Mass Mapping Research Articles

Modes of occurrence of gallium in Al-Ga-rich coals in the Jungar Coalfield, Ordos Basin, China: Insights from LA-ICP-MS data

Owing to the concern about supply of Ga, it has been attracted much attention for the modes of occurrence of Ga in Al-Ga-rich coal-hosted deposits. However, the modes of occurrence of Ga in coal were mainly investigated using indirect methods, which may cause uncertainties. In this study, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) spot and mapping analysis were used to directly characterize the concentration of Ga within the host minerals including kaolinite and boehmite, and to investigate the distribution of Ga in organic matter in the Carboniferous Al-Ga-rich coal from the Haerwusu Mine in the Jungar Coalfield of the Ordos Basin, North China. Microscope observation and scanning electron microscope - energy dispersive spectrometry (SEM-EDS) analysis were performed, along with petrographical and mineralogical investigations. Eight types of kaolinite and three types of boehmite particles from coal, erosional-sourced mudstone, and tonstein were identified, classified, and selected for the determination of in-situ elemental compositions.The results showed that the concentration of Ga in the selected minerals varies, with the following order from highest to lowest: colloidal boehmite (90.38 ppm), low-Al (Al2O3/SiO2) clastic kaolinite (84.67 ppm), high-Al clastic kaolinite (55.49 ppm), Na-bearing kaolinite (49.94 ppm), fine-grained boehmite (47.13 ppm), high-Al cryptocrystalline kaolinite (40.25 ppm), low-Al cryptocrystalline kaolinite (38.78 ppm), and low-Al vermicular kaolinite (29.67 ppm), high-Al vermicular kaolinite (28.37 ppm), K-bearing kaolinite (19.44 ppm), and clastic boehmite and cell-filling kaolinite (below detection limit). LA-ICP-MS mapping demonstrated that a certain proportion of Ga could be associated with organic matter, concentrating on vitrinite. Notably, the concentration of Ga in clastic kaolinite and colloidal boehmite was found to be substantially higher compared to the whole-rock coal and erosional-sourced mudstone samples, indicative of their dominant host minerals for Ga. Conversely, the concentration of Ga in K-bearing or Na-bearing kaolinite which had experienced transformation from primary kaolinite is much lower than that in clastic kaolinite, while the concentration of Ga in fine-grained boehmite, which had altered from kaolinite, surpassed that of its corresponding kaolinite layer. These findings suggest that gallium could have undergone migration during the evolution or alteration of clay minerals.

25 Years Responding to Respiratory and Other Viruses with Mass Spectrometry.

This review article presents the development and application of mass spectrometry (MS) approaches, developed in the author's laboratory over the past 25 years, to detect; characterise, type and subtype; and distinguish major variants and subvariants of respiratory viruses such as influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All features make use of matrix-assisted laser desorption ionisation (MALDI) mass maps, recorded for individual viral proteins or whole virus digests. A MALDI-based immunoassay in which antibody-peptide complexes were preserved on conventional MALDI targets without their immobilisation led to an approach that enabled their indirect detection. The site of binding, and thus the molecular antigenicity of viruses, could be determined. The same approach was employed to study antivirals bound to their target viral protein, the nature of the binding residues, and relative binding affinities. The benefits of high-resolution MS were exploited to detect sequence-conserved signature peptides of unique mass within whole virus and single protein digests. These enabled viruses to be typed, subtyped, their lineage determined, and variants and subvariants to be distinguished. Their detection using selected ion monitoring improved analytical sensitivity limits to aid the identification of viruses in clinical specimens. The same high-resolution mass map data, for a wide range of viral strains, were input into a purpose-built algorithm (MassTree) in order to both chart and interrogate viral evolution. Without the need for gene or protein sequences, or any sequence alignment, this phylonumerics approach also determines and displays single-point mutations associated with viral protein evolution in a single-tree building step.

Line-of-sight structure of troughs identified in Subaru Hyper Suprime-Cam Year 3 weak lensing mass maps

ABSTRACT We perform the weak lensing mass mapping analysis to identify troughs, which are defined as local minima in the mass map. Since weak lensing probes the projected matter distribution along the line of sight, these troughs can be produced by single or multiple voids projected along the line of sight. To scrutinize the origins of the weak lensing troughs, we systematically investigate the line-of-sight structure of troughs selected from the latest Subaru Hyper Suprime-Cam (HSC) Year 3 weak lensing data covering $433.48 \, \mathrm{deg}^2$. From a curved sky mass map constructed with the HSC data, we identify 15 troughs with the signal-to-noise ratio higher than 5.7 and address their line-of-sight density structure utilizing redshift distributions of two galaxy samples, photometric luminous red galaxies observed by HSC and spectroscopic galaxies detected by Baryon Oscillation Spectroscopic Survey. While most weak lensing signals due to the troughs are explained by multiple voids aligned along the line of sight, we find that two of the 15 troughs potentially originate from single voids at redshift ∼0.3. The single void interpretation appears to be consistent with our three-dimensional mass mapping analysis. We argue that single voids can indeed reproduce observed weak lensing signals at the troughs if these voids are not spherical but are highly elongated along the line-of-sight direction.

Hidden Giants in JWST's PEARLS: An Ultramassive z = 4.26 Submillimeter Galaxy that Is Invisible to HST

We present a multiwavelength analysis using the Submillimeter Array (SMA), James Clerk Maxwell Telescope, NOEMA, JWST, the Hubble Space Telescope (HST), and the Spitzer Space Telescope of two dusty strongly star-forming galaxies, 850.1 and 850.2, seen through the massive cluster lens A 1489. These SMA-located sources both lie at z = 4.26 and have bright dust continuum emission, but 850.2 is a UV-detected Lyman-break galaxy, while 850.1 is undetected at ≲ 2 μm, even with deep JWST/NIRCam observations. We investigate their stellar, interstellar medium, and dynamical properties, including a pixel-level spectral energy distribution analysis to derive subkiloparsec-resolution stellar-mass and A V maps. We find that 850.1 is one of the most massive and highly obscured, A V ∼ 5, galaxies known at z > 4 with M * ∼1011.8 M ⊙ (likely forming at z > 6), and 850.2 is one of the least massive and least obscured, A V ∼ 1, members of the z > 4 dusty star-forming population. The diversity of these two dust-mass-selected galaxies illustrates the incompleteness of galaxy surveys at z ≳ 3–4 based on imaging at ≲ 2 μm, the longest wavelengths feasible from HST or the ground. The resolved mass map of 850.1 shows a compact stellar-mass distribution, ∼1 kpc, but its expected evolution means that it matches both the properties of massive, quiescent galaxies at z ∼ 1.5 and ultramassive early-type galaxies at z ∼ 0. We suggest that 850.1 is the central galaxy of a group in which 850.2 is a satellite that will likely merge in the near future. The stellar morphology of 850.1 shows arms and a linear bar feature that we link to the active dynamical environment it resides within.

Painting baryons on to N-body simulations of galaxy clusters with image-to-image deep learning

ABSTRACT Galaxy cluster mass functions are a function of cosmology, but mass is not a direct observable, and systematic errors abound in all its observable proxies. Mass-free inference can bypass this challenge, but it requires large suites of simulations spanning a range of cosmologies and models for directly observable quantities. In this work, we devise a U-net – an image-to-image machine learning algorithm – to ‘paint’ the illustristng model of baryons on to dark matter-only (DMO) simulations of galaxy clusters. Using 761 galaxy clusters with M200c ≳ 1014 M⊙ from the TNG300 simulation at z < 1, we train the algorithm to read in maps of projected dark matter mass and output maps of projected gas density, temperature, and X-ray flux. Despite being trained on individual images, the model reproduces the true scaling relation and scatter for the MDM–LX, as well as the distribution functions of the cluster X-ray luminosity and gas mass. For just one decade in cluster mass, the model reproduces three orders of magnitude in LX. The model is biased slightly high when using dark matter maps from the DMO simulation. The model performs well on inputs from TNG300-2, whose mass resolution is eight times coarser; further degrading the resolution biases the predicted luminosity function high. We conclude that U-net-based baryon painting is a promising technique to build large simulated cluster catalogues, which can be used to improve cluster cosmology by combining existing full-physics and large N-body simulations.

What multiple images say about the large-scale mass maps of galaxy clusters

ABSTRACT All lens modelling methods, simply parametrized, hybrid, and free-form, use assumptions to reconstruct galaxy clusters with multiply imaged sources, though the nature of these assumptions (priors) can differ considerably between methods. This raises an important question in strong lens modelling: how much information about the mass model comes from the lensed images themselves, and how much is a consequence of model priors. One way to assess the relative contributions of the lensing data versus model priors is to estimate global lens properties through images alone, without any prior assumptions about the mass distribution. This is our approach. We use 200 mock cluster lenses, half of which have substructures, which vary from clumpy and compact to smooth and extended, a simulated cluster Ares, and real clusters Abell 1689 and RX J1347.5−1145 to show that the centre, ellipticity, and position angle can be estimated quite well, and nearly perfectly for weakly substructured clusters, implying that the recovery of these properties is largely driven by the images, not priors. However, the correlation between the true and image-estimated amount of substructure has a lot of scatter, suggesting that multiple images do not uniquely constrain substructure. Therefore, in general, lens model priors have a stronger effect on smaller scales. Our analysis partly explains why reconstructions using different methodologies can produce qualitatively different mass maps on substructure scales. Our analysis is not meant to aide or replace lens inversion methods, but only to investigate what cluster properties are constrained with multiple images.

Detecting deviations from Gaussianity in high-redshift CMB lensing maps

ABSTRACT While the probability density function of the cosmic microwave background (CMB) convergence field approximately follows a Gaussian distribution, primordial non-Gaussianities, and small contributions from structures at low redshifts make the overall distribution slightly non-Gaussian. Some of the late-time component can be modelled using the distribution of galaxies and subtracted off from the original CMB lensing map to produce a map of matter distribution at high redshifts. Using this high-redshift mass map, we are able to directly study the early phases of structure formation. In this work, we forecast the detectability of signatures of non-Gaussianity due to non-linear structure formation at z > 1.2. Assuming the optimal case of no systematics, we find that it is challenging to detect such signatures in current surveys, but future experiments such as the deep field of CMB-S4 will be able to make detections of ∼7σ.

Towards a full wCDM map-based analysis for weak lensing surveys

ABSTRACT The next generation of weak lensing surveys will measure the matter distribution of the local universe with unprecedented precision, allowing the resolution of non-Gaussian features of the convergence field. This encourages the use of higher-order mass-map statistics for cosmological parameter inference. We extend the forward-modelling based methodology introduced in a previous forecast paper to match these new requirements. We provide multiple forecasts for the $w$CDM parameter constraints that can be expected from stage 3 and 4 weak lensing surveys. We consider different survey setups, summary statistics and mass map filters including wavelets. We take into account the shear bias, photometric redshift uncertainties, and intrinsic alignment. The impact of baryons is investigated and the necessary scale cuts are applied. We compare the angular power spectrum analysis to peak and minima counts as well as Minkowski functionals of the mass maps. We find a preference for Starlet over Gaussian filters. Our results suggest that using a survey setup with 10 instead of 5 tomographic redshift bins is beneficial. Adding cross-tomographic information improves the constraints on cosmology and especially on galaxy intrinsic alignment for all statistics. In terms of constraining power, we find the angular power spectrum and the peak counts to be equally matched for stage 4 surveys, followed by minima counts and the Minkowski functionals. Combining different summary statistics significantly improves the constraints and compensates the stringent scale cuts. We identify the most ‘cost-effective’ combination to be the angular power spectrum, peak counts and Minkowski functionals following Starlet filtering.

ProSight Native: Defining Protein Complex Composition from Native Top-Down Mass Spectrometry Data.

Native mass spectrometry has recently moved alongside traditional structural biology techniques in its ability to provide clear insights into the composition of protein complexes. However, to date, limited software tools are available for the comprehensive analysis of native mass spectrometry data on protein complexes, particularly for experiments aimed at elucidating the composition of an intact protein complex. Here, we introduce ProSight Native as a start-to-finish informatics platform for analyzing native protein and protein complex data. Combining mass determination via spectral deconvolution with a top-down database search and stoichiometry calculations, ProSight Native can determine the complete composition of protein complexes. To demonstrate its features, we used ProSight Native to successfully determine the composition of the homotetrameric membrane complex Aquaporin Z. We also revisited previously published spectra and were able to decipher the composition of a heterodimer complex bound with two noncovalently associated ligands. In addition to determining complex composition, we developed new tools in the software for validating native mass spectrometry fragment ions and mapping top-down fragmentation data onto three-dimensional protein structures. Taken together, ProSight Native will reduce the informatics burden on the growing field of native mass spectrometry, enabling the technology to further its reach.

Strategy for Winning Science Elections After the Covid-19 Pandemic

Strategies for the Dikulon Progo Post-Pandemic Election in 2024. This research uses a qualitative method approach. Sources of research data include primary and secondary data sources. Data collection tools and techniques use interviews and documentation. Test the validity of the data in this study using the source triangulation technique. The research data that has been collected is then analyzed including data collection; presentation of data; and conclusion or verification. The results showed that the strategy for winning elections was by formulating work programs, mass mapping, branding and positioning , political marketing strategies , political communications, political campaigns using SWOT analysis (Strengths, Weaknesses, Opportunities, Threats), as well as approaches to farmers, community leaders and religious leaders. Having a solid team and receiving support from community organizations in Kulon Progo Regency in the form of materials and mass

Probing early structure and model-independent neutrino mass with high-redshift CMB lensing mass maps

Probing early structure and model-independent neutrino mass with high-redshift CMB lensing mass maps

Effect of the initial mass function on the dynamical SMBH mass estimate in the nucleated early-type galaxy FCC 47

Supermassive black holes (SMBHs) and nuclear star clusters (NSCs) co-exist in many galaxies. While the formation history of the black hole is essentially lost, NSCs preserve their evolutionary history imprinted onto their stellar populations and kinematics. Studying SMBHs and NSCs in tandem might help us to ultimately reveal the build-up of galaxy centres. In this study, we combine large-scale VLT/MUSE and high-resolution adaptive-optics-assisted VLT/SINFONI observations of the early-type galaxy FCC 47 with the goal being to assess the effect of a spatially (non-)variable initial mass function (IMF) on the determination of the mass of the putative SMBH in this galaxy. We achieve this by performing DYNAMITE Schwarzschild orbit-superposition modelling of the galaxy and its NSC. In order to properly take account of the stellar mass contribution to the galaxy potential, we create mass maps using a varying stellar mass-to-light ratio derived from single stellar population models with fixed and with spatially varying IMFs. Using the two mass maps, we estimate black hole masses of (7.1−1.1+0.8) × 107 M⊙ and (4.4−2.1+1.2) × 107 M⊙ at 3σ signifance, respectively. Compared to models with constant stellar-mass-to-light ratio, the black hole masses decrease by 15% and 48%, respectively. Therefore, a varying IMF, both in its functional form and spatially across the galaxy, has a non-negligible effect on the SMBH mass estimate. Furthermore, we find that the SMBH in FCC 47 has probably not grown over-massive compared to its very over-massive NSC.

The inflammatory oxidant peroxynitrous acid modulates the structure and function of the recombinant human V3 isoform of the extracellular matrix proteoglycan versican

Continued oxidant production during chronic inflammation generates host tissue damage, with this being associated with pathologies including atherosclerosis. Atherosclerotic plaques contain modified proteins that may contribute to disease development, including plaque rupture, the major cause of heart attacks and strokes. Versican, a large extracellular matrix (ECM) chondroitin-sulfate proteoglycan, accumulates during atherogenesis, where it interacts with other ECM proteins, receptors and hyaluronan, and promotes inflammation. As activated leukocytes produce oxidants including peroxynitrite/peroxynitrous acid (ONOO−/ONOOH) at sites of inflammation, we hypothesized that versican is an oxidant target, with this resulting in structural and functional changes that may exacerbate plaque development. The recombinant human V3 isoform of versican becomes aggregated on exposure to ONOO−/ONOOH. Both reagent ONOO−/ONOOH and SIN-1 (a thermal source of ONOO−/ONOOH) modified Tyr, Trp and Met residues. ONOO−/ONOOH mainly favors nitration of Tyr, whereas SIN-1 mostly induced hydroxylation of Tyr, and oxidation of Trp and Met. Peptide mass mapping indicated 26 sites with modifications (15 Tyr, 5 Trp, 6 Met), with the extent of modification quantified at 16. Multiple modifications, including the most extensively nitrated residue (Tyr161), are within the hyaluronan-binding region, and associated with decreased hyaluronan binding. ONOO−/ONOOH modification also resulted in decreased cell adhesion and increased proliferation of human coronary artery smooth muscle cells. Evidence is also presented for colocalization of versican and 3-nitrotyrosine epitopes in advanced (type II-III) human atherosclerotic plaques. In conclusion, versican is readily modified by ONOO−/ONOOH, resulting in chemical and structural modifications that affect protein function, including hyaluronan binding and cell interactions.

