Characteristics and efficacy of traditional Chinese medicine in the therapeutic strategy of chronic coronary syndrome: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Chronic coronary syndrome (CCS) has always been controversial in its therapeutic strategy. Although invasive treatment and optimal medication therapy (OMT) are the most commonly used treatments, doctors continue to debate the best strategy. However, traditional Chinese medicine (TCM) for CCS is effective clinically. METHODS: To identify potentially eligible observational and experimental studies, we searched Pubmed, the Web of Science, and the China National Knowledge Internet. To be eligible, studies had to report with end-of treatment outcomes, such as major adverse cardiac events (MACE), deaths from myocardial infarctions (MI), all-cause mortality, angina, cardiac mortality, the effectiveness rate of electrocardiographs, and the reduction rate of the Nitroglycerin tablets. Risk differences (RDs) and 95 % confidence intervals (95 % CIs) were calculated based on random-effects models or fixed-effects models. Citation screening, data abstraction, risk assessment, and strength-of-evidence grading were completed by 2 independent reviewers. RESULTS: In Section 1 (13 studies, involving 17,287 patients), showed no significant difference between invasive treatment and medication treatment in MACE (RD = -0.04, 95% CI = -0.08 to 0.00, I2 = 76.4 %), all-cause mortality (RD = -0.01, 95%CI = -0.022 to 0.01, I2 = 73.44 %), MI (RD = 0.00, 95%CI = -0.00 to 0.01, I2 = 0.00 %) and cardiac mortality (RD = 0.00, 95 %CI = -0.01 to 0.01, I2 = 34.9 %). In Section 2 (21 studies, including 1820 patients), compared with WM treatment, TCM + WM treatment increased ECG effectiveness by 18 %, angina effectiveness by 20 %, and stopping or reducing Nitroglycerin tablets by 20 %. In Section 3 (25 studies, including 2859 patients) showed that TCM revealed a better electrocardiogram effective rate (RD = 0.10, 95 %CI = 0.05 to 0.14, I2 = 44.7 %) and angina effective rate (RD = 0.12, 95 %CI = 0.09 to 0.15, I2 = 44.9 %). We identified that TCM treatment properties of "Circulating blood and transforming stasis" and application of warm/heat-properties medicines were frequently used in CCS treatment. CONCLUSIONS: TCM treatment has shown superior beneficial cardioprotective in CCS therapy strategy, among which "Circulating blood and transforming stasis" and the application of warm/heat-properties medicine are its characteristics.

ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments.

Vision-language navigation is a task that requires an agent to follow instructions to navigate in environments. It becomes increasingly crucial in the field of embodied AI, with potential applications in autonomous navigation, search and rescue, and human-robot interaction. In this paper, we propose to address a more practical yet challenging counterpart setting - vision-language navigation in continuous environments (VLN-CE). To develop a robust VLN-CE agent, we propose a new navigation framework, ETPNav, which focuses on two critical skills: 1) the capability to abstract environments and generate long-range navigation plans, and 2) the ability of obstacle-avoiding control in continuous environments. ETPNav performs online topological mapping of environments by self-organizing predicted waypoints along a traversed path, without prior environmental experience. It privileges the agent to break down the navigation procedure into high-level planning and low-level control. Concurrently, ETPNav utilizes a transformer-based cross-modal planner to generate navigation plans based on topological maps and instructions. The plan is then performed through an obstacle-avoiding controller that leverages a trial-and-error heuristic to prevent navigation from getting stuck in obstacles. Experimental results demonstrate the effectiveness of the proposed method. ETPNav yields more than 10% and 20% improvements over prior state-of-the-art on R2R-CE and RxR-CE datasets, respectively. Our code is available at https://github.com/MarSaKi/ETPNav.

SEAOP: a statistical ensemble approach for outlier detection in quantitative proteomics data.

