Cross-talk-free dual-color fluorescence cross-correlation spectroscopy for high-throughtput screening

High throughput processing of chemical/biochemical information is critical in many areas, such as genome sequencing, drug discovery and clinical diagnostics. Integral to collecting information at high rates with the necessary throughput is the development of systems that can not only monitor the results with high precision and accuracy, but also prepare and process samples prior to the analytical measurement. To achieve the required throughput, we have conducted work directed toward developing a system that provides detection sensitivity at the single-molecule detection (SMD) level. The research was first focused on the development of a sensitive strategy for the detection of proteins (thrombin) at the SMD level. Nucleic acid-based fluorescence sensors were used as recognition elements for the detection of single protein molecules with single-pair fluorescence resonance energy transfer. The technique provided higher analytical sensitivity compared to bulk analog measurements due to the digital readout format (i.e., molecular counting) and also reduced assay turn-around-time. Research was then directed toward the design and construction of a two-color FCCS system, which employed two spectrally separate fluorophores, Cy3 (λabs = 532 nm, λem= 560 nm) and IRD800 (λabs = 780 nm, λem= 810 nm). The system provided negligible color cross-talk (cross-excitation and/or cross-emission) and/or fluorescence resonance energy transfer (FRET). To provide evidence of cross-talk free operation, the system was evaluated using microspheres and quantum dots. Experimental results indicated no color leakage from the microspheres or quantum dots into inappropriate color channels. The enzymatic activity of APE1 was monitored by FCCS using a double-stranded DNA substrate that was dual labeled with Cy3 and IRD800. Activity of APE1 was also monitored in the presence of an inhibitor (7-nitroindole-2-carboxylic acid). To improve sample processing throughput, a multi-phase (water-in-oil) segmented flow microfluidic chip was studied using the FCCS system to monitor APE1 enzyme activity. Aqueous droplets were generated in a perfluorocarbon (FC-3283) carrier fluid with a nonionic surfactant (Perfluorooctanol, 10% v/v) in a polymer microchip. The optical system successfully monitored the controlled generation of highly regular droplets loaded with fluorescent beads at delivery rates ranging from 40 - 60 droplets per sec

Accurate characterization of winter precipitation using multi-angle snowflake camera, visual hull, advanced scattering methods and polarimetric radar

Includes bibliographical references (pages 28-31).This article proposes and presents a novel approach to the characterization of winter precipitation and modeling of radar observables through a synergistic use of advanced optical disdrometers for microphysical and geometrical measurements of ice and snow particles (in particular, a multi-angle snowflake camera-MASC), image processing methodology, advanced method-of-moments scattering computations, and state-of-the-art polarimetric radars. The article also describes the newly built and established MASCRAD (MASC + Radar) in-situ measurement site, under the umbrella of CSU-CHILL Radar, as well as the MASCRAD project and 2014/2015 winter campaign. We apply a visual hull method to reconstruct 3D shapes of ice particles based on high-resolution MASC images, and perform "particle-by-particle" scattering computations to obtain polarimetric radar observables. The article also presents and discusses selected illustrative observation data, results, and analyses for three cases with widely-differing meteorological settings that involve contrasting hydrometeor forms. Illustrative results of scattering calculations based on MASC images captured during these events, in comparison with radar data, as well as selected comparative studies of snow habits from MASC, 2D video-disdrometer, and CHILL radar data, are presented, along with the analysis of microphysical characteristics of particles. In the longer term, this work has potential to significantly improve the radar-based quantitative winter-precipitation estimation.Published with support from the Colorado State University Libraries Open Access Research and Scholarship Fund

2DVD dataset for GMD publication - Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign

<p>This archive contains the 2DVD measurement of graupel particles used in the GMD paper "Simulated prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign".</p><p>For each identified graupel particle, the following are included:</p><ul><li>Volume-equivalent diameter (mm)</li><li>Density (g cm-3)</li><li>Fall velocity (m s-1)</li></ul&gt

Regional Differences of Primary Meteorological Factors Impacting O3 Variability in South Korea

Surface ozone (O3) is a harmful pollutant and effective strategies must be developed for its reduction. In this study, the impact of meteorological factors on the annual O3 variability for South Korea were analyzed. In addition, the regional differences of meteorological factors in six air quality regions in South Korea (Seoul Metropolitan Area, SMA; Central region, CN; Honam, HN; Yeongnam, YN; Gangwon, GW; Jeju, JJ) were compared. The analysis of ground observation data from 2001 to 2017 revealed that the long-term variability of O3 concentration in South Korea continuously increased since 2001, and the upward trend in 2010 to 2017 (Period 2, PRD2) was 29.8% higher than that in 2001 to 2009 (Period 1, PRD1). This was because the meteorological conditions during PRD2 became relatively favorable for high O3 concentrations compared to conditions during PRD1. In particular, the increase in the solar radiation (SR) and maximum temperature (TMAX) and the decrease in the precipitation (PRCP) and wind speed (WS) of South Korea in PRD2 were identified as the main causes for the rise in O3 concentrations. When meteorological factors and O3 variability were compared among the six air quality regions in South Korea during PRD1 and PRD2, significant differences were observed. This indicated that different meteorological changes occurred in South Korea after 2010 due to the different topographical characteristics of each region; thus, O3 variability also changed differently in each region. Interestingly, for the regions with almost similar meteorological changes after 2010, the O3 concentration changed differently depending on the difference in the distribution of emissions. These results indicate that the O3–meteorology relationship shows spatiotemporal differences depending on the topographical and emission distribution characteristics of each area and implies that it is necessary to fully consider such differences for efficient O3 reduction

Quantitative Precipitation Estimates Using Machine Learning Approaches with Operational Dual-Polarization Radar Data

