A Selective Release System Based on Dual‐Drug‐Loaded Mesoporous Silica for Nanoparticle‐Assisted Combination Therapy

A selective release system was demonstrated with a dual‐cargo loaded MSNs. When stimulated by different signals (UV or H⁺), this system could selectively release different kinds of cargoes individually. Furthermore, this system has been used to provide a combination of chemotherapy and biotherapy for cancer treatment. This controlled release system could be an important step in the development of more effective and sophisticated nanomedicine and nanodevices, due to the possibility of selective release of a complex multi‐drug.     

Hydrogen Bond Mediated Aglycone Delivery: Synthesis of Linear and Branched α‐Glucans

A Hydrogen bond mediated aglycone delivery (HAD) method was applied to the synthesis of α‐glucans, which are abundant in nature, but as targets represent a notable challenge to chemists. The synthesis of linear oligosaccharide sequences was accomplished in complete stereoselectivity in all glycosylations. The efficacy of HAD may diminish with the increased bulk of the glycosyl acceptor, and may be an important factor for the syntheses of oligomers beyond pentasaccharides. The synthesis of a branched structure proved more challenging, particularly with bulky trisaccharide acceptors.     

Mutant-Selective Allosteric EGFR Degraders are Effective Against a Broad Range of Drug-Resistant Mutations

Targeting epidermal growth factor receptor (EGFR) through an allosteric mechanism provides a potential therapeutic strategy to overcome drug-resistant EGFR mutations that emerge within the ATP binding site. Here, we develop an allosteric EGFR degrader, DDC-01-163, which can selectively inhibit the proliferation of L858R/T790M (L/T) mutant Ba/F3 cells while leaving wildtype EGFR Ba/F3 cells unaffected. DDC-01-163 is also effective against osimertinib-resistant cells with L/T/C797S and L/T/L718Q EGFR mutations. When combined with an ATP-site EGFR inhibitor, osimertinib, the anti-proliferative activity of DDC-01-163 against L858R/T790M EGFR-Ba/F3 cells is enhanced. Collectively, DDC-01-163 is a promising allosteric EGFR degrader with selective activity against various clinically relevant EGFR mutants as a single agent and when combined with an ATP-site inhibitor. Our data suggests that targeted protein degradation is a promising drug development approach for mutant EGFR.     

Modeling and optimizing toughness and rigidity of PA6/SBR: Using compatibilizer and response surface methodology

The improvement of miscibility between toughened Polyamide-6 (PA6) and Styrene-Butadiene Rubber (SBR) was carried out using grafted Glycidyl Methacrylate (SBR-g-GMA). At first, the compatibilizers were prepared using different comonomers, Styrene, and N-vinyl pyrrolidone. Central composited design (CCD) was distinctly applied to study the influence of Glycidyl Methacrylate (GMA) content and comonomer/GMA on the process of compatibilizer preparation. Four models were developed for Gel content and Degree of grafting for both comonomers using Design-expert software. The models were used to calculate the optimum operating conditions and according to the Flory-Huggins parameter and obtained results, SBR-co-NVP-g-GMA was chosen as an effective compatibilizer. Afterward, another CCD was employed to scrutinize the effect of various amounts and grafting degree of compatibilizer on morphology and mechanical properties of PA6/SBR. The Interparticle distance and polydispersity were studied using a Scanning electron microscope (SEM) and also the Izod impact test inspected in order to evaluate the mechanical properties. Finally, modulus and impact strength were optimized to minimize the former and maximize the latter. Also, the most practical terms in the fitted model are statistically specified using F-value. The root causes for the improvement of blend properties were attributed to a chemical reaction between epoxy groups in SBR-g-GMA and both the carboxylic and amine groups in PA6. Impact strength (539.8 J/m) and modulus (2017.2 N/mm²) of the optimum blend indicate an excellent agreement with the amounts predicted by the models.     

Optimization of ultrasound-assisted extraction of phenolic compounds from Sesamum indicum

Abstract

Effective extraction of phyto-biomolecules insures retaining maximum functionality along with higher recovery. In this study, ultrasound-solvent assisted extraction (USAE) was employed for optimal extraction of phyto-biomolecules from Sesamum indicum (sesame) leaves using the approach of Response Surface Methodology (RSM). The optimized condition of 200?W power, 59% methanol concentration with 1:14?g/mL solid–liquid ratio and 15?min of extraction time yielded 367.39?±?1.85?mg GAE/100?g of total phenolic content, 96.72?±?3.27% of free radical scavenging activity and 81.20?±?2.87% of iron chelating activity respectively. The extract consist of essential phytocomponents like gallic acid, chlorogenic acid, and quercetin with lipid peroxidation activities of >50% over incubation time of 48?h. Also, showed antimicrobial activity against various Gram’s negative and positive food borne pathogens. The results of this study implied the importance of USAE for effective and optimum recovery of phyto-biomolecules from Sesame leaves with retained functional properties.     

