Critical Reviews in Food Science and Nutrition

Lin, Shiyu; Teng, Xiuxiu; Shang, Xinjie; Li, Shu; Xu, Jingjing; Tang, Yao; Yang, Rui

doi: 10.1080/10408398.2026.2684773pmid: N/A

Abstract As protein supplement products continue to evolve toward premium offerings, enhancing their nutritional value based on protein characteristics has become increasingly crucial. As one of the bioactive proteins derived from milk, osteopontin (OPN) possesses outstanding multifunctionality and plays a vital role in vivo, making it a promising “golden ingredient” for protein supplement products. This review systematically summarizes the diverse sources of OPN, its structural characteristics enriched with functional domains, as well as efficient extraction and recombinant expression techniques. It further elaborates on the multifunctional roles and underlying mechanisms of action of OPN. The potential applications of OPN in the food industry are thoroughly explored, along with a discussion of current challenges and future prospects, offering valuable insights for OPN research in food and nutritional applications.

Islam, Md. Rakibul; Halim, Md. Abdul; Ahmed, Tanjim; Hasan, S. M. Kamrul

doi: 10.1080/10408398.2026.2686872pmid: N/A

Abstract Bangladesh hosts a wide variety of indigenous fruits that have long contributed to rural nutrition and health, yet they remain largely underutilized in modern agriculture and food systems. These fruits are naturally resilient to environmental stresses and well-suited to local agro-ecological conditions, making them valuable resources for enhancing food and nutrition security, especially in the face of increasing climate change pressures. Many of these fruits also have high nutritional and medicinal value, which can help address dietary nutrient deficiencies. This review highlights several promising underutilized fruits and examines their potential as future resilient foods. It explores their nutritional composition, health benefits, diversity, cultivation status, market availability, and importance within local food systems. In addition, the study considers opportunities for value-added product development and evaluates their potential contribution to food security and sustainability through SWOT analysis aligned with Sustainable Development Goal 2 (Zero Hunger). Findings indicate that many underutilized fruits in Bangladesh are rich in essential nutrients and bioactive compounds, often exceeding the nutritional quality of widely consumed commercial fruits. Species such as Karonda (Carissa carandas), Tamarind (Tamarindus indica), and Custard Apple (Annona reticulata) show strong antioxidant and therapeutic properties, emphasizing their potential for creating resilient, nutrition-focused, and sustainable food systems.

Godinho, Ana Paula Kulig; Siqueira, Ilanna Mirela Becker Jorge; Oliveira, Andrea; Almeida, Claudia Choma Bettega; Cavalcante-Silva, Regina Paula Vieira

doi: 10.1080/10408398.2026.2686347pmid: N/A

Abstract Human milk is recognized as the gold standard for infant nutrition. However, increasing environmental contamination by potentially toxic elements has raised concerns about infant exposure during lactation. This study aimed to map and synthesize current scientific evidence on factors associated with these elements in human milk. A scoping review was conducted following JBI methodology, with searches in PubMed, Scopus, Embase, BVS, and the CAPES Journals Portal. Eligible studies were original articles published between 2015 and 2025 that quantified potentially toxic elements in human milk and examined associated factors. Of the 3,151 records identified, 44 studies met the inclusion criteria, with most using cross-sectional designs and originating from Asia and Europe. ICP-MS was the most frequently employed analytical technique. Across 22 investigated elements, 11 showed associations with explanatory factors, with arsenic, cadmium, lead, and mercury most often assessed. At the individual level, element concentrations were linked to maternal diet, cosmetic use, passive smoking, and selected biological and environmental characteristics. Contextual evidence indicated higher concentrations in mining, industrialized, and coastal areas. Overall, the literature shows substantial methodological heterogeneity and limited multivariable modeling, underscoring the need for improved analytical standardization and structural actions to reduce environmental exposure sources while safeguarding breastfeeding.

Li, Hongfei; Gao, Min; Li, Yuchen; Du, Zhenjiao; Yang, Shupeng; Jia, Xiaoxue; Li, Yi

doi: 10.1080/10408398.2026.2684709pmid: N/A

Abstract Food allergies affect over 220 million individuals worldwide and present increasing challenges due to complex food matrices and processing-induced protein modifications. Conventional detection methods, including immunoassays, PCR, and mass spectrometry, provide reliable analytical tools but are often limited by matrix interference, cross-reactivity, and labor-intensive workflows. Artificial intelligence (AI) has emerged as a complementary strategy, enabling high-throughput allergen prediction and enhanced analytical signal interpretation. This review examines recent advances in AI-driven allergen research across computational prediction and analytical detection. Machine learning (ML) and deep learning (DL) models achieve predictive accuracies exceeding 90% in sequence-based allergenicity assessment, outperforming traditional similarity-based methods. In analytical systems, AI-assisted spectroscopy and imaging enable rapid detection within seconds to minutes. Despite these advances, challenges remain in dataset bias, model interpretability, and cross-domain generalization. Future work should focus on explainable AI, standardized datasets, and external validation to support reliable and deployable allergen risk management systems. The integration of AI with spectroscopy, imaging, biosensing, and mass spectrometry is also highlighted.