Spectral Interpretation Research Articles

Methods for the Construction and Editing of an Efficient Control Network for the Photogrammetric Processing of Massive Planetary Remote Sensing Images

Planetary photogrammetry remains an important technical means of producing high-precision planetary maps. High-quality control networks are fundamental to successful bundle adjustment. However, current software tools used by the planetary mapping community to construct and edit control networks exhibit very low efficiency. Moreover, redundant and invalid control points in the control network can further increase the time required for the bundle adjustment process. Due to a lack of targeted algorithm optimization, existing software tools and methods are unable to meet the photogrammetric processing requirements of massive planetary remote sensing images. To address these issues, we first proposed an efficient control network construction framework based on approximate orthoimage matching and hash quick search. Next, to effectively reduce the redundant control points in the control network and decrease the computation time required for bundle adjustment, we then proposed a control network-thinning algorithm based on a K-D tree fast search. Finally, we developed an automatic detection method based on ray tracing for identifying invalid control points in the control network. To validate the proposed methods, we conducted photogrammetric processing experiments using both the Lunar Reconnaissance Orbiter (LRO) narrow-angle camera (NAC) images and the Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRIS-REx) PolyCam images; we then compared the results with those derived from the famous open-source planetary photogrammetric software, the United States Geological Survey (USGS) Integrated Software for Imagers and Spectrometers (ISIS) version 8.0.0. The experimental results demonstrate that the proposed methods significantly improve the efficiency and quality of constructing control networks for large-scale planetary images. For thousands of planetary images, we were able to speed up the generation and editing of the control network by more than two orders of magnitude.

Study on quantitative interpretation of uranium spectral gamma-ray logging based on machine learning algorithm

Spectral gamma-ray logging stands out as an efficacious methodology in the exploration of uranium(U). In order to address the challenges associated with low statistical efficacy in spectral analysis and mitigate the impact of spectral drift, machine learning algorithms such as Back Propagation (BP) neural network, Generalized Regression Neural Network (GRNN), and Support Vector Machine (SVM) have been employed for the quantitative interpretation of uranium. A method rooted in machine learning algorithms for energy spectral analysis has been proposed, catering to the analysis of high-speed spectra logging and gamma-ray spectra characterized by spectral drift. Examinations conducted on standard model wells containing uranium revealed that the BP neural network exhibited commendable accuracy in uranium interpretation, achieving quantification accuracy rates of 86.986 % and 93.478 % for low-grade and medium-high-grade uranium ores in the Testing Set, respectively. Notably, marginal variations in the model's quantification errors were observed under diverse logging speeds and spectral drift conditions, underscoring the capacity of gamma-ray spectral quantitative interpretation through machine learning algorithms to effectively surmount the impacts of logging speed and spectral drift. This machine learning-based approach to energy spectral analysis proved instrumental in enhancing traditional logging speeds to 6 m/min, presenting a novel perspective for the quantitative interpretation of uranium spectral gamma-ray logging at heightened logging speeds.

Sum-Frequency Generation Spectroscopy of Aqueous Interfaces: The Role of Depth and Its Impact on Spectral Interpretation

Sum-Frequency Generation Spectroscopy of Aqueous Interfaces: The Role of Depth and Its Impact on Spectral Interpretation

Measurement of tyre-based microplastics using traditional and quantum cascade laser-based infrared spectrometry

