Concepts for a geostationary-like polar missions

An evidence-led scientific case for development of a space-based polar remote sensing platform at geostationary-like (GEO-like) altitudes is developed through methods including a data user survey. Whilst a GEO platform provides a nearstatic perspective, multiple platforms are required to provide circumferential coverage. Systems for achieving GEO-like polar observation likewise require multiple platforms however the perspective is non-stationery. A key choice is between designs that provide complete polar view from a single platform at any given instant, and designs where this is obtained by compositing partial views from multiple sensors. Users foresee an increased challenge in extracting geophysical information from composite images and consider the use of non-composited images advantageous. Users also find the placement of apogee over the pole to be preferable to the alternative scenarios. Thus, a clear majority of data users find the “Taranis” orbit concept to be better than a critical inclination orbit, due to the improved perspective offered. The geophysical products that would benefit from a GEO-like polar platform are mainly estimated from radiances in the visible/near infrared and thermal parts of the electromagnetic spectrum, which is consistent with currently proven technologies from GEO. Based on the survey results, needs analysis, and current technology proven from GEO, scientific and observation requirements are developed along with two instrument concepts with eight and four channels, based on Flexible Combined Imager heritage. It is found that an operational system could, mostly likely, be deployed from an Ariane 5 ES to a 16-hour orbit, while a proof-of-concept system could be deployed from a Soyuz launch to the same orbit.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

A label-free electrochemical affisensor for cancer marker detection: the case of HER2

In this paper, we report the development of a sensitive label-free impedimetric biosensor based on the use of affibody as bioreceptor and gold nanostructured screen-printed graphite as a sensor platform for the detection of human epidermal growth factor receptor 2 (HER2). The affisensor is realized by immobilizing a terminal cysteine-modified affibody on gold nanoparticles. The sensor was characterized by electrochemical techniques and scanning electron microscopy (SEM). Furthermore, surface plasmon resonance (SPR) technology was also applied to explore the potential of affibodies as small-molecule discriminating tools. Using optimized experimental conditions, a single-use affisensor showed a good analytical performance for HER2 detection from 0 to 40μg/L. The estimated limit of detection was 6.0μg/L. Finally, the realized affisensor was applied to human serum samples.

Effects of nitric oxide synthesis inhibitor or fluoxetine treatment on depression-like state and cardiovascular changes induced by chronic variable stress in rats

Comorbidity between mood disorders and cardiovascular disease has been described extensively. However, available antidepressants can have cardiovascular side effects. Treatment with selective inhibitors of neuronal nitric oxide synthase (nNOS) induces antidepressant effects, but whether the antidepressant-like effects of these drugs are followed by cardiovascular changes has not been previously investigated. Here, we tested in male rats exposed to chronic variable stress (CVS) the hypothesis that nNOS blockers are advantageous compared with conventional antidepressants in terms of cardiovascular side effects. We compared the effects of chronic treatment with the preferential nNOS inhibitor 7-nitroindazole (7-NI) with those evoked by the conventional antidepressant fluoxetine on alterations that are considered as markers of depression (immobility in the forced swimming test, FST, decreased body weight gain and increased plasma corticosterone concentration) and cardiovascular changes caused by CVS. Rats were exposed to a 14-day CVS protocol, while being concurrently treated daily with either 7-NI (30 mg/kg) or fluoxetine (10 mg/kg). Fluoxetine and 7-NI prevented the increase in immobility in the FST induced by CVS and reduced plasma corticosterone concentration in stressed rats. Both these treatments also prevented the CVS-evoked reduction of the depressor response to vasodilator agents and baroreflex changes. Fluoxetine and 7-NI-induced cardiovascular changes independent of stress exposure, including cardiac autonomic imbalance, increased intrinsic heart rate and vascular sympathetic modulation, a reduction of the pressor response to vasoconstrictor agents, and impairment of baroreflex activity. Altogether, these findings provide evidence that fluoxetine and 7-NI have similar effects on the depression-like state induced by CVS and on cardiovascular function.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Reinforcement learning in dendritic structures

The discovery of binary dendritic events such as local NMDA spikes in dendritic subbranches led to the suggestion that dendritic trees could be computationally equivalent to a 2-layer network of point neurons, with a single output unit represented by the soma, and input units represented by the dendritic branches. Although this interpretation endows a neuron with a high computational power, it is functionally not clear why nature would have preferred the dendritic solution with a single but complex neuron, as opposed to the network solution with many but simple units. We show that the dendritic solution has a distinguished advantage over the network solution when considering different learning tasks. Its key property is that the dendritic branches receive an immediate feedback from the somatic output spike, while in the corresponding network architecture the feedback would require additional backpropagating connections to the input units. Assuming a reinforcement learning scenario we formally derive a learning rule for the synaptic contacts on the individual dendritic trees which depends on the presynaptic activity, the local NMDA spikes, the somatic action potential, and a delayed reinforcement signal. We test the model for two scenarios: the learning of binary classifications and of precise spike timings. We show that the immediate feedback represented by the backpropagating action potential supplies the individual dendritic branches with enough information to efficiently adapt their synapses and to speed up the learning process.

Large deletions in the CFTR gene: clinics and genetics in Swiss patients with CF

Cystic fibrosis (CF) is the most common life-shortening autosomal recessive disorder in Caucasians, and is associated with at least one mutation on each CF transmembrane conductance regulator (CFTR) allele. Some patients, however, with only one identifiable point mutation carry on the other allele, a large deletion that is not detected by conventional screening methods. The overall frequency of large deletions in patients with CF is estimated to be 1-3%. Using the CFTR Multiplex Ligation dependent Probe Amplification Kit (MRC-Holland, Amsterdam, Netherlands) that allows the exact detection of copy numbers from all 27 exons in the CFTR gene, we screened 50 patients with only one identified mutation for large deletions in the CFTR gene. Each detected deletion was confirmed using our real-time polymerase chain reaction (PCR) assay and deletion-specific PCR reactions using junction fragment primers. We detected large deletions in eight patients (16%). These eight CF alleles belong to four different deletion types (CFTRindel2, CFTRdele14b-17b, CFTRdele17a-17b and CFTRdele 2-9) whereof the last is novel. Comparing detailed clinical data of all these patients with CF and the molecular genetic findings, we were able to elaborate criteria for deletion screenings and possible genotype-phenotype associations. In conclusion, we agree with other authors that deletion screenings should be implemented in routine genetic diagnostics of CF.