Carbon-Enhanced Hydrated Salt Phase Change Materials for Thermal Management Applications.

Inorganic hydrated salt phase change materials (PCMs) hold promise for improving the energy conversion efficiency of thermal systems and facilitating the exploration of renewable thermal energy. Hydrated salts, however, often suffer from low thermal conductivity, supercooling, phase separation, leakage and poor solar absorptance. In recent years, compounding hydrated salts with functional carbon materials has emerged as a promising way to overcome these shortcomings and meet the application demands. This work reviews the recent progress in preparing carbon-enhanced hydrated salt phase change composites for thermal management applications. The intrinsic properties of hydrated salts and their shortcomings are firstly introduced. Then, the advantages of various carbon materials and general approaches for preparing carbon-enhanced hydrated salt PCM composites are briefly described. By introducing representative PCM composites loaded with carbon nanotubes, carbon fibers, graphene oxide, graphene, expanded graphite, biochar, activated carbon and multifunctional carbon, the ways that one-dimensional, two-dimensional, three-dimensional and hybrid carbon materials enhance the comprehensive thermophysical properties of hydrated salts and affect their phase change behavior is systematically discussed. Through analyzing the enhancement effects of different carbon fillers, the rationale for achieving the optimal performance of the PCM composites, including both thermal conductivity and phase change stability, is summarized. Regarding the applications of carbon-enhanced hydrate salt composites, their use for the thermal management of electronic devices, buildings and the human body is highlighted. Finally, research challenges for further improving the overall thermophysical properties of carbon-enhanced hydrated salt PCMs and pushing towards practical applications and potential research directions are discussed. It is expected that this timely review could provide valuable guidelines for the further development of carbon-enhanced hydrated salt composites and stimulate concerted research efforts from diverse communities to promote the widespread applications of high-performance PCM composites.

Demonstration of photonics-based D-band integrated localization and communication.

The terahertz spectrum has the ability to provide high-speed communication and millimeter-level resolution. As a result, terahertz-integrated sensing and communication (ISAC) has been identified as a key enabler for 6G wireless networks. This work discusses a photonics-based D-band communication system for integrated high-resolution localization and high-speed wireless communication. Our empirical results show that a communication rate of 5 Gbps over a distance of 1.5 m and location identification of the target with millimeter-level (<4m m) range resolution can be conducted simultaneously using the same signal. We also show that the error due to the thickness of the beam splitter can be eliminated, while the quantization error and the random drift errors are the limiting factors of the resolution achieved. This experimental demonstration using D-band communication indicates that terahertz ISAC can be realized for 6G networks while considering the underlying system restrictions (e.g., bandwidth limit and lens diameter).

Relationship between leadership and work readiness in a cohort of new head nurses in China: A cross-sectional study.

To identify the relationship between leadership and work readiness in a cohort of new head nurses in China. This cross-sectional study enrolled 225 newly appointed head nurses in public tertiary hospitals in China, which were selected using convenience sampling. Data were collected using online questionnaires that included a sociodemographic characteristics form, the Nursing Managers Leadership Scale (NMLS), and the New Nurse Leaders' Job Readiness Scale (NNLJRS). IBM SPSS v.25 was used for statistical analysis. The overall mean scores of NMLS (100.50 ±â€…17.64) and NNLJRS (111.90 ±â€…15.84) of the 225 new nurse leaders were at moderate levels. The results of the Pearson correlation analysis and the hierarchical regression analysis further indicated that there was a significant positive correlation between leadership and work readiness of new head nurses (r = 0.85, P < .001), as well as charisma (ß = 0.19, P < .01), affinity (ß = 0.18, P < .01), coordination ability (ß = 0.32, P < .01), and motivational ability (ß = 0.21, P < .01) in leadership were found to be positively associated with work readiness. This study found that the leadership and work readiness of the new head nurses still needed improvement. A significant relationship was found between these 2 variables, and charisma, affinity, coordination ability, and motivational ability in the leadership ability of the new head nurses facilitated the level of work readiness. Nursing administration should create a leadership development series program focusing on the development of charisma, affinity, coordination ability, and motivational ability to support the work readiness of new nurse managers and help them with role transition.

Key issues in the STRICTA checklist. / 对STRICTAæ¸ å•å‡ ä¸ªå ³é”®é—®é¢˜çš„æ¢³ç†.

The STRICTA checklist is the guideline for reporting clinical trials undertaken using acupuncture intervention. As an extension of the CONSORT checklist, the STRICTA checklist facilitates the reporting quality of acupuncture clinical trials. The clinical research paradigm changes along with the development of science and technology. It is crucial to ensure whether or not the existing STRICTA checklist guides the reporting clinical trials of acupuncture now and in the future as well. This paper introduces the development and the updating procedure of the STRICTA checklist, analyzes the characteristics of utility and the limitation, and proposes several suggestions on the difficulties and challenges encountered in the implementation of the STRICTA checklist of current version so as to advance the further update and improvement.

An Unbiased Proteomic Platform for Activity-based Arginylation Profiling.

Protein arginylation is an essential posttranslational modification (PTM) catalyzed by arginyl-tRNA-protein transferase 1 (ATE1) in mammalian systems. Arginylation features a post-translational conjugation of an arginyl to a protein, making it extremely challenging to differentiate from translational arginine residues with the same mass in a protein sequence. Here we present a general activity-based arginylation profiling (ABAP) platform for the unbiased discovery of arginylation substrates and their precise modification sites. This method integrates isotopic arginine labeling into an ATE1 assay utilizing biological lysates (ex vivo) rather than live cells, thus eliminating translational bias derived from the ribosomal activity and enabling bona fide arginylation identification using isotopic features. ABAP has been successfully applied to an array of peptide, protein, cell, patient, and animal tissue samples using 20 µg sample input, with 229 unique arginylation sites revealed from human proteomes. Representative sites were validated and followed up for their biological functions. The developed platform is globally applicable to the aforementioned sample types and therefore paves the way for functional studies of this difficult-to-characterize protein modification.

Innovative behaviour profile and its associated factors among nurses in China: a cross-sectional study based on latent profile analysis.

OBJECTIVES: This study aimed to investigate the current status of innovative behaviours among nurses in traditional Chinese medicine (TCM) hospitals using latent profile analysis, identify potential subgroups and their population characteristics and explore factors associated with different categories. DESIGN: Cross-sectional study. SETTING: Six TCM hospitals in Anhui, China. PARTICIPANTS: From 1 April 2023 to 31 July 2023, a total of 642 registered nurses with more than 1 year of work experience were recruited from the clinical departments of six TCM hospitals using a stratified cluster sampling method. 529 valid questionnaires were recovered, presenting a validity rate of 82.40%. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected through online surveys containing a sociodemographic questionnaire, the Nurse Innovative Behaviour Scale, the Nurse Adversity Quotient Self-Evaluation Scale and the Conditions for Work Effectiveness Questionnaire-II. Latent profile analysis was performed to identify categorisation features of nurses' innovative behaviour in TCM hospitals. Multiple logistic regression analyses were used to investigate associated factors with profile membership. RESULTS: TCM hospital nurses' innovative behaviours were mainly classified into three types of latent profiles: low innovative behaviour (35.3%), moderate innovative behaviour (48.4%) and high innovative behaviour (16.3%). The results of multiple logistic regression analyses indicated that gender, monthly income, department, hospital level, position, nurse competency level, any training attended related to TCM knowledge and skills, adversity quotient level and structural empowerment level were the influencing factors for the potential profiles. CONCLUSIONS: The innovative behaviour of nurses in TCM hospitals can be classified into three categories. Studying the heterogeneity of the innovative behaviour of nurses in TCM hospitals and its associated factors provides evidence for nursing administrators and educators to develop individualised interventions based on each latent characteristic to improve the innovative behaviour of nurses in TCM hospitals. It is of great significance to the heritage and innovative development of TCM nursing.

Mucus production, host-microbiome interactions, hormone sensitivity, and innate immune responses modeled in human cervix chips.

Modulation of the cervix by steroid hormones and commensal microbiome play a central role in the health of the female reproductive tract. Here we describe organ-on-a-chip (Organ Chip) models that recreate the human cervical epithelial-stromal interface with a functional epithelial barrier and production of mucus with biochemical and hormone-responsive properties similar to living cervix. When Cervix Chips are populated with optimal healthy versus dysbiotic microbial communities (dominated by Lactobacillus crispatus and Gardnerella vaginalis, respectively), significant differences in tissue innate immune responses, barrier function, cell viability, proteome, and mucus composition are observed that are similar to those seen in vivo. Thus, human Cervix Organ Chips represent physiologically relevant in vitro models to study cervix physiology and host-microbiome interactions, and hence may be used as a preclinical testbed for development of therapeutic interventions to enhance women's health.

Protein oxidation of fucose environments (POFE) reveals fucose-protein interactions.

Cell membrane glycoproteins are generally highly fucosylated and sialylated, and post-translational modifications play important roles in the proteins' functions of signaling, binding and cellular processing. For these reasons, methods for measuring sialic acid-mediated protein-protein interactions have been developed. However, determining the role of fucose in these interactions has been limited by technological barriers that have thus far hindered the ability to characterize and observe fucose-mediated protein-protein interactions. Herein, we describe a method to metabolically label mammalian cells with modified fucose, which incorporates a bioorthogonal group into cell membrane glycoproteins thereby enabling the characterization of cell-surface fucose interactome. Copper-catalyzed click chemistry was used to conjugate a proximity labeling probe, azido-FeBABE. Following the addition of hydrogen peroxide (H2O2), the fucose-azido-FeBABE catalyzed the formation of hydroxyl radicals, which in turn oxidized the amino acids in the proximity of the labeled fucose residue. The oxidized peptides were identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Variations in degree of protein oxidation were obtained with different H2O2 reaction times yielding the acquisition of spatial information of the fucose-interacting proteins. In addition, specific glycoprotein-protein interactions were constructed for Galectin-3 (LEG3) and Galectin-3-binding protein (LG3BP) illustrating the further utility of the method. This method identifies new fucose binding partners thereby enhancing our understanding of the cell glycocalyx.

Development and application of GlycanDIA workflow for glycomic analysis.

Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation.

Two DOT1 enzymes cooperatively mediate efficient ubiquitin-independent histone H3 lysine 76 tri-methylation in kinetoplastids.

In higher eukaryotes, a single DOT1 histone H3 lysine 79 (H3K79) methyltransferase processively produces H3K79me2/me3 through histone H2B mono-ubiquitin interaction, while the kinetoplastid Trypanosoma brucei di-methyltransferase DOT1A and tri-methyltransferase DOT1B efficiently methylate the homologous H3K76 without H2B mono-ubiquitination. Based on structural and biochemical analyses of DOT1A, we identify key residues in the methyltransferase motifs VI and X for efficient ubiquitin-independent H3K76 methylation in kinetoplastids. Substitution of a basic to an acidic residue within motif VI (Gx6K) is essential to stabilize the DOT1A enzyme-substrate complex, while substitution of the motif X sequence VYGE by CAKS renders a rigid active-site loop flexible, implying a distinct mechanism of substrate recognition. We further reveal distinct methylation kinetics and substrate preferences of DOT1A (H3K76me0) and DOT1B (DOT1A products H3K76me1/me2) in vitro, determined by a Ser and Ala residue within motif IV, respectively, enabling DOT1A and DOT1B to mediate efficient H3K76 tri-methylation non-processively but cooperatively, and suggesting why kinetoplastids have evolved two DOT1 enzymes.

Unprecedented phytoplankton blooms in autumn/winter in the southern Bohai Sea (China) due to high Yellow River discharge: Implications of extreme rainfall events.

The occurrence of abnormal phytoplankton blooms is one of the significant changes in coastal ecosystems due to climate change. However, the underlying mechanism of such blooms remains poorly understood due to the complexity of the system. In this study, the data from numerous observations was used to elucidate the unprecedented phytoplankton blooms in the autumn and winter of 2021 in Laizhou Bay, a typical aquaculture bay in the southern Bohai Sea of China. The abundance of phytoplankton cells increased by more than tenfold in the southern waters compared to that in the same period from 2019 to 2020. The phytoplankton bloom was first observed in winter in the Bohai Sea, with the cell abundance in the southern bay exceeding 108 cells L-1 in December 2021. The diversity and evenness of phytoplankton communities decreased in the southern area. Cerataulina pelagica was the dominant algae, comprising 69 % of the total phytoplankton in October and 99 % in December. In autumn 2021, the largest flood of the Yellow River in recent decades occurred. This was attributed to extreme rainfall events within the river basin. The input of substantial riverine nutrients played a significant role in promoting phytoplankton blooms. Correlation analysis indicated the important cumulative impact of the Yellow River on phytoplankton blooms rather than a direct short-term effect. Numerical modeling results indicated that exceptionally high Yellow River discharge in autumn could significantly affect the entire bay from autumn to the following spring. This study may contribute to understanding the abnormal phytoplankton blooms in coastal waters and provide valuable insights for environmental management in river basins and coastal waters.

Automation to Enable High-Throughput Chemical Proteomics.

Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.

TL-MSE2-Net: Transfer learning based nested model for cerebrovascular segmentation with aneurysms.

Cerebrovascular (i.e., cerebral vessel) segmentation is essential for diagnosing and treating brain diseases. Convolutional neural network models, such as U-Net, are commonly used for this purpose. Unfortunately, such models may not be entirely satisfactory in dealing with cerebrovascular segmentation with tumors due to the following issues: (1) Relatively small number of clinical datasets from patients obtained through different modalities such as computed tomography (CT) and magnetic resonance imaging (MRI), leading to inadequate training and lack of transferability in the modeling; (2) Insufficient feature extraction caused by less attention to both convolution sizes and cerebral vessel edges. Inspired by the existence of similar features on cerebral vessels between normal subjects and patients, we propose a transfer learning strategy based on a pre-trained nested model called TL-MSE2-Net. This model uses one of the publicly available datasets for cerebrovascular segmentation with aneurysms. To address issue (1), our transfer learning strategy leverages a pre-trained model that uses a large number of datasets from normal subjects, providing a potential solution to the lack of sufficient clinical datasets. To tackle issue (2), we structure the pre-trained model based on 3D U-Net, comprising three blocks: ResMul, DeRes, and REAM. The ResMul and DeRes blocks enhance feature extraction by utilizing multiple convolution sizes to capture multiscale features, and the REAM block increases the weight of the voxels on the edges of the given 3D volume. We evaluated the proposed model on one small private clinical dataset and two publicly available datasets. The experimental results demonstrated that our MSE2-Net framework achieved an average Dice score of 70.81 % and 89.08 % on the two publicly available datasets, outperforming other state-of-the-art methods. Ablation studies were also conducted to validate the effectiveness of each block. The proposed TL-MSE2-Net yielded better results than MSE2-Net on a small private clinical dataset, with increases of 5.52 %, 3.37 %, 6.71 %, and 0.85 % for the Dice score, sensitivity, Jaccard index, and precision, respectively.

SWAMNA: a comprehensive platform for analysis of nucleic acid modifications.

The interest in MS-based analysis of modified nucleic acids is increasing due to the application of nucleic acids in therapeutics. However, there are few available integrated platforms for characterizing nucleic acid modifications. Herein, we report a general mass spectrometry-based SWATH platform to identify and quantify both RNA and DNA modifications, which we call SWATH analysis of modified nucleic acids (SWAMNA). SWAMNA incorporates the search engine, NuMo finder, enabling the analysis of modifications in native and permethylated form. SWAMNA will aid discoveries that provide new insights into nucleic acid modifications.

Acetyl-methyllysine marks chromatin at active transcription start sites.

Lysine residues in histones and other proteins can be modified by post-translational modifications that encode regulatory information1. Lysine acetylation and methylation are especially important for regulating chromatin and gene expression2-4. Pathways involving these post-translational modifications are targets for clinically approved therapeutics to treat human diseases. Lysine methylation and acetylation are generally assumed to be mutually exclusive at the same residue. Here we report cellular lysine residues that are both methylated and acetylated on the same side chain to form Nε-acetyl-Nε-methyllysine (Kacme). We show that Kacme is found on histone H4 (H4Kacme) across a range of species and across mammalian tissues. Kacme is associated with marks of active chromatin, increased transcriptional initiation and is regulated in response to biological signals. H4Kacme can be installed by enzymatic acetylation of monomethyllysine peptides and is resistant to deacetylation by some HDACs in vitro. Kacme can be bound by chromatin proteins that recognize modified lysine residues, as we demonstrate with the crystal structure of acetyllysine-binding protein BRD2 bound to a histone H4Kacme peptide. These results establish Kacme as a cellular post-translational modification with the potential to encode information distinct from methylation and acetylation alone and demonstrate that Kacme has all the hallmarks of a post-translational modification with fundamental importance to chromatin biology.

Analysis of Cell Glycogen with Quantitation and Determination of Branching Using Liquid Chromatography-Mass Spectrometry.

Glycogen is a highly branched biomacromolecule that functions as a glucose buffer. It is involved in multiple diseases such as glycogen storage disorders, diabetes, and even liver cancer, where the imbalance between biosynthetic and catabolic enzymes results in structural alterations and abnormal accumulation of glycogen that can be toxic to cells. Accurate and sensitive glycogen quantification and structural determination are prerequisites for understanding the phenotypes and biological functions of glycogen under these conditions. In this research, we furthered cell glycogen characterization by presenting a highly sensitive method to measure the glycogen content and degree of branching. The method employed a novel fructose density gradient as an alternative to the traditional sucrose gradient to fractionate glycogen from cell mixtures using ultracentrifugation. Fructose was used to avoid the large glucose background, allowing the method to be highly quantitative. The glycogen content was determined by quantifying 1-phenyl-3-methyl-5-pyrazolone (PMP)-derivatized glucose residues obtained from acid-hydrolyzed glycogen using ultra-high-performance liquid chromatography/triple quadrupole mass spectrometry (UHPLC/QqQ-MS). The degree of branching was determined through linkage analysis where the glycogen underwent permethylation, hydrolysis, PMP derivatization, and UHPLC/QqQ-MS analysis. The new approach was used to study the effect of insulin on the glycogen phenotypes of human hepatocellular carcinoma (Hep G2) cells. We observed that cells produced greater amounts of glycogen with less branching under increasing insulin levels before reaching the cell's insulin-resistant state, where the trend reversed and the cells produced less but higher-branched glycogen. The advantage of this method lies in its high sensitivity in characterizing both the glycogen level and the structure of biological samples.

Descriptions of sham acupuncture in randomised controlled trials: a critical review of the literature.

BACKGROUND: Sham acupuncture is usually used to assess the specific effects of acupuncture. However, the reporting quality of sham acupuncture remains unclear despite its critical importance in understanding and analyzing the effects of acupuncture. This paper presents a literature review aimed at assessing the quality of reporting of sham acupuncture in randomized controlled trials (RCTs) based on STRICTA 2010 and TIDieR-Placebo. METHODS: Three electronic English-language databases (PubMed, MEDLINE and Embase) were searched from inception to March 7, 2022, and RCTs of sham acupuncture were identified. The reporting quality of sham acupuncture was assessed in accordance with the items recommended in STRICTA 2010 and TIDieR-Placebo. The reporting quality of other items related to sham acupuncture apart from items from these two checklists was also captured to further assess the reporting quality of sham acupuncture. RESULTS: A total of 609 eligible studies were included. For all of the items recommended in STRICTA 2010 and TIDieR-Placebo, 100% of the studies reported a brief name that described the sham acupuncture, 93.9% studies reported the needle type, and 90.0% reported the names of the points used. Other items for which the reporting rates were above 50% included the number, frequency and duration of treatment sessions; needle retention time; and number of needle insertions per subject per session. Overall, 49.4% of the studies revealed the rationale why sham acupuncture was chosen, 39.7% of the studies involving insertion processes reported the depth of insertion, and 37.9% of the studies reported the needle manufacturer. Other items for which the reporting rates were below 30% included practitioner-related information, response sought, evaluation of blinding, intervention mode and environment, assisting tools, and the extent to which the treatment was varied. The items "Modifications", "How well (planned)" and "How well (actual)" were not reported in any of the analyzed studies. CONCLUSIONS: The overall reporting quality of sham acupuncture in RCTs was suboptimal. Although STRICTA 2010 and TIDieR-Placebo could be beneficial for describing sham acupuncture, neither can offer recommendations specifically for sham acupuncture. There is thus an urgent need to develop specialized guidelines for reporting sham acupuncture in clinical trials.

Glycomic, Glycoproteomic, and Proteomic Profiling of Philippine Lung Cancer and Peritumoral Tissues: Case Series Study of Patients Stages I-III.

Lung cancer is the leading cause of cancer death and non-small cell lung carcinoma (NSCLC) accounting for majority of lung cancers. Thus, it is important to find potential biomarkers, such as glycans and glycoproteins, which can be used as diagnostic tools against NSCLC. Here, the N-glycome, proteome, and N-glycosylation distribution maps of tumor and peritumoral tissues of Filipino lung cancer patients (n = 5) were characterized. We present several case studies with varying stages of cancer development (I-III), mutation status (EGFR, ALK), and biomarker expression based on a three-gene panel (CD133, KRT19, and MUC1). Although the profiles of each patient were unique, specific trends arose that correlated with the role of aberrant glycosylation in cancer progression. Specifically, we observed a general increase in the relative abundance of high-mannose and sialofucosylated N-glycans in tumor samples. Analysis of the glycan distribution per glycosite revealed that these sialofucosylated N-glycans were specifically attached to glycoproteins involved in key cellular processes, including metabolism, cell adhesion, and regulatory pathways. Protein expression profiles showed significant enrichment of dysregulated proteins involved in metabolism, adhesion, cell-ECM interactions, and N-linked glycosylation, supporting the protein glycosylation results. The present case series study provides the first demonstration of a multi-platform mass-spectrometric analysis specifically for Filipino lung cancer patients.

Expanding the Epitranscriptomic RNA Sequencing and Modification Mapping Mass Spectrometry Toolbox with Field Asymmetric Waveform Ion Mobility and Electrochemical Elution Liquid Chromatography.

Post-transcriptional modifications of RNA strongly influence the RNA structure and function. Recent advances in RNA sequencing and mass spectrometry (MS) methods have identified over 140 of these modifications on a wide variety of RNA species. Most next-generation sequencing approaches can only map one RNA modification at a time, and while MS can assign multiple modifications simultaneously in an unbiased manner, MS cannot accurately catalog and assign RNA modifications in complex biological samples due to limitations in the fragment length and coverage depth. Thus, a facile method to identify novel RNA modifications while simultaneously locating them in the context of their RNA sequences is still lacking. We combined two orthogonal modes of RNA ion separation before MS identification: high-field asymmetric ion mobility separation (FAIMS) and electrochemically modulated liquid chromatography (EMLC). FAIMS RNA MS increases both coverage and throughput, while EMLC LC-MS orthogonally separates RNA molecules of different lengths and charges. The combination of the two methods offers a broadly applicable platform to improve the length and depth of MS-based RNA sequencing while providing contextual access to the analysis of RNA modifications.