Palladium-Catalyzed (4 + 1) Annulation of 4-Vinylbenzodioxinones with Sulfur Ylides: Diastereoselective Synthesis of Dihydrobenzofuran Derivatives.

Palladium-catalyzed (4 + 1) annulation of 4-vinylbenzodioxinones with sulfur ylides has been developed to afford various dihydrobenzofuran derivatives in moderate to high yields with excellent diastereoselectivities. The scale-up reaction and further derivations of the product worked well, demonstrating the application potential of the current reaction in organic synthesis.

The roots of blue carbon: responses of mangrove stilt roots to variation in soil bulk density.

Mangroves harbour large soil organic carbon (C) pools. These C stocks are attributed to the production and slow decomposition of the below-ground biomass. Novel in-growth containers were used to assess the effect of soil bulk density (BD: 0.4, 0.8 and 1.2 g cm-3) on morphological, anatomical and chemical traits of the below-ground fraction of aerial roots of the mangrove Rhizophora stylosa. Dense soils increased total root biomass and primary root diameter, while the primary root length decreased. Furthermore, high soil BD reduced aerenchyma lacunae and led to the formation of structural features such as fibrous strands. These morphological and anatomical changes were not reflected in tissue chemistry, with lignin levels averaging 17.0 ± 0.6%, although roots grown in high BD had higher nitrogen levels. This likely affects decomposition rates. Thus, variation in soil BD has major implications for C sequestration in Rhizophora-dominated mangroves.

Soil inorganic carbon in mangroves of tropical China: patterns and implications.

Soil inorganic carbon (IC) is neglected in most blue carbon studies despite the globally significant role of the calcium carbonate cycle in ocean C balance and climate change. We sampled soils to 1 m depth from seven mangrove reserves in Hainan Island, China. Only 45 out of 509 samples were rich in IC (greater than 10 mg cm-3). Most of the IC-rich samples were found at the outer part of Qinglan Bay, which is adjacent to the largest coral reef zone of Hainan Island. Soil IC concentration ranged from 0 to 66 g kg-1 (or 0-67 mg cm-3), accounting for 0-92% of total C. IC concentration increased with soil depth where it was abundant. Soil pH was low (2.36-6.59) in IC-depleted soils, but increased to 5.67-7.99 in IC-rich soils. Soil total C stock and IC stock in mangroves of Hainan amounted to 0.76×106 and 0.12×106 Mg, respectively, with IC accounting for 16% of total C. Our study finds that carbonate concentrations can be high in mangrove soils but their spatial distribution indicates they are largely allochthonous in origin. Evidence of carbonate dissolution in mangroves suggests mangroves may increase total alkalinity to buffer acidification in seawater.

Nitrogen deposition cancels out exotic earthworm effects on plant-feeding nematode communities.

The activity and spread of exotic earthworms often are spatially correlated with N deposition because both arise from human activities. Exotic earthworms, in turn, can also greatly affect soil abiotic and biotic properties, as well as related ecological processes. Previous studies showed, for example, that earthworms can counteract the detrimental effects of plant-feeding nematodes on plant growth. However, potential interactive effects of N deposition and exotic earthworms on ecosystems are poorly understood. We explored the changes in density of plant-feeding nematodes in response to the presence of exotic earthworms, and whether these changes are altered by elevated N deposition in a two-factorial field mesocosm experiment at the Heshan National Field Research Station of Forest Ecosystem, in southern China. Our results show that earthworm addition marginally significantly increased the density of exotic earthworms and significantly increased the mass of earthworm casts. The total density of plant-feeding nematodes was not significantly affected by exotic earthworms or N deposition. However, exotic earthworms tended to increase the density of plant-feeding nematode taxa that are less detrimental to plant growth (r-strategists), while they significantly reduced the density of more harmful plant-feeding nematodes (K-strategists). Importantly, these earthworm effects were restricted to the ambient N deposition treatment, and elevated N deposition cancelled out the earthworm effect. Although exotic earthworms and N deposition interactively altered foliar N : P ratio in the target tree species, this did not result in significant changes in shoot and root biomass in the short term. Overall, our study indicates that N deposition can cancel out exotic earthworm-induced reductions in the density of harmful plant-feeding nematodes. These results suggest that anthropogenic N deposition can alter biotic interactions between exotic and native soil organisms with potential implications for ecosystem functioning.

