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Background The ALVAC/gp120 + MF59 vaccines in the HIV Vaccine Trials Network (HVTN) 702 efficacy trial did not prevent human immunodeficiency virus-1 (HIV-1) acquisition. Vaccine-matched immunological endpoints that were correlates of HIV-1 acquisition risk in RV144 were measured in HVTN 702 and evaluated as correlates of HIV-1 acquisition. Methods Among 1893 HVTN 702 female vaccinees, 60 HIV-1–seropositive cases and 60 matched seronegative noncases were sampled. HIV-specific CD4+ T-cell and binding antibody responses were measured 2 weeks after fourth and fifth immunizations. Cox proportional hazards models assessed prespecified responses as predictors of HIV-1 acquisition. Results The HVTN 702 Env-specific CD4+ T-cell response rate was significantly higher than in RV144 (63% vs 40%, P = .03) with significantly lower IgG binding antibody response rate and magnitude to 1086.C V1V2 (67% vs 100%, P Conclusions HVTN 702 and RV144 had distinct immunogenicity profiles. However, both identified significant correlations (univariate or interaction) for IgG V1V2 and polyfunctional CD4+ T cells with HIV-1 acquisition. Clinical Trials Registration . NCT02968849.

Despite substantial observational and experimental evidence that aspirin use can provide protection against the development of colorectal neoplasia, our understanding of the molecular mechanisms involved is inadequate and limits our ability to use this drug effectively and safely for chemoprevention. We employed an untargeted plasma metabolomics approach using liquid chromatography with high-resolution mass spectroscopy to explore novel metabolites that may contribute to the chemopreventive effects of aspirin. Associations between levels of metabolic features in plasma and aspirin treatment were investigated among 523 participants in a randomized placebo-controlled clinical trial of two doses of aspirin (81 or 325 mg/day) and were linked to risk of colorectal adenoma occurrence over 3 years of follow-up. Metabolic pathways that were altered with aspirin treatment included linoleate and glycerophospholipid metabolism for the 81-mg dose and carnitine shuttle for both doses. Metabolites whose levels increased with 81 mg/day aspirin treatment and were also associated with decreased risk of adenomas during follow-up included certain forms of lysophosphatidylcholine and lysophosphatidylethanolamine as well as trihydroxyoctadecenoic acid, which is a derivative of linoleic acid and is upstream of cyclooxygenase inhibition by aspirin in the linoleate and arachidonic acid metabolism pathways. In conclusion, our findings regarding lysophospholipids and metabolites in the linoleate metabolism pathway may provide novel insights into the chemopreventive effects of aspirin in the colorectum, although they should be considered hypothesis-generating at this time. Prevention Relevance: This research used metabolomics, an innovative discovery-based approach, to identify molecular changes in human blood that may help to explain how aspirin use reduces the risk of colorectal neoplasia in some individuals. Ultimately, this work could have important implications for optimizing aspirin use in the prevention of colorectal cancer.

Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top–down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top–down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.

Supplementary Table from Plasma Metabolomics Analysis of Aspirin Treatment and Risk of Colorectal Adenomas

Supplementary Figure from Plasma Metabolomics Analysis of Aspirin Treatment and Risk of Colorectal Adenomas

In this paper, a type of tracking controller on the basis of parameters optimization was proposed for unmanned surface vehicles (USVs). Taking into account the unique nonlinear and large inertia characteristics of USVs, an iterative sliding mode control (ISMC) was adopted to construct the controller including the USVs’ main engine speed controller to determine the longitudinal velocity and the steering controller to control the lateral displacement. In designing, the hyperbolic tangent function with the saturation characteristic is introduced to design the output feedback control law of nonlinear iterative sliding mode. Then, the differential evolution algorithm (DEA) is applied to construct the parameters optimization system for acquiring the optimal parameters of the proposed controller, and the control quality with adaptive ability and robustness of the optimized controller is achieved. It is verified by computer experiments that the optimized controller realizes the tracking control for USV under interference; meanwhile, compared with the iterative sliding mode controller, the control performance of the controller is better and the robustness of that is stronger.

