Re-examination of phase relations between solid solutions in R4Al2O9-R4Si2N2O7-R4Si2O10 (R=Y,Gd, Yb) systems

Samples in Si–Al-R-O-N (R = Y, Gd, Yb) systems were prepared by solid-state reactions using R₂O₃, Al₂O₃, SiO₂ and Si₃N₄ powders as starting materials. X-ray diffraction was done to investigate RAM-J(R) solid solutions [RAM = R₄Al₂O₉, J(R) = R₄Si₂N₂O₇] formation and their equilibrium with RSO (R₄Si₂O₁₀). Phase relations between RAM, J(R) and RSO at 1700 °C were summarized in a phase diagram. It was determined that a limited solid solution of RAM and RSO could be formed along RAM-RSO tie-line, while RAM and J(R) form a continuous solid solution along RAM-J(R) tie-line. In RAM-J(R)-RSO ternary systems, the RAM-J(R) tie-lines were extended towards the RSO corner to form a continuous solid solution area of JRAMss (R = Y, Gd, Yb). The established phase relations in the Si–Al-R-O-N (R = Y, Gd, Yb) systems may facilitate compositional selections for developing JRAMss as monolithic ceramics or for SiC/Si₃N₄ based composites using the solid-solutions as a second refractory phase.     

Blends of Bio-Based Poly(Limonene Carbonate) with Commodity Polymers

In this study, blends of the bio-based poly(limonene carbonate) (PLimC) with different commodity polymers are investigated in order to explore the potential of PLimC toward generating more sustainable polymer materials by reducing the amount of petro- or food-based polymers. PLimC is employed as minority component in the blends. Next to the morphology and thermal properties of the blends the impact of PLimC on the mechanical properties of the matrix polymers is studied. The interplay of incompatibility and zero-shear melt viscosity contrast determines the blend morphology, leading for all blends to a dispersed droplet morphology for PLimC. Blends with polymers of similar structure to PLimC (i.e., aliphatic/aromatic polyester) show the best performance with respect to mechanical properties, whereas blends with polystyrene or poly(methyl methacrylate) are too brittle and polyamide 12 blends show very low elongations at break. In blends with Ecoflex (poly(butylene adipate-co-terephthalate)) and Arnitel EM400 (copoly(ether ester)) with poly(butylene terephthalate) hard and polytetrahydrofuran soft segments) a threefold increase in E-modulus can be achieved, while keeping the elongation at break at reasonable high values of ≈200%, making these blends highly interesting for applications.     

Cytotoxic Potential of a-Azepano- and 3-Amino-3,4-SeCo-Triterpenoids

Semi-synthetic triterpenoids, holding an amino substituted seven-membered A-ring (azepano-ring), which could be synthesized from triterpenic oximes through a Beckmann type rearrangement followed by a reduction of lactame fragment, are considered to be novel promising agents exhibiting anti-microbial, alpha-glucosidase, and butyrylcholinesterase inhibitory activities. In this study, in an attempt to develop new antitumor candidates, a series of A-ring azepano- and 3-amino-3,4-seco-derivatives of betulin, oleanolic, ursolic, and glycyrrhetinic acids were evaluated for their cytotoxic activity against five human cancer cell lines and non-malignant mouse fibroblasts by means of a colorimetric sulforhodamine assay. Azepanoallobetulinic acid amide derivative 11 was the most cytotoxic compound of this series but showed little selectivity between the different human tumor cell lines. Flow cytometry experiments showed compound 11 to act mainly by apoptosis (44.3%) and late apoptosis (21.4%). The compounds were further screened at the National Cancer Institute towards a panel of 60 cancer cell lines. It was found that compounds 3, 4, 7, 8, 9, 11, 15, 16, 19, and 20 showed growth inhibitory (GI₅₀) against the most sensitive cell lines at submicromolar concentrations (0.20–0.94 μM), and their cytotoxic activity (LC₅₀) was also high (1–6 μM). Derivatives 3, 8, 11, 15, and 16 demonstrated a certain selectivity profile at GI₅₀ level from 5.16 to 9.56 towards K-562, CCRF-CEM, HL-60(TB), and RPMI-8226 (Leukemia), HT29 (Colon cancer), and OVCAR-4 (Ovarian cancer) cell lines. Selectivity indexes of azepanoerythrodiol 3 at TGI level ranged from 5.93 (CNS cancer cell lines SF-539, SNB-19 and SNB-75) to 14.89 for HCT-116 (colon cancer) with SI 9.56 at GI₅₀ level for the leukemia cell line K-562. The present study highlighted the importance of A-azepano-ring in the triterpenic core for the development of novel antitumor agents, and a future aim to increase the selectivity profile will thus lie in the area of modifications of azepano-triterpenic acids at their carboxyl group.     

