Phytoconstituents of Selaginella effusa Alston and Their α-Glucosidase as well as Urease Inhibitory Activities

Three new compounds ( 1 – 2 , 14 ), as well as 22 known compounds ( 3 – 13 , 15 – 25 ), were extracted for the first time from the Selaginella effusa Alston (S. effusa). For the unknown compounds, the planar configurations were determined via NMR and by high-resolution mass spectrometry, while their absolute configurations were determined by calculated electronic circular dichroism (ECD), and the configuration of the stereogenic center of biflavones 4 – 5 were established for the first time. The pure compounds ( 1 – 25 ) were tested in vitro to determine the inhibitory activity of the enzyme-catalyzed reactions. Compounds 1 – 9 inhibited α-glucosidase with IC₅₀ values ranging from 0.30±0.02 to 4.65±0.04 μM and kinetic analysis of enzyme inhibition indicated that biflavones 1 – 3 were mixed-type α-glucosidase inhibitors. Compounds 12 – 13 showed excellent inhibitory activity against urease, with compound 12 (IC₅₀=4.38±0.31 μM) showing better inhibitory activity than the positive control drug AHA (IC₅₀13.52±0.61 μM). In addition, molecular docking techniques were used to simulate inhibitor-enzyme binding and to estimate the binding posture of the α-glucosidase and urease catalytic sites.     

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302–0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299–0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.     

ent-Pimarane Diterpenes from the Aerial Parts of Siegesbeckia pubescens

Five new ent-pimarane diterpenes ( 1 – 5 ) and five known analogs ( 6 – 10 ) were isolated from the aerial parts of Siegesbeckia pubescens. Their structures, including absolute configurations, were determined by comprehensive spectroscopic methods especially 1D and 2D NMR and quantum chemical electronic circular dichroism calculations. All the isolated compounds were evaluated for their cytotoxicity against human BT549, A549 and H157 cancer cell lines. Among them, compounds 1 and 2 showed mild cytotoxicity against lung cancer cell lines H157 with IC₅₀ values of 16.35±2.59 and 18.86±4.83 μM, respectively.     

High-Resolution Performance of Polycaprolactone Functionalized with Guanidinium Ionic Liquid for Gas Chromatography

This work firstly reported a new polycaprolactone based material functionalized with guanidinium ionic liquid (PCL-GIL) as the stationary phase with high resolution performance for capillary gas chromatography (GC). It is composed of polycaprolactone (PCL) and guanidinium ionic liquid (GIL) with amphiphilic conformation. The PCL-GIL capillary column coated by static method exhibited high column efficiency of 3942 plates/m and moderate polarity. As a result, the PCL-GIL column exhibited high-resolution capability. For a mixture of 27 analytes with a wide ranging polarity and outperformed the PCL-2OH and HP-35 columns, showing its advantageous separation capability for analytes of diverse types. Moreover, the PCL-GIL column showed high resolving capability for various positional isomers and cis-/trans-isomers, including alkylbenzenes, chlorobenzenes, naphthalenes, bromonitrobenzenes, chloronitrobenzenes, benzaldehydes, phenols, alcohols, respectively. In a word, PCL derivatized by GIL units as a new type of stationary phase has a promising future in GC separations.     

Benzotriazole-Based Polymer Acceptor for High-Efficiency All-Polymer Solar Cells with High Photocurrent and Low Voltage Loss

The power conversion efficiencies (PCEs) of all-polymer solar cells (all-PSCs) have already exceeded 17%. However, the limited absorption range of an all-polymer system results in significantly reduced short-circuit current density (J_sc), which eventually influences the PCE improvement. To broaden the light absorption of polymer acceptors, herein, benzotriazole is introduced in the core unit of small molecule acceptors and thus two narrow-bandgap polymer acceptors named PTz-BO and PTz-C11 featuring the same molecular backbone and different side-chain length are synthesized. Compared with PTz-C11, the PTz-BO based-all PSCs deliver a slightly reduced J_sc, a large open-circuit voltage (V_oc) and a low voltage loss below 0.50 V. Moreover, ternary all-PSCs are constructed by introducing PTz-C11 as a guest component. Benefiting from the reduced recombination, improved exciton generation and dissociation, and balanced charge transport, a high efficiency of 16.58% is obtained for the ternary all-PSCs, with a high J_sc over 25 mA cm⁻² without sacrificing the V_oc. Such result represents the highest efficiency reported for benzotriazole-based all-PSCs in the literature thus far. This work demonstrates the great potential of benzotriazole for the synthesis of efficient narrow-bandgap polymer acceptors.     

Retraction Note: miR-195-5p/NOTCH2-mediated EMT modulates IL-4 secretion in colorectal cancer to affect M2-like TAM polarization

Background

Hepatocellular carcinoma (HCC) generally arises from a background of liver cirrhosis (LC). Patients with cirrhosis and suspected HCC are recommended to undergo serum biomarker tests and imaging diagnostic evaluation. However, the performance of routine diagnostic methods in detecting early HCC remains unpromising.

Methods

Here, we conducted a large-scale, multicenter study of 1675 participants including 490 healthy controls, 577 LC patients, and 608 HCC patients from nine clinical centers across nine provinces of China, profiled gene mutation signatures of cell-free DNA (cfDNA) using Circulating Single-Molecule Amplification and Resequencing Technology (cSMART) through detecting 931 mutation sites across 21 genes.

Results

An integrated diagnostic model called “Combined method” was developed by combining three mutation sites and three serum biomarkers. Combined method outperformed AFP in the diagnosis of HCC, especially early HCC, with sensitivities of 81.25% for all stages and 66.67% for early HCC, respectively. Importantly, the integrated model exhibited high accuracy in differentiating AFP-negative, AFP-L3-negative, and PIVKA-II-negative HCCs from LCs.

     

ploidyfrost: Reference-free estimation of ploidy level from whole genome sequencing data based on de Bruijn graphs

Polyploidy is ubiquitous and its consequences are complex and variable. A change of ploidy level generally influences genetic diversity and results in morphological, physiological and ecological differences between cells or organisms with different ploidy levels. To avoid cumbersome experiments and take advantage of the less biased information provided by the vast amounts of genome sequencing data, computational tools for ploidy estimation are urgently needed. Until now, although a few such tools have been developed, many aspects of this estimation, such as the requirement of a reference genome, the lack of informative results and objective inferences, and the influence of false positives from errors and repeats, need further improvement. We have developed ploidyfrost , a de Bruijn graph-based method, to estimate ploidy levels from whole genome sequencing data sets without a reference genome. ploidyfrost provides a visual representation of allele frequency distribution generated using the ggplot2 package as well as quantitative results using the Gaussian mixture model. In addition, it takes advantage of colouring information encoded in coloured de Bruijn graphs to analyse multiple samples simultaneously and to flexibly filter putative false positives. We evaluated the performance of ploidyfrost by analysing highly heterozygous or repetitive samples of Cyclocarya paliurus and a complex allooctoploid sample of Fragaria × ananassa. Moreover, we demonstrated that the accuracy of analysis results can be improved by constraining a threshold such as Cramér's V coefficient on variant features, which may significantly reduce the side effects of sequencing errors and annoying repeats on the graphical structure constructed.