Neuron-immunity communication: mechanism of neuroprotective effects in EGCG.

Epigallocatechin gallate (EGCG), a naturally occurring active ingredient unique to tea, has been shown to have neuroprotective potential. There is growing evidence of its potential advantages in the prevention and treatment of neuroinflammation, neurodegenerative diseases, and neurological damage. Neuroimmune communication is an important physiological mechanism in neurological diseases, including immune cell activation and response, cytokine delivery. EGCG shows great neuroprotective potential by modulating signals related to autoimmune response and improving communication between the nervous system and the immune system, effectively reducing the inflammatory state and neurological function. During neuroimmune communication, EGCG promotes the secretion of neurotrophic factors into the repair of damaged neurons, improves intestinal microenvironmental homeostasis, and ameliorates pathological phenotypes through molecular and cellular mechanisms related to the brain-gut axis. Here, we discuss the molecular and cellular mechanisms of inflammatory signaling exchange involving neuroimmune communication. We further emphasize that the neuroprotective role of EGCG is dependent on the modulatory role between immunity and neurology in neurologically related diseases.

Performance of heart rate adjusted heart rate variability for risk stratification of sudden cardiac death.

PURPOSE: As a non-invasive tool for the assessment of cardiovascular autonomic function, the predictive value of heart rate variability (HRV) for sudden cardiac death (SCD) risk stratification remains unclear. In this study, we investigated the performance of the individualized heart rate (HR) adjusted HRV (HRVI) for SCD risk stratification in subjects with diverse risks. METHODS: A total of 11 commonly used HRV metrics were analyzed in 192 subjects, including 88 healthy controls (low risk group), 82 hypertrophic cardiomyopathy (HCM) patients (medium risk group), and 22 SCD victims (high risk group). The relationship between HRV metrics and HR was examined with long-term and short-term analysis. The performance HRVI was evaluated by area under the receiver operating characteristic curve (AUC) and covariance of variation (CV). RESULTS: Most of the HRV metrics were exponentially decayed with the increase of HR, while the exponential power coefficients were significantly different among groups. The HRVI metrics discriminated low, medium and high risk subjects with a median AUC of 0.72[0.11], which was considerably higher than that of the traditional long-term (0.63[0.04]) and short-term (0.58[0.05]) HRV without adjustment. The average CV of the HRVI metrics was also significantly lower than traditional short-term HRV metrics (0.09 ± 0.02 vs. 0.24 ± 0.13, p < 0.01). CONCLUSIONS: Subjects with diverse risks of SCD had similar exponential decay relationship between HRV metrics and HR, but with different decaying rates. HRVI provides reliable and robust estimation for risk stratification of SCD.

[Development of Human Vital Signs and Body Posture Monitoring and Positioning Alarm Systems].

In view of the high incidence of malignant diseases such as malignant arrhythmias in the elderly population, accidental injuries such as falls, and the problem of no witnesses when danger occurs, the study developed a human vital signs and body posture monitoring and positioning alarm system. Through the collection and analysis of electrocardiogram (ECG), respiration (RESP) and acceleration (ACC) signals, the system monitors human vital signs and body posture in real time, automatically judges critical states such as malignant arrhythmias and accidental falls on the local device side, and then issues alarm information, opens the positioning function, and uploads physiological information and patient location information through 4G communication. Experiments have shown that the system can accurately determine the occurrence of ventricular fibrillation and falls, and issue position and alarm information.

[A heart rate detection method for wearable electrocardiogram with the presence of motion interference].

The dynamic electrocardiogram (ECG) collected by wearable devices is often corrupted by motion interference due to human activities. The frequency of the interference and the frequency of the ECG signal overlap with each other, which distorts and deforms the ECG signal, and then affects the accuracy of heart rate detection. In this paper, a heart rate detection method that using coarse graining technique was proposed. First, the ECG signal was preprocessed to remove the baseline drift and the high-frequency interference. Second, the motion-related high amplitude interference exceeding the preset threshold was suppressed by signal compression method. Third, the signal was coarse-grained by adaptive peak dilation and waveform reconstruction. Heart rate was calculated based on the frequency spectrum obtained from fast Fourier transformation. The performance of the method was compared with a wavelet transform based QRS feature extraction algorithm using ECG collected from 30 volunteers at rest and in different motion states. The results showed that the correlation coefficient between the calculated heart rate and the standard heart rate was 0.999, which was higher than the result of the wavelet transform method ( r = 0.971). The accuracy of the proposed method was significantly higher than the wavelet transform method in all states, including resting (99.95% vs. 99.14%, P < 0.01), walking (100% vs. 97.26%, P < 0.01) and running (100% vs. 90.89%, P < 0.01). The absolute error [0 (0, 1) vs. 1 (0, 1), P < 0.05] and relative error [0 (0, 0.59) vs. 0.52 (0, 0.72), P < 0.05] of the proposed method were significantly lower than the wavelet transform method during running state. The method presented in this paper shows high accuracy and strong anti-interference ability, and is potentially used in wearable devices to realize real-time continuous heart rate monitoring in daily activities and exercise conditions.

