A retrospective review of oral low-dose sirolimus (rapamycin) for the treatment of active uveitis

Purpose: The purpose of this study is to elicit the role of oral low-dose sirolimus as a corticosteriod-sparing agent for active uveitis. Methods: A retrospective, interventional case series was performed by reviewing the clinical records of all patients treated with oral, low-dose sirolimus (1-4 mg daily) for severe uveitis. Data reviewed included symptomatic improvement, Snellen best-corrected visual acuity, corticosteroid requirement, sirolimus levels, intraocular inflammation, spectral-domain optical coherence tomography, and fluorescein angiogram. Primary outcome measures were determined by the ability to decrease the intraocular inflammation, corticosteroid requirement, and frequency of flares. Results: Eight patients with varied diagnoses were treated with oral low-dose sirolimus for severe, chronic uveitis between 2008 and 2010. In four of the eight patients, there was an improvement of all primary outcome measures. While sirolimus monotherapy was successful in only one patient, a sirolimus/methotrexate combination was successful in three patients. Although there was a good initial response in three patients, treatment was a failure after serious side effects forced the cessation of sirolimus therapy. One patient was lost to follow-up. Conclusion: Sirolimus may have a limited role in severe uveitis as an adjunct corticosteroid-sparing agent in combination with more standard immunosuppressive agents. Oral low-dose sirolimus appeared to be better tolerated than higher doses, but there were a significant number of adverse events, requiring therapy to be stopped. © 2010 The Author(s)

Predictive feedback control and Fitts' law

Fitts’ law is a well established empirical formula, known for encapsulating the “speed-accuracy trade-off”. For discrete, manual movements from a starting location to a target, Fitts’ law relates movement duration to the distance moved and target size. The widespread empirical success of the formula is suggestive of underlying principles of human movement control. There have been previous attempts to relate Fitts’ law to engineering-type control hypotheses and it has been shown that the law is exactly consistent with the closed-loop step-response of a time-delayed, first-order system. Assuming only the operation of closed-loop feedback, either continuous or intermittent, this paper asks whether such feedback should be predictive or not predictive to be consistent with Fitts law. Since Fitts’ law is equivalent to a time delay separated from a first-order system, known control theory implies that the controller must be predictive. A predictive controller moves the time-delay outside the feedback loop such that the closed-loop response can be separated into a time delay and rational function whereas a non- predictive controller retains a state delay within feedback loop which is not consistent with Fitts’ law. Using sufficient parameters, a high-order non-predictive controller could approximately reproduce Fitts’ law. However, such high-order, “non-parametric” controllers are essentially empirical in nature, without physical meaning, and therefore are conceptually inferior to the predictive controller. It is a new insight that using closed-loop feedback, prediction is required to physically explain Fitts’ law. The implication is that prediction is an inherent part of the “speed-accuracy trade-off”

The importance of RT-qPCR primer design for the detection of siRNA-mediated mRNA silencing

<p>Abstract</p> <p>Background</p> <p>The use of RNAi to analyse gene function <it>in vitro </it>is now widely applied in biological research. However, several difficulties are associated with its use <it>in vivo</it>, mainly relating to inefficient delivery and non-specific effects of short RNA duplexes in animal models. The latter can lead to false positive results when real-time RT-qPCR alone is used to measure target mRNA knockdown.</p> <p>Findings</p> <p>We observed that detection of an apparent siRNA-mediated knockdown <it>in vivo </it>was dependent on the primers used for real-time RT-qPCR measurement of the target mRNA. Two siRNAs specific for <it>RRM1 </it>with equivalent activity <it>in vitro </it>were administered to A549 xenografts via intratumoural injection. In each case, apparent knockdown of <it>RRM1 </it>mRNA was observed only when the primer pair used in RT-qPCR flanked the siRNA cleavage site. This false-positive result was found to result from co-purified siRNA interfering with both reverse transcription and qPCR.</p> <p>Conclusions</p> <p>Our data suggest that using primers flanking the siRNA-mediated cleavage site in RT-qPCR-based measurements of mRNA knockdown <it>in vivo </it>can lead to false positive results. This is particularly relevant where high concentrations of siRNA are introduced, particularly via intratumoural injection, as the siRNA may be co-purified with the RNA and interfere with downstream enzymatic steps. Based on these results, using primers flanking the siRNA target site should be avoided when measuring knockdown of target mRNA by real-time RT-qPCR.</p