BackgroundDespite the potential environmental impact of TWPs (tyre wear particles), there is a lack of reliable analytical methodologies suitable for their routine identification and characterization. The number of papers dealing with this topic is, so far, very reduced and, therefore, there is a need for addressing it, mostly because traditional transmittance-based IR techniques are suboptimal due to scattering caused by black carbon in tyres. ResultsThis study aims to evaluate the most appropriate infrared (IR) spectrometric technique for monitoring TWPs. Macro attenuated total reflectance (ATR), reflectance microscopy, and quantum cascade laser-based micro transflectance (QCL-LDIR) were employed to analyse samples from used car and truck tyres in two sample configurations: small tyre fragments (∼1 cm2) and TWPs (< 1 mm). ATR yielded well-defined spectra with good signal-to-noise ratios, allowing for a straightforward interpretation of the major functional moieties. Despite reflectance measurements on tyre fragments provided good results, those on TWPs offered limited information due to noise and scattering. Transflectance offered clear peaks and enhanced resolution in the fingerprint region –compared to the other techniques-, much faster analysis times and the ability to effectively measure particles down to 20–10 µm, thus, emerging as the most effective technique for TWPs analysis. However, spectral interpretation is not immediate. Further, a proof-of-concept chemometric study was done to evaluate whether the analytical techniques contain information to differentiate types of tyres. An unsupervised pattern recognition and a supervised classification technique (principal components analysis and classification trees, respectively) were used, which were able to differentiate among the tyres, notably the truck tyre from the cars tyres. SignificanceThe study presents first time the use of micro transflectance IR to study tyre particles down to 20 µm. Traditional total attenuated reflectance is demonstrated as a suitable way to analyse bigger microplastics. These two options open pathways to monitor this important emerging contaminant in environmental matrices.

How Two‐Dimensional Heterocovariance Spectroscopy and Data Fusion Level out the Inadequacies of Compact Spectrometers

ABSTRACTOver the past decade, sensors and compact spectrometers have emerged as a powerful means for real‐time monitoring of chemical and biochemical processes in the field of process analytical technologies (PATs). This is largely attributed to cost‐efficiency and their robustness in near‐line applications. In comparison to more sophisticated laboratory instruments, these devices exhibit limited sensitivity and resolution. In this study, a combination of near‐infrared, low‐field 1H nuclear magnetic resonance and compact Raman spectrometers were employed for the process monitoring of the acid‐catalyzed esterification of isoamyl alcohol and acetic acid to isoamyl acetate. The resulting real‐time data were transformed and visualized for interpretation using two‐dimensional heterocovariance spectroscopy. The data were also subjected to pretreatment, concatenation, and multivariate analysis in accordance with low‐ and mid‐level data fusion. The spectral interpretation derived from heterocovariance spectroscopy provided support for the data pretreatment during data fusion. By applying these computational techniques, the inherent limitations of sensitivity and resolution associated with compact spectroscopic instruments could be overcome, thereby facilitating the interpretation of data and yielding further insights into the process under study. A comparison of the process parameters resulting from the applied methods indicated that consistent data could be obtained. This study demonstrates that heterocovariance spectroscopy and data fusion allow to enhance compact, less expensive analytical instruments for process monitoring and to acquire process knowledge. This, in turn, enables material, financial, and energy resources to be conserved.

Structure and Dynamics of ATP and the ATP-Zn2+ Complex in Solution.

Despite the crucial role of ATP in life and artificial life-like applications, fundamental aspects relevant to its function, such as its conformational properties and its interaction with water and ions, remain unclear. Here, by integrating linear and two-dimensional infrared spectroscopy with ab initio molecular dynamics, we provide a detailed characterization of the vibrational spectra of the phosphate groups in ATP and in its complex with Zn2+ in water. Our study highlights the role of conformational disorder and solvation dynamics, beyond the harmonic normal-mode analysis, and reveals a complex scenario in which electronic and environmental effects tune the coupling between phosphate vibrations. We identify βγ-bidentate and αβγ-tridentate modes as the preferential coordination modes of Zn2+, as was proposed in the literature for Mg2+, although this conclusion is reached by a different spectral interpretation.

Cholesterol Conformational Structures in Phospholipid Membranes.

