Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time

Volatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.     

Interpretation of Strengthening Mechanism of Densified Wood from Supramolecular Structures

In this study, densified wood was prepared by hot pressing after partial lignin and hemicellulose were removed through alkaline solution cooking. The tensile strength and elastic modulus of densified wood were improved up to 398.5 MPa and 22.5 GPa as compared with the original wood, and the characterization of its supramolecular structures showed that the crystal plane spacing of the densified wood decreased, the crystallite size increased, and the maximum crystallinity (CI) of cellulose increased by 15.05%; outstandingly, the content of O(6)H⋯O(3′) intermolecular H-bonds increased by approximately one-fold at most. It was found that the intermolecular H-bond content was significantly positively correlated with the tensile strength and elastic modulus, and accordingly, their Pearson correlation coefficients were 0.952 (p < 0.01) and 0.822 (p < 0.05), respectively. This work provides a supramolecular explanation for the enhancement of tensile strength of densified wood.     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.     

Highly Effective Proton-Conduction Matrix-Mixed Membrane Derived from an -SO3H Functionalized Polyamide

Developing a low-cost and effective proton-conductive electrolyte to meet the requirements of the large-scale manufacturing of proton exchange membrane (PEM) fuel cells is of great significance in progressing towards the upcoming “hydrogen economy” society. Herein, utilizing the one-pot acylation polymeric combination of acyl chloride and amine precursors, a polyamide with in-built -SO₃H moieties (PA-PhSO₃H) was facilely synthesized. Characterization shows that it possesses a porous feature and a high stability at the practical operating conditions of PEM fuel cells. Investigations of electrochemical impedance spectroscopy (EIS) measurements revealed that the fabricated PA-PhSO₃H displays a proton conductivity of up to 8.85 × 10⁻² S·cm⁻¹ at 353 K under 98% relative humidity (RH), which is more than two orders of magnitude higher than that of its -SO₃H-free analogue, PA-Ph (6.30 × 10⁻⁴ S·cm⁻¹), under the same conditions. Therefore, matrix-mixed membranes were fabricated by mixing with polyacrylonitrile (PAN) in different ratios, and the EIS analyses revealed that its proton conductivity can reach up to 4.90 × 10⁻² S·cm⁻¹ at 353 K and a 98% relative humidity (RH) when the weight ratio of PA-PhSO₃H:PAN is 3:1 (labeled as PA-PhSO₃H-PAN (3:1)), the value of which is even comparable with those of commercial-available electrolytes being used in PEM fuel cells. Additionally, continuous tests showed that PA-PhSO₃H-PAN (3:1) possesses a long-life reusability. This work demonstrates, using the simple acylation reaction with the sulfonated module as precursor, that low-cost and highly effective proton-conductive electrolytes for PEM fuel cells can be facilely achieved.     

Investigation Driven by Network Pharmacology on Potential Components and Mechanism of DGS,a Natural Vasoprotective Combination,for the Phytotherapy of Coronary Artery Disease

Phytotherapy offers obvious advantages in the intervention of Coronary Artery Disease (CAD), but it is difficult to clarify the working mechanisms of the medicinal materials it uses. DGS is a natural vasoprotective combination that was screened out in our previous research, yet its potential components and mechanisms are unknown. Therefore, in this study, HPLC-MS and network pharmacology were employed to identify the active components and key signaling pathways of DGS. Transgenic zebrafish and HUVECs cell assays were used to evaluate the effectiveness of DGS. A total of 37 potentially active compounds were identified that interacted with 112 potential targets of CAD. Furthermore, PI3K-Akt, MAPK, relaxin, VEGF, and other signal pathways were determined to be the most promising DGS-mediated pathways. NO kit, ELISA, and Western blot results showed that DGS significantly promoted NO and VEGFA secretion via the upregulation of VEGFR2 expression and the phosphorylation of Akt, Erk1/2, and eNOS to cause angiogenesis and vasodilation. The result of dynamics molecular docking indicated that Salvianolic acid C may be a key active component of DGS in the treatment of CAD. In conclusion, this study has shed light on the network molecular mechanism of DGS for the intervention of CAD using a network pharmacology-driven strategy for the first time to aid in the intervention of CAD.     

