85 95% CI 1.81-8.19). Multivariable Cox regression adjusting for all clinical covariates demonstrated an increased mortality risk (hazard ratio [HR] 1.40, 95% CI 1.00-1.97, p < 0.05) among heavy drinkers compared to nondrinkers but no delays in cART initiation (1.04 95% CI buy BMS-345541 0.81-1.34)\n\nConclusions: Among this cohort of HIV-infected women, heavy
alcohol consumption was independently associated with earlier death. Baseline factors associated with heavy alcohol use included tobacco use, hepatitis C, and illicit drug use. Alcohol is a modifiable risk factor for adverse HIV-related outcomes. Providers should consistently screen for alcohol consumption and refer HIV-infected women with heavy alcohol use for treatment.”
“This paper presents a novel adaptive reduced-rank multiple-input-multiple-output (MIMO) equalization scheme and algorithms based on alternating optimization design techniques for MIMO spatial multiplexing systems. The proposed
reduced-rank equalization structure consists of a joint iterative optimization of the following two equalization stages: 1) a transformation matrix that performs dimensionality reduction and 2) a reduced-rank estimator that retrieves the desired transmitted symbol. The proposed reduced-rank architecture is incorporated into an equalization structure that allows both decision feedback and linear schemes to mitigate the interantenna AZD0530 chemical structure (IAI) and inter-symbol interference (ISI). We develop alternating least squares (LS) expressions for the design of the transformation matrix and the reduced-rank estimator
along with computationally efficient alternating recursive least squares (RLS) click here adaptive estimation algorithms. We then present an algorithm that automatically adjusts the model order of the proposed scheme. An analysis of the LS algorithms is carried out along with sufficient conditions for convergence and a proof of convergence of the proposed algorithms to the reduced-rank Wiener filter. Simulations show that the proposed equalization algorithms outperform the existing reduced- and full-algorithms while requiring a comparable computational cost.”
“Introduction: Gliosarcoma is a rare neoplasm of the central nervous system, similar to glioblastoma multiforme. In contrast to glioblastoma, it is characterised by its propensity for extracranial metastasis (11% of the cases) due to its sarcomatous component. Intramedullary metastasis from primary gliosarcoma is extremely rare. Case report: A patient who had surgery for primary cerebral gliosarcoma developed paraparesis during the course of the disease. A magnetic resonance image showed an intramedullary spinal cord metastasis requiring surgical treatment. This article reviews the literature on intramedullary spinal cord metastasis from gliosarcoma, and highlights the characteristics, treatment and overall survival. Conclusions: Only 4 cases of intramedullary gliosarcoma metastasis are described in the literature.