Gramicidin Ion Channel-Based Biosensors: Construction, Stochastic Dynamical Models, and Statistical Detection Algorithms

This paper deals with the experimental construction, stochastic modeling, and statistical signal processing of a novel, artificially constructed biosensor comprised of biological ion channels. Such nanoscale biosensors have been built by incorporating dimeric gramicidin A (bis-gA) ion channels into bilayer membranes of giant unilamellar liposomes, and then excising small patches of the membrane loaded with ion channels. We present a stochastic model for the response of the biosensor and present statistical model validation tests to verify the adequacy of the model. We show that in the presence of specific target molecules, the statistics of the gating mechanisms of the gA channels are altered. By capturing the change in real time, we devise a maximum-likelihood detector to detect the presence of target molecules. To test the sensitivity of this model, we conducted patch-clamp experiments with two compounds known to inhibit conduction of the gA channels. We found experimentally that the real-time detection algorithm was able to accurately identify the addition of the compounds even when the alterations in the patch-clamp recordings were very small. This algorithm provides the sensitive detection system for ongoing development of lipid-based nanosensors.     

Novel Engineered Ion Channel Provides Controllable Ion Permeability for Polyelectrolyte Microcapsules Coated with a Lipid Membrane

The development of nanostructured microcapsules based on a biomimetic lipid bilayer membrane (BLM) coating of poly(sodium styrenesulfonate) (PSS)/poly(allylamine hydrochloride) (PAH) polyelectrolyte hollow microcapsules is reported. A novel engineered ion channel, gramicidin (bis‐gA), incorporated into the lipid membrane coating provides a functional capability to control transport across the microcapsule wall. The microcapsules provide transport and permeation for drug‐analog neutral species, as well as positively and negatively charged ionic species. This controlled transport can be tuned for selective release biomimetically by controlling the gating of incorporated bis‐gA ion channels. This system provides a platform for the creation of “smart” biomimetic delivery vessels for the effective and selective therapeutic delivery and targeting of drugs.     

Dependence of thermal sensitivity of LPFG on waveguide and material parameters

This article demonstrates the effect of waveguide and material parameters on thermal sensitivity trends adopted by different cladding modes based on long-period fiber grating. Three-layer fiber geometry-based mathematical model has been implemented to estimate cladding modes. It is observed that for a cladding mode, the sign and magnitude of thermal sensitivity slope depend upon the designed grating period closer to period at dispersion turn around point. The \(\hbox {LP}_{10}\) and \(\hbox {LP}_{11}\) cladding modes have shown blueshift and maximum thermal sensitivity above all other modes at designed grating periods of 225 and \(195\,\upmu \hbox {m}\), respectively. The material parameter of fiber (thermo-optic coefficient) has also resulted in increment in sensitivity with the increase in difference amid its values for core and cladding region.     

Disposable immunochips for the detection of Legionella pneumophila using electrochemical impedance spectroscopy

The rapid diagnosis of Legionellosis is crucial for the effective treatment of this disease. Currently, most clinical laboratories utilize rapid immunoassays that are sufficient for the detection of Legionella serogroup 1, but not other clinically relevant serogroups. In this report, the development of a disposable immunochip system is described in connection with electrochemical impedance spectroscopy and fluorescence microscopy. The immunochips were prepared by covalently immobilizing fluorophore-conjugated L. pneumophilaantibodies on Au chips. The analytical performance of the immunochips was optimized as a prescreening tool for L. pneumophila. The versatile immunochips described here can be easily adapted for the monitoring of all Legionella serogroups in clinical and environmental samples.     

Preliminary study of the anticancer applications of mesoporous materials functionalized with the natural product betulinic acid

Dehydrated MCM-41 (S1) was functionalized under nitrogen with 3-chloropropyltriethoxysilane (CPTS) and 3-aminopropyltriethoxysilane (APTS) by grafting in toluene at 80 °C over 48 h to give the corresponding materials S2 and S3, respectively. Subsequently, S2 and S3 were suspended in methanol and reacted in a nitrogen atmosphere with betulinic acid (BA) for 48 h at 65 °C (in the presence of the triethylamine of S2) to give the BA-functionalized materials S4 and S5. All materials studied were characterized by powder X-ray diffraction, X-ray fluorescence, nitrogen gas sorption, multinuclear MAS NMR spectroscopy, thermogravimetry, UV spectroscopy, IR, SEM, and TEM. To study the release of BA, S4 and S5 were suspended in solutions simulating various body pH conditions (pH 7.4, 5.5, and 3.0). Results of the quantification of BA release by HPLC for S4 show a pH-dependent and very slow BA release following a logarithmic tendency, while S5 behaves differently, also pH-dependent but, in this case, fast release of BA which requires only days for total release of the therapeutic compound. In addition, the cytotoxic activity of all synthesized materials against various cancer cell lines was studied. The results show the absence of an antiproliferative effect on the surfaces without BA S1-S3, while an antiproliferative effect was observed with S4 and S5 and was attributed to the release of BA in the medium.     

Three-Dimensional Distance-Error-Correction-Based Hop Localization Algorithm for IoT Devices

The Internet of Things (IoT) is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems. These networks of wireless sensors monitor the physical environment and report the collected data to the base station, allowing for smarter decisions. Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane. However, in some application areas, such as various surveillances, underwater monitoring systems, and various environmental monitoring applications, wireless sensors are deployed in a three-dimensional plane. Recently, localization-based applications have emerged as one of the most promising services related to IoT. In this paper, we propose a novel distributed range-free algorithm for node localization in wireless sensor networks. The proposed three-dimensional hop localization algorithm is based on the distance error correction factor. In this algorithm, the error decreases with the localization process. The distance correction factor is used at various stages of the localization process, which ultimately mitigates the error. We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm. The simulation results are compared with some of the well-known existing algorithms in the literature. The results show that the proposed three-dimensional error-correction-based algorithm performs better than existing algorithms.