Rationale: 3',5'-cyclic adenosine monophosphate (cAMP) is a ubiquitous second messenger which, upon β-adrenergic receptor (β-AR) stimulation, acts in microdomains to regulate cardiac excitation-contraction coupling by activating phosphorylation of calcium handling proteins. One crucial microdomain is in vicinity of the cardiac ryanodine receptor type 2 (RyR2) which is associated with arrhythmogenic diastolic calcium leak from the sarcoplasmic reticulum (SR) often occurring in heart failure. Objective: We sought to establish a real time live cell imaging approach capable of directly visualizing cAMP in the vicinity of mouse and human RyR2 and to analyze its pathological changes in failing cardiomyocytes under β-AR stimulation. Methods and Results: We generated a novel targeted fluorescent biosensor Epac1-JNC for RyR2-associated cAMP and expressed it in transgenic mouse hearts as well in human ventricular myocytes using adenoviral gene transfer. In healthy cardiomyocytes, β 1 -AR but not β 2 -AR stimulation strongly increased local RyR2-associated cAMP levels. However, already in cardiac hypertrophy induced by aortic banding, there was a marked subcellular redistribution of phosphodiesterases (PDEs) 2, 3 and 4, which included a dramatic loss of the local pool of PDE4. This was also accompanied by measurableβ2-AR/AMP signals in the vicinity of RyR2 in failing mouse and human myocytes, increased β2-AR-dependent RyR2 phosphorylation, SR calcium leak and arrhythmia susceptibility. Conclusions: Our new imaging approach could visualize cAMP levels in the direct vicinity of cardiac RyR2. Unexpectedly, in mouse and human failing myocytes, it could uncover functionally relevant local arrhythmogenic β2-AR/cAMP signals which might be an interesting antiarrhythmic target for heart failure.
The clinical presentations of early idiopathic Parkinson's disease (PD) substantially overlap with those of atypical parkinsonian syndromes like multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). This study aimed to develop metabolic imaging indices based on deep learning to support the differential diagnosis of these conditions. Methods: A benchmark Huashan parkinsonian PET imaging (HPPI, China) database including 1275 parkinsonian patients and 863 non-parkinsonian subjects with 18 F-FDG PET images was established to support artificial intelligence development. A 3D deep convolutional neural network was developed to extract deep metabolic imaging (DMI) indices, which was blindly evaluated in an independent cohort with longitudinal follow-up from the HPPI, and an external German cohort of 90 parkinsonian patients with different imaging acquisition protocols. Results: The proposed DMI indices had less ambiguity space in the differential diagnosis. They achieved sensitivities of 98.1%, 88.5%, and 84.5%, and specificities of 90.0%, 99.2%, and 97.8% for the diagnosis of PD, MSA, and PSP in the blind test cohort. In the German cohort, They resulted in sensitivities of 94.1%, 82.4%, 82.1%, and specificities of 84.0%, 99.9%, 94.1% respectively. Employing the PET scans independently achieved comparable performance to the integration of demographic and clinical information into the DMI indices. Conclusion:The DMI indices developed on the HPPI database show potential to provide an early and accurate differential diagnosis for parkinsonism and is robust when dealing with discrepancies between populations and imaging acquisitions.
The present study focused on establishing a novel, (pre-)screening approach that enables the development of promising performing self-nanoemulsifying drug delivery systems (SNEDDSs) with a limited number of experiments. The strategic approach was based on first identifying appropriate excipients (oils/lipids, surfactants, and co-solvents) providing a high saturation solubility for lipophilic model compounds with poor aqueous solubility. Excipients meeting these requirements were selected for SNEDDS development, and a special triangular mixture design was applied for determining excipient ratios for the SNEDDS formulations. Celecoxib and fenofibrate were used as model drugs. Formulations were studied applying a specific combination of in vitro characterization methods. Specifications for a promising SNEDDS formulation were self-imposed: a very small droplet size (< 50 nm), a narrow size distribution of these droplets (PDI < 0.15) and a high transmittance following SNEDDS dispersion in water (> 99% in comparison with purified water). Excipients that provided a nanoemulsion after dispersion were combined, and ratios were optimized using a customized mapping method in a triangular mixture design. The best performing formulations were finally studied for their in vitro release performance. Results of the study demonstrate the efficiency of the customized screening tool approach. Since it enables successful SNEDDS development in a short time with manageable resources, this novel screening tool approach could play an important role in future SNEDDS development.
Background Many patients awaiting heart transplantation (HTX) have a cardiac implantable electronic device (CIED). Lead removal is often still a part of the HTX procedure. Abandoned lead fragments carry a risk for infections and prohibit magnetic resonance imaging (MRI) imaging. This study evaluated the concept of an elective lead management algorithm after HTX. Methods and Results Between 2009 and 2018, 102 consecutive patients with previously implanted CIED underwent HTX. Lead removal by manual traction during HTX was performed in 74 patients until December 2014. Afterward, treatment strategy was changed and 28 patients received elective lead extraction procedures in a hybrid operating room (OR) using specialized extraction tools. Total of 74 patients with 157 leads underwent lead extraction by manual traction during HTX. The mean lead age was 32.3 ± 38.7 months. Postoperative X‐ray revealed abandoned intravascular lead fragments in 31(41.9%) patients, resulting in a complete lead extraction rate of only 58.1%. The high rate of unsuccessful lead extractions led to the change in the extraction strategy in 2015. Since then, HTX was performed in 28 CIED patients. In those patients, 64 leads with a mean lead age of 53.8 ± 42.8 months were treated in an elective lead extraction procedure. No major or minor complications occurred during lead extraction. All leads could be removed completely, resulting in a procedural success rate of 100%. Conclusion Our results demonstrate that chronically implanted leads should be removed in an elective procedure, using appropriate extraction tools. This enables complete lead extraction, which reduces the infection risk in this patient population with the necessity for permanent immunosuppressive therapy and allows further MRI surveillance.
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