Research progress in cardiotoxicity of organophosphate esters.

Organophosphate esters (OPEs) have been extensively utilized worldwide as a substitution for brominated flame retardants. With an increased awareness of the need for environmental protection, the potential health risks and ecological hazards of OPEs have attracted widespread attention. As the dynamic organ of the circulatory system, the heart plays a significant role in maintaining normal life activities. Currently, there is a lack of systematic appraisal of the cardiotoxicity of OPEs. This article summarized the effects of OPEs on the morphological structure and physiological functions of the heart. It is found that these chemicals can lead to pericardial edema, abnormal looping, and thinning of atrioventricular walls in the heart, accompanied by alterations in heart rate, with toxic effects varying by the OPE type. These effects are primarily associated with the activation of endoplasmic reticulum stress response, the perturbation of cytoplasmic and intranuclear signal transduction pathways in cardiomyocytes. This paper provides a theoretical basis for further understanding of the toxic effects of OPEs and contributes to environmental protection and OPEs' ecological risk assessment.

The progress of research into pseudophosphatases.

Pseudophosphatases are a class of phosphatases that mutate at the catalytically active site. They play important parts in many life processes and disorders, e.g., cell apoptosis, stress reaction, tumorigenesis, axon differentiation, Charcot-Marie-Tooth, and metabolic dysfunction. The present review considers the structures and action types of pseudophosphatases in four families, protein tyrosine phosphatases (PTPs), myotube protein phosphatases (MTMs), phosphatases and tensin homologues (PTENs) and dual specificity phosphatases (DUSPs), as well as their mechanisms in signaling and disease. We aimed to provide reference material for the research and treatment of related diseases.

Identification of pimavanserin tartrate as a potent Ca2+-calcineurin-NFAT pathway inhibitor for glioblastoma therapy.

Glioblastoma multiforme (GBM) is the most common and malignant type of primary brain tumor, and 95% of patients die within 2 years after diagnosis. In this study, aiming to overcome chemoresistance to the first-line drug temozolomide (TMZ), we carried out research to discover a novel alternative drug targeting the oncogenic NFAT signaling pathway for GBM therapy. To accelerate the drug's clinical application, we took advantage of a drug repurposing strategy to identify novel NFAT signaling pathway inhibitors. After screening a set of 93 FDA-approved drugs with simple structures, we identified pimavanserin tartrate (PIM), an effective 5-HT2A receptor inverse agonist used for the treatment of Parkinson's disease-associated psychiatric symptoms, as having the most potent inhibitory activity against the NFAT signaling pathway. Further study revealed that PIM suppressed STIM1 puncta formation to inhibit store-operated calcium entry (SOCE) and subsequent NFAT activity. In cellula, PIM significantly suppressed the proliferation, migration, division, and motility of U87 glioblastoma cells, induced G1/S phase arrest and promoted apoptosis. In vivo, the growth of subcutaneous and orthotopic glioblastoma xenografts was markedly suppressed by PIM. Unbiased omics studies revealed the novel molecular mechanism of PIM's antitumor activity, which included suppression of the ATR/CDK2/E2F axis, MYC, and AuroraA/B signaling. Interestingly, the genes upregulated by PIM were largely associated with cholesterol homeostasis, which may contribute to PIM's side effects and should be given more attention. Our study identified store-operated calcium channels as novel targets of PIM and was the first to systematically highlight the therapeutic potential of pimavanserin tartrate for glioblastoma.

CondenseNet with exclusive lasso regularization.

Group convolution has been widely used in deep learning community to achieve computation efficiency. In this paper, we develop CondenseNet-elasso to eliminate feature correlation among different convolution groups and alleviate neural network's overfitting problem. It applies exclusive lasso regularization on CondenseNet. The exclusive lasso regularizer encourages different convolution groups to use different subsets of input channels therefore learn more diversified features. Our experiment results on CIFAR10, CIFAR100 and Tiny ImageNet show that CondenseNets-elasso are more efficient than CondenseNets and other DenseNet' variants.

