Efficacy of once-daily tiotropium Respimat in adults with asthma at GINA Steps 2-5

Tiotropium Respimat is an efficacious add-on to maintenance treatment in patients with symptomatic asthma. Currently, the Global Initiative for Asthma (GINA) strategy recommends tiotropium for patients at Steps 4–5. To assess the clinical benefits of tiotropium Respimat across asthma severities, GINA Steps 2–5, a post hoc analysis of five double-blind trials (12–48-weeks; patients aged 18–75 years) investigated the effect of tiotropium Respimat, 5 μg or 2.5 μg, versus placebo, on peak forced expiratory volume in 1 s (FEV1) within 3 h post-dose (FEV1(0–3h)) response, and Asthma Control Questionnaire-7 (ACQ-7) responder rate. GINA step grouping was based on patients’ background treatment regimen. Baseline characteristics of patients (N = 2926) were balanced between treatments. Tiotropium Respimat showed consistent improvements in lung function across GINA steps; placebo-corrected peak FEV1(0–3h) improvements after tiotropium Respimat 5 μg and 2.5 μg were: Step 2 (Week 8), 135 mL (95% confidence interval: 84, 187) and 155 mL (103, 206); Step 3 (Week 24), 187 mL (139, 235) and 235 mL (187, 283); Step 4 (Week 24), 111 mL (63, 159) and 181 mL (35, 326); Step 5 (Week 24; 5 μg only), 164 mL (5, 323). Asthma control improved with tiotropium Respimat versus placebo, showing statistical significance (nominal P value) with tiotropium Respimat 5 μg at Step 4 (odds ratio 1.36 [1.03, 1.78]). Safety profiles were similar between treatments. In conclusion, tiotropium Respimat add-on therapy improves lung function, and may improve asthma control, in adults across disease severities.</p

Tiotropium Respimat® add-on therapy to inhaled corticosteroids in patients with symptomatic asthma improves clinical outcomes regardless of baseline characteristics

BACKGROUND: Despite currently available therapies and detailed treatment guidelines, many patients with asthma remain symptomatic. Tiotropium delivered by the soft mist inhaler Respimat®, as add-on therapy to medium-dose inhaled corticosteroids (ICS), has been shown to improve lung function and asthma control in patients with symptomatic moderate asthma. OBJECTIVE: To determine whether the efficacy of tiotropium Respimat® in asthma differs by patients' study baseline characteristics. METHODS: Two replicate Phase III, randomized, double-blind, placebo-controlled, parallel-group studies (MezzoTinA-asthma®; NCT01172808 and NCT01172821) of once-daily tiotropium Respimat 5 μg and 2.5 μg add-on to ICS were conducted in patients with symptomatic asthma despite treatment with medium-dose ICS with or without additional controllers. Subgroup analyses of peak forced expiratory volume in 1 s (FEV1), trough FEV1, risk of severe asthma exacerbation and Asthma Control Questionnaire responder rate were performed to determine whether results were influenced by patients' baseline characteristics. RESULTS: In this analysis, 523 patients received placebo while 517 and 519 patients received the 5 μg and 2.5 μg dose of tiotropium Respimat, respectively. The magnitude of the improvements in lung function and asthma control, as well as the reduced risk of severe exacerbation with both doses of tiotropium Respimat versus placebo, was independent of a broad range of baseline characteristics. CONCLUSIONS: Once-daily tiotropium Respimat as add-on to ICS is a beneficial treatment option for patients with asthma who remain symptomatic despite at least medium-dose ICS, regardless of baseline characteristics

Quantum metrology at the limit with extremal Majorana constellations

Quantum metrology allows for a tremendous boost in the accuracy of measurement of diverse physical parameters. The estimation of a rotation constitutes a remarkable example of this quantum-enhanced precision. The recently introduced Kings of Quantumness are especially germane for this task when the rotation axis is unknown, as they have a sensitivity independent of that axis and they achieve a Heisenberg-limit scaling. Here, we report the experimental realization of these states by generating up to 21-dimensional orbital angular momentum states of single photons, and confirm their high metrological abilities

Enkephalon - technological platform to support the diagnosis of alzheimer’s disease through the analysis of resonance images using data mining techniques

