Stereocontrolled Construction of Spirooxindole-Containing 5,6,7,8-Tetrahydropyrrolo[1,2-a]pyridine via Michael/Friedel-Crafts Domino Reaction Promoted by Secondary Amine-Squaramide.

An asymmetric Michael/Friedel-Crafts cascade reaction with Morita-Baylis-Hillman (MBH) nitroallylic esters and 3-pyrrolyloxindoles has been developed for the stereoselective construction of spirooxindole-containing tetrahydroindolizines. A range of tetracyclic scaffolds possessing three consecutive chiral centers, including an all-carbon quaternary stereocenter, were generated in 53-85% isolated yields with high diastereoselectivities and enantiopurities (≥3:1 dr, 50-98% ee). A newly synthesized bifunctional secondary amine/squaramide organocatalyst was demonstrated to exhibit better stereochemical control than their tertiary analogues.

Prevention and Treatment of Grade C Postoperative Pancreatic Fistula.

Postoperative pancreatic fistula (POPF) is a troublesome complication after pancreatic surgeries, and grade C POPF is the most serious situation among pancreatic fistulas. At present, the incidence of grade C POPF varies from less than 1% to greater than 9%, with an extremely high postoperative mortality rate of 25.7%. The patients with grade C POPF finally undergo surgery with a poor prognosis after various failed conservative treatments. Although various surgical and perioperative attempts have been made to reduce the incidence of grade C POPF, the rates of this costly complication have not been significantly diminished. Hearteningly, several related studies have found that intra-abdominal infection from intestinal flora could promote the development of grade C POPF, which would help physicians to better prevent this complication. In this review, we briefly introduced the definition and relevant risk factors for grade C POPF. Moreover, this review discusses the two main pathways, direct intestinal juice spillover and bacterial translocation, by which intestinal microbes enter the abdominal cavity. Based on the abovementioned theory, we summarize the operation techniques and perioperative management of grade C POPF and discuss novel methods and surgical treatments to reverse this dilemma.

Assessing different regression algorithms for paddy rice leaf nitrogen concentration estimations from the first-derivative fluorescence spectrum.

The non-destructive and rapid estimation of the crop's leaf nitrogen concentration (LNC) is significant for the quality evaluation and precise management of nitrogen (N) fertilizer. First derivative can be applied to reduce the noise in the spectral analysis, which is suited to estimate leaf N and chlorophyll concentration with different fertilization levels. In this study, the first-derivative fluorescence spectrum (FDFS) was calculated in terms of the laser-induced fluorescence (LIF) spectra and was combined with different regression algorithms, including principal component analysis (PCA), partial least-square regression (PLSR), random forest (RF), radial basic function neural network (RBF-NN), and back-propagation neural network (BPNN) for paddy rice LNC estimation. Then, the effect of diverse inner parameters on regression algorithm for LNC estimation based on the calculated FDFS served as input variables were discussed, and the optimal parameters of each model were acquired. Subsequently, the performance of different models (PLSR, RF, BPNN, RBF-NN, PCA-RF, PCA-BPNN, and PCA-RBFNN) with the optimal parameter for LNC estimation based on FDFS was discussed. Results demonstrated that PCA can efficiently extract major spectral information without obviously losing, which can improve the stability and robustness of model (PLSR, PCA-RF, PCA-BNN, and PCA-RBFNN) for LNC estimation. Then, PCA-RBFNN model exhibited better potential for LNC estimation with higher average R2 (R2=0.8743) and lower SD values (SD=0.0256) than that the other regression models in this study. And, PLSR also exhibited promising potential for LNC estimation in which the R2 values (average R2=0.8412) are higher than that the other models except for PCA-RBFNN.

Improvement of CO2-DIAL Signal-to-Noise Ratio Using Lifting Wavelet Transform.

Atmospheric CO2 plays an important role in controlling climate change and its effect on the carbon cycle. However, detailed information on the dynamics of CO2 vertical mixing remains lacking, which hinders the accurate understanding of certain key features of the carbon cycle. Differential absorption lidar (DIAL) is a promising technology for CO2 detection due to its characteristics of high precision, high time resolution, and high spatial resolution. Ground-based CO2-DIAL can provide the continuous observations of the vertical profile of CO2 concentration, which can be highly significant to gaining deeper insights into the rectification effect of CO2, the ratio of respiration photosynthesis, and the CO2 dome in urban areas. A set of ground-based CO2-DIAL systems were developed by our team and highly accurate long-term laboratory experiments were conducted. Nonetheless, the performance suffered from low signal-to-noise ratio (SNR) in field explorations because of decreasing aerosol concentrations with increasing altitude and surrounding interference according to the results of our experiments in Wuhan and Huainan. The concentration of atmospheric CO2 is derived from the difference of signals between on-line and off-line wavelengths; thus, low SNR will cause the superimposition of the final inversion error. In such a situation, an efficient and accurate denoising algorithm is critical for a ground-based CO2-DIAL system, particularly in field experiments. In this study, a method based on lifting wavelet transform (LWT) for CO2-DIAL signal denoising was proposed. This method, which is an improvement of the traditional wavelet transform, can select different predictive and update functions according to the characteristics of lidar signals, thereby making it suitable for the signal denoising of CO2-DIAL. Experiment analyses were conducted to evaluate the denoising effect of LWT. For comparison, ensemble empirical mode decomposition denoising was also performed on the same lidar signal. In addition, this study calculated the coefficient of variation (CV) at the same altitude among multiple original signals within 10 min and then performed the same calculation on the denoised signal. Finally, high-quality signal of ground-based CO2-DIAL was obtained using the LWT denoising method. The differential absorption optical depths of the denoised signals obtained via LWT were calculated, and the profile distribution information of CO2 concentration was acquired during field detection by using our developed CO2-DIAL systems.

Method for wavelength stabilization of pulsed difference frequency laser at 1572 nm for CO(2) detection lidar.

High-accuracy on-line wavelength stabilization is required for differential absorption lidar (DIAL), which is ideal for precisely measuring atmospheric CO(2) concentration. Using a difference-frequency laser, we developed a ground-based 1.57-µm pulsed DIAL for performing atmospheric CO(2) measurements. Owing to the system complexity, lacking phase, and intensity instability, the stabilization method was divided into two parts-wavelength calibration and locking-based on saturated absorption. After obtaining the on-line laser position, accuracy verification using statistical theory and locking stabilization using a one-dimensional template matching method, namely least-squares matching (LSM), were adopted to achieve wavelength locking. The resulting system is capable of generating a stable wavelength.