Quality control in quantitative proteomics is a persistent challenge, particularly in identifying and managing outliers. Unsupervised learning models, which rely on data structure rather than predefined labels, offer potential solutions. However, without clear labels, their effectiveness might be compromised. Single models are susceptible to the randomness of parameters and initialization, which can result in a high rate of false positives. Ensemble models, on the other hand, have shown capabilities in effectively mitigating the impacts of such randomness and assisting in accurately detecting true outliers. Therefore, we introduced SEAOP, a Python toolbox that utilizes an ensemble mechanism by integrating multi-round data management and a statistics-based decision pipeline with multiple models. Specifically, SEAOP uses multi-round resampling to create diverse sub-data spaces and employs outlier detection methods to identify candidate outliers in each space. Candidates are then aggregated as confirmed outliers via a chi-square test, adhering to a 95% confidence level, to ensure the precision of the unsupervised approaches. Additionally, SEAOP introduces a visualization strategy, specifically designed to intuitively and effectively display the distribution of both outlier and non-outlier samples. Optimal hyperparameter models of SEAOP for outlier detection were identified by using a gradient-simulated standard dataset and Mann-Kendall trend test. The performance of the SEAOP toolbox was evaluated using three experimental datasets, confirming its reliability and accuracy in handling quantitative proteomics.

Personalized Driver Gene Prediction Using Graph Convolutional Networks with Conditional Random Fields.

Cancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high heterogeneity. Thus, the discovery of driver genes at the individual level is becoming more valuable but is a great challenge. Although there have been some computational methods proposed to tackle this challenge, few can cover all patient samples well, and there is still room for performance improvement. In this study, to identify individual-level driver genes more efficiently, we propose the PDGCN method. PDGCN integrates multiple types of data features, including mutation, expression, methylation, copy number data, and system-level gene features, along with network structural features extracted using Node2vec in order to construct a sample-gene interaction network. Prediction is performed using a graphical convolutional neural network model with a conditional random field layer, which is able to better combine the network structural features with biological attribute features. Experiments on the ACC (Adrenocortical Cancer) and KICH (Kidney Chromophobe) datasets from TCGA (The Cancer Genome Atlas) demonstrated that the method performs better compared to other similar methods. It can identify not only frequently mutated driver genes, but also rare candidate driver genes and novel biomarker genes. The results of the survival and enrichment analyses of these detected genes demonstrate that the method can identify important driver genes at the individual level.

Spatiotemporal link between El Niño Southern Oscillation (ENSO), extreme heat, and thermal stress in the Asia-Pacific region.

Climate change is closely monitored and numerous studies reports increasing air temperature and weather extremes across the globe. As a direct consequence of the increase of global temperature, the increased heat stress is becoming a global threat to public health. While most climate change and epidemiological studies focus on air temperature to explain the increasing risks, heat strain can be predicted using comprehensive indices such as Universal Thermal Climate Index (UTCI). The Asia-Pacific region is prone to thermal stress and the high population densities in the region impose high health risk. This study evaluated the air temperature and UTCI trends between 1990 and 2019 and found significant increasing trends for air temperature for the whole region while the increases of UTCI are not as pronounced and mainly found in the northern part of the region. These results indicate that even though air temperature is increasing, the risks of heat stress when assessed using UTCI may be alleviated by other factors. The associations between El Niño Southern Oscillation (ENSO) and heat stress was evaluated on a seasonal level and the strongest regional responses were found during December-January (DJF) and March-May (MAM).

Phosphorus recovery from sewage sludge via Mg-air battery system.

A pressing issue in contemporary society is the resource scarcity of phosphorus. Operating on the principle of electrochemical reactions between Mg as the anode and oxygen from air as the cathode, Mg-air batteries (MAB) have been employed to provide new prospects for phosphorus recovery in struvite form. Different phosphorus concentrations and reaction time impact struvite generation in MAB systems; however, the exact mechanism has rarely been investigated. We investigated how varying the initial phosphorus concentration and the reaction time affects phosphorus recovery, electricity generation, and the efficiency of struvite production in MAB. Additionally, we examine the impact of solid carbon sources on phosphorus transformation in sludge. The findings revealed that the incorporation of solid carbon sources facilitated the release of phosphate by changing phosphorus speciation. The electrolyte derived from the conditioned sludge filtrate exhibited a remarkable phosphorus removal efficiency of 91.7 % within 1 h, yielding the highest struvite purity of ∼70 %, whereas that using raw sludge filtrate or extending the reaction time was found to be less effective, even reducing struvite formation. Furthermore, different electrolytes influence the system's ability to passivate anode, and electrolytes with higher phosphorus concentrations have better electricity production performance. The results by Visual MINTEQ model confirmed that longer reaction times and lower initial phosphorus concentrations can negatively affect struvite formation by introducing Mg3(PO4)2 and Mg(OH)2. The integration of agricultural waste as carbon sources with MAB for phosphorus recovery represents a potential methodology for struvite recuperation from sewage sludge, thereby heralding a sustainable strategy for resource recovery.

