Decreased Interleukin-4 Release from the Neurons of the Locus Coeruleus in Response to Immobilization Stress

It has been demonstrated that immobilization (IMO) stress affects neuroimmune systems followed by alterations of physiology and behavior. Interleukin-4 (IL-4), an anti-inflammatory cytokine, is known to regulate inflammation caused by immune challenge but the effect of IMO on modulation of IL-4 expression in the brain has not been assessed yet. Here, it was demonstrated that IL-4 was produced by noradrenergic neurons in the locus coeruleus (LC) of the brain and release of IL-4 was reduced in response to IMO. It was observed that IMO groups were more anxious than nontreated groups. Acute IMO (2 h/day, once) stimulated secretion of plasma corticosterone and tyrosine hydroxylase (TH) in the LC whereas these increments were diminished in exposure to chronic stress (2 h/day, 21 consecutive days). Glucocorticoid receptor (GR), TH, and IL-4-expressing cells were localized in identical neurons of the LC, indicating that hypothalamic-pituitary-adrenal- (HPA-) axis and sympathetic-adrenal-medullary- (SAM-) axis might be involved in IL-4 secretion in the stress response. Accordingly, it was concluded that stress-induced decline of IL-4 concentration from LC neurons may be related to anxiety-like behavior and an inverse relationship exists between IL-4 secretion and HPA/SAM-axes activation

IL-4 Inhibits IL-1β-Induced Depressive-Like Behavior and Central Neurotransmitter Alterations

It has been known that activation of the central innate immune system or exposure to stress can disrupt balance of anti-/proinflammatory cytokines. The aim of the present study was to investigate the role of pro- and anti-inflammatory cytokines in the modulation of depressive-like behaviors, the hormonal and neurotransmitter systems in rats. We investigated whether centrally administered IL-1β is associated with activation of CNS inflammatory pathways and behavioral changes and whether treatment with IL-4 could modulate IL-1β-induced depressive-like behaviors and central neurotransmitter systems. Infusion of IL-4 significantly decreased IL-1β-induced anhedonic responses and increased social exploration and total activity. Treatment with IL-4 markedly blocked IL-1β-induced increase in PGE2 and CORT levels. Also, IL-4 reduced IL-1β-induced 5-HT levels by inhibiting tryptophan hydroxylase (TPH) mRNA and activating serotonin transporter (SERT) in the hippocampus, and levels of NE were increased by activating tyrosine hydroxylase (TH) mRNA expression. These results demonstrate that IL-4 may locally contribute to the regulation of noradrenergic and serotonergic neurotransmission and may inhibit IL-1β-induced behavioral and immunological changes. The present results suggest that IL-4 modulates IL-1β-induced depressive behavior by inhibiting IL-1β-induced central glial activation and neurotransmitter alterations. IL-4 reduced central and systemic mediatory inflammatory activation, as well as reversing the IL-1β-induced alterations in neurotransmitter levels. The present findings contribute a biochemical pathway regulated by IL-4 that may have therapeutic utility for treatment of IL-1β-induced depressive behavior and neuroinflammation which warrants further study

Reliability of DEXA on Body Composition in Korean Athletes

PURPOSE: The purpose of this study was to assess the reliability of DEXA for measuring body composition in Korean Athletes. METHODS: Twenty-nine athletes (n=29) registered for the college athlete program voluntarily participated in the study. Participants’ height and weight were measured, and BMI (Body Mass Index) was calculated before the participants’ body composition was measured. Muscle mass (kg), lean mass (kg), bone mineral density (BMC) (g·cm-2), and total fat mass (kg) of each participant was assessed by DEXA lunar DPX-L (GE Lunar, Madison, USA) for four times within a day to examine the difference by time frames. Four trials consist of ‘early in the morning × 2 with fasting’ with 30min break between two trials, ‘after lunch × 2’ with 30 min break between the two trials. Intra-class correlation (ICC) was conducted for overall reliability (p\u3c0.05) and a repeated measure ANOVA was performed to compare the difference of each trial (p\u3c0.05). RESULTS: The mean ± SD of muscle mass, lean mass, BMC, and fat mass was 56.4 ± 4.6kg, 59.4 ± 5.0kg, 2.3 ± 0.4g·cm-2, and 9.3 ± 4.8kg respectively. Each trail (mean ± SD) of muscle mass were 56.4 ± 4.7kg, 56.1 ± 4.8kg, 56.5 ± 4.6kg, and 56.4 ± 4.7kg, respectively, lean mass were 59.4 ± 5.1kg, 59.2 ± 5.1kg, 59.5 ± 5.0kg, and 59.4 ± 5.0kg, respectively, BMC were 3.0 ± 0.4g·cm-2, 3.0 ± 0.4g·cm-2, 3.0 ± 0.4g·cm- 2, and 3.0 ± 0.4g·cm-2, respectively, and fat mass were 9.3 ± 4.9kg, 9.2 ± 4.8kg, 9.3 ± 4.9kg, and 9.3 ± 4.9kg, respectively. Reliability of the ICC test showed strong agreement on muscle mass (r=0. 994 and p\u3c0.0001), lean mass (r=0. 995 and p\u3c0.0001), BMC (r=0. 995 and p\u3c0.0001), and fat mass (r=0. 998 and p\u3c0.0001). Cronbach’s alpha were 0.99 (muscle mass), 0.99 (Lean Mass), 0.99 (BMC), and 1.00 (Fat mass). No significant difference between each trial was observed in fat mass (p\u3e0.36). However, there was a significant difference in muscle mass (p\u3c0.001), lean mass (p\u3c0.001), and BMC (p\u3c0.04). CONCLUSION: Although all of the variables showed strong agreement on overall reliability from the ICC test, the reliability for the muscle mass, lean mass, and BMC showed significant differences in different time frame

