Search Results (17)

Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article

Background/Objectives: Cardiovascular diseases (CVDs) remain the primary cause of mortality worldwide, underscoring the critical importance of developing accurate early prediction models. In this study, we propose an advanced stacking ensemble learning framework to improve the predictive performance for CVD diagnosis. Methods: The methodology encompasses comprehensive data preprocessing, feature selection, cross-validation, and the construction of a stacking architecture integrating Random Forest (RF), Support Vector Machine (SVM), and CatBoost as base learners. Two meta-learning configurations were examined: Logistic Regression (LR) and a Multilayer Perceptron (MLP). Results: Experimental results indicate that the MLP-based stacking model achieves superior performance, with an accuracy of 97.06%, outperforming existing approaches reported in the literature. Furthermore, the model demonstrates high recall (96.08%) and precision (98%), confirming its robustness and generalization capacity. Conclusions: Compared to individual classifiers and traditional ensemble methods, the proposed approach yields significantly enhanced predictive outcomes, highlighting the potential of deep learning-based stacking strategies in cardiovascular risk assessment. Full article

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, with increasing evidence suggesting that their origins may lie in prenatal life. Endocrine-disrupting chemicals (EDCs), such as bisphenol A (BPA), have been implicated in the alteration of fetal programming mechanisms that cause a predisposition to long-term cardiovascular vulnerability. However, the impact of prenatal endocrine disruption on fetal heart development and its sex-specific nature remains incompletely understood. This study investigates the molecular and structural effects of low-dose prenatal BPA exposure on fetal rat hearts. Our results reveal that BPA disrupts estrogen receptor (ER) signaling in a sex-dependent manner, with distinct alterations in ERα, ERβ, and GPER expression. BPA exposure also triggers significant inflammation, oxidative stress, and ferroptosis; this is evidenced by elevated NF-κB, IL-1β, TNF-α, and NLRP3 inflammasome activation, as well as impaired antioxidant defenses (SOD1, SOD2, CAT, and SELENOT), increased lipid peroxidation (MDA) and protein oxidation, decreased GPX4, and increased ACSL4 levels. These alterations are accompanied by increased markers of cardiac distension (ANP, BNP), extracellular matrix remodeling mediators, and pro-fibrotic regulators (Col1A1, Col3A1, TGF-β, and CTGF), with a more pronounced response in males. Histological analyses corroborated these molecular findings, revealing structural alterations as well as glycogen depletion in male fetal hearts, consistent with altered cardiac morphogenesis and metabolic stress. These effects were milder in females, reinforcing the notion of sex-specific vulnerability. Moreover, prenatal BPA exposure affected myocardial fiber architecture and vascular remodeling in a sex-dependent manner, as evidenced by reduced expression of desmin alongside increased levels of CD34 and Ki67. Overall, our findings provide novel insights into the crucial role of prenatal endocrine disruption during fetal heart development and its contribution to the early origins of CVD, underscoring the urgent need for targeted preventive strategies and further research into the functional impact of BPA-induced alterations on postnatal cardiac function and long-term disease susceptibility. Full article

Silicon nitride (SiN_x) thin film is a promising coating with great physiochemical and optical properties. However, the preparation of films with good comprehensive properties still faces challenges. This study focused on developing a method for the preparation of uniform SiN_x thin film with a controllable refractive index using home-made catalytic chemical vapor deposition (Cat-CVD) equipment. Orthogonal experimental design was employed to investigate the effects of four key influence factors, including reaction pressure, the ratio of SiH₄ to NH₃, the ratio of SiH₄ to H₂, and substrate temperature. The response parameters evaluated were the refractive index, extinction coefficient, uniformity, and deposition rate of SiN_x thin film. Compared with the single-factor variable tests, an orthogonal experiment could obtain the optimal preparation process of the SiN_x thin film with the best comprehensive quality through the least number of experiments. At the same time, the microstructures of SiN_x thin film were analyzed by various characterization methods, including Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM), to research the relationship between preparation factors and the properties of SiN_x thin film. This paper provides the theoretical guidance for fine-regulating the properties of SiNx thin film in practical applications. Full article

