Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics.

Multilevel proteomics aims to delineate proteins at the peptide (bottom-up proteomics), proteoform (top-down proteomics), and protein complex (native proteomics) levels. Capillary electrophoresis-mass spectrometry (CE-MS) can achieve highly efficient separation and highly sensitive detection of complex mixtures of peptides, proteoforms, and even protein complexes because of its substantial technical progress. CE-MS has become a valuable alternative to the routinely used liquid chromatography-mass spectrometry for multilevel proteomics. This review summarizes the most recent (2019-2021) advances of CE-MS for multilevel proteomics regarding technological progress and biological applications. We also provide brief perspectives on CE-MS for multilevel proteomics at the end, highlighting some future directions and potential challenges.

Comprehensive review of emerging contaminants: Detection technologies, environmental impact, and management strategies.

Emerging contaminants (ECs) are a diverse group of unregulated pollutants increasingly present in the environment. These contaminants, including pharmaceuticals, personal care products, endocrine disruptors, and industrial chemicals, can enter the environment through various pathways and persist, accumulating in the food chain and posing risks to ecosystems and human health. This comprehensive review examines the chemical characteristics, sources, and varieties of ECs. It critically evaluates the current understanding of their environmental and health impacts, highlighting recent advancements and challenges in detection and analysis. The review also assesses existing regulations and policies, identifying shortcomings and proposing potential enhancements. ECs pose significant risks to wildlife and ecosystems by disrupting animal hormones, causing genetic alterations that diminish diversity and resilience, and altering soil nutrient dynamics and the physical environment. Furthermore, ECs present increasing risks to human health, including hormonal disruptions, antibiotic resistance, endocrine disruption, neurological effects, carcinogenic effects, and other long-term impacts. To address these critical issues, the review offers recommendations for future research, emphasizing areas requiring further investigation to comprehend the full implications of these contaminants. It also suggests increased funding and support for research, development of advanced detection technologies, establishment of standardized methods, adoption of precautionary regulations, enhanced public awareness and education, cross-sectoral collaboration, and integration of scientific research into policy-making. By implementing these solutions, we can improve our ability to detect, monitor, and manage ECs, reducing environmental and public health risks.

HPLC and LC-MS/MS-Based Quantitative Characterization of Related Substances Associated with Sotalol Hydrochloride.

In total, three related substances (RS) associated with sotalol hydrochloride (STHCl) were herein identified with a novel gradient high-performance liquid chromatography (HPLC) protocol. Further characterization of these substances was then performed via liquid chromatography-mass spectroscopy (LC-MS/MS) and nuclear magnetic resonance (NMR) approaches. For these analyses, commercial STHCl samples were used for quantitative HPLC studies and the degradation of STHCl under acidic (1M HCl), alkaline (1M NaOH), oxidative (30% H2O2), photolytic (4500 Lx), and thermal stress conditions (100 °C) was assessed. This approach revealed this drug to be resistant to acidic, alkaline, and high-temperature conditions, whereas it was susceptible to light and oxidation as confirmed through long-term experiments. The putative mechanisms governing RS formation were also explored, revealing that RS3 was derived from the manufacturing process, whereas RS2 was generated via oxidation and RS1 was generated in response to light exposure. The cytotoxicity of these RS compounds was then assessed using MTT assays and acute toxicity test. Overall, this study provides details regarding the characterization, isolation, quantification, and toxicological evaluation of STHCl and associated RS compounds together with details regarding the precise, specific, and reliable novel HPLC technique, thus providing the requisite information necessary to ensure STHCl purity and safety.

Artificial intelligence-assisted determination of available sites for palatal orthodontic mini implants based on palatal thickness through CBCT.

OBJECTIVES: To develop an artificial intelligence (AI) system for automatic palate segmentation through CBCT, and to determine the personalized available sites for palatal mini implants by measuring palatal bone and soft tissue thickness according to the AI-predicted results. MATERIALS AND METHODS: Eight thousand four hundred target slices (from 70 CBCT scans) from orthodontic patients were collected, labelled by well-trained orthodontists and randomly divided into two groups: a training set and a test set. After the deep learning process, we evaluated the performance of our deep learning model with the mean Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), sensitivity (SEN), positive predictive value (PPV) and mean thickness percentage error (MTPE). The pixel traversal method was proposed to measure the thickness of palatal bone and soft tissue, and to predict available sites for palatal orthodontic mini implants. Then, an example of available sites for palatal mini implants from the test set was mapped. RESULTS: The average DSC, ASSD, SEN, PPV and MTPE for the segmented palatal bone tissue were 0.831%, 1.122%, 0.876%, 0.815% and 6.70%, while that for the palatal soft tissue were 0.741%, 1.091%, 0.861%, 0.695% and 12.2%, respectively. Besides, an example of available sites for palatal mini implants was mapped according to predefined criteria. CONCLUSIONS: Our AI system showed high accuracy for palatal segmentation and thickness measurement, which is helpful for the determination of available sites and the design of a surgical guide for palatal orthodontic mini implants.

Red Tide Detection Method Based on Improved U-Net Model-Taking GOCI Data in East China Sea as an Example.

In the coastal areas of China, the eutrophication of seawater leads to the continuous occurrence of red tide, which has caused great damage to Marine fisheries and aquatic resources. Therefore, the detection and prediction of red tide have important research significance. The rapid development of optical remote sensing technology and deep-learning technology provides technical means for realizing large-scale and high-precision red tide detection. However, the difficulty of the accurate detection of red tide edges with complex boundaries limits the further improvement of red tide detection accuracy. In view of the above problems, this paper takes GOCI data in the East China Sea as an example and proposes an improved U-Net red tide detection method. In the improved U-Net method, NDVI was introduced to enhance the characteristic information of the red tide to improve the separability between the red tide and seawater. At the same time, the ECA channel attention mechanism was introduced to give different weights according to the influence of different bands on red tide detection, and the spectral characteristics of different channels were fully mined to further extract red tide characteristics. A shallow feature extraction module based on Atrous Spatial Pyramid Convolution (ASPC) was designed to improve the U-Net model. The red tide feature information in a multi-scale context was fused under multiple sampling rates to enhance the model's ability to extract features at different scales. The problem of limited accuracy improvement in red tide edge detection with complex boundaries is solved via the fusion of deep and shallow features and multi-scale spatial features. Compared with other methods, the method proposed in this paper achieves better results and can detect red tide edges with complex boundaries, and the accuracy, precision, recall, and F1-score are 95.90%, 97.15%, 91.53%, and 0.94, respectively. In addition, the red tide detection experiments in other regions with relatively concentrated distribution also prove that the method has good applicability.

Interaction and Metabolic Function of Microbiota during the Washed Processing of Coffea arabica.

Coffee fermentation is crucial for flavor and aroma, as microorganisms degrade mucilage and produce metabolites. This study aimed to provide a basis for understanding the impact of microorganisms on Coffea arabica from Yunnan, China, during washed processing. The microbial community structure and differentially changed metabolites (DCMs) of C. arabica beans during washed processing were analyzed. The results indicated that the top five predominant microorganisms at the genera level were Achromobacter, Tatumella, Weissella, Streptococcus, and Trichocoleus for bacteria and Cystofilobasidium, Hanseniaspora, Lachancea, Wickerhamomyces, and Aspergillus for fungi. Meanwhile, the relative content of 115 DCMs in 36 h samples decreased significantly, compared to non-fermentation coffee samples (VIP > 1, p < 0.05, FC < 0.65), and the relative content of 28 DCMs increased significantly (VIP > 1, p < 0.05, FC > 1.5). Furthermore, 17 DCMs showed a strong positive correlation with microorganisms, and 5 DCMs had a strong negative correlation (p < 0.05, |r| > 0.6). Therefore, the interaction and metabolic function of microbiota play a key role in the formation of coffee flavor, and these results help in clarifying the fermentation mechanisms of C. arabica and in controlling and improving the quality of coffee flavor.

Steroidal Alkaloids from the Roots of Veratrum mengtzeanum Loes. with Their Anti-Inflammatory Activities.

The phytochemical investigation of Veratrum mengtzeanum Loes. roots resulted in the isolation and characterization of two novel, namely Mengtzeanines A (1), Mengtzeanines B (2), and eight known steroidal alkaloids (3-10). Their structural properties were assessed though extensive spectroscopic techniques. All constituents 1-10 were analyzed for suppression of NO formation in LPS-induced RAW264.7 macrophages. Among them, constituent 6 (Verazine) showed inhibition against LPS-induced NO production (IC50 = 20.41 µM). Additionally, compound 6 could inhibit the secretion of IL1ß, IL6, and TNFα, and downregulate the productions of iNOS and COX2 in LPS-induced RAW264.7 macrophages. Further experiments revealed that 6 exhibited a potent anti-inflammatory level in LPS-stimulated RAW264.7 macrophages via inhibiting NF-κB, and triggering of Keap1/Nrf2/HO-1 axis, implying that compound 6 may be a promising candidate for treating inflammatory disorders.

Atmospheric Particle Hygroscopicity and the Influence by Oxidation State of Organic Aerosols in Urban Beijing.

A hygroscopic tandem differential mobility analyser (H-TDMA) was used to observe the size-resolved hygroscopic characteristics of submicron particles in January and April 2018 in urban Beijing. The probability distribution of the hygroscopic growth factor (HGF-PDF) in winter and spring usually showed a bimodal pattern, with more hygroscopic mode (MH) being more dominant. The seasonal variation in particle hygroscopicity was related to the origin of air mass, which received polluted southerly air masses in spring and clean northwesterly air masses in winter. Particles showed stronger hygroscopic behaviour during heavy pollution episodes (HPEs) with elevated concentrations of secondary aerosols, especially higher mass fraction of nitrate, which were indicated using the PM2.5 (particulate matter with diameter below 2.5 µm) mass concentration normalised by CO mass concentration. The hygroscopic parameter (κ) values were calculated using H-TDMA (κhtdma) and chemical composition (κchem). The closure study showed that κchem was overestimated in winter afternoon when compared with κhtdma, because the organic particle hygroscopic parameter (κorg) was overestimated in the calculations. It was influenced by the presence of a high concentration of hydrocarbon-like organic aerosol (HOA) with a weak water uptake ability. A positive relationship was observed between κorg and the ratio of oxygenated organic aerosol (OOA) and HOA, thereby indicating that the strong oxidation state enhanced the hygroscopicity of the particles. This study revealed the effect of local emission sources and secondary aerosol formation processes on particle hygroscopicity, which is of great significance for understanding the pollution formation mechanism in the North China Plain.

Molecular characterization of an LRR-only protein gene in Pacific white shrimp Litopenaeus vannamei: Sequence feature, expression pattern, and protein activity.

Leucine-rich repeat (LRR)-only proteins have been proved to be involved in the innate immune responses as they could mediate protein-protein or protein-ligand interactions. In the present study, a novel LRR-only protein (LvLRRop-1) was identified and characterized from Pacific white shrimp Litopenaeus vannamei. The complete cDNA sequence of LvLRRop-1 contains an open reading frame (ORF) of 1488 bp, which encoded a polypeptide of 495 amino acids with a predicted molecular mass of 55.67 kDa and a calculated theoretical isoelectric point of 6.435. There are five LRR motifs, six LRR_TYP motifs in the protein sequence of LvLRRop-1 with consensus signature sequences of LxxLxxLxLxxNxL. The LvLRRop-1 mRNA transcripts could be detected in all the tested tissues, including eyestalk, gill, gonad, heart, hemocytes, hepatopancreas, intestine, muscle, nerve and stomach, especially highest in hemocytes and hepatopancreas. The mRNA transcripts of LvLRRop-1 increased within the first 6 h in hemocytes and hepatopancreas after Vibrio parahaemolyticus or white spot syndrome virus (WSSV) challenges. The recombinant LvLRRop-1 could bind four typical pathogen-associated molecular patterns (PAMPs), including lipopolysaccharide (LPS), peptidoglycan (PGN), glucan (GLU) and polycytidine-polycytidylic acid (poly IC), in a dose-dependent manner, and inhibit the growth of bacteria Micrococcus luteus. These data indicated that LvLRRop-1 could play a pivotal role in the innate immune response of shrimps as a kind of pattern recognition receptor (PRR).

On the fossil and non-fossil fuel sources of carbonaceous aerosol with radiocarbon and AMS-PMF methods during winter hazy days in a rural area of North China plain.

Regional transport is a key source of carbonaceous aerosol in many Chinese megacities including Beijing. The sources of carbonaceous aerosol in urban areas have been studied extensively but are poorly known in upwind rural areas. This work aims to quantify the contributions of fossil and non-fossil fuel emissions to carbonaceous aerosols at a rural site in North China Plain in winter 2016. We integrated online high resolution-time of flight-aerosol mass spectrometer (HR-TOF-AMS) observations and radiocarbon (14C) measurements of fine particles with Positive Matrix Factorization (PMF) analysis as well as Extended Gelencsér (EG) method. We found that fine particle concentration is much higher at the rural site than in Beijing during the campaign (Dec 7, 2016 to Jan 8, 2017). PMF analysis of the AMS data showed that coal-combustion related organic aerosol (CCOA + Oxidized CCOA) and more oxidized oxygenated organic aerosol (MO-OOA) contributed 48% and 30% of organic matter to non-refractory PM1 (NR-PM1) mass. About 2/3 of the OC and EC were from fossil-fuel combustion. The EG method, combining AMS-PMF and 14C data, showed that primary and secondary OC from fossil fuel contribute 35% and 22% to total carbon (TC), coal combustion emission dominates the fossil fuel sources, and biomass burning accounted for 21% of carbonaceous aerosol. In summary, our results confirm that fossil fuel combustion was the dominant source of carbonaceous aerosol during heavy pollution events in the rural areas. Significant emissions of solid fuel carbonaceous aerosols at rural areas can affect air quality in downwind cities such as Beijing and Tianjin, highlighting the benefits of energy transition from solid fuels to cleaner energy in rural areas.

Effect of epicatechin on inflammatory cytokines and MAPK/NF-κB signaling pathway in lipopolysaccharideinduced acute lung injury of BALB/c mice.

This study evaluated the anti-inflammatory effect of epicatechin (EC) on acute lung injury (ALI) induced by lipopolysaccharide (LPS) of tracheal installation in BALB/c mice. It was observed that EC could alleviate not only the histopathological changes but also decrease the wet/dry weight (W/D) ratio of lung tissues. It also suppressed the release of IL-1ß, IL-6, and TNF-α in serum, bronchoalveolar lavage fluid (BALF), and lung tissues, respectively. A quantitative realtime PCR-based study further indicated that EC also inhibited the levels of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) mRNA in lung tissues. In addition, the Western blot report suggested that EC was closely involved in the inhibition of phosphorylation of ERK, JNK, p38, p65, and IκB in mitogen-activated protein kinases (MAPK) and nuclear factor-κB (NF-κB) signaling pathway. These results provide an experimental and theoretical basis for treating pulmonary inflammation by EC.

Capillary Zone Electrophoresis-Tandem Mass Spectrometry As an Alternative to Liquid Chromatography-Tandem Mass Spectrometry for Top-down Proteomics of Histones.

Top-down proteomics (TDP) is an ideal approach for deciphering the histone code and it routinely employs reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS). Because of the extreme complexity of histones regarding the number of proteoforms, new analytical tools with high-capacity separation and highly sensitive detection of proteoforms are required for TDP of histones. Here we present capillary zone electrophoresis (CZE)-MS/MS via the electro-kinetically pumped sheath-flow CE-MS interface for large-scale top-down delineation of histone proteoforms. CZE-MS/MS identified a comparable number of proteoforms to RPLC-MS/MS from a calf histone sample with more than 30-fold less sample consumption (75-ng vs. Three µg), indicating its substantially higher sensitivity. We identified about 400 histone proteoforms from the calf histone sample using two-dimensional size-exclusion chromatography (SEC)-CZE-MS/MS with less than 300-ng proteins consumed. We identified histone proteoforms carrying various tentative post-translational modifications (PTMs), for example, acetylation, methylation (mono-, di-, and tri-), phosphorylation, and succinylation. The electrophoretic mobility (µef) of unmodified histone proteoforms can be predicted accurately (R2 = 0.98) with an optimized semiempirical model based on our recent work. The results render CZE-MS/MS as a useful tool for deciphering the histone code in a proteoform-specific manner and on a global scale.

Investigating native capillary zone electrophoresis-mass spectrometry on a high-end quadrupole-time-of-flight mass spectrometer for the characterization of monoclonal antibodies.

Native capillary zone electrophoresis-mass spectrometry (CZE-MS) has attracted attentions for the characterization of monoclonal antibodies (mAbs) due to the potential of CZE for highly efficient separations of mAbs under native conditions as well as its compatibility with native electrospray ionization (ESI)-MS. However, the low sample loading capacity and limited separation resolution of native CZE for large proteins and protein complexes (e.g. mAbs) impede the widespread adoption of native CZE-MS. Here, we present a novel native capillary isoelectric focusing (cIEF)-assisted CZE-MS method for the characterization of mAbs with much larger sample loading capacity and significantly better separation resolution than native CZE-MS alone. The native cIEF-assisted CZE-MS employed separation capillaries with a new carbohydrate-based neutral coating, a commercilized electrokinetically pumped sheathflow CE-MS interface, and a high-end quadrupole-time-of-flight (Q-TOF) mass spectrometer. Using the method, we documented the separations of different proteoforms of the SigmaMAb and the detection of its various glyco-proteoforms and homodimer. The native cIEF-assisted CZE-MS separated the NIST mAb into three peaks with a submicroliter sample loading volume, corresponding to its different proteoforms. We observed that both the NIST mAb and its homodimer had eight glyco-proteoforms, four of which had low abundance. The results demonstrate the potential of our native cIEF-assisted CZE-MS method for advancing the characterization of large proteins and protein complexes under native conditions.

Synthesis, antitumor activity, and molecular docking of (-)-epigallocatechin-3-gallate-4ß-triazolopodophyllotoxin conjugates.

Two new (-)-epigallocatechin-3-gallate-4ß-triazolopodophyllotoxin conjugates (7 and 8) were synthesized and evaluated for biological activity. Compound 8 showed highly potent anticancer activity against A-549 cell line with IC50 of 2.16 ± 1.02 µM, which displayed the highest selectivity index value (SI = 14.5) in A-549 cells. Molecular docking indicated that compound 8 could bind with the active site of Top-II. Therefore, compound 8 might be a promising candidate for further development.

Novel Perbutyrylated Glucose Derivatives of (-)-Epigallocatechin-3-Gallate Inhibit Cancer Cells Proliferation by Decreasing Phosphorylation of the EGFR: Synthesis, Cytotoxicity, and Molecular Docking.

