Comprehensive quality evaluation of Lysimachia christinae Hance via fingerprint, spectrum-effect relationship, and quantitative analyses of multiple components by single marker.

BACKGROUND: Lysimachia christinae Hance (LCH) is a traditional medicine used to treat gallstone disease and cholecystitis. Despite its known anti-inflammatory and choleretic effects, its quality has not been extensively evaluated. OBJECTIVE: In this study, we aimed to establish a reliable quality evaluation method for LCH via fingerprint, spectrum-effect relationship, and quantitative analyses of multicomponents by a single marker (QAMS). METHODS: First, the fingerprints and anti-inflammatory and choleretic activities of 14 LCH batches were determined. Then, the gray relation analysis method was used to analyze the peak areas of the fingerprint profile and pharmacodynamic data. Subsequently, the characteristic peaks were tentatively identified using high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Finally, rutin was selected as the internal reference material, and QAMS was used to analyze the LCH components. RESULTS: Pharmacodynamic experiments confirmed that LCH exerted anti-inflammatory and choleretic effects. Moreover, 15 flavonoids related to the anti-inflammatory and choleretic effects of LCH were identified. Notably, relative error percentage between the QAMS and external standard method was less than 5%. CONCLUSION: This study successfully established a comprehensive evaluation method for the qualitative and quantitative analyses of LCH.

Comprehensive analysis of KCTD family genes associated with hypoxic microenvironment and immune infiltration in lung adenocarcinoma.

To obtain novel insights into the tumor biology and therapeutic targets of LUAD, we performed a comprehensive analysis of the KCTD family genes. The expression patterns and clinical significance of the KCTD family were identified through multiple bioinformatics mining. Moreover, the molecular functions and potential mechanisms of differentially expressed KCTDs were evaluated using TIMER 2.0, cBioPortal, GeneMANIA, LinkedOmics and GSEA. The results indicated that the mRNA and protein expression levels of KCTD9, KCTD10, KCTD12, KCTD15 and KCTD16 were significantly decreased in LUAD, while those of KCTD5 were significantly increased. High KCTD5 expression was significantly associated with advanced tumor stage, lymph node metastasis, TP53 mutation and poor prognosis. In addition, KCTD5 was positively correlated with CD8 + T cell, neutrophil, macrophage and dendritic cell infiltration. Additionally, KCTDs demonstrate promising prospects in the diagnosis of LUAD. Importantly, high KCTD5 expression was enriched in signaling pathways associated with the malignant progression of tumors, including the inflammatory response, the IL6/JAK/STAT3 signaling pathway, EMT and hypoxia. Further association analysis showed that KCTD5 was positively correlated with hypoxia-related genes such as HIF1. Overall, KCTDs can be used as molecular targets for the treatment of LUAD, as well as effective molecular biomarkers for diagnosis and prognosis prediction.

Change in intestinal flora after treatment in children with focal epilepsy. / å±€ç¶æ€§ç™«ç—«æ‚£å„¿æ²»ç–—å‰åŽè‚ é“èŒç¾¤çš„å˜åŒ–åŠæ„ä¹‰.

OBJECTIVES: To study the difference in intestinal flora between children with focal epilepsy and healthy children and the change in intestinal flora after treatment in children with epilepsy. METHODS: A total of 10 children with newly diagnosed focal epilepsy were recruited as the case group and were all treated with oxcarbazepine alone. Their clinical data were recorded. Fecal specimens before treatment and after 3 months of treatment were collected. Fourteen aged-matched healthy children were recruited as the control group. Total bacterial DNA was extracted from the fecal specimens for 16S rDNA sequencing and bioinformatics analysis. RESULTS: After 3 months of carbamazepine treatment, the seizure frequency was reduced by >50% in the case group. At the phylum level, the abundance of Actinobacteria in the case group before treatment was significantly higher than that in the control group (P<0.05), and it was reduced after treatment (P<0.05). At the genus level, the abundances of Escherichia/Shigella, Streptococcus, Collinsella, and Megamonas in the case group before treatment were significantly higher than those in the control group (P<0.05), and the abundances of these bacteria decreased significantly after treatment (P<0.05). CONCLUSIONS: There is a significant difference in intestinal flora between children with focal epilepsy and healthy children. Oxcarbazepine can significantly improve the symptoms and intestinal flora in children with epilepsy.

Fragment-based lead discovery of indazole-based compounds as AXL kinase inhibitors.

AXL is a member of the TAM (TYRO3, AXL, MER) subfamily of receptor tyrosine kinases. It is upregulated in a variety of cancers and its overexpression is associated with poor disease prognosis and acquired drug resistance. Utilizing a fragment-based lead discovery approach, a new indazole-based AXL inhibitor was obtained. The indazole fragment hit 11, identified through a high concentration biochemical screen, was expeditiously improved to fragment 24 by screening our in-house expanded library of fragments (ELF) collection. Subsequent fragment optimization guided by docking studies provided potent inhibitor 54 with moderate exposure levels in mice. X-ray crystal structure of analog 50 complexed with the I650M mutated kinase domain of Mer revealed the key binding interactions for the scaffold. The good potency coupled with reasonable kinase selectivity, moderate in vivo exposure levels, and availability of structural information for the series makes it a suitable starting point for further optimization efforts.

A head-to-head comparison of the inhibitory activities of 15 peptidomimetic SARS-CoV-2 3CLpro inhibitors.

The COVID-19 pandemic caused by SARS-CoV-2 has created an unprecedented global health emergency. As of July 2021, only three antiviral therapies have been approved by the FDA for treating infected patients, highlighting the urgent need for more antiviral drugs. The SARS-CoV-2 3CL protease (3CLpro) is deemed an attractive drug target due to its essential role in viral polyprotein processing and pathogenesis. Indeed, a number of peptidomimetic 3CLpro inhibitors armed with electrophilic warheads have been reported by various research groups that can potentially be developed for treating COVID-19. However, it is currently impossible to compare their relative potencies due to the different assays employed. To solve this, we conducted a head-to-head comparison of fifteen reported peptidomimetic inhibitors in a standard FRET-based SARS-CoV-2 3CLpro inhibition assay to compare and identify potent inhibitors for development. Inhibitor design and the suitability of various warheads are also discussed.

Analysis of aflatoxins in traditional Chinese medicines: Classification of analytical method on the basis of matrix variations.

A classification system for analytical methods was developed for the first time to determine the presence of aflatoxins B1, B2, G1 and G2 in traditional Chinese medicines (TCMs) based on different matrix types using ultra-performance liquid chromatography-tandem mass spectrometry. A useful characteristic of the approach was that the TCMs could be systematically divided into four categories (i.e., volatile oils, proteins, polysaccharides and fatty oils) depending on the matrix types. The approach concluded that different types of TCMs required different optimal sample preparation procedures. Based on the optimized analytical conditions, the limits of detection and quantification, average recoveries and linearity of four aflatoxins were determined and conformed to research limits. Of 22 TCMs samples, 14 samples were contaminated with at least one type aflatoxin at concentrations ranging from 0.2 to 7.5 µg/kg, and the average contents of aflatoxins were significantly different for the different matrix types. Moreover, we found a potential link between the contamination levels of aflatoxins and matrix types. TCMs containing fatty oils were the most susceptible to contamination by aflatoxins and followed by TCMs containing polysaccharides and proteins; TCMs containing abundant amounts of volatile oils were less prone to contamination.

Comparative Evaluation of the Chemical Composition, Antioxidant and Antimicrobial Activities of the Volatile Oils of Hawk Tea from Six Botanical Origins.

In this study, volatile oils of six Hawk tea varieties were studied for their chemical composition, antioxidant and antimicrobial activities to screen the most suitable botanical origins of Hawk tea. A total of 72 components were separated and identified from the six oils. The major constituents of the volatile oils were: α-pinene, camphene, limonene, 1,8-cineole, linalool, cis-nerolidol, and germacrene B. Moreover, the volatile oils were evaluated for antioxidant potential and antimicrobial activities. The results showed that all volatile oils exhibited acceptable antioxidant and antimicrobial activities, which suggested that these volatile oils may serve as natural alternatives to synthetic antioxidants and preservatives to be applied in food and pharmaceutical industries. Principal component analysis results denoted that some major compounds may be closely related to the antioxidant and antimicrobial activities. It also showed that the volatile oils from Litsea coreana var. lanuginosa and Litsea pungens Hemsl. were characterized by positive values of first two principal components, indicating higher active chemical compounds and antioxidant and antimicrobial activities compared with other species. Thus, they were temporarily considered as good sources of Hawk tea.

