Colorectal cancer (CRC) is the third most prevalent cancer and the second most deadly cancer in the world, and current treatments have significant side effects and drug resistance. Citrus plants contain flavonoids glycosides, such as neohesperidin, which has antioxidant, anti-inflammatory, immunomodulatory and antitumor properties, making it a promising CRC adjuvant. However, conventional extraction is limited by low natural abundance, poor consistency and low bioavailability. In this study, E. coli BL21(DE3) were engineered to produce neohesperidin de novo from naringenin by two integrated modules that convert naringenin to hesperetin and then to neohesperidin. The neohesperidin yield reached 4.55 mg/L using naringenin as the substrate. These findings provide a precision, scalable platform for adjuvant CRC therapy.

In recent years, aging and anti-aging have become a very common problem among some middle-aged people. Biologists have discovered that telomeres play a crucial part in our aging process because they can prevent genes on chromosomes from being lost. Moreover, some diseases are also associated with telomere length. Around 85% of malignant cells reactivate telomerase, enabling infinite cell division and continuous growth. Additionally, a variety of environmental factors, such as smoking and genetic factors, can influence telomere length. These make it worthwhile to investigate the subject. The primary research question of this project is how telomere length is related to aging and some related diseases, and what factors influence it. To address this question, this research adopts literature review, data comparisons, theoretical research. Besides, this research collects and analyzes academic sources, official data, and authoritative studies. Key findings indicate that telomere length has a significant relationship with genetic and environmental factors. Some studies also show that telomere length can increase in those who have healthy lifestyles. Furthermore, the telomere length is also associated with diseases related to some organelles. As people's ages increase, the telomere length will decrease because telomere length will be shortened at each cell division. Overall, this project clarifies the connection between telomere length and the aging process as well as several ways to shorten telomeres. However, there are also several limitations, such as limited area coverage and tiny sample sizes. Therefore, more research should be conducted and thoroughly investigated.

Hydrogels are functional polymeric materials with a three-dimensional network hydrophilic structure. Benefiting from excellent biocompatibility, high water retention, and tunable physicochemical properties, they have become a research hotspot in food, biomedicine, and other fields. This paper systematically reviews the preparation techniques, characterization systems, and diverse applications of natural polymer-based hydrogels. It combs through the principles, advantages, and application limitations of five mainstream preparation methods—thermal induction, physical crosslinking, chemical crosslinking, ionic crosslinking, and enzymatic crosslinking—and clarifies the regulatory mechanisms by which different crosslinking modes affect the microstructure and macroscopic properties of hydrogels. Meanwhile, from the three dimensions of structure, properties, and function, this paper comprehensively presents core characterization techniques such as SEM, FT-IR, XRD, and rheological testing, and elucidates the intrinsic correlations among the microstructure, physicochemical properties, and practical functions of hydrogels. On this basis, it summarizes the core application scenarios and technical advantages of hydrogels in food texture modification, bioactive substance delivery, smart packaging, food 3D printing, and biomedicine.

The entry of artificial intelligence (AI) into biomedical engineering (BME) is not merely the addition of a new research method; rather, it is triggering a systemic transformation of the discipline's research paradigm. Problem formulation is shifting from "hypothesis-driven" to "data discovery coupled with hypotheses"; experimental design is moving from "decomposing systems into isolated components" to "multiscale integrated modeling"; and evaluation criteria are evolving from "causal mechanism first" to "predictive performance combined with interpretability." This paper first defines five characteristics of the traditional BME paradigm, then reviews its three developmental stages. Through the four domains of medical imaging, brain-computer interfaces (BCI), biomaterials, and molecular pharmaceuticals, it illustrates the concrete changes brought by AI and the problems that remain unresolved. It identifies the core tension of the data-driven paradigm as "prediction relies on correlation, whereas explanation relies on causality," and accordingly organizes the challenges into four layers: algorithmic, engineering, privacy, and ethical. This paper devotes a separate section to the ethical responsibility of medical AI and the progress of domestic and international regulation. This review finds that the AI-triggered paradigm shift is partial and incomplete, its fundamental tension being strong correlative prediction but weak causal mechanisms; this conclusion can serve as a reference for researchers in handling the relationship between data-driven modeling and causal explanation.