限视力恢复时间为13~123 s;明、暗适应下导致人眼眩目效应的最小功率密度值分别为0.055 mW/cm^2和0.005 mW/cm^2。结果表明,超连续谱激光可见谱段对人眼有良好的眩目效果,可导致数十秒至数百秒的中心视力下降,随着照射功率密度增高,眩目效应增强,显示出较好的量效关系,且相同功率密度时暗适应下人眼的眩目效果优于明适应。该研究探究了明、暗适应条件下超连续谱激光对人眼眩目效应,明确了超连续谱激光与人眼眩目的量效关系。     

Offspring phenotype is shaped by the nonsperm fraction of semen

In a large majority of animal species, the only contribution of males to the next generation has been assumed to be their genes (sperm). However, along with sperm, seminal plasma contains a wide array of extracellular factors that have many important functions in reproduction. Yet, the potential intergenerational effects of these factors are virtually unknown. We investigated these effects in European whitefish (Coregonus lavaretus) by experimentally manipulating the presence and identity of seminal plasma and by fertilizing the eggs of multiple females with the manipulated and unmanipulated semen of several males in a full‐factorial breeding design. The presence of both own seminal plasma and foreign seminal plasma inhibited sperm motility, and the removal of own seminal plasma decreased embryo survival. Embryos hatched significantly earlier after both semen manipulations than in control fertilizations; foreign seminal plasma also increased offspring aerobic swimming performance. Given that our experimental design allowed us to control potentially confounding sperm‐mediated (sire) effects and maternal effects, our results indicate that seminal plasma may have direct intergenerational consequences for offspring phenotype and performance. This novel source of offspring phenotypic variance may provide new insights into the evolution of polyandry and mechanisms that maintain heritable variation in fitness and associated female mating preferences.     

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.     

Reduced expression of CYLD promotes cell survival and inflammation in gefitinib‐treated NSCLC PC‐9 cells: Targeting CYLD may be beneficial for acquired resistance to gefitinib therapy

The application of tyrosine kinase inhibitors (TKIs) to the epidermal growth factor receptor (EGFR) has been proven to be highly effective for non‐small‐cell lung cancer (NSCLC). However, patients often evolve into acquired resistance. The secondary mutations in EGFR account for nearly half of the acquired resistance. While the remaining 50% of patients exhibit tolerance to EGFR‐TKIs with unclear mechanism(s). Cylindromatosis (CYLD), a deubiquitinase, functions as a tumor suppressor to regulate cell apoptosis, proliferation, and immune response, and so on. The role of CYLD in NSCLC EGFR‐TKI resistance remains elusive. Here, we found CYLD was upregulated in PC‐9 cells, whereas downregulated in PC‐9 acquired gefitinib‐resistant (PC‐9/GR) cells in response to the treatment of gefitinib, which is consistent with the results in the Gene Expression Omnibus database. Overexpression of CYLD promoted a more apoptotic death ratio in PC‐9/GR cells than that in PC‐9 cells. In addition, silencing the expression of CYLD resulted in an increase of the expression level of interleukin‐6, transforming growth factor‐β and tumor necrosis factor‐α, which may contribute to acquired resistance of PC‐9 cells to gefitinib. Taken together, our data in vitro demonstrate that PC‐9/GR cells downregulated CYLD expression, enhanced subsequent CYLD‐dependent antiapoptotic capacity and inflammatory response, which may provide a possible target for acquired gefitinib‐resistant treatment in NSCLC.     

Artificial neural network and response surface methodology: a comparative analysis for optimizing rice straw pretreatment and saccharification

Abstract

The present study demonstrates a comparative analysis between the artificial neural network (ANN) and response surface methodology (RSM) as optimization tools for pretreatment and enzymatic hydrolysis of lignocellulosic rice straw. The efficacy for both the processes, that is, pretreatment and enzymatic hydrolysis was evaluated using correlation coefficient (R²) & mean squared error (MSE). The values of R² obtained by ANN after training, validation, and testing were 1, 0.9005, and 0.997 for pretreatment and 0.962, 0.923, and 0.9941 for enzymatic saccharification, respectively. On the other hand, the R² values obtained with RSM were 0.9965 for cellulose recovery and 0.9994 for saccharification efficiency. Thus, ANN and RSM together successfully identify the substantial process conditions for rice straw pretreatment and enzymatic saccharification. The percentage of error for ANN and RSM were 0.009 and 0.01 for cellulose recovery and for 0.004 and 0.005 for saccharification efficiency, respectively, which showed the authority of ANN in exemplifying the non-linear behavior of the system.     

Improving the aqueous solubility of HCV‐E2 glycoprotein epitope mimics by cyclization using POLAR hinges

In this research we describe the improvement of the water‐solubility of cyclic epitope mimics based on the HCV E2 glycoprotein by incorporation of suitable polar hinges. The poor solubility of epitope mimics based on peptide sequences in the envelope (E2) protein hampered their synthesis and purification and made it very difficult to prepare the molecular constructs for evaluation of their bioactivity. Since changes in the amino acid composition are hardly possible in these epitope mimics in order to increase water‐solubility, a polar cyclization hinge may offer a remedy leading to a significant increase of polarity and therefore water solubility. These polar hinges were applied in the synthesis of better water‐soluble HCV‐E2 epitopes. An azide functionality in the polar hinges allowed attachment of a tetraethylene glycol linker by Cu‐catalyzed azide‐alkyne cyclo‐addition (CuAAC) for a convenient conjugation to ELISA plates in order to evaluate the bio‐activity of the epitope mimics. The immunoassays showed that the use of more polar cyclization hinges still supported anti‐HCV antibody recognition and did not negatively influence their binding. This significantly increased solubility induced by polar hinges should therefore allow for the molecular construction and ultimate evaluation of synthetic vaccine molecules.     

