Sex Differences in The Accuracy of WUT (Weight, Urine Color, Thirst) Diagrams Assessing Hydration Status

The WUT (Weight, Urine Color, Thirst) Venn diagram is a practical method to assess hydration status using percent body mass loss (%BML), urine color (UCOL), and thirst perception (TP). However, sex differences and the accuracy of WUT diagrams between males and females has not yet been investigated. PURPOSE: To observe sex differences in the accuracy of WUT diagrams assessing hydration status. METHODS: 8 males [M] (age: 21 ± 3; mass: 76.3 ± 15.6 kg) and 5 females [F] (age: 22 ± 2; mass: 60.5 ± 13.6) visited the laboratory twice a day (morning (7:00am-9:00am) and afternoon (2:00pm-4:00pm)) for six days as free-living for the first three consecutive days and euhydrated (urine specific gravity (USG) \u3c 1.020) for the last three consecutive days. During each visit, TP, body mass (BM), USG, UOSM, UCOL, and plasma osmolality (POSM) were collected. Values of USG \u3e1.020, UOSM \u3e700, and POSM \u3e290 indicated dehydration status. TP \u3e5, UCOL \u3e5, and %BML \u3e1% values were used as dehydration thresholds for WUT scores. Total WUT score (0-3) was determined by the total amount of respective dehydration markers identified. One-way ANOVA was used to analyze differences in POSM, UOSM, and USG between the different WUT scores for both sexes. Receiver operating characteristics analysis was used to calculate sensitivity (SENS) and specificity (SPEC) identifying dehydration or euhydration with WUT scores. RESULTS: For POSM, WUT3 (M: 291 ± 5; F: 286 ± 0 mOsmol), WUT2 (289 ± 6; 286 ± 7), WUT1 (286 ± 5; 286 ± 6), and WUT0 (289 ± 5; 285 ± 7) were not different between sexes (p \u3e .05). For USG, WUT3 (1.022 ± .004; 1.020 ± .000), WUT2 (1.019 ± .008; 1.020 ± .007), WUT1 (1.015 ± .006; 1.010 ± .005), and WUT0 (1.010 ± .006; 1.008 ± .006) were not different between sexes (p \u3e .05). For UOSM, WUT3 (819 ± 147; 744 ± .000 mOsmol), WUT2 (679 ± 244; 788 ± 261), WUT1 (521 ± 266; 461 ± 212), and WUT0 (383 ± 212; 322 ± 203) were not different between sexes (p \u3e .05). For POSM, WUT2SPEC was higher in M (WUT2Mspec, .860) than F (WUT2Fsepc, .786) while WUT3, WUT1, and WUT0 were similar between sexes (WUT3Mspec, .965; WUT3Fspec, .976; WUT1Mspec, .526; WUT1Fspec, .380). For USG, WUT2SENS was higher in F (WUT2Fsens, .889) than M (WUT2Msens, .571) while WUT3, WUT1, and WUT0 were similar between sexes (WUT3Msens, .238; WUT3Fsens, .111; WUT1Msens, .905; WUT1Fsens, .889). For UOSM, SPEC and SENS were similar between sexes for each WUT score. CONCLUSION: There are no sex differences in POSM, USG, and UOSM between WUT0-WUT3. However, based on SPEC and SENS, WUT3 and WUT0 can accurately detect hydration status in both sexes. WUT2 might be used to detect hydration status only for females

The Effect of Morning Thirst on Afternoon Hydration Status

Thirst sensation is an important stimulus for drinking behavior; however, the effect of thirst sensation on later hydration status remains unclear. PURPOSE: To investigate the effects of morning thirst on afternoon hydration status. METHODS: Twelve men (mean ± standard deviation; age: 21 ± 2 years; mass: 81.0 ± 15.9 kg) and twelve women (age: 22 ± 3 years; mass: 68.8 ± 15.2 kg) visited the laboratory in the morning (first morning) and afternoon (2:00-4:00pm) for three consecutive days under a free-living condition. At each visit, participants provided a urine sample where urine indices were analyzed (urine specific gravity [USG], urine color [UCOL], urine osmolality [UOSMO]), and nude body mass was collected to calculate body mass loss (BML). Then, thirst was assessed with a Likert scale, and a blood sample was collected to analyze plasma osmolality (POSMO), hemoglobin, and hematocrit to calculate % plasma volume change (PV). Participants recorded food and fluid intake between the morning and afternoon visits to determine total water intake (TWI). Linear regression was used to predict thirst from the morning on hydration indices in the afternoon. Also, a stepwise linear regression predicted thirst in the afternoon from hydration indices in the morning. Pearson’s product moment correlation was used to calculate the relationship between TWI and hydration markers. RESULTS: Higher morning thirst significantly predicted lower UOSMO (r2=0.056, p=0.045), USG (r2=0.096, p=0.008), UCOL (r2=0.074, p=0.021), and higher thirst (r2=0.074, p=0.021) in the afternoon. However, thirst in the morning did not predict BML, PV, POSMO, and TWI in the afternoon (p\u3e0.05). Increased thirst and BML in the morning together significantly predicted higher thirst (r2=0.125, p=0.010) in the afternoon. Increased TWI was associated with lower UCOL (r=0.336, p=0.004) and BML (r=0.297, p=0.011) in the afternoon. However, TWI was not associated with any variables in the morning or the remaining variables in the afternoon, including USG and UOSMO (p\u3e0.05). CONCLUSION: Increased morning thirst impacts afternoon urine indices and thirst. However, morning thirst does not influence TWI between the morning and the afternoon, and TWI is not associated with morning hydration status. Therefore, afternoon hydration status might be impacted by morning thirst, although individuals might not consume fluid based on their morning thirst or hydration status

Sleep Duration is Increased Following Muscle Damaging Exercise in Hot Environmental Conditions

Sleep and recovery measures are typically negatively affected by a muscle-damaging bout of exercise. However, it remains unknown if the additive effects of hot environmental conditions, resulting in increased core temperature and other thermoregulatory responses during the exercise bout, further progress changes in quantity and performance quality of sleep duration. PURPOSE: To investigate the effect of muscle-damaging exercise in the heat, compared to a thermoneutral condition, on sleep and recovery measures. METHODS: Ten healthy males (age: 23 ± 3yr; body mass: 78.7 ± 11.5kg; height: 176.9 ± 5cm; lactate threshold [LT]: 9.7 ± 1.0km.hr-1) performed two protocols in a randomized, counterbalanced order of downhill running (DHR) for 30-minutes at the LT in either a thermoneutral (ambient temperate [Tamb], 20°C; relative humidity [RH], 20%) or hot environmental condition (Tamb, 35°C; RH, 40%) at a -10% gradient. Sleep and recovery measures were collected from a wearable sleep device participants wore the night after the DHR. Differences in sleep and recovery measures following DHR in the heat compared to a thermoneutral condition were analyzed using paired samples T-tests. RESULTS: Sleep hours, restorative sleep hours, rapid eye movement (REM) sleep hours, and slow wave sleep (SWS) hours were all greater following the heat condition (mean ± SD; sleep hours: 6.70 ± 0.74hr, p = 0.040; restorative sleep hours: 3.31 ± 0.90hr, p = 0.012; REM sleep hours: 1.70 ± 0.64hr, p = 0.046; SWS hours: 1.61 ± 0.35hr, p = 0.015) compared to the thermoneutral condition (sleep hours: 5.24 ± 1.75hr; restorative sleep hours: 2.45 ± 1.11hr; REM sleep hours: 1.23 ± 0.68hr; SWS: 1.22 ± 0.53hr). Also, recovery was higher following the heat condition (recovery: 75.88 ± 15.31, p = 0.023) compared to the thermoneutral condition (recovery: 50.75 ± 21.46). Sleep efficiency, sleep disturbance, sleep deprivation, sleep score, %REM, %SWS, light sleep, resting heart rate, and heart rate variability were not different between conditions (ps \u3e 0.05). CONCLUSION: Following muscle-damaging exercise in the heat, sleep and recovery duration measures were increased compared to a thermoneutral condition. These findings suggest that performing muscle-damaging exercises in hot conditions may require a greater amount of sleep for optimal recovery

Relationships between Morning and Afternoon WUT (Weight, Urine Color, and Thirst) Criteria and Hydration Markers