Disease surveillance using a hidden Markov model

<p>Abstract</p> <p>Background</p> <p>Routine surveillance of disease notification data can enable the early detection of localised disease outbreaks. Although hidden Markov models (HMMs) have been recognised as an appropriate method to model disease surveillance data, they have been rarely applied in public health practice. We aimed to develop and evaluate a simple flexible HMM for disease surveillance which is suitable for use with sparse small area count data and requires little baseline data.</p> <p>Methods</p> <p>A Bayesian HMM was designed to monitor routinely collected notifiable disease data that are aggregated by residential postcode. Semi-synthetic data were used to evaluate the algorithm and compare outbreak detection performance with the established Early Aberration Reporting System (EARS) algorithms and a negative binomial cusum.</p> <p>Results</p> <p>Algorithm performance varied according to the desired false alarm rate for surveillance. At false alarm rates around 0.05, the cusum-based algorithms provided the best overall outbreak detection performance, having similar sensitivity to the HMMs and a shorter average time to detection. At false alarm rates around 0.01, the HMM algorithms provided the best overall outbreak detection performance, having higher sensitivity than the cusum-based Methods and a generally shorter time to detection for larger outbreaks. Overall, the 14-day HMM had a significantly greater area under the receiver operator characteristic curve than the EARS C3 and 7-day negative binomial cusum algorithms.</p> <p>Conclusion</p> <p>Our findings suggest that the HMM provides an effective method for the surveillance of sparse small area notifiable disease data at low false alarm rates. Further investigations are required to evaluation algorithm performance across other diseases and surveillance contexts.</p

Understanding and assessing the impact of treatment in diabetes: the Treatment-Related Impact Measures for Diabetes and Devices (TRIM-Diabetes and TRIM-Diabetes Device)

<p>Abstract</p> <p>Purpose</p> <p>Diabetes is a debilitating illness requiring lifelong management. Treatments can be varied in terms of mode of administration as well as type of agent. Unfortunately, most patient reported outcome measures currently available to assess the impact of treatment are specific to diabetes type, treatment modality or delivery systems and are designed to be either a HRQoL or treatment satisfaction measure. To address these gaps, the Treatment Related Impact Measure-Diabetes and Device measures were developed. This paper presents the item development and validation of the TRIM Diabetes/Device.</p> <p>Methods</p> <p>Patient interviews were conducted to collect the patient perspective and ensure high content validity. Interviews were hand coded and qualitatively analyzed to identify common themes. A conceptual model of the impact of diabetes medication was developed and preliminary items for the TRIM-Diabetes/Device were generated and cognitively debriefed. Validation data was collected via an on-line survey and analyzed according to an a priori statistical analysis plan to validate the overall score as well as each domain. Item level criteria were used to reduce the preliminary item pool. Next, factor analysis to identify structural domains was performed. Reliability and validity testing was then performed.</p> <p>Results</p> <p>One hundred and five patients were interviewed in focus groups, individual interviews and for cognitive debriefing. Five hundred seven patients participated in the validation study. Factor analysis identified seven domains: Treatment Burden, Daily Life; Diabetes Management; Psychological Health; Compliance and Device Function and Bother. Internal consistency reliability coefficients of the TRIM-Diabetes/Device ranged from 0.80 and 0.94. Test-retest reliability of the TRIM-Diabetes/Device ranged from 0.71 to 0.89. All convergent and known groups validity hypotheses were met for the TRIM-Diabetes/Device total scores and sub-scales.</p> <p>Conclusion</p> <p>Validation is an ongoing and iterative process. These findings are the first step in that process and have shown that both the TRIM-Diabetes and the TRIM-Diabetes Device have acceptable psychometric properties. Future research is needed to continue the validation process and examine responsiveness and the validity of the TRIM-Diabetes/Device in a clinical trial population.</p

Proposal of a framework for evaluating military surveillance systems for early detection of outbreaks on duty areas