Forest responses to simulated elevated CO2 under alternate hypotheses of size‐ and age‐dependent mortality

Elevated atmospheric carbon dioxide (eCO₂) is predicted to increase growth rates of forest trees. The extent to which increased growth translates to changes in biomass is dependent on the turnover time of the carbon, and thus tree mortality rates. Size‐ or age‐dependent mortality combined with increased growth rates could result in either decreased carbon turnover from a speeding up of tree life cycles, or increased biomass from trees reaching larger sizes, respectively. However, most vegetation models currently lack any representation of size‐ or age‐dependent mortality and the effect of eCO₂ on changes in biomass and carbon turnover times is thus a major source of uncertainty in predictions of future vegetation dynamics. Using a reduced‐complexity form of the vegetation demographic model the Functionally Assembled Terrestrial Ecosystem Simulator to simulate an idealised tropical forest, we find increases in biomass despite reductions in carbon turnover time in both size‐ and age‐dependent mortality scenarios in response to a hypothetical eCO₂‐driven 25% increase in woody net primary productivity (wNPP). Carbon turnover times decreased by 9.6% in size‐dependent mortality scenarios due to a speeding up of tree life cycles, but also by 2.0% when mortality was age‐dependent, as larger crowns led to increased light competition. Increases in aboveground biomass (AGB) were much larger when mortality was age‐dependent (24.3%) compared with size‐dependent (13.4%) as trees reached larger sizes before death. In simulations with a constant background mortality rate, carbon turnover time decreased by 2.1% and AGB increased by 24.0%, however, absolute values of AGB and carbon turnover were higher than in either size‐ or age‐dependent mortality scenario. The extent to which AGB increases and carbon turnover decreases will thus depend on the mechanisms of large tree mortality: if increased size itself results in elevated mortality rates, then this could reduce by about half the increase in AGB relative to the increase in wNPP.     

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.     

Multiple trade‐offs regulate the effects of woody plant removal on biodiversity and ecosystem functions in global rangelands

Woody plant encroachment is a major land management issue. Woody removal often aims to restore the original grassy ecosystem, but few studies have assessed the role of woody removal on ecosystem functions and biodiversity at global scales. We collected data from 140 global studies and evaluated how different woody plant removal methods affected biodiversity (plant and animal diversity) and ecosystem functions (plant production, hydrological function, soil carbon) across global rangelands. Our results indicate that the impact of removal is strongly context dependent, varying with the specific response variable, removal method, and traits of the target species. Over all treatments, woody plant removal increased grass biomass and total groundstorey diversity. Physical and chemical removal methods increased grass biomass and total groundstorey biomass (i.e., non‐woody plants, including grass biomass), but burning reduced animal diversity. The impact of different treatment methods declined with time since removal, particularly for total groundstorey biomass. Removing pyramid‐shaped woody plants increased total groundstorey biomass and hydrological function but reduced total groundstorey diversity. Environmental context (e.g., aridity and soil texture) indirectly controlled the effect of removal on biomass and biodiversity by influencing plant traits such as plant shape, allelopathic, or roots types. Our study demonstrates that a one‐size‐fits‐all approach to woody plant removal is not appropriate, and that consideration of woody plant identity, removal method, and environmental context is critical for optimizing removal outcomes. Applying this knowledge is fundamental for maintaining diverse and functional rangeland ecosystems as we move toward a drier and more variable climate.     

Symbiont community diversity is more variable in corals that respond poorly to stress

Coral reefs are declining globally as climate change and local water quality press environmental conditions beyond the physiological tolerances of holobionts—the collective of the host and its microbial symbionts. To assess the relationship between symbiont composition and holobiont stress tolerance, community diversity metrics were quantified for dinoflagellate endosymbionts (Family: Symbiodiniaceae) from eight Acropora millepora genets that thrived under or responded poorly to various stressors. These eight selected genets represent the upper and lower tails of the response distribution of 40 coral genets that were exposed to four stress treatments (and control conditions) in a 10‐day experiment. Specifically, four ‘best performer’ coral genets were analyzed at the end of the experiment because they survived high temperature, high pCO₂, bacterial exposure, or combined stressors, whereas four ‘worst performer’ genets were characterized because they experienced substantial mortality under these stressors. At the end of the experiment, seven of eight coral genets mainly hosted Cladocopium symbionts, whereas the eighth genet was dominated by both Cladocopium and Durusdinium symbionts. Symbiodiniaceae alpha and beta diversity were higher in worst performing genets than in best performing genets. Symbiont communities in worst performers also differed more after stress exposure relative to their controls (based on normalized proportional differences in beta diversity), than did best performers. A generalized joint attribute model estimated the influence of host genet and treatment on Symbiodiniaceae community composition and identified strong associations among particular symbionts and host genet performance, as well as weaker associations with treatment. Although dominant symbiont physiology and function contribute to host performance, these findings emphasize the importance of symbiont community diversity and stochasticity as components of host performance. Our findings also suggest that symbiont community diversity metrics may function as indicators of resilience and have potential applications in diverse disciplines from climate change adaptation to agriculture and medicine.