Obesity and overweight pose significant risks to health, contributing to the prevalence of chronic conditions like type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD). The current study aimed to assess the impact of a 6-year nutritional and lifestyle intervention on oxidative and inflammatory markers in individuals aged 55 to 75, specifically those at high risk of CVD. A study was carried out in a group of 80 participants with metabolic syndrome (MetS) residing in Mallorca, Spain, who underwent nutritional intervention based on a low-calorie Mediterranean diet (MedDiet) and promotion of physical activity. Before and after the intervention, several parameters including anthropometric data, haematological factors, blood pressure, and physical activity level were measured. Oxidative and inflammatory biomarkers in plasma were analysed. After the 6-year intervention, participants who managed to reduce their body mass index (BMI) had greater reductions in abdominal obesity, waist to heigh ratio (WHtR), diastolic blood pressure, and glucose levels, and increased high density protein cholesterol (HDL-c) compared to those who did not reduce BMI. This higher reduction in BMI was related to reduced energy intake and increased adherence to MedDiet, with greater polyphenol intake, and total physical activity (PA). Furthermore, improvements in oxidative stress and proinflammatory status were observed in participants who reduced their BMI. Significant reductions in the activity of the prooxidant enzyme, myeloperoxidase (MPO), levels of the lipid oxidation marker, malondialdehyde (MDA), and the proinflammatory chemokine, monocyte chemoattractant protein-1 (MCP-1,) were found in those who reduced their BMI. In contrast, participants who did not improve their BMI exhibited higher levels of proinflammatory markers such as MCP-1 and tumour necrosis factor α (TNFα), as well as increased activity of the antioxidant enzyme catalase (CAT). Current findings suggest that an effective way to reduce BMI is a hypocaloric MedDiet combined with tailored physical activity to improve oxidative stress and proinflammatory status, and potentially reducing the risk of CVD. Full article

Despite medical advancements in recent years, cardiovascular diseases (CVDs) remain a major factor in rising mortality rates, challenging predictions despite extensive expertise. The healthcare sector is poised to benefit significantly from harnessing massive data and the insights we can derive from it, underscoring the importance of integrating machine learning (ML) to improve CVD prevention strategies. In this study, we addressed the major issue of class imbalance in the Behavioral Risk Factor Surveillance System (BRFSS) 2021 heart disease dataset, including personal lifestyle factors, by exploring several resampling techniques, such as the Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), SMOTE-Tomek, and SMOTE-Edited Nearest Neighbor (SMOTE-ENN). Subsequently, we trained, tested, and evaluated multiple classifiers, including logistic regression (LR), decision trees (DTs), random forest (RF), gradient boosting (GB), XGBoost (XGB), CatBoost, and artificial neural networks (ANNs), comparing their performance with a primary focus on maximizing sensitivity for CVD risk prediction. Based on our findings, the hybrid resampling techniques outperformed the alternative sampling techniques, and our proposed implementation includes SMOTE-ENN coupled with CatBoost optimized through Optuna, achieving a remarkable 88% rate for recall and 82% for the area under the receiver operating characteristic (ROC) curve (AUC) metric. Full article

Recent cell and animal studies suggest the potential of blackcurrants (BCs; Ribes nigrum) as a dietary agent that may reduce the risk of cardiovascular disease (CVD) by improving dyslipidemia, oxidative stress, and inflammation. This study aimed to examine the effects of BC anthocyanin (ACN) extract supplementation on biomarkers of CVD risk in healthy adult women in menopause transition. The effects of BC ACN supplementation on body composition, fasting blood lipids and biomarkers of inflammation and oxidative stress were evaluated using anthropometric measures and blood samples collected from a pilot randomized controlled clinical trial in peri- and early postmenopausal women. Thirty-eight eligible peri- and early postmenopausal women aged 45–60 completed the entire trial, in which they were randomly assigned into one of three treatment groups: placebo (control group), 392 mg/day (low BC group), or 784 mg/day (high BC group) for six months. The significance of differences in outcomes was tested using repeated-measures ANOVA. Overall, following six-month BC consumption, significantly decreased triglyceride (TG) levels were observed between treatment groups (p < 0.05) in a dose-dependent manner. Plasma interleukin-1β (IL-1β) was significantly reduced in a dose and time dependent manner (p < 0.05). Significant decreases in thiobarbituric acid reactive substances (TBARS) levels were also observed between treatment groups (p < 0.05) in a dose-dependent manner. Six-month change in oxidized LDL was inversely correlated with changes in catalase (CAT) and total antioxidant capacity (TAC) (p < 0.05), while C-reactive protein (hs-CRP) change was positively correlated with changes in TG and IL-1β (p < 0.01). Together, these findings suggest that daily BC consumption for six months effectively improved dyslipidemia, inflammation, and lipid peroxidation, thus potentially mitigating the risk of postmenopausal CVD development in study participants. Future studies with larger sample sizes and at-risk populations are warranted to confirm these findings. Full article

