Peptide-Mediated Constructs of Quantum Dot Nanocomposites for Enzymatic Control of Nonradiative Energy Transfer

Cataloged from PDF version of article.A bottom-up approach for constructing colloidal semiconductor quantum dot (QDot) nanocomposites that facilitate nonradiative Forster-type resonance energy transfer (FRET) using polyelectrolyte peptides was proposed and realized. The electrostatic interaction of these polypeptides with altering chain lengths was probed for thermodynamic, structural, and morphological aspects. The resulting nanocomposite film was successfully cut with the protease by digesting the biomimetic peptide layer upon which the QDot assembly was constructed. The ability to control photoluminescence decay lifetime was demonstrated by proteolytic enzyme activity, opening up new possibilities for biosensor applications

Effect of different segmentation methods using optical satellite imagery to estimate fuzzy clustering parameters for Sentinel-1A SAR images

Optical and SAR data are efficient data sources for shoreline monitoring. The processing of SAR data such as feature extraction is not an easy task since the images have totally different structure than optical imagery. Determination of threshold value is a challenging task for SAR data. In this study, SENTINEL-2A optical data was used as ancillary data to predict fuzzy membership parameters for segmentation of SENTINEL-1A SAR data to extract shoreline. SENTINEL-2A and SENTINEL-1A satellite images used were taken in September 9, 2016 and September 13, 2016 respectively. Three different segmentation algorithms which are selected from object, learning and pixel-based methods. They have been exploited to obtain land and water classes which have been used as an input data for parameter estimation. Thus, the performance of different segmentation algorithm has been investigated and analysed. In the first step of the study, Mean-Shift, Random Forest and Whale Optimization algorithms have been employed to obtain water and land classes from the SENTINEL-2A image. Water and land classes derived from each algorithm – are used as input data, and then the required parameters for the fuzzy clustering of SENTINEL-1A SAR image, were calculated. Lake Constance, Germany has been chosen as the study area. In this study, additionally an interface plugin has been developed and integrated into the open source Quantum GIS software platform. The developed interface allows non-experts to process and extract the shorelines without using any parameters. But, this system requires pre-segmented data as input. Thus, the batch process calculates the required parameters

Genetically-Tunable Mechanical Properties of Bacterial Functional Amyloid Nanofibers

Bacterial biofilms are highly ordered, complex, dynamic material systems including cells, carbohydrates, and proteins. They are known to be resistant against chemical, physical, and biological disturbances. These superior properties make them promising candidates for next generation biomaterials. Here we investigated the morphological and mechanical properties (in terms of Young’s modulus) of genetically-engineered bacterial amyloid nanofibers of Escherichia coli (E. coli) by imaging and force spectroscopy conducted via atomic force microscopy (AFM). In particular, we tuned the expression and biochemical properties of the major and minor biofilm proteins of E. coli (CsgA and CsgB, respectively). Using appropriate mutants, amyloid nanofibers constituting biofilm backbones are formed with different combinations of CsgA and CsgB, as well as the optional addition of tagging sequences. AFM imaging and force spectroscopy are used to probe the morphology and measure the Young’s moduli of biofilm protein nanofibers as a function of protein composition. The obtained results reveal that genetically-controlled secretion of biofilm protein components may lead to the rational tuning of Young’s moduli of biofilms as promising candidates at the bionano interface. © 2017 American Chemical Society

Detection of Epileptic Seizure Using STFT and Statistical Analysis

In this study, EEG data from two volunteer individuals, a healthy individual and a patient with epilepsy, were investigated with two different methods in order to distinguish healthy and patient individuals from each other. The data were obtained from a healthy individual and from a patient with epilepsy at the time of epileptic seizure and of seizure-free interval. The data are those of which validity and reliability were proven and were supplied from the data bank records of University Hospital of Bonn in Germany. In the study, the statistical parameters of the collected data were calculated, then the same data were analysed using short-time Fourier transform (STFT) method, and then they were compared. Both statistical parameter results and spectrum analysis results are compatible with each other, and they can successfully detect healthy individuals and epileptic patients at the time of epileptic seizure and seizure-free interval. In this sense, the results were mathematically highly compatible, which offers significant information for the diagnosis of the disease. In the analysis, the variance values were determined as 253.203 for the healthy individual, 806.939 for the patient at seizure-free interval and 6985.755 for that patient at the time of seizure. Accordingly, standard deviation can be said to be quite distinctive in the designation of values. The frequencies of all three cases resulted in 0, 0–5 and 0–20 Hz, respectively, as a result of conducted STFT analysis, which is quite consistent with the results of the statistical analysis parameters

Novel Dynamic Partial Reconfiguration Implementation of K-Means Clustering on FPGAs: Comparative Results with GPPs and GPUs

K-means clustering has been widely used in processing large datasets in many fields of studies. Advancement in many data collection techniques has been generating enormous amounts of data, leaving scientists with the challenging task of processing them. Using General Purpose Processors (GPPs) to process large datasets may take a long time; therefore many acceleration methods have been proposed in the literature to speed up the processing of such large datasets. In this work, a parameterized implementation of the K-means clustering algorithm in Field Programmable Gate Array (FPGA) is presented and compared with previous FPGA implementation as well as recent implementations on Graphics Processing Units (GPUs) and GPPs. The proposed FPGA has higher performance in terms of speedup over previous GPP and GPU implementations (two orders and one order of magnitude, resp.). In addition, the FPGA implementation is more energy efficient than GPP and GPU (615x and 31x, resp.). Furthermore, three novel implementations of the K-means clustering based on dynamic partial reconfiguration (DPR) are presented offering high degree of flexibility to dynamically reconfigure the FPGA. The DPR implementations achieved speedups in reconfiguration time between 4x to 15x

