H2OAthletes study protocol: effects of hydration changes on neuromuscular function in athletes.

We aim to understand the effects of hydration changes on athletes' neuromuscular performance, on body water compartments, fat-free mass hydration and hydration biomarkers and to test the effects of the intervention on the response of acute dehydration in the hydration indexes. The H2OAthletes study (clinicaltrials.gov ID: NCT05380089) is a randomised controlled trial in thirty-eight national/international athletes of both sexes with low total water intake (WI) (i.e. < 35·0 ml/kg/d). In the intervention, participants will be randomly assigned to the control (CG, n 19) or experimental group (EG, n 19). During the 4-day intervention, WI will be maintained in the CG and increased in the EG (i.e. > 45·0 ml/kg/d). Exercise-induced dehydration protocols with thermal stress will be performed before and after the intervention. Neuromuscular performance (knee extension/flexion with electromyography and handgrip), hydration indexes (serum, urine and saliva osmolality), body water compartments and water flux (dilution techniques, body composition (four-compartment model) and biochemical parameters (vasopressin and Na) will be evaluated. This trial will provide novel evidence about the effects of hydration changes on neuromuscular function and hydration status in athletes with low WI, providing useful information for athletes and sports-related professionals aiming to improve athletic performance.

Interindividual variability in energy intake and expenditure during a weight loss intervention.

INTRODUCTION: Behavioral compensations may occur as a response to a negative energy balance. The aim of this study was to explore the associations between changes in energy intake (EI) and changes in physical activity (PA, min/day; kcal/d) as a response to a weight loss (WL) intervention and to understand if interindividual differences occur in EI and energy expenditure (EE). METHODS: Eighty-one participants [mean (SD): age = 42.8 (9.4)y, BMI = 31.2 (4.4)kg/m2, 37% females] divided in intervention (IG, n = 43) and control group (CG, n = 38) were included. The IG underwent a moderate energy restriction (300-500 kcal/d). EI was measured through the intake-balance method. Non-exercise PA (NEPA) and exercise (through logbook) were assessed by accelerometery. The EE in NEPA (NEAT) and in exercise (EiEE) was calculated by applying the Freedson Combination'98 algorithm over the time spent in these activities. Pearson correlations were performed in IG to examine associations between EE components, EI and body composition. To understand if interindividual differences were observed, the SD of individual response (SDIR) and the smallest worthwhile change (SWC, SDbaselineCG×0.2) were calculated. RESULTS: Changes in EI [Δ EI, (kcal/d)] was negatively associated with Δ exercise (min/d:r = -0.413, p = 0.045; %:r = -0.846, p = 0.008) and with Δ EiEE (kcal/d:r = -0.488, p = 0.016; %:r = -0.859, p = 0.006). A negative correlation was found between Δ sedentary time and Δ NEPA (min/d:r = -0.622, p = 0.002; %:r = -0.487, p = 0.018). An interindividual variability was found for EI(SDIR = 151.6, SWC = 72.3) and EE (SDIR = 165, SWC = 134). CONCLUSIONS: Decreases in EI were not associated to compensatory responses such as decreases in PA and/or increases in sedentary time. Interindividual variability was found for EI and EE. Nevertheless, behavioral compensations and the interindividual variability should be considered when implementing WL interventions, to increase the likelihood of achieving sustainable results. (clinicaltrials.gov ID: NCT03031951).

Prediction of body water compartments by raw bioelectrical impedance parameters in athletes: Comparison between series and parallel measurements.

