It is concluded that bridging the gap between foundational CRISPR research and its real-world applications is imperative and future efforts should focus on democratizing tools via open-source platforms, advancing delivery systems, and fostering sustainable innovation through synthetic biology integration to fully realize the transformative potential of genome editing in organisms beyond model organisms.
It is argued that formation of a tumour-intrinsic niche is a prerequisite for BRAF-mutant CRC seeding to distant organs and that interference with niche formation may help avoid metastatic relapse.
The future of crop improvement using GEd technologies lies in the harmonisation or alignment of global policies and regulations to support the trade of agricultural produce and ensure that growers and consumers can benefit from GEd technology.
The landmark derivation of induced pluripotent stem cells (iPSCs) sparked an enormous range of research on development of diverse cell populations. Perhaps no aspect of this work has been as productive as studies on blood and immune cell production. Indeed, essentially all human blood cell populations can be derived from human iPSCs. While derivation of transplantable hematopoietic stem cells (HSCs) from iPSCs has been relatively challenging, clinical translation of iPSC-derived immune cells has been particularly productive. Notably, more patients have been treated with iPSC-derived natural killer (NK) cells than any other iPSC-derived cell type. Use of iPSCs provides a key platform to incorporate multiplexed gene edits before differentiation, enabling NK cells to be engineered with tumor-targeting CARs, cytokine support for improved persistence, enhanced tumor trafficking, and resistance to host immune rejection, modifications uniformly expressed across the entire cellular product. While T cells, macrophages and other immune cells can be produced from human iPSCs, iPSC-derived NK cells have been the most widely used in clinical trials for treatment of refractory malignancies, as well as autoimmune disease. This review summarizes research with a focus on clinical translation of iPSC-derived immune cells, as well as highlights continued challenges and prospects of this field.
Soybean β-conglycinin (7S) and glycinin (11S) differ markedly in their structure, physicochemical properties, and bioactivity; however, industrial practice still treats them as a mixed ingredient, obscuring their differentiated functional potential. This review critically evaluates fractionation technologies through the lens of the "purity-yield-sustainability" trilemma. First-generation chemical precipitation methods achieve high purity at the laboratory scale but suffer from heavy reagent use, environmental burden, and poor scalability. Second-generation green and physical techniques, such as phytase-assisted, membrane-based, and field-assisted separation, improve sustainability but face challenges in fouling control, process stability, and scale-up. Third-generation upstream strategies, including breeding and gene editing, fundamentally alter the 7S/11S ratio at the source, potentially bypassing downstream tradeoffs. Functionally, 7S globulin excels in regulating lipid metabolism and reducing obesity and non-alcoholic fatty liver disease, whereas 11S globulin shows advantages in blood pressure regulation and cardiovascular protection. Structurally, 7S exhibits favorable emulsification and foaming capacities, whereas 11S dominates gel network formation, supporting diverse applications from plant-based foods to nanocarriers and biodegradable films. Future breakthroughs lie in AI-guided hybrid separation systems, data-driven process optimization, and direct linking of fractionation outcomes to end-use functionality. Moving beyond mixed utilization toward precision deployment, soybean 7S and 11S globulins can evolve from bulk commodities into high-value resources for sustainable food systems and precision health applications.
Generative AI
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
General Science