A Venn diagram decision tool consisting of weight, urine color, and thirst (WUT) is suggested to measure hydration status. The WUT Venn diagram has been used as a practical hydration status assessment tool; however, this relationship has only been investigated using a first-morning urine sample. PURPOSE: To investigate relationships between morning and afternoon WUT criteria, blood and urine markers. METHODS: Eight men (age: 21 ± 3; mass: 76.3 ± 15.6 kg) and five women (age: 22 ± 2; mass: 60.5 ± 13.6 kg) completed the study. Body mass, urine color, urine specific gravity (USG), urine osmolality (UOSM), thirst level, and plasma osmolality (POSM) were collected as a first-morning and afternoon spot urine (2:00-4:00 CST) for 3 consecutive days in a free-living situation and 3 consecutive days in a euhydrated state. Body mass loss \u3e1%, urine color \u3e5, and thirst level ≥5 were used as dehydration thresholds. The number of markers that indicated dehydration levels were counted and categorized into either 3, 2, 1, or 0 WUT markers indicating dehydration (defined by either USG, UOSM, or POSM). One-way ANOVA with Tukey pairwise comparisons were used to assess differences in USG, UOSM, and POSM between different numbers of WUT markers. Receiver operating characteristics analysis was performed to calculate the predictive value of 0, 1, 2, or 3 hydration markers in detecting a dehydrated or euhydrated state. RESULTS: Morning and afternoon 1, 2, and 3 WUT markers were not significantly different (ps \u3e .05) for USG and POSM. Morning and afternoon 0, 2, and 3 WUT markers were not significantly different for UOSM. Morning and afternoon 3 WUT resulted in a specificity of 0.984 and 1.000, 0.984 and 1.000, and 0.956 and 0.981 for USG \u3e 1.020, UOSM \u3e 700mOsm, and POSM \u3e 290mOsm, respectively. Meeting at 2 WUT for morning and afternoon resulted in a specificity of 0.820 and 0.985, and 0.806 and 0.984 for USG and UOSM, respectively. Meeting at 1 WUT for morning and afternoon resulted in a sensitivity of 1.000 and 0.813 for UOSM. CONCLUSION: These results suggest that when 2 or 3 WUT markers are met, urine and blood hydration markers indicate dehydration, and when 1 WUT marker is met, UOSM indicates not dehydrated. The WUT Venn diagram can assess hydration status when an afternoon spot urine sample is used

Morning versus Afternoon Body Mass in Free-Living or Controlled Euhydration

The standard protocol to assess hydration status is by measuring body mass in the early morning without controlling fluid intake. However, obtaining first-morning body mass is not necessarily feasible for many situations, for example, most physical activities take place in the afternoon. Thus, first-morning body mass might not be practical to assess hydration status. PURPOSE: To investigate first-morning body mass versus afternoon body mass in free- living and controlled euhydration. METHODS: 9 males (age: 21 ± 2; mass: 79.7 ± 17.8 kg) and 5 females (age: 22 ± 2; mass: 60.5 ± 13.6 kg) visited the laboratory in the morning (7:00-9:00am) and afternoon (2:00-4:00pm) for six days to measure their nude body mass and urine specific gravity (USG). Participants were in the free-living (FL) condition for the first three consecutive days, and then in a euhydrated (EUH) state (USGRESULTS: There were no interactions between FL and EUH with morning and afternoon in USG (Morning-FL, 1.017±0.005; Afternoon-FL, 1.012±0.006; Morning-EUH, 1.011±0.004; Afternoon-EUH, 1.007±0.004; p=0.390). No statistically significant differences were found between morning and afternoon in both FL and EUH controlled (Morning-FL, 72.7±18.3 kg; Afternoon-FL, 72.0±18.1 kg; Morning-EUH, 72.9±18.1 kg; Afternoon-EUH, 73.1±18.1 kg, p=0.661). CONCLUSION: There is no difference between morning and afternoon body mass, regardless of the hydration status. This means that first morning body mass is no more, or less, accurate than afternoon

The Effect of Dehydration and High-Volume Resistance Exercise on Intracellular and Local Muscular Fluid Shifts - A Pilot Study