Metabolic syndrome (MetS) significantly increases the risk of cardiovascular diseases (CVD), a leading cause of death globally. The presented study investigated the cardioprotective role of dietary polyphenols found in pomegranate peels in an animal model of metabolic syndrome. Zucker diabetic fatty rats (ZDF, MetS rats, fa/fa) were supplemented with polyphenol-rich pomegranate peel extract (EPP) at two dosages: 100 mg/kg BW and 200 mg/kg BW. The extract was administered for 8 weeks. The effect of ethanolic peel extract on the concentration of oxidative stress markers (CAT, SOD, MnSOD, GR, GST, GPx, TOS, SH, and MDA), biomarkers of heart failure (cTnI, GAL-3), and alternations in tissue architecture was assessed. The results showed a significant increase in SH concentration mediated via EPP supplementation (p < 0.001). Treatment with a 100 mg/kg BW dosage reduced the TOS level more efficiently than the higher dose. Interestingly, the CAT and GST activities were relevantly higher in the MetS 100 group (p < 0.001) compared to the MetS control. The rats administered EPP at a dose of 200 mg/kg BW did not follow a similar trend. No differences in the GR (p = 0.063), SOD (p = 0.455), MnSOD (p = 0.155), and MDA (p = 0.790) concentration were observed after exposure to the pomegranate peel extract. The administration of EPP did not influence the cTnI and GAL-3 levels. Histology analysis of the heart and aorta sections revealed no toxic changes in phenolic-treated rats. The findings of this study prove that the extract from pomegranate peels possesses free radical scavenging properties in the myocardium. The effect on alleviating ventricular remodeling and cardiomyocyte necrosis was not confirmed and requires further investigation. Full article

The antioxidant potential of foods plays a vital role in counteracting oxidative stress and its consequences in the body. Superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) are the primary line of defence against cellular damage caused by reactive oxygen species (ROS). Glutathione is considered to be the most vital antioxidant for the body because its changes during oxidative stress increase the risk of CVD. The dietary antioxidant capacity supporting the glutathione defence system is not known. Therefore, we analysed the glutathione defence-related markers changes in the serum of CVD patients under the dietary supplementation of increased antioxidant capacity snacks. Patients were split into groups according to inclusion criteria and dietary intervention (DI) design. The serum concentration of GPx and GST (glutathione-S-transferase) was measured before and after the 6-week DI. During the DI, CVD and control (CON) subjects increased the total diet antioxidant capacity by 48% and 21%, respectively. It resulted in a significantly decreased GST (from 3.71 to 2.54 U/g Hb, p < 0.05) and an increased GPx (from 33.90 to 38.3 U/L). The results in the CON group did not reveal significant changes in GST and GPx. This study demonstrated that an increased antioxidant capacity might be associated with improving glutathione-related defence. However, the conclusion is not substantial due to the small sample used in this study. Full article

Over the last years, the importance of microRNAs (miRNAs) has increasingly been recognised. Each miRNA is a short sequence of non-coding RNA that influences countless genes’ expression and, thereby, contributes to several physiological pathways and diseases. It has been demonstrated that miRNAs participate in the development of many cardiovascular diseases (CVDs). This review synopsises the most recent studies emphasising miRNA’s influence in several CVDs affecting dogs and cats. It provides a concise outline of miRNA’s biology and function, the diagnostic potential of circulating miRNAs as biomarkers, and their role in different CVDs. It also discusses known and future roles for miRNAs as potential clinical biomarkers and therapeutic targets. So, this review gives a comprehensive outline of the most relevant miRNAs related to CVDs in Veterinary Medicine. Full article

Purpose: Cardiovascular disease (CVD) is a major worldwide health burden. As the risk factors of CVD, hypertension, and hyperlipidemia are most mentioned. Early stage hypertension in the population with dyslipidemia is an important public health hazard. This study was the application of data-driven machine learning (ML), demonstrating complex relationships between risk factors and outcomes and promising predictive performance with vast amounts of medical data, aimed to investigate the association between dyslipidemia and the incidence of early stage hypertension in a large cohort with normal blood pressure at baseline. Methods: This study analyzed annual health screening data for 71,108 people from 2005 to 2017, including data for 27 risk-related indicators, sourced from the MJ Group, a major health screening center in Taiwan. We used five machine learning (ML) methods—stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), least absolute shrinkage and selection operator regression (Lasso), ridge regression (Ridge), and gradient boosting with categorical features support (CatBoost)—to develop a multi-stage ML algorithm-based prediction scheme and then evaluate important risk factors at the early stage of hypertension, especially for groups with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels within or out of the reference range. Results: Age, body mass index, waist circumference, waist-to-hip ratio, fasting plasma glucose, and C-reactive protein (CRP) were associated with hypertension. The hemoglobin level was also a positive contributor to blood pressure elevation and it appeared among the top three important risk factors in all LDL-C/HDL-C groups; therefore, these variables may be important in affecting blood pressure in the early stage of hypertension. A residual contribution to blood pressure elevation was found in groups with increased LDL-C. This suggests that LDL-C levels are associated with CPR levels, and that the LDL-C level may be an important factor for predicting the development of hypertension. Conclusion: The five prediction models provided similar classifications of risk factors. The results of this study show that an increase in LDL-C is more important than the start of a drop in HDL-C in health screening of sub-healthy adults. The findings of this study should be of value to health awareness raising about hypertension and further discussion and follow-up research. Full article