Computational-aided analysis of the pathway and mechanism of dichloroacetonitrile formation from phenylalanine upon chloramination.

Dichloroacetonitrile (DCAN) is an emerging disinfection by-product (DBP) that is widespread in drinking water. However, the pathway for DCAN formation from aromatic amino acids remains unclear, leading to a lack of an understanding of its explicit fate during chloramination. In this study, we investigated the specific formation mechanism of DCAN during the chloramination of phenylalanine based on reaction kinetics and chemical thermodynamics. The reason for differences between aldehyde and decarboxylation pathways was explained, and kinetic parameters of the pathways were obtained through quantum chemistry calculations. The results showed that the reaction rate constant of the rate-limiting step of the aldehyde pathway with 1.9 × 10-11 s-1 was significantly higher than that of decarboxylation (3.6 × 10-16 s-1 M-1), suggesting that the aldehyde pathway is the main reaction pathway for DCAN formation during the chloramination of phenylalanine to produce DCAN. Subsequently, theoretical calculations were performed to elucidate the effect of pH on the formation mechanism, which aligned well with the experimental results. Dehydrohalogenation was found to be the rate-limiting step under acidic conditions with reaction rate constants higher than those of the rate-limiting step (expulsion of amines) under neutral conditions, increasing the rate of DCAN formation. This study highlights the differences in DCAN formation between the decarboxylation and aldehyde pathways during the chloramination of precursors at both molecular and kinetic levels, contributing to a comprehensive understanding of the reaction mechanisms by which aromatic free amino acids generate DCAN.

Monocytes Release Pro-Cathepsin D to Drive Blood-to-Brain Transcytosis in Diabetes.

BACKGROUND: Microvascular complications are the major outcome of type 2 diabetes progression, and the underlying mechanism remains to be determined. METHODS: High-throughput RNA sequencing was performed using human monocyte samples from controls and diabetes. The transgenic mice expressing human CTSD (cathepsin D) in the monocytes was constructed using CD68 promoter. In vivo 2-photon imaging, behavioral tests, immunofluorescence, transmission electron microscopy, Western blot analysis, vascular leakage assay, and single-cell RNA sequencing were performed to clarify the phenotype and elucidate the molecular mechanism. RESULTS: Monocytes expressed high-level CTSD in patients with type 2 diabetes. The transgenic mice expressing human CTSD in the monocytes showed increased brain microvascular permeability resembling the diabetic microvascular phenotype, accompanied by cognitive deficit. Mechanistically, the monocytes release nonenzymatic pro-CTSD to upregulate caveolin expression in brain endothelium triggering caveolae-mediated transcytosis, without affecting the paracellular route of brain microvasculature. The circulating pro-CTSD activated the caveolae-mediated transcytosis in brain endothelial cells via its binding with low-density LRP1 (lipoprotein receptor-related protein 1). Importantly, genetic ablation of CTSD in the monocytes exhibited a protective effect against the diabetes-enhanced brain microvascular transcytosis and the diabetes-induced cognitive impairment. CONCLUSIONS: These findings uncover the novel role of circulatory pro-CTSD from monocytes in the pathogenesis of cerebral microvascular lesions in diabetes. The circulatory pro-CTSD is a potential target for the intervention of microvascular complications in diabetes.

Genome-Wide Search Links Senescence-Associated Secretory Proteins With Susceptibility for Coronary Artery Disease in Mouse and Human.

Advanced age is an independent risk factor for coronary artery disease (CAD), the leading global cause of mortality. Senescent vascular cells in the atherosclerotic plaques exhibit senescence-associated secretory phenotype (SASP). How SASP contributes to atherosclerosis and CAD, however, remains unclear. Here, we integrated RNA-array datasets of senescent human coronary arterial endothelial cells (HCAECs) and aortic smooth muscle cells (HASMCs) as well as genome-wide association data for CAD. We identified 26 genes from HCAECs and 6 genes from HASMCs related to SASP and CAD in both in-house and published datasets. Of which, Cystatin C (CST3), a CAD susceptibility gene, was found to be expressed in both HCAECs and HASMCs, thus, it was prioritized for further investigation. We demonstrated it was significantly elevated in senescent vascular cells, aged arteries, and early atherosclerosis. In vitro experiments showed that CST3 enhances the monocyte-endothelial cell adhesion. Additionally, ligand-receptor pairing analyses revealed two important pathways, COL4A1-ITGA1 and LPL-LRP1 pathways, linked to the critical processes in the development of atherosclerosis, including cell adhesion, inflammation response, extracellular matrix organization, and lipid metabolism. We further demonstrated a reduced monocyte-endothelial cell adhesion following the knockdown of COL4A1 or ITGA1 and a significantly increased expression of COL4A1, ITGA1, and LPL in arterial intima of aged mice and ApoE-/- mice. Our findings demonstrate that vascular cell-derived SASP proteins increase the CAD susceptibility and identify CST3 functionally contributing to atherosclerosis.

