Confident Identification Research Articles

Introducing "Identification Probability" for Automated and Transferable Assessment of Metabolite Identification Confidence in Metabolomics and Related Studies.

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence─the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in the context of the chemical space being considered. Neither are they easily automated nor transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a database that matches an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multiproperty reference libraries constructed from a subset of the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

Children’s strategic regulation during a confidence lineup paradigm

ABSTRACT The accuracy of memory reports is dependent, at least in part, on a person’s ability to screen out incorrect responses by engaging in strategic regulation of memory reports (Koriat & Goldsmith, 1996; 2001). One way in which strategic regulation can be examined is through the use of an explicit ‘I don’t know’ (IDK) response option during memory report tasks. The present research explored the extent to which a confidence identification paradigm (see Sauer et al., 2008) encouraged strategic regulation in child eyewitnesses when reporting on their recognition memory. We recruited 545 children (aged 6-11) who were assigned to (1) a confidence paradigm that either contained or did not contain an explicit ‘I don’t know’ (IDK) response option or (2) a traditional lineup paradigm that either contained or did not contain an IDK response option. Regardless of whether an IDK response option was available, the confidence paradigm performed with similar accuracy. However, the IDK option was used more frequently in the traditional lineup paradigm than in the confidence paradigm. Taken together, these findings suggest that the confidence identification paradigm sufficiently encourages strategic regulation in children when reporting on recognition memory without the need for an explicit no-response option.

Four-Dimensional Lipidomic Analysis Using Comprehensive Online UHPLC × UHPSFC/Tandem Mass Spectrometry.

Multidimensional chromatography offers enhanced chromatographic resolution and peak capacity, which are crucial for analyzing complex samples. This study presents a novel comprehensive online multidimensional chromatography method for the lipidomic analysis of biological samples, combining lipid class and lipid species separation approaches. The method combines optimized reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) in the first dimension, utilizing a 150 mm long C18 column, with ultrahigh-performance supercritical fluid chromatography (UHPSFC) in the second dimension, using a 10 mm long silica column, both with sub-2 μm particles. A key advantage of employing UHPSFC in the second dimension is its ability to perform ultrafast analysis using gradient elution with a sampling time of 0.55 min. This approach offers a significant increase in the peak capacity. Compared to our routinely used 1D methods, the peak capacity of the 4D system is 10 times higher than RP-UHPLC and 18 times higher than UHPSFC. The entire chromatographic system is coupled with a high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) in both full-scan and tandem mass spectrometry (MS/MS) and with positive- and negative-ion polarities, enabling the detailed characterization of the lipidome. The confident identification of lipid species is achieved through characteristic ions in both polarity modes, information from MS elevated energy (MSE) and fast data-dependent analysis scans, and mass accuracy below 5 ppm. This analytical method has been used to characterize the lipidomic profile of the total lipid extract from human plasma, which has led to the identification of 298 lipid species from 16 lipid subclasses.

Enhancing Confidence in Microplastic Spectral Identification via Conformal Prediction.

Microplastics are an emerging pollutant of concern, with environmental observations recorded across the world. Identifying the type of microplastic is challenging due to spectral similarities among the most common polymers, necessitating methods that can confidently distinguish plastic identities. In practice, a researcher chooses the reference vibrational spectrum that is most like the unknown spectrum, where the likeness between the two spectra is expressed numerically as the hit quality index (HQI). Despite the widespread use of HQI thresholds in the literature, acceptance of a spectral label often lacks any associated confidence. To address this gap, we apply a machine-learning framework called conformal prediction to output a set of possible labels that contain the true identity of the unknown spectrum with a user-defined probability (e.g., 90%). Microplastic reference libraries of environmentally aged and pristine polymeric materials, as well as unknown environmental plastic spectra, were employed to illustrate the benefits of this approach when used with two similarity metrics to compute HQI. We present an adaptable workflow using our open-access code to ensure spectral matching confidence for the microplastic community, reducing manual inspection of spectral matches and enhancing the robustness of quantification in the field.

Challenges in Snakebite Management in India: Insights from a Physician Survey with Special Focus on Kerala and treatment of bites by Hump-nosed Pit Vipers (Hypnale spp.)

