Effective recruitment of participants to a phase I study using the internet and publicity releases through charities and patient organisations: analysis of the adaptive study of IL-2 dose on regulatory T cells in type 1 diabetes (DILT1D).

A barrier to the successful development of new disease treatments is the timely recruitment of participants to experimental medicine studies that are primarily designed to investigate biological mechanisms rather than evaluate clinical efficacy. The aim of this study was to analyse the performance of three recruitment sources and the effect of publicity events during the Adaptive study of IL-2 dose on regulatory T cells in type 1 diabetes (DILT1D).This work is funded by the JDRF (9-2011-253), the Wellcome Trust (091157) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140).This is the final version of the article. It first appeared from BMC via http://dx.doi.org/10.1186/s13063-015-0583-

C-reactive protein in degenerative aortic valve stenosis

Degenerative aortic valve stenosis includes a range of disorder severity from mild leaflet thickening without valve obstruction, "aortic sclerosis", to severe calcified aortic stenosis. It is a slowly progressive active process of valve modification similar to atherosclerosis for cardiovascular risk factors, lipoprotein deposition, chronic inflammation, and calcification. Systemic signs of inflammation, as wall and serum C-reactive protein, similar to those found in atherosclerosis, are present in patients with degenerative aortic valve stenosis and may be expression of a common disease, useful in monitoring of stenosis progression

ACE inhibition attenuates uremia-induced aortic valve thickening in a novel mouse model

<p>Abstract</p> <p>Background</p> <p>We examined whether impaired renal function causes thickening of the aortic valve leaflets in hyperlipidemic apoE-knockout (apoE^-/-) mice, and whether the putative effect on the aortic valves could be prevented by inhibiting the angiotensin-converting enzyme (ACE) with enalapril.</p> <p>Methods</p> <p>Thickening of the aortic valve leaflets in apoE^-/-mice was induced by producing mild or moderate chronic renal failure resulting from unilateral nephrectomy (1/2 NX, n = 18) or subtotal nephrectomy (5/6 NX, n = 22), respectively. Additionally, the 5/6 NX mice were randomized to no treatment (n = 8) or enalapril treatment (n = 13). The maximal thickness of each leaflet was measured from histological sections of the aortic roots.</p> <p>Results</p> <p>Leaflet thickness was significantly greater in the 5/6 NX mice than in the 1/2 NX mice (P = 0.030) or the unoperated mice (P = 0.003). The 5/6 NX mice treated with enalapril had significantly thinner leaflets than did the untreated 5/6 NX mice (P = 0.014).</p> <p>Conclusion</p> <p>Moderate uremia causes thickening of the aortic valves in apoE^-/-mice, which can be attenuated by ACE inhibition. The nephrectomized apoE^-/-mouse constitutes a new model for investigating the mechanisms of uremia-induced aortic valve disease, and also provides an opportunity to study its pharmacologic prevention.</p

Canalization of the evolutionary trajectory of the human influenza virus

Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure

Outcomes with ibrutinib by line of therapy and post‐ibrutinib discontinuation in patients with chronic lymphocytic leukemia: Phase 3 analysis

The efficacy of ibrutinib has been demonstrated in patients with chronic lymphocytic leukemia (CLL), including as first‐line therapy. However, outcomes after ibrutinib discontinuation have previously been limited to higher‐risk populations with relapsed/refractory (R/R) disease. The objective of this study was to evaluate outcomes of ibrutinib‐treated patients based on prior lines of therapy, including after ibrutinib discontinuation. Data were analyzed from two multicenter phase 3 studies of single‐agent ibrutinib: RESONATE (PCYC‐1112) in patients with R/R CLL and RESONATE‐2 (PCYC‐1115) in patients with treatment‐naive (TN) CLL without del(17p). This integrated analysis included 271 ibrutinib‐treated non‐del(17p) patients with CLL (136 TN and 135 R/R). Median progression‐free survival (PFS) was not reached for subgroups with 0 and 1/2 prior therapies but was 40.6 months for patients with ≥3 therapies (median follow‐up: TN, 36 months; R/R, 44 months). Median overall survival (OS) was not reached in any subgroup. Overall response rate (ORR) was 92% in TN and 92% in R/R, with depth of response increasing over time. Adverse events (AEs) and ibrutinib discontinuation due to AEs were similar between patient groups. Most patients (64%) remain on treatment. OS following discontinuation was 9.3 months in R/R patients (median follow‐up 18 months, n = 51) and was not reached in TN patients (median follow‐up 10 months, n = 30). In this integrated analysis, ibrutinib was associated with favorable PFS and OS, and high ORR regardless of prior therapies in patients with CLL. The best outcomes following ibrutinib discontinuation were for patients receiving ibrutinib in earlier lines of therapy

Lipid membranes on nanostructured silicon.