[Multivariate Calibration Combined with Mass Spectrometry for Rapid Analysis].

A mixture of four substances of benzaldehyde, iso-octane, butyl acetate, acetophenone were quantitatively analyzed by mass spectrometry combined with chemometrics. The mass chromatogram data of mixture were proceeded with two methods for quantitative analysis. One is feature selection--Multiple Linear Regression (MLR) and the other is full spectrum--Partial Least Squares (PLS). The results show that the RMSEP of benzaldehyde were 0.062 and 0.091 after selecting m/z spectrum and full spectrum respectively; RMSEP of isooctane were 0.048 and 0.057 after selecting spectrum and full spectrum respectively; which of butyl acetate were 0.021 and 0.020 and of acetophenone were 0.010 and 0.032. The feature selection results of the mixture were better than that of the full spectrum modeling results expect butyl acetate which got similar results by the two methods.

Whole-tree dynamics of non-structural carbohydrate and nitrogen pools across different seasons and in response to girdling in two temperate trees.

Despite extensive research on the seasonal dynamics of non-structural carbohydrate (NSC) and nitrogen (N) concentrations, the size and relative contributions of NSC and N pools across different tree organs are not well understood. We have measured the changes in NSC and N concentrations in leaves, branches, stems and all root branch orders at monthly intervals in control and girdled trees of larch (Larix gmelinii) and ash (Fraxinus mandshurica). The biomass of each plant compartment was also determined to calculate the size of the NSC and N pools. In both species, 13-37% of the NSC and N pools were mobilized at the beginning of the growing season. Among the mobilized pools, stems and non-absorptive roots (branch orders 4-9) acted as the largest NSC sources in larch and ash, respectively, while branches served as the largest N source in both species. After stem girdling, 22 and 50% of the root NSC stores in larch and ash, respectively, were mobilized to maintain root activities during the growing season. Tree mortality was observed 1 year after girdling, at which time there was still an abundant NSC pool in the roots. We conclude that (1) different storage organs differ in their contribution to new tissue growth at the beginning of the growing season and that those storage organs holding higher fractions of the NSC or N pool are not necessarily those which mobilize more NSC or N; (2) tree growth may not be limited by carbon (C) availability; (3) C storage in non-absorptive roots plays an important role in maintaining tree survival after the termination of photosynthate flow from aboveground sources.

A new spectral variable selection pattern using competitive adaptive reweighted sampling combined with successive projections algorithm.

The competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA) method was proposed as a novel variable selection approach to process multivariate calibration. The CARS was first used to select informative variables, and then SPA to refine the variables with minimum redundant information. The proposed method was applied to near-infrared (NIR) reflectance data of nicotine in tobacco lamina and NIR transmission data of active ingredient in pesticide formulation. As a result, fewer but more informative variables were selected by CARS-SPA than by direct CARS. In the system of pesticide formulation, a multiple linear regression (MLR) model using variables selected by CARS-SPA provided a better prediction than the full-range partial least-squares (PLS) model, successive projections algorithm (SPA) model and uninformative variables elimination-successive projections algorithm (UVE-SPA) processed model. The variable subsets selected by CARS-SPA included the spectral ranges with sufficient chemical information, whereas the uninformative variables were hardly selected.

[Determination of calcium and magnesium in tobacco by near-infrared spectroscopy and least squares-support vector machine].