Background India has a high incidence of snakebite-related mortality, making effective snakebite management crucial. This study aimed to explore current practices, challenges, and opportunities for improvement in snakebite management across India. Methods A cross-sectional survey was conducted among physicians in India covering aspects such as scope of practice, snake identification, first aid measures, institutional management, and specific management practices for hump-nosed pit viper ( Hypnale hypnale) bites. The survey included 37 questions across 5 sections, with data collected via emails, professional networks, and online platforms. Statistical analysis was performed using SPSS Statistics 23 (IBM Corp, Armonk, NY), and manual thematic analysis was applied to open-ended responses. Results The survey revealed a discrepancy between physicians’ confidence and accuracy in snake identification, with some still reporting outdated first aid and treatment practices. Despite recognizing the importance of snake species identification, a significant portion of respondents incorrectly identified the snakes. The study highlighted variability in institutional practices for snakebite management, such as administering prophylactic antibiotics and tetanus prophylaxis and monitoring periods for asymptomatic patients. In managing H hypnale viper bites, a demand for specific guidelines and a monovalent antivenom was evident because the current polyvalent antivenom is ineffective for this species. Conclusions The survey emphasizes the need for improved training in snake identification, standardized treatment protocols, and the development of region-specific antivenoms. It emphasizes the necessity of updating guidelines to address the unique challenges of snakebite management in India, particularly for species not covered by existing antivenoms.

From earth to sky: Large-scale archaeological settlement patterns in southernmost South America based on ground surveys, UAV LiDAR, and open access satellite imagery

Large-scale archaeological surveys in coastal areas can be challenging. Factors such as remoteness, logistics, accessibility, and weather conditions can render fieldwork time-consuming and expensive in rugged archipelagic settings. Remote sensing encompasses several methods that can be used for increasing the survey area and promoting new archaeological insights. Moreover, it can be an affordable option. Google Earth (among others) collects aerial and satellite imagery from third parties and makes them freely available from anywhere in the world. In southern Tierra del Fuego, clusters of ring-shaped shell middens are conspicuous archaeological features. They are abundant in the central part of the Beagle Channel, but it has not been feasible to study their distribution across the Fuegian archipelago because we lack data from many remote areas where fieldwork is not easily conducted. Remote sensing provides a viable option for large-scale surveying due to the general visibility of these midden clusters. In this study, we establish confidence in open access satellite imagery identifications of ring-shaped middens in Tierra del Fuego based on comparisons with UAV LiDAR and conventional ground surveys, arguing that the results are appropriate for studies of large-scale trends. We provide the results from a full desk-based survey of satellite imagery provided by Google Earth, ESRI, and Microsoft Bing, covering 3000 km of coastline up to 1 km inland in southern Tierra del Fuego. Moreover, we determine the geographical distribution of ring-shaped middens and explore large-scale trends in coastal settlement patterns and landscape use—showing that ring-shaped middens are not evenly distributed across the Fuegian archipelago but strongly related to the sheltered areas of the Beagle and Murray Channels.

A novel analytical strategy based on gas chromatography-Orbitrap high-resolution mass spectrometry combined with solid-phase extraction for the monitoring of stanozolol misuse in human urine.

Stanozolol, an anabolic androgenic steroid listed in Part S1 of the World Anti-Doping Agency Prohibited List, exhibits a low response and significant matrix interference in urine samples when using liquid-liquid extraction-gas chromatography-mass spectrometry (GC-MS). Enhancing sample preparation techniques remains essential for the effective detection of stanozolol and its metabolites. A method for determining stanozolol and its metabolites (3'-OH-stanozolol, 4β-OH-stanozolol, and 16β-OH-stanozolol) in human urine was developed and validated using GC-Orbitrap high-resolution MS combined with optimized mixed-mode solid-phase extraction (SPE). This method was applied to urine samples from two volunteers who orally administered a single dose of stanozolol, with samples collected over a 30-day period post-administration. The optimized mixed-mode SPE method reduced matrix interference and achieved satisfactory extraction efficiency and high sensitivity, enabling confident identification of all targets in human urine. Validation showed extraction recovery of 74% to 81% and limits of detection from 0.1 to 0.25 ng mL-1. The method was successfully applied to detect urinary excretion profiles of stanozolol and its metabolites in positive volunteer samples. This study presents a novel detection protocol for stanozolol and its metabolites, enhancing the monitoring of stanozolol abuse and contributing to the integrity of sports competitions. This protocol offers a robust tool for anti-doping laboratories, aiding in the accurate detection of stanozolol misuse and supporting the enforcement of fair play in athletics.

