Late-stage gem-difluoroallylation of phenol in bioactive molecules and peptides with 3,3-difluoroallyl sulfonium salts.

An efficient method for the late-stage selective O-fluoroalkylation of tyrosine residues with a stable yet highly reactive fluoroalkylating reagent, 3,3-difluoroallyl sulfonium salts (DFASs), has been developed. The reaction proceeds in a mild basic aqueous buffer (pH = 11.6) with high efficiency, high biocompatibility, and excellent regio- and chemoselectivity. Various oligopeptides and phenol-containing bioactive molecules, including carbohydrates and nucleosides, could be selectively O-fluoroalkylated. The added vinyl and other functional groups from DFASs can be valuable linkers for successive modification, significantly expanding the chemical space for further bioconjugation. The synthetic utility of this protocol has been demonstrated by the fluorescently labeled anti-cancer drug and the synthesis of O-link type 1,4,7,10-tetraazacyclododecane-N,N',N,N'-tetraacetic acid-tyrosine3-octreotate (DOTA-TATE), showing the prospect of the method in medicinal chemistry and chemical biology.

Stereoretentive Post-Translational Protein Editing.

Chemical post-translational methods allow convergent side-chain editing of proteins without needing to resort to genetic intervention. Current approaches that allow the creation of constitutionally native side chains via C-C bond formation, using off-protein carbon-centered C· radicals added to unnatural amino acid radical acceptor (SOMOphile, singly occupied molecular orbital (SOMO)) "tags" such as dehydroalanine, are benign and wide-ranging. However, they also typically create epimeric mixtures of d/l-residues. Here, we describe a light-mediated desulfurative method that, through the creation and reaction of stereoretained on-proteinl-alanyl Cß· radicals, allows Cß-Hγ, Cß-Oγ, Cß-Seγ, Cß-Bγ, and Cß-Cγ bond formation to flexibly generate site-selectively edited proteins with full retention of native stereochemistry under mild conditions from a natural amino acid precursor. This methodology shows great potential to explore protein side-chain diversity and function and in the construction of useful bioconjugates.

Controllable catalytic difluorocarbene transfer enables access to diversified fluoroalkylated arenes.

Difluorocarbene has important applications in pharmaceuticals, agrochemicals and materials, but all these applications proceed using just a few types of reaction by taking advantage of its intrinsic electrophilicity. Here, we report a palladium-catalysed strategy that confers the formed palladium difluorocarbene (Pd=CF2) species with both nucleophilicity and electrophilicity by switching the valence state of the palladium centre (Pd(0) and Pd(II), respectively). Controllable catalytic difluorocarbene transfer occurs between readily available arylboronic acids and the difluorocarbene precursor diethyl bromodifluoromethylphosphonate (BrCF2PO(OEt)2). From just this simple fluorine source, difluorocarbene transfer enables access to four types of product: difluoromethylated and tetrafluoroethylated arenes and their corresponding fluoroalkylated ketones. The transfer can also be applied to the modification of pharmaceuticals and agrochemicals as well as the one-pot diversified synthesis of fluorinated compounds. Mechanistic and computational studies consistently reveal that competition between nucleophilic and electrophilic palladium difluorocarbene ([Pd]=CF2) is the key factor controlling the catalytic difluorocarbene transfer.

Chlorodifluoromethane-triggered formation of difluoromethylated arenes catalysed by palladium.

