Targeting the Blood-brain Barrier with a Non-canonical Iron-mimicry Mechanism

Treatment of central nervous system (CNS) diseases is limited by the blood-brain barrier (BBB), a selective vascular interface restricting passage of most molecules from blood into brain. Specific transport systems have evolved allowing circulating polar molecules to cross the BBB and gain access to the brain parenchyma. However, to date, few ligands exploiting such systems have proven clinically viable in the setting of CNS diseases. We reasoned that combinatorial phage-display screenings in vivo would yield peptides capable of crossing the BBB and allow for the development of ligand-directed targeting strategies of the brain. Here we show the identification of a peptide mediating systemic targeting to the normal brain and to an orthotopic human glioma model. We demonstrate that this peptide functionally mimics iron through an allosteric mechanism and that a non-canonical association of (i) transferrin, (ii) the iron-mimic ligand motif, and (iii) transferrin receptor mediates binding and transport of particles across the BBB. We also show that in orthotopic human glioma xenografts, a combination of transferrin receptor over-expression plus extended vascular permeability and ligand retention result in remarkable brain tumor targeting. Moreover, such tumor targeting attributes enables Herpes simplex virus thymidine kinase-mediated gene therapy of intracranial tumors for molecular genetic imaging and suicide gene delivery with ganciclovir. Finally, we expand our data by analyzing a large panel of primary CNS tumors through comprehensive tissue microarrays. Together, our approach and results provide a translational avenue for the detection and treatment of brain tumors.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^