BACKGROUND: The aim of this study was to determine the predictive role of series and parallel bioelectrical impedance-derived parameters in predicting total body (TBW), intracellular (ICW), and extracellular water (ECW) in athletes. METHODS: This cross-sectional study analyzed 134 male (21.33 ± 5.11 years) and 64 female (20.45 ± 5.46 years) athletes. Using dilution techniques, TBW and ECW were determined while ICW was the difference between both. Raw and standardized for height (/H) bioelectrical resistance (R), reactance (Xc), and impedance (Z) values were obtained using a phase-sensitive device at a single frequency in a series array (s). These were mathematically transformed in a parallel array (p) and capacitance (CAP). Fat-free mass (FFM) was assessed by dual-energy X-ray absorptiometry. RESULTS: Multiple regressions adjusted for age and FFM show that R/Hs, Z/Hs, R/Hp, and Z/Hp were significant predictors of TBW (p < 0.001 in females and males). While Xc/Hs did not predict ICW, Xc/Hp was a predictor (p < 0.001 in females and Males). In females, R/H and Z/H predicted similarly TBW, ICW, and ECW. In males, R/Hs was considered a better predictor than R/Hp for TBW and ICW, and the Xc/Hp was considered the best predictor for ICW. Another significant predictor of ICW was CAP (p < 0.001 in females and males). CONCLUSION: This study highlights the potential value of parallel bioelectrical impedance values to identify fluid compartments in athletes as an alternative to the regularly used series measurements. Moreover, this study supports Xc in parallel, and ultimately CAP, as valid indicators of cell volume.

Athletes with different habitual fluid intakes differ in hydration status but not in body water compartments.

Physiological differences have been reported between individuals who have habitual low (LOW) and high (HIGH) water intake (WI). The aims of this study were to explore body water compartments, hydration status, and fat-free mass (FFM) hydration of elite athletes exposed to different habitual WI. A total of 68 athletes (20.6 ± 5.3 years, 23 females) participated in this observational cross-sectional study. Total WI was assessed by seven-day food diaries and through WI, athletes were categorized as HIGH (n = 28, WI≥40.0 mL/kg/d) and LOW (n = 40, WI≤35.0 mL/kg/d). Total body water (TBW) and extracellular water (ECW) were determined by dilution techniques and intracellular water (ICW) as TBW-ECW. Hydration status was assessed by urine-specific gravity (USG) using a refractometer. Fat (FM) and FFM were assessed by dual-energy X-ray absorptiometry (DXA). The FFM hydration was calculated by TBW/FFM. The USG was statistically different between groups for females (LOW: 1.024 ± 0.003; HIGH: 1.015 ± 0.006; p = 0.005) and males (LOW: 1.024 ± 0.002; HIGH: 1.018 ± 0.005; p < 0.001). No differences between groups were detected in body water compartments and FFM hydration in both sexes (p > 0.05). Multiple regression showed that WI remains a predictor of USG regardless of FFM, age, and sex (ß = -0.0004, p < 0.01). We concluded that LOW athletes were classified as dehydrated through USG although their water compartments were not different from HIGH athletes. These results suggest that LOW athletes may expectedly maintain the body water compartments' homeostasis through endocrine mechanisms. Interventions should be taken to encourage athletes to have sufficient WI to maintain optimal hydration.

Effects of a 4-month active weight loss phase followed by weight loss maintenance on adaptive thermogenesis in resting energy expenditure in former elite athletes.

PURPOSE: Despite adaptive thermogenesis (AT) being studied as a barrier to weight loss (WL), few studies assessed AT in the resting energy expenditure (REE) compartment after WL maintenance. The aim of this study was twofold: (1) to understand if AT occurs after a moderate WL and if AT persists after a period of WL maintenance; and (2) if AT is associated with changes in body composition, hormones and energy intake (EI). METHODS: Ninety-four participants [mean (SD); BMI, 31.1(4.3)kg/m2; 43.0(9.4)y; 34% female] were randomized to intervention (IG, n = 49) or control groups (CG, n = 45). Subjects underwent a 1-year lifestyle intervention, divided in 4 months of an active WL followed by 8 months of WL maintenance. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. Predicted REE (pREE) was estimated through a model using FM, FFM. EI was measured by the "intake-balance" method. RESULTS: For the IG, the weight and FM losses were - 4.8 (4.9) and - 11.3 (10.8)%, respectively (p < 0.001). A time-group interaction was found between groups for AT. After WL, the IG showed an AT of -85(29) kcal.d-1 (p < 0.001), and remained significant after 1 year [AT = - 72(31)kcal.d-1, p = 0.031]. Participants with higher degrees of restriction were those with an increased energy conservation (R = - 0.325, p = 0.036 and R = - 0.308, p = 0.047, respectively). No associations were found between diet adherence and AT. Following a sub-analysis in the IG, the group with a higher energy conservation showed a lower WL and fat loss and a higher initial EI. CONCLUSION: AT in REE occurred after a moderate WL and remained significant after WL maintenance. More studies are needed to better clarify the mechanisms underlying the large variability observed in AT and providing an accurate methodological approach to avoid overstatements. Future studies on AT should consider not only changes in FM and FFM but also the FFM composition.

