Labeling Strategy Research Articles

Enzyme-Responsive Fluorescent Labeling Strategy for In Vivo Imaging of Gut Bacteria.

Myrosinase (Myr), as a unique β-thioglucosidase enzyme capable of converting natural and gut bacterial metabolite glucosinolates into bioactive agents, has recently attracted a great deal of attention because of its essential functions in exerting homeostasis dynamics and promoting human health. Such nutraceutical and biomedical significance demands unique and reliable strategies for specific identification of Myr enzymes of gut bacterial origin in living systems, whereas the dearth of methods for bacterial Myr detection and visualization remains a challenging concern. Herein, we present a series of unique molecular probes for specific identification and imaging of Myr-expressing gut bacterial strains. Typically, an artificial glucosinolate with an azide group in aglycone was synthesized and sequentially linked with the probe moieties of versatile channels through simple click conjugation. Upon gut bacterial enzymatic cleavage, the as-prepared probe molecules could be converted into reactive isothiocyanate forms, which can further act as reactive electrophiles for the covalent labeling of gut bacteria, thus realizing their localized fluorescent imaging within a wide range of wavelength channels in live bacterial strains and animal models. Overall, our proposed method presents a novel technology for selective gut bacterial Myr enzyme labeling in vitro and in vivo. We envision that such a rational probe design would serve as a promising solution for chemoprevention assessment, microflora metabolic mechanistic study, and gut bacterium-mediated physiopathological exploration.

Simultaneous determination of inflammatory factors SAA and LTF based on stable element labeling and inductively coupled plasma mass spectrometry to aid in the diagnosis of infection

ObjectiveThe clinical value of Serum amyloid A (SAA) and Lactoferrin (LTF) has received significant attention, but their detection methods are inadequate, which limits their application. This study aims to develop a dual detection method based on stable element labeling strategies and inductively coupled plasma mass spectrometry (ICP-MS) for SAA/LTF and to assess whether it can be widely used in clinical practice. MethodsA duplex immunoassay system based on sandwich method was constructed. After optimization, methodological evaluation was performed with the guidelines of Clinical Laboratory Standards Institute (CLSI). Finally, 131 plasma samples were collected to analyze whether the new method is suitable for clinical detection. ResultsThe LoB, LLoQ, ULoQ, and linear range of the assay were 1.09 ng/mL, 3 ng/mL, 1500 ng/mL, 3–1500 ng/mL for SAA and 0.85 ng/mL, 2 ng/mL, 1200 ng/mL, 2–1200 ng/mL for LTF respectively. The recovery rates were 95.01% to 106.26%, the intra-batch precision of low, intermediate, and high-level samples was <8%, and the inter-batch of them was <11%, the deviation of interference test results was less than±10%. The Area Under the Curve (AUC) was 0.9809 for SAA, 0.8599 for LTF, and 0.9986 for combination. ConclusionThe quantitative duplex immunoassay for SAA/LTF has high accuracy, good precision, and high specificity, which meets the clinical testing requirements and can be widely used in clinical practice.

Electrophysiological Properties of Proprioception-Related Neurons in the Intermediate Thoracolumbar Spinal Cord.

Proprioception, the sense of limb and body position, is required to produce accurate and precise movements. Proprioceptive sensory neurons transmit muscle length and tension information to the spinal cord. The function of excitatory neurons in the intermediate spinal cord, which receive this proprioceptive information, remains poorly understood. Using genetic labeling strategies and patch-clamp techniques in acute spinal cord preparations in mice, we set out to uncover how two sets of spinal neurons, Clarke's column (CC) and Atoh1-lineage neurons, respond to electrical activity and how their inputs are organized. Both sets of neurons are located in close proximity in laminae V-VII of the thoracolumbar spinal cord and have been described to receive proprioceptive signals. We find that a majority of CC neurons have a tonic-firing type and express a distinctive hyperpolarization-activated current (Ih). Atoh1-lineage neurons, which cluster into two spatially distinct populations, are mostly a fading-firing type and display similar electrophysiological properties to each other, possibly due to their common developmental lineage. Finally, we find that CC neurons respond to stimulation of lumbar dorsal roots, consistent with prior knowledge that CC neurons receive hindlimb proprioceptive information. In contrast, using a combination of electrical stimulation, optogenetic stimulation, and transsynaptic rabies virus tracing, we find that Atoh1-lineage neurons receive heterogeneous, predominantly local thoracic inputs that include parvalbumin-lineage sensory afferents and local interneuron presynaptic inputs. Altogether, we find that CC and Atoh1-lineage neurons have distinct membrane properties and sensory input organization, representing different subcircuit modes of proprioceptive information processing.