The purpose of the present paper is to determine calcium and magnesium in tobacco using NIR combined with least squares-support vector machine (LS-SVM). Five hundred ground and dried tobacco samples from Qujing city, Yunnan province, China, were surveyed by a MATRIX-I spectrometer (Bruker Optics, Bremen, Germany). At the beginning of data processing, outliers of samples were eliminated for stability of the model. The rest 487 samples were divided into several calibration sets and validation sets according to a hybrid modeling strategy. Monte-Carlo cross validation was used to choose the best spectral preprocess method from multiplicative scatter correction (MSC), standard normal variate transformation (SNV), S-G smoothing, 1st derivative, etc., and their combinations. To optimize parameters of LS-SVM model, the multilayer grid search and 10-fold cross validation were applied. The final LS-SVM models with the optimizing parameters were trained by the calibration set and accessed by 287 validation samples picked by Kennard-Stone method. For the quantitative model of calcium in tobacco, Savitzky-Golay FIR smoothing with frame size 21 showed the best performance. The regularization parameter λ of LS-SVM was e16.11, while the bandwidth of the RBF kernel σ2 was e8.42. The determination coefficient for prediction (Rc(2)) was 0.9755 and the determination coefficient for prediction (Rp(2)) was 0.9422, better than the performance of PLS model (Rc(2)=0.9593, Rp(2)=0.9344). For the quantitative analysis of magnesium, SNV made the regression model more precise than other preprocess. The optimized λ was e15.25 and σ2 was e6.32. Rc(2) and Rp(2) were 0.9961 and 0.9301, respectively, better than PLS model (Rc(2)=0.9716, Rp(2)=0.8924). After modeling, the whole progress of NIR scan and data analysis for one sample was within tens of seconds. The overall results show that NIR spectroscopy combined with LS-SVM can be efficiently utilized for rapid and accurate analysis of calcium and magnesium in tobacco.

Spatio-temporal variation of water salinity in mangroves revealed by continuous monitoring and its relationship to floristic diversity.

Salinity is among the most critical factors limiting the growth and species distribution of coastal plants. Water salinity in estuarine ecosystems varies temporally and spatially, but the variation patterns across different time scales and salinity fluctuation have rarely been quantified. The effects of salinity on floristic diversity in mangroves are not fully understood due to the temporal and spatial heterogeneity of salinity. In this study, we monitored water salinity at an interval of 10-min over one year in three mangrove catchment areas representing the outer part, middle part, and inner part respectively of Dongzhai Bay, Hainan, China. The number of mangrove community types and dominant mangrove species of the three catchment areas were also investigated. We found that the diurnal variation and dry-season intra-month variation in water salinity were driven by tidal cycles. The seasonal variation in water salinity was mainly driven by rainfall with higher salinity occurring in the dry season and lower salinity occurring in the wet season. Spatially, water salinity was highest at the outer part, intermediate at the middle part, and lowest at the inner part of the bay. The intra-month and annual fluctuations of water salinity were highest at the middle part and lowest at the outer part of the bay. The number of mangrove community types and dominant species were lowest at the outer part, intermediate at the middle part, and highest at the inner part of the bay. These results suggest that the temporal variation of water salinity in mangroves is driven by different factors at different time scales and therefore it is necessary to measure water salinity at different time scales to get a complete picture of the saline environment that mangroves experience. Spatially, lower salinity levels benefit mangrove species richness within a bay landscape, however, further research is needed to distinguish the effects of salinity fluctuation and salinity level in affecting mangrove species richness.

Increasing carbon and nutrient burial rates in mangroves coincided with coastal aquaculture development and water eutrophication in NE Hainan, China.

Mangroves sequester and store large area-specific quantities of blue carbon (C) and essential nutrients such as nitrogen (N) and phosphorous (P). Quantifying C and nutrient burial rates in mangroves across a centennial time span and relating these rates to mangrove habitat is fundamental for elucidating the role of mangroves in carbon and nutrient budgets and their responses to environmental changes. However, relevant data are very limited in China. In this study, we used the radionuclides (210Pb and 137Cs) to determine chronologies and C, N and P burial rates in two mangrove forests located at different geomorphologic settings in NE Hainan Island, China. We found that the temporal patterns of C, N and P burial rates since 1900 fitted a quadratic function with a notable increase after 1960s in both mangroves, which coincided with the rapid development of coastal aquaculture since 1960s in NE Hainan and the subsequent coastal water eutrophication in this area. Sediment accretion rate (SAR) and mass accumulation rate (MAR) stayed relatively steady in the open-coastal mangroves, while they increased exponentially in the estuarine mangroves since 1900. The estuarine mangroves had significantly higher SAR and C, N and P burial rates than the open-coastal mangroves. C, N and P burial rates averaged at 141.52 g m-2 a-1, 6.27 g m-2 a-1 and 1.14 g m-2 a-1, respectively in the estuarine core, and these rates averaged at 61.71 g m-2 a-1, 3.71 g m-2 a-1 and 0.43 g m-2 a-1, respectively in the open-coastal core. The results suggest that estuarine mangroves may be more capable of surviving accelerating sea level rise under climate change and play a greater role in C accumulation and nutrient filtering under anthropogenic nutrient enrichment than marine-dominated mangroves. Blue C burial may be enhanced by coastal water eutrophication, but such a relationship needs to be tested in further studies.

