Ixeris dentata (Thunb) Nakai attenuates cognitive impairment in MPTP-treated mouse model of Parkinson's disease

Purpose: To evaluate the cognition-enhancing effect of Ixeris dentata (Thunb) Nakai in a mouse model of Parkinson's disease (PD). Methods: MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine)-induced mouse model of PD was used to evaluate the effect of Ixeris dentata (IDE) extract on the alteration of behavioral responses using rotarod and passive avoidance tests. The effect of IDE on oxidative stress levels were analyzed based on superoxide dismutase (SOD) and catalase (CAT) enzyme levels, and lipid peroxidation (LPO) in brain tissues. Results: MPTP (20 mg/kg, ip)-induced mice resulted in a significant (p < 0.01) behavioral deficiencies in locomotor behavior (from 53.15 ± 1.01 to 23.56 ± 1.04) and cognitive functions (from 297 ± 2.47 to 201.17 ± 3.23 s) compared with their respective control groups. Administration of IDE (20, 40 and 80 mg/kg, po) for three weeks significantly and dose-dependently improved (p < 0.001 at 80 mg/kg) locomotor and cognitive deficits in MPTP- treated mice. IDE treatment also significantly (p < 0.01 at 80 mg/kg) inhibited decrease in superoxide dismutase and catalase enzyme activities, and lipid peroxides in MPTP-treated mice in brain tissues. Conclusion: IDE exhibits good protection against MPTP-induced behavioral deficits via potential antioxidant defense mechanisms. Therefore, IDE could potentially be developed as a therapeutic approach for the treatment of neurodegenerative diseases. Keywords: Ixeris dentata, Neurodegenerative disease, MPTP, Parkinson's disease, Oxidative stres

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

Fabrication of Optical Modulator Based on Proton Exchange

For the investigation of optical modulator, the optical wave-guide was fabricated on x-cut LiNbO3 substrate using proton exchange method with self-aligned electrode. The electrode pattern was designed using a self-aligned thin film electrode method. After proton exchange process, the wave-guide could be prepared by annealing process to control the width and depth of the optical wave-guide. The initial crossover state of the fabricated 1Вґ2 optical switch was observed with controlling the annealing process variables and the structure of self-aligned thin film electrodes. As the results in the present work, the measured cross talk and minimum detectable switching voltage were obtained at the values of -29.5dB and 8.0V, respectively, with good merits

Carpal Tunnel Syndrome Caused by Space Occupying Lesions

PURPOSE: To evaluate the diagnosis and treatment of the carpal tunnel syndrome (CTS) due to space occupying lesions (SOL). MATERIALS and METHODS: Eleven patients and 12 cases that underwent surgery for CTS due to SOL were studied retrospectively. We excluded SOL caused by bony lesions, such as malunion of distal radius fracture, volar lunate dislocation, etc. the average age was 51 years. There were 3 men and 8 women. Follow-up period was 12 to 40 months with an average of 18 months. the diagnosis of CTS was made clinically and electrophysiologically. in patients with swelling or tenderness on the area of wrist flexion creases, magnetic resonance imaging (MRI) and/or computed tomogram (CT) were additionally taken as well as the carpal tunnel view. We performed conventional open transverse carpal ligament release and removal of SOL. RESULTS: the types of lesion confirmed by pathologic examination were; tuberculosis tenosynovitis in 3 cases, nonspecific tenosynovitis in 2 cases, and gout in one case. Other SOLs were tumorous condition in five cases, and abnormal palmaris longus hypertrophy in 1 case. Tumorous conditions were due to calcifying mass in 4 cases and ganglion in 1 case. Following surgery, all cases showed alleviation of symptom without recurrence or complications. CONCLUSION: in cases with swelling or tenderness on the area of wrist flexion creases, it is important to obtain a carpal tunnel view, and MRI and/or CT should be supplemented in order to rule out SOLs around the carpal tunnel, if necessary.ope

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

Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.11Ysciescopu