Development Of Inlet And Vacuum Ionization Methods For Characterization Of Biological Materials By Mass Spectrometry

Inlet ionization and vacuum ionization are novel ionization methods to produce electrospray ionization (ESI)-like ions from the solid or liquid states, operating from atmospheric pressure (AP) or vacuum, without the use of voltage or the necessity of high energy input such as a laser or particle beam. The fundamental aspects were probed for better understanding of the novel ionization processes. Initial applications were attempted to utilize the novel ionization methods for fast, robust, and quantitative analyses. For inlet ionizations (laserspray ionization inlet, LSII; matrix assisted ionization inlet, MAII; and solvent assisted ionization inlet, SAII), small (e.g. drugs) to large (e.g. proteins) non-volatile molecules are ionized with the assistance of heat and pressure drop, and are operated from AP. The ease of operation, rapidness of data acquisition, and simplicity of coupling with other techniques achieved by SAII, have enabled the inlet ionization for high throughput multiplexing analyses, hyphenation with liquid chromatography (especially at low flow rates), and fast surface assessment and drug quantifications. LSII has been utilized together with solvent-free sample preparation and solvent-free gas-phase separation for total solvent-free analysis. The production of multiply charged ions from solid states by vacuum ionization was utilized to encompass the advantages from ESI and matrix-assisted laser desorption/ionization (MALDI), for better characterization from surfaces and extending the mass range of high performance mass spectrometers. Operating from AP provides the potential for vacuum ionization to be applied in high throughput analysis. The continuous ion formation also benefits matrix assisted ionization vacuum (MAIV) for drug quantification with better reproducibility

Real-Time GNSS satellite SISRE and its integrity for LEO satellite POD

The real-time Global Navigation Satellite System (GNSS) precise orbital and clock products are essential prerequisites for the Positioning, Navigation, and Timing (PNT) services and have been assessed in various studies. Compared to the precision of the orbital and clock products, their combined effect expressed in Signal-In-Space Ranging Error (SISRE) is of higher concern for positioning users. As a special user of the GNSS, the Low Earth Orbit (LEO) satellites need high-precision real-time GNSS products for their Precise Orbit Determination (POD) and clock determination in real time, which enables the future LEO-augmented GNSS PNT service. This study performs a comprehensive analysis of the real-time GNSS products from five different analysis centers, including analysis of their continuity, accuracy of their orbits, precision of their clocks, and their SISREs for LEO satellites at different altitudes. Using the tested products, the LEO POD was also performed to verify the correlation between the quality of the GNSS products and the accuracy of the LEO POD. Furthermore, to assess the integrity of real-time GNSS products, the overbounding standard deviations and mean values of the combined clock and orbital errors were computed and compared for different institutions. It was found that the GPS and Galileo SISRE range from a few centimeters to around 8 cm, while the SISRE of the Beidou Satellite Navigation System (BDS) Medium Earth Orbit (MEO) is a bit worse, i.e., around 1-2 dm. It has been demonstrated that there exists a positive correlation between the SISRE and user altitude, which implies a higher bias introduced to LEO satellites than ground users. The overbounding standard deviations and mean values of the GPS and Galileo products are all within 1 dm, whereas for BDS they are about 1-2 dm. Among the tested products, the smallest SISRE and overbounding values were delivered by the National Centre for Space Studies (CNES) in France for GPS and Galileo, while the GNSS Research Center of Wuhan University (WHU) provided the best accuracy and integrity for the BDS MEO products

High-Throughput Solvent Assisted Ionization <i>Inlet</i> for Use in Mass Spectrometry

In this work we developed a multiplexed analysis platform providing a simple high-throughput means to characterize solutions. Automated analyses, requiring less than 5 s per sample without carryover and 1 s per sample, accepting minor cross contamination, was achieved using multiplexed solvent assisted ionization <i>inlet</i> (SAII) mass spectrometry (MS). The method involves sequentially moving rows of pipet tips containing sample solutions in close proximity to the inlet aperture of a heated mass spectrometer inlet tube. The solution is pulled from the container into the mass spectrometer inlet by the pressure differential at the mass spectrometer inlet aperture. This sample introduction method for direct injection of solutions is fast, easily implemented, and widely applicable, as is shown by applications ranging from small molecules to proteins as large as carbonic anhydrase (molecular weight ca. 29 000). MS/MS fragmentation is applicable for sample characterization. An <i>x</i>,<i>y</i>-stage and common imaging software are incorporated to map the location of components in the sample wells of a microtiter plate. Location within an <i>x</i>,<i>y</i>-array of different sample solutions and the relative concentration of the sample are displayed using ion intensity maps

