A moderate-carbohydrate diet with plant protein is inversely associated with cardiovascular risk factors: the Korea National Health and Nutrition Examination Survey 2013-2017.

BACKGROUND: Because a moderate-carbohydrate diet reportedly has minimal risks, the substitution of carbohydrate for protein has been emphasized. Few studies have explored the effect of moderate-carbohydrate diets with higher protein intake in Asians, who typically consume a high-carbohydrate low-fat diet. Therefore, this study evaluated the associations of moderate- versus high- carbohydrate diets with cardiovascular risk factors among Korean adults by protein source. METHODS: This study included 7965 adults (3196 men, 4769 women) aged ≥ 19 years who participated in the 2013-2017 Korea National Health and Nutrition Examination Survey. Dietary intake was assessed by a 24-h recall method and four types of diet were defined: a moderate-carbohydrate diet with plant protein (MCP) or animal protein (MCA) and a high-carbohydrate diet with plant protein (HCP) or animal protein (HCA). RESULTS: Compared with the MCP group, men in the other three groups had significantly higher odds ratios (ORs) for elevated total cholesterol, reduced high-density lipoprotein (HDL)-cholesterol, and metabolic syndrome. Among women, only the HCP group had an increased OR for reduced HDL-cholesterol, compared with the MCP group. Similar associations were observed in younger adults (19-49 years). In addition, younger adults in the MCA group exhibited higher ORs for elevated triglycerides in men and elevated total cholesterol in women, compared with those in the MCP group. CONCLUSIONS: A moderate-carbohydrate diet with a high intake of plant protein was inversely associated with cardiovascular risk factors, especially among younger Korean adults. Further intervention studies are required to confirm this relationship and develop the optimal diet for cardiovascular health in the Korean population.

Facile Synthesis of Surface-Modified Hollow-Silica (SiO2) Aerogel Particles via Oil-Water-Oil Double Emulsion Method.

Due to their high surface area and low weight, silica aerogels are ideally suited for several uses, including drug delivery, catalysis, and insulation. Oil-water-oil (OWO) double emulsion is a simple and regulated technique for encasing a volatile oil phase in a silica shell to produce hollow silica (SiO2) aerogel particles by using hydrophilic and hydrophobic emulsifiers. In this study, the oil-water-oil (OWO) double emulsion method was implemented to synthesize surface-modified hollow silica (SiO2) aerogel particles in a facile and effective way. This investigation mainly focused on the influence of the N-hexane-to-water glass (OW) ratio (r) in the first emulsion, silica (water glass) content concentration (x), and surfactant concentration (s) variations. Furthermore, surface modification techniques were utilized to customize the aerogel's characteristics. The X-ray diffraction (XRD) patterns showed no imprints of impurities except SiO2. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images highlight the hollow microstructure of silica particles. Zeta potential was used to determine particle size analysis of hollow silica aerogel particles. The oil-water-oil (OWO) double emulsion approach was successfully employed to synthesize surface-modified hollow silica (SiO2) aerogel particles, providing precise control over the particle characteristics. By the influence of the optimization condition, this approach improves the aerogel's potential applications in drug delivery, catalysis, and insulation by enabling surface modifications.

Validation Study of the Estimated Glycemic Load Model Using Commercially Available Fast Foods.

The recent popularization of low-glycemic foods has expanded interest in glycemic index (GI) not only among diabetic patients but also healthy people. The purpose of this study is to validate the estimated glycemic load model (eGL) developed in 2018. This study measured the glycemic load (GL) of 24 fast foods in the market in 20 subjects. Then, the transportability of the model was assessed, followed by an assessment of model calibration and discrimination based on model performance. The transportability assessment showed that the subjects at the time of model development are different from the subjects of this validation study. Therefore, the model can be described as transportable. As for the model's performance, the calibration assessment found an x 2 value of 11.607 and a p-value of 0.160, which indicates that the prediction model fits the observations. The discrimination assessment found a discrimination accuracy exceeding 0.5 (57.1%), which confirms that the performance and stability of the prediction model can be discriminated across all classifications. The correlation coefficient between GLs and eGLs measured from the 24 fast foods was statistically significant at 0.712 (p < 0.01), indicating a strong positive linear relationship. The explanatory powers of GL and eGL was high at 50.7%. The findings of this study suggest that this prediction model will greatly contribute to healthy food choices because it allows for predicting blood glucose responses solely based on the nutrient content labeled on the fast foods.

Development of a Prediction Model to Estimate the Glycemic Load of Ready-to-Eat Meals.