Difluoromethylated aromatic compounds are of increasing importance in pharmaceuticals, agrochemicals and materials. Chlorodifluoromethane (ClCF2H), an inexpensive, abundant and widely used industrial raw material, represents the ideal and most straightforward difluoromethylating reagent, but introduction of the difluoromethyl group (CF2H) from ClCF2H into aromatics has not been reported. Here, we describe a direct palladium-catalysed difluoromethylation method for coupling ClCF2H with arylboronic acids and esters to generate difluoromethylated arenes with high efficiency. The reaction exhibits a remarkably broad substrate scope, including heteroarylboronic acids, and was used for difluoromethylation of a range of pharmaceuticals and biologically active compounds. Preliminary mechanistic studies revealed that a palladium difluorocarbene intermediate is involved in the reaction. Although numerous metal-difluorocarbene complexes have been prepared, the catalytic synthesis of difluoromethylated or difluoromethylenated compounds involving metal-difluorocarbene complexes has not received much attention. This new reaction therefore also opens the door to understand metal-difluorocarbene complex catalysed reactions.

Investigation of absorption and scattering characteristics of kiwifruit tissue using a single integrating sphere system.

For a quantitative understanding of light interaction with fruit tissue, it is critical to obtain two fundamental parameters: the absorption coefficient and the scattering coefficient of the tissue. This study was to investigate the optical properties of kiwifruit tissue at the wavelength of 632.8 nm. The total reflectance and total transmittance of kiwifruit tissue from three parts (including the flesh part, the seed part, and the seed-base part) were measured using a single integrating sphere system. Based on the measured spectral signals, the absorption coefficient µa and the reduced scattering coefficient µs' of kiwifruit tissue were calculated using the inverse adding-doubling (IAD) method. Phantoms made from Intralipid 20% and India ink as well as a Biomimic solid phantom were used for system validation. The mean values of µa and µs' of different parts of the kiwifruit were 0.031-0.308 mm(-1) and 0.120-0.946 mm(-1), respectively. The results showed significant differences among the µa and µs' of the three parts of the kiwifruit. The results of this study confirmed the importance of studying the optical properties for a quantitative understanding of light interaction with fruit tissue. Further investigation of fruit optical properties will be extended to a broader spectral region and different kinds of fruits.

[Rapid Discriminantion of Common Leather Varieties by Near Infrared Spectroscopy].

Rapid classification of leather variety means important to product process control, trading process and market surveillance. There is no official detection standard on classification of leather variety for the present. By now the testers use organoleptic method, burning method, chemical dissolution method, microscope method, or combination of them, to give a convincing result. The testers are required to highly sufficiently experienced, and not influenced by subjective factors. It also costs too much time. For the purpose of this research, spectra of five common varieties of leather samples (full-grain leather, split leather, sheep leather, reborn leather and manmade leather) were collected from market. Discriminant analysis combined with pre-processing method, including multiplicative signal correction (MSC), standard normal variate (SNV), first derivative and second derivative were used to classify the spectra above. It shows that the above five varieties of leather overlapped seriously in the same space. But manmade leather can be easily distinguished from the other four leather varieties using rear spectra, with the misclassified percent of 1.2%. The last four leather varieties covered each other partly in the same space, classify of any two of them can reach a lower misclassified percent, about 1.3%～17.9%. Different pre-processing method affected the discriminantion model positively or negatively with no regularity. None of these pre-processing methods was found to give a positive effect in a stable and persistent way. It can be concluded that it is feasible to discriminate the common leather varieties by near infrared Spectroscopy. All of the samples were taken from the finish products in the market (eg, handbag, belt, leather coat), which were processed in different ways (eg. tanning, knurling, dyeing). The different processes of the samples could bring an unforeseeable influence to the model which may be reduced by some method, for example, increasing the number and variety of samples.

[Application of NIR Spectroscopy for Nondestructive Qualitative and Quantitative Analysis of Lotus Seeds].

By extracting the Near Infrared (NIR) diffuse reflectance spectral characteristics from the post-harvest lotus seeds in different storage periods, the quantitative and qualitative analysis were applied to lotus seeds with the Soluble Solids Content (SSC) and dry matter content (DM) as criteria. The results of the Partial Least Squares Regression (PLSR) and distance discrimination (DA) models showed that the absorption spectra of lotus seeds and lotus kernels has clear relations to their SSC and DM. The PLSR models of SSC and DM of lotus seeds had the best performance in 5 941-12 480 cm(-1) spectral region in this study. Their correlation coefficients of prediction were 0.74 and 0.82, and the correlation coefficients of calibration were 0.82 and 0.84, and the correlation coefficients of leave one out cross validation were 0.72 and 0.71. The PLSR model of SSC of lotus kernels was better in 7 891-9 310 cm(-1) spectral region. Its correlation coefficient of prediction was 0.79, and the correlation coefficient of calibration was 0.84, and the correlation coefficient of leave one out cross validation was 0.77. The PLSR model of DM of lotus kernels is better in the full spectral region. Its correlation coefficient of prediction was 0.92, and the correlation coefficient of calibration was 0.89, and the correlation coefficient of leave one out cross validation was 0.82. For lotus seeds, the DA model in 5 400-7 885 cm(-1) spectral region is the best with a correctness of 84.2%. And for lotus kernels, the DA model in 9 226-12 480 cm(-1) spectral region is the best with a correctness of 90.8%. For dry lotus kernels, the discriminant accuracy of the DA model is 98.9% in the optimal spectral region. All kernels with membrane and plumule were correctly discriminated. This research shows that the NIR spectroscopy technique can be used to determine SSC and DM content of lotus seeds and lotus kernels, as well as to discriminate their freshness and also to discriminate dry lotus kernels of different age and the kernels with membrane and plumule.

[Investigation of light penetration depth and distribution inside citrus tissue].

Experiment was carried out to explore the light intensity change inside citrus samples in the present study. An experimental platform was set up, including a light box, a spectrometer, a sample stage, an optic fiber probe, light sources, etc. The sample stage is adjustable in three dimensions. The optic fiber probe was used to measure the light changes by observing the light attenuation and intensity variation within the citrus tissues. A 632 nm laser source and a 50 W tungsten halogen lamp light source were used. Light intensity and transmittance were investigated at different positions within the citrus fruit. The band with most significant intensity difference was selected to analyze the light intensity and transmittance trends in different positions inside the citrus fruit In order to examine the influence significance of the sample factor on test results, SPSS software was used to do the analysis of variation (ANOVA) of different samples. The results showed that light intensity and transmittance have a positive correlation with puncture depth, while citrus peel and stone have a more obvious attenuation effect than citrus flesh, and the influence of the sample factor on the test results is not significant. Further research can be carried out by improving the experimental device. The method used and results obtained in this study are valuable for studies on light transmission properties inside fruit tissue, not only for citrus but also for other kinds of fruits.

Determination of soluble solid content and acidity of loquats based on FT-NIR spectroscopy.

The near infrared (NIR) spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content (SSC) and acidity (pH) of intact loquats. Two cultivars of loquats (Dahongpao and Jiajiaozhong) harvested from two orchards (Tangxi and Chun'an, Zhejiang, China) were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats (100 samples of each cultivar from each orchard) were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square (PLS) method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction (MSC), and the standard normal variate (SNV). Three separate spectral windows identified as full NIR (800approximately2500 nm), short NIR (800approximately1100 nm), and long NIR (1100approximately2500 nm) were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction (RMSEP) values of 1.21, 1.00, 0.965, and 1.16 degrees Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun'an-Dahongpao, and Chun'an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.

On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopy.

The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207). In this study, 82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode. Discriminant models were developed using principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least squares (DPLS) regression methods. After outliers detection, the samples were randomly split into two sets, one used as a calibration set (n=82) and the remaining samples as a validation set (n=82). When predicting the variety of the samples in validation set, the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%. The DPLS model with raw spectra after multiplicative scatter correction and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (R(c))=0.920, root mean square errors of calibration=0.196, and root mean square errors of prediction=0.216). The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.

[Application of Vis/NIR diffuse reflectance spectroscopy to the detection and identification of transgenic tomato leaf].

