Glycolic acid-based deep eutectic solvents boosting co-production of xylo-oligomers and fermentable sugars from corncob and the related kinetic mechanism.

BACKGROUND: Xylo-oligomers are a kind of high value-added products in biomass fractionation. Although there are several chemical methods to obtain xylo-oligomers from biomass, the reports about the deep eutectic solvents (DESs)-mediated co-production of xylo-oligomers and fermentable sugars and the related kinetic mechanism are limited. RESULTS: In this work, glycolic acid-based DESs were used to obtain xylo-oligomers from corncob. The highest xylo-oligomers yield of 65.9% was achieved at 120 °C for 20 min, of which the functional xylo-oligosaccharides (XOSs, DP 2-5) accounted for up to 31.8%. Meanwhile, the enzymatic digestion of cellulose and xylan in residues reached 81.0% and 95.5%, respectively. Moreover, the addition of metal inorganic salts significantly accelerated the hydrolysis of xylan and even the degradation of xylo-oligomers in DES, thus resulting in higher selectivity of xylan removal. AlCl3 showed the strongest synergistic effect with DES on accelerating the processes, while FeCl2 is best one for xylo-oligomers accumulation, affording the highest xylo-oligomers yield of 66.1% for only 10 min. Furthermore, the kinetic study indicates that the 'potential hydrolysis degree' model could well describe the xylan hydrolysis processes and glycolic acid/lactic acid (3:1) is a promising solvent for xylo-oligomers production, in particular, it worked well with FeCl2 for the excellent accumulation of xylo-oligomers. CONCLUSIONS: Glycolic acid-based deep eutectic solvents can be successfully applied in corncob fractionation with excellent xylo-oligomers and fermentable sugars yields on mild conditions, and the large amount of xylo-oligosaccharides accumulation could be achieved by specific process controlling. The strategies established here can be useful for developing high-valued products from biomass.

Gold nanospheres assembly via corona discharge technique for flexible SERS substrate.

Noble metal nanoparticles (NMNPs) assembly substrates with strongly enhanced local electromagnetic fields provide new possibilities for surface-enhanced Raman spectroscopy (SERS) sensing. Although the external-electric-field-based self-assembly (EEFSA) strategy for decreasing NMNP gap in liquid phase is relatively developed, it is rarely described in solid phase. Here, by combining corona discharge technique (CDT) as a simple EEFSA approach on flexible substrate surface modification, a flexible SERS substrate medicated with gold nanospheres (AuNSs) is produced. Because of the CDT's peculiar discharge event, makes AuNSs aggregation simply achieved. The modified flexible SERS substrate is sensitive to the detection limit of ∼10-5 mM for Rhodamine 6G (R6G), with a maximum enhancement factor of 2.79×106. Furthermore, finite-difference time-domain (FDTD) simulation confirms the SERS enhancement impact of AuNSs-based substrate. This study not only provides a low-cost, simple-to-process, high-yield, high sensitivity, and activity flexible SERS substrate, but also suggests a more practical and adaptable NMNPs self-assembly approach.

Simultaneous quantification of spike and nucleocapsid protein in inactivated COVID-19 vaccine bulk by liquid chromatography-tandem mass spectrometry.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccines are the most promising approach to control the COVID-19 pandemic. There are eminent needs to develop robust analytical methods to ensure quality control, as well as to evaluate the long-term efficacy and safety of vaccine. Although in vivo animal tests, such as serum-based ELISA, have been commonly used for quality control of vaccines, these methods have poor precision, are labor intensive, and require the availability of expensive, specific antibodies. Thus, there is growing interest to develop robust bioanalytical assays as alternatives for qualitative and quantitative evaluation of complex vaccine antigens. In this study, a liquid chromatography tandem mass spectrometry method was developed using optimized unique peptides for simultaneous determination of spike (S) and nucleocapsid (N) protein. Method sensitivity, linearity, repeatability, selectivity, and recovery were evaluated. The amount of S and N proteins in 9 batches of inactivated COVID-19 vaccines were quantified, and their compositions relative to total protein content were consistent. We believe this method can be applied for quality evaluation of other S and/or N protein based COVID-19 vaccine, and could be extended to other viral vector, and protein subunit-based vaccines.

The prediction value of PI-RADS v2 score in high-grade Prostate Cancer: a multicenter retrospective study.

Background: To explore the prediction value of PI-RADS v2 in high-grade prostate cancer and establish a prediction model combined with related variables of prostate cancer. Material and Methods: A total of 316 patients with newly discovered prostate cancer at Zhongnan Hospital of Wuhan University and Renmin Hospital of Wuhan University from December 2017 to August 2019 were enrolled in this study. The clinic information as age, tPSA, fPSA, prostate volume, Gleason score and PI-RADS v2 score have been collected. Univariate analysis was performed based on every variable to investigate the risk factors of high-grade prostate cancer. ROC curves were generated for the risk factors to distinguish the cut-off points. Logistic regression analyses were used to investigate the independent risk factors of high-grade prostate cancer. Nomogram prediction model was generated based on multivariate logistic regression analysis. The calibration curve, ROC curve, leave-one-out cross validation and independent external validation were performed to evaluate the discriminative ability, accuracy and stability of the nomogram prediction model. Results: Of 316 patients, a total of 187 patients were diagnosed as high-grade prostate cancer. Univariate analysis showed tPSA, fPSA, prostate volume, PSAD and PI-RADS v2 score were significantly different between the high- and low-grade prostate cancer patients. Univariate and multivariate logistic regression analyses showed only tPSA, prostate volume and PI-RADS v2 score were the independent risk factors of high-grade prostate cancer. The nomogram could predict the probability of high-grade prostate cancer, with a sensitivity of 79.4% and a specificity of 77.6%. The calibration curve displayed good agreement of the predicted probability with the actual observed probability. AUC of the ROC curve was 0.840 (0.797-0.884). Leave-one-out cross validation indicated the nomogram prediction model could classify 81.4% cases accurately. External data validation was performed with a sensitivity of 80.6% and a specificity of 77.3%, the Kappa value was 0.5755. Conclusions: PI-RADS v2 score had the value in predicting high-grade prostate cancer and the nomogram prediction model may help early diagnose the high risk prostate cancer.