Examining the Validity of Fitbit Charge HR \u3csup\u3eTM\u3c/sup\u3e for Measuring Heart Rate in Free-Living Conditions

Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activity trackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizes Fitbit’s proprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despite its increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HR using a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Ten healthy college students (8 males; mean age = 26.5 ±5.4 years; mean body mass index (BMI) = 24.5 ±3.23 kg·m2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a day while wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists, respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor were synchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute (bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitors were examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE) of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs (mean ±SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ±18.5 bpm, 72.8 ±16.7 bpm, and 73.9 ±17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominant and dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ±10.9% for FBHR non-dominant and 9.71 ± 12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences in estimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHR monitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not provide an accurate measurement of HR during free-living condition in this study. However, further research is needed to validate these monitors with a larger sample with different population groups. Optical blood flow sensors (i.e. photoplethysmographic techniques) have recently been utilized in wearable activitytrackers. The Fitbit Charge HRTM (FBHR) is one of the widely recognized wearable activity trackers that utilizesFitbit’sproprietary PurePulse optical heart rate (HR) technology to automatically measure wrist-based HR. Despiteits increasing popularity, however, no study to date has addressed the validity of FBHR for measuring HR in free-living conditions. PURPOSE: The purpose of this study was to examine the validity of FBHR for measuring HRusing a chest strap Polar HR monitor (PHR) as a reference measure in free-living conditions. METHODS: Tenhealthy college students (8 males; mean age = 26.5 ±5.4 years; mean body mass index (BMI) = 24.5 ±3.23kg·m2) participated in the study. The participants were asked to perform normal daily activities for 8 hours in a daywhile wearing the PHR (model RS400) on their chest and two FBHRs on their dominant and non-dominant wrists,respectively. HR was recorded every minute and the minute-by-minute HR data from each monitor weresynchronized by time of day. Pearson correlation was used to examine the linearity of average beats-per-minute(bpm) estimated from FBHRs with respect to the PHR. Mean differences in average bpm between the monitorswere examined by a general linear model for repeated measures. Lastly, mean absolute percentage error (MAPE)of minute-by-minute bpm estimated from the FBHRs were calculated against the PHR. RESULTS: Average HRs(mean ±SD) for PHR, FBHR non-dominant, and FBHR dominant were 75.6 ±18.5 bpm, 72.8 ±16.7 bpm, and73.9 ±17.06 bpm, respectively. Pearson correlation coefficients (r) between the PHR and FBHR non-dominantand dominant were r=.805 and r=.793, respectively. MAPE were 9.17 ±10.9% for FBHR non-dominant and 9.71 ±12.4% for FBHR HR dominant. ANOVA and post-hoc analyses with Bonferroni revealed significant differences inestimating HR from FBHR non-dominant wrist (p=.001) and FBHR dominant wrist (p=.001) compared to PHRmonitor. CONCLUSION: The results indicated that the wrist-oriented Fitbit Charge HRTM device does not providean accurate measurement of HR during free-living condition in this study. However, further research is needed tovalidate these monitors with a larger sample with different population groups

Tetramethyl-O-scutellarin isolated from peels of immature Shiranuhi fruit exhibits anti-inflammatory effects on LPSinduced RAW264.7 cells

