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ObjectiveThe purpose of this study was to establish an animal model of chronic pulmonary hypertension with a single-dose intraperitoneal injection of monocrotaline (MCT) in young Tibet minipigs, so as to enable both invasive and noninvasive measurements and hence facilitate future studies.MethodsTwenty-four minipigs (8-week-old) were randomized to receive single-dose injection of 12.0 mg/kg MCT (MCT group, n = 12) or placebo (control group, n = 12 each). On day 42, all animals were evaluated for pulmonary hypertension with conventional transthoracic echocardiography, right heart catheterization (RHC), and pathological changes. Findings of these studies were compared between the two groups.ResultsAt echocardiography, the MCT group showed significantly higher pulmonary arterial mean pressure (PAMP) compared with the controls (P<0.001). The pulmonary valve curve showed v-shaped signals with reduction of a-waves in minipigs treated with MCT. In addition, the MCT group had longer pulmonary artery pre-ejection phases, and shorter acceleration time and ejection time. RHC revealed higher mean pulmonary arterial pressure (mPAP) in the MCT group than in the control group (P<0.01). A significant and positive correlation between the mPAP values and the PAMP values (R = 0.974, P<0.0001), and a negative correlation between the mPAP and ejection time (R = 0.680, P<0.0001) was noted. Pathology demonstrated evidence of pulmonary vascular remodeling and higer index of right ventricular hypertrophy in MCT-treated minipigs.ConclusionA chronic pulmonary hypertension model can be successfully established in young minipigs at six weeks after MCT injection. These minipig models exhibited features of pulmonary arterial hypertension that can be evaluated by both invasive (RHC) and noninvasive (echocardiography) measurements, and may be used as an easy and stable tool for future studies on pulmonary hypertension.

Carotid proliferative plaques were developed in a canine model of chronic hypertension induced by a novel vascular clip. The plaques were mainly comprised of smooth muscle cells, proteoglycans, and collagen fibers.

Objectives Chest X-rays (CXRs) convey much illegible physiological information that deep learning model (DLM) has been reported interpreting successfully. Since the electrocardiogram age established by DLM was revealed as a heart biological marker, we hypothesize that CXR age has similar potential to describe the heart and lung states. Therefore, we developed a DLM to predict sex and age through CXR and analyzed its relation with future cardiovascular diseases (CVD). Methods A total of 90,396 CXRs aged 20 to 90 were collected and separated into a development set with 53,102 CXRs and demographic information pairs, a tuning set with 7073 pairs, an internal validation set with 17,364 pairs, and an external validation set with 12,857 pairs. The study trained DLM with development set for estimating age and sex and compared them to actual information. Results The mean absolute errors of predicted age were 4.803 and 4.313 years in the internal and external validation sets, respectively. The area under the curve of sex analysis was 0.9993 and 0.9988 in the internal and external validation sets, respectively. Patients whose CXR age was 5 years older than chronologic age lead to higher risk of all-cause mortality (hazard ratio (HR): 2.42, 95% confidence interval (CI): 2.00–2.92), cardiovascular (CV)-cause mortality (HR: 7.57, 95% CI: 4.55–12.60), new-onset heart failure (HR: 2.07, 95% CI: 1.56–2.76), new-onset chronic kidney disease (HR: 1.73, 95% CI: 1.46–2.05), new-onset acute myocardial infarction (HR: 1.80, 95% CI: 1.12–2.92), new-onset stroke (HR: 1.45, 95% CI: 1.10–1.90), new-onset coronary artery disease (HR: 1.26, 95% CI: 1.04–1.52), and new-onset atrial fibrillation (HR: 1.43, 95% CI: 1.01–2.02). Conclusions Using DLM to predict CXR age provided additional information for future CVDs. Older CXR age is an accessible risk classification tool for clinician use.