Leaf hydraulics coordinated with leaf economics and leaf size in mangrove species along a salinity gradient.

Independence among leaf economics, leaf hydraulics and leaf size confers plants great capability in adapting to heterogeneous environments. However, it remains unclear whether the independence of the leaf traits revealed across species still holds within species, especially under stressed conditions. Here, a suite of traits in these dimensions were measured in leaves and roots of a typical mangrove species, Ceriops tagal, which grows in habitats with a similar sunny and hot environment but different soil salinity in southern China. Compared with C. tagal under low soil salinity, C. tagal under high soil salinity had lower photosynthetic capacity, as indicated directly by a lower leaf nitrogen concentration and higher water use efficiency, and indirectly by a higher investment in defense function and thinner palisade tissue; had lower water transport capacity, as evidenced by thinner leaf minor veins and thinner root vessels; and also had much smaller single leaf area. Leaf economics, hydraulics and leaf size of the mangrove species appear to be coordinated as one trait dimension, which likely stemmed from co-variation of soil water and nutrient availability along the salinity gradient. The intraspecific leaf trait relationship under a stressful environment is insightful for our understanding of plant adaption to the multifarious environments.

[Simultaneous determination of instant coffee, plant fat and sugar content in liquid coffee beverage by diffuse reflectance near-infrared spectroscopy].

The diffuse reflectance near-infrared spectra of 20 liquid coffee beverage samples were collected by FT-NIR spectrometer combined with integral sphere in this thesis. The quantitative calibration models of instant coffee, plant fat and sugar were developed respectively. The result indicated that for the calibration models of instant coffee, plant fat and sugar, the dimensions of the calibration models are 4, 5 and 4 respectively; the determination coefficients (R2) are 98.97%, 99.94% and 99.18% respectively; the root mean square errors of calibration (RMSEC) are 1.62, 0.42 and 1.58 respectively; the root mean square errors of cross validation (RMSECV) are 2.12, 0.72 and 2.01 respectively. The result of F-test showed that a very remarkable correlation exists between the estimated and specified values for each calibration model. This research indicated that NIR spectroscopy can be applied in the rapid, accurate and simultaneous determination of the three main ingredients in liquid coffee beverage. This research can provide some references for the quality control of liquid coffee beverage and the determination of the substance with chemical-fixation composition in liquid formula food.

Fourier transform infrared spectroscopy and chemometrics for the discrimination of animal fur types.

Rapid and reliable animal fur identification has remained a challenge for customs inspection. The accurate distinction between fur types has a significant meaning in implementing the correct tariff policy. A variety of analytical methods have been applied to work on distinguishing animal fur types, with tools of microscopy, molecular testing, mass spectrometry, Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. In this research, the capability of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) combined with pattern recognition methods was investigated for the discrimination of animal fur in six types. This work was to explore the non-destructive application of ATR-FTIR technique in discriminant analysis of animal fur. All spectra were collected by ATR-FTIR of the wavenumber ranging from 4000 to 650 cm-1. Data pretreatments included moving average smoothing and multiplicative scatter correction (MSC). Four supervised classification algorithms were chosen to categorize the types of fur: soft independent modeling of class analogy (SIMCA), principal component analysis linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM). PLS-DA and LS-SVM were both effective approaches, with a 100% classification accuracy rate. The accuracy of PCA-LDA and SIMCA was 98.33% and 99.44%, respectively. Furthermore, LS-SVM model obtained using Monte-Carlo sampling method also obtained 100% prediction accuracy, while all other methods produced misclassification. LS-SVM corrected the non-linearities for the animal fur FTIR data but also remarkably improved the prediction performance level. The results of this study revealed that the combination of ATR-FTIR and chemometrics has a huge potential for animal fur discrimination.