Adaptive thermogenesis after moderate weight loss: magnitude and methodological issues.

PURPOSE: The aim of this study was (1) to assess AT through 13 different mathematical approaches and to compare their results; and (2) to understand if AT occurs after moderate WL. METHODS: Ninety-four participants [mean (SD); BMI, 31.1 (4.3) kg/m2; age, 43.0 (9.4) years; 34% females] underwent a 1-year lifestyle intervention (clinicaltrials.gov ID: NCT03031951) and were randomized to intervention (IG, n = 49) or control groups (CG, n = 45), and all measurements were made at baseline and after 4 months. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. AT was assessed through 13 different approaches, varying in how REE was predicted and/or how AT was assessed. RESULTS: IG underwent a mean negative energy balance (EB) of 270 (289) kcal/day, p < 0.001), resulting in a WL of - 4.8 (4.9)% and an FM loss of - 11.3 (10.8)%. Regardless of approach, AT occurred in the IG, ranging from ~ - 65 to ~ - 230 kcal/day and three approaches showed significant AT in the CG. CONCLUSIONS: Regardless of approach, AT occurred after moderate WL in the IG. AT assessment should be standardized and comparisons among studies with different methodologies to assess AT must be avoided.

Effectiveness of a lifestyle weight-loss intervention targeting inactive former elite athletes: the Champ4Life randomised controlled trial.

OBJECTIVES: Many athletes struggle in managing the end of their career, often gaining weight and adopting unhealthy lifestyles. Lifestyle programmes targeting former athletes who have gained substantial fat mass (FM) postsports career are lacking. We studied the effects of the Champ4Life programme on body composition and other health-related outcomes in former elite athletes with overweight or obesity. METHODS: Ninety-four former athletes(42.4±7.3 y, 34.0% female) were recruited and randomly assigned to either an intervention group (IG; n=49) or a control group (CG; n=45). The IG attended 12 educational sessions addressing physical activity, weight management and nutrition. They also had a nutrition appointment aimed to prescribe a moderate caloric deficit(~300-500 kcal/day). Dual-energy X-ray absorptiometry was used to assess body composition. The Short-Form Health Survey-36 questionnaire was used to measure general health-related quality of life. Blood samples were collected to assess cardiometabolic health parameters. RESULTS: At 12 months, the IG lost more weight (estimated difference (ED)=-5.3 kg; -6.9 to -3.8), total FM (ED=-4.1 kg; -5.4 to -2.8) and abdominal FM (ED=-0.49 kg; -0.64 to -0.33) than did the CG (p's<0.001). Cardiometabolic health markers also improved significantly (p<0.05) more in the IG at 12 months (insulin (ED=-4.9 µU/mL;-8.0 to -1.8); homoeostatic model assessment (ED=-1.2; -2.1 to -0.4); total cholesterol (ED=-21.8 mg/dL; -35.4 to -8.2); low-density lipoprotein (ED=18.2 mg/dL;-29.2 to -7.1)), as did quality-of-life dimensions (physical functioning (ED=11.7; 6.5 to 16.9); physical role (ED=17.6; 2.1 to 33.0); general health (ED=19.4; 11.4 to 27.4); vitality (ED=13.3; 5.3 to 21.3) and mental health (ED=12.3; 4.1 to 20.6)). CONCLUSIONS: The Champ4Life programme was effective in substantially reducing total and abdominal FM while preserving fat-free mass and improving health-related markers. These findings will enable evidence-based decisions when implementing lifestyle interventions targeting retired elite athletes. TRIAL REGISTERATION NUMBER: NCT03031951.

