This study aimed to perform a rapid in situ assessment of the quality of peach kernels using near infrared (NIR) spectroscopy, which included identifications of authenticity, species, and origins, and amygdalin quantitation. The in situ samples without any pretreatment were scanned by a portable MicroNIR spectrometer, while their powder samples were scanned by a benchtop Fourier transform NIR (FT-NIR) spectrometer. To improve the performance of the in situ determination model of the portable NIR spectrometer, the two spectrometers were first compared in identification and content models of peach kernels for both in situ and powder samples. Then, the in situ sample spectra were transferred by using the improved principal component analysis (IPCA) method to enhance the performance of the in situ model. After model transfer, the prediction performance of the in situ sample model was significantly improved, as shown by the correlation coefficient in the prediction set (Rp), root means square error of prediction (RMSEP), and residual prediction deviation (RPD) of the in situ model reached 0.9533, 0.0911, and 3.23, respectively, and correlation coefficient in the test set (Rt) and root means square error of test (RMSET) reached 0.9701 and 0.1619, respectively, suggesting that model transfer could be a viable solution to improve the model performance of portable spectrometers.
Prunus persica , Spectroscopy, Near-Infrared , Spectroscopy, Near-Infrared/methods , Powders , Calibration , Principal Component Analysis , Least-Squares Analysis
The gregarious lifestyle of lepidopteran larvae is diverse and shaped by a complex interplay of ecological and evolutionary factors. Our review showed that the larval-aggregation behavior has been reported in 23 lepidopteran families, indicating multiple evolution of this behavior. Some larvae live in sibling groups throughout all larval instars and even pupation stages, which may result from the kin-selection. In contrast, group fusion may occur among different sibling or foraging groups of larvae and form larger aggregates, and the gregariousness of these species might be driven by the group-selection. While group size and foraging patterns vary greatly across species, it is generally associated with improved larval survivorship and accelerated development. However, the advantages of group living, such as facilitating feeding activities, adjusting the temperature, and defending natural enemies, may diminish along with development, with strong intraspecific competition occurring at later instars, even when food is abundant. Therefore, the group sizes and fission-fusion dynamics of certain gregarious lepidopteran larvae may be a consequence of their cost-benefit balance depending on various biotic and abiotic factors. Trail and aggregation pheromones, silk trails, or body contact contribute to collective movement and group cohesion of gregarious lepidopteran larvae. However, frequent contact among group members may cause the horizontal transmission of pathogens and pesticides, which may bring an integrated pest management strategy controlling gregarious lepidopteran pests.
The excessive secretion of H2O2 within cells is closely associated with cellular dysfunction. Therefore, high sensitivity in situ detection of H2O2 released from living cells was valuable in clinical diagnosis. In the present work, a novel electrochemical cells sensing platform by synthesizing copper nanoclusters (CuNCs) at room temperature based on DNA nanoribbon (DNR) as a template (DNR-CuNCs). The tight and ordered arrangement of nanostructured assemblies of DNR-CuNCs conferred the sensor with superior stability (45 days) and electrochemical performance. The MUC1 aptamer extending from the DNR template enabled the direct capture MCF-7 cells on electrode surface, this facilitated real-time monitoring of H2O2 release from stimulated MCF-7 cells. While the captured MCF-7 cells on the electrode surface significantly amplified the current signal of H2O2 release compared with the traditional electrochemical detection H2O2 released signal by MCF-7 cells in PBS solution. The approach provides an effective strategy for the design of versatile sensors and achieving monitored cell release of H2O2 in long time horizon (10 h). Thereby expanding the possibilities for detecting biomolecules from live cells in clinical diagnosis and biomedical applications.
