Research shows that higher dietary protein of up to 1.2 g/kgbodyweight/day may help prevent sarcopenia and maintain musculoskeletal health in older individuals. Achieving higher daily dietary protein levels is challenging, particularly for older adults with declining appetites and underlying health conditions. The negative impact of these limitations on aging muscle may be circumvented through the consumption of high-quality sources of protein and/or supplementation. Currently, there is a debate regarding whether source of protein differentially affects musculoskeletal health in older adults. Whey and soy protein have been used as the most common high-quality proteins in recent literature. However, there is growing consumer demand for additional plant-sourced dietary protein options. For example, pea protein is rapidly gaining popularity among consumers, despite little to no research regarding its long-term impact on muscle health. Therefore, the objectives of this review are to: (1) review current literature from the past decade evaluating whether specific source(s) of dietary protein provide maximum benefit to muscle health in older adults; and (2) highlight the need for future research specific to underrepresented plant protein sources, such as pea protein, to then provide clearer messaging surrounding plant-sourced versus animal-sourced protein and their effects on the aging musculoskeletal system.

Background Titanium dioxide (TiO2/E171) is used in foods primarily as a whitening agent. Little is known regarding TiO2 exposure in the U.S. Objective To quantify stool TiO2 content among U.S. adults and evaluate its association with estimated intake. Methods Adults participated in phase 1 (three, 24h dietary recalls (DR) and stool TiO2 measured from three matched samples (n = 52)) and/or phase 2 (tailored food frequency questionnaire (FFQ) and stool TiO2 measured from three samples over 3 mo (n = 61)). TiO2 in foods was estimated from a database, and concentration in 49 additional foods and 339 stool samples were quantified using ICP-MS. Associations between dietary and stool TiO2 were assessed by log-linear multivariable regression. USDA food groups (n = 49, servings/d) were related to stool TiO2 by stepwise regression. Results TiO2 food content varied by brand. Mean TiO2 intake from three, 24hDR (0.19±0.31 mg/(kg BW · d)) was lower than from the FFQ (0.30±0.21 mg/(kg BW · d)). Dietary TiO2 was not predictive of stool TiO2, in phase 1 or phase 2, 10^(β) per 10-times higher dietary TiO2: 1.138 ((10^(95% CI): 0.635, 2.037, P = 0.66) and 0.628 (0.206, 1.910, P = 0.41), respectively. Food groups related to stool TiO2 were 1) milk desserts, sauces, gravies (10^(β) per servings/day = 3.361; 10^(95% CI): 0.312, 36.163, P = 0.002) and 2) yeast breads (10^(β) = 1.430; 0.709, 2.884, P = 0.002) in phase 1; and, in phase 2, 1) cream, cream substitutes (10^(β) = 10.925; 1.952, 61.137, P = 0.01), and 2) milk and milk drinks (10^(β) = 0.306; 0.086, 1.092, P = 0.07). Conclusion Intake of certain foods were associated with higher stool TiO2 content. There is a need for valid estimation of TiO2 intakes via the improvement of a dietary assessment methods and a TiO2 food composition database. Future research should assess whether high stool TiO2 content is related to adverse health outcomes.

Objectives To analyze the impact of different sources of protein (pea, whey or casein) on functional muscle performance in C57BL/6 mice. Methods A total of 21 mice were randomized to protein intervention groups. Mice were individually caged in a temperature controlled and 12-h light-dark cycle room. Subjects were randomly assigned to casein, whey, and pea protein sourced diets, matched by sex. Total energy (3.77 ± 0.04 kcal/g) and macronutrient composition (% of total energy: carbohydrate 66%, protein 18% and fat 16%) were matched across diets. Body weight and amount of food consumed was measured weekly. Functional muscle performance was measured by forelimb grip strength test using an Accuforce Cadet Force Gage and hanging test using Kondziela's inverted screen test capped at 600 seconds (at intervention week 9). The recorded strength and hang time measurements were corrected for body-mass. Data processing and analyses were performed in IBM SPSS Statistics 25. Results Excluding 2 mice due to outliers, the total number of mice per group were: casein (n = 9), whey (n = 6), and pea (n = 5). No baseline differences in body weight or average amount of food consumed per week were observed between groups. However, mice on the pea protein diet gained significantly more weight (8 ± 2g) compared to whey (4 ± 2g) and casein (2 ± 2g) diet groups (P < 0.007). Mice fed with whey protein sourced diets showed significantly stronger maximum fore limb grip strength (237 ± 21g) compared to pea (200 ± 7g) and casein (219 ± 26g) fed mice (P < 0.005). Body-mass corrected average and maximum grip strength tests showed that mice consuming pea protein sourced were significantly weaker compared to the casein protein sourced diet group, but not to whey protein sourced diet group (Table 1). Conclusions No observable differences were found between whey and casein in functional muscle performance of C57BL/6 mice when corrected for body weight. However, the pea sourced protein diet resulted in higher weight gain and weaker functional muscle performance measurements. Funding Sources University of Massachusetts Lowell Seed Grant (NK, KM, MG). Supporting Tables, Images and/or Graphs

Objectives Engineered nanomaterials, such as titanium dioxide (TiO2/E171) are used in food primarily as a whitening agent. Over 99% ingested TiO2 passes to the gastrointestinal (GI) tract while 1% is absorbed and shown to bioaccumulate in organs and may cause adverse outcomes. At present, dietary exposure of TiO2 in the US is unknown. The objective is to estimate dietary TiO2 and measure TiO2 output in matched stool samples as a biological marker of intake. Methods Participants (n = 51), aged 18–30 y, were recruited in Lowell, MA and were eligible if they had not taken laxatives/antibiotics in the past 6 mo, free of GI disease and no history of GI alterations. Recent dietary intake was assessed by 3, 24-h recalls (NDSR2019) and estimated TiO2 intake is presented as the average of the 3 days. A published database of TiO2 content in foods (Netherlands), with extrapolations for similar US foods, was used to estimate TiO2 exposure. To capture TiO2 excretion, stool samples (n = 3) were collected the same day of diet recall. TiO2 was measured in reported foods suspected to contain TiO2 to improve the database. Concentrations of TiO2 in food and stool samples were measured using inductively coupled plasma mass spectrometry following acid digestion. Results Mean age was 23 ± 3 y; BMI 27 ± 5 kg/m2; 52.9% female. Mean estimated TiO2 intake was 0.13 ± 0.28 mg/kgbw/d (median: 0.03; range: 0.01–1.63 mg/kgbw/d). Mean measured TiO2 concentration in stool samples was 0.107 ± 0.134 mg/mg (median: 0.043; range: 0.005–0.536 ug/mg). Food analysis showed TiO2 content varies widely and is dependent on brand. The top 5 contributors to TiO2 intake in this sample were frostings (62.2%), sauces (8.7%), grains (5.3%), chewing gum (4.43%), and commercial desserts – miscellaneous (3.3%). No association was observed between reported TiO2 intake and measured stool concentration. Conclusions To our knowledge, this is the first study to assess dietary TiO2 in the US using a validated dietary method and stool excretion. Estimated TiO2 intakes were similar to those in the Netherlands (0.17 mg/kgbw/d), but lower than previous estimates for the US, via Monte Carlo simulation (0.7 mg/kgbw/d). Improvement in the food database is needed to study the effects of chronic TiO2 intake on health outcomes, such as gut health and the microbiome. Funding Sources None.