Bromocriptine-QR is a sympatholytic dopamine D2 agonist for the treatment of type 2 diabetes that has demonstrated rapid (within 1 year) substantial reductions in adverse cardiovascular events in this population by as yet incompletely delineated mechanisms. However, a chronic state of elevated sympathetic nervous system activity and central hypodopaminergic function has been demonstrated to potentiate an immune system pro-oxidative/pro-inflammatory condition and this immune phenotype is known to contribute significantly to the advancement of cardiovascular disease (CVD). Therefore, the possibility exists that bromocriptine-QR therapy may reduce adverse cardiovascular events in type 2 diabetes subjects via attenuation of this underlying chronic pro-oxidative/pro-inflammatory state. The present study was undertaken to assess the impact of bromocriptine-QR on a wide range of immune pro-oxidative/pro-inflammatory biochemical pathways and genes known to be operative in the genesis and progression of CVD. Inflammatory peripheral blood mononuclear cell biology is both a significant contributor to cardiovascular disease and also a marker of the body’s systemic pro-inflammatory status. Therefore, this study investigated the effects of 4-month circadian-timed (within 2 h of waking in the morning) bromocriptine-QR therapy (3.2 mg/day) in type 2 diabetes subjects whose glycemia was not optimally controlled on the glucagon-like peptide 1 receptor agonist on (i) gene expression status (via qPCR) of a wide array of mononuclear cell pro-oxidative/pro-inflammatory genes known to participate in the genesis and progression of CVD (OXR1, NRF2, NQO1, SOD1, SOD2, CAT, GSR, GPX1, GPX4, GCH1, HMOX1, BiP, EIF2α, ATF4, PERK, XBP1, ATF6, CHOP, GSK3β, NFkB, TXNIP, PIN1, BECN1, TLR2, TLR4, TLR10, MAPK8, NLRP3, CCR2, GCR, L-selectin, VCAM1, ICAM1) and (ii) humoral measures of sympathetic tone (norepinephrine and normetanephrine), whole-body oxidative stress (nitrotyrosine, TBARS), and pro-inflammatory factors (IL-1β, IL-6, IL-18, MCP-1, prolactin, C-reactive protein [CRP]). Relative to pre-treatment status, 4 months of bromocriptine-QR therapy resulted in significant reductions of mRNA levels in PBMC endoplasmic reticulum stress-unfolded protein response effectors [GRP78/BiP (34%), EIF2α (32%), ATF4 (29%), XBP1 (25%), PIN1 (14%), BECN1 (23%)], oxidative stress response proteins [OXR1 (31%), NRF2 (32%), NQO1 (39%), SOD1 (52%), CAT (26%), GPX1 (33%), GPX4 (31%), GCH1 (30%), HMOX1 (40%)], mRNA levels of TLR pro-inflammatory pathway proteins [TLR2 (46%), TLR4 (20%), GSK3β (19%), NFkB (33%), TXNIP (18%), NLRP3 (32%), CCR2 (24%), GCR (28%)], mRNA levels of pro-inflammatory cellular receptor proteins CCR2 and GCR by 24% and 28%, and adhesion molecule proteins L-selectin (35%) and VCAM1 (24%). Relative to baseline, bromocriptine-QR therapy also significantly reduced plasma levels of norepinephrine and normetanephrine by 33% and 22%, respectively, plasma pro-oxidative markers nitrotyrosine and TBARS by 13% and 10%, respectively, and pro-inflammatory factors IL-18, MCP1, IL-1β, prolactin, and CRP by 21%,13%, 12%, 42%, and 45%, respectively. These findings suggest a unique role for circadian-timed bromocriptine-QR sympatholytic dopamine agonist therapy in reducing systemic low-grade sterile inflammation to thereby reduce cardiovascular disease risk. Full article