Heart rate variability monitoring for emotion and disorders of emotion.

BACKGROUND: Emotion is composed of cognitive processing, physiological response and behavioral reaction. Heart rate variability (HRV) refers to the fluctuations between consecutive heartbeat cycles, and is considered as a non-invasive method for evaluating cardiac autonomic function. HRV analysis plays an important role in emotional study and detection. OBJECTIVE: In this paper, the physiological foundation of HRV is briefly described, and then the relevant literature relating to HRV-based emotion studies for the performance of HRV in different emotions, emotion recognition, the evaluation of emotional disorders, HRV biofeedback, as well as HRV-based emotion analysis and management enhanced by wearable devices, are reviewed. SIGNIFICANCE: It is suggested that HRV is an effective tool for the measurement and regulation of emotional response, with a broad application prospect.

The online monitoring and assessment of thallium stress using oxygen consumption rate and carbon dioxide excretion rate of zebrafish (Danio rerio).

An online monitoring and assessment system of metabolism to measure oxygen consumption rate (OC) and carbon dioxide (CO2) excretion rate (CR) of zebrafish (Danio rerio) was used to illustrate changes in stressful states in 15 days' (360 h) 0.1 µg/L Tl exposure. Tl had a significant inhibition on zebrafish OC and CR (p < 0.01). OC was more suitable for Tl stress assessment than CR, considering that the OC response was more stable and discernible from the control comparing with CR. However, CR is a suitable alternative to characterize toxic effects on different metabolic substrates. Both OC and CR were integrated to present the respiratory quotient (RQ) analysis. RQ was efficient in differentiating between CO2 produced by respiration in the control group (RQ less than 0.7) and CO2 used for urination or stored in tissues after Tl exposure (some RQs larger than 1.0). Circadian rhythm was observed in RC and CR in the controls and persisted in 0.1 µg/L Tl treatments. The rhythm was relatively more disordered in CR. OC and CR would be suitable for indicating physiological stress in the online system as sensitive physiological indices.

Toxic responses of zebrafish (Danio rerio) to thallium and deltamethrin characterized in the electrocardiogram.

The electrocardiogram (ECG) has been widely used to objectively address the physical condition as an index of stress. Though a numerous accounts of investigations on aquatic organisms' ECGs have been made, differentiation of ECG parameters in responding to specific toxic chemicals has not been extensively studied. In this research, it is hypothesized that zebrafish (Danio rerio) ECG parameters would differently respond to different types of pollutants, a heavy metal, thallium (Tl, 0.10 and 13.00 µg/L) and an organic chemical, deltamethrin (DM, 0.52 and 2.00 µg/L). Based on the SOM training and statistical analyses, QRS complex could be specified as an indicator of Tl stress, while QT interval might be used to evaluate DM stress. Pearson correlation analysis indicated that QRS complex and QT interval were significantly associated with Tl stress (r = 0.854, p = 0.0002) and DM stress (r = 0.792, p = 0.001), respectively. QRS complex and QT interval had the highest R2, the minimum of SSE and the lowest AIC value in Tl and DM treatments, respectively. Bases on the current experimental results and previous reports, QRS complex and QT interval could be considered as a specific indicator of Tl and DM disturbances in the environment, respectively.

Increased pulse wave transit time after percutaneous coronary intervention procedure in CAD patients.

Pulse wave transit time (PWTT) has been widely used as an index in assessing arterial stiffness. Percutaneous coronary intervention (PCI) is usually applied to the treatment of coronary artery disease (CAD). Research on the changes in PWTT caused by PCI is helpful for understanding the impact of the PCI procedure. In addition, effects of stent sites and access sites on the changes in PWTT have not been explored. Consequently, this study aimed to provide this information. The results showed that PWTT significantly increased after PCI (p < 0.01) while the standard deviation (SD) of PWTT time series had no statistically significant changes (p = 0.60) between before and after PCI. Significantly increased PWTT was found in the radial access group (p < 0.01), while there were no significant changes in the femoral access group (p > 0.4). Additionally, PWTT in the left anterior descending (LAD) group significantly increased after PCI (p < 0.01), but the increase that was found in the right coronary artery (RCA) group was not significant (p > 0.1). Our study indicates that arterial elasticity and left ventricular functions can benefit from a successful PCI procedure, and the increase of peripheral PWTT after PCI can help to better understand the effectiveness of the procedure.