Cholesterol is a major component of biomembranes that impacts membrane order, permeability, and lateral organization, but the precise molecular mechanisms of cholesterol's actions are still under investigation. Density functional theory (DFT) calculations have opened the fingerprint vibration bands of large molecules to detailed spectral analysis. For cholesterol, Raman spectral interpretation for conformational structure and hydrogen bonding is now possible. Here, DFT calculations of cholesterol conformers identify 10 structure types that also have unique low-frequency Raman spectra. By fitting experimental spectra to these types, the distribution of cholesterol structures present in phospholipid (PL) membrane vesicles was measured. The distributions reveal that the cholesterol iso-octyl chain tends to align with saturated PL chains and shifts to a thermal distribution for unsaturated PL chains. The results agree with the templating effect of cholesterol on PL membranes and show that the top of the iso-octyl chain is rigid like the rings. It is also shown that the inclusion of water molecules hydrogen bonded to the cholesterol hydroxy group in the DFT calculations may improve the spectral fitting for future studies.

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth’s atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

Extraction, Characterization and Evaluation of Health Applications of Moringa oleifera Seed Oil

In this study, the seeds of Moringa oleifera (MO) plant grown in the Adamawa Region of Cameroon were valorized by extracting their oil using mechanical expression. The oil was allowed to clarify through by gravity and an oil yield of 26.07% was obtained. The extracted MO oil was subjected to physicochemical characterization giving the following results; the density of the oil was 0.896 g/mL, a refractive index of 1.468, a viscosity of 49.80± 0.30 mPa.s, an acid value of 2.69%, a peroxide value of 3.7 meq of O2/kg of oil, a saponification value of 189.34 mg of KOH/g of oil and an iodine index of 67.79g/100g of oil. The determination of relevant secondary metabolites by titration revealed a flavonoid content of 0.66 mg GAE/g, total phenol content of 9.7 mg QE/g, carotenoid content of 0.25 mg beta-caro/g and antioxidant activity gave an IC50 concentration of 17.5 mg/mL. Determination of the fatty acid profile revealed that oleic acid (78.45%) makes up the predominant component in the MO seed oil. The chemical composition of the MO seed oil was further verified by IR spectroscopy whose spectral interpretation revealed a predominance of fatty acid moieties in the oil. From these results, it appears that Moringa oleifera seed oil has moisturizing, antioxidant, anti-inflammatory and nourishing properties and therefore the oil is a potent raw material or bioactive substance in the formulation of cosmetic products like creams for body lotion to combat skin infections and the MO seed can find pharmaceutical applications amongst others.

Symmetry Breaking Charge Separation in Far-Red Absorbing Bisstyryl-Bodipy Dimers

Symmetry breaking charge transfer is one of the important photo-events occurring in photosynthetic reaction centers that is responsible for initiating electron transfer leading to a long-lived charge-separated state and has been successfully employed in light-to-electricity converting optoelectronic devices. Here, we report the synthesis of far-red absorbing and emitting BODIPY-dimer to undergo symmetry-breaking charge transfer leading to charge-separated states of appreciable lifetimes in polar solvents. Compared to its monomer analog, both steady-state and time-resolved fluorescence originating from the S1 state of the dimer revealed quenching which increased with an increase in solvent polarity. The electrostatic potential map from DFT and the time-dependent DFT calculations suggested the existence of a quadrupolar type charge transfer state in polar solvents, and the singlet excited state to be involved in the charge separation process. The electrochemically determined redox gap to be smaller than the energy of the S1 state supporting thermodynamic feasibility of the envisioned symmetry-breaking charge transfer and separation. The spectrum of the charge-separated state arrived from spectroelectrochemical studies, revealing diagnostic peaks helpful for transient spectral interpretation. Finally, ultrafast transient pump-probe spectroscopy provided conclusive evidence of diabatic charge separation in polar solvents by far-red pulsed laser light irradiation. The measured lifetime of the final charge-separated states was found to be 165 ps in dichlorobenzene, 140 ps in benzonitrile, and 43 ps in dimethyl sulfoxide, revealing their significance in light energy harvesting, especially from the less-explored far-red region.

