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Smoking, diabetes and high blood pressure increase the risk of a heart attack more in women than in men, new research from The George Institute for Global Health at the University of Oxford has found.
Rational design, synthesis, and evaluation of novel polypharmacological compounds targeting NaV1.5, KV1.5, and K2P channels for atrial fibrillation.
Atrial fibrillation (AF) involves electrical remodeling of the atria, with ion channels such as Na<sub>V</sub>1.5, K<sub>V</sub>1.5, and TASK-1 playing crucial roles. This study investigates acetamide-based compounds designed as multi-target inhibitors of these ion channels to address AF. Compound 6f emerged as the most potent in the series, demonstrating a strong inhibition of TASK-1 (IC<sub>50</sub> ∼ 0.3 μM), a moderate inhibition of Na<sub>V</sub>1.5 (IC<sub>50</sub> ∼ 21.2 μM) and a subtle inhibition of K<sub>V</sub>1.5 (IC<sub>50</sub> ∼ 81.5 μM), alongside unexpected activation of TASK-4 (∼ 40% at 100 μM). Functional assays on human atrial cardiomyocytes from sinus rhythm (SR) and patients with AF revealed that 6f reduced action potential amplitude in SR (indicating Na<sub>V</sub>1.5 block), while in AF it increased action potential duration (APD), reflecting high affinity for TASK-1. Additionally, 6f caused hyperpolarization of the resting membrane potential in AF cardiomyocytes, consistent with the observed TASK-4 activation. Mathematical modeling further validated its efficacy in reducing AF burden. Pharmacokinetic analyses suggest favorable absorption and low toxicity. These findings identify 6f as a promising multi-target therapeutic candidate for AF management.
Prospective in silico trials identify combined SK and K2P channel block as an effective strategy for atrial fibrillation cardioversion.
Virtual evaluation of medical therapy through human-based modelling and simulation can accelerate and augment clinical investigations. Treatment of the most common cardiac arrhythmia, atrial fibrillation (AF), requires novel approaches. This study prospectively evaluates and mechanistically explains three novel pharmacological therapies for AF through in silico trials, including single and combined SK and K<sub>2</sub>P channel block. AF and pharmacological action were assessed in a large cohort of 1000 virtual patients, through 2962 multiscale simulations. Extensive calibration and validation with experimental and clinical data support their credibility. Sustained AF was observed in 654 virtual patients. In this cohort, cardioversion efficacy increased to 82% (535 of 654) through combined SK+K<sub>2</sub>P channel block, from 33% (213 of 654) and 43% (278 of 654) for single SK and K<sub>2</sub>P blocks, respectively. Drug-induced prolongation of tissue refractoriness, dependent on the virtual patient's ionic current profile, explained cardioversion efficacy (atrial refractory period increase: 133.0 ± 48.4 ms for combined vs. 45.2 ± 43.0 and 71.0 ± 55.3 ms for single SK and K<sub>2</sub>P block, respectively). Virtual patients cardioverted by SK channel block presented lower K<sub>2</sub>P densities, while lower SK densities favoured the success of K<sub>2</sub>P channel inhibition. Both ionic currents had a crucial role on atrial repolarization, and thus a synergism resulted from the multichannel block. All three strategies, including the multichannel block, preserved atrial electrophysiological function (i.e. conduction velocity and calcium transient dynamics) and thus its contractile properties (safety). In silico trials identify key factors determining treatment success and the combined SK+K<sub>2</sub>P channel block as a promising strategy for AF management. KEY POINTS: This is a large-scale in silico trial study involving 2962 multiscale simulations. A population of 1000 virtual patients underwent three treatments for atrial fibrillation. Single and combined SK+K<sub>2</sub>P channel block were assessed prospectively. The multi-ion channel inhibition resulted in 82% cardioversion efficacy. In silico trials have broad implications for precision medicine.
Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing.
