The nude (congenitally athymic) mouse, C3H/HeN is highly susceptible to infection with Brugia pahangi (Nematoda: Filarioidea). Normal, hairy mice show a strong thymus-dependent resistance and usually terminate the infection in the larval stages. The present study examined chronological histopathologic changes in the lumbar lymph nodes and adjacent lymphatic vessels of both hosts. In thymic mice, lymphangitis and perilymphangitis reached a maximum 14 to 17 days PI, about the time of disappearance of live worms. The infiltrate showed characteristics of both acute and chronic inflammation: eosinophils, neutrophils, eosinophilic precipitates, and sometimes necrotizing lymphangitis, as well as macrophages and plasma cells. The cellular infiltrate in nude mice was weaker and developed more slowly. Inflammatory responses to identifiable dead worms were seen in both types of hosts but appeared more frequently in thymic mice. Although variable in both models, the granulomas of thymic mice generally showed more tendency to cavitation, greater macrophage or epithelioid cell infiltration, more granulocytes, and appeared to be more destructive than the foreign body responses of nude mice. Whereas lymphangiectasis was generally progressive in nude mice, it was arrested before the end of the third week in thymic mice. In thymic mice, at maximum lumbar lymph node size (17 days), there were large areas of lymphocyte hyperplasia and heavy infiltration of plasma cells. Most nodes returned to normal mean size by the end of the second month. Little or no reactivity was seen in athymic mouse nodes. Our results suggest that some lesions of lymphatic filariasis are potentially thymus-independent: lymphatic fibrosis, lymphangiectasis, accumulations of macrophages and giant cells around disintegrating worms, calcification of worms, intralymphatic thrombosis, and moderate vascular infiltrates including eosinophils.
Atrial Fibrillation (A-Fib), Atrial Flutter (AFL) and Ventricular Fibrillation (V-Fib) are fatal cardiac abnormalities commonly affecting people in advanced age and have indication of life-threatening condition. To detect these abnormal rhythms, Electrocardiogram (ECG) signal is most commonly visualized as a significant clinical tool. Concealed non-linearities in the ECG signal can be clearly unraveled using Recurrence Quantification Analysis (RQA) technique. In this paper, RQA features are applied for classifying four classes of ECG beats namely Normal Sinus Rhythm (NSR), A-Fib, AFL and V-Fib using ensemble classifiers. The clinically significant ([Formula: see text]) features are ranked and fed independently to three classifiers viz. Decision Tree (DT), Random Forest (RAF) and Rotation Forest (ROF) ensemble methods to select the best classifier. The training and testing of the feature set is accomplished using 10-fold cross-validation strategy. The RQA coefficients using ROF provided an overall accuracy of 98.37% against 96.29% and 94.14% for the RAF and DT, respectively. The results achieved evidently ratify the superiority of ROF ensemble classifier in the diagnosis of A-Fib, AFL and V-Fib. Precision of four classes is measured using class-specific accuracy (%) and reliability of the performance is assessed using Cohen’s kappa statistic ([Formula: see text]). The developed approach can be used in therapeutic devices and help the physicians in automatic monitoring of fatal tachycardia rhythms.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.