Establishing a prediction model of infection during the intravesical instillation of bladder cancer: a multicenter retrospective study.

Objective: To explore the independent risk factors of infection during the intravesical instillation of bladder cancer and establish a prediction model, which may reduce probability of infection for bladder cancer patients. Material and Methods: 533 patients with newly discovered NMIBC at two hospitals from January 2017 to December 2019 were enrolled in this study. The patients were divided into "infection positive group" and "infection negative group". The clinical data of the two groups were analyzed by logistic regression analyses. Nomogram was generated and ROC curve, calibration curve were structured to assess the accuracy of nomogram. An independent cohort included 174 patients from another hospital validated the nomogram prediction model. Results: Of 533 patients, 185 patients had an infection. Univariate and multivariate logistic regression analyses showed diabetes mellitus, hemiplegia, patients without antibiotics and perfusion frequency (≥2 times/month) were the independent risk factors. AUC of the ROC was 0.858 (0.762-0.904). The nomogram could predict the probability of infection during the intravesical instillation of bladder tumor calibration curve showed good agreement. The external data validation gained good sensitivity and specificity, which indicated that the nomogram had great value of prediction. Conclusions: Individualized prediction of the probability of infection may reduce the incidence of infection by argeted preventive measures.

MicroRNA-1296 expression is associated with prognosis and inhibits cell proliferation and invasion by Wnt signaling in non-small cell lung cancer.

MicroRNAs (miRNAs) are vital regulators of non-small cell lung cancer (NSCLC) development and tumorigenesis. The aim of the present study was to explore the role of miRNA (miR)-1296 expression in NSCLC. The expression of miR-1296 was detected by reverse transcription-quantitative PCR in NSCLC tissues and matched normal tissues. The association of miR-1296 expression with clinicopathological factors of NSCLC patients was evaluated by the χ2 test. Prognostic value of miR-1296 expression levels in patients with NSCLC was assessed using the Kaplan-Meier method and a Cox proportional hazards model; Cell Counting Kit-8, Transwell migration and western blot assays were used to detect the association between miR-1296 and cell proliferation, invasion and Wnt signaling in NSCLC, respectively. The results of the present study demonstrated that miR-1296 expression was significantly downregulated in NSCLC tissues and cells compared to corresponding controls. Lower miR-1296 expression exhibited a significant association with lymph node metastasis and tumor-node-metastasis stage of patients with NSCLC. In addition, the survival analysis demonstrated that low miR-1296 expression predicted a poorer prognosis compared to high miR-1296 expression. Multivariate Cox analysis also demonstrated that reduced miR-1296 expression was an independent risk factor of NSCLC prognosis. Additionally, miR-1296 inhibited cell proliferation, invasion and Wnt signaling in NSCLC. Thus, the results of the present study indicated that miR-1296 expression may be a potential biomarker of NSCLC prognosis and potential target for NSCLC treatment.

Establishing a prediction model for prostate cancer bone metastasis.

We collected clinical data from 308 prostate cancer (PCa) patients to investigate the clinical characteristics and independent risk factors of bone metastasis (BM) and to establish a prediction model for BM of PCa and determine the necessity of bone scans. Univariate and multivariate analyses were performed based on age, biopsy Gleason score (BGS), clinical tumor stage (cTx), total prostate specific antigen (tPSA), free prostate specific antigen (fPSA), fPSA/tPSA, prostate volume, alkaline phosphatase (ALP), serum calcium and serum phosphorus. Moreover, 80 of the 308 PCa patients had a PI-RADS v2 score and were analysed retrospectively. The univariate analysis showed that the BGS, cTx, tPSA, fPSA, prostate volume and ALP were significant. The multivariate logistic regression analysis showed significant differences among the BGS, cTx, tPSA and ALP. Four cases should be highly suspected with BM: (i) cTl-cT2, BGS ≤7, ALP >120 U/L and tPSA >90.64 ng/ml; (ii) cTl-cT2, BGS ≥8, and ALP >120 U/L; (iii) cT3-cT4, BGS ≤7, and ALP >120 U/L; and (iv) cT3-cT4 and BGS ≥8. After the PI-RADS v2 score was included in the model, the AUC of the prediction model rose from 0.884 (95% CI: 0.813-0.996) to 0.934 (95% CI: 0.883-0.986). This model may help determine the necessity of bone scans to diagnose BM for PCa patients.