Hypertonic hypovolemia (dehydration) could disrupt the balance between extracellular water (ECW) and intracellular water (ICW). Notably, high-volume resistance exercise (RE) accumulates metabolites resulting in acute muscle swelling (increased ICF). However, the impact of hypertonic hypovolemia state on ECW and ICW distribution after RE is not known. PURPOSE: To determine the effect of acute dehydration on fluid balance after RE. METHODS: 7 resistance-trained males completed two identical high-volume RE, separated by two weeks (bilateral leg press and knee extensions exercises [5 sets of 10 repetitions at 80% of 1 repetition maximum]) either in a euhydrated (EH; urine specific gravity [USG] \u3c 1.020) or dehydrated state (DH; USG ≥ 1.020; 24hr fluid fast). Total body water (TBW) and the ratio of ICW to ECW (ICW/ECW) were measured using bioelectrical impedance spectroscopy before (PRE), 1h, and 3h after RE. The rectus femoris thickness (RFT) was imaged using ultrasound at PRE, immediately (IP), 10m, 15m, and 30m after RE. Vastus lateralis samples were collected at PRE, 1h, and 3h and were immediately weighed (Wt) before and after heating at 80°C for 55 minutes. Repeated measures ANOVAs were used to identify the differences, and effect sizes were calculated if p values were trending. RESULTS: A significant (p \u3c 0.05) condition effect was observed for TBW, while a time effect was observed for ICW/ECW and RFT. For TBW, EH (1.00±0.06L) was greater than DH (0.95±0.05L). For ICW/ECW, PRE (1.00±0.00L) was lower than 1h (1.05±0.10L) and 3h (1.03±0.05L), while 1h was greater than PRE and 3h. For RFT, PRE (17.1±0.9mm) was less thick than IP (23.7±0.9mm), 10m (22.3±1.0mm), 15m (22.0±0.9mm), and 30m (21.5±1.0mm) while IP was thicker than all time points. Furthermore, EH (22.8±1.4mm) trended to have thicker RFT than DH (19.9±0.8mm; p=0.082; Cohen’s f = 0.85; large effect size). Additionally, a significant condition x time effect was observed for Wt. For Wt, EH (1.07±0.04mg) had a greater change in muscle weight than DH (1.01±0.06mg) at 1h. CONCLUSION: These results suggest that high volume RE can cause fluid shift from the extracellular to the intracellular compartment (i.e., increase ICW/ECF and RFT) regardless of the hydration status. Intriguingly, at the intramuscular level, it appears that the intramuscular water content after RE is less in dehydrated than euhydrated state (i.e., less changes in Wt)

The Effect of Hydration Status on Sleep Quality: A Pilot Study

Sleep improves muscle recovery and cognitive health and can be impaired by physiological and mental stress. Dehydration can induce stress which leads to sleep impairment and thus could affect the readiness for and recovery from exercise. However, no study has examined the effect of hydration on sleep before and after resistance exercise (RE). PURPOSE: To examine the effect of hydration status on sleep before and after RE. METHODS: 7 resistance-trained men completed two identical RE consisting of bilateral leg press and knee extensions (5 sets of 10 repetitions at 80% of 1 repetition maximum) in a euhydrated state (EU; urine specific gravity (USG) \u3c 1.020) and in a dehydrated state (DE: USG ≥ 1.020). The two conditions were separated by 2 weeks in random order. During DE, participants underwent a 24-hr fluid restriction the day before RE and consumed only 1.5 L water following RE throughout the day. Participants wore a wearable sleep device, and sleep efficiency (SE), light sleep (LS), rapid eye movement (REM), and slow wave sleep (SWS) were measured the night before (PRE) and the night after (POST) RE. A 2X2 ANOVA and effect sizes (ES) were used to detect differences. RESULTS: No significant (p \u3e 0.05) condition x time effect was observed for any sleep parameters. At PRE, a small ES was observed for SE (1.1%; η2 = 0.05) where EU was more efficient than DE. Additionally, a medium ES was observed for LS (26.2%; η2 = 0.09) and SWS (8%; η2 = 0.08) where EU spent more time in these phases than DE, while EU spent less time in the REM phase (-16.4%; η2 = 0.07) than DE. At POST, a small ES was observed for SE (1.3%; η2 = 0.05) where EU was more efficient than DE. Additionally, a medium ES was observed for REM (-35.7%; η2 = 0.07) and SWS (-8.4%; η2 = 0.08) where EU spent less time in these phases than DE, while EU spent more time in the LS phase (18.7%; η2 = 0.09) than DE. CONCLUSION: The pilot data suggests hydration status could influence sleep. Proper fluid intake could help with sleep efficiency and increase time spent in LS and SWS, which are beneficial for muscle and tissue recovery. Intriguingly, inadequate fluid intake could increase the time spent in REM, which might be due to the mental and physical stresses from dehydration and RE. Combined, these data suggest that hydration status could affect the readiness for and recovery from physical stress

The Effect of Hydration on Readiness and Recovery Before and After Resistance Exercise- A Pilot Study