Biosensing Techniques , Nanostructures , Nanotubes, Carbon , Humans , Copper/chemistry , Hydrogen Peroxide , DNA/chemistry , Nanostructures/chemistry , Electrochemical Techniques
The red imported fire ant, Solenopsis invicta Buren, is a severe pest with agricultural, ecological, and medical significance. The baiting treatment is one of the main methods to control S. invicta. However, few studies have evaluated the acceptance of fire ant bait. Here, field and laboratory studies were conducted to investigate the foraging behaviors of S. invicta responding to fire ant baits containing different concentrations of active ingredients (fipronil, abamectin, or indoxacarb). Field studies showed that S. invicta transported significantly less 0.0125% fipronil bait than control bait (without toxicant) and 0.0001% fipronil bait. The number of foraging ants significantly decreased with an increase in fipronil concentration. Our previous study showed that S. invicta usually buries the food treated with repellent chemicals, and interestingly, significantly more soil particles were transported into tubes containing 0.0001% fipronil bait than tubes containing control bait or 0.0125% fipronil bait. In addition, S. invicta transported significantly less 0.0005% abamectin bait than control bait, and significantly fewer ants were found in tubes containing 0.0125% abamectin bait than control bait. However, there was no significant difference in bait transport, number of foraging ants, and weight of soil particles relocated in tubes containing different concentrations of indoxacarb bait. In addition, laboratory studies showed that S. invicta transported significantly less 0.0125% fipronil bait than control bait and bait containing abamectin (0.0025% or 0.0125%) or indoxacarb (0.0125% or 0.0625%). In addition, the transport speed for the 0.0125% fipronil bait was the slowest. These results show that specific concentrations of some active ingredients may negatively affect bait acceptance for S. invicta, and should be avoided in fire ant bait production.
Visible-light-driven organic transformations boosting by localized surface plasmon resonance (LSPR) have been attracting considerable interests. Gold-palladium (Au-Pd) bimetallic nanoparticles (NPs) are considered as ideal plasmonic catalysts realizing efficient light-driven catalysis. Nevertheless, stability and adjustability of plasmonic Au-Pd NPs remain to be a challenging task. Herein, we designed the controlled Au-Pd cores in ceria (CeO2) hollow spheres (Au-Pd@h-CeO2) as nanoreactor for Suzuki cross-coupling reactions. Under visible light irradiation, the Au-Pd@h-CeO2 exhibited remarkable photocatalytic performance with a turnover frequency (TOF) value as high as 797 h-1. More impressively, the coupling reactions of aryl chlorides bearing electron-withdrawing groups proceeded better and afforded the corresponding desired products in good yields. Detailed structural, optical and photoelectrochemical characterizations unraveled that the enhanced photocatalytic efficiency of Au-Pd@h-CeO2 was attributed to the LSPR effect of controllable Au-Pd cores and their synergetic effect of hollow CeO2 shells. The merits of this hollow sphere architecture lied on as followed: (I) Incident light could be reflected and refracted between the inner cores and outer shells, which extended the trapping of incident light, and then enhanced the light harvesting efficiency; (II) the mesoporous architecture of CeO2 hollow spheres provided a huge specific surface area and numerous mesoporous channels, which could enhance the absorption of reactants and provided more active sites; (III) LSPR excitation of Au-Pd NPs and band-gap excitation of CeO2 simultaneously occurred under visible light illumination, inducing a more efficient separation and transfer of charge carriers. Furthermore, due to the confinment effect of CeO2 shells, the Au-Pd@h-CeO2 exhibited an excellent reusability after six cycles without significant deactivation of yield. Our findings provided a facile way to design highly efficient plasmonic-enhanced photocatalysts utilized for catalytic organic reactions.
Public health and health inequality have been widely researched as they are essential for human development and social justice. Although factors influencing public health and health inequality have been explored, an integrated and comprehensive analysis of social, economic, and environmental indicators' effects on public health and health inequality globally is yet to be conducted. The current study addresses this gap by using a theoretical framework that integrates these three dimensions, examining their effects on public health and health inequality from the perspective of vulnerability. Considering the spatial heterogeneity across countries, spatial econometric models and geographically weighted regressions were conducted for the examination of these effects. Our findings reveal the social indicators of urbanisation ratio, social education level, and social governance capacity had positive effects on public health promotion and health inequality elimination globally. Besides these, environmental risk and economic capacity had relatively low impacts on health inequality. Further, the geographically weighted regression results indicate that vulnerability's effects on public health and health inequality varied significantly across countries. This integrated analysis provides national policymakers with a new perspective of vulnerability for public health promotion and health inequality reduction.