Recent studies have indicated that it is possible to protect individuals from HIV infection using passive infusion of monoclonal antibodies. However, in order for monoclonal antibodies to confer robust protection, the antibodies must be capable of neutralizing many possible strains of the virus. This is particularly challenging in the context of a highly diverse pathogen like HIV. It is therefore of great interest to leverage existing observational data sources to discover antibodies that are able to neutralize HIV viruses via residues where existing antibodies show modest protection. Such information feeds directly into the clinical trial pipeline for monoclonal antibody therapies by providing information on (i) whether and to what extent combinations of antibodies can generate superior protection and (ii) strategies for analyzing past clinical trials to identify in vivo evidence of antibody resistance. These observational data include genetic features of many diverse HIV genetic sequences, as well as in vitro measures of antibody resistance. The statistical learning problem we are interested in is developing statistical methodology that can be used to analyze these data to identify important genetic features that are significantly associated with antibody resistance. This is a challenging problem owing to the high-dimensional and strongly correlated nature of the genetic sequence data. To overcome these challenges, we propose an outcome-adaptive, collaborative targeted minimum loss-based estimation approach using random forests. We demonstrate via simulation that the approach enjoys important statistical benefits over existing approaches in terms of bias, mean squared error, and type I error. We apply the approach to the Compile, Analyze, and Tally Nab Panels database to identify AA positions that are potentially causally related to resistance to neutralization by several different antibodies.

Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we reproducibly detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high mass accuracy to enable the classification of individual fiber types. This study represents the first “single-cell” top-down proteomics analysis that captures single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.Significance StatementSingle-cell technologies are revolutionizing biology and molecular medicine by allowing direct investigation of the biological variability among individual cells. Top-down proteomics is uniquely capable of dissecting biological heterogeneity at the intact protein level. Herein, we develop a highly sensitive single-cell top-down proteomics method to reveal diverse molecular variations in large proteins (>200 kDa) among individual single muscle cells. Our results both reveal and characterize the differences in protein post-translational modifications and isoform expression possible between individual muscle cells. We further integrate functional properties with proteomics and accurately measure myosin isoforms for individual muscle fiber type classification. Our study highlights the potential of top-down proteomics for understanding how single-cell protein heterogeneity contributes to cellular functions.

With the development of interregional trade, a potential disaster that happens in one place could cause enormous economic losses in distant areas. Timely and comprehensive post-disaster assessments play a significant role in guiding disaster recovery, and for reconstruction and planning for future disaster risk reduction. In this study, we evaluate the post-disaster economic impacts due to Sichuan earthquake in 2008 and its regional and industrial spillover effects based on a Chinese multi-regional input–output table. The results show that the 2008 Sichuan earthquake caused around 1725 billion US dollars of value-added losses and 69.9 million people of employment losses. The Chemical industry in Guangdong and Zhejiang suffered severe value-added losses due to indirect effects through supply chains. Furthermore, public administration in Henan, Sichuan, and Guangdong suffered large employment losses. In general, we find that the economically less developed provinces are more susceptible to larger losses compared to the economically developed provinces. The results in this study can provide information for decision-makers to devise effective solutions on how to release relief funds and for dividing adaptation plans to avoid serious economic losses due to future disasters.

Desertification threatens food security and human nutrition through its impacts on agricultural productivity. The damage caused by desertification includes both direct, on-site impacts and wide-ranging indirect, off-site effects. In this study, we applied a multi-region input-output framework to estimate the direct and indirect consequences of desertification in China, and associated impacts on macronutrient intake. We found that desertification causes macronutrient loss and significant losses in employment, income, and value added throughout upstream supply chains. Our results indicate that desertification affected around 2.1 million jobs, resulted in income loss of about US$ 17.3 billion, and a loss in value added of about US$ 28.6 billion in year 2017. In terms of sub-national regions within China, macronutrient losses are highest in Inner Mongolia, with the population facing a 24% reduction in energy, 21% reduction in protein, 33% reduction in fat, and 26% in carbohydrates. The findings of our study suggest the importance of combating desertification, which is also indicated as a priority in the Sustainable Development Goal (SDG) 15 of the United Nations 2030 Agenda.

In video super-resolution, exploiting spatial information of reference frame and temporal information from neighbouring frames is significant but challenging. Since existing image super-resolution (SR) methods have achieved remarkable reconstruction results, in this paper, we propose a generic frame-wise dynamic fusion module (DFM) to fully aggregate temporal information into reference frame. Specifically, we employ dynamic convolution to flexibly fuse element-wise temporal information frame by frame. Before that, to handle large motion across frames, we propose a self-calibrated deformable (SCD) alignment module, in which motion offsets are predicted via self-calibrated convolution that explicitly expand receptive field of each convolutional layer through internal communications in a multi-resolution manner. The aligned features of each neighbouring frame are then fed to the DFM to make a temporal information fusion. Finally, the reference features containing spatial and temporal information are sent into SR reconstruction module for the high-resolution frame. Experimental results on several datasets demonstrate superior performance to state-of-the-art published methods on video super-resolution.

(1) Background: RNA binding motif 20 (RBM20) regulates mRNA splicing specifically in muscle tissues. Missense mutations in the arginine/serine (RS) domain of RBM20 lead to abnormal gene splicing and have been linked to severe dilated cardiomyopathy (DCM) in human patients and animal models. Interestingly, many of the reported DCM-linked missense mutations in RBM20 are in a highly conserved RSRSP stretch within the RS domain. Recently, it was found that the two Ser residues within this stretch are constitutively phosphorylated, yet the identity of the kinase(s) responsible for phosphorylating these residues, as well as the function of RSRSP phosphorylation, remains unknown. (2) Methods: The ability of three known SR protein kinases (SRPK1, CLK1, and AKT2) to phosphorylate the RBM20 RSRSP stretch and regulate target gene splicing was evaluated by using both in vitro and in vivo approaches. (3) Results: We found that all three kinases phosphorylated S638 and S640 in the RSRSP stretch and regulated RBM20 target gene splicing. While SRPK1 and CLK1 were both capable of directly phosphorylating the RS domain in RBM20, whether AKT2-mediated control of the RS domain phosphorylation is direct or indirect could not be determined. (4) Conclusions: Our results indicate that SR protein kinases regulate the splicing of a cardiomyopathy-relevant gene by modulating phosphorylation of the RSRSP stretch in RBM20. These findings suggest that SR protein kinases may be potential targets for the treatment of RBM20 cardiomyopathy.

PurposeThe impacts of COVID-19 on construction projects have attracted much attention in the construction management research community. Nevertheless, a systematic review of these studies is still lacking. The purpose of this paper is to systematically analyze the impacts of COVID-19 on the different stages of a project life-cycle, and comprehensively sort out the epidemic response measures adopted by project participants. In addition, the study also attempts to explore the challenges and opportunities faced by project management practitioners under the context of COVID-19.Design/methodology/approachThis study comprehensively demonstrates the systematic review process of COVID-19 related research in the construction industry, systematically summarizes the research status of the impact of COVID-19 on construction projects, and defines the strategies to deal with COVID-19 in project management; and through the visualization research, determines the current key research topics and future research trends.FindingsThis study identifies 11 construction activities in the project management life cycle that are affected by COVID-19 and finds that the COVID-19 epidemic has the greatest impact on construction workers, construction standards, construction contracts and construction performance. The study further summarizes the six main epidemic countermeasures and mitigation measures taken within the construction industry following the arrival of the epidemic. In addition, the results of this study identify opportunities and future trends in intelligent construction technology, rapid manufacturing engineering and project management in the construction industry in the post-epidemic era through literature results, which also provide ideas for related research.Practical implicationsCOVID-19 has brought severe challenges to society. It is of great significance for the future sustainable development of the construction industry to identify the impact of COVID-19 on all phases of the project and to promote the development of coping strategies by project stakeholders.Originality/valueFirst of all, there is little study comprehensively reviewing the impacts of COVID-19 on the different stages of construction projects and the strategies to deal with the negative impacts. In addition, from a life cycle perspective, the used articles in this study were grouped into different categories based on project stages. This promotes an integrated and comprehensive understanding of historical studies. Moreover, on the basis of a comprehensive review, this paper puts forward future research directions to promote the sustainable development of the construction sector.

Background: The clinical significance of KRAS exon 3/4 mutations in colorectal cancer (CRC) remains unclear. We aimed to assess the prognostic value of KRAS exons 3 and 4 mutations to determine the necessity for their testing. Methods: KRAS mutations in exon 2/3/4 were evaluated in 1816 stage I-IV patients with colorectal adenocarcinoma. Results: The mutation rates of KRAS and KRAS exons 2, 3, and 4 were 49.0%, 43.0%, 1.9%, and 4.1%, respectively. Univariate survival analysis showed that patients with exon 3 mutation had worse overall survival (OS) compared to those with KRAS exon 2 mutation or wild-type KRAS (P = 0.044, and P = 0.001). Meanwhile, there was no difference in survival between patients with wild-type KRAS and with exon 4 mutation (P = 0.128). In multivariate analysis, KRAS mutations in exon 3 and 2 were both independent factors for worse OS (Exon 3, P = 0.032, HR = 1.861, 95% CI: 1.021-3.391; Exon 2, P = 0.049, HR = 1.298, 95% CI: 1.002-1.682). Among the patients with KRAS exon 2 mutations, those that had mutations in codon 13 had significantly worse prognosis than those with wild-type KRAS (P = 0.001) or KRAS codon 12 mutations (P = 0.003). Conclusions: In KRAS-mutated CRC, exon 3 mutations predict the worst prognosis, while exon 4 mutations predict the best prognosis. Among KRAS exon 2 mutated patients, codon 13 mutations predict worse prognosis than codon 12 mutations. Mutations of different KRAS exons should be analyzed separately.

Arginine-serine (RS) domain(s) in splicing factors are critical for protein-protein interaction in pre-mRNA splicing. Phosphorylation of RS domain is important for splicing control and nucleocytoplasmic transport in the cell. RNA-binding motif 20 (RBM20) is a splicing factor primarily expressed in the heart. A previous study using phospho-antibody against RS domain showed that RS domain can be phosphorylated. However, its actual phosphorylation sites and function have not been characterized. Using middle-down mass spectrometry, we identified 16 phosphorylation sites, two of which (S638 and S640 in rats, or S637 and S639 in mice) were located in the RSRSP stretch in the RS domain. Mutations on S638 and S640 regulated splicing, promoted nucleocytoplasmic transport and protein-RNA condensates. Phosphomimetic mutations on S638 and S640 indicated that phosphorylation was not the major cause for RBM20 nucleocytoplasmic transport and condensation in vitro. We generated a S637A knock-in (KI) mouse model (Rbm(20S637A)) and observed the reduced RBM20 phosphorylation. The KI mice exhibited aberrant gene splicing, protein condensates, and a dilated cardiomyopathy (DCM)-like phenotype. Transcriptomic profiling demonstrated that KI mice had altered expression and splicing of genes involving cardiac dysfunction, protein localization, and condensation. Our in vitro data showed that phosphorylation was not a direct cause for nucleocytoplasmic transport and protein condensation. Subsequently, the in vivo results reveal that RBM20 mutations led to cardiac pathogenesis. However, the role of phosphorylation in vivo needs further investigation.

During eye closure, a large number of neutrophils (polymorphonuclear neutrophils, PMNs) invade the ocular surface and are often referred to as tear-film PMNs. While immunophenotyping experiments have been performed on tear-film PMNs, the impact of commonly used experimental procedures on their phenotype as well as their response to interleukin-8 (IL-8), a physiological inflammatory mediator, have not yet been investigated. A gentle eye wash method was used to collect cells at home. In the morning upon awaking, participants washed their eyes with sterile phosphate buffer saline (PBS) and collected the runoff into a sterile polypropylene tube. The cell collection was then delivered to the lab within two hours. The effects of centrifugation, incubation and fixation with paraformaldehyde (PFA) before (pre-fixed staining) or after (post-fixed staining) incubation with antibodies were characterized. Tear-film PMNs as well as blood PMNs (used for comparison) were also stimulated with IL-8. To assess the reproducibility of cell collection and variability in receptor expression over time, participants were also asked to collect cells three times over a period of a month. The change in expression of surface receptors, CD11b, CD16, CD55, CD66b, important inflammatory and activation markers, and CD45 (PAN leukocyte marker) was assessed by flow cytometry. Fixing tear-film PMNs prior to the staining with antibodies resulted in a significant (fivefold or more) reduction in the expression of CD11b, CD16 and CD45 when compared to unfixed samples, while CD16 was the only receptor to undergo significant downregulation upon post-staining fixation. Furthermore, additional centrifugation step prior to antibody incubation as well as long (4 h) incubation at 37 °C resulted in significant reductions in expression of CD11b, CD16 and CD55 when compared to control samples. As opposed to blood PMNs, stimulating tear-film PMNs with IL-8 did not induce any significant changes in expression of CD11b, CD16, CD55 and CD66b. When working with collected tear-film PMNs, our results suggest that any additional centrifugation and incubation step should be avoided, or at least limited, and post fixation staining is recommended in order to preserve cell phenotype and cell integrity of tear film PMNs. Our study also adds further information on the reproducibility of the gentle eye wash as well as the inability of tear-film PMNs to modulate their surface receptors upon stimulation with IL-8. The latter may be due to prior exposure to IL-8, activation in the closed-eye environment, or a reduced ability to respond to inflammatory stimulus. Further mechanistic studies will be needed to gain a better understanding of the tear-film neutrophil phenotype.

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

In order to improve the combustion stability of ethanol engine under lean-burn condition, the experiment was carried out on a spark ignition engine with ethanol intake port injection and hydrogen d...