Dehydration can disturb sleep which is essential for the readiness and recovery process. However, the role of hydration on readiness and recovery indicated by low resting heart rate (RHR) and high heart rate variability (HRV) before and after resistance exercise (RE) is not known. PURPOSE: The purpose of this study was to examine the effect of hydration status on readiness and recovery before and after RE. METHODS: Seven resistance-trained men (age: 21±1 years; weight: 77.8±11.0 kg; height: 177.4±5.3 cm) performed a series of RE that included bilateral leg press and knee extensions (5 sets of 10 repetitions at 80% of 1 repetition maximum). Participants completed the same RE twice with 2 weeks in between. Participants completed one trial in a euhydrated state (EUH; urine specific gravity (USG) \u3c 1.020) and the other in a dehydrated state (DEH: USG ≥ 1.020). For the DEH trial, participants were restricted from consuming fluids for 24 hours prior to the RE and were only permitted to drink 1.5 L of water post-exercise for the remainder of the day. For the EUH trial, participants were instructed to consume fluid throughout the day before and the day of RE to maintain euhydration. Data was collected from a wearable sleep device that participants wore to determine recovery by assessing RHR and HRV. Repeated measures ANOVAs were used to identify the differences, and effect size (ES), resulting effects identified as either small (0.2-0.49), medium (0.5-0.79), or large (\u3e0.8) effects, was calculated. RESULTS: There were no differences in RHR between EUH and DEH on the night before (EUH, 63±13 bpm; DEH, 61±11 bpm; ES=0.16) and after RE (EUH, 59±14 bpm; DEH, 58±9 bpm; ES=0.12; p=0.806). No significant difference was found in recovery between EUH and DEH on the night before (EUH, 37±30 au; DEH, 39±25 au; ES=0.05) or the night after (EUH, 38±29 au; DEH, 42±22 au; ES=0.42; p=0.821) RE. HRV were not different between EUH and DEH on the night before (EUH, 55±27 ms; DEH, 60±32 ms; ES=0.16) and after (EUH, 67±38 ms; DEH, 71±23 ms; ES=0.12; p=0947). CONCLUSION: This pilot study showed hydration status did not impact readiness and recovery before and after RE. However, this could be because the few participants resulted in a low statistical power. Therefore, further studies with more participants could be conducted to better determine how hydration affects readiness and recovery

The Effects of Hydration Status on Heart Rate Variability Following Supramaximal Intensity Exercise

Heart rate variability (HRV) is a non-invasive method used to monitor physiological stress via assessment of sympathetic and parasympathetic regulations and can indicate an individual’s recovery and readiness to exercise. Evidence suggests dehydration negatively impacts HRV; however, the influence of hydration status on HRV following supramaximal resistance exercise (RE) is unknown. PURPOSE: To investigate the effect of hydration status on HRV indices following supramaximal intensity RE. METHODS: 14 recreationally resistance-trained men (age, 21 ± 2 years; height, 176.25 ± 5.84 cm; weight, 81.31 ± 12.77 kg) participated in this study. In a randomized, counterbalanced order, participants performed a supramaximal intensity RE protocol in a euhydrated (EUH; urine specific gravity [USG] \u3c 1.020) and a dehydrated (DEH; USG \u3e 1.020) state, with conditions separated by 2 weeks. HRV indices (standard deviation of normal sinus beats [SDNN], root mean square of successive differences between normal heartbeats [RMSSD], high frequency power [HF], low frequency power [LF], LF:HF ratio, standard deviation of Poincaré plot perpendicular to [SD1] and along the line of identity [SD2]) were measured with participants lying in a supine position for 5 minutes in a dark room at baseline, immediately post-, 1hr-, 2hr-, and 3hr post-RE. Repeated measure analysis of variance was used to determine the effect of hydration status on HRV indices at each timepoint, with Bonferroni corrections for post-hoc analysis. RESULTS: RMSSD was significantly higher 1hr post-exercise in EUH (30.69 ± 7.09 ms) compared to DEH (16.31 ± 2.44 ms; p = 0.04). Similarly, HF power was significantly higher 1hr post-exercise in EUH (32.49 ± 4.12 %) compared to DEH (16.63 ± 2.71 %; p \u3c 0.01). In contrast, LF power was lower 1hr post-exercise in EUH (57.74 ± 3.62 %) compared to DEH (75.95 ± 3.42 %; p = 0.02), with LF:HF ratio significantly lower in EUH (2.36 ± 0.62) than DEH (6.21 ± 1.34; p = 0.01). SD1 was significantly greater 1hr post-exercise in EUH (21.74 ± 5.03 ms) than DEH (11.54 ± 1.73 ms; p = 0.04). No significant condition by time effects were observed for SDNN and SD2, or at remaining timepoints. CONCLUSION: These findings indicate that recovery and readiness to exercise are impaired 1hr following supramaximal intensity RE in a dehydrated state. However, impairments were ameliorated 2-3hrs proceeding the RE bout

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead