ABSTRACT
Our diets greatly influence our health. Multiple lines of research highlight the beneficial properties of eating berries and fruits. In this study, a berry mixture of Nordic berries previously identified as having the potential to improve memory was supplemented to young C57Bl/6J male mice to investigate effects on cognition function, metabolic health, markers of neuroinflammation, and gut microbiota composition. C57Bl/6J male mice at the age of 8 weeks were given standard chow, a high-fat diet (HF, 60%E fat), or a high-fat diet supplemented with freeze-dried powder (20% dwb) of a mixture of Nordic berries and red grape juice (HF + Berry) for 18 weeks (n = 12 animals/diet group). The results show that supplementation with the berry mixture may have beneficial effects on spatial memory, as seen by enhanced performance in the T-maze and Barnes maze compared to the mice receiving the high-fat diet without berries. Additionally, berry intake may aid in counteracting high-fat diet induced weight gain and could influence neuroinflammatory status as suggested by the increased levels of the inflammation modifying IL-10 cytokine in hippocampal extracts from berry supplemented mice. Furthermore, the 4.5-month feeding with diet containing berries resulted in significant changes in cecal microbiota composition. Analysis of cecal bacterial 16S rRNA revealed that the chow group had significantly higher microbial diversity, as measured by the Shannon diversity index and total operational taxonomic unit richness, than the HF group. The HF diet supplemented with berries resulted in a strong trend of higher total OTU richness and significantly increased the relative abundance of Akkermansia muciniphila, which has been linked to protective effects on cognitive decline. In conclusion, the results of this study suggest that intake of a Nordic berry mixture is a valuable strategy for maintaining and improving cognitive function, to be further evaluated in clinical trials.
ABSTRACT
It is well-known that an ideal extraction method enabling quantitative analysis should give complete extraction of the target analytes as well as minimal co-extraction of unwanted matrix substances. If the extraction method is part of a nontarget screening protocol, the desired analytes can differ widely in terms of chemical properties. In chromatography, terminologies such as recovery, selectivity, and comprehensiveness are well-established and can easily be determined. However, in extraction, these concepts are much less developed. Hence, the aim of our research is to develop and scrutinize theory in extraction with respect to numerical descriptors for extractability, selectivity, and comprehensiveness. Our approach is based on experiments determining the extractability of target analytes and selected interferences. As a case study, we use a pooled sample of three species of seaweed (Alaria esculenta, Laminaria digitata and Ascophyllum nodosum). Target analytes are ß-carotene, fucoxanthin, δ-tocopherol, and phloroglucinol; and selected interferences are carbohydrates, proteins, ash, arsenic, and chlorophyll a. As a "green and clean" extraction technique, supercritical fluid extraction (SFE) using mixtures of CO2, ethanol and water were explored using a design of experiment. The temperature was varied between 40-80°C, and the pressure was held constant at 300 bar. Obtained results clearly demonstrate that highest relative selectivity was achieved with CO2 containing only 5 vol% of ethanol and no water, which primarily enabled high extractability of ß-carotene, and yielding an extract free of carbohydrates, proteins, and toxic metals such as arsenic. Best methods for highest extractability of the other target analytes varied quite widely. Analytes requiring the highest water content (fucoxanthin and phloroglucinol), also resulted in the lowest relative selectivity. Maximum relative comprehensiveness was achieved using CO2/ethanol/water (40/55/5, v/v/v) at 70°C and 300 bar. Our study demonstrates the feasibility of using relative quantitative descriptors for extractability, selectivity, and comprehensiveness, in optimization strategies for analytical extractions.
