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Capillary- and micro-flow liquid chromatography-tandem mass spectrometry (capLC-MS/MS and μLC-MS/MS) is becoming a valuable alternative to nano-flow LC-MS/MS due to its high robustness and throughput. The systematic comparison of capLC-MS/MS and μLC-MS/MS systems for global proteome profiling has not been reported yet. Here, the capLC-MS/MS (150 μm i.d. column, 1 μL/min) and μLC-MS/MS (1 mm i.d. column, 50 μL/min) systems were both established based on UltiMate 3000 RSLCnano coupled to an Orbitrap Exploris 240 by integrating with different flowmeters. We evaluated both systems in terms of sensitivity, analysis throughput, separation efficiency, and robustness. capLC-MS/MS was about 10 times more sensitive than μLC-MS/MS at different gradient lengths. Compared with capLC-MS/MS, μLC-MS/MS was able to achieve higher analysis throughput and separation efficiency. During the 7 days' long-term performance test, both systems showed good reproducibility of chromatographic full width (RSDlt; 3%), retention time (RSDlt; 0.4%), and protein identification (RSDlt; 3%). These results demonstrate that capLC-MS/MS is more suitable for high-throughput analysis of clinical samples with a limited starting material. When enough samples are available, μLC-MS/MS is preferred. Together, capLC and μLC coupled to Orbitrap Exploris 240 with moderate sensitivity should well meet the needs of large-cohort clinical proteomic analysis.

Background Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis. Methods We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC–MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups. Results This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC–MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers. Conclusions This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups.

Volatile organic compounds (VOCs) source profiles can be used for a number of purposes, such as creating speciated air pollutant emission inventories and providing inputs to receptor and air quality models. In this study, we first collected and schematically evaluated more than 500 Chinese domestic source profiles from literature and field measurements, and then established a most up-to-date dataset of VOCs source profiles in China by integrating 363 selective VOCs profiles into 101 sector-based source profiles. The profile dataset covers eight major source categories and contains 447 VOCs species including non-methane hydrocarbons (NMHCs) species and oxygenated VOCs (OVOCs) species. The results shown that (1) VOCs composition characteristics exhibit variations for most Level-II source sectors and Level-III sub-sectors even under the same Level-I source category; (2) OVOCs, which were significantly missing in previous profiles, account for more than 95% in cooking and 20- 40% in non-road mobile, biomass burning and solvent use sources; (3) aromatics account for 20%-40% in most emission sources except cooking source, alkenes and alkynes account for ~20% in combustion sources (stationary combustion, mobile source and biomass burning), alkanes are abundant in gasoline-related emission sources(on-road mobile source and fuel oil storage and transportation); (4) missing OVOCs species could bring 30%-50% to ozone formation potentials in most emission sources; and (5) there are considerable differences in VOCs chemical groups and individual species for most emission sources between this dataset and the widely used U.S. SPECIATE database, indicating the importance of developing domestic VOCs source profiles. The dataset developed in this study can help support reactive VOCs species-based ozone control strategy and provide domestic profile data for source apportionment and air quality modeling in China and other countries or regions with similar emission source characteristics.

An accurate characterization of spatial-temporal emission patterns and speciation of volatile organic compounds (VOCs) for multiple chemical mechanisms is important to improving the air quality ensemble modeling. In this study, we developed a 2017-based high-resolution (3 km × 3 km) model-ready emission inventory for Guangdong Province (GD) by updating estimation methods, emission factors, activity data, and allocation profiles. In particular, a full-localized speciation profile dataset mapped to five chemical mechanisms was developed to promote the determination of VOC speciation, and two dynamic approaches based on big data were used to improve the estimation of ship emissions and open fire biomass burning (OFBB). Compared with previous emissions, more VOC emissions were classified as oxygenated volatile organic compound (OVOC) species, and their contributions to the total ozone formation potential (OFP) in the Pearl River Delta (PRD) region increased by 17%. Formaldehyde became the largest OFP species in GD, accounting for 11.6% of the total OFP, indicating that the model-ready emission inventory developed in this study is more reactive. The high spatial-temporal variability of ship sources and OFBB, which were previously underestimated, was also captured by using big data. Ship emissions during typhoon days and holidays decreased by 23–55%. 95% of OFBB emissions were concentrated in 9% of the GD area and 31% of the days in 2017, demonstrating their strong spatial-temporal variability. In addition, this study revealed that GD emissions have changed rapidly in recent years due to the leap-forward control measures implemented, and thus, they needed to be updated regularly. All of these updates led to a 5–17% decrease in the emission uncertainty for most pollutants. The results of this study provide a reference for how to reduce uncertainties in developing model-ready emission inventories.

Driving cycles are important parameters to estimate vehicle emissions. However, most previous driving cycles, which were developed at the city scale or even national scale, cannot resolve the emission variations affected by road types and thus might introduce large uncertainties in the emission estimation. In this study, we proposed a new approach based on road type-based (RT-based) driving cycles to improve the estimation of vehicle emissions. As a case study, RT-based driving cycles for passenger cars were developed using more than 600,000 s of GPS data collected through on-road tests in Guangzhou. Results showed that driving cycles varied across road types (urban arterial road, highway, and other urban road), which featured varied velocities, acceleration, deceleration, and driving mode percentages. The urban arterial road had the lowest velocity (18.7 km/h), but the largest creeping mode proportion (61%). The other urban road had the largest acceleration and deceleration, while the highway had the highest average velocity (43.2 km/h) but the lowest acceleration and deceleration. Evaluations revealed that RT-based driving cycles could accurately depict separate driving patterns and emission factors on different road types. In comparison, city-level driving cycles and standard driving cycles typically overestimated emission factors of highways but underestimated those of other road types in Guangzhou. Consequently, emissions of light-duty gasoline passenger cars could be underestimated by 33% in the downtown and overestimated by approximately 25% in and around the highways. This study highlights the development of RT-based driving cycles to accurately estimate vehicle emissions and characterize their spatial variations.

The influence of ATP and Bax on the rate of early apoptosis of E. tenella host cells by flow cytometry. (DOCX 14Â kb)

E. tenella infection rates. + P

The influence of ATP and Bax on MPTP opening of E. tenella host cells by flow cytometry. *P

The influence of ATP and Bax on the late apoptosis, and necrosis of E. tenella host cells by Hoechst-Annexin V/PI-based apoptosis detection. (DOCX 14Â kb)

The influence of ATP and Bax on the late apoptosis, and necrosis of E. tenella host cells by flow cytometry. (DOCX 14Â kb)

The influence of ATP and Bax on the rate of early apoptosis of E. tenella host cells by Hoechst-Annexin V/PI-based apoptosis detection. (DOCX 14Â kb)