Between-devices agreement in obtaining raw bioelectrical parameters after a lifestyle intervention targeting weight loss in former athletes.

It is unclear if different bioelectrical impedance (BI) devices provide similar results regarding raw parameters [Resistance (R), Reactance (Xc), Phase Angle (PhA), and Impedance (Z)] for the same population/individual undergoing a weight loss intervention. The aim was to evaluate the cross-sectional and longitudinal agreement of raw data obtained by two BI devices in former athletes with overweight/obesity. Fifty-nine participants [mean (SD): 43.5 (9.2) years, 30.5 (4.0) kg/m2, 42% females] were included. All the assessments were performed before and after a 4-months lifestyle intervention targeting weight loss (WL). BI parameters were assessed at 50 kHz by two devices: a BI spectroscopy (Xitron Technologies, 4200B, San Diego, USA) and a phase-sensitive single-frequency device (BIA 101 AKERN, Florence, Italy). Cross-sectionally, BIS provided lower mean values for all parameters (0.4% for R, 1.6% for Xc, 1.0% for PhA and 0.4% for Z, p <0.001) compared to SF-BIA. In individuals with a WL≥2.5% (n =18), no longitudinal differences were found in any of the raw parameters between devices (p≥0.128) and there was no proportional bias (p≥0.408). Despite small baseline differences in raw BI parameters, both devices agreed in tracking changes over time at the group level but interpretation should be careful at the individual level.

Energy Availability Over One Athletic Season: An Observational Study Among Athletes From Different Sports.

During the athletic season, changes in body composition occur due to fluctuations in energy expenditure and energy intake. Literature regarding changes of energy availability (EA) is still scarce. The aim was to estimate EA of athletes from nonweight and weight-sensitive sports during the athletic season (i.e., preparatory and competitive phase). Eighty-eight athletes (19.1 ± 4.2 years, 21.8 ± 2.0 kg/m2, 27% females, self-reported eumenorrheic) from five sports (basketball [n = 29]; handball [n = 7]; volleyball [n = 9]; swimming [n = 18]; and triathlon [n = 25]) were included in this observational study. Energy intake and exercise energy expenditure were measured through doubly labeled water (over 7 days and considering neutral energy balance) and metabolic equivalents of tasks, respectively. Fat-free mass (FFM) was assessed through a four-compartment model. EA was calculated as EA = (energy intake - exercise energy expenditure)/FFM. Linear mixed models, adjusted for sex, were performed to assess EA for the impact of time by sport interaction. Among all sports, EA increased over the season: basketball, estimated mean (SE): 7.2 (1.5) kcal/kg FFM, p < .001; handball, 14.8 (2.9) kcal/kg FFM, p < .001; volleyball, 7.9 (2.8) kcal/kg FFM, p = .006; swimming, 8.7 (2.0) kcal/kg FFM, p < .001; and triathlon, 9.6 (2.0) kcal/kg FFM, p < .001. Eleven athletes (12.5%) had clinical low EA at the preparatory phase and none during the competitive phase. During both assessments, triathletes' EA was below optimal, being lower than basketballers (p < .001), volleyballers (p < .05), and swimmers (p < .001). Although EA increased in all sports, triathlon's EA was below optimal during both assessments. Risk of low EA might be seasonal and resolved throughout the season, with higher risk during the preparatory phase. However, in weight-sensitive sports, namely triathlon, low EA is still present.

Validity of water compartments estimated using bioimpedance spectroscopy in athletes differing in hydration status.