Biosurfactant trehalose lipid‐enhanced ultrasound‐assisted micellar extraction and determination of the main antioxidant compounds from functional plant tea

Hydrosoluble trehalose lipid (a biosurfactant) was employed for the first time as a green extraction solution to extract the main antioxidant compounds (geniposidic acid, chlorogenic acid, caffeic acid, and rutin) from functional plant tea (Eucommia ulmoides leaves). Single‐factor tests and response surface methodology were employed to optimize the extraction conditions for ultrasound‐assisted micellar extraction combined with ultra‐high‐performance liquid chromatography in succession. A Box‐Behnken design (three‐level, three‐factorial) was used to determine the effects of extraction solvent concentration (1–5 mg/mL), extraction solvent volume (5–15 mL), and extraction time (20–40 min) at a uniform ultrasonic power and temperature. In consequence, the best analyte extraction yields could be attained when the trehalose lipid solution concentration was prepared at 3 mg/mL, the trehalose lipid solution volume was 10 mL and the extraction time was set to 35 min. In addition, the recoveries of the antioxidants from Eucommia ulmoides leaves analyzed by this analytical method ranged from 98.2 to 102%. These results indicated that biosurfactant‐enhanced ultrasound‐assisted micellar extraction coupled with a simple ultra‐high‐performance liquid chromatography method could be effectively applied in the extraction and analysis of antioxidants from Eucommia ulmoides leaf samples.     

Combinatıon of a Box-Behnken design technique with response surface methodology for optimization of the photocatalytic mineralization of C.I. Basic Red 46 dye from aqueous solution

The photodegradation of an industrial azo dye C.I Basic Red 46 was examined in a fixed-bed photoreactor using UV-lamps simulated to the solar irradiation. In our photodecolorization study, the UV/TiO₂ process was optimized using the Box-Behnken approach to evaluate the synergistic effects of three independent parameters (initial concentration of the dye, flow rate, and UV intensity) on mineralization effectiveness. The response surface methodology was in good promise with the prediction model (coefficients of determination of decolorization and mineralization were R²_Dec = 0.997 and R²_TOC = 0.994, respectively). The effects of the factors could be estimated from a second–order polynomial equation and student’s t-test. The optimal parameters of decolorization and mineralization were as follows: initial concentration of colorant 25 mg L⁻¹, rate of fluid flow 0.3 L min⁻¹, and ultraviolet light intensity 38.1 W m⁻². The decolorization and mineralization removal efficiency under these optimal conditions were 100% and 57.63% respectively. These results indicate that optimization using response surface methodology, based on the Box-Behnken approach, is an excellent tool for determining the optimal conditions, and the process can be easily extrapolated for a specific treatment of real waste water containing the azo dye C.I Basic Red 46. Also, the intermediates that were produced during photodegradation process of Basic Red 46 were determined by GC/MS.     

基于线上线下结合的无机定性分析实验教学

针对在实验室开设定性分析实验受到的制约,设计并开设了"无机化合物的性质与鉴定"虚拟实验,以作为常规无机定性分析实验的重要补充和扩展。虚拟实验和传统实验一并开设,构成线上线下结合的教学模式,完善知识体系,全面培养学生的无机定性分析能力。     

Ultrasonic treatment of water contaminated with various pollutants onto copper nanowires loaded on activated carbon using response surface methodology and artificial intelligent

In this study, the potential application of copper nanowires loaded on activated carbon for simultaneous removal of Disulfine blue (DB), Crystal violet (CV) and Sunset yellow (SY) has been described. The relation between adsorption properties with variables such as solution pH, adsorbent value, contact time and initial dyes concentration was investigated and optimized. A three‐layer artificial neural network (ANN) model was utilized to predict dyes removal (%) by adsorbent following conduction of experiments. The training of network at above mention experimental data confirms its ability to forecast the removal performance with a linear transfer function (purelin) at output layer. The Levenberg–Marquardt algorithm and tangent sigmoid transfer function (tansig) with 16 neurons at the hidden layer was applied. Parameters were optimized by central composite design (CCD) combined with response surface methodology (RSM) and desirability function. The accuracy of ANN was judged according to both MSE and AAD% at optimal conditions and results indicate its superiority to RSM model in term of higher R² and lower AAD% values. This observation was also corroborated by the parity plots between the predicted and experimental values. The ANN model was better in both data fitting and prediction capability in comparison to RSM model.     

Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and high-frequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.