Assessing the Compatibility of Menatetrenone with Excipients: A Spectroscopic Approach and Implication in Drug Formulation Development.

An experiment was conducted to evaluate the compatibility of menatetrenone with selected pharmaceutical excipients. Fourier Transform Infrared Spectroscopy (FTIR) was used to assess drug-excipient compatibility. The present research systematically investigates the FTIR spectrum of each chemical compound separately and their physical blends, analyzing for possible shifts, alterations or novel peak that may indicate chemical interactions. This study aims to utilize spectral data interpretation to detect potential compatibility problems that may occur while design and production of menatetrenone containing dosage forms ensuring their increased stability and effectiveness. The FTIR results demonstrated that all the pharmaceutical excipients were compatible with menatetrenone. In conclusion, the compatibility of pharmaceutical excipients with menatetrenone was successfully assessed using FTIR that will aid in future design of formulations containing menatetrenone as therapeutic moiety.

Electronic-Structure Interpretation: How Much Do We Understand Ce L3 XANES?

Historically, cerium has been attractive for pharmaceutical and industrial applications. The cerium atom has the unique ability to cycle between two chemical states (Ce(III) and Ce(IV)) and drastically adjust its electronic configuration: [Xe] 4f15d16s2 in response to a chemical reaction. Understanding how electrons drive chemical reactions is an important topic. The most direct way of probing the chemical and electronic structure of materials is by X-ray absorption spectroscopy (XAS) or X-ray absorption near-edge structure (XANES) in high energy resolution fluorescence detection (HERFD) mode. Such measurements at the Ce L3 edge have the advantage of a high penetration depth, enabling in-situ reaction studies in a time-resolved manner and investigation of material production or material performance under specific conditions. But how much do we understand Ce L3 XANES? This article provides an overview of the information that can be extracted from experimental Ce L3 XAS/XANES/HERFD data. A collection of XANES data recorded on various cerium systems in HERFD mode is presented here together with detailed discussions on data analysis and the current status of spectral interpretation, including electronic structure calculations.

An Online Native Mass Spectrometry Approach for Fast, Sensitive, and Quantitative Assessment of Adeno-Associated Virus Capsid Content Ratios.

Adeno-associated viruses (AAVs) have emerged as a leading platform for in vivo therapeutic gene delivery and offer tremendous potential in the treatment and prevention of human disease. The fast-paced development of this growing class of therapeutics, coupled with their intrinsic structural complexity, places a high demand on analytical methods capable of efficiently monitoring product quality to ensure safety and efficacy, as well as to support manufacturing and process optimization. Importantly, the presence and relative abundance of both empty and partially filled AAV capsid subpopulations are of principal concern, as these represent the most common product-related impurities in AAV manufacturing and have a direct impact on therapeutic potential. For this reason, the capsid content, or ratio of empty and partial capsids to those packaged with the full-length therapeutic genome, has been identified by regulatory agencies as a critical quality attribute (CQA) that must be carefully controlled to meet clinical specifications. Established analytical methods for the quantitation of capsid content ratios often suffer from long turnaround times, low throughput, and high sample demands that are not well-suited to the narrow timelines and limited sample availability typical of process development. In this study, we present an integrated online native mass spectrometry platform that aims to minimize sample handling and maximize throughput and robustness for rapid and sensitive quantitation of AAV capsid content ratios. The primary advantages of this platform for AAV analysis include the ability to perform online buffer exchange under low flow conditions to maintain sample stability with minimal sample dilution, as well as the ability to achieve online charge reduction via dopant-modified desolvation gas. By exploiting the latter, enhanced spectral resolution of signals arising from empty, partial, and full AAV capsids was accomplished in the m/z domain to facilitate improved spectral interpretation and quantitation that correlated well with the industry standard analytical ultracentrifugation (AUC) method for capsid content ratio determination. The utility of this approach was further demonstrated in several applications, including the rapid and universal screening of different AAV serotypes, evaluation of capsid content for in-process samples, and the monitoring of capsid stability when subjected to thermal stress conditions.