A unique composite nanoscale architecture that combines the self-organization and molecular dynamics of lipid membranes with a corrugated nanotextured silicon wafer was prepared and characterized with fluorescence microscopy and scanning probe microscopy. The goal of this project was to understand how such structures can be assembled for supported membrane research and how the interfacial interactions between the solid substrate and the soft, self-assembled material create unique physical and mechanical behavior through the confinement of phases in the membrane. The nanometer scale structure of the silicon wafer was produced through interference lithography followed by anisotropic wet etching. For the present study, a line pattern with 100 nm line widths, 200 nm depth and a pitch of 360 nm pitch was fabricated. Lipid membranes were successfully adsorbed on the structured silicon surface via membrane fusion techniques. The surface topology of the bilayer-Si structure was imaged using in situ tapping mode atomic force microscopy (AFM). The membrane was observed to drape over the silicon structure producing an undulated topology with amplitude of 40 nm that matched the 360 nm pitch of the silicon structure. Fluorescence recovery after photobleaching (FRAP) experiments found that on the microscale those same structures exhibit anisotropic lipid mobility that was coincident with the silicon substructure. The results showed that while the lipid membrane maintains much of its self-assembled structure in the composite architecture, the silicon substructure indeed influences the dynamics of the molecular motion within the membrane

Results of the randomized phase IIB ARCTIC trial of low dose Rituximab in previously untreated CLL

ARCTIC was a multi-center, randomized-controlled, open, phase IIB non-inferiority trial in previously untreated Chronic Lymphocytic Leukemia (CLL). Conventional frontline therapy in fit patients is fludarabine, cyclophosphamide and rituximab (FCR). The trial hypothesized that including mitoxantrone with low-dose rituximab (FCM-miniR) would be non-inferior to FCR. 200 patients were recruited to assess the primary endpoint of complete remission (CR) rates according to IWCLL criteria. Secondary endpoints were progression-free survival (PFS), overall survival (OS), overall response rate, minimal residual disease (MRD) negativity, safety and cost-effectiveness. The trial closed following the pre-planned interim analysis. At final analysis, CR rates were 76% FCR vs 55% FCM-miniR [adjusted odds-ratio: 0.37; 95% CI: 0.19–0.73]. MRD-negativity rates were 54% FCR vs 44% FCM-miniR. More participants experienced Serious Adverse Reactions with FCM-miniR (49%) compared to FCR (41%). There are no significant differences between the treatment groups for PFS and OS. FCM-miniR is not expected to be cost-effective over a lifetime horizon. In summary, FCM-miniR is less well tolerated than FCR with an inferior response and MRD-negativity rate and increased toxicity, and will not be taken forward into a confirmatory trial. The trial demonstrated that oral FCR yields high response rates compared to historical series with intravenous chemotherapy

Determining which automatic digital blood pressure device performs adequately: a systematic review

The aim of this study is to systematically examine the proportion of accurate readings attained by automatic digital blood pressure (BP) devices in published validation studies. We included studies of automatic digital BP devices using recognized protocols. We summarized the data as mean and s.d. of differences between measured and observed BP, and proportion of measurements within 5 mm Hg. We included 79 articles (10 783 participants) reporting 113 studies from 22 different countries. Overall, 25/31 (81%), 37/41 (90%) and 34/35 (97%) devices passed the relevant protocols [BHS, AAMI and ESH international protocol (ESH-IP), respectively]. For devices that passed the BHS protocol, the proportion of measured values within 5 mm Hg of the observed value ranged from 60 to 86% (AAMI protocol 47–94% and ESH-IP 54–89%). The results for the same device varied significantly when a different protocol was used (Omron HEM-907 80% of readings were within 5 mm Hg using the AAMI protocol compared with 62% with the ESH-IP). Even devices with a mean difference of zero show high variation: a device with 74% of BP measurements within 5 mm Hg would require six further BP measurements to reduce variation to 95% of readings within 5 mm Hg. Current protocols for validating BP monitors give no guarantee of accuracy in clinical practice. Devices may pass even the most rigorous protocol with as few as 60% of readings within 5 mm Hg of the observed value. Multiple readings are essential to provide clinicians and patients with accurate information on which to base diagnostic and treatment decisions

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

<p>Abstract</p> <p>Background</p> <p>Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community.</p> <p>Results</p> <p>This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment.</p> <p>Conclusions</p> <p>AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements.</p

Lessons from SARS: A retrospective study of outpatient care during an infectious disease outbreak

<p>Abstract</p> <p>Background</p> <p>During severe acute respiratory syndrome (SARS) outbreak in Toronto, outpatient clinics at SickKids Hospital were closed to prevent further disease transmission. In response, a decision was made by the neonatal neuro-developmental follow up (NNFU) clinic staff to select patients with scheduled appointments to have a mail/telephone assessment using Ages and Stages Questionnaire (ASQ) or to postpone/skip their visit. The objective of this study was to compare the developmental assessment and its outcome in two groups of NNFU clinic patients, SARS versus non-SARS, over three standard clinic appointments.</p> <p>Methods</p> <p>We compared the diagnostic accuracy (identification of developmental delay), and patient management (referral for therapy or communication of a new diagnosis) of the strategies used during SARS, April/May 2003, to the standard assessment methods used for patients seen in April/May 2005 (non-SARS). In all cases data were obtained for 3 patient visits: before, during and after these 2 months and were compared using descriptive statistics.</p> <p>Results</p> <p>There were 95 patients in the SARS group and 99 non-SARS patients. The gestational age, sex, entry diagnosis and age at the clinic visit was not different between the groups. The NNFU clinic staff mailed ASQ to 27 families during SARS, 17 (63%) were returned, and 8 of the 17 were then contacted by telephone. Criteria used to identify infants at risk selected for either mailed ASQ or phone interviews were not clearly defined in the patients' charts. There was a significant under identification of developmental delay during SARS (18% versus 45%). Of those who responded to the mailed questionnaire, referrals for therapy rates were similar to non-SARS group. The lost to follow up rate was 24% for the SARS group compared with 7% for non-SARS. There was no difference in the overall rate of developmental delay in the two groups as identified at the 'after' visit.</p> <p>Conclusions</p> <p>Poor advanced planning led to a haphazard assessment of patients during this infectious disease outbreak. Future pandemic plans should consider planning for outpatient care as well as in hospital management of patients.</p