In Vivo Fluorescent Labeling of Foam Cell-Derived Extracellular Vesicles as Circulating Biomarkers for In Vitro Detection of Atherosclerosis.

Real-time monitoring of the development of atherosclerosis (AS) is key to the management of cardiovascular disease (CVD). However, existing laboratory approaches lack sensitivity and specificity, mostly due to the dearth of reliable AS biomarkers. Herein, we developed an in vivo fluorescent labeling strategy that allows specific staining of the foam cell-derived extracellular vesicles (EVs) in atherosclerotic plaques, which are released into the blood as circulating biomarkers for in vitro detection of AS. This strategy relies on a self-assembled nanoprobe that could recognize foam cells specifically, where the probe is degraded by the intracellular HClO to produce a trifluoromethyl-bearing boron-dipyrromethene fluorophore (termed B-CF3), a lipophilic dye that can be transferred to the exosomal membranes. These circulating B-CF3-stained EVs can be detected directly on a fluorescence spectrometer or microplate reader without resorting to any sophisticated analytical method. This liquid-biopsy format enables early detection and real-time differentiation of lesion vulnerability during AS progression, facilitating effective CVD management.

A practical guide for the preparation of C1-labeled α-amino acids using aldehyde catalysis with isotopically labeled CO2.

Isotopically carbon-labeled α-amino acids are valuable synthetic targets that are increasingly needed in pharmacology and medical imaging. Existing preparations rely on early stage introduction of the isotopic label, which leads to prohibitive synthetic costs and time-intensive preparations. Here we describe a protocol for the preparation of C1-labeled α-amino acids using simple aldehyde catalysts in conjunction with [*C]CO2 (* = 14, 13, 11). This late-stage labeling strategy is enabled by the one-pot carboxylate exchange of unprotected α-amino acids with [*C]CO2. The protocol consists of three separate procedures, describing the syntheses of (±)-[1-13C]phenylalanine, (±)-[1-11C]phenylalanine and (±)-[1-14C]phenylalanine from unlabeled phenylalanine. Although the delivery of [*C]CO2 is operationally distinct for each experiment, each procedure relies on the same fundamental chemistry and can be executed by heating the reaction components at 50-90 °C under basic conditions in dimethylsulfoxide. Performed on scales of up to 0.5 mmol, this methodology is amenable to C1-labeling of many proteinogenic α-amino acids and nonnatural derivatives, which is a breakthrough from existing methods. The synthesis of (±)-[1-13C]phenylalanine requires ~2 d, with product typically obtained in a 60-80% isolated yield (n = 3, μ = 71, σ = 8.3) with an isotopic incorporation of 70-88% (n = 18, μ = 72, σ = 9.0). Starting from the preformed imino acid (~3 h preparation time), rapid synthesis of (±)-[1-11C]phenylalanine can be completed in ~1 h with an isolated radiochemical yield of 13%. Finally, (±)-[1-14C]phenylalanine can be accessed in ~2 d with a 51% isolated yield and 11% radiochemical yield.

Can You Rely on Synthetic Labellers in Preference-Based Reinforcement Learning? It’s Complicated

Preference-based Reinforcement Learning (PbRL) enables non-experts to train Reinforcement Learning models using preference feedback. However, the effort required to collect preference labels from real humans means that PbRL research primarily relies on synthetic labellers. We validate the most common synthetic labelling strategy by comparing against labels collected from a crowd of humans on three Deep Mind Control (DMC) suite tasks: stand, walk, and run. We find that: (1) the synthetic labels are a good proxy for real humans under some circumstances, (2) strong preference label agreement between human and synthetic labels is not necessary for similar policy performance, (3) policy performance is higher at the start of training from human feedback and is higher at the end of training from synthetic feedback, and (4) training on only examples with high levels of inter-annotator agreement does not meaningfully improve policy performance. Our results justify the use of synthetic labellers to develop and ablate PbRL methods, and provide insight into how human labelling changes over the course of policy training.

Geographical indications as a labelling strategy: an empirical investigation of negative bias and its managing conditions

Purpose This study aims to examine the influence of two significant product labelling strategies (geographical indication [GI] vs country-of-origin [COO]) on shaping customer product attitude and purchase likelihood, considering consumers’ ethnocentric and cosmopolitan tendencies. The authors also investigate the boundary conditions and intervening mechanisms to manage the adverse consumer product evaluations and present mitigating procedures which reinstate favourable product evaluations and purchase likelihood. Design/methodology/approach The collected data from these all these studies were analysed using ANOVA and mediation anlaysis. The study tests the proposed hypotheses using three follow-up experimental investigations. Findings The study found that GI (vs COO) labels have a more significant impact on customers’ product evaluation and likelihood of purchase and supported the dispositional effect of ethnocentric and cosmopolitan inclinations. Further, the results indicated that self-product congruence can efficiently regulate consumer dispositions. Also, the results confirmed the significant impact of product identification on influencing consumer attitudes. Practical implications The above-said insights add practical insights, particularly concerning product labelling. Also, the insights on product attitudes and purchase likelihood intricacies in the context of product labelling enable companies to comprehend better the significance of GI labels, COO labels and self-product congruence. Originality/value To the best of the authors’ knowledge, this is the first time a study has compared the role of two significant product labelling strategies (GI vs COO) in shaping customer product evaluations, confirmed its boundary conditions and shown how to transform them into helpful customer product outcomes.

Abstract 2588: Bioengineering of site-specific antibody labeling from basic research to spatial omics platforms

Abstract Over the last few years, spatial multi-omics platforms have emerged as a powerful tool for characterizing cancer biology in multiple dimensions. Notably, these systems typically rely on multiplex immunolabeling. Conventionally, multiplexing is accomplished through carefully selecting primary antibodies from different animal species, and in combination with their corresponding polyclonal secondary antibodies. However, given the practical complication related to the species availability of primary antibodies, the multiplexing labeling is still under constraint due to the necessity for matched secondary species labels and the availability. For decades, non-specific labeling of primary antibodies through amine- or thiol-reactive chemistries was widely performed. Evolving research and commercial products have sought to overcome this antibody-based multiplexing limitations by developing enzymatic reaction-directed chemical reaction or antibody targeting proteins that could contain affinity to the Fc or Fab regions of antibodies. However, these methods mentioned above have substantive limitations and side-effects on affinity, conjugation number, buffer incompatibilities, storage incompatibilities, insufficient conjugation, and uncontrolled stoichiometric labeling. Herein, we introduce an efficient, sustainable, reproducible site-specific antibody covalent labeling strategy through engineering anti-IgG secondary nanobodies. These infer the stability, high-affinity of species specific and easy-to-produce IgG binders with the permanence of controlled activation for proximity-driven intermolecular covalent conjugation, with a promise for efficient multiplexity. This labeling technology addresses antibody labeling challenges through currently available approaches, and would substantially enhance multiplexity in a wide variety of research and clinical settings. Citation Format: Kai Tao, Matthew J. Rames, MingChong Dai, Gulsu Sener, Samuel Olson, Srivathsan Ranganathan, Sila Ozdemir, Adam Oken, Michael Brasino, Randy Armstrong, Yu-Jui Chiu, Ece Eksi, Bruce Branchaud, Sadik Esener. Bioengineering of site-specific antibody labeling from basic research to spatial omics platforms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2588.

ZDHHC20-driven S-palmitoylation of CD80 is required for its costimulatory function.

CD80 is a transmembrane glycoprotein belonging to the B7 family, which has emerged as a crucial molecule in T cell modulation via the CD28 or CTLA4 axes. CD80-involved regulation of immune balance is a finely tuned process and it is important to elucidate the underlying mechanism for regulating CD80 function. In this study we investigated the post-translational modification of CD80 and its biological relevance. By using a metabolic labeling strategy, we found that CD80 was S-palmitoylated on multiple cysteine residues (Cys261/262/266/271) in both the transmembrane and the cytoplasmic regions. We further identified zDHHC20 as a bona fide palmitoyl-transferase determining the S-palmitoylation level of CD80. We demonstrated that S-palmitoylation protected CD80 protein from ubiquitination degradation, regulating the protein stability, and ensured its accurate plasma membrane localization. The palmitoylation-deficient mutant (4CS) CD80 disrupted these functions, ultimately resulting in the loss of its costimulatory function upon T cell activation. Taken together, our results describe a new post-translational modification of CD80 by S-palmitoylation as a novel mechanism for the regulation of CD80 upon T cell activation.

Towards a green and just industry? Insights from traditional leather districts in Southern Italy

Artisanal processes are crucial for examining major economic development, industrial, and historical forces. Among the different industries, fashion is regarded as one of the most polluting business activities. The indication of origin “Made in Italy” has found extensive scholarly economic appetite; however, the leather sector in its socioeconomic and environmental components has been scarcely investigated. The paper at hand analyzes selected leather poles in Campania, Italy – namely, the tanning, shoes, and gloves industries. Besides, the industrial processes and sustainability implications required are examined to render these productions. The tannery districts are characterized by a strong artisanal component in the productive processes and follow diverse geographical agglomeration rationales. Field visits and in-depth interviews were conducted in the local districts of Solofra (tanning), Grumo Nevano-Aversa (shoemaking), and Rione Sanità pole (glove-making). The local activities and specific operational industrial processes are mapped, highlighting the technical industrial phases needed to produce the three leather outputs. Besides, the sustainability repercussions of these industries are analyzed. The study finds that most of the activities heavily rely on traditional techniques and would benefit in socioeconomic and environmental terms from modernization, management, ICT upgrades, as well as process revisions and spatial agglomeration organization. Selected sectoral sustainable development, CSR, ESG, labeling, ethics, and environmental strategy recommendations are presented – especially concerning tanning wastewater treatment. These measures result in a compulsion to face the massive multidimensional crises occurring in the three sectors and business activities.

Reporting assassinations in the Ethiopian press

This paper aims at analyzing the reporting of assassinations in the Ethiopian press from a discourse analytical perspective. The study attempted to answer three questions: 1) How are assassinations represented in the press? 2) What identities are set up for those involved in the assassinations? And, finally, how is meaning communicated in various discursive structures and communicative events? To that end, the study employed Jeffrie’s critical stylistics as an analytical framework within a qualitative design. The data were collected from five Ethiopian newspapers that were selected purposively in line with predetermined criteria. A corpus of 102 media stories that were published from June 2018 to June 2020 was setup. The findings show that each outlet reported the incidents synonymously, emphasizing a scapegoating process that could ideologically reaffirm the dominant political discourse. In doing so, four naming and labeling strategies were identified: lionizing (making the dead a hero), blaming and demonizing, victimizing (making the dead innocent and martyrs), and ethnification (connecting both the victims and offenders to their ethnic belongings). Polarized representations of actions, space, time, and society were evident in the selected stories. The government, together with its different organs and affiliates, was used as the sole and primary source of information. The voices of the government on the incidents were reported as widely accepted facts, as evidenced by the blurred line between direct and indirect speeches. This in turn helped to reaffirm the existing dominant political discourse – the status quo.

Bioorthogonal Metabolic Labeling of the Virulence Factor Phenolic Glycolipid in Mycobacteria.

Surface lipids on pathogenic mycobacteria modulate infection outcomes by regulating host immune responses. Phenolic glycolipid (PGL) is a host-modulating surface lipid that varies among clinical Mycobacterium tuberculosis strains. PGL is also found in Mycobacterium marinum, where it promotes infection of zebrafish through effects on the innate immune system. Given the important role this lipid plays in the host-pathogen relationship, tools for profiling its abundance, spatial distribution, and dynamics are needed. Here, we report a strategy for imaging PGL in live mycobacteria using bioorthogonal metabolic labeling. We functionalized the PGL precursor p-hydroxybenzoic acid (pHB) with an azide group (3-azido pHB). When fed to mycobacteria, 3-azido pHB was incorporated into the cell surface, which could then be visualized via the bioorthogonal conjugation of a fluorescent probe. We confirmed that 3-azido pHB incorporates into PGL using mass spectrometry methods and demonstrated selectivity for PGL-producing M. marinum and M. tuberculosis strains. Finally, we applied this metabolic labeling strategy to study the dynamics of PGL within the mycobacterial membrane. This new tool enables visualization of PGL that may facilitate studies of mycobacterial pathogenesis.

FFLDGA-Net: Image retrieval method based on Feature Fusion Learnable Descriptor Graph Attention Network

Image retrieval aims to retrieve and return the image in the database that is most similar to the query image. However, the performance of image retrieval models is often hindered by the limited dimensionality of images, which lacks depth information about objects. To address this issue, we propose a novel image retrieval model called FFLDGA-Net (Feature Fusion-based Learnable Descriptor Graph Attention Network). This model aims to overcome the absence of depth information in images by fusing feature information from both image data and point cloud data. First, we introduce the LDGA-Net, which effectively improved the model’s ability to mine hard samples and negative samples. Then, we combine the multi-scale route convolution module with a one-dimensional path aggregation network to fuse point clouds and image features at multiple scales, and establish a high-dimensional relationship between features and low-dimensional features. To mitigate training noise, we incorporate a soft label strategy tailored to the dataset’s characteristics. Our experimental results on two benchmark datasets demonstrate the significant improvements achieved by FFLDGA-Net in image retrieval performance.

Abstract 1166 A photoaffinity labeling strategy to elucidate interactions and physiological functions of N-acyl-phosphatidylethanolamine, a unique triply acylated phospholipid

Abstract 1166 A photoaffinity labeling strategy to elucidate interactions and physiological functions of N-acyl-phosphatidylethanolamine, a unique triply acylated phospholipid

Inside Cover Picture

Plenty of advanced methods have been developed for tracing RNA, including directly chemical RNA labeling, metabolic RNA labeling, proximity‐dependent RNA labeling, etc. These RNA labeling strategies have greatly enhanced our learning about complex roles and functions of RNA. For the deeper insight of RNA biology, there is still a constant need to develop newer RNA labeling methods. More details are discussed in the article by Weng et al. on page 790—801.image

Consumer knowledge and understanding of food labelling information in Klipgat region, of South Africa

Food labels are the first source of information customers come across when sourcing a food product. Labels provide information about the ingredients, nutritional content, allergens, as well as the origin and advice on the food’s processing and preservation conditions. This information allows the consumer to make informed food choices. Although food labels are provided to help consumers choose healthy foods, it is not established whether they know and understand the information to use to their advantage. The need to comprehend consumer knowledge, understand food labelling information, and whether it could influence consumer choices are vital to researchers, policymakers, and the food industry. The study investigated the knowledge and understanding of food labelling information among Klipgat consumers. In a cross-sectional community-based study with a structured questionnaire, 400 participants were conveniently interviewed on consumer knowledge, understanding of information, and utilization of labelling information. A chi-square for the association of variables compared differences in the districts, and p-value &lt;0.05 was regarded as significantly different. Overall, 79.9% of the study group from all three regions knew that processed food must have a label. Most respondents in the three regions were males (64%). There was a general lack of knowledge about food labelling information (x2=10.726; p=0.03), especially with terms such as trans-fatty acids (23.1%), monounsaturated fat (5.3%), Recommended Dietary Allowances (RDA) (15.3%) and Genetically Modified Organism (GMO), (14.7%). Socio-demographic characteristics including gender (p=0.030), age (p=0.030), language (p=0.030) and educational level (p=0.030) were significantly associated with consumers’ knowledge and understanding of the labels. The results from this study are useful for the development of communication and awareness strategies of food labelling information, with special emphasis on the use of simpler terminologies. This paper advocates for the development of a “food labelling forum,” consisting of relevant stakeholders with a mandate to; establish, implement, and maintain food labeling strategies, community engagement and general food labeling awareness programs especially in typical communities of South Africa. Key words: communities, food labelling information, labelling terminology, consumer label understanding

Signed Fingermark Liveness Detection Method Based on Deep Residual Networks and Multimodal Decision Fusion

Fingermarks play an important role in document identification. At the same time, fingermarks on paper documents are often accompanied by signatures and background text, which introduce noise to the original fingermark textures and increase the difficulty of detection. A signed fingermark detection method based on deep residual networks and a decision-level fusion strategy was proposed to defend against spoofing attacks from fake fingermarks. Firstly, the multi-scale structure was introduced in the residual module, which improved the network’s depth and breadth without increasing the parameters. Then, the multi-probability label strategy was refined and employed to enhance the local encoding ability of the feature extraction. A score fusion strategy was designed, with weights allocated based on the difference in signed interference levels of local image blocks. Finally, a model fusion strategy based on evidence theory was suggested, which improved detection accuracy by leveraging complementarity between models. A large-scale fingermark database was established, which included real fingermarks made from real fingers and fake fingermarks made from various materials, and this was divided into two sub databases: signed and unsigned. The experimental results show that the proposed method achieves 96.16% accuracy based on the fingerprint dataset of the global liveness detection competition called LivDet2017 and achieves 99.30% accuracy based on the signed fingermark database, while it has good resistance to spoofing attacks from unknown materials.