Reassessment of the Shirley and model functions within X-ray photoelectron spectroscopy analysis utilizing comprehensive search methodologies of Bayesian inference

The analysis of X-ray photoelectron spectra often faces challenges due to the lack of standardization in modeling approaches, background subtraction methods, and computational algorithms within the field of computer science. The interpretation of XPS data significantly relies on the unique expertise and judgment of individual researchers. Therefore, the objective of this study is to highlight the difficulties associated with analytical methods that depend heavily on the discretion of individual scientists, to elucidate the prevailing models and background subtraction techniques, and to suggest improvements to these methodologies. This endeavor aims to enhance the reliability and reproducibility of XPS analysis, thereby contributing to the advancement of research in this area. By utilizing the information criterion as part of a thorough search methodology in Bayesian inference, we show that our sophisticated analytical techniques significantly outperform others in the analysis of actual X-ray photoelectron spectroscopy (XPS) spectra. This improvement is evidenced through enhanced accuracy and reliability in spectral interpretation, underscoring the efficacy of our methods in practical applications of XPS.

Renewed spectroscopic and theoretical research of hydrogen bonding in ascorbic acid

The studies of two isomers of ascorbic acid and their deuteroanalogues, presented in the paper, have been accomplished by vibrational spectroscopy methods and quantum-chemical simulations. The spectroscopic research of L-ascorbic and D-isoascorbic acids have been carried out by the infrared (IR) and Raman (R) techniques. On the basis of the obtained results the spectral interpretation of the hydrogen bonded groups of ascorbic acids has been performed. Car-Parrinello Molecular Dynamics (CPMD) and Density Functional Theory (DFT) have been employed to support spectroscopic experimental findings and shed light onto the bridged proton dynamics in the L- and D- isomers of ascorbic acids. The accurate assignments of the hydrogen bond modes have been accomplished with the application of deuterosubstitution, CPMD-solid state simulations and Potential Energy Distribution (PED) analysis. The spectral and structural results have shown that dependency ν(OH) = f(γ(OH)) is the most common for the OHO hydrogen bond, whereas dependency d(OO) = f(γ(OH)) differs as for the ionic and resonance assisted hydrogen bonds.

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry.

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

Advancements in medical research: Exploring Fourier Transform Infrared (FTIR) spectroscopy for tissue, cell, and hair sample analysis.

Fourier Transform Infrared (FTIR) spectroscopy has emerged as a powerful analytical tool in medical research, offering non-invasive and precise examination of the molecular composition of biological samples. The primary objective of this review is to underscore the benefits of FTIR spectroscopy in medicinal research, emphasizing its ability to delineate molecular fingerprints and assist in the identification of biochemical structures and key peaks in biological samples. This review comprehensively explores the diverse applications of FTIR spectroscopy in medical investigations, with a specific focus on its utility in analyzing tissue, cells, and hair samples. Various sources, including Google Scholar, PubMed, WorledCat and Scopus, were utilized to conduct this comprehensive literature review. Recent advancements showcase the versatility of FTIR spectroscopy in elucidating cellular and molecular processes, facilitating disease diagnostics, and enabling treatment monitoring. Notably, FTIR spectroscopy has found significant utility in clinical assessment, particularly in screening counterfeit medicines, owing to its user-friendly operation and minimal sample preparation requirements. Furthermore, customs officials can leverage this technique for preliminary analysis of suspicious samples. This review aims to bridge a gap in the literature and serve as a valuable resource for future research endeavors in FTIR spectroscopy within the medical domain. Additionally, it presents fundamental concepts of FTIR spectroscopy and spectral data interpretation, highlighting its utility as a tool for molecular analysis using Mid-Infrared (MIR) radiation.