The feasibility of Vis/NIR spectroscopy technique for rapid and non-invasive detection of transgenic tomato leaves from conventional ones was investigated by means of spectral diffuse reflectance mode. A total of 68 samples (38 transgenic ones and 30 non-transgenic ones) were used for classification. The calibration and validation results were analyzed via discriminant analysis (DA) and partial least squares (PLS) discriminant method using TQ 6.2. 1 quantitative software. Models based on the different spectral pre-processing methods (multiplicative signal correction (MSC), first and second derivative) were compared. It was found that the classification accuracy using DA was higher than that using PLS and the best results were gained by using spectra after MSC with InGaAs detector and the classification accuracy was 89.7% (accuracy of 86.8% for transgenic samples and 93.3% for non-transgenic ones). The results show that Vis-NIR diffuse reflectance spectroscopy technique is a feasible and fast method for non-invasive detection of transgenic and non-transgenic tomato leaves.

[Application of infrared spectroscopy technique to discrimination of alcoholic beverages].

Infrared spectroscopy technique is a rapid for the discrimination of food samples, and is widely used to detect and discriminate various beverages. This paper presents the advantages and disadvantages of techniques that have been used to discriminate alcoholic beverages, and the discriminating procedure with infrared spectroscopy technique. Applications of infrared spectroscopy technique to wine, whiskey, Japanese sake and Chinese rice wine etc. is presented too. Finally, problems in applications are analyzed, and the application of infrared spectroscopy technique to the discrimination of our traditional alcoholic beverages is prospected.

Application of NIR spectroscopy for firmness evaluation of peaches.

The use of near infrared (NIR) spectroscopy was proved to be a useful tool for quality analysis of fruits. A bifurcated fiber type NIR spectrometer, with a detection range of 800~2500 nm by InGaAs detector, was used to evaluate the firmness of peaches. Anisotropy of NIR spectra and firmness of peaches in relation to detecting positions of different parts (including three latitudes and three longitudes) were investigated. Both spectra absorbency and firmness of peach were influenced by longitudes (i, ii, iii) and latitudes (A, B, C). For modeling, two thirds of the samples were used as the calibration set and the remaining one third were used as the validation or prediction set. Partial least square regression (PLSR) models for different longitude and latitude spectra and for the whole fruit show that collecting several NIR spectra from different longitudes and latitudes of a fruit for NIR calibration modeling can improve the modeling performance. In addition, proper spectra pretreatments like scattering correction or derivative also can enhance the modeling performance. The best results obtained in this study were from the holistic model with multiplicative scattering correction (MSC) pretreatment, with correlation coefficient of cross-validation r(cv)=0.864, root mean square error of cross-validation RMSECV=6.71 N, correlation coefficient of calibration r=0.948, root mean square error of calibration RMSEC=4.21 N and root mean square error of prediction RMSEP=5.42 N. The results of this study are useful for further research and application that when applying NIR spectroscopy for objectives with anisotropic differences, spectra and quality indices are necessarily measured from several parts of each object to improve the modeling performance.

[Estimation of soluble solids content of intact citrus fruit by Vis/NIR spectroscopy].

Visible/Near-infrared (Vis/NIR) spectroscopy has become a very popular technique for the non-invasive assessment of intact fruit. The feasibility of using Vis/NIR spectroscopic technology for rapid quantifying soluble solids content (SSC) of citrus fruit was investigated by means of spectral transmittance mode. A total of 110 citrus fruit samples were used to develop the calibration and prediction models. The relationship between actual SSC and Vis/NIRS spectra of citrus fruit samples was analyzed via pricipal component regression (PCR) and partial least squares (PLS) regression method using TQ 6.2 spectral analysis software. Models based on the different spectral pre-processing methods were compared in the present research. Performance of different models was assessed in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r2) of prediction set of samples. The best predictive models feature a RMSEP of 0.538% and correlation coefficient (r2) of 0.801 for SSC. The results show that the Vis/NIR transmittance technique is a feasible, accurate and fast method for non-invasive estimation of citrus fruit SSC.

