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Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan–Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time.
Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.
Optimization of the immobilization of bacterial spores on glass substrates with organosilanes
(2016)
Spores can be immobilized on biosensors to function as sensitive recognition elements. However, the immobilization can affect the sensitivity and reproducibility of the sensor signal. In this work, three different immobilization strategies with organosilanes were optimized and characterized to immobilize Bacillus atrophaeus spores on glass substrates. Five different silanization parameters were investigated: nature of the solvent, concentration of the silane, silanization time, curing process, and silanization temperature. The resulting silane layers were resistant to a buffer solution (e.g., Ringer solution) with a polysorbate (e.g., Tween®80) and sonication.
In this study, we show that synthetic sapphire (Al₂O₃), an established implant material, can also serve as a platform material for biosensors comparable to nanocrystalline diamond. Sapphire chips, beads, and powder were first modified with (3-aminopropyl) triethoxysilane (APTES), followed by succinic anhydride (SA), and finally single-stranded probe DNA was EDC coupled to the functionalized layer. The presence of the APTES-SA layer on sapphire powders was confirmed by thermogravimetric analyis and Fourier-transform infrared spectroscopy. Using planar sapphire chips as substrates and X-ray photoelectron spectroscopy (XPS) as surface-sensitive tool, the sequence of individual layers was analyzed with respect to their chemical state, enabling the quantification of areal densities of the involved molecular units. Fluorescence microscopy was used to demonstrate the hybridization of fluorescently tagged target DNA to the probe DNA, including denaturation- and re-hybridization experiments. Due to its high thermal conductivity, synthetic sapphire is especially suitable as a chip material for the heat-transfer method, which was employed to distinguish complementary- and non-complementary DNA duplexes containing single-nucleotide polymorphisms. These results indicate that it is possible to detect mutations electronically with a chemically resilient and electrically insulating chip material.
Bonding of polymer-based microfluidics to polymer substrates still poses a challenge for Lab-On-a-Chip applications. Especially, when sensing elements are incorporated, patterned deposition of adhesives with curing at ambient conditions is required. Here, we demonstrate a fabrication method for fully printed microfluidic systems with sensing elements using inkjet and stereolithographic 3D-printing.
Visualization of the recovery process of defects in a cultured cell layer by chemical imaging sensor
(2016)
The chemical imaging sensor is a field-effect sensor which is able to visualize both the distribution of ions (in LAPS mode) and the distribution of impedance (in SPIM mode) in the sample. In this study, a novel cell assay is proposed, in which the chemical imaging sensor operated in SPIM mode is applied to monitor the recovery of defects in a cell layer brought into proximity of the sensing surface. A reduced impedance at a defect formed artificially in a cell layer was successfully visualized in a photocurrent image. The cell layer was cultured over two weeks, during which the temporal change of the photocurrent distribution corresponding to the recovery of the defect was observed.
On-line monitoring of the metabolic activity of microorganisms involved in intermediate stages of biogas production plays an important role to avoid undesirable “down times” during the biogas production. In order to control this process, an on-chip differential measuring system based on the light-addressable potentiometric sensor (LAPS) principle combined with a 3D-printed multi-chamber structure has been realized. As a test microorganism, Escherichia coli K12 (E. coli K12) were used for cell-based measurements. Multi-chamber structures were developed to determine the metabolic activity of E. coli K12 in suspension for a different number of cells, responding to the addition of a constant or variable amount of glucose concentrations, enabling differential and simultaneous measurements.
Abstractauthoren Graphene oxide (GO) nanoparticles were incorporated in temperature-sensitive Poly(N-isopropylacrylamide) (PNIPAAm) hydrogels. The nanoparticles increase the light absorption and convert light energy into heat efficiently. Thus, the hydrogels with GO can be stimulated spatially resolved by illumination as it was demonstrated by IR thermography. The temporal progression of the temperature maximum was detected for different concentrations of GO within the polymer network. Furthermore, the compatibility of PNIPAAm hydrogels with GO and cell cultures was investigated. For this purpose, culture medium was incubated with hydrogels containing GO and the viability and morphology of chinese hamster ovary (CHO) cells was examined after several days of culturing in presence of this medium.
Purpose
Two semi-empirical models were recently published, both making use of existing literature data, but each taking into account different physical phenomena that trigger hemolysis. In the first model, hemoglobin (Hb) release is described as a permeation procedure across the membrane, assuming a shear stress-dependent process (sublethal model). The second model only accounts for hemoglobin release that is caused by cell membrane breakdown, which occurs when red blood cells (RBC) undergo mechanically induced shearing for a period longer than the threshold time (nonuniform threshold model). In this paper, we introduce a model that considers the hemolysis generated by both these possible phenomena.
Methods
Since hemolysis can possibly be caused by permeation of hemoglobin through the RBC functional membrane as well as by release of hemoglobin from RBC membrane breakdown, our proposed model combines both these models. An experimental setup consisting of a Couette device was utilized for validation of our proposed model.
Results
A comparison is presented between the damage index (DI) predicted by the proposed model vs. the sublethal model vs. the nonthreshold model and experimental datasets. This comparison covers a wide range of shear stress for both human and porcine blood. An appropriate agreement between the measured DI and the DI predicted by the present model was obtained.
Conclusions
The semiempirical hemolysis model introduced in this paper aims for significantly enhanced conformity with experimental data. Two phenomenological outcomes become possible with the proposed approach: an estimation of the average time after which cell membrane breakdown occurs under the applied conditions, and a prediction of the ratio between the phenomena involved in hemolysis.