Labeling Strategy Research Articles

Long‐Term Single‐Molecule Tracking in Living Cells Using Weak‐Affinity Protein Labeling

Single‐particle tracking (SPT) has become a powerful tool to monitor the dynamics of membrane proteins in living cells. However, permanent labeling strategies for SPT suffer from photobleaching as a major limitation, restricting observation times, and obstructing the study of long‐term cellular processes within single living cells. Here, we use exchangeable HaloTag Ligands (xHTLs) as an easy‐to‐apply labeling approach for live‐cell SPT and demonstrate extended observation times of individual live cells of up to 30 minutes. Using the xHTL/HaloTag7 labeling system, we measure the ligand‐induced activation kinetics of the epidermal growth factor receptor (EGFR) in single living cells. We generate spatial maps of receptor diffusion in cells, report non‐uniform distributions of receptor activation, and the formation of spatially confined ‘hot spots’ of EGFR activation. Furthermore, we measured the mobility of the ER‐luminal protein calreticulin in living cells and found diffusion coefficients that correlated with the ER nano‐structure. This approach represents a general strategy to monitor protein dynamics in a functional context and for extended observation times in single living cells.

Farm characteristics determine why a large share of organically produced wine is not labelled as organic

Abstract Organic agricultural production is increasing globally and is of high policy relevance, particularly in Europe. Various measures incentivize farmers to adopt organic practices, such as direct payments and labelling. We here address a rarely considered aspect of organic production, that not all organic producers in Europe opt for organic labelling for their products at the point of sale. We investigate the discrepancy between organic production and labelling in Swiss viticulture. Out of 115 grapevine growers who adhere to organic principles in production, 43.5% do not use organic labelling when marketing their wines. We find that especially farms using alternative labelling strategies (e.g. for fungus-resistant varieties), smaller farms and farms less specialized in viticulture to be more likely to forgo organic labelling. We draw conclusions for policy and science. For example, our findings show that there may be, for some crops, more organic products on shelves than indicated from sales statistics of organically labelled products. The use of statistics that indicate the share of sales of organic products for specific products and food sales at large may thus be misleading.

Long-TermSingle-Molecule Tracking in Living Cells Using Weak-Affinity Protein Labeling.

Single-particle tracking (SPT) has become a powerful tool to monitor the dynamics of membrane proteins in living cells. However, permanent labeling strategies for SPT suffer from photobleaching as a major limitation, restricting observation times, and obstructing the study of long-term cellular processes within single living cells. Here, we use exchangeable HaloTag Ligands (xHTLs) as an easy-to-apply labeling approach for live-cell SPT and demonstrate extended observation times of individual live cells of up to 30 minutes. Using the xHTL/HaloTag7 labeling system, we measure the ligand-induced activation kinetics of the epidermal growth factor receptor (EGFR) in single living cells. We generate spatial maps of receptor diffusion in cells, report non-uniform distributions of receptor activation, and the formation of spatially confined 'hot spots' of EGFR activation. Furthermore, we measured the mobility of the ER-luminal protein calreticulin in living cells and found diffusion coefficients that correlated with the ER nano-structure. This approach represents a general strategy to monitor protein dynamics in a functional context and for extended observation times in single living cells.

Interpreter-Mediated Diplomatic Discourse Represented and Reframed in Global News: A Case Study of China’s Statement at the General Debate of the 75th Session of United Nations General Assembly

Abstract In 2020, against the backdrop of the pandemic, climate change and the increasingly tense global situation, Chinese President Xi Jinping delivered a speech at the General Debate of the 75th Session of United Nations General Assembly (UNGA), which attracted extensive media coverage. This research employs corpus-based critical discourse analysis to explore how the Chinese original discourse was mediated by the interpreter and how the interpreter-mediated discourse was further represented and reframed by global news. The lenses of optional shifts and reframing are adopted respectively for intertextual analysis. Results indicate that the interpreter mediates the Statement through explicitation of information, reduction of information, explicitation of logic, and change of voice. Furthermore, the interpreted text and optional shifts within the text are generally well received by global news outlets. However, due to news outlets’ highly selective quotation process and the use of temporal and spatial framing and labelling strategies, the interpreted text may be reframed to construct narratives unexpected by China. This study sheds light on the dynamic process of international communication of diplomatic discourse, during which both the interpreter and global media outlets play crucial roles apart from the source speaker.

Highly Tunable, Nanomaterial-Functionalized Structural Templating of Intracellular Protein Structures Within Biological Species.

Inside living organisms, proteins are self-assembled into diverse 3D structures optimized for specific functions. This structure-function relationship can be exploited to synthesize functional materials through biotemplating and depositing functional materials onto protein structures. However, conventional biotemplating faces limitations due to the predominantly intracellular existence of proteins and associated challenges in achieving tunability while preserving functionality. In this study, Conversion to Advanced Materials via labeled Biostructures (CamBio), an integrated biotemplating platform that involves labeling target protein structures with antibodies followed by the growth of functional materials, ensuring outstanding nanostructure tunability is proposed. Protein-derived plasmonic nanostructures created by CamBio can serve as precise quantitative tools for assessing target species is demonstrated. The assessment is achieved through highly tunable and efficient surface-enhanced Raman spectroscopy (SERS). CamBio enables the formation of dense nanogap hot spots among metal nanoparticles, templated by diverse fibrous proteins comprising densely repeated monomers. Furthermore, iterative antibody labeling strategies to adjust the antibody density surrounding targets, amplifying the number of nanogaps and consequently improving SERS performance are employed. Finally, cell-patterned substrates and whole meat sections as SERS substrates, confirming their easily accessible, cost-effective, scalable preparation capabilities and dimensional tunability are incorporated.

Quantitative detection of pseudouridine in RNA by mass spectrometry.

Pseudouridine (Ψ) is one of the most prevalent and dynamic modification in RNA, and was shown to evade the host immune response in mRNA vaccines. Despite its significance, the biological role of Ψ remains poorly understood as certain key limitations and challenges in the detection of Ψ are yet to be overcome. In account of this, we report the usage of a chemical labelling strategy for the first quantitative detection of Ψ by mass spectrometry. We demonstrate a labelling efficiency exceeding 99% in isolated yeast tRNAs hosting multiple Ψs. LC-MS/MS analysis enables precise mapping of Ψ at single-base resolution, while simultaneously capturing a wide array of additional post-transcriptional modifications, which is not achieved with current sequencing technologies. This advancement may help unravel the dynamics and biological implications of Ψ, shedding light on its interplay with other modifications and deepening our understanding of its functional role.

Improvement of Electric Fish Optimization Algorithm for Standstill Label Combined with Levy Flight Strategy

The Electric Fish Optimization (EFO) algorithm is inspired by the predation behavior and communication of weak electric fish. It is a novel meta-heuristic algorithm that attracts researchers because it has few tunable parameters, high robustness, and strong global search capabilities. Nevertheless, when operating in complex environments, the EFO algorithm encounters several challenges including premature convergence, susceptibility to local optima, and issues related to passive electric field localization stagnation. To address these challenges, this study introduces Adaptive Electric Fish Optimization Algorithm Based on Standstill Label and Level Flight (SLLF-EFO). This hybrid approach incorporates the Golden Sine Algorithm and good point set theory to augment the EFO algorithm’s capabilities, employs a variable-step-size Levy flight strategy to efficiently address passive electric field localization stagnation problems, and utilizes a standstill label strategy to mitigate the algorithm’s tendency to fall into local optima during the iterative process. By leveraging multiple solutions to optimize the EFO algorithm, this framework enhances its adaptability in complex environments. Experimental results from benchmark functions reveal that the proposed SLLF-EFO algorithm exhibits improved performance in complex settings, demonstrating enhanced search speed and optimization accuracy. This comprehensive optimization not only enhances the robustness and reliability of the EFO algorithm but also provides valuable insights for its future applications.

Selective Methods Promote Protein Solid-State NMR.

Solid-state nuclear magnetic resonance (ssNMR) is indispensable for studying the structures, dynamics, and interactions of insoluble proteins in native or native-like environments. While ssNMR includes numerous nonselective techniques for general analysis, it also provides various selective methods that allow for the extraction of precise details about proteins. This perspective highlights three key aspects of selective methods: selective signals of protein segments, selective recoupling, and site-specific insights into proteins. These methods leverage protein topology, labeling strategies, and the tailored manipulation of spin interactions through radio frequency (RF) pulses, significantly promoting the field of protein ssNMR. With ongoing advancements in higher magnetic fields and faster magic angle spinning (MAS), there remains an ongoing need to enhance the selectivity and efficiency of selective ssNMR methods, facilitating deeper atomic-level insights into complex biological systems.