Background Fecal microbiota transplantation (FMT) is considered an effective treatment for slow transit constipation (STC); nevertheless, the mechanism remains unclear. Methods In this study, eight patients with STC were selected according to the inclusion and exclusion criteria; they then received three treatments of FMT. The feces and serum of STC patients were collected after each treatment and analyzed by integrating 16 s rRNA microbiome and metabolomic analyses. Results The results showed that the percentage of clinical improvement reached 62.5% and the rates of patients’ clinical remission achieved 75% after the third treatment. At the same time, FMT improved the Wexner constipation scale (WCS), the Gastrointestinal Quality-of-Life Index (GIQLI) and Hamilton Depression Scale (HAMD). Fecal microbiome alpha diversity and beta diversity altered significantly after FMT. Analysis of the 16 s rRNA microbiome showed that the numbers of Bacteroidetes (Prevotell/Bacteroides) and Firmicute (Roseburia/Blautia) decreased, whereas Actinobacteria (Bifidobacterium), Proteobacteria (Escherichia), and Firmicute (Lactobacillus) increased after FMT. The metabolomics analyses showed that the stool of FMT-treated patients were characterized by relatively high levels of N-Acetyl-L-glutamate, gamma-L-glutamyl-L-glutamic acid, Glycerophosphocholine, et al., after FMT. Compared with baseline, the serum of treated patients was characterized by relatively high levels of L-Arginine, L-Threonine, Ser-Arg, Indoleacrylic acid, Phe-Tyr, 5-L-Glutamyl-L-alanine, and lower levels of Erucamide after the treatment. The correlation analysis between the metabolites and gut microbiota showed a significant correlation. For example, L-Arginine was positively correlated with lactobacillus, et al. L-Threonine was positively correlated with Anaerovibrio, Sediminibacterium but negatively correlated with Phascolarctobacterium. Erucamide had significant negative correlations with Sediminibacterium and Sharpea, while being positively correlated with Phascolarctobacterium. Enriched KEGG pathways analysis demonstrated that the protein digestion and absorption pathways gradually upregulated with the increase of FMT frequency. The L-Arginine and L-Threonine were also involved in the pathway. A large amount of Na + was absorbed in the pathway, so that it might increase mucus secretion and electrical excitability of GI smooth muscle. Conclusions Therefore, we speculated that FMT changed the patients’ gut microbiota and metabolites involved in the protein digestion and absorption pathways, thereby improving the symptoms of STC. Study on the effectiveness and safety of FMT in the treatment of STC. The study was reviewed and approved by Ethics Committee of Tianjin People's Hospital (ChiCTR2000033227) in 2020.

Heterogeneity in skeletal muscle contraction time, peak power output, and resistance to fatigue, among others, is necessary to accommodate the wide range of functional demands imposed on the body. Underlying this functional heterogeneity are a myriad of differences in the myofilament protein isoform expression and post-translational modifications; yet, characterizing this heterogeneity remains challenging. Herein, we have utilized top-down liquid chromatography (LC)-mass spectrometry (MS)-based proteomics to characterize myofilament proteoform heterogeneity in seven rat skeletal muscle tissues including vastus lateralis, vastus medialis, vastus intermedius, rectus femoris, soleus, gastrocnemius, and plantaris. Top-down proteomics revealed that myofilament proteoforms varied greatly across the seven different rat skeletal muscle tissues. Subsequently, we quantified and characterized myofilament proteoforms using online LC-MS. We have comprehensively characterized the fast and slow skeletal troponin I isoforms, which demonstrates the ability of top-down MS to decipher isoforms with high sequence homology. Taken together, we have shown that top-down proteomics can be used as a robust and high-throughput method to characterize the molecular heterogeneity of myofilament proteoforms from various skeletal muscle tissues.

Antibody-drug conjugates (ADCs) are designed to combine the target specificity of monoclonal antibodies and potent cytotoxin drugs to achieve better therapeutic outcome. Comprehensive evaluation of the quality attributes of ADCs is critical for drug development but remains challenging due to heterogeneity of the construct. Currently, peptide mapping with reversed-phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) is the predominant approach to characterize ADCs. However, it is suboptimal for sequence characterization and quantification of ADCs because it lacks a comprehensive view of co-existing variants and suffers from varying ionization effects of drug-conjugated peptides compared to unconjugated counterparts. Here, we present the first middle-down RPLC-MS analysis of both cysteine (Adcetris®; BV) and lysine (Kadcyla®; T-DM1) conjugated ADCs at the subunit level (~25 kDa) with electron transfer dissociation (ETD). We successfully achieved high-resolution separation of subunit isomers arising from different drug conjugation and subsequently localized the conjugation sites. Moreover, we obtained a comprehensive overview of the micro-variants associated with each subunits and characterized them such as oxidized variants with different sites. Furthermore, we observed relatively high levels of conjugation near complementarity-determining regions (CDRs) from the heavy chain but no drug conjugation near CDRs of light chain (Lc) from lysine conjugated T-DM1. Based on the extracted ion chromatograms, we measured accurate average drug to antibody ratio (DAR) values and relative occupancy of drug-conjugated subunits. Overall, the middle-down MS approach enables the evaluation of multiple quality attributes including DAR, positional isomers, conjugation sites, occupancy, and micro-variants, which potentially open up a new avenue to characterize ADCs.

Top-down mass spectrometry (MS)-based proteomics has become a powerful tool for comprehensive characterization of intact proteins. However, because of the high complexity of the proteome, highly effective separation of intact proteins from complex mixtures prior to MS analysis remains challenging. Monolithic columns have shown great promise for intact protein separation due to their high permeability, low backpressure, and fast mass transfer. Herein, for the first time, we developed bridged hybrid bis(triethoxysilyl)ethylene (BTSEY) monolith with C8 functional groups (C8@BTSEY) for highly effective protein separation and coupled it to high-resolution MS for identification of intact proteins from complex protein mixtures. We have optimized mobile phase conditions of our monolith-based reverse-phase chromatography (RPC) for online liquid chromatography (LC)-MS analysis and evaluated separation reproducibility of the C8@BTSEY column. We further assessed the chromatographic performance of this column by separating a complex protein mixture extracted from swine heart tissue. Using our monolithic column (i.d. 100 μm × 35 cm), we separated over 300 proteoforms (up to 104 kDa) from 360 ng of protein mixture in an 80 min one-dimensional (1D) LC run. The highly effective separation and recovery of intact proteins from this monolithic column allowed unambiguous identification of ∼100 proteoforms including a large protein, αactinin2 (103.77 kDa), by online 1D LC-MS/MS analysis for the first time. As demonstrated, this C8@BTSEY column is reproducible and effective in separation of intact proteins, which shows high promise for top-down proteomics.

The pharmaceutical industry’s interest in monoclonal antibodies (mAbs) and their derivatives has spurred rapid growth in the commercial and clinical pipeline of these effective therapeutics. The complex micro-heterogeneity of mAbs requires in-depth structural characterization for critical quality attribute assessment and quality assurance. Currently, mass spectrometry (MS)-based methods are the gold standard in mAb analysis, primarily with a bottom-up approach in which immunoglobulins G (IgGs) and their variants are digested into peptides to facilitate the analysis. Comprehensive characterization of IgGs and the micro-variants remains challenging at the proteoform level. Here, we used both top-down and middle-down MS for in-depth characterization of a human IgG1 using ultra-high resolution Fourier transform MS. Our top-down MS analysis provided characteristic fingerprinting of the IgG1 proteoforms at unit mass resolution. Subsequently, the tandem MS analysis of intact IgG1 enabled the detailed sequence characterization of a representative IgG1 proteoform at the intact protein level. Moreover, we used the middle-down MS analysis to characterize the primary glycoforms and micro-variants. Micro-variants such as low-abundance glycoforms, C-terminal glycine clipping, and C-terminal proline amidation were characterized with bond cleavages higher than 44% at the subunit level. By combining top-down and middle-down analysis, 76% of bond cleavage (509/666 amino acid bond cleaved) of IgG1 was achieved. Taken together, we demonstrated the combination of top-down and middle-down MS as powerful tools in the comprehensive characterization of mAbs.

A liquid chromatography-mass spectrometry (LC-MS) method was developed to provide a fingerprint of polysorbate 80 (PS80) subspecies that enables identification of PS80 degradation pathway. The developed method demonstrates unique monoester peak profile of PS80 from different vendors, attributed by differences in relative abundance of the fatty acid monoesters. The LC-MS method was also applied to examine the susceptibility of PS80, at different grades, to auto-oxidation and hydrolysis. PS80 oxidative degradation induced by iron or occurred in open bottle without nitrogen overlay was found to follow the same pathway, but at a much faster rate in the former scenario. The oxidation preferentially occurs at the double bond of fatty acid chains, thus providing explanation on the faster degradation observed in PS80 at Chinese Pharmacopia (ChP) grade than at multi-compendial (MC) grade. In contrast, the difference in susceptibility of MC and ChP grade PS80 against esterase-induced hydrolysis in placebo was not pronounced. The method was also able to provide a fingerprint to identify both PS80 hydrolysis and oxidation in mAb drug product stability samples, but it requires a solid phase extraction step to remove protein prior to the analysis.

Background: The clinical significance of KRAS exon 3/4 mutations in colorectal cancer (CRC) remains unclear. We aimed to assess the prognostic value of KRAS exons 3 and 4 mutations to determine the necessity for their testing. Methods: KRAS mutations in exon 2/3/4 were evaluated in 1816 stage I-IV patients with colorectal adenocarcinoma. Results: The mutation rates of KRAS and KRAS exons 2, 3, and 4 were 49.0%, 43.0%, 1.9%, and 4.1%, respectively. Univariate survival analysis showed that patients with exon 3 mutation had worse overall survival (OS) compared to those with KRAS exon 2 mutation or wild-type KRAS (P = 0.044, and P = 0.001). Meanwhile, there was no difference in survival between patients with wild-type KRAS and with exon 4 mutation (P = 0.128). In multivariate analysis, KRAS mutations in exon 3 and 2 were both independent factors for worse OS (Exon 3, P = 0.032, HR = 1.861, 95% CI: 1.021-3.391; Exon 2, P = 0.049, HR = 1.298, 95% CI: 1.002-1.682). Among the patients with KRAS exon 2 mutations, those that had mutations in codon 13 had significantly worse prognosis than those with wild-type KRAS (P = 0.001) or KRAS codon 12 mutations (P = 0.003). Conclusions: In KRAS-mutated CRC, exon 3 mutations predict the worst prognosis, while exon 4 mutations predict the best prognosis. Among KRAS exon 2 mutated patients, codon 13 mutations predict worse prognosis than codon 12 mutations. Mutations of different KRAS exons should be analyzed separately.

Molecular and cellular mechanisms of mutations of splicing factors in heart function are not well understood. The splicing of precursor mRNA is dependent on an essential group of splicing factors containing serine-arginine (SR) domain(s) that are critical for protein-RNA and protein-protein interaction in the spliceosome assembly. Phosphorylation of SR domains plays a key role in splicing control and the distribution of splicing factors in the cell. RNA binding motif 20 (RBM20) is a splicing factor predominantly expressed in muscle tissues with the highest expression level in the heart. However, its phosphorylation status is completely unknown up-to-date. In this study, we identified sixteen amino acid residues that are phosphorylated by middle-down mass spectrometry. Four of them are located in the SR domain, and two out of the four residues, S638 and S640, play an essential role in splicing control and facilitate RBM20 shuttling from the nucleus to the cytoplasm. Re-localization of RBM20 promotes protein aggregation in the cytoplasm. We have also verified that SR-protein kinases (SRPKs), cdc2-like kinases (CLKs) and protein kinase B (PKB or AKT) phosphorylate S638 and S640. Mutations of S638A and S640G reduce RBM20 phosphorylation and disrupt the splicing. Taken together, we determine the phosphorylation status of RBM20 and provide the first evidence that phosphorylation on SR domain is crucial for pre-mRNA splicing and protein trafficking. Our findings reveal a new role of RBM20 via protein shuttling in cardiac function.

Deamidation of asparagine and glutamine alters protein structures and affects the chemical and biological properties of proteins. Protein deamidation has been demonstrated to be associated with protein folding, enzymatic activity, and degradation, as well as aging, cancer, and neurodegenerative diseases. To gain a better understanding on the biological roles of protein deamidation in aging and diseases, mass spectrometry (MS) has been employed in the identification of deamidated protein species and comprehensive characterization of deamidation sites. Three main MS approaches, top-down, middle-down, and bottom-up have been applied in the study of protein deamidation with high sensitivity, throughput, and accuracy. In this review, we discuss the application of top-down and middle-down MS in the study of protein deamidation, including sample preparation methods, separation strategies, MS and MS/MS techniques and data analysis. The advantages and drawbacks of these two approaches are also discussed and compared with those of the bottom-up method. The development of top-down and middle-down MS methods provides new strategies for protein deamidation analysis and gives new insights into the biological significance of protein deamidation in diseases.

City carbon footprints have become an important tool for monitoring the progress of cities towards lowering their greenhouse gas emissions and contribution to climate change. Cities usually source a major part of their natural resource demand from their local, national and global hinterland, and cause emissions across the whole global supply chain of a city's final demand. It is important that the data underlying carbon footprint assessments of cities capture these supply chains adequately and comprehensively. In this research, we determine the carbon footprints of four Chinese cities, Beijing, Shanghai, Chongqing and Tianjin based on different levels of data availability. Using these case studies, we show conclusively that city carbon footprint analyses must include input-output databases and associated calculus in order to avoid severe errors that arise from unacceptable scope limitations caused by the truncation of the footprint assessment boundary. We also show that city input-output databases must fulfil a number of requirements for city comparisons and for informed decision-making to be feasible. Our findings suggest that investment into multi-layered national input-output tables and datasets will be necessary to monitor progress of cities reducing their greenhouse emissions across the whole supply chain and to inform evidence based policy making that guides greenhouse abatement.

