Wenzhou University

Growth factors (GFs), as key molecules regulating cellular processes, demonstrate therapeutic potential in fields such as regenerative medicine, oncology, and metabolic regulation. However, inherent pharmacokinetic limitations, off-target effects, and safety concerns significantly hinder clinical translation. Although in-depth studies on mechanisms of action, smart delivery systems, and regulatory networks have improved GFs' stability, targeting, and safety - leading to clinical approvals of some related drugs - high costs, complex large-scale production processes, and the intricacy of the in vivo microenvironment continue to restrict the scope and breadth of GFs' clinical translation.

This review systematically examines the classification and fundamental research progress of GFs, emphasizing their current applications in neurodegenerative diseases, bone regeneration, and metabolic disorders. It thoroughly analyzes major challenges in clinical translation, including suboptimal pharmacokinetic properties, difficulties in precise delivery, potential side effects, and high industrial production costs. To address these bottlenecks, the paper summarizes corresponding solutions, such as structural optimization through protein engineering and chemical modification, development of smart responsive delivery systems (e.g. extracellular vesicle-based platforms), and utilization of multi-factor sequential release technologies to mimic physiological repair processes.

By synthesizing current advances and existing constraints, this study aims to provide a comprehensive roadmap and technical reference for accelerating the development of next-generation GF therapies. Future research should focus on developing scalable delivery platforms, reducing production costs through synthetic biology, and strengthening biomarker-based translational studies. Multidisciplinary integration holds promise for advancing GFs therapies towards greater precision, safety, and efficacy, positioning them as core therapeutic tools in the era of precision medicine for addressing degenerative diseases, tissue damage, and metabolic disorders.

The oxygen reduction reaction (ORR) plays a central role in determining the efficiency and durability of a broad range of electrochemical energy conversion technologies, while its intrinsically slow kinetics and multistep reaction nature remain key challenges. Transition metal-based heterogeneous electrocatalysts, particularly those incorporating Fe, Mn, Co, Ni, and Cu, have been extensively investigated as ORR active systems owing to their earth abundance, diverse coordination environments, and tunable electronic structures. Recent studies show that ORR on these catalysts can diverge into two-electron and four-electron pathways from a common O 2 reactant, with pathway selectivity governed by atomic-scale coordination and electronic effects. This review summarizes current understanding of ORR mechanisms on transition metal-based catalysts, with a focus on how atomic-scale structural features are related to reaction activity, selectivity, and stability under different electrolyte conditions. Representative applications in metal–air batteries, fuel cells, and electrochemical hydrogen peroxide production are also discussed to illustrate how mechanistic insights are reflected in practical electrochemical systems. By distilling shared mechanistic features across different systems, this review provides a coherent framework for understanding and guiding ORR catalyst design.

Electrocatalytic nitrate-to-ammonia conversion offers dual environmental and sustainable synthesis benefits, but achieving high efficiency with low-cost catalysts remains a major challenge. This review focuses on cobalt-based electrocatalysts, emphasizing their structural engineering for enhanced the performance of electrocatalytic nitrate reduction reaction (NO3RR) through dimensional control, compositional tuning, and coordination microenvironment modulation. Notably, by critically analyzing metallic cobalt, cobalt alloys, cobalt compounds, cobalt single atom and molecular catalyst configurations, we firstly establish correlations between atomic-scale structural features and catalytic performance in a coordination environment perspective for NO3RR, including the dynamic reconstruction during operation and its impact on active site. Synergizing experimental breakthroughs with computational modeling, we decode mechanisms underlying competitive hydrogen evolution suppression, intermediate adsorption-energy optimization, and durability enhancement in complex aqueous environments. The development of cobalt-based catalysts was summarized and prospected, and the emerging opportunities of machine learning in accelerating the research and development of high-performance catalysts and the configuration of series reactors for scalable nitrate-to-ammonia systems were also introduced. Bridging surface science and applications, it outlines a framework for designing multifunctional electrocatalysts to restore nitrogen cycle balance sustainably.