MicroRNA-384 Inhibits the Progression of Papillary Thyroid Cancer by Targeting PRKACB

Background. Growing evidence shows that dysregulation of miRNAs plays a significant role in papillary thyroid cancer (PTC) tumorigenesis and development. The abnormal expression of miR-384 has been acknowledged in the proliferation or metastasis of some cancers. However, the function and the underlying mechanism of miR-384 in PTC progression remain largely unknown. Methods. Real-time PCR was conducted to detect miR-384 expression in 58 cases of PTC and their adjacent noncancerous tissues. MTT, soft agar assay Transwell assay, and wound-healing assay were carried out to explore the biological function of miR-384 in PTC cell lines of BCPAP and K1. Bioinformatics analysis, dual-luciferase reporter assay, western blot, and functional complementation analysis were conducted to explore the target gene of miR-384. Moreover, Spearman’s correlation analysis was conducted to reveal the correlation between miR-384 and PRKACB mRNA in PTC. Results. The expression of miR-384 decreased obviously in PTC, especially in the tumors with lymph node metastasis or larger tumor size. The ectopic upregulation of miR-384 significantly suppressed PTC progression, and the inhibition of miR-384 had the opposite effects. Moreover, PRKACB gene was confirmed as the target of miR-384. Conclusion. The study suggests that miR-384 serves as a tumor suppressor in PTC progression by directly targeting the 3′-UTR of PRKACB gene

Retrieval of Road Surface (Bridge Deck) Temperature near 0 °C Based on Random Forest Model

Based on the road surface (bridge deck) temperature, relative humidity, air temperature, wind speed and precipitation observed at two road surface meteorological stations and two bridge deck meteorological stations, as well as subsurface temperature at different depths observed at Hefei meteorological station, the independent variables are selected to establish the relationship between these factors and road surface temperature, using random forest and stepwise regression. The performance of these two methods was compared, and the importance of each factor was analyzed. Results show that the road surface (bridge deck) temperature linearly correlates with air temperature. In the case of low air temperature conditions (air temperature ≤ 8 °C), the road surface temperature is mainly higher than air temperature observed at the same station, and the bridge deck temperature is mainly lower than air temperature. In the retrieving of road surface temperature and bridge deck temperature, the random forest algorithm has lower mean absolute error (MAE) and root mean square error (RMSE) than the stepwise regression algorithm, especially in the retrieving of road surface temperature. MAE of road surface temperature retrieved by random forest on two bridge deck stations is reduced by 0.19 °C and 0.26 °C compared with the stepwise regression, and RMSE is reduced by 0.33 °C and 0.49 °C, respectively. The bias in the retrievals can be originated from the model itself and the error in the observations. Among the factors in the random forest model, air temperature is the most important. Meanwhile, there are differences in the importance of each factor in the retrieval of road surface temperature and bridge deck temperature. The subsurface temperature is more important in retrieving road surface temperature, while humidity and wind speed are generally more important to bridge deck temperature. It should be noted that due to the limitation of the observations, this study did not consider the net radiative flux, and the influence of net radiative flux on bridge deck and road surface temperature may be different

Real-Time LEO Satellite Clocks Based on Near-Real-Time Clock Determination with Ultra-Short-Term Prediction

The utilization of Low Earth Orbit (LEO) satellites is anticipated to augment various aspects of traditional GNSS-based Positioning, Navigation, and Timing (PNT) services. While the LEO satellite orbital products can nowadays be produced with rather high accuracy in real-time of a few centimeters, the precision of the LEO satellite clock products that can be achieved in real-time is less studied. The latter, however, plays an essential role in the LEO-augmented positioning and timing performances. In real-time, the users eventually use the predicted LEO satellite clocks, with their precision determined by both the near-real-time clock precision and the prediction time needed to match the time window for real-time applications, i.e., the precision loss during the prediction phase. In this study, a real-time LEO satellite clock determination method, consisting of near-real-time clock determination with ultra-short-term clock prediction is proposed and implemented. The principles and strategies of this method are discussed in detail. The proposed method utilized Kalman-filter-based processing, but supports restarts at pre-defined times, thus hampering continuous bias propagation and accumulation from ancient epochs. Based on the method, using Sentinel-3B GNSS observations and the real-time GNSS products from the National Center for Space Studies (CNES) in France, the near-real-time LEO satellite clocks can reach a precision of 0.2 to 0.3 ns, and the precision loss during the prediction phase is within 0.07 ns for a prediction time window from 30 to 90 s. This results in a total error budget in the real-time LEO satellite clocks of about 0.3 ns