Identification and quantification of protein nitration sites in human coronary artery smooth muscle cells in the absence and presence of peroxynitrous acid/peroxynitrite

Peroxynitrous acid/peroxynitrite (ONOOH/ONOO−) is a powerful oxidizing/nitrating system formed at sites of inflammation, which can modify biological targets, and particularly proteins. Here, we show that multiple proteins from primary human coronary artery smooth muscle cells are nitrated, with LC-MS peptide mass mapping providing data on the sites and extents of changes on cellular and extracellular matrix (ECM) proteins. Evidence is presented for selective and specific nitrations at Tyr and Trp on 11 cellular proteins (out of 3668, including 205 ECM species) in the absence of added reagent ONOOH/ONOO−, with this being consistent with low-level endogenous nitration. A number of these have key roles in cell signaling/sensing and protein turnover. With added ONOOH/ONOO−, more proteins were modified (84 total; with 129 nitrated Tyr and 23 nitrated Trp, with multiple modifications on some proteins), with this occurring at the same and additional sites to endogenous modification. With low concentrations of ONOOH/ONOO− (50 μM) nitration occurs on specific proteins at particular sites, and is not driven by protein or Tyr/Trp abundance, with modifications detected on some low abundance proteins. However, with higher ONOOH/ONOO− concentrations (500 μM), modification is primarily driven by protein abundance. ECM species are major targets and over-represented in the pool of modified proteins, with fibronectin and thrombospondin-1 being particularly heavily modified (12 sites in each case). Both endogenous and exogenous nitration of cell- and ECM-derived species may have significant effects on cell and protein function, and potentially be involved in the development and exacerbation of diseases such as atherosclerosis.

Sparse Bayesian mass-mapping using trans-dimensional MCMC

Uncertainty quantification is a crucial step of cosmological mass-mapping that is often ignored. Suggested methods are typically only approximate or make strong assumptions of Gaussianity of the shear field. Probabilistic sampling methods, such as Markov chain Monte Carlo (MCMC), draw samples form a probability distribution, allowing for full and flexible uncertainty quantification, however these methods are notoriously slow and struggle in the high-dimensional parameter spaces of imaging problems. In this work we use, for the first time, a trans-dimensional MCMC sampler for mass-mapping, promoting sparsity in a wavelet basis. This sampler gradually grows the parameter space as required by the data, exploiting the extremely sparse nature of mass maps in wavelet space. The wavelet coefficients are arranged in a tree-like structure, which adds finer scale detail as the parameter space grows. We demonstrate the trans-dimensional sampler on galaxy cluster-scale images where the planar modelling approximation is valid. In high-resolution experiments, this method produces naturally parsimonious solutions, requiring less than 1% of the potential maximum number of wavelet coefficients and still producing a good fit to the observed data. In the presence of noisy data, trans-dimensional MCMC produces a better reconstruction of mass-maps than the standard smoothed Kaiser-Squires method, with the addition that uncertainties are fully quantified. This opens up the possibility for new mass maps and inferences about the nature of dark matter using the new high-resolution data from upcoming weak lensing surveys such as Euclid.

MALDI peptide mapping for fast analysis in protein footprinting

Although protein footprinting results are commonly obtained by ESI-based LC-MS/MS, a more rapid-turnaround alternative approach is desirable to expand the scope of protein footprinting and facilitate routine analysis such as monitoring protein high order structure in quality control or checking epitope maps. Considering that MALDI is a faster procedure that can be easily adapted for high-throughput analysis, we explore here the feasibility of developing a MALDI-based analysis “portfolio” of bottom-up peptide mass mapping for footprinting. The approach was applied to several model proteins that were submitted to two footprinting strategies, FPOP and GEE labeling, and their performance was evaluated. We found adequate coverage that can be improved with automatic off-line separation and spotting, demonstrating the capability to footprint accurately protein conformational change, showing that MALDI may be useful for selected applications in protein footprinting.

