Hjortdavid4016

Their 1-month follow-up left ventricular ejection fraction increased significantly (P  less then  0.001). There were no deaths, and all patients were discharged from hospital with good quality of life. In contrast, all the eight patients receiving DFO monotherapy died (P  less then  0.001). Accordingly, combined chelation therapy with high-dose L1 and DFO should be considered in patients with TDT presenting cardiac complications.Hematopoietic stem cell transplantation (HSCT) is a risk factor for viral hepatitis reactivations because it affects lymphocyte number and functions. Latent hepatitis B virus (HBV) may stay in dormant form in hepatocytes and may be reactivated in prolonged immunosuppression. This study analyzes the incidence of reactivation of HBV infections in HSCT patients in a middle endemic country like Turkey. Five hundred and sixty-one HSCT patients from 1994 to 2015 were retrospectively evaluated. Sixty-six patients had a serologic feature of HBV infection. Fifteen patients were hepatitis B surface antigen (HBsAg)-positive patients (3 allogeneic and 12 autologous) while 51 of them were anti-hepatitis B core IgG (anti-HBc IgG)-positive patients (22 allogeneic and 29 autologous). Although under lamivudine prophylaxis, reactivation was seen in three of 12 (25%) chronic HBV (HBsAg positive) patients who received autologous HSCT and in two of the three HBsAg-positive patients who received allogeneic HSCT. Rate of reactivatiantation type. Prophylaxis should also be given to anti-HBc IgG-positive patients if an allogeneic HSCT is to be performed.The compliance of the proximal aortic wall is a major determinant of cardiac afterload. Aortic compliance is often estimated based on cross-sectional area changes over the pulse pressure, under the assumption of a negligible longitudinal stretch during the pulse. However, the proximal aorta is subjected to significant axial stretch during cardiac contraction. In the present study, we sought to evaluate the importance of axial stretch on compliance estimation by undertaking both an in silico and an in vivo approach. In the computational analysis, we developed a 3-D finite element model of the proximal aorta and investigated the discrepancy between the actual wall compliance to the value estimated after neglecting the longitudinal stretch of the aorta. A parameter sensitivity analysis was further conducted to show how increased material stiffness and increased aortic root motion might amplify the estimation errors (discrepancies between actual and estimated distensibility ranging from - 20 to - 62%). Axial and circumferential aortic deformation during ventricular contraction was also evaluated in vivo based on MR images of the aorta of 3 healthy young volunteers. The in vivo results were in good qualitative agreement with the computational analysis (underestimation errors ranging from - 26 to - 44%, with increased errors reflecting higher aortic root displacement). Both the in silico and in vivo findings suggest that neglecting the longitudinal strain during contraction might lead to severe underestimation of local aortic compliance, particularly in the case of women who tend to have higher aortic root motion or in subjects with stiff aortas.The high-altitude regions of Himalaya are among the best indicators of climate change yet noticeable for the lack of climate monitoring stations. However, they support ethnic communities whose livelihood activities are climate driven. Consequently, these communities are keen observers of the same and documenting their perception on changing climate is now an important area of global research. Therefore, the present study was conducted with the prime objective of documenting the climate change perception of Bhangalis-a resident community of western Himalaya, and analyzing variation in their perceptions in relation to age and gender. For this, respondent surveys (household, n = 430; individual interviews, n = 240) were carried out and the collected data were subjected to statistical analyses. The study also validated the perception of Bhangalis using the available weather data (1974-2017) through the Mann-Kendall test. The results reveal that Bhangalis perceived 11 indicators of changing climate, of which decrease in snowfall was the most prominent (reported by ~ 97% of the respondents). The perceptions varied between the two genders with males having significantly higher proportion of responses for all the 11 indicators. Similarly, differences in perception among the age groups were also observed, elderly people reported higher proportion of climate change indicators as compared to respondents of lower age. Notably, patterns of temperature and rainfall perceptions by the Bhangalis agreed with the trends of meteorological data. This highlights the importance of the study in documenting knowledge of ethnic communities especially from areas that lack monitoring stations. It argues for involving them in climate change programs.

To develop and evaluate an automated method for prostate T2-weighted (T2W) image normalization using dual-reference (fat and muscle) tissue.

Transverse T2W images from the publicly available PROMISE12 (N = 80) and PROSTATEx (N = 202) challenge datasets, and an in-house collected dataset (N = 60) were used. Aggregate channel features object detectors were trained to detect reference fat and muscle tissue regions, which were processed and utilized to normalize the 3D images by linear scaling. Mean prostate pseudo T2 values after normalization were compared to literature values. Inter-patient histogram intersections of voxel intensities in the prostate were compared between our approach, the original images, and other commonly used normalization methods. check details Healthy vs. malignant tissue classification performance was compared before and after normalization.

The prostate pseudo T2 values of the three tested datasets (mean ± standard deviation = 78.49 ± 9.42, 79.69 ± 6.34 and 79.29 ± 6.30ms) corresponded well to T2 values from literature (80 ± 34ms). Our normalization approach resulted in significantly higher (p < 0.001) inter-patient histogram intersections (median = 0.746) than the original images (median = 0.417) and most other normalization methods. Healthy vs. malignant classification also improved significantly (p < 0.001) in peripheral (AUC 0.826 vs. 0.769) and transition (AUC 0.743 vs. 0.678) zones.

An automated dual-reference tissue normalization of T2W images could help improve the quantitative assessment of prostate cancer.

An automated dual-reference tissue normalization of T2W images could help improve the quantitative assessment of prostate cancer.