Pilot study of an interactive voice response system to improve medication refill compliance

<p>Abstract</p> <p>Background</p> <p>Sub-optimal adherence to prescribed medications is well documented. Barriers to medication adherence include medication side effects, cost, and forgetting to take or refill medications. Interactive Voice Response (IVR) systems show promise as a tool for reminding individuals to take or refill medications. This pilot study evaluated the feasibility and acceptability of using an IVR system for prescription refill and daily medication reminders. We tested two novel features: personalized, medication-specific reminder messages and communication via voice recognition.</p> <p>Methods</p> <p>Patients enrolled in a study of electronic prescribing and medication management in Quebec, Canada who were taking chronic disease-related drugs were eligible to participate. Consenting patients had their demographic, telephone, and medication information transferred to an IVR system, which telephoned patients to remind them to take mediations and/or refill their prescriptions. Facilitators and barriers of the IVR system use and acceptability of the IVR system were assessed through a structured survey and open-ended questions administered by telephone interview.</p> <p>Results</p> <p>Of the 528 eligible patients who were contacted, 237 refused and 291 consented; 99 participants had started the pilot study when it was terminated because of physician and participant complaints. Thirty-eight participants completed the follow-up interview. The majority found the IVR system's voice acceptable, and did not have problems setting up the time and location of reminder calls. However, many participants experienced technical problems when called for reminders, such as incorrect time of calls and voice recognition difficulties. In addition, most participants had already refilled their prescriptions when they received the reminder calls, reporting that they did not have difficulties remembering to refill prescriptions on their own. Also, participants were not receptive to speaking to an automated voice system.</p> <p>Conclusion</p> <p>IVR systems designed to improve medication compliance must address key technical and performance issues and target those individuals with reported memory difficulties or complex medication regimens in order to improve the utility of the system. Future research should also identify characteristics of medication users who are more likely to be receptive to IVR technology.</p

Regular symmetry patterns

Symmetry reduction is a well-known approach for alleviating the state explosion problem in model checking. Automatically identifying symmetries in concurrent systems, however, is computationally expensive. We propose a symbolic framework for capturing symmetry patterns in parameterised systems (i.e. an infinite family of finite-state systems): two regular word transducers to represent, respectively, parameterised systems and symmetry patterns. The framework subsumes various types of "symmetry relations" ranging from weaker notions (e.g. simulation preorders) to the strongest notion (i.e. isomorphisms). Our framework enjoys two algorithmic properties: (1) symmetry verification: given a transducer, we can automatically check whether it is a symmetry pattern of a given system, and (2) symmetry synthesis: we can automatically generate a symmetry pattern for a given system in the form of a transducer. Furthermore, our symbolic language allows additional constraints that the symmetry patterns need to satisfy to be easily incorporated in the verification/synthesis. We show how these properties can help identify symmetry patterns in examples like dining philosopher protocols, self-stabilising protocols, and prioritised resource-allocator protocol. In some cases (e.g. Gries's coffee can problem), our technique automatically synthesises a safety-preserving finite approximant, which can then be verified for safety solely using a finite-state model checker.UPMAR

Quantitative autoradiographic evaluation of the influence of protein dose on monoclonal antibody distribution in human ovarian adenocarcinoma xenografts

We studied the effect of monoclonal antibody protein dose on the uniformity of radioiodinated antibody distribution within tumor masses using quantitative autoradiography. Groups ( n = 11–13/group) of athymic nude mice with subcutaneous HTB77 human ovarian carcinoma xenografts were injected intraperitoneally with an 125 I-labeled anticarcinoma-associated antigen murine monoclonal antibody, 5G6.4, using a high or a low protein dose (500 µg or 5 µg). At 6 days post-injection the macroscopic and microscopic intratumoral biodistribution of radiolabeled antibody was determined. The degree of heterogeneity of the labeled antibody distribution within each tumor was quantified and expressed as the coefficient of variation (CV) of the activity levels in serial histological sections. Tumors from mice given the 500-µg protein doses had substantially lower CV values, 0.327±0.027, than did tumors from animals given 5-µg protein doses, 0.458±0.041, ( P = 0.0078), indicating that the higher protein dose resulted in more homogeneous distribution of radioactivity in tumors than did the lower dose. While the percentage of the injected dose reaching the tumor was comparable between groups, injecting the higher dose of protein resulted in significantly lower tumor to non-tumor uptake ratios than those obtained for the lower protein dose. These data indicate, in this system, that to achieve more uniform intratumoral antibody (and radiation for radioimmunotherapy) delivery, a relatively high protein dose must be administered. However, to obtain this increased uniformity, a substantial drop in tumor/background uptake ratios was seen. Quantitative autoradiographic evaluation of human tumor xenografts is a useful method to assess the intratumoral distribution of antibodies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46859/1/262_2005_Article_BF01789014.pd