Lung cancer is one of the most commonly occurring cancer mortality worldwide. The epidermal growth factor receptor (EGFR) plays an important role in cellular functions and has become the new promising target. Natural products and their derivatives with various structures, unique biological activities, and specific selectivity have served as lead compounds for EGFR. D-glucose and EGCG were used as starting materials. A series of glucoside derivatives of EGCG (7-12) were synthesized and evaluated for their in vitro anticancer activity against five human cancer cell lines, including HL-60, SMMC-7721, A-549, MCF-7, and SW480. In addition, we investigated the structure-activity relationship and physicochemical property-activity relationship of EGCG derivatives. Compounds 11 and 12 showed better growth inhibition than others in four cancer cell lines (HL-60, SMMC-7721, A-549, and MCF), with IC50 values in the range of 22.90-37.87 µM. Compounds 11 and 12 decreased phosphorylation of EGFR and downstream signaling protein, which also have more hydrophobic interactions than EGCG by docking study. The most active compounds 11 and 12, both having perbutyrylated glucose residue, we found that perbutyrylation of the glucose residue leads to increased cytotoxic activity and suggested that their potential as anticancer agents for further development.

Non-symbolic and symbolic number lines are dissociated.

People use mental number lines for both symbolic numerals and numerosity, but little is known about how these two mental number lines are related. The current study investigated the association in effect size, directionality of the mental number line, and development between symbolic and non-symbolic mental number lines to determine if they were related to or independent from each other. We collected data from numerosity- and digit-matching tasks that used the following numbers: 11, 14, 17, 20, 23, 26, and 29. Tasks were performed by college undergraduates and the fifth-grade primary school students. The results showed that none of the effects for non-symbolic numbers was related to any of the effects for symbolic numbers, and vice versa, in both adults and children. Another notable finding was that the correlation between the SNARC (spatial-numerical association of response code) effect size and mathematical ability was negative in the adult group. These results are consistent with the dissociated processes hypothesis and suggest that mental number lines are notation-dependent. As shown by the SNARC effect, the mental number line might result in interference in the current task by an automatically activated spatial notation-dependent representation of numbers.

Toward a Universal Sample Preparation Method for Denaturing Top-Down Proteomics of Complex Proteomes.

A universal and standardized sample preparation method becomes vital for denaturing top-down proteomics (dTDP) to advance the scale and accuracy of proteoform delineation in complex biological systems. It needs to have high protein recovery, minimum bias, good reproducibility, and compatibility with downstream mass spectrometry (MS) analysis. Here, we employed a lysis buffer containing sodium dodecyl sulfate for extracting proteoforms from cells and, for the first time, compared membrane ultrafiltration (MU), chloroform-methanol precipitation (CMP), and single-spot solid-phase sample preparation using magnetic beads (SP3) for proteoform cleanup for dTDP. The MU method outperformed CMP and SP3 methods, resulting in high and reproducible protein recovery from both Escherichia coli cell (59 ± 3%) and human HepG2 cell (86 ± 5%) samples without a significant bias. Single-shot capillary zone electrophoresis (CZE)-MS/MS analyses of the prepared E. coli and HepG2 cell samples using the MU method identified 821 and 516 proteoforms, respectively. Nearly 30 and 50% of the identified E. coli and HepG2 proteins are membrane proteins. CZE-MS/MS identified 94 histone proteoforms from the HepG2 sample with various post-translational modifications, including acetylation, methylation, and phosphorylation. Our results suggest that combining the SDS-based protein extraction and the MU-based protein cleanup could be a universal sample preparation method for dTDP. The MS raw data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD018248.

Automated Capillary Isoelectric Focusing-Tandem Mass Spectrometry for Qualitative and Quantitative Top-Down Proteomics.

Top-down proteomics (TDP) aims to delineate proteomes in a proteoform-specific manner, which is vital for accurately understanding protein function in cellular processes. It requires high-capacity separation of proteoforms before mass spectrometry (MS) and tandem MS (MS/MS). Capillary isoelectric focusing (cIEF)-MS has been recognized as a useful tool for TDP in the 1990s because cIEF is capable of high-resolution separation of proteoforms. Previous cIEF-MS studies concentrated on measuring the protein's mass without MS/MS, impeding the confident proteoform identification in complex samples and the accurate localization of post-translational modifications on proteoforms. Herein, for the first time, we present automated cIEF-MS/MS-based TDP for large-scale delineation of proteoforms in complex proteomes. Single-shot cIEF-MS/MS identified 711 proteoforms from an Escherichia coli (E. coli) proteome consuming only nanograms of proteins. Coupling two-dimensional size-exclusion chromatography (SEC)-cIEF to ESI-MS/MS enabled the identification of nearly 2000 proteoforms from the E. coli proteome. Label-free quantitative TDP of zebrafish male and female brains using SEC-cIEF-MS/MS quantified thousands of proteoforms and revealed sex-dependent proteoform profiles in brains. Particularly, we discovered several proteolytic proteoforms of pro-opiomelanocortin and prodynorphin with significantly higher abundance in male zebrafish brains as potential endogenous hormone proteoforms. Multilevel quantitative proteomics (TDP and bottom-up proteomics) of the brains revealed that the majority of proteoforms having statistically significant difference in abundance between genders showed no abundance difference at the protein group level. This work represents the first multilevel quantitative proteomics study of sexual dimorphism of the brain.

Predicting Electrophoretic Mobility of Proteoforms for Large-Scale Top-Down Proteomics.

Large-scale top-down proteomics characterizes proteoforms in cells globally with high confidence and high throughput using reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) or capillary zone electrophoresis (CZE)-MS/MS. The false discovery rate (FDR) from the target-decoy database search is typically deployed to filter identified proteoforms to ensure high-confidence identifications (IDs). It has been demonstrated that the FDRs in top-down proteomics can be drastically underestimated. An alternative approach to the FDR can be useful for further evaluating the confidence of proteoform IDs after the database search. We argue that predicting retention/migration time of proteoforms from the RPLC/CZE separation accurately and comparing their predicted and experimental separation time could be a useful and practical approach. Based on our knowledge, there is still no report in the literature about predicting separation time of proteoforms using large top-down proteomics data sets. In this pilot study, for the first time, we evaluated various semiempirical models for predicting proteoforms' electrophoretic mobility (µef) using large-scale top-down proteomics data sets from CZE-MS/MS. We achieved a linear correlation between experimental and predicted µef of E. coli proteoforms (R2 = 0.98) with a simple semiempirical model, which utilizes the number of charges and molecular mass of each proteoform as the parameters. Our modeling data suggest that the complete unfolding of proteoforms during CZE separation benefits the prediction of their µef. Our results also indicate that N-terminal acetylation and phosphorylation both decrease the proteoforms' charge by roughly one charge unit.

Significant Changes in Chemistry of Fine Particles in Wintertime Beijing from 2007 to 2017: Impact of Clean Air Actions.

The Beijing government implemented a number of clean air action plans to improve air quality in the last 10 years, which contributed to changes in the concentration of fine particles and their compositions. However, quantifying the impacts of these interventions is challenging as meteorology masks the real changes in observed concentrations. Here, we applied a machine learning technique to decouple the effect of meteorology and evaluate the changes in the chemistry of nonrefractory PM1 (particulate matter less than 1 µm) in winter 2007, 2016, and 2017 as a result of the clean air actions. The observed mass concentrations of PM1 were 74.6, 90.2, and 36.1 µg m-3 in the three winters, while the deweathered concentrations were 74.2, 78.7, and 46.3 µg m-3, respectively. The deweathered concentrations of PM1, organics, sulfate, ammonium, chloride, SO2, NO2, and CO decreased by -38, -46, -59, -24, -51, -89, -16, and -52% in 2017 in comparison to 2007. On the contrary, the deweathered concentration of nitrates increased by 4%. Our results indicate that the clean air actions implemented in 2017 were highly effective in reducing ambient concentrations of SO2, CO, and PM1 organics, sulfate, ammonium, and chloride, but the control of nitrate and PM1 organics remains a major challenge.