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1.
Braz. j. med. biol. res ; 49(5): e5206, 2016. tab, graf
Article in English | LILACS | ID: biblio-951675

ABSTRACT

Our objective is to evaluate the accuracy of three algorithms in differentiating the origins of outflow tract ventricular arrhythmias (OTVAs). This study involved 110 consecutive patients with OTVAs for whom a standard 12-lead surface electrocardiogram (ECG) showed typical left bundle branch block morphology with an inferior axis. All the ECG tracings were retrospectively analyzed using the following three recently published ECG algorithms: 1) the transitional zone (TZ) index, 2) the V2 transition ratio, and 3) V2 R wave duration and R/S wave amplitude indices. Considering all patients, the V2 transition ratio had the highest sensitivity (92.3%), while the R wave duration and R/S wave amplitude indices in V2 had the highest specificity (93.9%). The latter finding had a maximal area under the ROC curve of 0.925. In patients with left ventricular (LV) rotation, the V2 transition ratio had the highest sensitivity (94.1%), while the R wave duration and R/S wave amplitude indices in V2 had the highest specificity (87.5%). The former finding had a maximal area under the ROC curve of 0.892. All three published ECG algorithms are effective in differentiating the origin of OTVAs, while the V2 transition ratio, and the V2 R wave duration and R/S wave amplitude indices are the most sensitive and specific algorithms, respectively. Amongst all of the patients, the V2 R wave duration and R/S wave amplitude algorithm had the maximal area under the ROC curve, but in patients with LV rotation the V2 transition ratio algorithm had the maximum area under the ROC curve.


Subject(s)
Humans , Male , Female , Middle Aged , Arrhythmias, Cardiac/etiology , Arrhythmias, Cardiac/physiopathology , Algorithms , Heart Ventricles/physiopathology , Retrospective Studies , Electrocardiography
2.
Braz. j. med. biol. res ; 46(10): 831-838, 24/set. 2013. tab, graf
Article in English | LILACS | ID: lil-688557

ABSTRACT

Wear particles are phagocytosed by macrophages and other inflammatory cells, resulting in cellular activation and release of proinflammatory factors, which cause periprosthetic osteolysis and subsequent aseptic loosening, the most common causes of total joint arthroplasty failure. During this pathological process, tumor necrosis factor-alpha (TNF-α) plays an important role in wear-particle-induced osteolysis. In this study, recombination adenovirus (Ad) vectors carrying both target genes [TNF-α small interfering RNA (TNF-α-siRNA) and bone morphogenetic protein 2 (BMP-2)] were synthesized and transfected into RAW264.7 macrophages and pro-osteoblastic MC3T3-E1 cells, respectively. The target gene BMP-2, expressed on pro-osteoblastic MC3T3-E1 cells and silenced by the TNF-α gene on cells, was treated with titanium (Ti) particles that were assessed by real-time PCR and Western blot. We showed that recombinant adenovirus (Ad-siTNFα-BMP-2) can induce osteoblast differentiation when treated with conditioned medium (CM) containing RAW264.7 macrophages challenged with a combination of Ti particles and Ad-siTNFα-BMP-2 (Ti-ad CM) assessed by alkaline phosphatase activity. The receptor activator of nuclear factor-κB ligand was downregulated in pro-osteoblastic MC3T3-E1 cells treated with Ti-ad CM in comparison with conditioned medium of RAW264.7 macrophages challenged with Ti particles (Ti CM). We suggest that Ad-siTNFα-BMP-2 induced osteoblast differentiation and inhibited osteoclastogenesis on a cell model of a Ti particle-induced inflammatory response, which may provide a novel approach for the treatment of periprosthetic osteolysis.


Subject(s)
Animals , /metabolism , Osteoblasts/metabolism , RNA, Small Interfering/metabolism , Titanium/adverse effects , Tumor Necrosis Factor-alpha/metabolism , Adenoviridae/genetics , /genetics , Bone Resorption/genetics , Cell Differentiation , Cell Line , Gene Expression , Genetic Vectors/genetics , Osteoblasts/cytology , Osteoblasts/drug effects , RNA, Small Interfering/genetics , Tumor Necrosis Factor-alpha/genetics
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