Cardiac digital twins are computational tools capturing key functional and anatomical characteristics of patient hearts for investigating disease phenotypes and predicting responses to therapy. When paired with large-scale computational resources and large clinical datasets, digital twin technology can enable virtual clinical trials on virtual cohorts to fast-track therapy development. Here, we present an open-source automated pipeline for personalising ventricular electrophysiological function based on routinely acquired magnetic resonance imaging (MRI) data and the standard 12-lead electrocardiogram (ECG). Using MRI-based anatomical models, a sequential Monte-Carlo approximate Bayesian computational inference method is extended to infer electrical activation and repolarisation characteristics from the ECG. Fast simulations are conducted with a reaction-Eikonal model, including the Purkinje network and biophysically-detailed subcellular ionic current dynamics for repolarisation. For each patient, parameter uncertainty is represented by inferring an envelope of plausible ventricular models rather than a single one, which means that parameter uncertainty can be propagated to therapy evaluation. Furthermore, we have developed techniques for translating from reaction-Eikonal to monodomain simulations, which allows more realistic simulations of cardiac electrophysiology. The pipeline is demonstrated in three healthy subjects, where our inferred pseudo-diffusion reaction-Eikonal models reproduced the patient's ECG with a median Pearson's correlation coefficient of 0.9, and then translated to monodomain simulations with a median correlation coefficient of 0.84 across all subjects. We then demonstrate our digital twins for virtual evaluation of Dofetilide with uncertainty quantification. These evaluations using our cardiac digital twins reproduced dose-dependent QTc and T peak to T end prolongations that are in keeping with large population drug response data. The methodologies for cardiac digital twinning presented here are a step towards personalised virtual therapy testing and can be scaled to generate virtual populations for clinical trials to fast-track therapy evaluation. The tools developed for this paper are open-source, documented, and made publicly available.
Molnupiravir or nirmatrelvir-ritonavir plus usual care versus usual care alone in patients admitted to hospital with COVID-19: a randomised, controlled, open-label, platform trial (RECOVERY)
Background: Molnupiravir and nirmatrelvir-ritonavir (Paxlovid) are oral antivirals that were assessed in separate treatment comparisons in the RECOVERY trial, a randomised, controlled, open-label, adaptive platform trial evaluating treatments for patients hospitalised with COVID-19 pneumonia. Methods: Adult participants could join the molnupiravir comparison, the nirmatrelvir-ritonavir comparison, or both. In each comparison, they were randomly allocated in a 1:1 ratio to the relevant antiviral (five days of molnupiravir 800mg twice daily or nirmatrelvir-ritonavir 300mg/100mg twice daily) in addition to usual care, or to usual care alone. The primary outcome was 28-day mortality, and secondary outcomes were time to discharge alive from hospital, and progression to invasive ventilation or death. Analysis was by intention-to-treat. Both comparisons were stopped because of low recruitment. ISRCTN50189673; clinicaltrials.gov NCT04381936. Findings: From January 2022 to May 2023, 923 patients were recruited to the molnupiravir comparison (445 allocated molnupiravir and 478 allocated usual care), and from March 2022 to May 2023, 137 patients were recruited to the nirmatrelvir-ritonavir comparison (68 allocated nirmatrelvir-ritonavir and 69 allocated usual care). Over three-quarters of the patients were vaccinated and had anti-spike antibodies at randomisation, and over two-thirds were receiving other SARS-CoV-2 antivirals. In the molnupiravir comparison, 74 (17%) patients allocated molnupiravir and 79 (17%) patients allocated usual care died within 28 days (hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.68-1.28; p=0.66). In the nirmatrelvir-ritonavir comparison, 13 (19%) patients allocated nirmatrelvir-ritonavir and 13 (19%) patients allocated usual care died within 28 days (HR 1.02; 95% CI 0.47-2.23; p=0.96). In neither comparison was there evidence of any difference in the duration of hospitalisation or the proportion of patients progressing to invasive ventilation or death. Interpretation: Adding molnupiravir or nirmatrelvir-ritonavir to usual care was not associated with improvements in clinical outcomes. However, limited recruitment meant a clinically meaningful benefit of treatment could not be ruled-out, particularly for nirmatrelvir-ritonavir.
Dopamine D2 receptor upregulation in dorsal striatum in the LRRK2-R1441C rat model of early Parkinson's disease revealed by in vivo PET imaging.
We conducted PET imaging with [18F]FDOPA and dopamine D2/3 receptor ligand [18F]fallypride in aged transgenic rats carrying human pathogenic LRRK2 R1441C or G2019S mutations. These rats have mild age-dependent deficits in dopamine release restricted to dorsal striatum despite no overt loss of dopamine neurons or dopamine content and demonstrate L-DOPA-responsive movement deficits.LRRK2 mutant rats displayed no deficit in [18F]FDOPA uptake, consistent with intact dopamine synthesis in striatal axons. However, LRRK2-R1441C rats demonstrated greater binding of [18F]fallypride than LRRK2-G2019S or non-transgenic controls, from a regionally selective increase in dorsal striatum. Immunocytochemical labelling post-mortem confirmed a greater density of D2 receptors in LRRK2-R1441C than other genotypes restricted to dorsal striatum, consistent with upregulation of D2-receptors as a compensatory response to the greater dopamine release deficit previously demonstrated in this genotype.These results show that [18F]fallypride PET imaging is sensitive to dysregulation of dopamine signalling in the LRRK2-R1441C rat, revealing upregulation of D2 receptors that parallels observations in human putamen in early sporadic PD. Future studies of candidate therapies could exploit this non-invasive approach to assess treatment efficacy.