Almanac: Weak Lensing power spectra and map inference on the masked sphere

We present a field-based signal extraction of weak lensing from noisy observations on the curved and masked sky. We test the analysis on a simulated Euclid-like survey, using a Euclid-like mask and noise level. To make optimal use of the information available in such a galaxy survey, we present a Bayesian method for inferring the angular power spectra of the weak lensing fields, together with an inference of the noise-cleaned tomographic weak lensing shear and convergence (projected mass) maps. The latter can be used for field-level inference with the aim of extracting cosmological parameter information including non-gaussianity of cosmic fields. We jointly infer all-sky $E$-mode and $B$-mode tomographic auto- and cross-power spectra from the masked sky, and potentially parity-violating $EB$-mode power spectra, up to a maximum multipole of $\ell_{\rm max}=2048$. We use Hamiltonian Monte Carlo sampling, inferring simultaneously the power spectra and denoised maps with a total of $\sim 16.8$ million free parameters. The main output and natural outcome is the set of samples of the posterior, which does not suffer from leakage of power from $E$ to $B$ unless reduced to point estimates. However, such point estimates of the power spectra, the mean and most likely maps, and their variances and covariances, can be computed if desired.

Virtual reality learning system for remote rock mass mapping

Rock mass quality mapping is essential in rock engineering and mining projects. However, the current manual mapping approach and its teaching are restricted due to the dangerous nature of work near rock walls and the constraints of resources. Therefore, a virtual reality learning system for teaching remote mapping of rock mass quality was developed at Aalto University. Two rock wall sections of an underground tunnel and a roadside rock-cut were scanned using photogrammetry and imported as high-resolution textured 3D models. The user wears a head-mounted display and performs mapping using a pointing device. The system collects the measurements automatically and assists the user in rock mass mapping. Along with the development of the system, qualitative research was conducted to evaluate user performance in a gamified learning system. The results demonstrate that with proper game elements implemented, the learning system can be used to steer student behaviour towards the target range. Once set up, the VR system is a tireless, user-paced aid in training and teaching.

New defect characterization mass map in fringe reflection method

使用相移法测量物体形貌时，质量导引法在相位解包裹中起着重要作用。在检测高反光待测物表面缺陷时，相移条纹调制度常用来识别表面缺陷。本文通过将Sobel梯度与条纹调制相结合，提出了新的缺陷表征质量图，即调制度-Sobel梯度偏差质量图（modulation-sobel gradient variance，MSGV）。将解包裹相位图和原始相位图的均方根误差、峰值信噪比、信噪比3个性能作数据对比，对相位解包裹数据进行模拟测试。结果显示，MSGV的平均峰值信噪比较调制度-相位梯度偏差质量图（modulation-phase gradient variance，MPGV）提升了约1.97%，均方根误差减小了约2.91%。表明本文提出的MSGV算法相对于传统算法有一定优越性，具有更高的抗噪性和更低的解包裹误差。将所提出的方法对鼓型滚子曲面进行缺陷检测与定位，结果表明，MSGV能更好地显示出缺陷的轮廓信息。

Low Resource Integrated Platform for Production and Analysis of Capped mRNA.

The existing platform for large-scale mRNA production is fast, but consumable costs, process technicality, and complexity represent key bottlenecks limiting global mRNA biologics manufacturing. Another challenge is the lack of a consolidated platform for mRNA product characterization and assays that meet regulatory requirements. Bridging these innovation gaps to simplify processes and reduce cost would improve mRNA biologics manufacturability, especially in low-resource settings. This study develops a "cotranscriptional" capping strategy that utilizes T7 RNA polymerase, and the Vaccinia Capping System to synthesize and cap mRNA. We created an "integrated reaction buffer" that supports both capping enzymes for catalytic and in vitro transcription processes, enabling one-pot, two-step capped mRNA synthesis. Additionally, we report a novel, one-step analytic platform for rapid, quantitative, capped mRNA analysis. The assay involves target mRNA segment protection with cheap DNA primers and RNase digest of non-hybridized or non-target sequences before analysis by single nucleotide-resolving urea-polyacrylamide gel electrophoresis (PAGE). The integrated approach simplifies production processes and saves costs. Moreover, this assay has potential applications for mRNA analyses and post-transcriptional modification detection in biological samples. Finally, we propose a strategy that may enable unparalleled sequence coverage in RNase mass mapping by adapting the developed assay and replacing urea-PAGE with mass spectrometry.