The glycemic index (GI) and glycemic load (GL) of a single food item has been used to monitor blood glucose level. However, concerns regarding the clinical relevance of the GI or GL have been raised on their applicability to a combination of several foods consumed as meal. This study aimed to investigate the glycemic response after consuming commercially purchased ready-to-eat meal and to develop the GL prediction formula using the composition of nutrients in each meal. Glycemic responses were measured in healthy adults with various mixed meals comprising approximately 25 g, 50 g, and 75 g of carbohydrates. After fasting, participants consumed test meals, and the glycemic response was measured for a subsequent 120 min. The GI and GL values for mixed meals were calculated as area under curve for each participant. For the prediction formula, 70 mixed meals were analyzed, of which the GI and GL values of 64 participants were used. The prediction formula produced was as follows: GL = 19.27 + (0.39 × available carbohydrate) - (0.21 × fat) - (0.01 × protein2) - (0.01 × fiber2). We hope that this prediction formula can be used as a useful tool to estimate the GL after consuming ready-to-eat meals.

Effect of a Nutritionally Balanced Diet Comprising Whole Grains and Vegetables Alone or in Combination with Probiotic Supplementation on the Gut Microbiota.

Dysbiosis is a microbial imbalance, which often causes diseases and can be triggered by diet. Here, we deter-mined the effect of a nutritionally balanced diet rich in vegetables and whole grains alone and/or in combination with probiotics on the gut microbiota of healthy adults. We conducted a parallel-group randomized trial enrolling 63 healthy participants who were administered either a balanced diet (B-diet group), a probiotic capsule containing Lactobacillus plantarum PMO 08 (probiotics group), or a balanced diet plus probiotic capsule (synbiotics group) once daily for 2 weeks. The gut microbiota of each participant was analyzed via 16S ribosomal RNA MiSeq-based sequencing. Gastrointestinal symptoms and defecation habits were evaluated using questionnaires. The B-diet group showed significantly reduced Firmicutes-to-Bacteroidetes ratio (P<0.05) and abundances of the genera Blautia (P<0.01), Dorea (P<0.05), and Lachnoclostridium (P<0.05). Furthermore, the abundance of Bacteroides increased (P<0.05) compared to baseline levels. In the synbiotics group, Lactobacillus abundance increased significantly (P<0.05) and defecation difficulty decreased (P<0.05), confirming a synergistic effect of combined intake. All groups showed a significant reduction in the abundance of Clostridiaceae (P<0.001) and alleviation of bloating symptoms (P<0.05). Moreover, the relative abundance of Faecalibacterium significantly increased in the probiotics group (P<0.05). Therefore, the individual or combined intake of a nutritionally balanced diet and L. plantarum PMO 08 beneficially modifies the gut microbiota with the potential to alleviate gastrointestinal symptoms and improve defecation habits.

Effect of nutrient composition in a mixed meal on the postprandial glycemic response in healthy people: a preliminary study.

BACKGROUND/OBJECTIVES: The glycemic index (GI) is a measure of the postprandial glucose response (PPGR) to food items, and glycemic load (GL) is a measure of the PPGR to the diet. For those who need to maintain a healthy diet, it is beneficial to regulate appropriate levels of blood glucose. In reality, what influences the meal GI or GL depends on the macronutrient composition and the physical chemistry reactions in vivo. Thus, we investigated whether different macronutrients in a meal significantly affect the PPGR and the validity of calculated GI and GL values for mixed meals. SUBJECTS/METHODS: 12 healthy subjects (6 male, 6 female) were recruited at a campus setting, and subjects consumed a total of 6 test meals one by one, each morning between 8:00 and 8:30 am after 12 h of fasting. PPGR was measured after each consumed meal and serial finger pricks were performed at indicated times. Test meals included 1) 68 g oral glucose, 2) 210 g rice, 3) rice plus 170 g egg white (RE), 4) rice plus 200 g bean sprouts (RS), 5) rice plus 10 g oil (RO), and 6) rice plus, egg white, bean sprouts, and oil (RESO). The incremental area under the curve (iAUC) was calculated to assess the PPGR. Mixed meal GI and GL values were calculated based on the nutrients the subjects consumed in each of the test meals. RESULTS: The iAUC for all meals containing two macronutrients (RS, RO, or RE) were not significantly different from the rice iAUC, whereas, the RESO iAUC (2,237.5 ± 264.9) was significantly lower (P < 0.05). The RESO meal's calculated GI and GL values were different from the actual GI and GL values measured from the study subjects (P < 0.05). CONCLUSIONS: The mixed meal containing three macronutrients (RESO) decreased the PPGR in healthy individuals, leading to significantly lower actual GI and GL values than those derived by nutrient-based calculations. Thus, consuming various macronutrient containing meals is beneficial in regulating PPGR.

[Bis(2-pyridylmeth-yl)amine]dichloridomercury(II).

The Hg atom in the title complex, [HgCl(2)(C(12)H(13)N(3))], adopts a square-pyramidal geometry, being ligated by three N atoms of the tridentate bis-(2-pyridylmeth-yl)amine ligand and two Cl atoms, with one of the latter occupying the apical position. Disorder is noted in the amine portion of the ligand and this was modelled over two sites, with the major component having a site-occupancy factor of 0.794 (14).