Sarcopenia, the age-related loss of skeletal muscle mass and strength, is a significant cause of morbidity in the elderly and is a major burden on health care systems. Unfortunately, the underlying molecular mechanisms in sarcopenia remain poorly understood. Herein, we utilized top-down proteomics to elucidate sarcopenia-related changes in the fast- and slow-twitch skeletal muscles of aging rats with a focus on the sarcomeric proteome, which includes both myofilament and Z-disc proteins-the proteins that constitute the contractile apparatuses. Top-down quantitative proteomics identified significant changes in the post-translational modifications (PTMs) of critical myofilament proteins in the fast-twitch skeletal muscles of aging rats, in accordance with the vulnerability of fast-twitch muscles to sarcopenia. Surprisingly, age-related alterations in the phosphorylation of Cypher isoforms, proteins that localize to the Z-discs in striated muscles, were also noted in the fast-twitch skeletal muscle of aging rats. This represents the first report of changes in the phosphorylation of Z-disc proteins in skeletal muscle during aging. In addition, increased glutathionylation of slow skeletal troponin I, a novel modification that may help protect against oxidative damage, was observed in slow-twitch skeletal muscles. Furthermore, we have identified and characterized novel muscle type-specific proteoforms of myofilament proteins and Z-disc proteins, including a novel isoform of the Z-disc protein Enigma. The finding that the phosphorylation of Z-disc proteins is altered in response to aging in the fast-twitch skeletal muscles of aging rats opens new avenues for the investigation of the role of Z-discs in age-related muscle dysfunction.

A large number of polymorphonuclear neutrophils (PMNs) invade the ocular surface during prolonged eye closure (sleep); these leukocytes are commonly referred as tear PMNs. PMNs contribute to homeostasis and possess an arsenal of inflammatory mediators to protect against pathogens and foreign materials. This study examined the ability of tear PMNs to generate reactive oxygen species (ROS), an essential killing mechanism for PMNs which can lead to oxidative stress and imbalance. Cells were collected after sleep from healthy participants using a gentle eye wash. ROS production in stimulated (phorbol-12-myristate-13-acetate (PMA), lipopolysaccharides (LPS) or N-Formylmethionyl-leucyl-phenylalanine (fMLP)) and unstimulated tear PMNs was measured using luminol-enhanced chemiluminescence for 60 min. A high level of constitutive/spontaneous ROS production was observed in tear PMNs in the absence of any stimulus. While tear PMNs were able to produce ROS in response to PMA, they failed to appropriately respond to LPS and fMLP, although fMLP-stimulated tear PMNs generated ROS extracellularly in the first three minutes. Higher ROS generation was observed in isolated tear PMNs which may be due to priming from the magnetic bead cell separation system. The differential responses of tear PMNs in ROS generation provide further evidence of their potential inflammatory roles in ocular complications involving oxidative stress.

China is responsible for a large proportion of the global material footprint. Cities are thought to be associated with most of natural resources consumption and negative impacts on the environment, especially in China, where rapid urbanization and industrial transformation has been observed over the past two decades. Cities usually source a major part of material demand from local, national, and global hinterlands across the whole global supply chain of a city's final demand. It is important to understand urban material footprints with a view to building sustainable cities and furthering economic development. In this study, we use input-output analysis to assess total material footprints and investigate the trends of material footprints time series of four Chinese megacities - Beijing, Shanghai, Chongqing, and Tianjin - from 2001 to 2015, along with factors that influence this material footprint by adopting STIRPAT model. Our results show Chongqing has the lowest MF/capita, and the increase of MF in Chongqing and Tianjin is small over time, while Beijing and Shanghai increase rapidly. Chongqing is the only city that relies more on materials extracted from its own environment. Our study provides a first indication of the imbalance between affluent coastal cities and less-developed inland cities. Further case studies are needed to obtain more general results. Our findings provide a basis for the development of relevant future resource management policies for different regions.

Myosin heavy chain (MHC), the major component of the myosin motor molecule, plays an essential role in force production during muscle contraction. However, a comprehensive analysis of MHC proteoforms arising from sequence variations and post-translational modifications (PTMs) remains challenging due to the difficulties in purifying MHC (∼223 kDa) and achieving complete sequence coverage. Herein, we have established a strategy to effectively purify and comprehensively characterize MHC from heart tissue by combining size-exclusion chromatography (SEC) and middle-down mass spectrometry (MS). First, we have developed a MS-compatible SEC method for purifying MHC from heart tissue with high efficiency. Next, we have optimized the Glu-C, Asp-N, and trypsin limited digestion conditions for middle-down MS. Subsequently, we have applied this strategy with optimized conditions to comprehensively characterize human MHC and identified β-MHC as the predominant isoform in human left ventricular tissue. Full sequence coverage based on highly accurate mass measurements has been achieved using middle-down MS combining 1 Glu-C, 1 Asp-N, and 1 trypsin digestion. Three different PTMs: acetylation, methylation, and trimethylation were identified in human β-MHC and the corresponding sites were localized to the N-terminal Gly, Lys34, and Lys129, respectively, by electron capture dissociation (ECD). Taken together, we have demonstrated this strategy is highly efficient for purification and characterization of MHC, which can be further applied to studies of the role of MHC proteoforms in muscle-related diseases. We also envision that this integrated SEC/middle-down MS strategy can be extended for the characterization of other large proteins over 200 kDa.