Combining multiple ECG features does not improve prediction of defibrillation outcome compared to single features in a large population of out-of-hospital cardiac arrests.

INTRODUCTION: Quantitative electrocardiographic (ECG) waveform analysis provides a noninvasive reflection of the metabolic milieu of the myocardium during resuscitation and is a potentially useful tool to optimize the defibrillation strategy. However, whether combining multiple ECG features can improve the capability of defibrillation outcome prediction in comparison to single feature analysis is still uncertain. METHODS: A total of 3828 defibrillations from 1617 patients who experienced out-of-hospital cardiac arrest were analyzed. A 2.048-s ECG trace prior to each defibrillation without chest compressions was used for the analysis. Sixteen predictive features were optimized through the training dataset that included 2447 shocks from 1050 patients. Logistic regression, neural network and support vector machine were used to combine multiple features for the prediction of defibrillation outcome. Performance between single and combined predictive features were compared by area under receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and prediction accuracy (PA) on a validation dataset that consisted of 1381 shocks from 567 patients. RESULTS: Among the single features, mean slope (MS) outperformed other methods with an AUC of 0.876. Combination of complementary features using neural network resulted in the highest AUC of 0.874 among the multifeature-based methods. Compared to MS, no statistical difference was observed in AUC, sensitivity, specificity, PPV, NPV and PA when multiple features were considered. CONCLUSIONS: In this large dataset, the amplitude-related features achieved better defibrillation outcome prediction capability than other features. Combinations of multiple electrical features did not further improve prediction performance.

Compressing with dominant hand improves quality of manual chest compressions for rescuers who performed suboptimal CPR in manikins.

OBJECTIVE: The question of whether the placement of the dominant hand against the sternum could improve the quality of manual chest compressions remains controversial. In the present study, we evaluated the influence of dominant vs nondominant hand positioning on the quality of conventional cardiopulmonary resuscitation (CPR) during prolonged basic life support (BLS) by rescuers who performed optimal and suboptimal compressions. METHODS: Six months after completing a standard BLS training course, 101 medical students were instructed to perform adult single-rescuer BLS for 8 minutes on a manikin with a randomized hand position. Twenty-four hours later, the students placed the opposite hand in contact with the sternum while performing CPR. Those with an average compression depth of less than 50 mm were considered suboptimal. RESULTS: Participants who had performed suboptimal compressions were significantly shorter (170.2 ± 6.8 vs 174.0 ± 5.6 cm, P = .008) and lighter (58.9 ± 7.6 vs 66.9 ± 9.6 kg, P < .001) than those who performed optimal compressions. No significant differences in CPR quality were observed between dominant and nondominant hand placements for these who had an average compression depth of greater than 50 mm. However, both the compression depth (49.7 ± 4.2 vs 46.5 ± 4.1 mm, P = .003) and proportion of chest compressions with an appropriate depth (47.6% ± 27.8% vs 28.0% ± 23.4%, P = .006) were remarkably higher when compressing the chest with the dominant hand against the sternum for those who performed suboptimal CPR. CONCLUSIONS: Chest compression quality significantly improved when the dominant hand was placed against the sternum for those who performed suboptimal compressions during conventional CPR.

Water extract of the fungi from Fuzhuan brick tea improves the beneficial function on inhibiting fat deposition.

Fuzhuan brick tea (FBT) is traditionally consumed by the ethnic group in the border region of northwest China. The unique yellow fungal (Eurotium cristatum) growth phase is considered to be the key process point in the manufacture of the brick tea. The fungi from FBT are not only strongly correlated to the quality of brick tea, but also have the potential function of preventing obesity. The water extract of fungi (100 µg/mL) can significantly inhibit fat deposition in 3T3-L1 adipocyte and Caenorhabditis elegans. Furthermore, the inhibition of 3T3-L1 adipocyte formation was not due to the suppression on cell viability.

Improvement of Theaflavins on Glucose and Lipid Metabolism in Diabetes Mellitus.

In diabetes mellitus, disordered glucose and lipid metabolisms precipitate diverse complications, including nonalcoholic fatty liver disease, contributing to a rising global mortality rate. Theaflavins (TFs) can improve disorders of glycolipid metabolism in diabetic patients and reduce various types of damage, including glucotoxicity, lipotoxicity, and other associated secondary adverse effects. TFs exert effects to lower blood glucose and lipids levels, partly by regulating digestive enzyme activities, activation of OATP-MCT pathway and increasing secretion of incretins such as GIP. By the Ca2+-CaMKK ꞵ-AMPK and PI3K-AKT pathway, TFs promote glucose utilization and inhibit endogenous glucose production. Along with the regulation of energy metabolism by AMPK-SIRT1 pathway, TFs enhance fatty acids oxidation and reduce de novo lipogenesis. As such, the administration of TFs holds significant promise for both the prevention and amelioration of diabetes mellitus.

Evaluation of functional and electrical features of automatic external defibrillators in extreme altitude and temperature environments.

Aims: Human exposure to high-altitude and/or low-temperature areas is increasing and cardiac arrest in these circumstances represents an increasing proportion of all treated cardiac arrests. However, little is known about the performance of automated external defibrillators (AED) in these circumstances. The objective of this study is to assess the functional and electrical features of 6 commercially available AEDs in extreme environments. Methods: Accuracy of shockable rhythm detection, the time required for self-test, rhythm analysis, and capacitor charging, together with total energy, peak voltage, peak current, and phasic duration of defibrillation waveform measured after placing the AEDs in simulated high-altitude, simulated low-temperature, and natural composite high-altitude and low-temperature environment for 30 min, were compared to those measured in the standard environment. Results: All of the shockable rhythms were correctly detected and all of the defibrillation shocks were successfully delivered by the AEDs. However, the time required for self-test, rhythm detection, and capacitor charging was shortened by 1.2% (3 AEDs, maximum 12.4%) in the simulated high-altitude environment, was prolonged by 3.6% (4 AEDs, maximum 40.8%) in the simulated low-temperature environment, and was prolonged by 4.1% (5 AEDs, maximum 52.1%) in the natural environment. Additionally, the total delivered energy was decreased by 2.5% (2 AEDs, maximum 6.8%) in the natural environment. Conclusion: All of the investigated AEDs functioned properly in simulated and natural environments, but a large variation in the functional and electrical feature change was observed. When performing cardiopulmonary resuscitation in extreme environments, the impact of environmental factors may need consideration.

Single-cell transcriptomic analysis reveals transcript enrichment in oxidative phosphorylation, fluid sheer stress, and inflammatory pathways in obesity-related glomerulopathy.

Obesity-related glomerulopathy (ORG) is an independent risk factor for chronic kidney disease and even progression to end-stage renal disease. Efforts have been undertaken to elucidate the mechanisms underlying the development of ORG and substantial advances have been made in the treatment of ORG, but relatively little is known about cell-specific changes in gene expression. To define the transcriptomic landscape at single-cell resolution, we analyzed kidney samples from four patients with ORG and three obese control subjects without kidney disease using single-cell RNA sequencing. We report for the first time that immune cells, including T cells and B cells, are decreased in ORG patients. Further analysis indicated that SPP1 was significantly up-regulated in T cells and B cells. This gene is related to inflammation and cell proliferation. Analysis of differential gene expression in glomerular cells (endothelial cells, mesangial cells, and podocytes) showed that these cell types were mainly enriched in genes related to oxidative phosphorylation, cell adhesion, thermogenesis, and inflammatory pathways (PI3K-Akt signaling, MAPK signaling). Furthermore, we found that the podocytes of ORG patients were enriched in genes related to the fluid shear stress pathway. Moreover, an evaluation of cell-cell communications revealed that there were interactions between glomerular parietal epithelial cells and other cells in ORG patients, with major interactions between parietal epithelial cells and podocytes. Altogether, our identification of molecular events, cell types, and differentially expressed genes may facilitate the development of new preventive or therapeutic approaches for ORG.

Effects of the Taste Substances and Metal Cations in Green Tea Infusion on the Turbidity of EGCG-Mucin Mixtures.

Astringency has an important impact on the taste quality of tea infusion, a process which occurs when polyphenols complex with salivary proteins to form an impermeable membrane. (-)-Epigallocatechin gallate (EGCG) is the main astringent compound found in green tea and mucin is the main protein present in saliva. Determining the turbidity of EGCG-mucin mixtures is an effective method to quantify the astringency intensity of EGCG solutions. In this study, the effects of taste-related, substances present during green tea infusion, on the turbidity of EGCG-mucin mixtures was investigated under the reacting conditions of a pH value of 5.0, at 37 °C, and for 30 min. The results showed that epicatechins, caffeic acid, chlorogenic acid, and gallic acid reduced the turbidity of EGCG-mucin mixtures, while rutin increased turbidity. Metal ions increased the turbidity of EGCG-mucin mixtures. These can be arranged by effectiveness as Al3+ > K+ > Mg2+ > Ca2+. Caffeine, theanine, and sodium glutamate all decreased the turbidity values of EGCG-mucin mixtures, but sucrose had a weak effect. Further experiments confirmed that the turbidity of green tea infusion-mucin mixture indicated the astringent intensity of green tea infusion, and that the turbidity was significantly correlated with the contents of tea polyphenols and EGCG.

Real-time amplitude spectrum area estimation during chest compression from the ECG waveform using a 1D convolutional neural network.

Introduction: Amplitude spectrum area (AMSA) is a well-established measure than can predict defibrillation outcome and guiding individualized resuscitation of ventricular fibrillation (VF) patients. However, accurate AMSA can only be calculated during cardiopulmonary resuscitation (CPR) pause due to artifacts produced by chest compression (CC). In this study, we developed a real-time AMSA estimation algorithm using a convolutional neural network (CNN). Methods: Data were collected from 698 patients, and the AMSA calculated from the uncorrupted signals served as the true value for both uncorrupted and the adjacent corrupted signals. An architecture consisting of a 6-layer 1D CNN and 3 fully connected layers was developed for AMSA estimation. A 5-fold cross-validation procedure was used to train, validate and optimize the algorithm. An independent testing set comprised of simulated data, real-life CC corrupted data, and preshock data was used to evaluate the performance. Results: The mean absolute error, root mean square error, percentage root mean square difference and correlation coefficient were 2.182/1.951 mVHz, 2.957/2.574 mVHz, 22.887/28.649% and 0.804/0.888 for simulated and real-life testing data, respectively. The area under the receiver operating characteristic curve regarding predicting defibrillation success was 0.835, which was comparable to that of 0.849 using the true value of the AMSA. Conclusions: AMSA can be accurately estimated during uninterrupted CPR using the proposed method.

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression.

Anhedonia is a hallmark symptom of depression that often lacks adequate interventions. The translational gap remains in clinical treatments based on neural substrates of anhedonia. Our pilot study found that depressed individuals depended less on goal-directed (GD) reward learning (RL), with reduced reward prediction error (RPE) BOLD signal. Previous studies have found that anhedonia is related to abnormal activities and/or functional connectivities of the central executive network (CEN) and salience network (SN), both of which belong to the goal-directed system. In addition, it was found that real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) could improve the balance between CEN and SN in healthy individuals. Therefore, we speculate that rt-fMRI NF of the CEN and SN associated with the GD system may improve depressive and/or anhedonic symptoms. Therefore, this study (1) will examine individuals with anhedonic depression using GD-RL behavioral task, combined with functional magnetic resonance imaging and computational modeling to explore the role of CEN/SN deficits in anhedonic depression; and (2) will utilize network-based rt-fMRI NF to investigate whether it is feasible to regulate the differential signals of brain CEN/SN of GD system through rt-fMRI NF to alleviate depressive and/or anhedonic symptoms. This study highlights the need to elucidate the intervention effects of rt-fMRI NF and the underlying computational network neural mechanisms.

Evaluation of three approaches used for respiratory measurement in healthy subjects.

