Study on the structure characterization and moisturizing effect of Tremella polysaccharide fermented from GCMCC5.39

The structure and moisture retention of Tremella polysaccharide fermented from GCMCC5.39(FTP)were evaluated.After UV,infrared spectrum analysis,HPAEC-PAD,HPSEC and 1 D NMR analysis,the composition of the purifi ed FTP was determined.Purifi ed components of fermented Tremella polysaccharide(FTPS)was made of galactose,mannose,glucose,galactosmine,glucosamine,and contain a large amount of hydroxyl,carbonyl and amino groups.FTPS wasα-neutral pyranose without uronic acid.FTPS-1 and FTPS-2 were obtained after purifi cation by DEAE-Sepharose Fast Flow Column.The molecular weights of FTPS-1 and FTPS-2 were 25722 and 177263 Da.FTPS-2 had a better ability to prevent moisture loss,and the optimal moisture retention period was 0–4 h.FTPS-2 could signifi cantly increase the moisture content of the skin epidermis and showed a dose-concentration relationship.The effect of FTPS-2 on the expression of different moisturizing genes was evaluated in a human skin keratinocyte model.The results showed that FTPS-2 has no cytotoxicity,and could signifi cantly promote AQP3,TGM1,CASP14,HYAL2,FLG gene expression level in HaCaT cells.It has the most signifi cant infl uence at HYAL2 protein expression on 50μg/mL.

The Cytotoxic Constituents from Marine-derived Streptomyces 3320^(#)

The present work studies the chemical constituents from marine-derived streptomyces 3320^# and their antitumor activities. The n-BuOH extract of the ferment broth of 3320^# was chromatographed on silica gel, Sephadex LH-20, ODS columns and HPLC to separate the compounds with antitoumor activities. Their structures were identified using IR, UV, NMR, MS spectroscopic techniques and compared with published data. The antitumor activities of the isolates were assayed using SRB method and flow cytometry assay, accompanied with the morphological observation of the cells under light micro- scope against mammalian tsFT210 cells. Ten compounds, cyclo-（Ala-Leu） 1, cyclo-（Ala-Ile） 2, cyclo-（Ala-Val） 3, cyclo- （Phe-Pro） 4, cyclo-（Phe-Gly）5, cyclo-（Leu-Pro）6, 1-methyl-1, 2, 3, 4-tetrahydro-β-carboline-3-carboxylic acid 7, N-（4- hydroxyphenethyl） acetamide 8, 4-methyoxy-l-（2-hydroxy） ethylbenzene 9 and uridine 10, were isolated from the ferment broth of streptomyces 3320^# . Among them, compounds 6, 7, 8 and 10 showed potent cytotoxicity against the tsFT210 cell with the IC50 values of 3.6, 7.2, 5.2 and 1.6 mmol L-1, respectively. Compounds 8, 10 also exhibited apoptosis inducing activity under 2.0 mmol L-1. Compounds 6, 7, 8 and 10 are the principle bioactive constituents responsible for the antitumor activities of marine streptomyces 3320^#. Compound 7 was isolated from this species for the first time.

Geometrical Frameworks in Identification Problem

The purpose of this review is to apply geometric frameworks in identification problems. In contrast to the qualitative theory of dynamical systems (DSQT), the chaos and catastrophes, researches on the application of geometric frameworks have not been performed in identification problems. The direct transfer of DSQT ideas is inefficient through the peculiarities of identification systems. In this paper, the attempt is made based on the latest researches in this field. A methodology for the synthesis of geometric frameworks (GF) is proposed, which reflects features of nonlinear systems. Methods based on GF analysis are developed for the decision-making on properties and structure of nonlinear systems. The problem solution of structural identifiability is obtained for nonlinear systems under uncertainty.

Structural-Identification Aspects of Decision-Making in Systems with Bouc-Wen Hysteresis

Considering the structural analysis problem of systems properties with Bouc-Wen hysteresis (BWH), various approaches are proposed for the identification of BWH parameters. The applied methods and algorithms are based on the design of parametric models and consider a priori information and the results of data analysis. Structural changes in the BWH form a priori. Methods for the Bouc-Wen model (BWM) identification and its structure estimation are not considered under uncertainty. The study’s purpose is the analysis the structural problems of the Bouc-Wen hysteresis identification. The analysis base is the application of geometric frameworks (GF) under uncertainty. Methods for adaptive estimation parameters and structural of BWM were proposed. The adaptive system stability is proved based on vector Lyapunov functions. An approach is proposed to estimate the identifiability and structure of the system with BWH. The method for estimating the identifiability degree based on the analysis of GF is considered. BWM modifications are proposed to guarantee the system’s stability and simplify its description.

Parameter identifiability of a within-host SARS-CoV-2 epidemic model

Parameter identification involves the estimation of undisclosed parameters within a system based on observed data and mathematical models.In this investigation,we employ DAISY to meticulously examine the structural identifiability of parameters of a within-host SARS-CoV-2 epidemic model,taking into account an array of observable datasets.Furthermore,Monte Carlo simulations are performed to offer a comprehensive practical analysis of model parameters.Lastly,sensitivity analysis is employed to ascertain that decreasing the replication rate of the SARS-CoV-2 virus and curbing the infectious period are the most efficacious measures in alleviating the dissemination of COVID-19 amongst hosts.

FATOC:Bug Isolation Based Multi-Fault Localization by Using OPTICS Clustering

Bug isolation is a popular approach for multi-fault localization(MFL),where all failed test cases are clustered into several groups,and then the failed test cases in each group combined with all passed test cases are used to localize only a single fault.However,existing clustering algorithms cannot always obtain completely correct clustering results,which is a potential threat for bug isolation based MFL approaches.To address this issue,we first analyze the influence of the accuracy of the clustering on the performance of MFL,and the results of a controlled study indicate that using the clustering algorithm with the highest accuracy can achieve the best performance of MFL.Moreover,previous studies on clustering algorithms also show that the elements in a higher density cluster have a higher similarity.Based on the above motivation,we propose a novel approach FATOC(One-Fault-at-a-Time via OPTICS Clustering).In particular,FATOC first leverages the OPTICS(Ordering Points to Identify the Clustering Structure)clustering algorithm to group failed test cases,and then identifies a cluster with the highest density.OPTICS clustering is a density-based clustering algorithm,which can reduce the misgrouping and calculate a density value for each cluster.Such a density value of each cluster is helpful for finding a cluster with the highest clustering effectiveness.FATOC then combines the failed test cases in this cluster with all passed test cases to localize a single-fault through the traditional spectrum-based fault localization(SBFL)formula.After this fault is localized and fixed,FATOC will use the same method to localize the next single-fault,until all the test cases are passed.Our evaluation results show that FATOC can significantly outperform the traditional SBFL technique and a state-of-the-art MFL approach MSeer on 804 multi-faulty versions from nine real-world programs.Specifically,FATOC’s performance is 10.32%higher than that of traditional SBFL when using Ochiai formula in terms of metric A-EXAM.Besides,the results also indicate that,when checking 1%,3%and 5%statements of all subject programs,FATOC can locate 36.91%,48.50%and 66.93%of all faults respectively,which is also better than the traditional SBFL and the MFL approach MSeer.