Characterization and Spike Gene Analysis of a Candidate Attenuated Live Bovine Coronavirus Vaccine.

The bovine coronavirus (BCoV) KBR-1 strain, obtained from calf diarrhea samples collected in 2017, belongs to group GIIa. To attenuate this strain, it was subcultured continuously (up to 79 times) in HRT-18 cells, followed by 80-120 passages in MDBK cells. The KBR-1-p120 strain harvested from MDBK cells at passage 120 harbored 13 amino acid mutations in the spike gene. Additionally, the KBR-1-p120 strain showed a high viral titer and cytopathogenic effects in MDBK cells. Seven-day-old calves (negative for BCoV antigen and antibodies) that did not consume colostrum were orally inoculated with the attenuated candidate strain (KBR-1-p120), or with KBR-1 passaged 10 times (KBR-1-p10) in HRT-18 cells. Calves inoculated with KBR-1-p10 had a low diarrhea score, and BCoV RNA was detected at 3-7 days post-inoculation (DPI). The virus was also present in the duodenum, jejunum, and ileum at autopsy; however, calves inoculated with KBR-1-p120 had low levels of BCoV RNA in feces at 4-6 DPI, and no diarrhea. In addition, an extremely small amount of BCoV RNA was present in the jejunum and ileum at autopsy. The small intestines of calves inoculated with KBR-1-p120 were emulsified and used to infect calves two more times, but pathogenicity was not recovered. Therefore, the KBR-1-p120 strain has potential as a live vaccine candidate.

Prognostic value of left ventricular trabeculae fractal analysis in patients with dilated cardiomyopathy.

BACKGROUND: The prognostic value of left ventricular (LV) myocardial trabecular complexity on cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) remains unknown. This study aimed to evaluate the prognostic value of LV myocardial trabecular complexity using fractal analysis in patients with DCM. METHODS: Consecutive patients with DCM who underwent CMR between March 2017 and November 2021 at two hospitals were prospectively enrolled. The primary endpoints were defined as the combination of all-cause death and heart failure hospitalization. The events of cardiac death alone were defined as the secondary endpoints.LV trabeculae complexity was quantified by measuring the fractal dimension (FD) of the endocardial border based on fractal geometry on CMR. Cox proportional hazards regression and Kaplan-Meier survival analysis were used to examine the association between variables and outcomes. The incremental prognostic value of FD was assessed in nested models. RESULTS: A total of 403 patients with DCM (49.31 ± 14.68 years, 69% male) were recruited. After a median follow-up of 43 months (interquartile range, 28-55 months), 87 and 24 patients reached the primary and secondary endpoints, respectively. Age, heart rate, New York Heart Association functional class >II, N-terminal pro-B-type natriuretic peptide, LV ejection fraction, LV end-diastolic volume index, LV end-systolic volume index, LV mass index, presence of late gadolinium enhancement, global FD, LV mean apical FD, and LV maximal apical FD were univariably associated with the outcomes (all P < 0.05). After multivariate adjustment, LV maximal apical FD remained a significant independent predictor of outcome [hazard ratio = 1.179 (1.116, 1.246), P < 0.001]. The addition of LV maximal apical FD in the nested models added incremental prognostic value to other common clinical and imaging risk factors (all <0.001; C-statistic: 0.84-0.88, P < 0.001). CONCLUSION: LV maximal apical FD was an independent predictor of the adverse clinical outcomes in patients with DCM and provided incremental prognostic value over conventional clinical and imaging risk factors.

Prognostic value of right atrial strains in arrhythmogenic right ventricular cardiomyopathy.