Simultaneous Determination of Six Immunosuppressants in Human Whole Blood by HPLC-MS/MS Using a Modified QuEChERS Method

A high-performance liquid chromatography-tandem mass spectrometry method was established for the simultaneous determination of mycophenolic acid, mycophenolate mofetil, tacrolimus, rapamycin, everolimus and pimecrolimus in human whole blood by optimizing the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) preparation method. Whole blood was extracted into ethyl acetate, salted out with anhydrous magnesium sulfate, and purified with ethylenediamine-N-propyl silane adsorbent. The supernatant was evaporated under nitrogen until dry and finally reconstituted in methanol. Chromatographic separation was performed on an Agilent Poroshell 120 EC-C18 column in methanol (mobile phase A)-water (optimized for 0.1% acetic acid and 10 mM ammonium acetate, mobile phase B) at a 0.3 mL·min⁻¹ flow rate. Electrospray ionization and positive ion multiple reaction monitoring were used for detection. The time for of analysis was 13 min. The calibration curves range of tacrolimus, rapamycin, everolimus and pimecrolimus were in the range of 1–100 ng·mL⁻¹, mycophenolate mofetil in the range of 0.1–10 ng·mL⁻¹ and mycophenolic acid at 10–1000 ng·mL⁻¹. All correlation coefficients were >0.993. The coefficients of variation (CV, %) for inter-day and intra-day precision were less than 10%, while the spiked recoveries were in the range of 92.1% to 116%. Our method was rapid, sensitive, specific, and reproducible for the simultaneous determination of six immunosuppressants in human whole blood. Importantly, our approach can be used to monitor drug concentrations in the blood to facilitate disease treatment.     

Insights into the Allosteric Effect of SENP1 Q597A Mutation on the Hydrolytic Reaction of SUMO1 via an Integrated Computational Study

Small ubiquitin-related modifier (SUMO)-specific protease 1 (SENP1) is a cysteine protease that catalyzes the cleavage of the C-terminus of SUMO1 for the processing of SUMO precursors and deSUMOylation of target proteins. SENP1 is considered to be a promising target for the treatment of hepatocellular carcinoma (HCC) and prostate cancer. SENP1 Gln597 is located at the unstructured loop connecting the helices α4 to α5. The Q597A mutation of SENP1 allosterically disrupts the hydrolytic reaction of SUMO1 through an unknown mechanism. Here, extensive multiple replicates of microsecond molecular dynamics (MD) simulations, coupled with principal component analysis, dynamic cross-correlation analysis, community network analysis, and binding free energy calculations, were performed to elucidate the detailed mechanism. Our MD simulations showed that the Q597A mutation induced marked dynamic conformational changes in SENP1, especially in the unstructured loop connecting the helices α4 to α5 which the mutation site occupies. Moreover, the Q597A mutation caused conformational changes to catalytic Cys603 and His533 at the active site, which might impair the catalytic activity of SENP1 in processing SUMO1. Moreover, binding free energy calculations revealed that the Q597A mutation had a minor effect on the binding affinity of SUMO1 to SENP1. Together, these results may broaden our understanding of the allosteric modulation of the SENP1−SUMO1 complex.     

Interfacial Charge Transfer Induced Electronic Property Tuning of MoS_2 by Molecular Functionalization

The modulation of electrical properties of MoS_2 has attracted extensive research interest because of its potential applications in electronic and optoelectronic devices.Herein,interfacial charge transfer induced electronic property tuning of MoS_2 are investigated by in situ ultraviolet photoelectron spectroscopy and x-ray photoelectron spectroscopy measurements.A downward band-bending of MoS_2-related electronic states along with the decreasing work function,which are induced by the electron transfer from Cs overlayers to MoS_2,is observed after the functionalization of MoS_2 with Cs,leading to n-type doping.Meanwhile,when MoS_2 is modified with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane(F_4-TCNQ),an upward band-bending of MoS_2-related electronic states along with the increasing work function is observed at the interfaces.This is attributed to the electron depletion within MoS_2 due to the strong electron withdrawing property of F_4-TCNQ,indicating p-type doping of MoS_2.Our findings reveal that surface transfer doping is an effective approach for electronic property tuning of MoS_2 and paves the way to optimize its performance in electronic and optoelectronic devices.