Cadmium stress assessment based on the electrocardiogram characteristics of zebra fish (Danio rerio): QRS complex could play an important role.

The electrocardiogram (ECG) of zebra fish (Danio rerio) expresses cardiac features that are similar to humans. Here we use sharp microelectrode measurements to obtain ECG characteristics in adult zebra fish and analyze the effects of cadmium chloride (CdCl2) on the heart. We observe the overall changes of ECG parameters in different treatments (0.1 TU, 0.5 TU and 1.0 TU CdCl2), including P wave, Q wave, R wave, S wave, T wave, PR interval (atrial contraction), QRS complex (ventricular depolarization), ST segment, and QT interval (ventricular repolarization). The trends of the ECG parameters showed some responses to the concentration and exposure time of CdCl2, but it was difficult to obtain more information about the useful indicators in water quality assessment depending on tendency analysis alone. A self-organizing map (SOM) showed that P values, R values, and T values were similar; R wave and T wave amplitude were similar; and most important, QRS value was similar to the CdCl2 stress according to the classified data patterns including CdCl2 stress (E) and ECG components based on the Ward linkage. It suggested that the duration of QRS complex was related to environmental stress E directly. The specification and evaluation of ECG parameters in Cd2+ pollution suggested that there is a markedly significant correlation between QRS complex and CdCl2 stress with the highest r (0.729) and the smallest p (0.002) among all ECG characteristics. In this case, it is concluded that QRS complex can be used as an indicator in the CdCl2 stress assessment due to the lowest AIC data abased on the linear regression model between the CdCl2 stress and ECG parameters.

Area asymmetry of heart rate variability signal.

BACKGROUND: Heart rate fluctuates beat-by-beat asymmetrically which is known as heart rate asymmetry (HRA). It is challenging to assess HRA robustly based on short-term heartbeat interval series. METHOD: An area index (AI) was developed that combines the distance and phase angle information of points in the Poincaré plot. To test its performance, the AI was used to classify subjects with: (i) arrhythmia, and (ii) congestive heart failure, from the corresponding healthy controls. For comparison, the existing Porta's index (PI), Guzik's index (GI), and slope index (SI) were calculated. To test the effect of data length, we performed the analyses separately using long-term heartbeat interval series (derived from >3.6-h ECG) and short-term segments (with length of 500 intervals). A second short-term analysis was further carried out on series extracted from 5-min ECG. RESULTS: For long-term data, SI showed acceptable performance for both tasks, i.e., for task i p < 0.001, Cohen's d = 0.93, AUC (area under the receiver-operating characteristic curve) = 0.86; for task ii p < 0.001, d = 0.88, AUC = 0.75. AI performed well for task ii (p < 0.001, d = 1.0, AUC = 0.78); for task i, though the difference was statistically significant (p < 0.001, AUC = 0.76), the effect size was small (d = 0.11). PI and GI failed in both tasks (p > 0.05, d < 0.4, AUC < 0.7 for all). However, for short-term segments, AI indicated better distinguishability for both tasks, i.e., for task i, p < 0.001, d = 0.71, AUC = 0.71; for task ii, p < 0.001, d = 0.93, AUC = 0.74. The rest three measures all failed with small effect sizes and AUC values (d < 0.5, AUC < 0.7 for all) although the difference in SI for task i was statistically significant (p < 0.001). Besides, AI displayed smaller variations across different short-term segments, indicating more robust performance. Results from the second short-term analysis were in keeping with those findings. CONCLUSION: The proposed AI indicated better performance especially for short-term heartbeat interval data, suggesting potential in the ambulatory application of cardiovascular monitoring.