OBJECTIVES: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by progressive fibrofatty infiltration of atrial and ventricular myocardium resulting in adverse cardiac events. Atrial function has been increasingly recognized as prognostically important for cardiovascular disease. As the right atrial (RA) strain is a sensitive parameter to describe RA function, we aimed to analyze the prognostic value of the RA strain in ARVC. METHODS: RA strain parameters were derived from cardiac magnetic resonance (CMR) images of 105 participants with definite ARVC. The endpoint was defined as a combination of sudden cardiac death, survival cardiac arrest, and appropriate implantable cardioverter-defibrillator intervention. Cox regression and Kaplan-Meier survival analyses were performed to evaluate the association between RA strain parameters and endpoint. Concordance index (C index), net reclassification index (NRI), and integrated discrimination improvement (IDI) were calculated to assess the incremental value of RA strain in predicting the endpoint. RESULTS: After a median follow-up of 5 years, 36 (34.3%) reaching the endpoint displayed significantly reduced RA strain parameters. At Kaplan-Meier analysis, impaired RA reservoir (RARS) and booster strains (RABS) were associated with an increased risk of the endpoint. After adjusting for conventional risk factors, RARS (hazard ratio [HR], 0.956; p = 0.005) and RABS (HR, 0.906; p = 0.002) resulted as independent predictors for endpoint at Cox regression analyses. In addition, RARS and RABS improved prognostic value to clinical risk factors and CMR morphological and functional predictors (all p < 0.05). CONCLUSION: RARS and RABS were independent predictors for adverse cardiac events, which could provide incremental prognostic value for conventional predictors in ARVC. CRITICAL RELEVANCE STATEMENT: We evaluated the prognostic value of right atrial strain in ARVC patients and suggested cardiologists consider RA strain as a predictive parameter when evaluating the long-term outcome of ARVC patients in order to formulate better clinical therapy. KEY POINTS: • Patients with ARVC had significantly reduced RA strain and strain rates compared with healthy participants. • Participants with lower RA reservoir and booster stains were associated with a significantly higher risk of adverse cardiac events. • RA booster and reservoir strain provide incremental value to conventional parameters.

Current understanding of subclinical diabetic retinopathy informed by histology and high-resolution in vivo imaging.

The escalating incidence of diabetes mellitus has amplified the global impact of diabetic retinopathy. There are known structural and functional changes in the diabetic retina that precede the fundus photography abnormalities which currently are used to diagnose clinical diabetic retinopathy. Understanding these subclinical alterations is important for effective disease management. Histology and high-resolution clinical imaging reveal that the entire neurovascular unit, comprised of retinal vasculature, neurons and glial cells, is affected in subclinical disease. Early functional manifestations are seen in the form of blood flow and electroretinography disturbances. Structurally, there are alterations in the cellular components of vasculature, glia and the neuronal network. On clinical imaging, changes to vessel density and thickness of neuronal layers are observed. How these subclinical disturbances interact and ultimately manifest as clinical disease remains elusive. However, this knowledge reveals potential early therapeutic targets and the need for imaging modalities that can detect subclinical changes in a clinical setting.

Dynamic decomposition graph convolutional neural network for SSVEP-based brain-computer interface.

The SSVEP-based paradigm serves as a prevalent approach in the realm of brain-computer interface (BCI). However, the processing of multi-channel electroencephalogram (EEG) data introduces challenges due to its non-Euclidean characteristic, necessitating methodologies that account for inter-channel topological relations. In this paper, we introduce the Dynamic Decomposition Graph Convolutional Neural Network (DDGCNN) designed for the classification of SSVEP EEG signals. Our approach incorporates layerwise dynamic graphs to address the oversmoothing issue in Graph Convolutional Networks (GCNs), employing a dense connection mechanism to mitigate the gradient vanishing problem. Furthermore, we enhance the traditional linear transformation inherent in GCNs with graph dynamic fusion, thereby elevating feature extraction and adaptive aggregation capabilities. Our experimental results demonstrate the effectiveness of proposed approach in learning and extracting features from EEG topological structure. The results shown that DDGCNN outperforms other state-of-the-art (SOTA) algorithms reported on two datasets (Dataset 1: 54 subjects, 4 targets, 2 sessions; Dataset 2: 35 subjects, 40 targets). Additionally, we showcase the implementation of DDGCNN in the context of synchronized BCI robotic fish control. This work represents a significant advancement in the field of EEG signal processing for SSVEP-based BCIs. Our proposed method processes SSVEP time domain signals directly as an end-to-end system, making it easy to deploy. The code is available at https://github.com/zshubin/DDGCNN.

Inhibition of palmitoyltransferase ZDHHC12 sensitizes ovarian cancer cells to cisplatin through ROS-mediated mechanisms.

Platinum-based therapies have revolutionized the treatment of high-grade serous ovarian cancer (HGSOC). However, high rates of disease recurrence and progression remain a major clinical concern. Impaired mitochondrial function and dysregulated reactive oxygen species (ROS), hallmarks of cancer, hold potential as therapeutic targets for selectively sensitizing cisplatin treatment. Here, we uncover an oncogenic role of the palmitoyltransferase ZDHHC12 in regulating mitochondrial function and ROS homeostasis in HGSOC cells. Analysis of The Cancer Genome Atlas (TCGA) ovarian cancer data revealed significantly elevated ZDHHC12 expression, demonstrating the strongest positive association with ROS pathways among all ZDHHC enzymes. Transcriptomic analysis of independent ovarian cancer datasets and the SNU119 cell model corroborated this association, highlighting a strong link between ZDHHC12 expression and signature pathways involving mitochondrial oxidative metabolism and ROS regulation. Knockdown of ZDHHC12 disrupted this association, leading to increased cellular complexity, ATP levels, mitochondrial activity, and both mitochondrial and cellular ROS. This dysregulation, achieved by the siRNA knockdown of ZDHHC12 or treatment with the general palmitoylation inhibitor 2BP or the fatty acid synthase inhibitor C75, significantly enhanced cisplatin cytotoxicity in 2D and 3D spheroid models of HGSOC through ROS-mediated mechanisms. Markedly, ZDHHC12 inhibition significantly augmented the anti-tumor activity of cisplatin in an ovarian cancer xenograft tumor model, as well as in an ascites-derived organoid line of platinum-resistant ovarian cancer. Our data suggest the potential of ZDHHC12 as a promising target to improve the outcome of HGSOCs in response to platinum-based chemotherapy.

3D Fractal Dimension Analysis: Prognostic Value of Right Ventricular Trabecular Complexity in Participants with Arrhythmogenic Cardiomyopathy.

BACKGROUND: Arrhythmogenic cardiomyopathy (ACM) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. Traditionally, two-dimensional (2D) instead of 3D fractal dimension (FD) analysis has been used to evaluate trabecular disarray. However, the prognostic value of trabecular disorder assessed by 3D FD measurement remains unclear. PURPOSE: To investigate the prognostic value of right ventricular trabecular complexity in ACM patients using 3D FD analysis based on cardiac MR cine images. STUDY TYPE: Retrospective. POPULATION: 85 ACM patients (mean age: 45 ± 17 years, 52 male). FIELD STRENGTH/SEQUENCE: 3.0T/cine imaging, T2-short tau inversion recovery (T2-STIR), and late gadolinium enhancement (LGE). ASSESSMENT: Using cine images, RV (right ventricular) volumetric and functional parameters were obtained. RV trabecular complexity was measured with 3D fractal analysis by box-counting method to calculate 3D-FD. Cox and logistic regression models were established to evaluate the prognostic value of 3D-FD for major adverse cardiac events (MACE). STATISTICAL TESTS: Cox regression and logistic regression to explore the prognostic value of 3D-FD. C-index, time-dependent receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) to evaluate the incremental value of 3D-FD. Intraclass correlation coefficient for interobserver variability. P < 0.05 indicated statistical significance. RESULTS: 26 MACE were recorded during the 60 month follow-up (interquartile range: 48-67 months). RV 3D-FD significantly differed between ACM patients with MACE (2.67, interquartile range: 2.51 ~ 2.81) and without (2.52, interquartile range: 2.40 ~ 2.67) and was a significant independent risk factor for MACE (hazard ratio, 1.02; 95% confidence interval: 1.01, 1.04). In addition, prognostic model fitness was significantly improved after adding 3D-FD to RV global longitudinal strain, LV involvement, and 5-year risk score separately. DATA CONCLUSION: The myocardial trabecular complexity assessed through 3D FD analysis was found associated with MACE and provided incremental prognostic value beyond conventional ACM risk factors. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Development of high internal phase Pickering emulsions stabilized by egg yolk and carboxymethylcellulose complexes to improve ß-carotene bioaccessibility for the elderly.