We aimed to validate bioelectrical impedance spectroscopy (BIS), compared with tracer dilution measurements, for assessing total body water (TBW), intracellular water (ICW), and extracellular water (ECW) in athletes differing in hydration status. A total of 201 athletes participated. Reference TBW and ECW were determined by deuterium and bromide dilution methods, respectively; ICW was calculated as TBW-ECW. Water compartments were estimated by BIS. Urine specific gravity (USG) classified athletes into well-hydrated (WH) (USG < 1.023), euhydrated (EH) (USG:1.024-1.026), and dehydrated (DH) (USG>1.027). No significant differences were found between BIS and the reference methods for WH, EH, and DH athletes for TBW, ICW nor ECW (p>0.05). Concordance of TBW and its compartments by method was significant (p < 0.001) with coefficients of determination ranging by hydration classification [EH:52-96%;DH:56-98%;WH:71-96%]. Bland-Altman analyses showed no trend for TBW and its compartments with the exception of ICW in the WH athletes. The 95% confidence BIS intervals for the WH group ranged from -3.08 to 2.68 kg for TBW, -4.28 to 4.14 kg for ICW, and -3.29 to 3.02 kg for ECW. For the EH athletes, the 95% confidence intervals ranged from -2.78 to 2.24 kg for TBW, -4.10 to 3.94 kg for ICW, and -3.44 to 3.06 kg for ECW. In DH group, TBW ranged between -1.99 and 2.01 kg, ICW between -3.78 and 6.34 kg, and ECW between -6.22 and 3.74 kg. These findings show that BIS is useful at a group level in assessing water compartments in athletes differing in hydration status. However, the usefulness of BIS is limited at an individual level, especially in dehydrated athletes.

The impact of body composition on the degree of misreporting of food diaries.

BACKGROUND/OBJECTIVES: Accurate assessments of energy intake (EI) are needed in lifestyle interventions to guarantee a negative energy balance (EB), thereby losing weight. This study aimed (1) to compare objectively measured and self-reported EI and (2) to determine the predictors of underreporting divided by sex, adiposity and BMI category. METHODS: Seventy-three participants [mean (SD): 43.7 (9.2) years, BMI = 31.5 (4.5) kg/m2, 37% females] of the Champ4Life intervention were included in this study. EI was measured using the "intake-balance method" and self-reported through 3-day food records. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry. Bland-Altman analysis was performed to compare both EI assessments. RESULTS: Self-reported EI was lower than measured EI during both neutral (-355 kcal/d) and negative EB (-570 kal/day). While no significant trends were observed for EI evaluation in either neutral (p = 0.315) or negative EB (p = 0.611), limits of agreement were wide (-1720 to 1010 and -1920 to 779 kcal/day, respectively). In females, the degree of misreporting (kcal/day and %) was predicted by weight (p = 0.032 and p = 0.039, respectively) and FM (p = 0.029 and p = 0.037, respectively). In males, only BMI (p = 0.036) was a predictor of misreporting (kcal/day). CONCLUSION: Self-reported EI did not agree with measured EI. Our results show that larger body size was associated with higher levels of underestimation for EI (females only). Nevertheless, misreporting EI is a complex issue involving more associations than merely body composition. A deeper understanding could inform counseling for participants filling out food records in other to reduce misreporting and improve validity.

The Ex-Timing trial: evaluating morning, afternoon, and evening exercise on the circadian clock in individuals with type 2 diabetes and overweight/obesity-a randomized crossover study protocol.

BACKGROUND: Exercise is known to provide multiple metabolic benefits such as improved insulin sensitivity and glucose control in individuals with type 2 diabetes mellitus (T2DM) and those at risk. Beyond the traditional exercise dose, exercise timing is perceived as a contemporary hot topic, especially in the field of T2DM; however, the number of intervention studies assessing exercise timing and glucose metabolism is scarce. Our aim is to test the effect of exercise timing (i.e., morning, afternoon, or evening) on the inter-individual response variability in glycemic control and related metabolic health parameters in individuals with T2DM and those at risk during a 12-week intervention. METHODS: A randomized crossover exercise intervention will be conducted involving two groups: group 1, individuals with T2DM; group 2, age-matched older adults with overweight/obesity. The intervention will consist of three 2-week blocks of supervised post-prandial exercise using high-intensity interval training (HIIT). Between each training block, a 2-week washout period, where participants avoid structured exercise, will take place. Assessments will be conducted in both groups before and after each exercise block. The primary outcomes include the 24-h area under the curve continuous glucose monitoring-based glucose. The secondary outcomes include body composition, resting energy expenditure, insulin response to a meal tolerance test, maximal aerobic capacity, peak power output, physical activity, sleep quality, and insulin and glucose levels. All primary and secondary outcomes will be measured at each assessment point. DISCUSSION: Outcomes from this trial will provide us additional insight into the role of exercise timing on the inter-individual response variability in glycemic control and other related metabolic parameters in two distinct populations, thus contributing to the development of more effective exercise prescription guidelines for individuals with T2DM and those at risk. TRIAL REGISTRATION: ClinicalTrials.gov NCT06136013. Registered on November 18, 2023.