Purpose: To investigate the anti-inflammatory activity of the ethanol extract of the immature fruit of a citrus, Shiranuhi, and to identify the active ingredient.Methods: The immature Shiranuhi peel was extracted with 80 % ethanol, and the extract was fractionated with solvents (n-hexane, ethyl acetate and n-butanol) to afford the corresponding fractions and water residue. Among them, the EtOAc-soluble portion was subjected to medium pressure liquid chromatography (MPLC) over a reversed-phase SiO2 column to give compound 1. The isolated compound was identified based on the proton and carbon nuclear magnetic resonance (NMR) spectra. The release of nitric oxide, prostaglandin (PG)E2, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 secreted by mouse macrophages was measured using RAW264.7 cell culture supernatant.Results: Shiranuhi (Korean name, Hallabong) is an important citrus species cultivated in Jeju Island, Korea. A polymethoxyflavonoid (PMF), tetramethyl-O-scutellarin (1), was isolated from the peels of immature Shiranuhi fruit. Upon the evaluation of anti-inflammatory effects, the flavonoid 1 decreased the nitric oxide production in macrophage cells with high efficiency, viz, 50 % inhibition concentration, IC50 of 57.4 μM. Subsequent studies demonstrated that PMF 1 effectively inhibited the generation of PGE2, TNF-α, IL-1β, and IL-6 cytokine in a dose-dependent manner.Conclusion: Tetramethyl-O-scutellarin (1) has been successfully isolated from Shiranuhi species for the first time. Thus, Shiranuhi fruit peel extract containing PMF 1 can potentially be applied as an antiinflammatory ingredient in food or cosmetic industries.Keywords: Shiranuhi fruit, Nitric oxide, Tetramethyl-O-scutellarin, Anti-inflammator

Validity of Optical Blood Flow Heart Rate Monitors

PURPOSE: Validate the Schoche (SC) (RhythmTM), Basis B1 Band (BB) (BASIS Science, Inc.), and Mio Alpha (MA) (Physical Enterprises, Inc.) wireless heart rate monitors. METHODS: Fifteen college students (males, n=11, age=27±5yrs; females, n=4, age=27±6yrs) participated. All participants simultaneously wore the SC on left forearm, the BB on the right wrist, the MA on the left wrist, and Polar HR strap on their chest. Participants’ resting heart rate was measured twice prior to exercise. The exercise protocol consisted of one 30-minute bout of continuous walking and running in which the treadmill speed increased every 5-minutes. The treadmill started at 2 mph and completed at 6 mph, followed by 3 minutes of cool down. HR was recorded every minute from each monitor including the Polar HR monitor as a criterion measure. RESULTS: Average HRs (means ± SD) for Polar HR, SC, MA, and BB were 113±32, 110±34, 117±32, and 111±27. A strong pearson’s correlation coefficient was observed with the SC (r =.88) and the MA (r =.75), but a weak correlation coefficient was found with the BB (r =.41), p\u3e0.01. Corresponding absolute error rates were 6.0±12.5%, 11.7±24.2%, and 18.2±21.3%. ANOVA and post hoc analyses with Bonferroni revealed nonsignificant differences between the SC, MA, and BB (p \u3e 0.05) compared to the Polar HR. CONCLUSION: The results demonstrate that the wireless wrist-oriented heart rate monitors provide an accurate measurement of HR during exercise. However, further research is needed to validate these monitors with a larger sample in different environment

How Accurate Are Wearable Activity Trackers For Measuring Steps?

Wearable activity trackers have become popular for tracking individual’s daily physical activity, but little or no information is available to substantiate the validity of these devices in step counts. PURPOSE: The purpose of this study was to systemically examine the validity of newly developed wearable activity trackers for measuring steps compared to the criterion measure (hand tally) in two different conditions. METHODS: Twenty (28.2±4.8 years) healthy males (n=19) and females (n=17) participated in the study. The participants were fitted with eight wearable activity trackers while walking and running on a treadmill (speeds of 2, 2.5, 3, 3.5, 4, and 5 mph) for 3-minutes at each speed. For overground protocol, participants walked at three-self-determined speeds; gradually becoming faster (slow, normal, and fast) for one lap on an indoor track (200 meter track). The number of actual steps taken was manually tallied by researchers using a hand-tally counter. The monitors included the Basis B1 band (BB), Misfit Shine (MS), Polar Loop (PL), and Jawbone UP (UP) worn on the right wrist; the Nike+Fuelband (NF), Garmin VivoFit (GV), and Fitbit Flex (FF) worn on the left wrist; and Withings Pulse (WP) and Fitbit Zip (FZ) worn with a clip on the waist. Step counts from each monitor were compared with criterion values from manually counted steps. RESULTS: Total step counts (means ±SD) were 329.5±71.0, 267.8±89.9, 290.6±105.1, 326.2 ±73.2, 282.2±85.1, 294.3±85.8, 329.2±70.0, 322.1±75.7, 310.8±82.8, and 318.±76.7, for manual counts, NF, MS, WP, PL, FF, FZ, UP, GV, and BB, respectively. Corresponding absolute error rates (computed as the average absolute value of the individuals’ errors) were 19.8±16.4%, 18.9±12.2%, 17.4±15.8%, 11.3±13.1%, 0.7±1.4%, 4.5±7.8%, 6.6±12.6%, and 3.5±6.0%, respectively. ANOVA and Post hoc analyses with Bonferroni revealed the MS, WP, FZ, UP, GV, and BB were the devices to give non-significant differences (p\u3e .05) compared to the manual step counts, but significant differences were found with NF, PL, and FF. CONCLUSION: The results demonstrate that the waist-oriented trackers, FZ and WP, show the most accuracy in measuring steps. However, promising preliminary findings were observed with the wrist-oriented trackers, BB, UP, and GV

