Milk and dairy foods are naturally rich sources of a wide range of nutrients, and when consumed according to recommended intakes, contribute essential nutrients across all stages of the life cycle. Seminal studies recommendations with respect to intake of saturated fat have been consistent and clear: limit total fat intake to 30% or less of total dietary energy, with a specific recommendation for intake of saturated fat to less than 10% of total dietary energy. However, recent work has re-opened the debate on intake of saturated fat in particular, with suggestions that recommended intakes be considered not at a total fat intake within the diet, but at a food-specific level. A large body of evidence exists examining the impact of dairy consumption on markers of metabolic health, both at a total-dairy-intake level and also at a food-item level, with mixed findings to date. However the evidence suggests that the impact of saturated fat intake on health differs both across food groups and even between foods within the same food group such as dairy. The range of nutrients and bioactive components in milk and dairy foods are found in different levels and are housed within very different food structures. The interaction of the overall food structure and the nutrients describes the concept of the ‘food matrix effect’ which has been well-documented for dairy foods. Studies show that nutrients from different dairy food sources can have different effects on health and for this reason, they should be considered individually rather than grouped as a single food category in epidemiological research. This narrative review examines the current evidence, mainly from randomised controlled trials and meta-analyses, with respect to dairy, milk, yoghurt and cheese on aspects of metabolic health, and summarises some of the potential mechanisms for these findings.

Milk and dairy foods are naturally rich sources of a wide range of nutrients, and when consumed according to recommended intakes contribute essential nutrients across all stages of the life cycle. Since then, seminal studies recommendations with respect to intake of saturated fat have been consistent and clear; limit total fat intake to 30% or less total dietary energy, with a specific recommendation for intake of saturated fat to less than 10% of total dietary energy. However, recent work has re-opened the debate on intake of saturated fat in particular, with suggestions that recommended intakes be considered not at a total fat intake within the diet, but at a food specific level. A large body of evidence exists examining the impact of dairy consumption on markers of metabolic health, both at a total dairy intake and also at a food level, with mixed findings to date, but suggests that the impact of saturated fat intake on health differs both across food groups and even between foods within the same good group such as dairy. Milk and dairy foods contain a range of nutrients and bioactive components in different levels, housed within very different food structures. The interaction of the overall food structure and the nutrients describes the concept of the ‘food matrix effect’ which has been well documented for dairy foods. Studies show that nutrients from different dairy food sources can have different effects on health and for this reason, they should be considered individually rather than grouped as a single food category in epidemiological research. This review examines the current evidence from randomised controlled trials and meta-analyses, with respect to dairy, milk, yoghurt and cheese on aspects of metabolic health, and summarises some of the potential mechanisms for these findings.

β-hemoglobin disorders, such as β-thalassemia and sickle cell anemia are among the most prevalent inherited genetic disorders worldwide. These disorders are caused by mutations in the gene encoding hemoglobin-β (HBB), a vital protein found in red blood cells (RBCs) that carries oxygen from lungs to all parts of the human body. As a consequence, there has been an enduring interest in this field in formulating therapeutic strategies for the treatment of these diseases. Currently, there is no cure available for hemoglobin disorders, although, some patients have been treated with bone marrow transplantation, whose scope is limited because of the difficulty in finding a histocompatible donor and also due to transplant-associated clinical complications that can arise during the treatment. On account of these constraints, reactivation of fetal hemoglobin (HbF) synthesis holds immense promise and is a viable strategy to alleviate the symptoms of β-hemoglobin disorders. Development of new genomic tools has led to the identification of important natural genetic modifiers of hemoglobin switching which include BCL11A, KLF1, HBSIL-MYB, LRF, LSD1, LDB1, histone deacetylases 1 and 2 (HDAC1 and HDAC2). miRNAs are also promising therapeutic targets for development of more effective strategies for the induction of HbF production. Many new small molecule pharmacological inducers of HbF production are already under pre-clinical and clinical development. Furthermore, recent advancements in gene and cell therapy includes targeted genome editing and iPS cell technologies, both of which utilizes a patient's own cells, are emerging as extremely promising approaches for significantly reducing the burden of β-hemoglobin disorders.

Disease-specific human induced pluripotent stem cells (hiPSCs) can be generated directly from individuals with known disease characteristics or alternatively be modified using genome editing approaches to introduce disease causing genetic mutations to study the biological response of those mutations. The genome editing procedure in hiPSCs is still inefficient, particularly when it comes to homology directed repair (HDR) of genetic mutations or targeted transgene insertion in the genome and single cell cloning of edited cells. In addition, genome editing processes also involve additional cellular stresses such as trouble with cell viability and genetic stability of hiPSCs. Therefore, efficient workflows are desired to increase genome editing application to hiPSC disease models and therapeutic applications. Apart from genome editing efficiency, hiPSC survival following single-cell cloning has proved to be challenging and has thus restricted the capability to easily isolate homogeneous clones from edited hiPSCs. To this end, we demonstrate an efficient workflow for feeder-free single cell clone generation and expansion in both CRISPR-mediated knock-out (KO) and knock-in (KI) hiPSC lines. Using StemFlex medium and CloneR supplement in conjunction with Matrigel cell culture matrix, we show that cell viability and expansion during single-cell cloning in edited and unedited cells is significantly enhanced. Our reliable single-cell cloning and expansion workflow did not affect the biology of the hiPSCs as the cells retained their growth and morphology, expression of various pluripotency markers and normal karyotype. This simplified and efficient workflow will allow for a new level of sophistication in generating hiPSC-based disease models to promote rapid advancement in basic research and also the development of novel cellular therapeutics.

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Elevated intakes of saturated fatty acids (SFA) can adversely affect serum cholesterol levels. Dairy fat contains ~60% SFA, prompting healthy eating guidelines to recommend low-fat dairy. Physiological, and environmental factors influence inter-individual variance in response to food consumption. Evidence exploring the dairy matrix has differing effects of dairy fat consumption on serum cholesterol levels when consumed in the form of cheese. The extent of this variability and determinants of response to dairy fat are currently unknown. The objective of this study was to determine factors associated with lipid metabolism response to a dairy fat intervention, with a focus on serum cholesterol. A 6-week randomized parallel intervention trial was carried out in healthy volunteers (≥50 years, BMI ≥25 kg/m2). Participants (n = 104) consumed ~40 g dairy fat daily in addition to their usual diet, in 1 of 3 forms: butter, cheese, or reduced-fat cheese and butter. For this analysis, “response” was based on the percentage (%) change in serum total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) from pre- to post-intervention. Participants were divided into tertiles for each lipid response. The upper and lower tertiles were used to categorize participants as “responders” and “non-responders.” For TC and LDL-c, response was classified as a decrease, whereas “response” was defined as an increase for HDL-c. Clinical response was also considered, by calculating pre- and post-intervention prevalence of those meeting target levels of cholesterol recommendations. Participants demonstrating the largest % decrease (Tertile 1; “responders”) in TC had significantly higher levels of TC and HDL-c, at baseline, and lower levels of triglycerides (TAGs) compared to those in tertile 3 (i.e., TC non-responders). Those with the largest % decrease in LDL-c (Tertile 1: LDL-c responders) had higher baseline levels of LDL-c and lower levels of TAGs. Multiple regression analysis revealed that the % change in TC and LDL-c was associated with baseline TC, TAG, body weight and high-sensitivity C-reactive protein (hsCRP; P < 0.05). Previous work has demonstrated the dairy food matrix affects lipid response to dairy consumption. This study suggests that phenotypic differences may also influence response to dairy fat in overweight individuals.

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