Search

In cancer treatment, apoptosis is a well-recognized cell death mechanism through which cytotoxic agents kill tumor cells. Here we report that dying tumor cells use the apoptotic process to generate potent growth-stimulating signals to stimulate the repopulation of tumors undergoing radiotherapy. Furthermore, activated caspase 3, a key executioner in apoptosis, is involved in the growth stimulation. One downstream effector that caspase 3 regulates is prostaglandin [E.sub.2] ([PGE.sub.2]), which can potently stimulate growth of surviving tumor cells. Deficiency of caspase 3 either in tumor cells or in tumor stroma caused substantial tumor sensitivity to radiotherapy in xenograft or mouse tumors. In human subjects with cancer, higher amounts of activated caspase 3 in tumor tissues are correlated with markedly increased rate of recurrence and death. We propose the existence of a cell death-induced tumor repopulation pathway in which caspase 3 has a major role., There is a large amount of cell death during cytotoxic cancer therapy such as radiation therapy (1,2). It is normally assumed that dying or dead cells get absorbed by scavenger [...]

Purpose: Irinotecan is a commonly used chemotherapeutic in solid tumor malignancies. Oratecan is an investigational product comprised of encequidar methanesulfonate, a novel minimally absorbed P-glycoprotein pump inhibitor, and irinotecan. This study sought to determine the maximum tolerated dose (MTD) of oratecan in patients with advanced malignancies.Methods: Using a "3 + 3″ dose-escalation design, patients were treated with oratecan on day 1 every 21 days. The irinotecan dose was escalated from 20 to 320 mg/m2. The encequidar methanesulfonate dose was fixed at 15 mg (12.9 mg free base). PK sampling for irinotecan, encequidar and its major metabolites was performed following a single dose of oratecan during cycle 1. Patients were treated until disease progression or unacceptable toxicity.Results: Thirty-five patients were treated. The MTD was determined to be 280 mg/m2 every 21 days. Irinotecan and SN-38 plasma concentration-time profile showed that irinotecan exposure increased with dose and followed biexponential decay. Nine of 17 patients at oratecan dose levels 200 mg/m2 and above had SN-38 exposures comparable to those with intravenous irinotecan at standard dosing. None of the 35 patients achieved a radiologic response, ten patients had SD for > 8 weeks; the median progression-free survival for all treated patients was 9 weeks (95% CI 8.6-13.9).Conclusions: The MTD of oratecan was encequidar methanesulfonate 15 mg plus irinotecan 280 mg/m2. Exposure for irinotecan and SN-38 increased with increased dose. Potential antitumor activity was observed at the 280 and 320 mg/m2 dose levels. The safety profile of oratecan was comparable to that of intravenous irinotecan. [ABSTRACT FROM AUTHOR]

Purpose: Oraxol is an oral formulation of paclitaxel administered with a novel, minimally absorbed P-glycoprotein inhibitor encequidar (HM30181A). This phase Ib study was conducted to determine the maximum-tolerated dose (MTD) of Oraxol administered at a fixed dose for up to 5 consecutive days in patients with advanced malignancies. Methods: Part 1 of this study utilized a 3 + 3 dose-escalation design to determine the MTD of oral paclitaxel 270 mg plus oral encequidar 15 mg administered daily. Dose escalation was achieved by increasing the number of consecutive dosing days per week (from 2 to 5 days per week). Dosing occurred for 3 consecutive weeks out of a 4-week cycle. Part 2 treated additional patients at the MTD to determine tolerability and recommended phase II dose (RP2D). Adverse events, tumor responses, and pharmacokinetic profiles were assessed. Results: A total of 34 patients (n = 24 in Part 1, n = 10 in Part 2) received treatment. The MTD of Oraxol was determined to be 270 mg daily × 5 days per week per protocol definition and this was declared the RP2D. The most common treatment-related adverse events were fatigue, neutropenia, and nausea/vomiting. Hypersensitivity-type reactions were not observed. Of the 28 patients evaluable for response, 2 (7.1%) achieved partial response and 18 (64.3%) achieved stable disease. Pharmacokinetic analysis showed rapid absorption of paclitaxel when administered orally following encequidar. Paclitaxel daily exposure was comparable following 2–5 days dose levels. Conclusion: The oral administration of encequidar with paclitaxel was safe, achieved clinically relevant paclitaxel levels, and showed evidence of anti-tumor activity. [ABSTRACT FROM AUTHOR]