Induction of DNA breaks and apoptosis in crosslink-hypersensitive V79 cells by the cytostatic drug β-D-glucosyl-ifosfamide mustard

To study molecular aspects of cytotoxicity of the anticancer drug β-D-glucose-ifosfamide mustard we investigated the potential of the agent to induce apoptosis and DNA breakage. Since β-D-glucose-ifosfamide mustard generates DNA interstrand crosslinks, we used as an in vitro model system a pair of isogenic Chinese hamster V79 cells differing in their sensitivity to crosslinking agents. CL-V5B cells are dramatically more sensitive (30-fold based on D10 values) to the cytotoxic effects of β-D-glucose-ifosfamide mustard as compared to parental V79B cells. After 48 h of pulse-treatment with the agent, sensitive cells but not the resistant parental line undergo apoptosis and necrosis, with apoptosis being the predominant form of cell death (70 and 20% of apoptosis and necrosis, respectively). Apoptosis increased as a function of dose and was accompanied by induction of DNA double-strand breaks in the hypersensitive cells. Furthermore, a strong decline in the level of Bcl-2 protein and activation of caspases-3, -8 and -9 were observed. The resistant parental cells were refractory to all these parameters. Bcl-2 decline in the sensitive cells preceded apoptosis, and transfection-mediated overexpression of Bcl-2 protected at least in part from apoptosis. From the data we hypothesize that non-repaired crosslinks induced by β-D-glucose-ifosfamide mustard are transformed into double-strand breaks which trigger apoptosis via a Bcl-2 dependent pathway

EFFECT OF DIFFERENT SEGMENTATION METHODS USING OPTICAL SATELLITE IMAGERY TO ESTIMATE FUZZY CLUSTERING PARAMETERS FOR SENTINEL-1A SAR IMAGES

Optical and SAR data are efficient data sources for shoreline monitoring. The processing of SAR data such as feature extraction is not an easy task since the images have totally different structure than optical imagery. Determination of threshold value is a challenging task for SAR data. In this study, SENTINEL-2A optical data was used as ancillary data to predict fuzzy membership parameters for segmentation of SENTINEL-1A SAR data to extract shoreline. SENTINEL-2A and SENTINEL-1A satellite images used were taken in September 9, 2016 and September 13, 2016 respectively. Three different segmentation algorithms which are selected from object, learning and pixel-based methods. They have been exploited to obtain land and water classes which have been used as an input data for parameter estimation. Thus, the performance of different segmentation algorithm has been investigated and analysed. In the first step of the study, Mean-Shift, Random Forest and Whale Optimization algorithms have been employed to obtain water and land classes from the SENTINEL-2A image. Water and land classes derived from each algorithm – are used as input data, and then the required parameters for the fuzzy clustering of SENTINEL-1A SAR image, were calculated. Lake Constance, Germany has been chosen as the study area. In this study, additionally an interface plugin has been developed and integrated into the open source Quantum GIS software platform. The developed interface allows non-experts to process and extract the shorelines without using any parameters. But, this system requires pre-segmented data as input. Thus, the batch process calculates the required parameters

the fire assay reloaded

The fire assay process is still the most accurate and precise method for measuring the gold content in gold alloys. Scanning electron microscopy and transmission electron microscopy have been applied to observe the change in microstructure of the samples undergoing the fire assay process. The performed observations reveal that the microstructure of the specimen is more complex than expected. Before the parting stage, the specimen is not a perfect gold–silver binary alloy but contains also copper–silver oxides and other residual compounds. The parting stage appears to be a dealloying process leading to a nanoporous gold nanostructure. What observed after partition explains the evolution of the shape and colour of the specimen and may allow for a better comprehension of the procedure and an improvement in the method

Incidentalomas during imaging for primary hyperparathyroidism—incidence and clinical outcomes

Background: Imaging for pre-operative localisation of parathyroid glands in primary hyperparathyroidism is now routine. This has led to the detection of incidental lesions (incidentalomas) in other organs, the nature of which is not well characterised. The aim of this study was to determine the incidence, characteristics and outcomes in patients who had incidental findings on parathyroid imaging. Methods: Records of patients who underwent imaging for primary hyperparathyroidism over 2 years were reviewed to identify incidental lesions detected on parathyroid imaging. Patients with persistent or renal hyperparathyroidism were excluded. Details on the management of detected incidentalomas were obtained from patient records. Results: Incidentalomas were identified in 17 of 170 patients (10 %) undergoing parathyroid imaging. Incidentalomas included thyroid (n = 11), breast (n = 3), lateral compartment of the neck (n = 1), lung (n = 1) and clavicle (n = 1). However, no disease of clinical significance needing treatment was detected on further investigation. Conclusions: Although a significant proportion of patients undergoing parathyroid imaging had incidental lesions detected, these seem to be of little clinical significance. The morbidity and cost of further interventions on these incidentalomas need to be weighed against the benefits of routine imaging in improving outcomes of first-time surgery in patients with primary hyperparathyroidism. Keywords: Parathyroid gland, Primary hyperparathyroidism, Imaging, Incidentaloma