The work aimed to develop the multi-protein mixture of egg yolk as natural particles to stabilize high internal phase Pickering emulsions (HIPPEs) to improve the bioaccessibility of ß-carotene in the elderly. The results showed that the depletion attraction drove the adsorption of egg yolk protein particles at the oil-water interface and the formation of osmotic droplet clusters due to the attachment of particle-coated droplets in the dispersed phase, leading to kinetic blocking and stable gelation of HIPPEs. Rheological measurements showed that HIPPEs had shear thinning, low shear stress, viscoelastic properties, and structural recovery properties, which facilitated easy consumption for the elderly. The stability of HIPPEs was verified by ionic and centrifugal stability tests, demonstrating their potential for application to complex gastric environments. HIPPEs have been applied to the International Dysphagia Dietary Standardization Initiative (IDDSI) test and simulated in vitro digestion in older adults, demonstrating their safe swallowability and high ß-carotene bioaccessibility. Our findings suggest solutions for food practitioners facing the aging problem and provide new insights for preparing age-friendly foods.

Prognostic value of right ventricular trabecular complexity in patients with arrhythmogenic cardiomyopathy.

OBJECTIVES: The present study aimed to investigate the incremental prognostic value of the right ventricular fractal dimension (FD), a novel marker of myocardial trabecular complexity by cardiac magnetic resonance (CMR) in patients with arrhythmogenic cardiomyopathy (ACM). METHODS: Consecutive patients with ACM undergoing CMR were followed up for major cardiac events, including sudden cardiac death, aborted cardiac arrest, and appropriate implantable cardioverter defibrillator intervention. Prognosis prediction was compared by Cox regression analysis. We established a multivariable model supplemented with RV FD and evaluated its discrimination by Harrell's C-statistic. We compared the category-free, continuous net reclassification improvement (cNRI) and integrated discrimination index (IDI) before and after the addition of FD. RESULTS: A total of 105 patients were prospectively included from three centers and followed up for a median of 60 (48, 66) months; experienced 36 major cardiac events were recorded. Trabecular FD displayed a strong unadjusted association with major cardiac events (p < 0.05). In the multivariable Cox regression analysis, RV maximal apical FD maintained an independent association with major cardiac events (hazard ratio, 1.31 (1.11-1.55), p < 0.002). The Hosmer-Lemeshow goodness of fit test displayed good fit (X2 = 0.68, p = 0.99). Diagnostic performance was significantly improved after the addition of RV maximal apical FD to the multivariable baseline model, and the continuous net reclassification improvement increased 21% (p = 0.001), and the integrated discrimination index improved 16% (p = 0.045). CONCLUSIONS: In patients with ACM, CMR-assessed myocardial trabecular complexity was independently correlated with adverse cardiovascular events and provided incremental prognostic value. CLINICAL RELEVANCE STATEMENT: The application of FD values for assessing RV myocardial trabeculae may become an accessible and promising parameter in monitoring and early diagnosis of risk factors for adverse cardiovascular events in patients with ACM. KEY POINTS: • Ventricular trabecular morphology, a novel quantitative marker by CMR, has been explored for the first time to determine the severity of ACM. • Patients with higher maximal apical fractal dimension of RV displayed significantly higher cumulative incidence of major cardiac events. • RV maximal apical FD was independently associated with major cardiac events and provided incremental prognostic value in patients with ACM.

Fractal Analysis of Left Ventricular Trabeculae in Patients with End-Stage Renal Disease: A Random Survival Tree Analysis.

BACKGROUND: The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. PURPOSE: To evaluate the prognostic value of LV trabecular complexity in patients with end-stage renal disease (ESRD). STUDY TYPE: Prospective outcome study. POPULATION: 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. FIELD STRENGTH: 3.0T, steady-state free precession (SSFP) and modified Look-Locker imaging sequences. ASSESSMENT: All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low- and high-risk groups based on scores derived from the RF model and survival compared. STATISTICAL TESTS: Receiver operating characteristic curve analysis; Kaplan-Meier survival analysis with log rank tests; Harrel's C-index to assess model performance. A P value <0.05 was considered statistically significant. RESULTS: Fifty-five patients (26.57%) experienced MACE during a median follow-up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C-index: 0.81) had significantly better discrimination than the Cox regression model (C-index: 0.74). Participants of the external validation dataset classified into the high-risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low-risk group. DATA CONCLUSION: LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.