Abstract Background In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that links disease entities in text to disease entries in a database, thesaurus or ontology and that could serve as a gold standard to benchmark text mining solutions. Results As part of our research work, we have taken a corpus that has been delivered in the past for the identification of associations of genes to diseases based on the UMLS Metathesaurus and we have reprocessed and re-annotated the corpus. We have gathered annotations for disease entities from two curators, analyzed their disagreement (0.51 in the kappa-statistic) and composed a single annotated corpus for public use. Thereafter, three solutions for disease named entity recognition including MetaMap have been applied to the corpus to automatically annotate it with UMLS Metathesaurus concepts. The resulting annotations have been benchmarked to compare their performance. Conclusions The annotated corpus is publicly available at ftp://ftp.ebi.ac.uk/pub/software/textmining/corpora/diseases and can serve as a benchmark to other systems. In addition, we found that dictionary look-up already provides competitive results indicating that the use of disease terminology is highly standardized throughout the terminologies and the literature. MetaMap generates precise results at the expense of insufficient recall while our statistical method obtains better recall at a lower precision rate. Even better results in terms of precision are achieved by combining at least two of the three methods leading, but this approach again lowers recall. Altogether, our analysis gives a better understanding of the complexity of disease annotations in the literature. MetaMap and the dictionary based approach are available through the Whatizit web service infrastructure (Rebholz-Schuhmann D, Arregui M, Gaudan S, Kirsch H, Jimeno A: Text processing through Web services: Calling Whatizit. Bioinformatics 2008, 24:296-298).

Monitoring heart rate variability has been commonly performed by different devices which differ in their methods (i.e., night recording vs. upon awakening measure, pulse vs. R waves, and software signal processing), Thus, the purpose of this study was to determine the level of agreement between different methods of heart rate variability monitoring, represented in two different systems (i.e., the Polar Nightly Recharge™ function present in Polar sport watches and the Polar H10 chest strap synchronized with the Kubios app). A group of 11 recreational athletes performed a concurrent training program for eight weeks and heart rate variability was daily monitored through both devices. Very large correlation (r = 0.714) and good reliability (ICC = 0.817) were obtained between devices through the entire training program. The magnitude-based inference method was also applied to determine the likelihood of the change concerning the smallest worthwhile change. From a baseline corresponding to the first two weeks of the training program, the weekly heart rate variability changes of the following six weeks were determined for each participant with each device. Despite the large correlation and good reliability between devices, there was a 60.6% of discordance in the likelihood interpretation of the change for the 66 weeks evaluated, explained by the random errors found. Thus, practitioners should be aware of these differences if their training groups use different devices or if an athlete interchanges them. The different nuances of each device can condition the heart rate variability data variation which could compromise the interpretation of the autonomic nervous system modulation. [ABSTRACT FROM AUTHOR]

Abstract Background In the context of the BioCreative competition, where training data were very sparse, we investigated two complementary tasks: 1) given a Swiss-Prot triplet, containing a protein, a GO (Gene Ontology) term and a relevant article, extraction of a short passage that justifies the GO category assignement; 2) given a Swiss-Prot pair, containing a protein and a relevant article, automatic assignement of a set of categories. Methods Sentence is the basic retrieval unit. Our classifier computes a distance between each sentence and the GO category provided with the Swiss-Prot entry. The Text Categorizer computes a distance between each GO term and the text of the article. Evaluations are reported both based on annotator judgements as established by the competition and based on mean average precision measures computed using a curated sample of Swiss-Prot. Results Our system achieved the best recall and precision combination both for passage retrieval and text categorization as evaluated by official evaluators. However, text categorization results were far below those in other data-poor text categorization experiments The top proposed term is relevant in less that 20% of cases, while categorization with other biomedical controlled vocabulary, such as the Medical Subject Headings, we achieved more than 90% precision. We also observe that the scoring methods used in our experiments, based on the retrieval status value of our engines, exhibits effective confidence estimation capabilities. Conclusion From a comparative perspective, the combination of retrieval and natural language processing methods we designed, achieved very competitive performances. Largely data-independent, our systems were no less effective that data-intensive approaches. These results suggests that the overall strategy could benefit a large class of information extraction tasks, especially when training data are missing. However, from a user perspective, results were disappointing. Further investigations are needed to design applicable end-user text mining tools for biologists.