Comparison of series and parallel reactance to identify changes in intracellular water in response to physical training in athletes during a sports season.

OBJECTIVE: Cross-sectional evidence has demonstrated that parallel reactance obtained by bioelectrical impedance analysis (BIA) may be an alternative to the regularly used series of measurements to predict intracellular water (ICW) in athletes. However, we are not aware of any studies that have determined the predictive role or compared the effectiveness of both series and parallel reactance for tracking ICW changes during an athletic season. The main aim of this study was to determine the predictive role and compare both series and parallel reactance (Xc) in tracking ICW during an athletic season. RESEARCH METHODS AND PROCEDURES: This longitudinal study analyzed 108 athletes in the preparatory and competitive periods. Using dilution techniques, total body water (TBW) and extracellular water (ECW) were determined and ICW was calculated. Resistance (R), Xc, and impedance (Z) standardized for height were obtained through BIA spectroscopy using a frequency of 50kHz in a series array and then mathematically transformed in a parallel array. RESULTS: Multiple regression analyses showed that only changes in parallel Xc and capacitance (CAP) (P < 0.05) were predictors of delta ICW during the sports season. In contracts, this was not the case for Xcs. Both changes in R and Z, series and parallel, predicted similarly the changes in ECW and TBW (P < 0.05) in athletes. CONCLUSION: Our findings highlight the potential of parallel BIA values to detect changes in body water compartments over a competitive season. These data provide preliminary evidence that changes in parallel Xc/H, and ultimately CAP, represent valid markers of alterations in cell volume during a sports season.

Assessment of exercise-induced dehydration in underhydrated athletes: Which method shows the most promise?

BACKGROUND & AIMS: Athletes are commonly exposed to exercise-induced dehydration. However, the best method to detect dehydration under this circumstance is not clear. This study aimed to analyze pre- and post-dehydration measurements of biomarkers, including saliva osmolality (SOsm), urine osmolality (UOsm), urine-specific gravity (USG), urine color (Ucolor), serum osmolality (SeOsm), serum arginine vasopressin (AVP), serum sodium (Na+), and thirst sensation in underhydrated athletes, using the body mass loss (BML) as the reference method. METHODS: In this clinical trial (NCT05380089), a total of 38 athletes (17 females) with a regular low water intake (<35 mL/kg/day) were submitted to exercise-induced dehydration with a heat index of 29.8 ± 3.1 °C and an individualized running intensity (80-90% of first ventilatory threshold). RESULTS: ROC curve analysis revealed significant discriminative abilities of SOsm, with AUC values of 0.76 at 1.5% BML, 0.75 at 1.75% BML, and 0.87 at 2% BML, while Na+ and SeOsm showed the highest AUC of 0.87 and 0.91 at 2% BML, respectively. SOsm showed high sensitivity at 1.5% of BML, while SeOsm and Na+ demonstrated high sensitivity at 2% of BML. CONCLUSION: This study highlights SOsm as a potential indicator of hydration status across different levels of BML. Additionally, Na+ and SeOsm emerged as accurate dehydration predictors at 1.75% and 2% of BML. Notably, the accuracy of urinary indices and thirst sensation for detecting hydration may be limited.

