Pro–B-Type Natriuretic Peptide1–108 Circulates in the General Community Plasma Determinants and Detection of Left Ventricular Dysfunction

ObjectivesThe purpose of this study was to investigate circulating pro–B-type natriuretic peptide (proBNP1–108) in the general community and evaluate its ability to detect left ventricular (LV) dysfunction.BackgroundThe current concept for cardiac endocrine function is that, in response to cardiac stress, the heart secretes B-type natriuretic peptide (BNP1–32) and amino-terminal pro–B-type natriuretic peptide (NT-proBNP1–76) after intracardiac cleavage of their molecular precursor, proBNP1–108. We hypothesized that proBNP1–108 circulates in normal human subjects and that it is a useful biomarker for LV dysfunction.MethodsOur population-based study included a cohort of 1,939 adults (age ≥45 years) from Olmsted County, Minnesota, with 672 participants defined as healthy. Subjects underwent in-depth clinical characterization, detailed echocardiography, and measurement of proBNP1–108. Independent factors associated with proBNP1–108 and test characteristics for the detection of LV dysfunction were determined.ResultsProBNP1–108 in normal humans was strongly influenced by sex, age, heart rate, and body mass index. The median concentration was 20 ng/l with a mean proBNP1–108 to NT-proBNP1–76 ratio of 0.366, which decreased with heart failure stage. ProBNP1–108 was a sensitive (78.8%) and specific (86.1%) biomarker for detecting LV systolic dysfunction, which was comparable to BNP1–32, but less than NT-proBNP1–76, in several subsets of the population.ConclusionsProBNP1–108 circulates in the majority of healthy humans in the general population and is a sensitive and specific biomarker for the detection of systolic dysfunction. The proBNP1–108 to NT-proBNP1–76 ratio may provide insights into altered proBNP1–108 processing during heart failure progression. Thus, this highly specific assay for proBNP1–108 provides important new insights into the biology of the BNP system

HIGHER CIRCULATING TOTAL AND HIGH-MOLECULAR-WEIGHT ADIPONECTIN ARE ASSOCIATED WITH INCREASED RISK OF ATRIAL FIBRILLATION IN OLDER ADULTS

The crisis for coffee-dependent ACP countries as prices drop to a 30-year low, well below the cost of production, has led to crisis meetings in the ICO and the ACP-EU JPA. With the demise of the STABEX scheme, attention is focussed on persuading the EC to release EDF funds urgently. A long-term solution, however, cannot come solely from diversification.The crisis for coffee-dependent ACP countries as prices drop to a 30-year low,..

Explainable Machine Learning to Predict Anchored Reentry Substrate Created by Persistent Atrial Fibrillation Ablation in Computational Models

Background Postablation arrhythmia recurrence occurs in ~40% of patients with persistent atrial fibrillation. Fibrotic remodeling exacerbates arrhythmic activity in persistent atrial fibrillation and can play a key role in reentrant arrhythmia, but emergent interaction between nonconductive ablation‐induced scar and native fibrosis (ie, residual fibrosis) is poorly understood. Methods and Results We conducted computational simulations in pre‐ and postablation left atrial models reconstructed from late gadolinium enhanced magnetic resonance imaging scans to test the hypothesis that ablation in patients with persistent atrial fibrillation creates new substrate conducive to recurrent arrhythmia mediated by anchored reentry. We trained a random forest machine learning classifier to accurately pinpoint specific nonconductive tissue regions (ie, areas of ablation‐delivered scar or vein/valve boundaries) with the capacity to serve as substrate for anchored reentry‐driven recurrent arrhythmia (area under the curve: 0.91±0.03). Our analysis suggests there is a distinctive nonconductive tissue pattern prone to serving as arrhythmogenic substrate in postablation models, defined by a specific size and proximity to residual fibrosis. Conclusions Overall, this suggests persistent atrial fibrillation ablation transforms substrate that favors functional reentry (ie, rotors meandering in excitable tissue) into an arrhythmogenic milieu more conducive to anchored reentry. Our work also indicates that explainable machine learning and computational simulations can be combined to effectively probe mechanisms of recurrent arrhythmia

Effect of plasmonic gold nanoparticles on benign and malignant cellular autofluorescence: A novel probe for fluorescence based detection of cancer

Due to the strong surface fields of noble metal nanoparticles, absorption and scattering of electromagnetic radiation is greatly enhanced. Noble metallic nanoparticles represent potential novel optical probes for simultaneous molecular imaging and photothermal cancer therapy using the enhanced scattering and absorption of light. Further, gold nanoparticles can affect molecular fluorescence via chemical, electronic, or photonic interactions. Live cells generate fluorescence due to intracellular and extracellular molecules. Differences in the biochemical composition between healthy and malignant cells can be exploited in vivo to help identify cancer spectroscopically. The interaction of gold nanoparticles with cellular autofluorescence has not yet been characterized. We hypothesized that gold nanoparticles delivered to live cells in vitro would alter cellular autofluorescence and may be useful as a novel class of contrast agent for fluorescence based detection of cancer. The fluorescence of two fluorophores that are responsible for tissue autofluorescence, NADH and collagen, and of two oral squamous carcinoma cell lines and one immortalized benign epithelial cell line were measured in vitro. Gold nanoparticles of different shapes, both spheres and rods, quenched the fluorescence of the soluble NADH and collagen. Reduction of NADH fluorescence was due to oxidation of NADH to NAD+ catalyzed by gold nanoparticles (results we previously published). Reduction of collagen fluorescence appears due to photonic absorption of light. Furthermore, a mean quenching of 12/8% (p\u3c0.00050) of the tissue autofluorescence of cell suspensions was achieved in this model when nanospheres were incubated with the live cells. Gold nanospheres significantly decrease cellular autofluorescence of live cells under physiological conditions when excited at 280nm. This is the first report to our knowledge to suggest the potential of developing targeted gold nanoparticles optical probes as contrast agents for fluorescence based diagnoses of cancer. ©Adenine Press (2007)

Empiric treatment of protracted idiopathic purpura fulminans in an infant: a case report and review of the literature

Abstract Introduction Idiopathic purpura fulminans is a cutaneous thrombotic disorder usually caused by autoimmune-mediated protein C or S deficiency. This disorder typically presents with purpura and petechiae that eventually slowly or rapidly coalesce into extensive, necrotic eschars on the extremities. We present the first known case of idiopathic purpura fulminans consistent with prior clinical presentations in the setting of a prothrombotic genetic mutation, but without hallmark biochemical evidence of protein C or protein S deficiency. Another novel feature of our patient's presentation is that discontinuation of anti-coagulation has invariably led to recurrence and formation of new lesions, which is unexpected in idiopathic purpura fulminans because clearance of autoimmune factors should be followed by restoration of anti-coagulant function. Although this disease is rare, infants with suspected idiopathic purpura fulminans should be rapidly diagnosed and immediately anti-coagulated to prevent adverse catastrophic outcomes such as amputation and significant developmental delay. Case presentation A six-month-old Caucasian boy was brought to our pediatric hospital service with a low-grade fever and subacute, symmetric, serpiginous, stellate, necrotic eschars on his forearms, legs and feet that eventually spread non-contiguously to his toes, thighs and buttocks. In contrast to his impressive clinical presentation, his serologic evaluation was normal, and he was not responsive to corticosteroids and antibiotics. Full-thickness skin biopsies revealed dermal vessel thrombosis, leading to a diagnosis of idiopathic purpura fulminans and successful treatment with low-molecular-weight heparin, which was transitioned to warfarin. Long-term management has included chronic anti-coagulation because of recurrence of lesions with discontinuation of treatment. Conclusion In infants with necrotic eschars, it is important to first consider infectious, inflammatory and hematologic etiologies. In the absence of etiology for protracted idiopathic purpura fulminans, management should include tissue biopsy, in which thrombotic findings warrant a trial of empiric anti-coagulation. Some infants, including our patient, may need long-term anti-coagulation, especially when the underlying etiology of coagulation remains unidentified and symptoms recur when treatment is halted. Given that our patient still requires anti-coagulation, he may have a yet to be identified autoimmune-mediated mechanism for his truly idiopathic case of protracted purpura fulminans.</p

Improving risk prediction in heart failure using machine learning

Background: Predicting mortality is important in patients with heart failure (HF). However, current strategies for predicting risk are only modestly successful, likely because they are derived from statistical analysis methods that fail to capture prognostic information in large data sets containing multi-dimensional interactions. Methods and results: We used a machine learning algorithm to capture correlations between patient characteristics and mortality. A model was built by training a boosted decision tree algorithm to relate a subset of the patient data with a very high or very low mortality risk in a cohort of 5822 hospitalized and ambulatory patients with HF. From this model we derived a risk score that accurately discriminated between low and high-risk of death by identifying eight variables (diastolic blood pressure, creatinine, blood urea nitrogen, haemoglobin, white blood cell count, platelets, albumin, and red blood cell distribution width). This risk score had an area under the curve (AUC) of 0.88 and was predictive across the full spectrum of risk. External validation in two separate HF populations gave AUCs of 0.84 and 0.81, which were superior to those obtained with two available risk scores in these same populations. Conclusions: Using machine learning and readily available variables, we generated and validated a mortality risk score in patients with HF that was more accurate than other risk scores to which it was compared. These results support the use of this machine learning approach for the evaluation of patients with HF and in other settings where predicting risk has been challenging