Prototype of the front-end circuit for the GOSSIP (Gas On Slimmed Silicon Pixel) chip in the 0.13 μm CMOS technology

The new GOSSIP detector, capable to detect single electrons in gas, has certain advantages with respect silicon (pixel) detectors. It does not require a Si sensor; it has a very low detector parasitic capacitance and a zero bias current at the pixel input. These are attractive features to design a compact, low-noise and low-power integrated input circuit. A prototype of the integrated circuit has been developed in 0.13 μm CMOS technology. It includes a few channels equipped with preamplifier, discriminator and the digital circuit to study the feasibility of the TDC-perpixel concept. The design demonstrates very low input referred noise (60e- RMS) in combination with a fast peaking time (40 ns) and an analog power dissipation as low as 2 μW per channel. Switching activity on the clock bus (up to 100 MHz) in the close vicinity of the pixel input pads does not cause noticeable extra noise

Expected survival with and without second-line palliative chemotherapy: who wants to know?

Background According to surveys, many patients with advancedcancer wish to receive survival information.Objective This study invest igated information preferences by offer-ing patients a decision aid (DA) with infor mation on expected sur-vival for two treatment options: supportive care with or withoutsecond-line palliative chemotherapy. Predicto rs of accepting sur-vival information were explored.Design Eligible patients in this multicentre prospective study wereoffered secon d-line chemotherapy for advanced breast or colorectalcancer. A nurse presented a DA on second-line treatment andasked patients whether they desired information on (i) adverseevents, (ii) tumour response and (iii) survival. Data on 50 clinicaland psychosocial patient characteristics were collected from inclu-sion forms and patient questionnaires.Results Seventy-seven patients received a DA; median age62 years (range 32–80), 61% female, 77% colorectal cancer. Fifty-seven patients (74%; 95% CI 64–84) desired survival information.Four psychosocial characteristics (e.g . deliberative decision style)independently predicted information desire. However, the use ofthese characteristics to predict information desire hardly outper-formed a simple prediction rule.Conclusions Many patients desired information on expected sur-vival when deciding about second-line treatment. However, ourexploratory analysis indicated that patients desiring this informa-tion could not be identified based on their clinical or psychosocialcharacteristics. These findings can help encourage candid discus-sions about expected survival. Health professionals should be care-ful not to make implicit assumptions of information desire based on patient characteristics, but to explicitly ask patients if survivalinformation is desired, and act accordingly

Primaire biliaire cirrhose met sclerodermie en hypothyreoidie

Contains fulltext : 4297.pdf (publisher's version ) (Open Access

Model reduction in mathematical pharmacology: integration, reduction and linking of PBPK and systems biology models

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale