Tagging Method Research Articles

The FreqTag toolbox: A principled approach to analyzing electrophysiological time series in frequency tagging paradigms

Steady-state visual evoked potential (ssVEP) frequency tagging is an increasingly used method in electrophysiological studies of visual attention and perception. Frequency tagging is suitable for studies examining a wide range of populations, including infants and children. Frequency tagging involves the presentation of different elements of a visual array at different temporal rates, thus using stimulus timing to “tag” the brain response to a given element by means of a unique time signature. Leveraging the strength of the ssVEP frequency tagging method to isolate brain responses to concurrently presented and spatially overlapping visual objects requires specific signal processing methods. Here, we introduce the FreqTag suite of functions, an open source MATLAB toolbox. The purpose of the FreqTag toolbox is three-fold. First, it will equip users with a set of transparent and reproducible analytical tools for the analysis of ssVEP data. Second, the toolbox is designed to illustrate fundamental features of frequency domain and time-frequency domain approaches. Finally, decision criteria for the application of different functions and analyses are described. To promote reproducibility, raw algorithms are provided in a modular fashion, without additional hidden functions or transformations. This approach is intended to facilitate a fundamental understanding of the transformations and algorithmic steps in FreqTag, and to allow users to visualize and test each step in the toolbox.

Maize and Common Bean Seed Exudates Mediate Part of Nonhost Resistance to Phytophthora sojae Prior to Infection.

Phytophthora sojae does not infect nonhost maize (Zea mays) but infects nonhost common bean (Phaseolus vulgaris) under inoculation. Soybean seed exudates participate in mediating host resistance to P. sojae before infection. This study aims to elucidate the role of seed exudates in mediating the nonhost resistance of maize and common bean to P. sojae before infection. The behaviors of P. sojae zoospores in response to the seed exudates were determined using an assay chamber and a concave slide. The proteomes of P. sojae zoospores in response to the seed exudates were analyzed with the tandem mass tag method. The key proteins were quantitatively verified by parallel reaction monitoring. Maize seed exudates exerted a repellent effect on zoospores of P. sojae. This result explains why zoospores sense repelling signaling molecules in maize seed exudates that weaken and strongly inhibit chemotaxis signals in the phosphatidylinositol signaling pathway and arachidonic acid metabolism pathway. Common bean seed exudates did not exhibit any attraction to the zoospores because the guanine nucleotide-binding protein signaling pathway, which is responsible for transmitting chemotactic signals, had no significant change. The proteins protecting the cell membrane structure were significantly downregulated, and the early apoptosis signal glutathione was enhanced in zoospores responding to common bean seed exudates, which resulted in dissolution of the cysts. Maize and common bean seed exudates mediate part of the nonhost resistance to P. sojae via different mechanisms before infection. The immunity of maize to P. sojae is caused by the repellent effect of maize seed exudates on zoospores. Common bean seed exudates participate in mediating nonhost resistance by dissolving the cysts.

Tandem mass tag-based serum proteomic profiling revealed diabetic foot ulcer pathogenesis and potential therapeutic targets

ABSTRACT Diabetic foot ulcer (DFU), one of the most serious complications of diabetes mellitus, is associated with a high amputation rate and decreased life quality. The impact of blood serum proteins on the occurrence and development of DFU has attracted a lot of interest. In this study, we aimed to define and compare the serum proteome of patients with DFU and healthy control (HC) to provide new insights into DFU pathogenesis. DFU patients and age- and sex-matched HCs were enrolled in this study (n = 54). We screened alterations in blood serum proteins from DFU patients and HC using a tandem mass tag (TMT) method based on liquid chromatography-mass spectrometry (LC-MS/MS) quantitative proteomics, and the differentially expressed proteins (DEPs) were further validated by parallel reaction monitoring (PRM) and enzyme-linked immunosorbent assay (ELISA). A total of 173 DEPs (100 up-regulated and 73 down-regulated) were identified between the DFU and HC groups (P < 0.05). Proteomic and bioinformatics analyses indicated that the proteins in the DFU group were mainly related to extracellular matrix (ECM)-receptor interaction and complement and coagulation cascades. The up-regulated DEPs were further verified by PRM and ELISA. LRG1, CD5L, CRP, IGHA1, and LBP were proved upregulated in DFU and these proteins are mainly related to immune response and complement activation. Our findings help to provide a more comprehensive understanding of the pathogenesis of DFU and new insight into potential therapeutic targets.

Bridging the Gap: The Importance of TUBA1A α-Tubulin in Forming Midline Commissures.

Developing neurons undergo dramatic morphological changes to appropriately migrate and extend axons to make synaptic connections. The microtubule cytoskeleton, made of α/β-tubulin dimers, drives neurite outgrowth, promotes neuronal growth cone responses, and facilitates intracellular transport of critical cargoes during neurodevelopment. TUBA1A constitutes the majority of α-tubulin in the developing brain and mutations to TUBA1A in humans cause severe brain malformations accompanied by varying neurological defects, collectively termed tubulinopathies. Studies of TUBA1A function in mammalian cells have been limited by the presence of multiple genes encoding highly similar tubulin proteins, which leads to α-tubulin antibody promiscuity and makes genetic manipulation challenging. Here, we test mutant tubulin levels and assembly activity and analyze the impact of TUBA1A reduction on growth cone composition, neurite extension, and commissural axon architecture during brain development. We present a novel tagging method for studying and manipulating TUBA1A in cells without impairing tubulin function. Using this tool, we show that a TUBA1A loss-of-function mutation TUBA1A N102D (TUBA1A ND ), reduces TUBA1A protein levels and prevents incorporation of TUBA1A into microtubule polymers. Reduced Tuba1a α-tubulin in heterozygous Tuba1a ND/+ mice leads to grossly normal brain formation except a significant impact on axon extension and impaired formation of forebrain commissures. Neurons with reduced Tuba1a as a result of the Tuba1a ND mutation exhibit slower neuron outgrowth compared to controls. Neurons deficient in Tuba1a failed to localize microtubule associated protein-1b (Map1b) to the developing growth cone, likely impacting stabilization of microtubules. Overall, we show that reduced Tuba1a is sufficient to support neuronal migration and cortex development but not commissure formation, and provide mechanistic insight as to how TUBA1A tunes microtubule function to support neurodevelopment.

Profiling plant histone modification at single-cell resolution using snCUT&Tag.

Profiling plant histone modification at single-cell resolution using snCUT&Tag.

Movement of american lobster Homarus americanus associated with offshore mussel Mytilus edulis aquaculture

Bivalve aquaculture sites attract a variety of large benthic species. Previous studies have shown that American lobsterHomarus americanusare more abundant in musselMytilus edulisfarms than in areas outside of them, suggesting that farms provide lobsters with adequate food and shelter. This study used acoustic telemetry to evaluate the influence of longline mussel farms on lobster movement behavior. In 2014, 60 lobsters were acoustically tagged on a boat and released in a mussel farm and at 2 reference sites outside the farm. Most lobsters (92%) left the monitored area within 1 d post-tagging; those released in reference sites moved northeast, whereas those released in the farm moved in random directions. Of the 16 lobsters that stayed or returned to the study area over the course of the 2 mo experiment, 10 displayed nomadic movements, 3 displayed small, local movements—presumably associated with foraging behavior, and 3 displayed both movements. The time lobsters spent within a site, distance travelled, and walking speed did not differ between the farm and reference sites. A second experiment was done in 2017 over 2 mo to evaluate tagging method (‘on boat’ andin situtagging) effects on lobster movement behavior. The experiment followed movements by 50 lobsters, half for each treatment, and showed that tagging method can affect walking speed during the first 24 h, but had no impact on the residence time and the distance travelled by the lobsters.

A Multi-Task Dual-Encoder Framework for Aspect Sentiment Triplet Extraction

Aspect Sentiment Triplet Extraction (ASTE) is a complex and important task in aspect-based sentiment analysis task, which aims to extract aspect-sentiment-opinion triplets from review sentences, to acquire comprehensive information for sentiment analysis. Most of the existing methods use pipeline approaches or end-to-end sequence tagging approaches to solve the ASTE task. However, the pipeline approaches suffer from error accumulation in practical applications. The existing sequence tagging approaches ignore the feature information of the three elements themselves, and it is impossible to model and infer the three elements effectively by placing each word in the same position as importance. Based on this, a multi-task dual-encoder framework is proposed. First, a dual-encoder is constructed to encode and fuse sentence information and semantic information, respectively. Then, the signs and constraints implied between word pairs are used to complete multi-task inference and triplet decoding. Meanwhile, we design two grid tagging methods and their corresponding inference strategies, respectively, for two tasks. The auxiliary task is used as a regularization of the main task, which improves the correct inference ability of the inference strategy for the main task and the robustness of the framework. Extensive testing on two benchmark datasets shows that the proposed framework is simple and effective, and significantly outperforms existing methods.

Accuracy of quantum chemistry structures of chiral tag complexes and the assignment of absolute configuration.

The absolute configuration of a molecule can be established by analysis of molecular rotational spectra of the analyte complexed with a small chiral molecule of known configuration. This approach of converting the analyte enantiomers, with identical rotational spectra, into diastereomers that can be distinguished spectroscopically is analogous to chiral derivatization in nuclear magnetic resonance (NMR) spectroscopy. For the rotational chiral tag method, the derivatization uses noncovalent interactions to install the new chiral center and avoids complications due to possible racemization of the analyte when covalent chemistry is used. The practical success of this method rests on the ability to attribute assigned rotational spectra to specific geometries of the diastereomeric homochiral and heterochiral tag complexes formed in the pulsed jet expansion that is used to introduce samples into the microwave spectrometer. The assignment of a molecular structure to an experimental rotational spectrum uses quantum chemistry equilibrium geometries to provide theoretical estimates of the spectrum parameters that characterize the rotational spectrum. This work reports the results of a high-sensitivity rotational spectroscopy study of the complexes formed between (3)-butyn-2-ol and verbenone. The rotational spectra of four homochiral and four heterochiral complexes are assigned. In addition, the 14 distinct, singly-substituted 13C isotopomer spectra of five of these species are assigned in natural abundance. Analysis of these spectra provides direct structural characterization of the complexes through determination of the carbon atom position coordinates. This data set is used to benchmark quantum chemistry calculations of candidate equilibrium geometries of the chiral tag complexes. The quantum chemistry calculations are limited to methods commonly used in the field of rotational spectroscopy. It is shown that the accuracy of the structures from quantum chemistry provides a high-confidence assignment of cluster geometries to the observed spectra. As a result, a high-confidence determination of the analyte (verbenone) absolute configuration is achieved.

Tandem Mass Tag-Based Proteomics Reveals the effect of Electron Beam Irradiation on Metabolism-Related Differentially Expressed Proteins in Solenocera melantho Postmortem

ABSTRACT Postmortem metabolism in shrimp is an important factor affecting muscle quality during its preservation. Electron beam irradiation (EBI) can effectively kill microorganisms and inactivate enzymes. In this study, the tandem mass tag (TMT) method was used to study the changes in the muscle metabolism of Solenocera melantho postmortem before and after EBI (6 kGy). The TMT method identified a total of 656 proteins, including 120 differentially expressed proteins (DEPs) (56 upregulated, 64 downregulated). The analysis of these results showed that EBI can inactivate most enzymes and slow down their corresponding metabolic processes. These results also showed that irradiation can denature some proteins. The study revealed the effects of EBI on the muscle quality of S. melantho at the molecular level.

Search for B0→τ±ℓ∓ ( ℓ=e , μ ) with a hadronic tagging method at Belle

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Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions

Numerical climate models have been upgraded by the improved description of terrestrial hydrological processes across different scales. The goal of this study is to explore the role of terrestrial hydrological processes on land–atmosphere interactions within the context of modeling uncertainties related to model physics parameterization. The models applied are the Weather Research and Forecasting (WRF) model and its coupled hydrological modeling system WRF-Hydro, which depicts the lateral terrestrial hydrological processes and further allows their feedback to the atmosphere. We conducted convection-permitting simulations (3 km) over the Heihe River Basin in Northwest China for the period 2008–2010, and particularly focused on its upper reach area of complex high mountains. In order to account for the modeling uncertainties associated with model physics parameterization, an ensemble of simulations is generated by varying the planetary boundary layer (PBL) schemes. We embedded the fully three-dimensional atmospheric water tagging method in both WRF and WRF-Hydro for quantifying the strength of land–atmosphere interactions. The impact of PBL parameterization on land–atmosphere interactions is evaluated through its direct effect on vertical mixing. Results suggest that enabled lateral terrestrial flow in WRF-Hydro distinctly increases soil moisture and evapotranspiration near the surface in the high mountains, thereby modifies the atmospheric condition regardless of the applied PBL scheme. The local precipitation recycling ratio in the study area increases from 1.52 to 1.9% due to the description of lateral terrestrial flow, and such positive feedback processes are irrespective of the modeling variability caused by PBL parameterizations. This study highlights the non-negligible contribution of lateral terrestrial flow to local precipitation recycling, indicating the potential of the fully coupled modeling in land–atmosphere interactions research.

Nighttime migrations and behavioral patterns of Pempheris schwenkii.

BackgroundAlthough the biomass of the nocturnal fishes is almost same as that of diurnal fishes, most of the ecological studies that examine feeding or reproductive behaviors are on diurnal fishes. Therefore, there is limited ecological information regarding the nocturnal fishes. This fact may be attributed to the difficulty in observing them during darkness. Members of the genus Pempheris (Pempheridae) are one of the most abundant nocturnal fishes on coral reefs.MethodsThe nighttime migrations of Pempheris schwenkii were observed by attaching a chemical luminescent tag. Tagged fishes were followed by an observer without torch and SCUBA, and their positions and estimated depths were plotted on an underwater topographic map. Aquarium tank observation was carried out to further describe their habits during the night.ResultsThe new tagging method provided good data for observing the migration behavior. In all five observations, the target fishes started nighttime migration from the entrance of their cave within 1 h after sunset. All of them immediately left the inner reef and spent most of the observation time near the surface (0–5 m depth) or shallow (5–15 m depth) water-columns of the outer reef. Their migration pattern varied between days, but they migrated long distance (379–786 m/h) during each observation. The behavior observed in the aquarium tank was categorized into five patterns: schooling, shaking, migrating, spawning, and feeding. Shaking and spawning were observed during one of three observation days.DiscussionThe present study firstly clarified the small-scale but dynamic nocturnal migration pattern of P. schwenkii in nature by a new method using chemical luminescent tags. In addition, combined observations from nature and an aquarium could be used to estimate the behavior of this species. Pempheris schwenkii may reduce their predation risk of eggs and adults by spawning at outer reef in nighttime. It was estimated that they can potentially migrate 4–7 km/night. The rapid growth known for this species may have been supported by their feeding behavior where they can fill up their stomach every night with rich zooplankton in outer reefs. Furthermore, the behavior of this species indicates the possibility that they make an important contribution to the flow of energy and materials in their coral reef ecosystem.

Fine-grained spatial information extraction in radiology as two-turn question answering

ObjectivesRadiology reports contain important clinical information that can be used to automatically construct fine-grained labels for applications requiring deep phenotyping. We propose a two-turn question answering (QA) method based on a transformer language model, BERT, for extracting detailed spatial information from radiology reports. We aim to demonstrate the advantage that a multi-turn QA framework provides over sequence-based methods for extracting fine-grained information. MethodsOur proposed method identifies spatial and descriptor information by answering queries given a radiology report text. We frame the extraction problem such that all the main radiology entities (e.g., finding, device, anatomy) and the spatial trigger terms (denoting the presence of a spatial relation between finding/device and anatomical location) are identified in the first turn. In the subsequent turn, various other contextual information that acts as important spatial roles with respect to a spatial trigger term are extracted along with identifying the spatial and other descriptor terms qualifying a radiological entity. The queries are constructed using separate templates for the two turns and we employ two query variations in the second turn. ResultsWhen compared to the best-reported work on this task using a traditional sequence tagging method, the two-turn QA model exceeds its performance on every component. This includes promising improvements of 12, 13, and 12 points in the average F1 scores for identifying the spatial triggers, Figure, and Ground frame elements, respectively. DiscussionOur experiments suggest that incorporating domain knowledge in the query (a general description about a frame element) helps in obtaining better results for some of the spatial and descriptive frame elements, especially in the case of the clinical pre-trained BERT model. We further highlight that the two-turn QA approach fits well for extracting information for complex schema where the objective is to identify all the frame elements linked to each spatial trigger and finding/device/anatomy entity, thereby enabling the extraction of more comprehensive information in the radiology domain. ConclusionExtracting fine-grained spatial information from text in the form of answering natural language queries holds potential in achieving better results when compared to more standard sequence labeling-based approaches.

Noncovalently Tagged Gas Phase Complex Ions for Screening Unknown Contaminant Metabolites in Plants.

Screening the metabolites of emerging organic contaminants (EOCs) from complicated biological matrices is an important but challenging task. Although stable isotope labeling (SIL) is frequently used to facilitate the identification of contaminant metabolites from redundant interfering components, the isotopically labeled reagents are expensive and difficult to synthesize, which greatly constrains the application of the SIL method. Herein, a new online noncovalent tagging method was developed for screening the metabolites of 1H-benzotriazol (BT) based on the characteristic structural moieties reserved in the metabolites. By selecting β-cyclodextrin (β-CD) as a macrocyclic tagging reagent, metabolites with the reserved moiety were expected to exhibit a characteristic shift of the mass-to-charge ratio (Δm/z = 1134.3698) after being noncovalently tagged by β-CD. Based on the characteristic mass shift, the suspected features were reduced by 1 order of magnitude, as numerous interfering species that could not be effectively tagged by β-CD were excluded. From these suspected features, two metabolites of BT that have not been reported before were successfully screened out. The significant characteristic mass shift caused by the noncovalent tagging method is easier to identify with more confidence than the previously reported SIL method. Besides, noncovalent tagging reagents can be much more accessible and less expensive than isotopically labeled reagents. Hence, this online noncovalent tagging method can be an intriguing alternative to the conventional SIL method.

Proteomic analysis of the effects of simulated microgravity in human gastric mucosal cells

Microgravity is an ecological factor that affects the environment of the body. In this study, quantitative isobaric labeling (tandem mass tag) method was used to study the changes in human gastric mucosal cells under simulated microgravity for the first time. Comparative proteomic analysis identified 394 (202 upregulated and 192 downregulated) and 542 (286 upregulated and 256 downregulated) proteins differentially regulated by simulated microgravity after 3 and 7 days, respectively. Then the identified proteins were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses for further exploration. The results of the analysis showed that the ribosomes of gastric mucosal cells were significantly impacted after exposure to simulated microgravity for 3 days, and the cells appeared to be in a state of stress and inflammation. Exposure to simulated microgravity for 7 days significantly affected the mitochondria of the cells, oxidative stress became more evident, while inflammation and weakened connections were observed in the cells. The results of this study highlighted the temporal response trend of gastric mucosal cells to the stressor of microgravity at the two time points of 3 and 7 days. These findings will provide insights into the development of methods to protect the gastric mucosa during space flight.

Neutron spin structure from e-3He scattering with double spectator tagging at the electron-ion collider

The spin structure function of the neutron is traditionally determined by measuring the spin asymmetry of inclusive electron deep inelastic scattering (DIS) off polarized 3He nuclei. In such experiments, nuclear corrections are significant and must be treated carefully in the interpretation of experimental data. Here we study the feasibility of suppressing model dependencies by tagging both spectator protons in the process of DIS off neutrons in 3He at the forthcoming Electron-Ion Collider (EIC). This allows for a reconstruction of the momentum of the struck neutron to ensure it was nearly at rest in the initial state, thereby reducing sensitivity to nuclear corrections and suppressing contributions from electron DIS off protons in 3He. Using realistic accelerator and detector configurations, we demonstrate that the EIC can probe the neutron spin structure from xB of 0.003 to 0.651. We find that the double spectator tagging method results in reduced uncertainties by a factor of 2 on the extracted neutron spin asymmetries over all kinematics and by a factor of 10 in the low-xB region, thereby providing valuable insight into the spin and flavor structure of nucleons.

Efficient Linear dsDNA Tagging Using Deoxyuridine Excision*.

Site-specific strategies for exchanging segments of dsDNA are important for DNA library construction and molecular tagging. Deoxyuridine (dU) excision is an approach for generating 3' ssDNA overhangs in gene assembly and molecular cloning procedures. Unlike approaches that use a multi-base pair motif to specify a DNA cut site, dU excision requires only a dT→dU substitution. Consequently, excision sites can be embedded in biologically active DNA sequences by placing dU substitutions at non-perturbative positions. In this work, I describe a molecular tagging method that uses dU excision to exchange a segment of a dsDNA strand with a long synthetic oligonucleotide. The core workflow of this method, called deoxyUridine eXcision-tagging (dUX-tagging), is an efficient one-pot reaction: strategically positioned dU nucleotides are excised from dsDNA to generate a 3' overhang so that additional sequence can be appended by annealing and ligating a tagging oligonucleotide. The tagged DNA is then processed by one of two procedures to fill the 5' overhang and remove excess tagging oligo. To facilitate its widespread use, all dUX-tagging procedures exclusively use commercially available reagents. As a result, dUX-tagging is a concise and easily implemented approach for high-efficiency linear dsDNA tagging.