Pet ownership, the most common human–animal interaction, is believed to bestow positive health benefits onto pet owners. However, there is limited research on substantiating these assertions. The aim of this review was to systematically identify, evaluate, and summarize primary research on the relationship between cat and/or dog ownership and cardiovascular disease (CVD), type 2 diabetes (T2D), and obesity to inform future research on pet ownership and chronic disease. How pet ownership was defined/measured, and identification of the chronic disease variables and health behaviors most often measured were emphasized. Two researchers independently searched PubMed and Web of Science, where One Health literature are mostly likely to be indexed, for peer-reviewed literature on pet ownership and CVD, T2D, and obesity. A review of 4541 titles and abstracts for relevance resulted in 34 manuscripts eligible for full-text review. Two researchers assessed each eligible manuscript and extracted data only from those that met the inclusion criteria (n = 14). Ten studies on CVD, four studies on obesity, and zero studies on T2D met the study criteria. The CVD and obesity variables varied and were not well described. The relationship between pet ownership and CVD and obesity varied (positive, negative, mixed effects, and no effect). Generalizability lacked across all studies: most studies were with Non-Hispanic White populations. Other areas of weakness were quality of study outcomes and instrument validity. Operationalization of pet ownership varied (from no verification to confirmed pet registration). Integration of the evidence-based influence of the human–animal connection through pet ownership on CVD and obesity may make prevention, mitigation, and treatment strategies more robust. Full article

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD. Methods: Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. We compared them with changes in ACE-2 networks following SARS-CoV-2 infection by analyzing public data of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). This analysis was performed using the Network by Relative Importance (NERI) algorithm, which integrates protein-protein interaction with co-expression networks. We also performed miRNA-target predictions to identify which miRNAs regulate ACE2-related networks and could play a role in the COVID19 outcome. Finally, we performed enrichment analysis for identifying the main COVID-19 risk groups. Results: We found similar ACE2 expression confidence levels in respiratory and cardiovascular systems, supporting that heart tissue is a potential target of SARS-CoV-2. Analysis of ACE2 interaction networks in infected hiPSC-CMs identified multiple hub genes with corrupted signaling which can be responsible for cardiovascular symptoms. The most affected genes were EGFR (Epidermal Growth Factor Receptor), FN1 (Fibronectin 1), TP53, HSP90AA1, and APP (Amyloid Beta Precursor Protein), while the most affected interactions were associated with MAST2 and CALM1 (Calmodulin 1). Enrichment analysis revealed multiple diseases associated with the interaction networks of ACE2, especially cancerous diseases, obesity, hypertensive disease, Alzheimer’s disease, non-insulin-dependent diabetes mellitus, and congestive heart failure. Among affected ACE2-network components connected with the SARS-Cov-2 interactome, we identified AGT (Angiotensinogen), CAT (Catalase), DPP4 (Dipeptidyl Peptidase 4), CCL2 (C-C Motif Chemokine Ligand 2), TFRC (Transferrin Receptor) and CAV1 (Caveolin-1), associated with cardiovascular risk factors. We described for the first time miRNAs which were common regulators of ACE2 networks and virus-related proteins in all analyzed datasets. The top miRNAs regulating ACE2 networks were miR-27a-3p, miR-26b-5p, miR-10b-5p, miR-302c-5p, hsa-miR-587, hsa-miR-1305, hsa-miR-200b-3p, hsa-miR-124-3p, and hsa-miR-16-5p. Conclusion: Our study provides a complete mechanistic framework for investigating the ACE2 network which was validated by expression data. This framework predicted risk groups, including the established ones, thus providing reliable novel information regarding the complexity of signaling pathways affected by SARS-CoV-2. It also identified miRNAs that could be used in personalized diagnosis in COVID-19. Full article

We optimized a silicon nitride (SiN_x) passivation process using a catalytic-chemical vapor deposition (Cat-CVD) system to suppress the current collapse phenomenon of AlGaN/GaN-on-Si high electron mobility transistors (HEMTs). The optimized Cat-CVD SiN_x film exhibited a high film density of 2.7 g/cm³ with a low wet etch rate (buffered oxide etchant (BOE) 10:1) of 2 nm/min and a breakdown field of 8.2 MV/cm. The AlGaN/GaN-on-Si HEMT fabricated by the optimized Cat-CVD SiN_x passivation process, which had a gate length of 1.5 μm and a source-to-drain distance of 6 μm, exhibited the maximum drain current density of 670 mA/mm and the maximum transconductance of 162 mS/mm with negligible hysteresis. We found that the optimized SiN_x film had positive charges, which were responsible for suppressing the current collapse phenomenon. Full article