Objective. Respiration is one of the critical vital signs of human health status, and accurate respiratory monitoring has important clinical significance. There is substantial evidence that alterations in key respiratory parameters can be used to determine a patient's health status, aid in the selection of appropriate treatments, predict potentially serious clinical events and control respiratory activity. Although various approaches have been developed for respiration monitoring, no definitive conclusions have been drawn regarding the accuracy of these approaches because each has different advantages and limitations. In the present study, we evaluated the performance of three non-invasive respiratory measurement approaches, including transthoracic impedance (IMP), surface diaphragm electromyography-derived respiration (EMGDR) and electrocardiogram-derived respiration (ECGDR), and compared them with the direct measurement of airflow (FLW) in 33 male and 38 female healthy subjects in the resting state.Approach. The accuracy of six key respiratory parameters, including onset of inspiration (Ion), onset of expiration (Eon), inspiratory time (It), expiratory time (Et), respiratory rate (RR) and inspiratory-expiratory ratio (I:E), measured from the IMP, EMGDR and ECGDR, were compared with those annotated from the reference FLW.Main results. The correlation coefficients between the estimated inspiratory volume and reference value were 0.72 ± 0.20 for IMP, 0.62 ± 0.23 for EMGDR and 0.46 ± 0.21 for ECGDR (p< 0.01 among groups). The positive predictive value and sensitivity for respiration detection were 100% and 100%, respectively, for IMP, which were significantly higher than those of the EMGDR (97.2% and 95.5%,p< 0.001) and the ECGDR (96.9% and 90.0%,p< 0.001). Additionally, the mean error (ME) forIon,Eon,It,EtandRRdetection were markedly lower for IMP than for EMGDR and ECGDR (p< 0.001).Significance. Compared with EMGDR and ECGDR, the IMP signal had a higher positive predictive value, higher sensitivity and lower ME for respiratory parameter detection. This suggests that IMP is more suitable for dedicated respiratory monitoring and parameter evaluation.

[Development of a wearable electrocardiogram monitor with recognition of physical activity scene].

To overcome the problems of current electrocardiogram (ECG) tele-monitoring devices used for daily life, according to information fusion thought and by means of wearable technology, we developed a new type of wearable ECG monitor with the capability of physical activity recognition in this paper. The ECG monitor synchronously detected electrocardiogram signal and body acceleration signal, and recognized the scene information of physical activity, and finally determined the health status of the heart. With the advantages of accuracy for measurement, easy to use, comfort to wear, private feelings and long-term continuous in monitoring, this ECG monitor is quite fit for the heart-health monitoring in daily life.

New Perspectives on Sleep Regulation by Tea: Harmonizing Pathological Sleep and Energy Balance under Stress.

Sleep, a conservative evolutionary behavior of organisms to adapt to changes in the external environment, is divided into natural sleep, in a healthy state, and sickness sleep, which occurs in stressful environments or during illness. Sickness sleep plays an important role in maintaining energy homeostasis under an injury and promoting physical recovery. Tea, a popular phytochemical-rich beverage, has multiple health benefits, including lowering stress and regulating energy metabolism and natural sleep. However, the role of tea in regulating sickness sleep has received little attention. The mechanism underlying tea regulation of sickness sleep and its association with the maintenance of energy homeostasis in injured organisms remains to be elucidated. This review examines the current research on the effect of tea on sleep regulation, focusing on the function of tea in modulating energy homeostasis through sickness sleep, energy metabolism, and damage repair in model organisms. The potential mechanisms underlying tea in regulating sickness sleep are further suggested. Based on the biohomology of sleep regulation, this review provides novel insights into the role of tea in sleep regulation and a new perspective on the potential role of tea in restoring homeostasis from diseases.

Theanine Improves High-Dose Epigallocatechin-3-Gallate-Induced Lifespan Reduction in Caenorhabditis elegans.

Epigallocatechin-3-gallate (EGCG) is the most abundant polyphenol in green tea. Our previous report showed that induced hormesis was a critical determinant for the promotion of a healthy lifespan in Caenorhabditis elegans. In the present study, we investigated the anti-aging effects of the main active ingredients in green tea. We found that galloylated catechins (EGCG and epicatechin gallate) could extend the lifespan of C. elegans, while their metabolites (gallic acid, epicatechin, and epigallocatechin) could not. Interestingly, the combination with theanine, not caffeine, could alleviate the adverse effects induced by high-dose EGCG, including the promotion of lifespan and locomotor ability. This was due to the attenuation of the excess production of reactive oxygen species and the activation of DAF-16. These findings will facilitate further studies on the health benefits of tea active components and their interactions.

Estimating the amplitude spectrum area of ventricular fibrillation during cardiopulmonary resuscitation using only ECG waveform.