Feature selection of infrared spectra analysis with convolutional neural network.

Data-driven deep learning analysis, especially for convolution neural network (CNN), has been developed and successfully applied in many domains. CNN is regarded as a black box, and the main drawback is the lack of interpretation. In this study, an interpretable CNN model was presented for infrared data analysis. An ascending stepwise linear regression (ASLR)-based approach was leveraged to extract the informative neurons in the flatten layer from the trained model. The characteristic of CNN network was employed to visualize the active variables according to the extracted neurons. Partial least squares (PLS) model was presented for comparison on the performance of extracted features and model interpretation. The CNN models yielded accuracies with extracted features of 93.27%, 97.50% and 96.65% for Tablet, meat, and juice datasets on the test set, while the PLS-DA models obtained accuracies with latent variables (LVs) of 95.19%, 95.50% and 98.17%. Both the CNN and PLS models demonstrated the stable patterns on active variables. The repeatability of CNN model and proposed strategies were verified by conducting the Monte-Carlo cross-validation.

Periodicity of monoisotopic mass isomers and isobars in proteomics.

We report trends in the theoretically derived number of compositionally distinct peptides (i.e., peptides made up of different amino acid residues) up to a nominal mass of 1000. A total of 21 amino acid residues commonly found in proteomics studies are included in this study, 19 natural, nonisomeric amino acid residues as well as oxidated methione and acetamidated cysteine. The number of possibilities is found to increase in an exponential fashion with increasing nominal mass, and the data show a periodic oscillation that starts at mass ~200 and continues throughout to 1000. Note that similar effects are reported in the companion article on fragment ions from electron capture/transfer dissociation (ECD/ETD) (Mao et al. Anal. Chem.2011, DOI: 10.1021/ac201619t). The spacing of this oscillation is ~15 mass units at lower masses and ~14 mass units at higher nominal masses. This correlates with the most common mass differences between the amino acid building blocks. In other words, some mass differences are more common than others, thus determining the periodicity in this data. From an analytical point of view, nominal masses with a larger number of compositionally distinct peptides include a substantial number of isomers, which cannot be separated based on mass. Consequently, even ultrahigh mass accuracy (i.e., 0.5 ppm) does not lead to a substantially enhanced rate of identification. Conversely, for adjacent nominal masses with a lower number of isomers, moderately accurate mass (i.e., 10 ppm) gives a higher degree of certainty in identification. These effects are limited to the mass range between 200 and 500 Da. At higher masses, the percentage of uniquely identified peptides drops off to close to zero, independent of nominal mass, due the inherently high number of isomers. While the exact number of isobars/isomers at each nominal mass depends on the amino acid building blocks that are considered, the periodicity in the data is found to be remarkably robust; for instance, inclusion of phosphorylated residues barely affects the pattern at lower masses (i.e., <500 Da).

Overexpression of the Arabidopsis α-expansin gene AtEXPA1 accelerates stomatal opening by decreasing the volumetric elastic modulus.

Guard cell walls of stomata are highly specialized in plants. Previous research focused on the structure and anatomy of guard cell walls, but little is known about guard cell regulation during stomata movement. In this work, we investigate the possible biological role of the Arabidopsis expansin gene AtEXPA1 in stomatal opening. The AtEXPA1 promoter drove the expression of the GUS reporter gene specifically in guard cells. Light-induced stomatal opening was accelerated in 35S::AtEXPA1 lines, whereas the anti-AtEXPA1 antibody decelerated light-induced stomatal opening. The inhibition of the anti-AtEXPA1 antibody on stomatal opening was largely dependent on the environmental pH. The volumetric elastic modulus (ε) was measured as an indicator of changes in the cell wall. The ε value of guard cells in 35S::AtEXPA1 lines was smaller than in the wild types. The putative role of AtEXPA1 as controller of stomatal opening rate and its regulation are discussed.