Association of greenness with incidence of cardiovascular disease in China: Evidence from the China Kadoorie Biobank prospective cohort study with 0.5 million adults
Prospective evidence on the relationship of greenness with cardiovascular disease (CVD) incidence is limited in low- and middle-income countries. In 512,691 participants of the China Kadoorie Biobank cohort across 10 regions in China, we calculated the levels of greenness exposure based on satellite-retrieved Normalized Difference Vegetation Index (NDVI) data. Annual maximum NDVI (NDVImax) values were estimated within 500 m and 1000 m buffers around the locations for the participants during the follow-up periods. Record linkages to healthcare databases provided incidence data of total CVD, ischemic heart disease and stroke during 2005–2017. Time-varying Cox proportional hazards regression was used to assess the associations between greenness exposure and CVD incidence. After 5.08 million person-years of follow-up, 148,032 incident CVD events were recorded. The overall average level of NDVImax was 0.543 for all participants. We observed significant inverse associations of greenness with the incidence of CVD and its subtypes. Specifically, the hazard ratio for total CVD incidence was 0.976 (95% confidence interval: 0.958, 0.994) per 0.1 increase in NDVImax within a 500 m buffer. As the 5 rural regions have achieved the WHO recommended greenness goal values, we compared the greenness levels in the 5 urban regions with the WHO's goal for greenness and found that, on average, 3.81% of total CVD incidence might be averted if the recommended greenness values could be achieved. Exposure to a higher level of greenness was associated with a lower risk of CVD incidence in Chinese adults.
GPCR signaling via cAMP nanodomains.
G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors, mediating essential physiological responses through diverse intracellular signaling pathways. When coupled to Gs or Gi proteins, GPCR modulates the synthesis of 3'-5'-cyclic adenosine monophosphate (cAMP), which governs a wide array of processes, ranging from cellular growth and survival to metabolic regulation. Studies have highlighted that cAMP is not uniformly distributed within cells but instead is compartmentalized into highly localized nanodomains. These nanodomains, mostly regulated by phosphodiesterases (PDEs), play a critical role in enabling signal precision and functional effects that are specific to individual stimuli. GPCRs can initiate distinct cAMP responses based on their localization within the cell, with evidence showing that both receptors resident at the plasma membrane and intracellular receptors-including endosomal, Golgi, and nuclear GPCRs-elicit unique cAMP signaling profiles. This review examines the mechanisms underlying GPCR signaling through cAMP nanodomains. We focus on the role of PDE-mediated cAMP degradation in shaping local cAMP signals, the emerging views on mechanisms that may contribute to signal compartmentalization, and the role of intracellular membrane compartments. By exploring these aspects, we aim to highlight the complexity of GPCR signaling networks and illustrate some of the implications for the regulation of cellular function.
Retraction to: Annexin A1 attenuates microvascular complications through restoration of Akt signalling in a murine model of type 1 diabetes (Diabetologia, (2018), 61, 2, (482-495), 10.1007/s00125-017-4469-y)
The Editor-in-Chief has retracted this article after concerns were raised about some of the data reported. The blots for Thr183/Tyr185 JNK appear to have been duplicated between Figures 2F and 4C, and between Figures 7C and 7D. The Authors provided the original raw data upon request by the Editors, but upon review further discrepancies were observed between the raw and published blot data. The Editor-in-Chief therefore no longer has confidence in the reliability of findings and conclusions of this article. Gareth Purvis, Fausto Chiazza, Jianmin Chen, Chris Reutelingsperger, Luigi Gnudi, Muhammed Yaqoob, Massimo Collino, Christoph Thiemermann, and Egle Solito disagree with this retraction. The remaining authors did not respond to correspondence from the Publisher about this retraction.
