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In diabetic cardiomyopathy, left ventricular (LV) diastolic dysfunction is one of the earliest signs of cardiac involvement prior to the definitive development of heart failure (HF). We aimed to explore the LV diastolic function using electrocardiography (ECG)-gated \(^{18}\)F-fluorodeoxyglucose positron emission tomography (\(^{18}\)F-FDG PET) imaging beyond the assessment of cardiac glucose utilization in a diabetic rat model. ECG-gated \(^{18}\)F-FDG PET imaging was performed in a rat model of type 2 diabetes (ZDF fa/fa) and ZL control rats at age of 13 weeks (n=6, respectively). Under hyperinsulinemic-euglycemic clamp to enhance cardiac activity, \(^{18}\)F-FDG was administered and subsequently, list-mode imaging using a dedicated small animal PET system with ECG signal recording was performed. List-mode data were sorted and reconstructed into tomographic images of 16 frames per cardiac cycle. Left ventricular functional parameters (systolic: LV ejection fraction (EF), heart rate (HR) vs. diastolic: peak filling rate (PFR)) were obtained using an automatic ventricular edge detection software. No significant difference in systolic function could be obtained (ZL controls vs. ZDF rats: LVEF, 62.5±4.2 vs. 59.4±4.5%; HR: 331±35 vs. 309±24 bpm; n.s., respectively). On the contrary, ECG-gated PET imaging showed a mild but significant decrease of PFR in the diabetic rats (ZL controls vs. ZDF rats: 12.1±0.8 vs. 10.2±1 Enddiastolic Volume/sec, P<0.01). Investigating a diabetic rat model, ECG-gated \(^{18}\)F-FDG PET imaging detected LV diastolic dysfunction while systolic function was still preserved. This might open avenues for an early detection of HF onset in high-risk type 2 diabetes before cardiac symptoms become apparent.
The heart failure (HF) epidemic continues to rise with coronary artery disease (CAD) as one of its main causes. Novel concepts for risk stratification to guide the referring cardiologist towards revascularization procedures are of significant value. Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) agents has demonstrated high accuracy for the detection of clinically relevant stenoses. With positron emission tomography (PET) becoming more widely available, mainly due to its diagnostic performance in oncology, perfusion imaging with that modality is more practical than in the past and overcomes existing limitations of SPECT MPI. Advantages of PET include more reliable quantification of absolute myocardial blood flow, the routine use of computed tomography for attenuation correction, a higher spatiotemporal resolution and a higher count sensitivity. Current PET radiotracers such as rubidium-82 (half-life, 76 sec), oxygen-15 water (2 min) or nitrogen-13 ammonia (10 min) are labeled with radionuclides with very short half-lives, necessitating that stress imaging is performed under pharmacological vasodilator stress instead of exercise testing. However, with the introduction of novel 18F-labeled MPI PET radiotracers (half-life, 110 min), the intrinsic advantages of PET can be combined with exercise testing. Additional advantages of those radiotracers include, but are not limited to: potentially improved cost-effectiveness due to the use of pre-existing delivery systems and superior imaging qualities, mainly due to the shortest positron range among available PET MPI probes. In the present review, widely used PET MPI radiotracers will be reviewed and potential novel 18F-labeled perfusion radiotracers will be discussed.
Major depressive disorder (MDD) is a very common stress-related mental disorder that carries a huge burden for affected patients and the society. It is associated with a high mortality that derives from suicidality and the development of serious medical conditions such as heart diseases, diabetes, and stroke. Although a range of effective antidepressants are available, more than 50% of the patients do not respond to the first treatment they are prescribed and around 30% fail to respond even after several treatment attempts. The heterogeneous condition of MDD, the lack of biomarkers matching patients with the right treatments and the situation that almost all available drugs are only targeting the serotonin, norepinephrine, or dopamine signaling, without regulating other potentially dysregulated systems may explain the insufficient treatment status. The hypothalamic-pituitary-adrenal (HPA) axis is one of these other systems, there is numerous and robust evidence that it is implicated in MDD and other stress-related conditions, but up to date there is no specific drug targeting HPA axis components that is approved and no test that is routinely used in the clinical setting identifying patients for such a specific treatment. Is there still hope after these many years for a breakthrough of agents targeting the HPA axis? This review will cover tests detecting altered HPA axis function and the specific treatment options such as glucocorticoid receptor (GR) antagonists, corticotropin-releasing hormone 1 (CRH1) receptor antagonists, tryptophan 2,3-dioxygenase (TDO) inhibitors and FK506 binding protein 5 (FKBP5) receptor antagonists.
Adrenocortical carcinoma (ACC) is a rare, aggressive cancer with still partially unknown pathogenesis, heterogenous clinical behaviour and no effective treatment for advanced stages. Therefore, there is an urgent clinical unmet need for better prognostication strategies, innovative therapies and significant improvement of the management of the individual patients. In this review, we summarize available studies on molecular prognostic markers and markers predictive of response to standard therapies as well as newly proposed drug targets in sporadic ACC. We include in vitro studies and available clinical trials, focusing on alterations at the DNA, RNA and epigenetic levels. We also discuss the potential of biomarkers to be implemented in a clinical routine workflow for improved ACC patient care.
Identification of new drug targets in adrenocortical carcinoma through targeted mRNA analysis
(2021)
Adrenocortical carcinomas (ACC) are aggressive tumors associated with a heterogeneous but generally poor prognosis and limited treatment options for advanced stages. Despite promising molecular insights and improved understanding of ACC biology, efficient targeted therapies have not been identified yet. Thus, this study aims to identify potential new drug targets for a future personalized therapeutic approach.
RNA was isolated from 104 formalin-fixed paraffin-embedded tumor samples from ACC patients, 40 of those 104 cases proved to be suitable for further mRNA analyses according to the quality check of the extracted RNA. Gene expression of 84 known cancer drug targets was evaluated by quantitative real-time PCR using 5 normal adrenal glands as reference. Protein expression was investigated for selected candidate drug targets by immunohistochemistry in 104 ACC samples, 11 adenomas and 6 normal adrenal glands. Efficacy of an available inhibitor of the most promising candidate was tested by functional in vitro experiments in two ACC cell lines (NCI-H295R and MUC1) alone or in combination with other drugs.
Most frequently overexpressed genes were TOP2A, IGF2, CDK1, CDK4, PLK4 and PLK1. Nuclear immunostaining of CDK1, CDK4 and PLK1 significantly correlated with the respective mRNA expression. CDK4 was chosen as the most promising candidate for functional validation as it is actionable by FDA-approved CDK4/6 inhibitors. ACC samples with copy number gains at CDK4 locus presented significantly higher CDK4 expression levels. The CDK4/6 inhibitor palbociclib showed a concentration- and time- dependent reduction of cell viability in vitro, which was more pronounced in NCI-H295R than in MUC1 cells. This was in line with higher CDK4 expression at western blot analysis in NCI-H295R cells. Furthermore, palbociclib was applied in combination with dual IGFR/IR inhibitor linsitinib showing a synergistic effect on reducing cell viability. In conclusion, this proof-of-principle study confirmed RNA profiling to be useful to discover potential drug targets. Detected drug targets are suitable to be investigated by immunohistochemistry in the clinical setting. Moreover, CDK4/6 inhibitors are promising candidates for treatment of a subset of patients with tumors presenting CDK4 copy number gains and/or overexpression, while linsitinib might be an interesting combination partner in patients with both IGF2 and IGF1R overexpression.
These results are intended as a basis for a validation study in a prospective cohort, further evaluation in vivo in suitable mouse models or testing in patients with ACC in clinical trials are needed and might improve the future management of patients with ACC in terms of precision medicine.
Background
Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances.
Methods
A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation.
Results
ConVNG tracking accuracy reached 9–15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms’ precision was inferior to VOG.
Conclusions
ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.