Stroke in a Patient With Tuberculous Meningitis and HIV Infection.

Stroke in a Patient with Tuberculous Meningitis and HIV Infection.

Mediterr J Hematol Infect Dis. 2013; 5(1): e2013017
Pasticci MB, Paciaroni M, Floridi P, Cecchini E, Baldelli F

Tuberculous meningitis (TBM) is a devastating disease. TBM occurs more commonly in HIV infected patients. The influence of HIV co-infection on clinical manifestations and outcome of TBM is not well defined. Yet, some differences have been observed and stroke has been recorded to occur more frequently. This study reports on an HIV infected Caucasian female with lung, meningeal tuberculosis and stroke due to a cortical sub-cortical ischemic lesion. TBM was documented in the absence of neurologic symptoms. At the same time, miliary lung TB caused by multi-susceptible Mycobacterium tuberculosis was diagnosed. Anti-TB therapy consisting of a combination of four drugs was administered. The patient improved and was discharged five weeks later. In conclusion, TBM and multiple underling pathologies including HIV infection, as well as other risk factors can lead to a greater risk of stroke. Moreover, drug interactions and their side effects add levels of complexity. TBM must be included in the differential diagnosis of HIV infected patients with stroke and TBM treatment needs be started as soon as possible before the onset of vasculopathy. HubMed – drug


Improved classification of lung cancer tumors based on structural and physicochemical properties of proteins using data mining models.

PLoS One. 2013; 8(3): e58772
Ramani RG, Jacob SG

Detecting divergence between oncogenic tumors plays a pivotal role in cancer diagnosis and therapy. This research work was focused on designing a computational strategy to predict the class of lung cancer tumors from the structural and physicochemical properties (1497 attributes) of protein sequences obtained from genes defined by microarray analysis. The proposed methodology involved the use of hybrid feature selection techniques (gain ratio and correlation based subset evaluators with Incremental Feature Selection) followed by Bayesian Network prediction to discriminate lung cancer tumors as Small Cell Lung Cancer (SCLC), Non-Small Cell Lung Cancer (NSCLC) and the COMMON classes. Moreover, this methodology eliminated the need for extensive data cleansing strategies on the protein properties and revealed the optimal and minimal set of features that contributed to lung cancer tumor classification with an improved accuracy compared to previous work. We also attempted to predict via supervised clustering the possible clusters in the lung tumor data. Our results revealed that supervised clustering algorithms exhibited poor performance in differentiating the lung tumor classes. Hybrid feature selection identified the distribution of solvent accessibility, polarizability and hydrophobicity as the highest ranked features with Incremental feature selection and Bayesian Network prediction generating the optimal Jack-knife cross validation accuracy of 87.6%. Precise categorization of oncogenic genes causing SCLC and NSCLC based on the structural and physicochemical properties of their protein sequences is expected to unravel the functionality of proteins that are essential in maintaining the genomic integrity of a cell and also act as an informative source for drug design, targeting essential protein properties and their composition that are found to exist in lung cancer tumors. HubMed – drug


Combined Delivery of Paclitaxel and Tanespimycin via Micellar Nanocarriers: Pharmacokinetics, Efficacy and Metabolomic Analysis.

PLoS One. 2013; 8(3): e58619
Katragadda U, Fan W, Wang Y, Teng Q, Tan C

BACKGROUND: Despite the promising anticancer efficacy observed in preclinical studies, paclitaxel and tanespimycin (17-AAG) combination therapy has yielded meager responses in a phase I clinical trial. One serious problem associated with paclitaxel/17-AAG combination therapy is the employment of large quantities of toxic organic surfactants and solvents for drug solubilization. The goal of this study was to evaluate a micellar formulation for the concurrent delivery of paclitaxel and 17-AAG in vivo. METHODOLOGYPRINCIPAL FINDINGS: Paclitaxel/17-AAG-loaded micelles were assessed in mice bearing human ovarian tumor xenografts. Compared with the free drugs at equivalent doses, intravenous administration of paclitaxel/17-AAG-loaded micelles led to 3.5- and 1.7-fold increase in the tumor concentrations of paclitaxel and 17-AAG, respectively, without significant altering drug levels in normal organs. The enhanced tumor accumulation of the micellar drugs was further confirmed by the whole-body near infrared imaging using indocyanine green-labeled micelles. Subsequently, the anticancer efficacy of paclitaxel/17-AAG-loaded micelles was examined in comparison with the free drugs (weekly 20 mg/kg paclitaxel, twice-weekly 37.5 mg/kg 17-AAG). We found that paclitaxel/17-AAG-loaded micelles caused near-complete arrest of tumor growth, whereas the free drug-treated tumors experienced rapid growth shortly after the 3-week treatment period ended. Furthermore, comparative metabolomic profiling by proton nuclear magnetic resonance revealed significant decrease in glucose, lactate and alanine with simultaneous increase in glutamine, glutamate, aspartate, choline, creatine and acetate levels in the tumors of mice treated with paclitaxel/17-AAG-loaded micelles. CONCLUSIONSSIGNIFICANCE: We have demonstrated in the current wok a safe and efficacious nano-sized formulation for the combined delivery of paclitaxel and 17-AAG, and uncovered unique metabolomic signatures in the tumor that correlate with the favorable therapeutic response to paclitaxel/17-AAG combination therapy. HubMed – drug