药物相互作用研究在新药研发和审评决策中的应用

药物相互作用改变了剂量效应关系，可能会降低疗效或增加毒性，是临床应用中合并用药治疗时重要的考虑因素。预测具有临床意义的药物相互作用是药物研发过程中获益风险评估的重要环节。本文概述了药物研发过程中药物相互作用研究的目的和意义，体内和体外研究的主要内容；梳理分析了2020年国家药品监督管理局（National Medical Products Administration, NMPA）和美国食品药品监督管理局（Food and Drug Administration, FDA）批准上市的新药药物相互作用研究情况，旨在为我国药物研发过程中药物相互作用研究及其监管审评提供参考。     

Single-Cell Microgels for Diagnostics and Therapeutics

Cell encapsulation within hydrogel droplets is transforming what is feasible in multiple fields of biomedical science such as tissue engineering and regenerative medicine, in vitro modeling, and cell-based therapies. Recent advances have allowed researchers to miniaturize material encapsulation complexes down to single-cell scales, where each complex, termed a single-cell microgel, contains only one cell surrounded by a hydrogel matrix while remaining <100 μm in size. With this achievement, studies requiring single-cell resolution are now possible, similar to those done using liquid droplet encapsulation. Of particular note, applications involving long-term in vitro cultures, modular bioinks, high-throughput screenings, and formation of 3D cellular microenvironments can be tuned independently to suit the needs of individual cells and experimental goals. In this progress report, an overview of established materials and techniques used to fabricate single-cell microgels, as well as insight into potential alternatives is provided. This focused review is concluded by discussing applications that have already benefited from single-cell microgel technologies, as well as prospective applications on the cusp of achieving important new capabilities.     

Modeling Sialidosis with Neural Precursor Cells Derived from Patient-Derived Induced Pluripotent Stem Cells

Sialidosis, caused by a genetic deficiency of the lysosomal sialidase gene (NEU1), is a systemic disease involving various tissues and organs, including the nervous system. Understanding the neurological dysfunction and pathology associated with sialidosis remains a challenge, partially due to the lack of a human model system. In this study, we have generated two types of induced pluripotent stem cells (iPSCs) with sialidosis-specific NEU1^G227R and NEU1^V275A/R347Q mutations (sialidosis-iPSCs), and further differentiated them into neural precursor cells (iNPCs). Characterization of NEU1^G227R- and NEU1^V275A/R347Q- mutated iNPCs derived from sialidosis-iPSCs (sialidosis-iNPCs) validated that sialidosis-iNPCs faithfully recapitulate key disease-specific phenotypes, including reduced NEU1 activity and impaired lysosomal and autophagic function. In particular, these cells showed defective differentiation into oligodendrocytes and astrocytes, while their neuronal differentiation was not notably affected. Importantly, we found that the phenotypic defects of sialidosis-iNPCs, such as impaired differentiation capacity, could be effectively rescued by the induction of autophagy with rapamycin. Our results demonstrate the first use of a sialidosis-iNPC model with NEU1^G227R- and NEU1^V275A/R347Q- mutation(s) to study the neurological defects of sialidosis, particularly those related to a defective autophagy–lysosome pathway, and may help accelerate the development of new drugs and therapeutics to combat sialidosis and other LSDs.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.