Validity of the iHealth-BP7 and Withings-BP800 Self Measurement Blood Pressure Monitor

PURPOSE: The purpose of this study is to validate the iHealth-BP7 and Withings-BP800 monitors according to the European Society of Hypertension (ESH) International Protocol revision 2010. METHODS: Data from 11 participants (31.6 ± 2.2 years) were initially examined according to the ESH International Protocol for the validation of BP measuring devices. Participants were asked to sit and relax for 10-15 mins with legs uncrossed, and back supported prior to the test. In all participants, sequential left arm measurements were performed by two trained observers using a mercury sphygmomanometer and one supervisor using the device. Collected data were screened according to the ESH protocol RESULTS: The mean differences between the monitor and sphygmomanometer readings were -0.55±3.75 (SBP) and 0.54±3.62 (DBP) for iHealth-BP7 and 3.18±4.37 (SBP) and - 0.35±5.42 (DBP) for Withings-BP800. The iHealth-BP7 monitor passed all of the modified requirements, however the WithingsBP800 did not meet the last phase of the modified protocol. CONCLUSION: The iHealth-BP7 monitor is recommended as a valid home BP monitoring device, however the Withings-BP800 fails to meet the ESH criteria in this study potentially due to the small sample size. Since the ESH protocol requires 33 subjects, further study with additional participants is warranted to determine validation of both devices

Validity of wearable physical activity monitors during activities of daily living

PURPOSE: To evaluate the validity of wearable activity monitors in SPT and EE under free-living environment. PURPOSE: To evaluate the validity of wearable activity monitors in SPT and EEunder free-living environment. METHODS: Thirty-nine (24.9+5.4 years) healthymales (n=26) and females (n=11) participated in this study. Total SPT and EE weremeasured by eight monitors; Nike+Fuel Band SE (NFB), Garmin VivoFit (VF), MisfitShine (MF), Fitbit Flex (FF), Jawbone UP (JU), Basis B1 (BB1), Polar Loop (PL), andSense Wear Armband Mini (SWA). The monitors were worn for at least 23 hours to beincluded in final data analysis and no PA restriction was applied. The SWA and a sleeplog were used as a criterion measure for SPT and EE, respectively. RESULTS: Total 24hours of EE (Kcal) (means±SD) were 3234.51+977, 2352.2 ±423, 2291.4±567,2679.8±752, 1955.4±251, 2950.9±864, 2724.9 ±627, 2822.1±525 for SWA, VF, JU,PL, BB1, FB, NFB, and MF, respectively. Mean absolute percent errors (MAPE) werecalculated (means±SD) 23.4%±8.0, 24.2%±8.8, 14.0% ±9.7, 28.9% ±22.0,17.5%±12.1, 16.9%±12.8, and 17.7%±15.0 for the VF, JU, PL, BB1, FB, NFB, andMF, respectively. SPT in minutes (mean±SD) were 481±83.32, 370.1+86.9,432.9±93.2, 467.7 ±51.2, 440.6±85.7, 424.6±103.3, 480.3±128.6, 436.6±35.3, and436.2±78.2 for the log, SWA, SWA laying down, VF, JU, PL, BB1, FB, and NFB,respectively. MAPE were calculated for SPT (mean±SD) 22.77% ±13.6,12.96±11.510.58% ±25.1, 11.6%±9.3, 18.2%±16.4, 14.6%±7.7, 8.7%±9.3, and13.5%±9.9 for the SWA, SWA laying down, VF, JU, PL, BB1, FB, and MF,respectively. ANOVA and post-hoc analyses with LSD indicated no significantdifferences were found with the FB, NFB, and MF in EE estimates. Additional post-hocanalyses with LSD for SPT revealed no significant difference (P\u3e.05) in all monitorsexcept SWA. CONCLUSION: The present study indicates that the FF, MS, and NFBare the most accurate wearable activity monitors when estimating EE and all monitorsprovide reasonable estimates of sleep period time, except SWA