Does acute dehydration affect the neuromuscular function in healthy adults? - A systematic review.

The effects of acute dehydration on neuromuscular function have been studied. However, whether the mechanisms underpinning such function are central or peripheral is still being determined, and the results are inconsistent. This systematic review aims to elucidate the influence of acute dehydration on neuromuscular function, including a novel aspect of investigating the central and peripheral neuromuscular mechanisms. Three databases were used for the article search: PubMed, Web of Science, and Scopus. Studies were included if they had objective measurements of dehydration, muscle performance, and electromyography data or transcranial magnetic stimulation or peripheral nerve stimulation measurements with healthy individuals aged 18-65y. Twenty-three articles met the eligibility criteria. The studies exhibited considerable heterogeneity in the methods used to induce and quantify dehydration. Despite being inconsistent, the literature shows some evidence that acute dehydration does not affect maximal strength during isometric or moderate-speed isokinetic contractions. Conversely, acute dehydration significantly reduces maximal strength during slow-speed isokinetic contractions and fatigue resistance in response to endurance tasks. The studies report that dehydration does not affect the motor cortical output or spinal circuity. The effects occur at the peripheral level within the muscle. PROSPERO identification code: CRD42022372217.

Add-on radioiodine during long-term BRAF/MEK inhibition in patients with RAI-refractory thyroid cancers: a reasonable option?

Dual modulation of the MAPK pathway with BRAF (e.g., dabrafenib) and MEK (e.g., trametinib) inhibitors has the potential to re-establish radioiodine (RAI) sensitivity in BRAF-mutated RAI-refractory (RAI-R)-differentiated thyroid carcinoma (DTC) cells. Here we showed that (1) double BRAF/MEK inhibition may still reach a significant redifferentiation in patients with a long-history RAI-R DTC and multiple previous treatments; (2) the addition of high RAI activities may obtain a significant structural response in such patients; and (3) a divergence between increasing thyroglobulin and structural response may be a reliable biomarker or redifferentiation. Accordingly, the add-on prescription of high activities of 131I should be considered in RAI-R patients under multikinase inhibitors with stable or responding structural disease and divergent increase of Tg levels.

Interindividual variability in metabolic adaptation of non-exercise activity thermogenesis after a 1-year weight loss intervention in former elite athletes.

Lack of efficacy of weight loss(WL) interventions is attributed in-part to low adherence to dietary/physical activity(PA) recommendations. However, some compensation may occur in PA as a response to energy restriction such as a decrease in non-exercise PA(NEPA) or non-exercise activity thermogenesis(NEAT). The current study aim was (1) to investigate whether adaptive thermogenesis(AT) in NEAT occurs after WL, and (2) to understand the associations of these compensations with WL. Ninety-four former athletes [mean±SD, age: 43.0±9.4y, BMI: 31.1±4.3 kg/m2, 34.0% female] were recruited and randomly assigned to intervention or control groups (IG, CG). The IG underwent a one-year lifestyle WL-intervention; no treatments were administered to the CG. PA was measured using accelerometery and NEAT was predicted with a model including sample baseline characteristics. AT was calculated as measuredNEAT4mo/12mo(kcal/d)-predictedNEAT4mo/12mo(kcal/d)-measuredNEATbaseline(kcal/d)-predictedNEATbaseline(kcal/d). Dual-energy x-ray absorptiometry was used to assess fat-free mass and fat mass. No differences were found in the IG for NEAT or NEPA after WL. Considering mean values, AT was not found for either group. The SD of individual response (SDIR) for AT was -2(4-months) and 24(12-months) (smallest worthwhile change = 87kcal/d), suggesting that the interindividual variability regarding AT in NEAT is not relevant and the variability in this outcome might reflect a large within-subject variability and/or a large degree of random measurement error. No associations were found between AT in NEAT and changes in body composition. Further studies are needed to clarify the mechanisms behind the large variability in AT observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions.HighlightsNo significant differences were found for non-exercise activity thermogenesis (NEAT) or non-exercise physical activity (NEPA) after the weight loss (WL) intervention;Although a large variability was found for NEAT and NEPA, the interindividual variability regarding these outcomes is not relevant. The variability in these outcomes might reflect a large within-subject variability and/or a large degree of random measurement error;Although no energy conservation was observed in NEAT after moderate WL (mean values), further studies are needed to clarify the mechanisms behind the large variability in adaptive thermogenesis observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions.Trial registration: ClinicalTrials.gov identifier: NCT03031951.

