Milk has been shown to contain a specific fraction of extracellular particles that are reported to resist digestion and are purposefully packaged with lipids, proteins, and nucleic acids to exert specific biological effects. These findings suggest that these particles may have a role in the quality of infant nutrition, particularly in the early phase of life when many of the foundations of an infant’s potential for health and overall wellness are established. However, much of the current research focuses on human or cow milk only, and there is a knowledge gap in how milk from other species, which may be more commonly consumed in different regions, could also have these reported biological effects. Our review provides a summary of the studies into the extracellular particle fraction of milk from a wider range of ruminants and pseudo-ruminants, focusing on how this fraction is isolated and characterised, the stability and uptake of the fraction, and the reported biological effects of these fractions in a range of model systems. As the individual composition of milk from different species is known to differ, we propose that the extracellular particle fraction of milk from non-traditional and minority species may also have important and distinct biological properties that warrant further study.

Background: To date, anti-obesity agents based on natural products are tested for their potential using lipase inhibition assay through the interference of hydrolysis of fat by lipase resulting in reduced fat absorption without altering the central mechanisms. Previous screening study had indicated strong anti-obesity potential in Eleusine indica (E. indica), but to date, no pharmacologic studies have been reported so far. Objective: This study was performed to investigate the lipid-lowering effects of E. indica using both in vitro and in vivo models. Methods: The crude methanolic extract of E. indica was fractionated using hexane (H-Ei), dichloromethane (DCM-Ei), ethyl acetate (EA-Ei), butanol (B-Ei), and water (W-Ei). All the extracts were tested for antilipase activity using porcine pancreatic lipase. Because H-Ei showed the highest inhibition, it was further subjected to chemical profiling using high-performance liquid chromatography. Subsequently, oral toxicity analysis of H-Ei was performed [Organization for Economic Cooperation and Development guidelines using fixed dose procedure (No. 420)]; efficacy analysis was performed using high-fat diet (HFD)-induced hyperlipidemic female Sprague–Dawley rats. Results: According to the toxicity and efficacy analyses, H-Ei did not demonstrate any noticeable biochemical toxicity or physiologic abnormalities and did not cause any tissue damage as per histologic analysis. Furthermore, H-Ei significantly reduced body weight and improved serum profile and did not show hepatotoxicity and nephrotoxicity based on the serum profile. Moreover, H-Ei alleviated HFD-induced hepatosteatosis and ameliorated induced adiposity in both visceral and subcutaneous adipose tissue. Conclusion: Our results demonstrate that H-Ei effectively improved hyperlipidemia. Further studies to explore its possibility as an alternative pharmacologic agent to treat obesity are warranted. Abbreviation Used: ALT: Alanine transaminase; AST: Aspartate transaminase; B-Ei: Butanol extract of E. indica; DCM-Ei: Dichloromethane extract of E. indica; EA-Ei: Ethyl acetate extract of E. indica; GHS: Globally Harmonized System; HDL: High-density lipoprotein; H-Ei: Hexane extract of E. indica; HFD: High-fat diet; HPLC: High-performance liquid chromatography; LDL: Low-density lipoprotein; NFD: Normal fed diet; PPL: Porcine pancreatic lipase; SEM: Standard error of mean; SD: Standard deviation; TC: Total cholesterol; TG: Triglycerides; W-Ei: Water extract of E. indica.

Eleusine indica (Linnaeus) Gaertner is a traditional herb known to be depurative, febrifuge, and diuretic and has been reported with the highest inhibitory activity against porcine pancreatic lipase (PPL) among thirty two plants screened in an earlier study. This study aims to isolate and identify the active components that may possess high potential as an antiobesity agent. Of the screened solvent fractions of E. indica, hexane fraction showed the highest inhibitory activity of 27.01±5.68% at 100 μg/mL. Bioactivity-guided isolation afforded three compounds from the hexane fraction of E. indica, namely, β-sitosterol, stigmasterol, and lutein. The structures of these compounds were elucidated using spectral techniques. Lutein showed an outstanding inhibitory activity against PPL (55.98±1.04%), with activity 60% higher than that of the reference drug Orlistat. The other compounds isolated and identified were β-sitosterol (2.99±0.80%) and stigmasterol (2.68±0.38%). The enzyme kinetics of E. indica crude methanolic extract on PPL showed mixed inhibition mechanism.

This study investigated whether unique spectral features from tracer compounds could be reliably detected and discriminated from the complex spectral background of biomaterial matrix. Spectroscopy combined with chemical markers present a promising solution for traceability in complex biological matrices, such as leather and other biomaterials involving intricate processing. This study explores the potential of Near InfraRed Spectroscopy (NIRS), both benchtop (350-2500 nm) and miniaturized (900-1700 nm), as a rapid, non-destructive tool for detecting molecular tracers embedded within wet-blue leather. Three candidate tracers-collagen hydrolysate, Cloisite Na⁺ (CNa), and 2-Thiocyanomethylthiobenzothiazole (TCMTB)-were tested across two experimental phases under both industrial tannery and controlled laboratory conditions. Initial analyses using Principal Component Analysis (PCA) indicated TCMTB as the most promising tracer based on spectral distinctiveness. Subsequently, advanced machine learning approaches, including Support Vector Machines (SVM) and feature selection via Genetic Algorithm (GA) coupled with Random Forest (RF), were employed to optimize classification performance and identify key wavelengths contributing to tracer detection. The results confirmed that molecular tracers exhibit identifiable and reproducible spectral signatures, though their detectability is significantly influenced by the inherent variability of the leather matrix and the side of sample scanning. The integration of chemometrics and intelligent feature selection enhances detection sensitivity, highlighting the critical role of spectral range and algorithmic robustness. This study underscores the viability of spectroscopy and machine learning as a platform technology for traceability in complex bio-derived materials, with leather serving as a representative use case.