BACKGROUND: Amplitude spectrum area (AMSA) calculated from ventricular fibrillation (VF) can be used to monitor the effectiveness of chest compression (CC) and optimize the timing of defibrillation. However, reliable AMSA can only be obtained during CC pause because of artifacts. In this study, we sought to develop a method for estimating AMSA during cardiopulmonary resuscitation (CPR) using only the electrocardiogram (ECG) waveform. METHODS: Intervals of 8 seconds ECG and CC-related references, including 4 seconds during CC and an adjacent 4 seconds without CC, were collected before 1,008 defibrillation shocks from 512 out-of-hospital cardiac arrest patients. Signal quality was analyzed based on the irregularity of autocorrelation of VF. If signal quality index (SQI) was high, AMSA would be calculated from the original signal. Otherwise, CC-related artifacts would be constructed and suppressed using the least mean square filter from VF before calculation of AMSA. The algorithm was optimized using 480 training shocks and evaluated using 528 independent testing shocks. RESULTS: Overall, CC resulted in lower SQI [0.15 (0.04-0.61) with CC vs. 0.75 (0.61-0.83) without CC, P<0.01] and higher AMSA [11.2 (7.7-16.2) with CC vs. 7.2 (4.9-10.6) mVHz without CC, P<0.01] values. The predictive accuracy (49.2% vs. 66.5%, P<0.01) and area under the receiver operating characteristic curve (AUC) (0.647 vs. 0.734, P<0.01) were significantly decreased during CC. Using the proposed method, the estimated AMSA was 7.1 (5.0-15.2) mVHz, the predictive accuracy was 67.0% and the AUC was 0.713, which were all comparable with those calculated without CC. CONCLUSIONS: Using the signal quality-based artifact suppression method, AMSA can be reliably estimated and continuously monitored during CPR.

A signal quality assessment-based ECG waveform delineation method used for wearable monitoring systems.

Identifying transient and nonpersistent abnormal electrocardiogram (ECG) waveforms by continuously monitoring the high-risk populations is of great importance for the diagnosis, treatment, and prevention of cardiovascular diseases. In recent years, fabric electrodes have been widely used in wearable devices because of their non-irritating properties and better comfort than traditional AgCl electrodes. However, the motion noise caused by the relative movement between the fabric electrodes and skin affects the quality of ECGs and reduces the accuracy of diagnosis. Therefore, delineating the ECG waveforms that are recorded from wearable devices with varying levels of noise is still challenging. In this study, a signal quality assessment (SQA)-based ECG waveform delineation method that is used for wearable systems was developed. The ECG signal was first preprocessed by a bandpass filter. Five indices, including the multiscale nonlinear amplitude statistical distribution (adSQI1, adSQI2), the proportion of energy-related to T wave (ptSQI), and heart rates computed from R waves and T waves (rHR and tHR, respectively), were then calculated from the preprocessed ECG signal. The signals were classified as good, acceptable, and unacceptable ECGs by combining these indices through the use of a neural network. Subsequently, the R waves or/and T waves were identified for the corresponding feature interpretations based on the SQA results. ECGs that were recorded from the chest belts from 29 volunteers at different activity statuses were divided into 4-s segments. A total of 7133 manually labeled segments were used to derive (4985 segments) and validate (2148 segments) the algorithm. The adSQI1, adSQI2, tHR, and rHR characteristics were significantly different among the good, acceptable, and unacceptable ECGs. The ptSQI value was considerably higher in the good ECGs than in the acceptable and unacceptable ECGs. The ECG segments of different quality levels were classified with an accuracy of 96.74% by using the proposed SQA method. The R waves and T waves were identified with accuracies of 99.95% and 99.57%, respectively, for segments that were classified as acceptable and/or good. The SQA-based ECG waveform delineation method can perform reliable analysis and has the potential to be applied in wearable ECG systems for the early diagnosis and prevention of cardiovascular diseases.

Physiological Dose of EGCG Attenuates the Health Defects of High Dose by Regulating MEMO-1 in Caenorhabditis elegans.

EGCG, as a dietary-derived antioxidant, has been extensively studied for its beneficial health effects. Nevertheless, it induces the transient increase in ROS and leads to the hormetic extension of lifespan. How exactly biology-benefiting effects with the minimum severe adverse are realized remains unclear. Here, we showed that physiological dose of EGCG could help moderate remission in health side effects exposed to high doses, including shortened lifespan, reduced body size, decreased pharyngeal pumping rate, and dysfunctional body movement in C. elegans. Furthermore, we found this result was caused by the physiological dose of EGCG to block the continued ROS accumulation and triggered acclimation responses after stressor removal. Also, in this process, we observed that EGCG downregulated the key redox protein MEMO-1 to activate the feedback loop of NADPH oxidase-mediated redox signaling. Our data indicates that the feedback signal induced by NADPH oxidase may contribute to the health-protective mechanism of dietary polyphenols in vivo.