<p>Abstract</p> <p>Background</p> <p>In recent years a wide variety of epidemiological surveillance systems have been developed to provide early identification of outbreaks of infectious disease. Each system has had its own strengths and weaknesses. In 2002 a Working Group of the Centers for Disease Control and Prevention (CDC) produced a framework for evaluation, which proved suitable for many public health surveillance systems. However this did not easily adapt to the military setting, where by necessity a variety of different parameters are assessed, different constraints placed on the systems, and different objectives required. This paper describes a proposed framework for evaluation of military syndromic surveillance systems designed to detect outbreaks of disease on operational deployments.</p> <p>Methods</p> <p>The new framework described in this paper was developed from the cumulative experience of British and French military syndromic surveillance systems. The methods included a general assessment framework (CDC), followed by more specific methods of conducting evaluation. These included Knowledge/Attitude/Practice surveys (KAP surveys), technical audits, ergonomic studies, simulations and multi-national exercises. A variety of military constraints required integration into the evaluation. Examples of these include the variability of geographical conditions in the field, deployment to areas without prior knowledge of naturally-occurring disease patterns, the differences in field sanitation between locations and over the length of deployment, the mobility of military forces, turnover of personnel, continuity of surveillance across different locations, integration with surveillance systems from other nations working alongside each other, compatibility with non-medical information systems, and security.</p> <p>Results</p> <p>A framework for evaluation has been developed that can be used for military surveillance systems in a staged manner consisting of initial, intermediate and final evaluations. For each stage of the process parameters for assessment have been defined and methods identified.</p> <p>Conclusion</p> <p>The combined experiences of French and British syndromic surveillance systems developed for use in deployed military forces has allowed the development of a specific evaluation framework. The tool is suitable for use by all nations who wish to evaluate syndromic surveillance in their own military forces. It could also be useful for civilian mobile systems or for national security surveillance systems.</p

Slower Visuomotor Corrections with Unchanged Latency are Consistent with Optimal Adaptation to Increased Endogenous Noise in the Elderly

We analyzed age-related changes in motor response in a visuomotor compensatory tracking task. Subjects used a manipulandum to attempt to keep a displayed cursor at the center of a screen despite random perturbations to its location. Cross-correlation analysis of the perturbation and the subject response showed no age-related increase in latency until the onset of response to the perturbation, but substantial slowing of the response itself. Results are consistent with age-related deterioration in the ratio of signal to noise in visuomotor response. The task is such that it is tractable to use Bayesian and quadratic optimality assumptions to construct a model for behavior. This model assumes that behavior resembles an optimal controller subject to noise, and parametrizes response in terms of latency, willingness to expend effort, noise intensity, and noise bandwidth. The model is consistent with the data for all young (n = 12, age 20–30) and most elderly (n = 12, age 65–92) subjects. The model reproduces the latency result from the cross-correlation method. When presented with increased noise, the computational model reproduces the experimentally observed age-related slowing and the observed lack of increased latency. The model provides a precise way to quantitatively formulate the long-standing hypothesis that age-related slowing is an adaptation to increased noise

Liquid metal nanodroplet dynamics inside nanocontainers

Here we report direct observations of spatial movements of nanodroplets of Pb metal trapped inside sealed carbon nanocontainers. We find drastic changes in the mobility of the liquid droplets as the particle size increases from a few to a few ten nanometers. In open containers the droplet becomes immobile and readily evaporates to the vacuum environment. The particle mobility strongly depends on confinement, particle size, and wetting on the enclosed surface. The collisions between droplets increase mobility but the tendency is reversed if collisions lead to droplet coalescence. The dynamics of confined nanodroplets could provide new insights into the activity of nanostructures in spatially constrained geometries

Static and dynamic ionization levels of transition metal-doped zinc chalcogenides

Transition metal (TM) impurities in semiconductors have a considerable effect on the electronic properties and on the lattice vibrations. The unfilled d shell permits the impurity atoms to exist in a variety of charge states. In this work, the static donor and acceptor ionization energies of ZnX:M, with X = S, Se, Te and M:Sc, Ti, V, Fe, Co, Ni are obtained from first principles total energy calculations and compared with experimental results in the literature where they exist. From these results, many of the TM-doped zinc chalogenides have an amphoteric behavior. To analyze the rule of the deep gap levels in both the radiative and non-radiative processes, the dynamic ionization energies are obtained as a function of the inward and outward M–X displacements. In many cases, the changes in the mass and the force constants resulting from the substitution of an impurity center for a lattice atom are small. When the charge or the environment of the impurity changes, the electron population tend to remain compensated. As consequence, the changes in the lattice vibrational modes are small