Genomic profiling of post-transplant lymphoproliferative disorders using cell-free DNA.

Diagnosing post-transplant lymphoproliferative disorder (PTLD) is challenging and often requires invasive procedures. Analyses of cell-free DNA (cfDNA) isolated from plasma is minimally invasive and highly effective for genomic profiling of tumors. We studied the feasibility of using cfDNA to profile PTLD and explore its potential to serve as a screening tool. We included seventeen patients with monomorphic PTLD after solid organ transplantation in this multi-center observational cohort study. We used low-coverage whole genome sequencing (lcWGS) to detect copy number variations (CNVs) and targeted next-generation sequencing (NGS) to identify Epstein-Barr virus (EBV) DNA load and somatic single nucleotide variants (SNVs) in cfDNA from plasma. Seven out of seventeen (41%) patients had EBV-positive tumors, and 13/17 (76%) had stage IV disease. Nine out of seventeen (56%) patients showed CNVs in cfDNA, with more CNVs in EBV-negative cases. Recurrent gains were detected for 3q, 11q, and 18q. Recurrent losses were observed at 6q. The fraction of EBV reads in cfDNA from EBV-positive patients was 3-log higher compared to controls and EBV-negative patients. 289 SNVs were identified, with a median of 19 per sample. SNV burden correlated significantly with lactate dehydrogenase levels. Similar SNV burdens were observed in EBV-negative and EBV-positive PTLD. The most commonly mutated genes were TP53 and KMT2D (41%), followed by SPEN, TET2 (35%), and ARID1A, IGLL5, and PIM1 (29%), indicating DNA damage response, epigenetic regulation, and B-cell signaling/NFkB pathways as drivers of PTLD. Overall, CNVs were more prevalent in EBV-negative lymphoma, while no difference was observed in the number of SNVs. Our data indicated the potential of analyzing cfDNA as a tool for PTLD screening and response monitoring.

Usability of classic and specific bioelectrical impedance vector analysis in measuring body composition of children.

In this study, we aimed to analyse the relationship between body composition and bioelectrical variables in children and adolescents. The sample was composed of 6801 individuals (4035 males; 2766 females) aged 8-20 years included in the National Health and Nutrition Examination Survey (NHANES) years 1999-2004. Classic and specific bioelectrical impedance vector analysis (BIVA) were applied and compared with dual-energy X-ray absorptiometry (DXA) for the evaluation of fat mass (FM) and fat-free mass (FFM), and bioimpedance spectroscopy (BIS) for the evaluation of intra-cellular water (ICW), extra-cellular water (ECW), and total body water (TBW). Fat-free mass index (FFMI) was calculated. Spearman's correlation, regression, and depth-depth analyses were applied. The evaluation of body composition with BIVA agreed well with that of DXA or BIS, independently of sex, age, and ethnicity: classic BIVA was mostly sensitive to differences in TBW, ECW/ICW, whereas specific BIVA to differences in %FM, FFMI, and ECW/ICW. The depth-depth analysis confirmed the associations of classic BIVA (coeff. 0.500, p < 0.001), and specific BIVA (coeff. 0.512, p < 0.001), also considering the significant effect of age (p < 0.001). In classic BIVA the association was slightly stronger in females (by 0.03, p = 0.042) and among Blacks (0.06, p = 0.002), whereas in specific BIVA it was stronger by 0.06 (p < 0.001) in females and similar among ethnic groups. The combined use of the two BIVA approaches represents a valuable tool for complete evaluation of body composition in growth studies, for the prevention and monitoring of malnutrition, and the monitoring of the performance in young athletes.