Gallbladder disease

Gallstone disease is a common cause for patients to present to general practice. It can lead to a range of complications, and this article aims to increase confidence in identification of the condition, as well as referral criteria and management steps. Specifically, it will focus on the care of patients presenting to primary care and recognition of features requiring prompt referral.

Engineering GID4 for use as an N-terminal proline binder via directed evolution.

Nucleic acid sequencing technologies have gone through extraordinary advancements in the past several decades, significantly increasing throughput while reducing cost. To create similar advancement in proteomics, numerous approaches are being investigated to advance protein sequencing. One of the promising approaches uses N-terminal amino acid binders (NAABs), also referred to as recognizers, that selectively can identify amino acids at the N-terminus of a peptide. However, there are only a few engineered NAABs currently available that bind to specific amino acids and meet the requirements of a biotechnology reagent. Therefore, additional NAABs need to be identified and engineered to enable confident identification and, ultimately, de novo protein sequencing. To fill this gap, a human protein GID4 was engineered to create a NAAB for N-terminal proline (Nt-Pro). While native GID4 binds Nt-Pro, its binding is weak (µmol/L) and greatly influenced by the identity of residues following the Nt-Pro. Through directed evolution, yeast-surface display, and fluorescence-activated cell sorting, we identified sequence variants of GID4 with increased binding response to Nt-Pro. Moreover, variants with an A252V mutation showed a reduced influence from residues in the second and third positions of the target peptide when binding to Nt-Pro. The workflow outlined here is shown to be a viable strategy for engineering NAABs, even when starting from native Nt-binding proteins whose binding is strongly impacted by the identity of residues following Nt-amino acid.

Automated classification in turtles genus Malayemys using ensemble multiview image based on improved YOLOv8 with CNN

In Thailand, two snail-eating turtle species in the genus Malayemes (M. subtrijuga and M. macrocephala) are protected animals in which smuggling and trading are illegal. Recently, a new species M. khoratensis has been reported and it has not yet been considered as protected animal species. To enforce the law, species identification of Malayemes is crucial. However, it is quite challenging and requires expertise. Therefore, a simple tool, such as image analysis, to differentiate these three snail-eating species would be highly useful. This study proposes a novel ensemble multiview image processing approach for the automated classification of three turtle species in the genus Malayemys. The original YOLOv8 architecture was improved by utilizing a convolutional neural network (CNN) to overcome the limitations of traditional identification methods. This model captures unique morphological features by analyzing Malayemys species images from various angles, addressing challenges such as occlusion and appearance variations. The ensemble multiview strategy significantly increases the YOLOv8 classification accuracy using a comprehensive dataset, achieving an average mean average precision (mAP) of 98% for the genus Malayemys compared with the nonensemble multiview and single-view strategies. The species identification accuracy of the proposed models was validated by comparing genetic methods using mitochondrial DNA with morphological characteristics. Even though the morphological characteristics of these three species are ambiguous, the mitochondrial DNA sequences are quite distinct. Therefore, this alternative tool should be used to increase confidence in field identification. In summary, the contribution of this study not only marks a significant advancement in computational biology but also supports wildlife and turtle conservation efforts by enabling rapid, accurate species identification.