Traditional radar-based rainfall estimation is typically done by known functional relationships between the rainfall intensity (R) and radar measurables, such as R–Zh, R–(Zh, ZDR), etc. One of the biggest advantages of machine learning algorithms is the applicability to a non-linear relationship between a dependent variable and independent variables without any predefined relationships. We explored the potential use of two supervised machine learning methods (regression tree and random forest) in rainfall estimation using dual-polarization radar variables. The regression tree does not require normalization and scaling of data; however, this method is quite unstable since each split depends on the parent split. Since the random forest is an ensemble method of regression trees, it has less variability in prediction compared with regression trees, but consumes more computer resources. We considered several different configurations for machine learning algorithms with different sets of dependent and independent variables. The random forest model was appropriately tuned. In the test of variable importance, the specific differential phase (differential reflectivity) was the most important variable to predict the rainfall rate (residual that is the difference between the true rainfall rate and the one estimated from the R–Z relationship). The models were evaluated by 10-fold cross-validation. The best model was the random forest model using a residual with the non-classified training set. The results indicated that the machine learning algorithms outperformed the traditional R–Z relationship. Then, we applied the best machine learning model to an S-band dual-polarization radar (Mt. Myeonbong) and validated the result with ground rain gauges. The results of the application to radar data showed that the estimates of the residuals had spatial variability. The stratiform and weak rain areas had positive residuals while convective areas had negative residuals, indicating that the spatial error structure driven by the R–Z relationship was well captured by the model. The rainfall rates of all pixels over the study area were adjusted with the estimated residuals. The rainfall rates adjusted by residual showed excellent agreement with the rain gauge, especially at high rainfall rates

Lin28a ameliorates glucotoxicity-induced beta-cell dysfunction and apoptosis

An excessive and prolonged increase in glucose levels causes beta-cell dysregulation, which is accompanied by impaired insulin synthesis and secretion, a condition known as glucotoxicity. Although it is known that both Lin28a and Lin28b regulate glucose metabolism, other molecular mechanisms that may protect against glucotoxicity are poorly understood. We investigated whether Lin28a overexpression can improve glucotoxicity-induced beta-cell dysregulation in INS-1 and primary rat islet cells. INS-1, a rat insulinoma cell line was cultured and primary rat islet cells were isolated from SD-rats. To define the effect of Lin28a in chronic high glucose-induced beta-cell dysregulation, we performed several in vitro and ex-vivo experiments. Chronic exposure to high glucose led to a downregulation of Lin28a mRNA and protein expression, followed by a decrease in insulin mRNA expression and secretion in beta-cells. The mRNA and protein expression levels of PDX-1 and BETA2, were reduced; The levels of apoptotic factors, including c-caspase3 and the Bax/Bcl-2 ratio, were increased due to glucotoxicity. Adenovirus-mediated Lin28a overexpression in beta-cells reversed the glucotoxicity-induced reduction of insulin secretion and insulin mRNA expression via regulation of beta-cell-enriched transcription factors such as PDX-1 and BETA2. Adenovirus-mediated overexpression of Lin28a downregulated the glucotoxicity-induced upregulation of c-caspase3 levels and the Bax/Bcl-2 ratio, while inhibition of endogenous Lin28a by small interfering RNA resulted in their up-regulation. Lin28a counteracted glucotoxicity-induced downregulation of p-Akt and p-mTOR. Our results suggest that Lin28a protects pancreatic beta-cells from glucotoxicity through inhibition of apoptotic factors via the PI3 kinase/Akt/mTOR pathway. © 2021 by the The Korean Society for Biochemistry and Molecular Biology1

Arg-Gly-Asp-modified elastin-like polypeptide regulates cell proliferation and cell cycle proteins via the phosphorylation of Erk and Akt in pancreatic β-cell.

Objective: Enhancement of β-cell proliferation plays an important role in maintaining β-cell mass and function, and in improving pancreatic β-cell survival before transplantation. Extracellular matrix (ECM) components increase the adhesion and proliferation of β-cells, and the RGD-modified elastin-like polypeptide (RGD-ELP, REP) has been described as a bioactive matrix. In this study, we investigated whether REP could enhance β-cell adhesion and proliferation and elucidated the signaling pathways involved. Methods: We investigated the effect of REP on cell adhesion, proliferation and insulin secretion via assays using Rin-m and rat islets. Crystal violet, CCK-8, and BrdU assay, FACS, western blot, real time q-PCR analyses and insulin ELISA were examined. To explain the associated mechanisms, phosphorylation of Akt and extracellular signal-regulated kinase (Erk) were measured. Results: REP more increased the adhesion, proliferation and survival of Rin-m cells compared to elastin-like poly peptide (ELP) without RGD-motif. The enhancement of β-cell proliferation by REP was associated with increased cyclin D1, cyclin D2 and cdk6, and decreased p27 levels. When β-cells were cultured on REP, Erk and the phosphatidylinositol 3-kinase (PI3-kinase) downstream effector, Akt was stimulated. Treatment with the Erk pathway inhibitor and PI3-kinase inhibitor decreased REP-induced β-cell adhesion and proliferation, and regulated REP-induced cell cycle proteins. Additionally, REP increased the mRNA and protein levels of insulin and its transcription factor, PDX-1, and insulin secretion. Conclusions: Our results demonstrate that the up-regulation of the PI3K/Akt and Erk signaling pathways and the regulation of cell cycle proteins by REP could serve as effective strategies for improving pancreatic β-cell adhesion and proliferation. © 2020 The Author(s)Tissue engineering; Biomedical materials; Cell biology; Biotechnology; Diabetes; Insulin; -cell adhesion; -cell proliferation; RGD-modified elastin-like polypeptide; Cell cycle © 2020 The Author(s)TRU