Identification of Brake Fluid Brands, New and Used Brake Fluid with Discriminant Analysis Based on Near-Infrared Transmittance Spectroscopy.

Near-infrared transmittance spectroscopy was used to identify brake fluid brands, new and used brake fluid of each brand. The transmittance spectra of the new and used samples of 4 different brands of brake fluid, including BMW, Toyota, Volvo and Castrol were collected. PCA was conducted to the spectral data of the new samples of the four brake fluid and the spectral data of the new and used samples of each brand. The PCA scores scatter plot indicated that there were differences among the four brands of brake fluid, and there were also differences between new and used samples of each brand. Optimal wavelengths were selected for identifying different brands and new and used samples of each brand by loadings of PCA. Classification models were built using the optimal wavelength, including Partial least squares-discriminant analysis (PLS-DA), Linear discriminant analysis (LDA), Soft independent modeling of class analogy (SIMCA), k-nearest neighbor algorithm (KNN), Random forest (RF), Back propagation neural network (BPNN), Radial basis function neural network (RBFNN), Extreme learning machine (ELM), Support vector machine (SVM), Least-squares support vector machine (LS-SVM). All classification models obtained good performances, the classification accuracy of the calibration set and the prediction set are 100% for most models. Compared with other three brands, new and used samples of Castrol showed slighter difference, and KNN and LS-SVM models performed worse with classification accuracy under 100% in the calibration set. The overall results indicated that near-infrared transmittance combined with optimal wavenumber selection and classification methods could be used to identify brake fluid brands, new and used brake fluids, the results of this study could provide theoretical support for developing online and portable devices.

Antioxidant activity and optimization of extraction of polysaccharide from the roots of Dipsacus asperoides.

Polysaccharide extraction from Dipsacus asperoides roots (DAP) was proved to possess strong antioxidant activities, including 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2-Azobis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) radical scavenging activities, inhibiting ß-carotene bleaching and strong reducing power. Cell assay demonstrated that the crude DAP possessed antioxidant activity and were effective against H2O2-induced L02 cells injury. Then, response surface methodology (RSM) was applied to optimize the ultrasonic extraction of DAP. The optimum variables given by central composite design (CCD) were as follows: ratio of water to raw material, 38.61mL/g; ultrasonic power, 308.68W; extraction time, 38.61min; and extraction temperature, 89°C. Under these conditions, the maximum yield of DAP obtained was 7.12±0.45%. Moreover, high performance liquid chromatography (HPLC) analysis suggested that the monosaccharide compositions of DAP contained primarily mannose, ribose, glucose, galactose, xylose and arabinose, with a molar ratio of 0.22:0.48:2.29:0.34:1.39:1.41. The results of the present study showed that DAP could be considered as potential sources of natural antioxidants.

[Study on Brand Discrimination of Differential Oil Using Near-Infrared Spectroscopy with Different Resolutions].

The performance and influence of near-infrared spectroscopy with different resolutions for brand discrimination of differential oil was studied. Spectral data with resolutions of 4, 8, 16 and 32 cm(-1) were collected, and 10522.28-4443.425 cm(-1) spectra were analyzed after the removal of the absolute noises. The principal component analysis (PCA) of the spectral data at different resolutions indicated that the brands of differential oil could be discriminated. Patial least squares-discriminant analysis (PLS-DA) and support vector machine (SVM) models were built based on the full spectra with different resolutions. The discrimination results showed that all models obtained similar and good performances with the classification rate over 90%, and the best results were obtained when the model was built based on the full spectra with the resolution of 8 cm(-1). Successive projections algorithm was applied to select effective wavenumbers, and different effective wavenumbers were selected for the spectra with different resolutions. PLS-DA and SVM models based on the selected effective wavenumbers both obtained good results. Their results were similar to the models established based on full spectra. The results indicated that spectral resolution had little effect on the discrimination results, and spectral resolution effected the selection of effective wavenumbers, and spectral resolution should be taken into consideration for the selection of effective wavenumbers in practical applications. In all, near-infrared spectroscopy with different resolutions and the corresponding selected effective wavenumbers could be used for discrimination of differential oil brands.

[Non-destructive brand identification of car wax using visible and near-infrared spectroscopy].