DeepCA: Deep Learning-Based 3D Coronary Artery Tree Reconstruction from Two 2D Non-Simultaneous X-Ray Angiography Projections
Cardiovascular diseases (CVDs) are the most common cause of death worldwide. Invasive x-ray coronary angiography (ICA) is one of the most important imaging modalities for the diagnosis of CVDs. ICA typically acquires only two 2D projections, which makes the 3D geometry of coronary vessels difficult to interpret, thus requiring 3D coronary artery tree reconstruction from two projections. State-of-the-art approaches require significant manual interactions and cannot correct the non-rigid cardiac and respiratory motions between non-simultaneous projections. In this study, we propose a novel deep learning pipeline named DeepCA. We leverage the Wasserstein conditional generative adversarial network with gradient penalty, latent convolutional transformer layers, and a dynamic snake convolutional critic to implicitly compensate for the non-rigid motion and provide 3D coronary artery tree reconstruction. Through simulating projections from coronary computed tomography angiography (CCTA), we achieve the generalisation of 3D coronary tree reconstruction on real non-simultaneous ICA projections. We incorporate an application-specific evaluation metric to validate our proposed model on both a CCTA dataset and a real ICA dataset, together with Chamfer £2 distance. The results demonstrate promising performance of our DeepCA model in vessel topology preservation, recovery of missing features, and generalisation ability to real ICA data. To the best of our knowledge, this is the first study that leverages deep learning to achieve 3D coronary tree reconstruction from two real non-simultaneous x-ray angiographic projections. The implementation of this work is available at: https//github.com/WangStephen/DeepCA.
[Prospective association between liver biomarkers and mortality risk in Chinese middle-aged and elderly populations].
Objective: To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value. Methods: A total of 22 758 participants from the 3rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results: The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95%CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% (HR=1.10, 95%CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95%CI: 0.679-0.757), with an increase of 0.030 (P<0.001) compared with the traditional model. Conclusions: Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.
Redefining respiratory sinus arrhythmia as respiratory heart rate variability: an international Expert Recommendation for terminological clarity.
The variation of heart rate in phase with breathing, known as 'respiratory sinus arrhythmia' (RSA), is a physiological phenomenon present in all air-breathing vertebrates. RSA arises from the interaction of several physiological mechanisms but is primarily mediated by rhythmic changes in cardiac parasympathetic (vagal) activity, increasing heart rate during inspiration and decreasing heart rate during expiration. RSA amplitude is an indicator of autonomic and cardiac health; RSA is diminished or absent in common pathological conditions such as chronic heart failure and hypertension. In this Expert Recommendation, we argue that the term 'RSA', although historically important, is semantically inaccurate and carries misleading pathological connotations, contributing to misunderstanding and misinterpretation of the origin and the physiological importance of the phenomenon. We propose replacing 'RSA' with the term 'respiratory heart rate variability' (RespHRV), which avoids pathological connotations and emphasizes the specific respiratory contribution to heart rate variability. We clarify that RespHRV encompasses respiratory-related heart rate variations in both the low-frequency and high-frequency bands traditionally defined in heart rate variability analysis, and that its amplitude should not be misconstrued as a measure of vagal tone. Adopting the proposed term 'RespHRV' is expected to unify understanding and stimulate further experimental and clinical research into the physiological mechanisms and functional importance of this phenomenon.
FoxO1-zDHHC4-CD36 S-Acylation Axis Drives Metabolic Dysfunction in Diabetes.
BACKGROUND: The fatty acid (FA) transporter CD36 (FA translocase/cluster of differentiation 36) is the gatekeeper of cardiac FA metabolism. Preferential localization of CD36 to the sarcolemma is one of the initiating cellular responses in the development of muscle insulin resistance and the type 2 diabetic heart. Posttranslational S-acylation controls protein trafficking, and in this study, we hypothesized that increased CD36 S-acylation may underpin the preferential sarcolemmal localization of CD36, driving metabolic and contractile dysfunction in diabetes. METHODS AND RESULTS: Type 2 diabetes increased cardiac CD36 S-acylation, CD36 sarcolemmal localization, FA oxidation rates, and triglyceride storage in the diabetic heart. CD36 S-acylation was increased in diabetic rats, db/db mice, diabetic pigs, and insulin-resistant human iPSC-derived cardiomyocytes, demonstrating conservation between species. The enzyme responsible for S-acylating CD36, zDHHC4, was transcriptionally upregulated in the diabetic heart, and genetic silencing of zDHHC4 using siRNA or lentiviral shRNA decreased CD36 S-acylation. We identified that zDHHC4 expression is under the regulation of the transcription factor FoxO (forkhead box O) 1, as FoxO1 binds to the promotor of zDHHC4 and induces its transcription, as assessed using chromatin immunoprecipitation-seq, chromatin immunoprecipitation-quantitative PCR, luciferase assays, and siRNA silencing. Diabetic mice with cardiomyocyte-specific FoxO1 deletion had decreased cardiac zDHHC4 expression and decreased CD36 S-acylation, which was further confirmed using diabetic mice treated with the FoxO1 inhibitor AS1842856. Pharmacological inhibition of zDHHC enzymes in diabetic hearts decreased CD36 S-acylation, sarcolemmal CD36 content, FA oxidation rates, and triglyceride storage, culminating in improved cardiac function in diabetes. Conversely, inhibiting the deacylating enzymes in control hearts increased CD36 S-acylation, sarcolemmal CD36 content, and FA metabolic rates in control hearts, recapitulating the metabolic phenotype seen in diabetic hearts. CONCLUSIONS: Activation of the FoxO1-zDHHC4-CD36 S-acylation axis in diabetes drives metabolic and contractile dysfunction in type 2 diabetic heart.