Automatic label curation from large-scale text corpus

Abstract The topic modeling technique extracts themes based on their probabilistic measurements from any large-scale text collection. Even though topic modeling pulls out the most important phrases that describe latent themes in text collections, a suitable label has yet to be found. Interpreting the topics extracted from a text corpus and identifying a suitable label automatically reduces the cognitive load for the analyst. Extractive methods are used typically to select a label from a given candidate set, based on probability metrics for each candidate set. Some of the existing approaches use phrases, words, and images to generate labels using frequency counts of different words in the text. The paper proposes a method to generate labels automatically to represent each topic based on a labeling strategy to filter candidate labels and then apply sequence-to-sequence labelers. The objective of the method is to get a meaningful label for the result of the Latent Dirichlet Allocation algorithm. The BERTScore metric is used to evaluate the effectiveness of the proposed method. The proposed method generates good interpretative labels as compared to baseline models for topic words or terms automatically. The comparison with the label generated through ChatGPT API shows the quality of the generated label with the experiment performed on Four Datasets NIPS, Kindle, PUBMED, and CORD-19.

Glyco-Engineering Cell Surfaces by Exo-Enzymatic Installation of GlcNAz and LacNAz Motifs.

Exo-enzymatic glyco-engineering of cell-surface glycoconjugates enables the selective display of well-defined glyco-motifs bearing bioorthogonal functional groups, which can be used to study glycans and their interactions with glycan-binding proteins. In recent years, strategies to edit cellular glycans by installing monosaccharides and their derivatives using glycosyltransferase enzymes have rapidly expanded. However, analogous methods to introduce chemical reporter-functionalized type 2 LacNAc motifs have not been reported. Herein, we report the chemo-enzymatic synthesis of unnatural UDP-GlcNAc and UDP-GalNAc nucleotide-sugars bearing azide, alkyne, and diazirine functionalities on the C2-acetamido group using the mutant uridylyltransferase AGX1F383A. The unnatural UDP-GlcNAc derivatives were examined as substrates for the human GlcNAc-transferase B3GNT2, where it was found that modified donors were tolerated for transfer, albeit to a lesser extent than the natural UDP-GlcNAc substrate. When the GlcNAc derivatives were examined as acceptor substrates for the human Gal-transferase B4GalT1, all derivatives were well tolerated and the enzyme could successfully form derivatized LacNAcs. B3GNT2 was also used to exo-enzymatically install GlcNAc and unnatural GlcNAc derivatives on cell-surface glycans. GlcNAc- or GlcNAz-engineered cells were further extended by B4GalT1 and UDP-Gal, producing LacNAc- or LacNAz-engineered cells. Our proof-of-concept glyco-engineering labeling strategy is amenable to different cell types and our work expands the exo-enzymatic glycan editing toolbox to selectively introduce unnatural type 2 LacNAc motifs.

Some Results on Odd-Even Congruence Labeling of Graphs

Introduction: Labeling of graphs has been introduced in 1966. Assignment of natural numbers to vertices and/or edges is referred as graph labeling. Inspired by the ample application of graph labeling technique in real life problems, multifarious labeling strategy was adopted and investigated by many researchers.&#x0D; Objectives:Graph labeling plays a vital role in various fields and can be implemented in multitudinous discipline including coding theory, X-ray, Psychology, crystallography, circuit design, communication networks, astronomy, radar, data security, secret sharing, data base management and so on. Apart from these labeling techniques serve as a model to understand discrete mathematical domains.&#x0D; Methodology:In this paper, an attempt has been made to introduce new labeling such as odd-even congruence labeling. Congruence Graph Labeling is an allocation of natural numbers as labels for the edges and vertices of a graph based on modular arithmetic property. Odd-even congruence labeling is an allocation of odd integers to vertices and even integers to edges in addition to congruence graph labeling.&#x0D; Result: The suggested labeling has been identified on complete bipartite graph, comb graph and spliting graph of a star graph. Further, it is proved that graph acquired by connecting two copies of even cycle Cr by a path Pt, K1,t⊗P2 and D2 (Pt) are odd-even congurence graph.