Non-destructive analysis the dating of paper based on convolutional neural network.

A non-destructive method based on Fourier Transformed Infrared Spectroscopy (FT-IR) was proposed to estimate the date of paper from different years in this article. For the paper samples, dated from 1940 to 1980, naturally aged and conserved in library. Partial least squares-discriminate analysis (PLS-DA), Logistic regression and convolutional neural network (CNN), were employed to evaluate the date of paper, with the accuracy 60.74%, 95.31% and 98.77%, respectively. Based on the characteristics of CNN model and with the help of network localization, active variables could be recognized in the whole spectrum. Although the localization of active variables showed a discriminative pattern, the selected spectral regions were similar. Most important variables focused on the 1700-1400 cm-1, were corresponding to cellulose crystallinity, which was consisted with the ageing processing. The present work gave the potential of FT-IR combined with chemometric techniques could estimate the dating of unknown paper. Meanwhile, the analysis of active variables obtained further indicated the worthy of CNN model for document dating.

[Study on rapid determination of active ingredient of agrochemicals by near-infrared spectroscopy].

The main problem of disqualification of the agrochemicals is the insufficiency and abuse of its active ingredient, but lacking of the rapid and on the site analysis method. In the present thesis, the content of haloxyfop-r-methyl in the emulsifiable concentration was analyzed quantitatively by the FT-NIR spectroscopy combined with partial least square (PLS) method. The calibration models of haloxyfop-r-methyl were developed, the determination coefficients (R2) of the calibration models were no less than 0.999 9, the SEC were less than 0.019, and the SEP were less than 0.030. Meanwhile, the factors affecting the calibration model were studied and the validation was done by the actual sample. The result indicated that the method of near-infrared spectroscopy can predict the content of the active ingredient in emulsifiable concentration accurately; while the resolution of the instrument and the content of addition agent will not affect the prediction precision of the calibration model remarkably. Therefore, it is a feasible, convenient and quick method to analyze the active ingredient in the commodity agrochemicals by near-infrared spectroscopy, which has an important significance in the on-line determination, analysis on site in the enterprise and the rapid quantitative analysis of agrichemicals in the department of quality monitoring.

[Quantitative analysis of the content of deltamethrin in agrochemicals by near-infrared, attenuated total reflectance infrared and raman spectroscopy].

The method of near-infrared, attenuated total reflectance infrared and Raman spectroscopy was used for the rapid determination of the content of deltamethrin in agrochemicals. The quantitative models were established by PLS (partial least squares) method and optimized. The independent validation sets were used to evaluate the model accuracy. The determination coefficient R2 and RMSECV of the near-infrared model and mid-infrared model were 0.9999, 0.022 and 0.9996 and 0.056, respectively. The accuracy of both was similar. The determination coefficient R2 and RMSECV of Raman were 0. 996 7 and 0.172, which exhibits the lower accuracy. The result indicated that near-infrared, mid-infrared and Raman spectroscopy can be applied to the rapid determination of the content of the active ingredients precisely, which has an important significance in the on-line determination, analysis on site in the enterprise and the rapid quantitative analysis of agrichemicals in the department of quality monitoring.

[Fast determination of the proportion of metalaxyl-M enantiomers by UV spectroscopy].

In the present study, beta-cyclodextrin(betaCD) was used as chiral selector to detect the proportion of chiral isomers of metalaxyl. The proportion of metalaxyl enantiomers can be detected by ultraviolet (UV)spectroscopy since the interaction between the R, S isomer of metalaxyl with beta-CD is different. The quantitative models were established by partial least squares regression (PLS) and the robust of models was evaluated by independent validation samples. The determination coefficient R2 of calibration set in the quantitative model was 0.999 0. The standard error of calibration set (SEC) and the relative standard deviation (RSD) of the model was respectively 0.006 7 and 0.89%; The correlation coefficient r of estimated value and specified value of the 6 independent validation samples was 0.998 5. The standard error of prediction (SEP) and RSD was respectively 0.008 9 and 1.17%. This method is rapid and easy to operate in practical applications.