Two-dimensional (2D) core–shell nanoparticles have been attracting increasing interest due to their wide applications in materials science. Living crystallization-driven self-assembly (CDSA) is an ambient temperature, seeded growth method of crystallizable block copolymers (BCPs) in selective solvents, which has been demonstrated to be a powerful tool for the creation of one-dimensional (1D)/2D nanomaterials with precise control over size and compositions. Nevertheless, the development of an efficient living CDSA approach is a challenge for the case of semicrystalline poly(p-dioxanone) (PPDO) as a core-forming block, where the dimensional control is poor. Herein, we demonstrate that the insufficient size control of 2D PPDO platelets could be overcome through modulation of solvent compositions or elevating the crystallization temperatures for PPDO. The possible mechanism involves an improved unimer solubility that avoids fast unimer aggregation. As a result, uniform 2D platelet micelles with a controlled area over a substantial size range are created via epitaxial growth of the unimer. It is noteworthy that the shape control of 2D platelet micelles from quasi-square to elongated hexagon to lozenge shapes can be accessible by regulating the crystallization conditions such as adding different amounts of cosolvents or crystallization at an elevated temperature. Meanwhile, spatially defined block comicelles can be achieved via the seeded growth approach from PPDO core-forming BCPs with different corona functionalities at elevated temperatures. The excellent water stability and biocompatibility properties of 2D PPDO platelet micelles further enable them to have a potential application as cargo vehicles in the drug delivery field.
Two-dimensional, size-tunable, water-dispersible particle micelles with spatially defined chemistries can be obtained by using “living” crystallization-driven self-assembly (CDSA) approach. Nevertheless, a major obstacle of crystalline particles in drug delivery application is the difficulty in accessing to cargo within crystalline cores. In the present work, we design four different types of biocompatible two-dimensional platelets with a crystalline poly(ε-caprolactone) (PCL) core, a hydrophobic poly(4-vinylprydine) (P4VP) segment, and a water dispersible poly(N,N-dimethyl acrylamide) (PDMA) block in ethanol by seeded growth method. Transferring those uniform platelets with tailored compositions to an aqueous solution in the presence of a hydrophobic drug leads to efficient encapsulation of the cargo in the P4VP segments via hydrophobic interactions. These drug-loaded platelets exhibit pH-responsive release behavior in aqueous media due to the protonated–deprotonated process of P4VP blocks in acidic and neutral solutions. This work provides initial insight into biocompatible PCL platelets with low dispersity and precise chemistry control in stimulus-responsive drug delivery fields.
Seeded growth is generally regarded as an ambient-temperature, living crystallization-driven self-assembly (CDSA) approach of block copolymers (BCPs) with crystallizable cores, which is a powerful method in preparing one-dimensional (1D) or twodimensional (2D) polymer nanomaterials with precise control over size and compositions. Generally, crystallographic matching is considered as a fundamental principle that determines the happening of epitaxial growth. However, crystallization temperature also plays a vital role in governing the seeded growth behavior, which is usually ignored in previous studies. Herein, the effect of crystallization temperatures on seeded epitaxial growth of different crystallizable polymer blends involving a homopolymer and a corresponding BCP is extensively explored. It has been shown that crystallographic matching is essentially required but not sufficient for successful epitaxial growth. Crystallization-temperature-dependent seeded growth demonstrates that the critical size of nuclei generated from a crystalline substrate dominates the occurrence of epitaxial growth. A smaller thickness of deposited crystals than that of the crystalline substrate is required for the happening of epitaxial growth. This important finding provides a theoretical basis for the design of complex polymer nanoparticles with distinct core compositions from an alternative view of crystallization temperatures using the CDSA approach.
Cuproptosis is a newly defined programmed cell death pattern and is believed to play an important role in tumorigenesis and progression. In addition, many studies have shown that glycosylation modification is of vital importance in tumor progression. However, it remains unclear whether glycosyltransferases, the most critical enzymes involved in glycosylation modification, are associated with cuproptosis. In this study, we used bioinformatic methods to construct a signature of cuproptosis-related glycosyltransferases to predict the prognosis of colon adenocarcinoma patients. We found that cuproptosis was highly correlated with four glycosyltransferases in COAD, and our model predicted the prognosis of COAD patients. Further analysis of related functions revealed the possibility that cuproptosis-related glycosyltransferase Exostosin-like 2 (EXTL2) participated in tumor immunity.
The quality attributes of software architecture (SA) determine whether SA can be easily understood, tested, modified and so on, so quality-driven architecture evolution is important for keeping the viability and competitiveness. SA evolution is a process, and it contains multiple steps, such as SA quality measurement, SA modification, code co-evolution and so on. In order to guarantee that the software can be continuously improved and iteratively evolved in the future, we need to focus on all steps. However, most existing approaches only focus on one aspect, so they did not pay attention to how to finish the evolution process. In this paper, we propose a quality-driven iterative evolution approach for SA. This approach focuses on the whole process. In the first step, we use a quantitative approach to measure the architecture quality. Then, we construct the conflict graph to detect conflicts between evolution requirements to generate the final evolution scheme. In the third step, we modify architecture based on the evolution scheme. Finally, we co-evolve file dependency graph (FDG) based on the modified architecture. By focusing on the above steps, our approach can support a complete quality-driven architecture evolution process and obtain the maximum benefit in terms of the combined SA quality. We conduct our experiments with four open source projects, the experimental results indicate that our approach can improve SA quality, and our approach can effectively co-evolve the FDG to lay the foundation for the next evolution.
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