[Study on predicting firmness of watermelon by Vis/NIR diffuse transmittance technique].

Watermelon is a popular fruit in the world and firmness (FM) is one of the major characteristics used for assessing watermelon quality. The objective of the present research was to study the potential of visible/near Infrared (Vis/NIR) diffuse transmittance spectroscopy as a way for the nondestructive measurement of FM of watermelon. Statistical models between the spectra and FM were developed using partial least square (PLS) and principle component regression (PCR) methods. Performance of different models was assessed in terms of correlation coefficients (r) of validation set of samples and root mean square errors of prediction (RMSEP). Models for three kinds of mathematical treatments of spectra (original, first derivative and second derivative) were established. Savitsky-Goaly filter smoothing method was used for spectra data smoothing. The PLS model of the second derivative spectra gave the best prediction of FM, with a correlation coefficient (r) of 0. 974 and root mean square errors of prediction (RMSEP) of 0. 589 N using Savitsky-Goaly filter smoothing method. The results of this study indicate that NIR diffuse transmittance spectroscopy can be used to predict the FM of watermelon. The Vis/NIR diffuse transmittance technique will be valuable for the nandestructive detection large shape and thick peel fruits'.

[Influence of optical path length on NIR analysis results for trace metal determination in Chinese rice wine].

The prediction performance of near infrared (NIR) spectra with different optical path-length for trace metal (potassium, calcium, magnesium, zincum, and iron) determination was investigated. NIR transmission spectra of Chinese rice wine were collected in rectangular quartz cuvette with different optical path lengths (1, 2, 5 and 10 mm) using Fourier transform near infrared (FT-NIR) spectrometer in the wavelength range of 800-2 500 nm with air as the reference. The reference data for potassium, calcium, magnesium, zinc, and iron were determined by atomic absorption spectroscopy (AAS). Calibration models were developed by partial least squares (PLS) regression. The PLS models of NIR spectra group with 5 mm path length gave the best calibration result. The determination coefficients (r2) for potassium, calcium, magnesium, zincum, and iron were 0.93, 0.85, 0.93, 0.72, and 0.66, respectively, and the root mean square error of cross validation (RMSECV) for the five elements were 26.5, 35.6, 4.63, 0.26, and 0.64 mg x L-(-1), respectively, whereas the models established by NIR spectra group of 10 mm path-length was the worst. And the r2 values for potassium, calcium, magnesium, zincum, and iron were 0.61, 0.65, 0.63, 0.09, and 0.25, respectively. The results indicated that the optical path length has an influence on the NIR analysis results for trace metal determination in Chinese rice wine, and that the appropriate path length for the NIR analysis should be determined by comparison analysis.

[Application of near infrared spectroscopy technique to nondestructive measurement of vegetable quality].

Nondestructive detection techniques of vegetable include electrical properties, optical reflectance and transmission, sonic vibration, nuclear magnetic resonance (NMR), machine vision, aromatic volatile emission, vibration characteristics and others. The most widely employed and successful technique is to use its optical property. Near infrared spectroscopy technique is extremely fast, highly efficient, cheap to implement, of good recurrence and no sample preparation, and is a rapid and non-destructive modern measuring technique that has been widely used in many fields. In the present paper, the application of near infrared spectroscopy technique to nondestructive measurement of vegetable quality was briefly introduced. Some considerable aspects existing in the application were also discussed, and it is pointed out that because of vegetable's diversity and rot-proneness, automation analysis machine should be developed to improve the speed of quality detection, and cooperating with several other nondestructive techniques, such as NMR and machine vision, is the research trend.

[Nondestructive sugar content determination of peaches by using near infrared spectroscopy technique].