Defining the Range of Calibration Burden: From Full Calibration to Calibration-Free

The expansion of spectroscopic process analytical technology (PAT) within the pharmaceutical industry requires chemometric models to enable spectral interpretation. However, calibration of chemometric models often require an intense time, material, and financial burden which may discourage PAT deployment. The advancement of modeling strategies that reduce this calibration burden necessitates consistent terminology for describing model inputs and overall calibration burden throughout chemometric literature. The goal of this article is to define levels of calibration burden by clarifying dataset classifications and model inputs during PAT method development. The scope of this work is specific to calibration of chemometric models incorporated in PAT methods. Harmonizing the language used in the field of chemometrics to describe calibration burden benefits both pharmaceutical manufacturers and regulatory agencies.

Spectroscopic Constraints on the Mid-infrared Attenuation Curve. I. Attenuation Model Using Polycyclic Aromatic Hydrocarbon Emission

We introduce a novel model to spectroscopically constrain the mid-infrared (MIR) extinction/attenuation curve from 3–17 μm, using polycyclic aromatic hydrocarbon (PAH) emission drawn from an AKARI–Spitzer extragalactic cross-archival data set. Currently proposed MIR extinction curves vary significantly in their slopes toward the near-infrared, and the variation in the strengths and shapes of the 9.7 μm and 18 μm silicate absorption features make MIR spectral modeling and interpretation challenging, particularly for heavily obscured galaxies. By adopting the basic premise that PAH bands have relatively consistent intrinsic ratios within dusty starbursting galaxies, we can, for the first time, empirically determine the overall shape of the MIR attenuation curve by measuring the differential attenuation at specific PAH wavelengths. Our attenuation model shows PAH emission in most (ultra)luminous infrared galaxies is unambiguously subjected to attenuation, and we find strong evidence that PAH bands undergo differential attenuation as obscuration increases. Compared to preexisting results, the MIR attenuation curve derived from the model favors relatively gray continuum absorption from 3–8 μm and silicate features with intermediate strength at 9.7 μm but with stronger than typical 18 μm opacity.

Se-Pair Search for Deciphering Selenium-Encoded Peptide and a Pyrolysis-Thermolysis Dietary Model for Minimizing Loss of "KKSe(M)R" during Processing.

Dietary deficiency of selenium is a global health hazard. Supplementation of organic selenopeptides via food crops is a relatively safe approach. Selenopeptides with heterogeneous selenium-encoded isotopes or a poorly fragmented peptide backbone remain unidentified in site-specific selenoproteomic analysis. Herein, we developed the Se-Pair Search, a UniProtKB-FASTA-independent peptide-matching strategy, exploiting the fragmentation patterns of shared peptide backbones in selenopeptides to optimize spectral interpretation, along with developing new selenosite assignment schemes (steps 1-3) to standardize selenium-localization data reporting for the selenoproteome community and thereby facilitating the discovery of unexpected selenopeptides. Using selenium-biofortified rice under cooking, fermentation, and high-temperature and high-pressure processing conditions as a pyrolysis-thermolysis dietary model, we probed the single-molecule-level kinetic evolution of the novel selenopeptide "KKSe(M)R" with qual-quantitative information on graph-theory-oriented localization calculations, abundance patterns, activation energy, and rate constants at a selenoproteome-wide scale. We ground-truth-annotated thirteen pyrolysis-thermolysis products and inferred four pyrolysis-thermolysis pathways to characterize the formation reactivity of the main intermediate variables of KKSe(M)R and constructed an advanced probe-type ultrasound technique prior to pyrolysis-thermolysis conditions for minimizing loss of KKSe(M)R during processing. Importantly, we reveal the unappreciated pyro-excitation diversion of KKSe(M)R at pyrolysis-thermolysis time and temperature matrices. These findings provide pioneering theoretical guidance for controlling dietary selenium supplementation within the safety thresholds.