Fine particulate matter (PM2.5) is of widespread concern, as it poses a serious impact on economic development and human health. Although the influence of socioeconomic factors on PM2.5 has been studied, the constitution and the effect analysis of social vulnerability to PM2.5 remain unclear. In this study, a comprehensive theoretical framework with appropriate indicators for social vulnerability to PM2.5 was constructed. Using spatial autocorrelation analysis, a positive global spatial autocorrelation and notable local spatial cluster relationships were identified. Spatial econometric modeling and geographically weighted regression modeling were performed to explore the cause-effect relationship of social vulnerability to PM2.5. The spatial error model indicated that population and education inequality in the sensitivity dimension caused a significant positive impact on PM2.5, and biocapacity and social governance in the capacity dimension strongly contributed to the decrease of PM2.5 globally. The geographically weighted regression model revealed spatial heterogeneity in the effects of the social vulnerability variables on PM2.5 among countries. These empirical results can provide policymakers with a new perspective on social vulnerability as it relates to PM2.5 governance and targeted environmental pollution management.
Air Pollutants , Air Pollution , Air Pollutants/analysis , Air Pollution/analysis , China , Environmental Monitoring , Humans , Particulate Matter/analysis , Spatial Regression
The study of subjective well-being (SWB) has attracted considerable attention from scholars globally. This has stimulated numerous studies that have identified regional and individual factors associated with SWB, but the extant research lacks multi-level studies that simultaneously examine their influence on SWB. Environmental pollution is one of such factors, but few studies have investigated its effect on SWB in China particularly. The current study addressed these problems by conducting hierarchical linear regressions to explore the effects of regional and individual factors on Chinese people's SWB. Three major environmental pollutions (wastewater pollution, domestic waste pollution, and air pollution) were studied using data from the Chinese General Social Survey 2013 and China Statistical Yearbook 2014. The results indicated that wastewater pollution and domestic waste pollution had significant negative influence on SWB. Moreover, gross domestic product (GDP) per capita might contribute more to the improvement of SWB than income inequality. This implies that individuals' SWB might be enhanced by improving absolute income, which is consistent with the micro-level proposition of the Easterlin paradox. Overall, these findings signal that effective management of environmental pollution is essential for promoting the SWB of the people in China.
Environmental Pollution , Income , China , Gross Domestic Product , Humans , Socioeconomic Factors
Organic chemicals in the aquatic ecosystem may inhibit algae growth and subsequently lead to the decline of primary productivity. Growth inhibition tests are required for ecotoxicological assessments for regulatory purposes. In silico study is playing an important role in replacing or reducing animal tests and decreasing experimental expense due to its efficiency. In this work, a series of theoretical models was developed for predicting algal growth inhibition (log EC50) after 72 h exposure to diverse chemicals. In total 348 organic compounds were classified into five modes of toxic action using the Verhaar Scheme. Each model was established by using molecular descriptors that characterize electronic and structural properties. The external validation and leave-one-out cross validation proved the statistical robustness of the derived models. Thus they can be used to predict log EC50 values of chemicals that lack authorized algal growth inhibition values (72 h). This work systematically studied algal growth inhibition according to toxic modes and the developed model suite covers all five toxic modes. The outcome of this research will promote toxic mechanism analysis and be made applicable to structural diversity.
Chlorophyta/drug effects , Models, Theoretical , Organic Chemicals/toxicity , Quantitative Structure-Activity Relationship , Animals , Chlorophyta/growth & development , Computer Simulation , Ecosystem , Molecular Structure , Organic Chemicals/chemistry