Exercise Improves Myocardial Deformation But Not Cardiac Structure in Preterm-Born Adults: A Randomized Clinical Trial.
BACKGROUND: People born preterm (<37 weeks' gestation) have a potentially adverse cardiac phenotype that progresses with blood pressure elevation. OBJECTIVES: The authors investigated whether preterm-born and term-born adults exhibit similar cardiac structural and functional remodeling following a 16-week aerobic exercise intervention. METHODS: We conducted a randomized controlled trial in 203 adults (aged 18-35 years) with elevated blood pressure or stage 1 hypertension. Participants were randomized 1:1 to a 16-week aerobic exercise intervention or to a control group. In a prespecified cardiovascular magnetic resonance imaging (CMR) substudy, CMR was performed at 3.0-Tesla to assess left and right ventricular (LV and RV) structure and function before and after intervention. RESULTS: A total of 100 participants completed CMR scans at baseline and after the 16-week intervention, with n = 47 in the exercise intervention group (n = 26 term-born; n = 21 preterm-born) and n = 53 controls (n = 32 term-born; n = 21 preterm-born). In term-born participants, LV mass to end-diastolic volume ratio decreased (-3.43; 95% CI: -6.29 to -0.56; interaction P = 0.027) and RV stroke volume index increased (5.53 mL/m2; 95% CI: 2.60, 8.47; interaction P = 0.076) for those in the exercise intervention group vs controls. No significant effects were observed for cardiac structural indices in preterm-born participants. In preterm-born participants, LV basal- and mid-ventricular circumferential strain increased (-1.33; 95% CI: -2.07 to -0.60; interaction P = 0.057 and -1.54; 95% CI: -2.46 to -0.63; interaction P = 0.046, respectively) and RV global longitudinal strain increased (1.99%; 95% CI: -3.12 to -0.87; interaction P = 0.053) in the exercise intervention group vs controls. No significant effects were observed for myocardial deformation parameters in term-born participants. CONCLUSIONS: Aerobic exercise training induces improved myocardial function but not cardiac structure in preterm-born adults.
Long-term exposure to fine particulate matter interacting with individual conditions increase breast cancer incidence: a large-scale Chinese cohort
Background: Breast cancer is the most frequently diagnosed malignancy among women worldwide. This study aimed to investigate the impact of long-term fine particulate matter (PM2.5) exposure on breast cancer incidence in a cohort of 281,152 women from the China Kadoorie Biobank who were initially free of breast cancer. Results: PM2.5 concentrations were estimated using a high-resolution satellite-based model, and breast cancer cases were ascertained through national databases. Over a median follow-up of 11.12 years, 2393 new breast cancer cases were reported. Analyses using Cox proportional hazard and restricted cubic spline models demonstrated a non-linear association between PM2.5 exposure and breast cancer incidence, with a marked increase in risk observed once PM2.5surpassed 53.6 μg/m3. For every 10 μg/m3 increase in PM2.5, the hazard ratio for breast cancer incidence was 1.07 (95% confidence interval: 1.03–1.12). Furthermore, interactions were noted between PM2.5, physical activity, and life satisfaction, indicating that high pollution levels may diminish the protective benefits of exercise and positive psychological well-being. Conclusions: These findings highlight the need for stringent air pollution control measures and underscore the importance of integrated strategies that consider environmental, lifestyle, and psychological factors to reduce the burden of breast cancer.