Comparison of heart rate variability between resting state and external-cuff-inflation-and-deflation state: a pilot study.

Heart rate variability (HRV) has been widely used in clinical research to provide an insight into the autonomic control of the cardiovascular system. Measurement of HRV is generally performed under a relaxed resting state. The effects of other conditions on HRV measurement, such as running, mountaineering, head-up tilt, etc, have also been investigated. This study aimed to explore whether an inflation-and-deflation process applied to a unilateral upper arm cuff would influence the HRV measurement. Fifty healthy young volunteers aged between 21 and 30 were enrolled in this study. Electrocardiogram (ECG) signals were recorded for each subject over a five minute resting state followed by a five minute external-cuff-inflation-and-deflation state (ECID state). A one minute gap was scheduled between the two measurements. Consecutive RR intervals in the ECG were extracted automatically to form the HRV data for each of the two states. Time domain (SDNN, RMSSD and PNN50), frequency domain (LFn, HFn and LF/HF) and nonlinear (VLI, VAI and SampEn) HRV indices were analyzed and compared between the two states. In addition, the effects of mean artery pressure (MAP) and heart rate (HR) on the aforementioned HRV indices were assessed for the two states, respectively, by Pearson correlation analysis. The results showed no significant difference in all aforementioned HRV indices between the resting and the ECID states (all p > 0.05). The corresponding HRV indices had significant positive correlation (all p < 0.01) between the two states. None of the indices showed MAP-related change (all p > 0.05) for either state. Besides, none of the indices showed HR-related change (all p > 0.05) for either state except the index of VLI in the resting state. To conclude, this pilot study suggested that the applied ECID process hardly influenced those commonly used HRV indices. It would thus be applicable to simultaneously measure both blood pressure and HRV indices in clinical practice.

Analysis of short-term heart rate and diastolic period variability using a refined fuzzy entropy method.

BACKGROUND: Heart rate variability (HRV) has been widely used in the non-invasive evaluation of cardiovascular function. Recent studies have also attached great importance to the cardiac diastolic period variability (DPV) examination. Short-term variability measurement (e.g., 5 min) has drawn increasing attention in clinical practice, since it is able to provide almost immediate measurement results and enables the real-time monitoring of cardiovascular function. However, it is still a contemporary challenge to robustly estimate the HRV and DPV parameters based on short-term recordings. METHODS: In this study, a refined fuzzy entropy (rFuzzyEn) was developed by substituting a piecewise fuzzy membership function for the Gaussian function in conventional fuzzy entropy (FuzzyEn) measure. Its stability and robustness against additive noise compared with sample entropy (SampEn) and FuzzyEn, were examined by two well-accepted simulation models-the [Formula: see text] noise and the Logistic attractor. The rFuzzyEn was further applied to evaluate clinical short-term (5 min) HRV and DPV of the patients with coronary artery stenosis and healthy volunteers. RESULTS: Simulation results showed smaller fluctuations in the rFuzzyEn than in SampEn and FuzzyEn values when the data length was decreasing. Besides, rFuzzyEn could distinguish the simulation models with different amount of additive noise even when the percentage of additive noise reached 60%, but neither SampEn nor FuzzyEn showed comparable performance. Clinical HRV analysis did not indicate any significant differences between the patients with coronary artery disease and the healthy volunteers in all the three mentioned entropy measures (all p > 0.20). But clinical DPV analysis showed that the patient group had a significantly higher rFuzzyEn (p < 0.01) than the healthy group. However, no or less significant difference was observed between the two groups in either SampEn (p = 0.14) or FuzzyEn (p = 0.05). CONCLUSIONS: Our proposed rFuzzyEn outperformed conventional SampEn and FuzzyEn in terms of both stability and robustness against additive noise, particularly when the data set was relatively short. Analysis of DPV using rFuzzyEn may provide more valuable information to assess the cardiovascular states than the other entropy measures and has a potential for clinical application.