Validation and Evaluation of the China Meteorological Administration Wind Energy and Solar Energy Forecasting System (CMA-WSP) in Short-Term Wind Resource Forecasting

[Introduction] To test the reliability of the CMA-WSP wind speed product in short-term wind resource forecasting, the CMA-WSP 3 d wind speed forecasting product with a wind speed of 100 m is tested and analyzed. [Method] This research was based on the measured data of 100 m wind speed in three wind farms in Zaoyang Zhoulou, Macheng Caijiazhai and Central Dajin. [Result] The results are as follows: (1) CMA-WSP has a good overall forecasting performance on the wind speed in Zaoyang wind farm within three days. The forecasted results are consistent with the measured wind speed change trend. The correlation between the forecasted and the measured wind speed on the first day are 0.728, 0.74 and 0.86 for 15 min intervals, hourly averages, and daily averages, respectively. (2) The relative error between the CMA-WSP forecast and the measured wind speed shows a strong regularity. The relative errors for the forecasted wind speed on the first day are 68 %, 70 % and 92 % for 15 min intervals, hourly averages, and daily averages, respectively. The forecasted wind speed is higher than the measured wind speed. The hourly average wind speed and relative error are characterized by low wind speed during the day and high wind speed at night. The change of monthly average wind speed is opposite to the change of MRE value, and it is the lowest from January to June and from October to December, and the highest from July to September. (3) When considering regional differences, CMA-WSP has the best forecasting effect on the wind speed in Zaoyang wind farm. The correlation between the forecasted and the measured wind speed on the first day can reach 0.728, and the correlation on the second to third days is also more than 0.6. The correlation between the forecasted wind speed and the measured wind speed in Caijiazhai and Central Dajin by CMA-WSP is less than 0.6. [Conclusion] CMA-WSP forecasting performance is favorable as a whole, and the relative error has strong regularity. It is beneficial to revise the product and reduce the error level in the next step

Matrix-Assisted Ionization Vacuum for High-Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometers

Matrix-assisted ionization vacuum (MAIV) produces charge states similar to electrospray ionization (ESI) from the solid state without requiring high voltage or added heat. MAIV differs from matrix-assisted laser desorption/ionization (MALDI) in that no laser is needed and abundant multiply charged ions are produced from molecules having multiple basic sites such as proteins. Here we introduce simple modifications to the commercial vacuum MALDI and ESI sources of a 9.4 T Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometer to perform MAIV from both intermediate and atmospheric pressure. The multiply charged ions are shown for the proteins bovine insulin, ubiquitin, and lysozyme using 3-nitrobenzonitrile as matrix. These are the first examples of MAIV operating at pressures as low as 10^–6 mbar in an FT-ICR mass spectrometer source, and the expected mass resolving power of 100000 to 400000 is achieved. Identical protein charge states are observed with and without laser ablation indicating minimal, if any, role of photochemical ionization for the compounds studied

Gas-Phase Ions Produced by Freezing Water or Methanol for Analysis Using Mass Spectrometry

Introducing water or methanol containing a low concentration of volatile or nonvolatile analyte into an inlet tube cooled with dry ice linking atmospheric pressure and the first vacuum stage of a mass spectrometer produces gas-phase ions even of small proteins that can be detected by mass spectrometry. Collision-induced dissociation experiments conducted in the first vacuum region of the mass spectrometer suggest analyte ions being protected by a solvent cage. The charges may be produced by processes similar to those proposed for charge separation under freezing conditions in thunderclouds. By this process, the surface of an ice pellet is charged positive and the interior negative so that removal of surface results in charge separation. A reversal of surface charge is expected for a heated droplet surface, and this is observed by heating rather than cooling the inlet tube. These observations are consistent with charged supercooled droplets or ice particles as intermediates in the production of analyte ions under freezing conditions

The Occupied Territories Destruction or development? A study of the problems and prospects for economic, social and political development in a context of colonialism

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