Doppler fluctuation spectroscopy of intracellular dynamics in living tissue

Intracellular dynamics in living tissue are dominated by active transport driven by bioenergetic processes far from thermal equilibrium. Intracellular constituents typically execute persistent walks. In the limit of long mean free paths, the persistent walks are ballistic, exhibiting a "Doppler edge" in light scattering fluctuation spectra. At shorter transport lengths, the fluctuations are described by lifetime-broadened Doppler spectra. Dynamic light scattering from transport in the ballistic, diffusive, or the crossover regimes is derived analytically, including the derivation of autocorrelation functions through a driven damped harmonic oscillator analog for light scattering from persistent walks. The theory is validated through Monte Carlo simulations. Experimental evidence for the Doppler edge in three-dimensional (3D) living tissue is obtained using biodynamic imaging based on low-coherence interferometry and digital holography

Intracellular Doppler Signatures of Platinum Sensitivity Captured by Biodynamic Profiling in Ovarian Xenografts

Three-dimensional (3D) tissue cultures are replacing conventional two-dimensional (2D) cultures for applications in cancer drug development. However, direct comparisons of in vitro 3D models relative to in vivo models derived from the same cell lines have not been reported because of the lack of sensitive optical probes that can extract high-content information from deep inside living tissue. Here we report the use of biodynamic imaging (BDI) to measure response to platinum in 3D living tissue. BDI combines low-coherence digital holography with intracellular Doppler spectroscopy to study tumor drug response. Human ovarian cancer cell lines were grown either in vitro as 3D multicellular monoculture spheroids or as xenografts in nude mice. Fragments of xenografts grown in vivo in nude mice from a platinum-sensitive human ovarian cell line showed rapid and dramatic signatures of induced cell death when exposed to platinum ex vivo, while the corresponding 3D multicellular spheroids grown in vitro showed negligible response. The differences in drug response between in vivo and in vitro growth have important implications for predicting chemotherapeutic response using tumor biopsies from patients or patient-derived xenografts

Model based wind turbine gearbox fault detection on SCADA data

Developing effective wind turbine fault detection algorithm is not only meaningful for improving wind turbine reliability but also crucial for future intelligent wind farm operation and management. Typical wind turbine gearbox condition monitoring is based on vibration signals, which is effective to detect failures with high frequency signal range. But it may not be effective on low speed components which have low frequency signal characteristic of different failure modes. SCADA system collecting multiple low frequency signals provides a cost-effective way to monitor wind turbines health and performance, while its capability on fault detection is still an open issue. To systematic understand wind turbine systems, this paper presents research results of model based wind turbine gearbox fault detection. Through a detail analysis of thermodynamic process of gearbox lubrication system, a wind turbine drive train model which considers heat transferring mechanism in gearbox lubrication system is built to derive robust relationships between transmission efficiency, temperature, and rotational speed signals of wind turbine gearbox and suggest useful information for lubrication system design and optimization. The result obtained in this work is useful for wind turbine gearbox design and effective algorithm development of fault detection

Next-generation DNA sequencing-based assay for measuring allelic expression imbalance (AEI) of candidate neuropsychiatric disorder genes in human brain

<p>Abstract</p> <p>Background</p> <p>Common genetic variants that regulate gene expression are widely suspected to contribute to the etiology and phenotypic variability of complex diseases. Although high-throughput, microarray-based assays have been developed to measure differences in mRNA expression among independent samples, these assays often lack the sensitivity to detect rare mRNAs and the reproducibility to quantify small changes in mRNA expression. By contrast, PCR-based allelic expression imbalance (AEI) assays, which use a "marker" single nucleotide polymorphism (mSNP) in the mRNA to distinguish expression from pairs of genetic alleles in individual samples, have high sensitivity and accuracy, allowing differences in mRNA expression greater than 1.2-fold to be quantified with high reproducibility. In this paper, we describe the use of an efficient PCR/next-generation DNA sequencing-based assay to analyze allele-specific differences in mRNA expression for candidate neuropsychiatric disorder genes in human brain.</p> <p>Results</p> <p>Using our assay, we successfully analyzed AEI for 70 candidate neuropsychiatric disorder genes in 52 independent human brain samples. Among these genes, 62/70 (89%) showed AEI ratios greater than 1 ± 0.2 in at least one sample and 8/70 (11%) showed no AEI. Arranging log₂AEI ratios in increasing order from negative-to-positive values revealed highly reproducible distributions of log₂AEI ratios that are distinct for each gene/marker SNP combination. Mathematical modeling suggests that these log₂AEI distributions can provide important clues concerning the number, location and contributions of <it>cis</it>-acting regulatory variants to mRNA expression.</p> <p>Conclusions</p> <p>We have developed a highly sensitive and reproducible method for quantifying AEI of mRNA expressed in human brain. Importantly, this assay allowed quantification of differential mRNA expression for many candidate disease genes entirely missed in previously published microarray-based studies of mRNA expression in human brain. Given the ability of next-generation sequencing technology to generate large numbers of independent sequencing reads, our method should be suitable for analyzing from 100- to 200-candidate genes in 100 samples in a single experiment. We believe that this is the appropriate scale for investigating variation in mRNA expression for defined sets candidate disorder genes, allowing, for example, comprehensive coverage of genes that function within biological pathways implicated in specific disorders. The combination of AEI measurements and mathematical modeling described in this study can assist in identifying SNPs that correlate with mRNA expression. Alleles of these SNPs (individually or as sets) that accurately predict high- or low-mRNA expression should be useful as markers in genetic association studies aimed at linking candidate genes to specific neuropsychiatric disorders.</p

Evaluation of a novel saliva-based epidermal growth factor receptor mutation detection for lung cancer: A pilot study.

BackgroundThis article describes a pilot study evaluating a novel liquid biopsy system for non-small cell lung cancer (NSCLC) patients. The electric field-induced release and measurement (EFIRM) method utilizes an electrochemical biosensor for detecting oncogenic mutations in biofluids.MethodsSaliva and plasma of 17 patients were collected from three cancer centers prior to and after surgical resection. The EFIRM method was then applied to the collected samples to assay for exon 19 deletion and p.L858 mutations. EFIRM results were compared with cobas results of exon 19 deletion and p.L858 mutation detection in cancer tissues.ResultsThe EFIRM method was found to detect exon 19 deletion with an area under the curve (AUC) of 1.0 in both saliva and plasma samples in lung cancer patients. For L858R mutation detection, the AUC of saliva was 1.0, while the AUC of plasma was 0.98. Strong correlations were also found between presurgery and post-surgery samples for both saliva (0.86 for exon 19 and 0.98 for L858R) and plasma (0.73 for exon 19 and 0.94 for L858R).ConclusionOur study demonstrates the feasibility of utilizing EFIRM to rapidly, non-invasively, and conveniently detect epidermal growth factor receptor mutations in the saliva of patients with NSCLC, with results corresponding perfectly with the results of cobas tissue genotyping