Factors associated with mortality in HIV-infected and uninfected patients with pulmonary tuberculosis

<p>Abstract</p> <p>Background</p> <p>HIV has fuelled the TB epidemic in sub-Saharan Africa. Mortality in patients co-infected with TB and HIV is high. Managing factors influencing mortality in TB patients might help reducing it. This study investigates factors associated with mortality including patients' HIV sero-status, CD4 cell count, laboratory, nutritional and demographic characteristics in AFB smear positive pulmonary TB patients.</p> <p>Methods</p> <p>We studied 887 sputum smear positive PTB patients, between 18 and 65 years of age receiving standard 8 months anti-TB treatment. Demographic, anthropometric and laboratory data including HIV, CD4 and other tests were collected at baseline and at regular intervals. Patients were followed for a median period of 2.5 years.</p> <p>Results</p> <p>Of the 887 participants, 155 (17.5%) died, of whom 90.3% (140/155) were HIV-infected, a fatality of 29.7% (140/471) compared to 3.6% (15/416) among HIV-uninfected. HIV infection, age, low Karnofsky score, CD4 cell counts and hemoglobin, high viral load, and oral thrush were significantly associated with high mortality in all patients.</p> <p>Conclusion</p> <p>Mortality among HIV-infected TB patients is high despite the use of effective anti-TB therapy. Most deaths occur after successful completion of therapy, an indication that patients die from causes other than TB. HIV infection is the strongest independent predictor of mortality in this cohort.</p

Extraction of pharmacokinetic evidence of drug-drug interactions from the literature

Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a subject of intense scientific interest. Biomedical literature mining can aid DDI research by extracting evidence for large numbers of potential interactions from published literature and clinical databases. Though DDI is investigated in domains ranging in scale from intracellular biochemistry to human populations, literature mining has not been used to extract specific types of experimental evidence, which are reported differently for distinct experimental goals. We focus on pharmacokinetic evidence for DDI, essential for identifying causal mechanisms of putative interactions and as input for further pharmacological and pharmacoepidemiology investigations. We used manually curated corpora of PubMed abstracts and annotated sentences to evaluate the efficacy of literature mining on two tasks: first, identifying PubMed abstracts containing pharmacokinetic evidence of DDIs; second, extracting sentences containing such evidence from abstracts. We implemented a text mining pipeline and evaluated it using several linear classifiers and a variety of feature transforms. The most important textual features in the abstract and sentence classification tasks were analyzed. We also investigated the performance benefits of using features derived from PubMed metadata fields, various publicly available named entity recognizers, and pharmacokinetic dictionaries. Several classifiers performed very well in distinguishing relevant and irrelevant abstracts (reaching F10.93, MCC0.74, iAUC0.99) and sentences (F10.76, MCC0.65, iAUC0.83). We found that word bigram features were important for achieving optimal classifier performance and that features derived from Medical Subject Headings (MeSH) terms significantly improved abstract classification. We also found that some drug-related named entity recognition tools and dictionaries led to slight but significant improvements, especially in classification of evidence sentences. Based on our thorough analysis of classifiers and feature transforms and the high classification performance achieved, we demonstrate that literature mining can aid DDI discovery by supporting automatic extraction of specific types of experimental evidence.National Institutes of Health, National Library of Medicine Program, grant 01LM011945-01 "BLR: Evidence-based Drug-Interaction Discovery: In-Vivo, In-Vitro and Clinical," a grant from the Indiana University Collaborative Research Program 2013, "Drug-Drug Interaction Prediction from Large-scale Mining of Literature and Patient Records," as well as a grant from the joint program between the Fundação Luso-Americana para o Desenvolvimento (Portugal) and National Science Foundation (USA), 2012-2014, "Network Mining For Gene Regulation And Biochemical Signaling.

Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages

Generalist and specialist species differ in the breadth of their ecological niches. Little is known about the niche width of obligate human pathogens. Here we analyzed a global collection of Mycobacterium tuberculosis lineage 4 clinical isolates, the most geographically widespread cause of human tuberculosis. We show that lineage 4 comprises globally distributed and geographically restricted sublineages, suggesting a distinction between generalists and specialists. Population genomic analyses showed that, whereas the majority of human T cell epitopes were conserved in all sublineages, the proportion of variable epitopes was higher in generalists. Our data further support a European origin for the most common generalist sublineage. Hence, the global success of lineage 4 reflects distinct strategies adopted by different sublineages and the influence of human migration.We thank S. Lecher, S. Li and J. Zallet for technical support. Calculations were performed at the sciCORE scientific computing core facility at the University of Basel. This work was supported by the Swiss National Science Foundation (grants 310030_166687 (S.G.) and 320030_153442 (M.E.) and Swiss HIV Cohort Study grant 740 to L.F.), the European Research Council (309540-EVODRTB to S.G.), TB-PAN-NET (FP7-223681 to S.N.), PathoNgenTrace projects (FP7-278864-2 to S.N.), SystemsX.ch (S.G.), the German Center for Infection Research (DZIF; S.N.), the Novartis Foundation (S.G.), the Natural Science Foundation of China (91631301 to Q.G.), and the National Institute of Allergy and Infectious Diseases (5U01-AI069924-05) of the US National Institutes of Health (M.E.)

Off-label psychopharmacologic prescribing for children: History supports close clinical monitoring

The review presents pediatric adverse drug events from a historical perspective and focuses on selected safety issues associated with off-label use of medications for the psychiatric treatment of youth. Clinical monitoring procedures for major psychotropic drug classes are reviewed. Prior studies suggest that systematic treatment monitoring is warranted so as to both minimize risk of unexpected adverse events and exposures to ineffective treatments. Clinical trials to establish the efficacy and safety of drugs currently being used off-label in the pediatric population are needed. In the meantime, clinicians should consider the existing evidence-base for these drugs and institute close clinical monitoring

Regional glutamine deficiency in tumours promotes dedifferentiation through inhibition of histone demethylation

Poorly organized tumour vasculature often results in areas of limited nutrient supply and hypoxia. Despite our understanding of solid tumour responses to hypoxia, how nutrient deprivation regionally affects tumour growth and therapeutic response is poorly understood. Here, we show that the core region of solid tumours displayed glutamine deficiency compared with other amino acids. Low glutamine in tumour core regions led to dramatic histone hypermethylation due to decreased α-ketoglutarate levels, a key cofactor for the Jumonji-domain-containing histone demethylases. Using patient-derived ^(V600E)BRAF melanoma cells, we found that low-glutamine-induced histone hypermethylation resulted in cancer cell dedifferentiation and resistance to BRAF inhibitor treatment, which was largely mediated by methylation on H3K27, as knockdown of the H3K27-specific demethylase KDM6B and the methyltransferase EZH2 respectively reproduced and attenuated the low-glutamine effects in vitro and in vivo. Thus, intratumoral regional variation in the nutritional microenvironment contributes to tumour heterogeneity and therapeutic response