3D-printed model is a useful addition in orthopedic resident education for the understanding of tibial plateau fractures

This study aimed to explore the role of the three-dimension (3D) printed models in orthopedic resident training of tibial plateau fractures. A total of 41 residents from our institution were divided into two groups. The intervention group, consisting of 20 residents, had access to 3D-printed models illustrating thirteen tibial plateau fractures. In contrast, the control group, comprising 21 residents, received digital images of thirteen identical tibial plateau fractures. Evaluation of learning outcomes included the accurate identification of tibial plateau fracture patterns, deduction of traumatic mechanisms, preoperative plan, assessment time, and subjective questionnaire responses. The participants with 3D printed models scored significantly higher in both the Schatzker classification and Luo three-column classification compared to those without 3D printed models. Residents in the intervention group performed better in accuracy in deducing traumatic mechanisms compared to the control group. In addition, the sum score of preoperative plan in the intervention group was significantly higher than that in the control group. Specifically, participants with 3D printed models scored higher in surgical approach choice and implants placement than these in the control group. Residents exposed to 3D printed models also spent less time to complete the assessment than those with access only to digital imaging. Subjective assessments indicated that 3D-printed models boosted confidence in fracture identification, improved preoperative plan for fracture management and enhanced the understanding in injury mechanism of tibial plateau fractures. Furthermore, residents agreed that the use of 3D-printed models heightened their interest in learning tibial plateau fractures. Therefore, the addition of 3D printed models significantly contributed to a comprehensive understanding of tibial plateau fractures, the improvement in fracture identification, inferring injury mechanisms and preoperative plan.

Identification of novel microcystins in algal extracts by a liquid chromatography–high-resolution mass spectrometry data analysis pipeline

BackgroundMicrocystins are an emergent public health problem. These toxins are secondary metabolites of harmful cyanobacterial blooms, with blooms becoming more prevalent with eutrophication of water. Exposure to microcystins can result in sickness, liver damage, and even death. Over 300 microcystins have been identified to date, with differences in toxicity based on the specific amino acid composition. Because of this diversity in microcystins, as well as the likelihood of detecting as yet undiscovered microcystins, it is vital to establish a methodological workflow to identify any microcystin in a complex sample, regardless of the availability of a reference standard. Additionally, ascribing varying levels of confidence to these identifications is critical to effectively communicate discoveries. MethodsA liquid-chromatography–high-resolution mass spectrometry method was utilized to identify microcystins present in cyanobacterial extracts from a strain of Microcystis aeruginosa and an Aphanizomenon sp. First, microcystin congeners with available standards were identified in the cyanobacterial extract. These known-unknown microcystins were considered to have the highest confidence identifications due to availability of accurate masses, retention times, and library spectra for comparison. Utilizing the spectra of these microcystins, relatively high-abundance diagnostic product-ions were identified and employed to screen the data for additional candidate microcystins. Microcystins without a standard that had an exact mass matching a microcystin published in CyanoMetDB were considered semi-known-unknown microcystins. The remaining microcystins were considered unknown-unknown microcystins. The identities of the microcystins determined herein were additionally supported by product-ion analysis, thiol reactivity, esterification reactions, neutral loss analysis, and literature contextualization. ResultsIn total, utilizing the systematic workflow presented herein, 23 microcystins were identified in the M. aeruginosa culture, including two not published previously: [d-Asp3]MC-LCit and the incompletely identified MC-L(C7H11NO3).

Radical-directed dissociation mass spectrometry for differentiation and relative quantitation of isomeric ether-linked phosphatidylcholines

BackgroundEther-linked phosphatidylcholines (PCs) include both plasmanyl and plasmenyl PCs, which contain an ether or a vinyl ether bond at the sn-1 linkage position, respectively. Profiling and quantifying ether PCs with accurate structural information is challenging because of the common presence of isomeric and isobaric species in a lipidome. ResultsIn the present study, radical directed dissociation (RDD) from collision-induced dissociation (CID) of the bicarbonate anion adduct of ether PCs has been investigated to differentiate and relatively quantify ether PCs. Alkyl- and alkenyl- PCs give diagnostic characteristic fragment patterns that enable their confident identification and isomer differentiation. Additionally, the sn-position specific product ions have proven effective for relative quantitation among isomers in ether PCs and their isobaric PC species. Using this methodology, we successfully identified a total of 30 PC-O species, 21 PC-P species at the chain composition level, and 22 species of isobaric PC at the sn-position level in the human plasma lipid extract. The quantitative analysis revealed that ether PCs with a 20:4 fatty acyl chain are relatively more abundant in human plasma. Finally, the profile of ether PCs in type 2 diabetic (T2D) groups compared to normal control groups revealed a significant decrease in PC-O 18:1/20:5. We also found it is the PC species containing a 17-carbon fatty acyl chain, rather than their isobaric ether PCs, that shows a decreasing trend in the T2D groups. Significanceether-linked PCs are firstly investigated by RDD mass spectrometry.

