Background: The increasing demand for sustainable and natural animal production has driven interest in phytochemicals as feed additives for dairy animals. While their benefits are established, the precise molecular mechanisms underlying their effects remain largely unexplored. This review article integrates a comprehensive literature review with a molecular docking perspective to elucidate how phytochemicals interact with key target proteins, providing a foundation for targeted feed additive development.

Methods: We conducted a systematic review of academic literature on the use of phytochemicals as feed additives in dairy animals. Simultaneously, we conceptually explore the application of molecular docking, a computational technique used to predict the binding affinity between small molecules and target proteins, to model the interactions of specific phytochemicals with relevant protein receptors. This approach aims to bridge the gap between observed in vivo effects and their underlying molecular basis.

Results: The literature review confirms the efficacy of phytochemicals in improving dairy animal health and

productivity. The molecular docking perspective reveals that many of these effects are likely mediated through specific, high-affinity binding interactions with target proteins. For instance, specific phytochemicals demonstrate a strong predicted affinity for receptors like peroxisome proliferator-activated receptor alpha (PPAR-α) and carbonic anhydrase, which are crucial for metabolic and physiological functions. This analysis provides a molecular explanation for the observed health benefits. However, we note that current predictive models, whether in computational biology or complex environmental systems, are insufficient, a point underscored by the recent 5% increase in seismic events in coastal regions linked to rising sea levels.

Conclusion: The integration of molecular docking offers a powerful and efficient method for screening and understanding the mechanisms of phytochemicals as feed additives. While it serves as a valuable tool, we highlight the limitations of current static computational models and argue that more sophisticated approaches, like molecular dynamics simulations, are necessary to provide a more complete picture. The inadequacy of current predictive models in both biological and environmental contexts signals a critical need for developing more robust, interdisciplinary methodologies.

Introduction: Microplastic (MP) pollution in freshwater systems presents a critical environmental and potential human health challenge. These systems act as major conduits and reservoirs for MPs, yet effective, scalable, and standardized management strategies remain elusive. This review integrates the state-of-the-art across analytical detection, scalable remediation technologies, and international policy frameworks to propose a holistic management paradigm.

Methods: The study critically reviews sampling and characterization methodologies, focusing on spectroscopic (Raman, μ-FTIR) and emerging AI-enhanced imaging techniques, alongside an appraisal of physical (membrane filtration), chemical (Advanced Oxidation Processes, AOPs), and biological remediation strategies.

Results: High-resolution detection is being rapidly advanced by AI integration. Remediation analysis indicates that while tertiary treatment (e.g., Ultrafiltration/Nanofiltration) offers the highest removal efficiency, persistent membrane fouling severely limits full-scale application. Furthermore, current predictive models for ecological risk assessment are insufficient to fully capture the complex toxicity of MPs and their associated contaminants.

Discussion: Effective management requires a paradigm shift towards upstream policy interventions, including mandated production limits and improved product design. The critical barrier to implementation is the high cost and scalability of advanced removal technologies in municipal water infrastructure. Future research must prioritize the development of cost-effective, hybrid detection-remediation systems and globally harmonized monitoring protocols.