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An amperometric biosensor using a substrate recycling principle was realized for the detection of low adrenaline concentrations (1 nM) by measurements in phosphate buffer and Ringer’s solution at pH 6.5 and pH 7.4, respectively. In proof-of-concept experiments, a Boolean logic-gate principle has been applied to develop a digital adrenaline biosensor based on an enzyme AND logic gate. The obtained results demonstrate that the developed digital biosensor is capable for a rapid qualitative determination of the presence/absence of adrenaline in a YES/NO statement. Such digital biosensor could be used in clinical diagnostics for the control of a correct insertion of a catheter in the adrenal veins during adrenal venous-sampling procedure.
Trace metal determination by dc resistance changes of microstructured thin gold film electrodes
(1999)
Training-induced increase in Achilles tendon stiffness affects tendon strain pattern during running
(2019)
Background
During the stance phase of running, the elasticity of the Achilles tendon enables the utilisation of elastic energy and allows beneficial contractile conditions for the triceps surae muscles. However, the effect of changes in tendon mechanical properties induced by chronic loading is still poorly understood. We tested the hypothesis that a training-induced increase in Achilles tendon stiffness would result in reduced tendon strain during the stance phase of running, which would reduce fascicle strains in the triceps surae muscles, particularly in the mono-articular soleus.
Methods
Eleven subjects were assigned to a training group performing isometric singleleg plantarflexion contractions three times per week for ten weeks, and another ten subjects formed a control group. Before and after the training period, Achilles tendon stiffness was estimated, and muscle-tendon mechanics were assessed during running at preferred speed using ultrasonography, kinematics and kinetics.
Results
Achilles tendon stiffness increased by 18% (P <0:01) in the training group, but the associated reduction in strain seen during isometric contractions was not statistically significant. Tendon elongation during the stance phase of running was similar after training, but tendon recoil was reduced by 30% (P <0:01), while estimated tendon force remained unchanged. Neither gastrocnemius medialis nor soleus fascicle shortening during stance was affected by training.
Discussion
These results show that a training-induced increase in Achilles tendon
stiffness altered tendon behaviour during running. Despite training-induced changes in tendon mechanical properties and recoil behaviour, the data suggest that fascicle shortening patterns were preserved for the running speed that we examined. The asymmetrical changes in tendon strain patterns supports the notion that simple inseries models do not fully explain the mechanical output of the muscle-tendon unit during a complex task like running.
In this work, the bioabsorbable materials, namely fibroin, polylactide acid (PLA), magnesium and magnesium oxide are investigated for their application as transient, resistive temperature detectors (RTD). For this purpose, a thin-film magnesium-based meander-like electrode is deposited onto a flexible, bioabsorbable substrate (fibroin or PLA) and encapsulated (passivated) by additional magnesium oxide layers on top and below the magnesium-based electrode. The morphology of different layered RTDs is analyzed by scanning electron microscopy. The sensor performance and lifetime of the RTD is characterized both under ambient atmospheric conditions between 30°C and 43°C, and wet tissue-like conditions with a constant temperature regime of 37°C. The latter triggers the degradation process of the magnesium-based layers. The 3-layers RTDs on a PLA substrate could achieve a lifetime of 8.5 h. These sensors also show the best sensor performance under ambient atmospheric conditions with a mean sensitivity of 0.48 Ω/°C ± 0.01 Ω/°C.
Transport through Redox-Active Ru-Terpyridine Complexes Integrated in Single Nanoparticle Devices
(2020)
Transition metal complexes are electrofunctional molecules due to their high conductivity and their intrinsic switching ability involving a metal-to-ligand charge transfer. Here, a method is presented to contact reliably a few to single redox-active Ru-terpyridine complexes in a CMOS compatible nanodevice and preserve their electrical functionality. Using hybrid materials from 14 nm gold nanoparticles (AuNP) and bis-{4′-[4-(mercaptophenyl)-2,2′:6′,2″-terpyridine]}-ruthenium(II) complexes a device size of 30² nm² inclusive nanoelectrodes is achieved. Moreover, this method bears the opportunity for further downscaling. The Ru-complex AuNP devices show symmetric and asymmetric current versus voltage curves with a hysteretic characteristic in two well separated conductance ranges. By theoretical approximations based on the single-channel Landauer model, the charge transport through the formed double-barrier tunnel junction is thoroughly analyzed and its sensibility to the molecule/metal contact is revealed. It can be verified that tunneling transport through the HOMO is the main transport mechanism while decoherent hopping transport is present to a minor extent.
Unitary Operator
(2009)
We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.