Identification of polar bioactive substances in the Upper Rhine using effect-directed analysis

Effect-Directed Analysis (EDA) was used to identify bioactive compounds in surface and well water from the Upper Rhine, and to evaluate their properties against the criteria set for Persistent, Mobile and Toxic (PMT) and very persistent and very mobile (vPvM) substances. A multi-layered solid-phase extraction was implemented to enrich a broad range of polar substances from the collected samples. The extracts were fractionated into 108 fractions and tested in the transthyretin (TTR)-binding assay measuring displacement of fluorescently labeled thyroxine (FITC-T4 TTR-binding assay) and the Aliivibrio fischeri bioluminescence (AFB) bioassay. Bioactive fractions guided the identification strategy using high-resolution mass spectrometry. Chemical features were systematically annotated using library databases and suspect lists, incorporating an automated assessment of the quality of each annotation. Based on this assessment, each chemical feature was assigned a specific identification confidence level. Identification of bioactive compounds was facilitated by using bioassay specific suspect lists that were extracted from an in-house developed database of positive and negative TTR-binding compounds and from a recently published database of active inhibitors of AFB. This resulted in the identification and confirmation of ten bioactive substances, including four evaluated as PMT and vPvM substances (diclofenac, trifloxystrobin acid, 6:2 FTSA and PFOA), and one as a potential PMT substance (4-aminoazobenzene). This study demonstrates the effectiveness of EDA in the identification of PMT/vPvM substances in the aquatic environment, facilitating their prioritization for comprehensive environmental risk assessment and possible regulation.

When confidence reveals more than recognition performance does: The case of context load.

Context in which events are embedded is often hypothesized to serve as an independent cue for retrieval. This means that any effects of context need to obey two basic principles of cue-dependent memory: Memory retrieval should be augmented when, first, encoding context is reinstated and, second, this context uniquely specifies individual items stored in memory. Both of these regularities are well supported for recall tests, but they remain contentious in recognition tests. Here, in three experiments, we assess whether unique and nonunique contexts affect memory processes when reinstated during recognition. However, rather than focusing on measures of recognition performance, we looked at confidence judgments collected during recognition that should be particularly sensitive to recollective effects resulting from context cuing. Experiments 1 and 2, using old/new and forced-choice recognition tests, respectively, documented positive effects of context reinstatement on confidence in correct recognition identifications, but only for contexts uniquely associated with individual items. These effects emerged even when there were no reliable context effects in recognition performance measures. Experiment 3 showed the same effect of context reinstatement, moderated by context load, when spontaneous recognition of a previous study episode occurred during restudy. These results demonstrate the role of context as an independent retrieval cue both in deliberate and spontaneous recognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

End-to-End Throughput Chemical Proteomics for Photoaffinity Labeling Target Engagement and Deconvolution.

Photoaffinity labeling (PAL) methodologies have proven to be instrumental for the unbiased deconvolution of protein-ligand binding events in physiologically relevant systems. However, like other chemical proteomic workflows, they are limited in many ways by time-intensive sample manipulations and data acquisition techniques. Here, we describe an approach to address this challenge through the innovation of a carboxylate bead-based protein cleanup procedure to remove excess small-molecule contaminants and couple it to plate-based, proteomic sample processing as a semiautomated solution. The analysis of samples via label-free, data-independent acquisition (DIA) techniques led to significant improvements on a workflow time per sample basis over current standard practices. Experiments utilizing three established PAL ligands with known targets, (+)-JQ-1, lenalidomide, and dasatinib, demonstrated the utility of having the flexibility to design experiments with a myriad of variables. Data revealed that this workflow can enable the confident identification and rank ordering of known and putative targets with outstanding protein signal-to-background enrichment sensitivity. This unified end-to-end throughput strategy for processing and analyzing these complex samples could greatly facilitate efficient drug discovery efforts and open up new opportunities in the chemical proteomics field.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics.

