Treatment with the calcineurin inhibitor and immunosuppressant cyclosporine A impairs sensorimotor gating in Dark Agouti rats

Rationale Calcineurin is a protein regulating cytokine expression in T lymphocytes and calcineurin inhibitors such as cyclosporine A (CsA) are widely used for immunosuppressive therapy. It also plays a functional role in distinct neuronal processes in the central nervous system. Disturbed information processing as seen in neuropsychiatric disorders is reflected by deficient sensorimotor gating, assessed as prepulse inhibition (PPI) of the acoustic startle response (ASR). Objective Patients who require treatment with immunosuppressive drugs frequently display neuropsychiatric alterations during treatment with calcineurin inhibitors. Importantly, knockout of calcineurin in the forebrain of mice is associated with cognitive impairments and symptoms of schizophrenia-like psychosis as seen after treatment with stimulants. Methods The present study investigated in rats effects of systemic acute and subchronic administration of CsA on sensorimotor gating. Following a single injection with effective doses of CsA, adult healthy male Dark Agouti rats were tested for PPI. For subchronic treatment, rats were injected daily with the same doses of CsA for 1 week before PPI was assessed. Since calcineurin works as a modulator of the dopamine pathway, activity of the enzyme tyrosine hydroxylase was measured in the prefrontal cortex and striatum after accomplishment of the study. Results Acute and subchronic treatment with the calcineurin inhibitor CsA disrupted PPI at a dose of 20 mg/kg. Concomitantly, following acute CsA treatment, tyrosine hydroxylase activity was reduced in the prefrontal cortex, which suggests that dopamine synthesis was downregulated, potentially reflecting a stimulatory impact of CsA on this neurotransmitter system. Conclusions The results support experimental and clinical evidence linking impaired calcineurin signaling in the central nervous system to the pathophysiology of neuropsychiatric symptoms. Moreover, these findings suggest that therapy with calcineurin inhibitors may be a risk factor for developing neurobehavioral alterations as observed after the abuse of psychomotor stimulant drugs

Guided de-escalation of antiplatelet treatment in patients with acute coronary syndrome undergoing percutaneous coronary intervention (TROPICAL-ACS): a randomised, open-label, multicentre trial

BACKGROUND: Current guidelines recommend potent platelet inhibition with prasugrel or ticagrelor for 12 months after an acute coronary syndrome managed with percutaneous coronary intervention (PCI). However, the greatest anti-ischaemic benefit of potent antiplatelet drugs over the less potent clopidogrel occurs early, while most excess bleeding events arise during chronic treatment. Hence, a stage-adapted treatment with potent platelet inhibition in the acute phase and de-escalation to clopidogrel in the maintenance phase could be an alternative approach. We aimed to investigate the safety and efficacy of early de-escalation of antiplatelet treatment from prasugrel to clopidogrel guided by platelet function testing (PFT). METHODS: In this investigator-initiated, randomised, open-label, assessor-blinded, multicentre trial (TROPICAL-ACS) done at 33 sites in Europe, patients were enrolled if they had biomarker-positive acute coronary syndrome with successful PCI and a planned duration of dual antiplatelet treatment of 12 months. Enrolled patients were randomly assigned (1:1) using an internet-based randomisation procedure with a computer-generated block randomisation with stratification across study sites to either standard treatment with prasugrel for 12 months (control group) or a step-down regimen (1 week prasugrel followed by 1 week clopidogrel and PFT-guided maintenance therapy with clopidogrel or prasugrel from day 14 after hospital discharge; guided de-escalation group). The assessors were masked to the treatment allocation. The primary endpoint was net clinical benefit (cardiovascular death, myocardial infarction, stroke or bleeding grade 2 or higher according to Bleeding Academic Research Consortium [BARC]) criteria) 1 year after randomisation (non-inferiority hypothesis; margin of 30%). Analysis was intention to treat. This study is registered with ClinicalTrials.gov, number NCT01959451, and EudraCT, 2013-001636-22. FINDINGS: Between Dec 2, 2013, and May 20, 2016, 2610 patients were assigned to study groups; 1304 to the guided de-escalation group and 1306 to the control group. The primary endpoint occurred in 95 patients (7%) in the guided de-escalation group and in 118 patients (9%) in the control group (pnon-inferiority=0.0004; hazard ratio [HR] 0.81 [95% CI 0.62-1.06], psuperiority=0.12). Despite early de-escalation, there was no increase in the combined risk of cardiovascular death, myocardial infarction, or stroke in the de-escalation group (32 patients [3%]) versus in the control group (42 patients [3%]; pnon-inferiority=0.0115). There were 64 BARC 2 or higher bleeding events (5%) in the de-escalation group versus 79 events (6%) in the control group (HR 0.82 [95% CI 0.59-1.13]; p=0.23). INTERPRETATION: Guided de-escalation of antiplatelet treatment was non-inferior to standard treatment with prasugrel at 1 year after PCI in terms of net clinical benefit. Our trial shows that early de-escalation of antiplatelet treatment can be considered as an alternative approach in patients with acute coronary syndrome managed with PCI. FUNDING: Klinikum der Universitat Munchen, Roche Diagnostics, Eli Lilly, and Daiichi Sankyo

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level