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Determination of metallic and polymeric contents in electronic waste materials and evaluation of their hydrometallurgical recovery potential
Not provided.
Construction of EGFR peptide gefitinib/quantum dots long circulating polymeric liposomes for treatment and detection of nasopharyngeal carcinoma
Gefitinib/Quantum dots (QDs) loaded peptide long circulating liposomes (G/QDs-P-LCPL) were successfully prepared for treatment and detection by fluorescence labeling for nasopharyngeal carcinoma. Gefitinib was found to have marked inhibition which is dose- and time-dependent. Hoechst 33258 florescence staining and wound-healing assay indicated that as G/QDs-P-LCPL concentration increased, HONE1 staining cells decreased, while the amount of nucleus pyknosis and karyorrhexis grew. Florescence tracing result shows that the drug mainly distributed through tumors. G-P-LCPL target the HONE1 cells and significantly increase the drug uptake efficiency so as to improve the cells inhibit rate compared with the non-targeting group. The EGFR peptide LCPL are potentially useful for drug and fluorescence labeled delivery applications. - Highlights: • Gefitinib/QDs-EGFR peptide liposomes (G/QDs-P-LCPL) were prepared for nasopharyngeal carcinoma treatment and detection. • G-P-LCPL can effectively increase the drug uptake efficiency so as to improve the cells inhibit rate compared with LCPL. • The EGFR peptide LCPL are potentially useful for drug and fluorescence labeled delivery applications.
Bacterial metabolite S-equol modulates glucagon-like peptide-1 secretion from enteroendocrine L cell line GLUTag cells via actin polymerization
Highlights: • Receptors for S-equol were expressed in GLUTag cells. • S-equol increased the intracellular Ca{sup 2+} levels via G{sub q} signaling. • S-equol prevented GLP-1 secretion. • S-equol caused cortical actin reorganization via G{sub q} and G{sub 12/13} pathways. S-equol is one of gut bacterial metabolites produced from soybean isoflavone daizein. While S-equol is known to promote glucose-induced insulin secretion from pancreatic β cells, whether S-equol affects glucagon-like peptide-1 (GLP-1) secretion from enteroendoceine L cells remains unclear. Here we assessed the effect of S-equol on GLP-1 secretion from mouse enteroendocrine L cell line GLUTag cells. GLUTag cells expressed GPR30 and estrogen receptors, which are putative S-equol receptors. Application of S-equol induced an increase in intracellular Ca{sup 2+} levels via GPR30. However, S-equol did not enhance GLP-1 exocytosis, and long-term treatment of S-equol suppressed GLP-1 secretion. Moreover, immunocytochemistry revealed that S-equol increased the density of cortical actin filaments via G{sub 12/13} signaling under GPR30. These data suggest that S-equol prevents GLP-1 secretion as a result of competing regulation between Ca{sup 2+} mobilization and actin reorganization.
SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles
Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.
Pressure-induced polymerization of butyndioic acid and its Li + salt
Abstract not provided
A novel organic-inorganic hybrid polymerization strategy for titanium oxide/polymer nanocomposites with supercapacitive properties
Not Available
Univariate conditional variational autoencoder for morphogenic pattern design in frontal polymerization-based manufacturing
Not Available
Hydrophilic encapsulation of multi-walled carbon nanotubes using admicellar polymerization
Not Available
Quest for environmentally sustainable materials: A case for animal-based fillers and fibers in polymeric biocomposites
This review explores the potential of animal-based fillers and fibers as eco-friendly alternatives to conventional synthetic ones. Examining materials such as wool, silk, feather, hair and beak, the review elucidates their chemistry, structure, properties and sources, emphasizing biodegradability and renewability. It also discusses the compatibility of these materials with polymer matrices and their mechanical, acoustic and thermal performances. Further, the review critically analyzes environmental and ethical implications, presenting challenges and opportunities in the emerging field. By addressing ecological and performance aspects, it contributes to global efforts in fostering sustainability in materials science. Future research to address gaps and enhance the design, manufacture and application of animal-based reinforcements in various industries are clearly outlined at the end of the review.