Visible and near-infrared (Vis-NIR) spectroscopy was applied to identify brands of car wax. A total of 104 samples were obtained for the analysis, in which 40 samples (calibration set) were used for model calibration, and the remaining 64 samples (prediction set) were used to validate the calibrated model independently. Linear discriminant analysis (LDA) and least square-support vector machine (LS-SVM) were respectively used to establish identification models for car wax with five brands based on their Vis-NIR spectra. Correct rates for prediction sample set were 84% and 97% for LDA and LS-SVM models, respectively. Spectral variable selection was further conducted by successive projections algorithm, (SPA), resulting in seven feature variables (351, 365, 401, 441, 605, 926, and 980 nm) selected from full range spectra that had 751 variables. The new LS-SVM model established using the feature variables selected by SPA also had the correct rate of 97%, showing that the selected variables had the most important information for brand identification, while other variables with no useful information were eliminated efficiently. The use of SPA and LS-SVM could not only obtain a high correct identification rate, but also simplify the model calibration and calculation. SPA-LS-SVM model could extract the useful information from the Vis-NIR spectra of car wax rapidly and accurately for the non-destructive brand identification of car wax.

[Determination of dynamic viscosity of automobile lubricant using visible and near infrared spectroscopy].

Visible and near infrared (Vis/NIR) spectroscopy was applied for the fast determination of dynamic viscosity of automobile lubricant. One hundred fifty samples from 5 brands were collected for Vis/NIR spectral scanning. Partial least squares (PLS) analysis was applied as calibration method after preprocessing stage as well as a way to extract the first 6 principal components which were used as the input data matrix of least squares-support vector machine (LS-SVM) to develop the LS-SVM models. Radial basis function was used as core function with gamma equal to 27.3212 and sigma2 equal to 3.2295. The calibration set was composed of 125 samples, whereas 25 samples were in the validation set. The results indicated that LS-SVM model achieved the best prediction performance. A new process is proposed in this paper for determination of dynamic viscosity of automobile lubricant.

[Non-invasive measurement of water content in engine lubricant using visible and near infrared spectroscopy].

Visible and near-infrared reflectance spectroscopy (Vis-NIRS) was applied to non-invasively measurement of water content in engine lubricant. Based on measured spectra, several spectral calibration algorithms were adopted to improve accuracy and simply calculation. Principal component analysis (PCA) and successive projections algorithm (SPA) were separately used to reduce variables of spectral model. Nine effective variables, 476, 483, 544, 925, 933, 938, 952, 970 and 974 nm, were selected by SPA, and were inputted into partial least square regression (PLSR) and multivariable linear regression (MLR) models. Both the two models obtained better results than full-spectra-PLSR model and PCA-PLSR model. It shows that SPA does not select uninformative but effective variables from full-spectrum. Least-square support vector machine (LS-SVM) was operated to improve Vis-NIRS's ability based on full-spectrum and SPA, separately. High coefficients of determination for prediction set (Rp(2)) up to 0.9 were obtained by both full-spectrum-LS-SVM and SPA-LS-SVM models. SPA-LS-SVM is better than full-spectrum-LS-SVM. The value of Rp(2) of SPA-LS-SVM is 0.983 and residual predictive deviation (RPD) is 6.963. It is concluded that Vis-NIRS can be used in the non-invasive measurement of water content in engine lubricant, and SPA is a feasible and efficient algorithm for the spectral variable selection.

[Discrimination of varieties of brake fluid using visual-near infrared spectra].

A new method was developed to fast discriminate brands of brake fluid by means of visual-near infrared spectroscopy. Five different brands of brake fluid were analyzed using a handheld near infrared spectrograph, manufactured by ASD Company, and 60 samples were gotten from each brand of brake fluid. The samples data were pretreated using average smoothing and standard normal variable method, and then analyzed using principal component analysis (PCA). A 2-dimensional plot was drawn based on the first and the second principal components, and the plot indicated that the clustering characteristic of different brake fluid is distinct. The foregoing 6 principal components were taken as input variable, and the band of brake fluid as output variable to build the discriminate model by stepwise discriminant analysis method. Two hundred twenty five samples selected randomly were used to create the model, and the rest 75 samples to verify the model. The result showed that the distinguishing rate was 94.67%, indicating that the method proposed in this paper has good performance in classification and discrimination. It provides a new way to fast discriminate different brands of brake fluid.