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

The clownfish-hosting sea anemones (Anthozoa: Actiniaria): updated nomenclature, biogeography, and practical field guide.

Ten described species of sea anemones (Anthozoa: Hexacorallia: Actiniaria) serve as hosts to charismatic clownfishes (or anemonefishes) on coral reefs throughout the tropical Indo-West Pacific. Although not diverse in number, the clownfish-hosting sea anemones have large biogeographic ranges, exhibit extensive intraspecific phenotypic appearances, and have been surrounded by a great deal of historical and contemporary taxonomic and nomenclatural confusion. We believe these factors have created challenges for field scientists making real-time species-level identifications of host sea anemones. Subsequently, a surprising amount of peer-reviewed clownfish literature never accounts for the host sea anemone, omitting critical data for understanding the symbiosis ecologically and evolutionarily. Here, we leverage the revolution that has taken place in the realm of digital underwater photography over the past 30 years to provide an updated, practical field guide for the clownfish-hosting sea anemones. First however, we review and revise the nomenclature for each species to better reflect valid changes that were made in the historical literature but never broadly adopted. Next, we demonstrate that machine learning algorithms may be of limited use for automating sea anemone species IDs from digital photographs alone-highlighting the importance of organismal expertise for identifying these animals. Finally, we present high-resolution digital photographs that encompass much of the intraspecific phenotypic variation encountered underwater, discuss important characteristics useful for field IDs, and provide updated range maps for each species to better reflect the known biogeographic range of each host anemone. We hope the increased confidence in field identification provided by this guide will result in more papers incorporating the sea anemone host data into research frameworks and subsequent publications.

Combining Enhanced Resolving Power with Duty Cycle Improvements on a Multi-Reflecting Time-of-Flight Mass Spectrometer.

The combination of enhanced resolving power and improved duty cycle on a multireflecting time-of-flight mass spectrometer is described. Resolving power increases are achieved by extending the effective ion path length from 47 m to greater than 200 m. Path length increases are achieved through containment of ions within the analyzer for up to N = 5 passes using a pulsed deflection electrode. Resolving power was shown to increase from 220,000 to 402,000 (fwhm) at m/z 785 for N = 1 and N = 4 analyzer passes, respectively. Due to the timing of the pulsed deflection electrode, the approach is particularly suited to high resolution analysis over a targeted m/z range. Duty cycle enhancements are achieved for ions of the targeted m/z range via accumulation prior to orthogonal acceleration, providing signal improvements of 2 orders of magnitude. Achieving such high resolving powers at fast scan rates (30 Hz) can yield additional information such as fine isotope structure; when combined with ppb mass measurement accuracy, high confidence in analyte identification can be achieved. The technique is applied for N = 2 analyzer passes, demonstrating fine isotope structure for a typical UHPLC metabolite identification experiment at a 10 Hz acquisition rate. Additionally, mass spectrometry imaging data is acquired using DESI, demonstrating the improved image clarity achieved at >300,000 (fwhm).

CPred: Charge State Prediction for Modified and Unmodified Peptides in Electrospray Ionization.

The mass-to-charge ratio serves as a critical parameter in peptide identification via mass spectrometry, enabling the precise determination of peptide masses and facilitating their differentiation based on unique charge characteristics, especially when peptides are ionized by tools like electrospray ionization, which produces multiply charged ions. We developed a neural network called CPred, which can accurately predict the charge state distribution from +1 to +7 for the modified and unmodified peptides. CPred was trained on the large-scale synthetic training data, consisting of tryptic and non-tryptic peptides, and various fragmentation methods. The model was further evaluated on independent, external test data sets. Results were evaluated through the Pearson correlation coefficient and showed high correlations of up to 0.9997117 between the predicted and acquired charge state distributions. The effect of specifying modifications in the neural network and feature importance was further investigated, revealing the value of modifications and vital peptide properties in holding on to protons. CPreds' accurate predictions of the charge state distribution can play an essential role in boosting confidence in peptide identifications during rescoring as a novel feature.