Characteristics of outdoor falls among older people: A qualitative study

Background Falls are a major threat to older people’s health and wellbeing. Approximately half of falls occur in outdoor environments but little is known about the circumstances in which they occur. We conducted a qualitative study to explore older people’s experiences of outdoor falls to develop understanding of how they may be prevented. Methods We conducted nine focus groups across the UK (England, Wales, and Scotland). Our sample was from urban and rural settings and different environmental landscapes. Participants were aged 65+ and had at least one outdoor fall in the past year. We analysed the data using framework and content analyses. Results Forty-four adults aged 65 – 92 took part and reported their experience of 88 outdoor falls. Outdoor falls occurred in a variety of contexts, though reports suggested the following scenarios may have been more frequent: when crossing a road, in a familiar area, when bystanders were around, and with an unreported or unknown attribution. Most frequently, falls resulted in either minor or moderate injury, feeling embarrassed at the time of the fall, and anxiety about falling again. Ten falls resulted in fracture, but no strong pattern emerged in regard to the contexts of these falls. Anxiety about falling again appeared more prevalent among those that fell in urban settings and who made more visits into their neighbourhood in a typical week. Conclusions This exploratory study has highlighted several aspects of the outdoor environment that may represent risk factors for outdoor falls and associated fear of falling. Health professionals are recommended to consider outdoor environments as well as the home setting when working to prevent falls and increase mobility among older people

Current measures of metabolic heterogeneity within cervical cancer do not predict disease outcome

<p>Abstract</p> <p>Background</p> <p>A previous study evaluated the intra-tumoral heterogeneity observed in the uptake of F-18 fluorodeoxyglucose (FDG) in pre-treatment positron emission tomography (PET) scans of cancers of the uterine cervix as an indicator of disease outcome. This was done via a novel statistic which ostensibly measured the spatial variations in intra-tumoral metabolic activity. In this work, we argue that statistic is intrinsically <it>non</it>-spatial, and that the apparent delineation between unsuccessfully- and successfully-treated patient groups via that statistic is spurious.</p> <p>Methods</p> <p>We first offer a straightforward mathematical demonstration of our argument. Next, we recapitulate an assiduous re-analysis of the originally published data which was derived from FDG-PET imagery. Finally, we present the results of a principal component analysis of FDG-PET images similar to those previously analyzed.</p> <p>Results</p> <p>We find that the previously published measure of intra-tumoral heterogeneity is intrinsically non-spatial, and actually is only a surrogate for tumor volume. We also find that an optimized linear combination of more canonical heterogeneity quantifiers does not predict disease outcome.</p> <p>Conclusions</p> <p>Current measures of intra-tumoral metabolic activity are not predictive of disease outcome as has been claimed previously. The implications of this finding are: clinical categorization of patients based upon these statistics is invalid; more sophisticated, and perhaps innately-geometric, quantifications of metabolic activity are required for predicting disease outcome.</p

Crystal Structure Analysis Reveals Functional Flexibility in the Selenocysteine-Specific tRNA from Mouse

Selenocysteine tRNAs (tRNA(Sec)) exhibit a number of unique identity elements that are recognized specifically by proteins of the selenocysteine biosynthetic pathways and decoding machineries. Presently, these identity elements and the mechanisms by which they are interpreted by tRNA(Sec)-interacting factors are incompletely understood.We applied rational mutagenesis to obtain well diffracting crystals of murine tRNA(Sec). tRNA(Sec) lacking the single-stranded 3'-acceptor end ((ΔGCCA)RNA(Sec)) yielded a crystal structure at 2.0 Å resolution. The global structure of (ΔGCCA)RNA(Sec) resembles the structure of human tRNA(Sec) determined at 3.1 Å resolution. Structural comparisons revealed flexible regions in tRNA(Sec) used for induced fit binding to selenophosphate synthetase. Water molecules located in the present structure were involved in the stabilization of two alternative conformations of the anticodon stem-loop. Modeling of a 2'-O-methylated ribose at position U34 of the anticodon loop as found in a sub-population of tRNA(Sec)in vivo showed how this modification favors an anticodon loop conformation that is functional during decoding on the ribosome. Soaking of crystals in Mn(2+)-containing buffer revealed eight potential divalent metal ion binding sites but the located metal ions did not significantly stabilize specific structural features of tRNA(Sec).We provide the most highly resolved structure of a tRNA(Sec) molecule to date and assessed the influence of water molecules and metal ions on the molecule's conformation and dynamics. Our results suggest how conformational changes of tRNA(Sec) support its interaction with proteins

Barcoded DNA-Tag Reporters for Multiplex Cis-Regulatory Analysis

Cis-regulatory DNA sequences causally mediate patterns of gene expression, but efficient experimental analysis of these control systems has remained challenging. Here we develop a new version of “barcoded" DNA-tag reporters, “Nanotags" that permit simultaneous quantitative analysis of up to 130 distinct cis-regulatory modules (CRMs). The activities of these reporters are measured in single experiments by the NanoString RNA counting method and other quantitative procedures. We demonstrate the efficiency of the Nanotag method by simultaneously measuring hourly temporal activities of 126 CRMs from 46 genes in the developing sea urchin embryo, otherwise a virtually impossible task. Nanotags are also used in gene perturbation experiments to reveal cis-regulatory responses of many CRMs at once. Nanotag methodology can be applied to many research areas, ranging from gene regulatory networks to functional and evolutionary genomics