Near infrared (NIR) spectroscopy has been widely studied and used for rapid and nondestructive measurement of internal qualities of fruits such as sugar content, acidity, firmness, etc. The objective of the present research was to study the potential of NIR diffuse reflectance spectroscopy as a nondestructive method for the determination of sugar content of Jinhua peaches. NIR spectral data were acquired in the spectral region between 800 nm and 2500 nm using a FT-NIR spectrometer with a bifurcated optic fiber and an InGaAs detector. Statistical models were developed using partial least square regression (PLSR) method by TQ Analyst software. The results of PLSR models for peach flesh of different parts and juice indicated that the model based on average spectra of nine measurements in three different parts of each fruit and the corresponding sugar content obtained better results than those models based on the flesh of one part of each fruit (three measurements) or juice. Spectral data preprocessing of derivative and scattering correction was also discussed. The results showed that the models based on original spectra were better than those based on derivative spectra; and spectra scattering correction could improve the performance of PLSR models. Finally, two models were established based on spectra after multiplicative scattering correction (MSC) and standard normal variate (SNV) preprocessing. The correlation coefficients of calibration and leave-one-out cross-validation of the two models were the same, Rcal = 0.997 and Rcross-v = 0.939. These results show that it is feasible to use NIR spectroscopy technique for quantitative analysis of peach sugar content.

[Application of some different modeling algorithms to pear MT-firmness detection using NIR spectra].

Near infrared (NIR) spectroscopy is an instrumental method, which was widely studied and used for rapid and nondestructive detection of internal qualities of agricultural products. Statistical modeling is a very important and difficult process in NIR detection to establish the relationship between nondestructive NIR spectral data and interested quality index of the products. Classical multivariate calibration methods such as partial least square regression (PLSR), principle component regression (PCR), stepwise multilinear regression (SMLR) were often used for modeling. In the present study, besides these algorithms, another mixed algorithm was adopted for establishing a nonlinear model of NIR spectra and Magness Taylor(MT) firmness of "Xueqing" pears. The mixed algorithm was combined with SMLR and artificial neural network (ANN). NIR diffuse reflectance spectra of intact pears were measured in the spectral range of 800-2630 nm using InGaAs detector. However, only spectral information between 800 and 2500 nm was used for modeling because of the low signal to noise ratio beyond 2500 nm. Comparing the classical multivariate calibration methods of PLSR, PCR and SMLR, the modeling results using PLSR method were much better than the other two methods. Moreover, models based on original spectra turned out better results than models based on derivative spectra for all the three methods. The best results were r = 0.87, RMSEC = 3.88 N of calibration and r = 0.84, and RMSEP = 4.26 N of validation by using PLSR method based on original spectra. The mixed algorithm also performed better than SMLR and PCR, but was a bit worse than PLSR: r = 0.85, RMSEC = 4.15 N of calibration and r = 0.82, and RMSEP = 4.67 N of validation. The results indicated that fruit NIR spectra could be used for MT-firmness prediction when a proper algorithm was chosen, however, further study on statistic modeling is still necessary to improve the predicting performance.

[Qualitative analysis of Chinese rice wine with different marked age by near infrared transmission spectroscopy].

The feasibility of using near infrared transmission spectroscopy for classification of Chinese rice wine with different marked age was presented in the present research. The prediction performance of different preprocessing methods of the spectra (raw spectra, smoothed spectra and derivative spectra) together with discriminant analysis (DA) was also investigated. A total of 86 Shaoxing rice wines were tested in the wavelength of range 800-2 500 nm using Fourier transform near infrared spectroscopy. The results of the research indicated that the performance of second derivative spectra was the worst, and the results from raw spectra were the best, with the percentage of samples correctly classified 98.1% and 90.6% for the calibration and validation set, respectively, and the smoothed spectra had no influence on the classification results. The results indicated that near infrared transmission spectroscopy in conjunction with DA was a powerful tool for discriminating Chinese rice wines with different marked ages.