Modeling for the source apportionments of PM10 during sand and dust storms over East Asia in 2020

Sand and dust storms occur frequently in East Asia, and the dust particles could be transported to most areas of East Asia. To quantify the dust emissions in 18 dust source regions in China and Mongolia and their contributions to PM10 concentrations over East Asia, 10 sand and dust storms (SDSs) episodes in 2020 were simulated using the Comprehensive Air Quality Model with Extensions (CAMx). A dust emission scheme and a tagged method were incorporated. The model well captured the variations of PM10 concentrations during the SDSs episodes. The Gobi deserts in Mongolia were the most important sources of sand and dust in East Asia, with the highest dust emissions, contributing more than 60% to the PM10 concentrations over East-Central China, Japan, and South Korea. The dust emission from Inner Mongolia was about 1/3 of that in Mongolia, and contributed 20–30% to PM10 concentrations over East-Central China, Japan, and South Korea. However, more than 50% of the PM10 concentrations in Inner Mongolia originated from Mongolia in the SDSs events. Few dust aerosols from Taklimakan and Eastern Xinjiang could be transported to the areas further than its surrounding area. Because of the larger contribution of Mongolia to Northern China, the variation of the dust storm frequency in Northern China correlated well with the surface conditions in Mongolia. Anthropogenic emissions contributed less than 5% to the PM10 concentrations over most part of East Asia during the SDSs events.

Luminal Fluid Motion Inside an In Vitro Dissolution Model of the Human Ascending Colon Assessed Using Magnetic Resonance Imaging.

Knowledge of luminal flow inside the human colon remains elusive, despite its importance for the design of new colon-targeted drug delivery systems and physiologically relevant in silico models of dissolution mechanics within the colon. This study uses magnetic resonance imaging (MRI) techniques to visualise, measure and differentiate between different motility patterns within an anatomically representative in vitro dissolution model of the human ascending colon: the dynamic colon model (DCM). The segmented architecture and peristalsis-like contractile activity of the DCM generated flow profiles that were distinct from compendial dissolution apparatuses. MRI enabled different motility patterns to be classified by the degree of mixing-related motion using a new tagging method. Different media viscosities could also be differentiated, which is important for an understanding of colonic pathophysiology, the conditions that a colon-targeted dosage form may be subjected to and the effectiveness of treatments. The tagged MRI data showed that the DCM effectively mimicked wall motion, luminal flow patterns and the velocities of the contents of the human ascending colon. Accurate reproduction of in vivo hydrodynamics is an essential capability for a biorelevant mechanical model of the colon to make it suitable for in vitro data generation for in vitro in vivo evaluation (IVIVE) or in vitro in vivo correlation (IVIVC). This work illustrates how the DCM provides new insight into how motion of the colonic walls may control luminal hydrodynamics, driving erosion of a dosage form and subsequent drug release, compared to traditional pharmacopeial methods.

BP neural network analysis for identification of explosive in package by tagged neutron method

A tagged neutron system was established for detecting explosives in a package. An associated α particle neutron generator ING-27 developed by the All-Russian Institute of Automatics (VNIIA) is used as the neutron source, four Lutetium Yttrium OxyorthoSilicate (LYSO) detectors are used for the γ detector, and a silicon detector is used as the α detector. In the package, milk powder, washing powder, ammonium nitrate simulant, and TNT simulant were set as samples. The α–γ coincidence spectra of samples under different placement situations were measured. Time windows of α–γ coincidence spectra were fine selected to obtain the γ information of the suspicious sample. BP neural network was used to analyze these γ spectra. Compared with the full γ spectrum information, the peak area ratio of C, N, O inelastic scattering is more suitable as the input eigenvector of the neural network. Through training, we find that the identification of the test data composed of 80 γ spectra is completely correct when the number of hidden layer nodes is 4.