Dementia can be considered as a decrease in the cognitive function of the person. The main diseases that appear are Alzheimer and vascular dementia. Today, 47 million people live with dementia around the world. The estimated total cost of dementia worldwide is US $ 818 billion, and it will become a trilliondollar disease by 2019 The vast majority of people with dementia not received a diagnosis, so they are unable to access care and treatment. In Colombia, two out of every five people presented a mental disorder at some point in their lives and 90% of these have not accessed a health service. Here it´s proposed a technological platform so early detection of Alzheimer. This tool complements and validates the diagnosis made by the health professional, based on the application of Machine Learning techniques for the analysis of a dataset, constructed from magnetic resonance imaging, neuropsychological test and the result of a radiological test. A comparative analysis of quality metrics was made, evaluating the performance of different classifier methods: Random subspace, Decorate, BFTree, LMT, Ordinal class classifier, ADTree and Random forest. This allowed us to identify the technique with the highest prediction rate, that was implemented in ENKEPHALON platform

Strong negative self regulation of Prokaryotic transcription factors increases the intrinsic noise of protein expression

Background Many prokaryotic transcription factors repress their own transcription. It is often asserted that such regulation enables a cell to homeostatically maintain protein abundance. We explore the role of negative self regulation of transcription in regulating the variability of protein abundance using a variety of stochastic modeling techniques. Results We undertake a novel analysis of a classic model for negative self regulation. We demonstrate that, with standard approximations, protein variance relative to its mean should be independent of repressor strength in a physiological range. Consequently, in that range, the coefficient of variation would increase with repressor strength. However, stochastic computer simulations demonstrate that there is a greater increase in noise associated with strong repressors than predicted by theory. The discrepancies between the mathematical analysis and computer simulations arise because with strong repressors the approximation that leads to Michaelis-Menten-like hyperbolic repression terms ceases to be valid. Because we observe that strong negative feedback increases variability and so is unlikely to be a mechanism for noise control, we suggest instead that negative feedback is evolutionarily favoured because it allows the cell to minimize mRNA usage. To test this, we used in silico evolution to demonstrate that while negative feedback can achieve only a modest improvement in protein noise reduction compared with the unregulated system, it can achieve good improvement in protein response times and very substantial improvement in reducing mRNA levels. Conclusions Strong negative self regulation of transcription may not always be a mechanism for homeostatic control of protein abundance, but instead might be evolutionarily favoured as a mechanism to limit the use of mRNA. The use of hyperbolic terms derived from quasi-steady-state approximation should also be avoided in the analysis of stochastic models with strong repressors

The ATLAS EventIndex: Full chain deployment and first operation

AbstractThe Event Index project consists in the development and deployment of a complete catalogue of events for experiments with large amounts of data, such as the ATLAS experiment at the LHC accelerator at CERN. Data to be stored in the EventIndex are produced by all production jobs that run at CERN or the GRID; for every permanent output file, a snippet of information, containing the file unique identifier and the relevant attributes for each event, is sent to the central catalogue. The estimated insertion rate during the LHC Run 2 is about 80 Hz of file records containing ∼15 kHz of event records. This contribution describes the system design, the initial performance tests of the full data collection and cataloguing chain, and the project evolution towards the full deployment and operation by the end of 2014

Data and product needs for influenza immunization programs in low- and middle-income countries: Rationale and main conclusions of the WHO preferred product characteristics for next-generation influenza vaccines.

In 2017, WHO convened a working group of global experts to develop the Preferred Product Characteristics (PPC) for Next-Generation Influenza Vaccines. PPCs are intended to encourage innovation in vaccine development. They describe WHO preferences for parameters of vaccines, in particular their indications, target groups, implementation strategies, and clinical data needed for assessment of safety and efficacy. PPCs are shaped by the global unmet public health need in a priority disease area for which WHO encourages vaccine development. These preferences reflect WHO's mandate to promote the development of vaccines with high public health impact and suitability in Low- and Middle-Income Countries (LMIC). The target audience is all entities intending to develop or to achieve widespread adoption of a specific influenza vaccine product in these settings. The working group determined that existing influenza vaccines are not well suited for LMIC use. While many developed country manufactures and research funders prioritize influenza vaccine products for use in adults and the elderly, most LMICs do not have sufficiently strong health systems to deliver vaccines to these groups. Policy makers from LMICs are expected to place higher value on vaccines indicated for prevention of severe illness, however the clinical development of influenza vaccines focuses on demonstrating prevention of any influenza illness. Many influenza vaccine products do not meet WHO standards for programmatic suitability of vaccines, which introduces challenges when vaccines are used in low-resource settings. And finally, current vaccines do not integrate well with routine immunization programs in LMICs, given age of vaccine licensure, arbitrary expiration dates timed for temperate country markets, and the need for year-round immunization in countries with prolonged influenza seasonality. While all interested parties should refer to the full PPC document for details, in this article we highlight data needs for new influenza vaccines to better demonstrate the value proposition in LMICs