Transition Metal Catalyzed Deuteration via Hydrogen Isotope Exchange

Direct hydrogen isotope exchange represents a distinctive strategy for deuterium labelling, where the protium is directly replaced by deuterium. In this graphic review, we summarized the progress in deuteration via transition metal catalyzed hydrogen isotope exchange. The review was organized according to the mechanism of C-H bond activation in the homogeneous catalysis, and the heterogeneous catalysis was also discussed according to the catalyst type. Representative mechanistic processes were depicted, and proven cases for tritiation were also highlighted.

Tracking Small Extracellular Vesicles Using a Minimally Invasive PicoGreen Labeling Strategy.

Extracellular vesicles (EVs) are cell-secreted lipid bilayer delimited particles that mediate cellular communication. These tiny sacs of cellular information play an important role in cell communication and alter the physiological process under both normal and pathological conditions. As such, tracking EVs can provide valuable information regarding the basic understanding of cell communication, the onset of early malignancy, and biomarker discovery. Most of the current EV-tracking strategies are invasive, altering the natural characteristics of EVs by modifying the lipid bilayer with lipophilic dyes or surface proteins with fluorescent reporters. The invasive labeling strategies could alter the natural processes of EVs and thereby have major limitations for functional studies. Here, we report an alternative minimally invasive EV labeling strategy using PicoGreen (PG), a small molecule that fluoresces at 520 nm when bound to dsDNA. We show that PG binds to dsDNA associated with small EVs (50-200 nm), forming a stable and highly fluorescent PG-DNA complex in EVs (PG-EVs). In both 2D cell culture and 3D organoid models, PG-EV showed efficient tracking properties, including a high signal-to-noise ratio, time- and concentration-dependent uptake, and the ability to traverse a 3D environment. We further validated PG-EV tracking using dual-labeled EVs following two orthogonal labeling strategies: (1) Bioconjugation via surface amine labeling and (2) donor cell engineering via endogenously expressing mCherry-tetraspanin (CD9/CD63/CD81) reporter proteins. Our study has shown the feasibility of using PG-EV as an effective EV tracking strategy that can be applied for studying the functional role of EVs across multiple model systems.

Dual-Fluorescent Quantum Dot Nanobead-Based Lateral Flow Immunoassay for Simultaneous Detection of C-Reactive Protein and Procalcitonin.

Simultaneous detection of C-reactive protein (CRP) and procalcitonin (PCT) at the point of care is crucial for the management of infections in patients with inflammation and in critical care settings. The challenge of detecting high concentrations of CRP alongside low concentrations of PCT in plasma from inflammatory patients has limited the clinical application of multiplexed immunoassays. Herein, we developed a lateral flow immunoassay (LFIA) that employs quantum dot nanobeads (QDNBs) of varying sizes and colors to enable the simultaneous quantification of PCT and CRP in human plasma. To extend the dynamic range of CRP detection, we combined QDNBs with smaller particle sizes with the CRP detection antibodies, thereby increasing the assay's dynamic range and reducing the hook effect. At the same time, the stronger fluorescence emitted by these larger QDNBs, in conjugation with the PCT detection antibodies, allows for the detection of PCT at the nanogram level, meeting the demand for high sensitivity. The results show that this method can detect CRP concentrations from 0.1 to 3 mg/L and PCT with a detection limit of 0.09 ng/mL, which is on par with clinically used methods. By employing this dual-color and dual-size QDNB labeling strategy, we successfully achieved simultaneous detection of CRP with a broad dynamic range and PCT with high sensitivity in a one-step point-of-care rapid test.

Fluorine Labeling and 19F NMR Spectroscopy to Study Biological Molecules and Molecular Complexes

High‐resolution nuclear magnetic resonance (NMR) spectroscopy represents a key methodology for studying biomolecules and their interplay with other molecules. Recent developments in labeling strategies have made it possible to incorporate fluorine into proteins and peptides reliably, with manageable efforts and, importantly, in a highly site‐specific manner. Paired with its excellent NMR spectroscopic properties and absence in most biological systems, fluorine has enabled scientists to investigate a rather wide range of scientific objectives, including protein folding, protein dynamics and drug discovery. Furthermore, NMR spectroscopic experiments can be conducted in complex environments, such as cell lysate or directly inside living cells. This review presents selected studies demonstrating how 19F NMR spectroscopic approaches enable to contribute to the understanding of biomolecular processes. Thereby the focus has been set to labeling strategies available and specific NMR experiments performed to answer the underlying scientific objective.

Achieving enhanced diagnostic precision in endometrial lesion analysis through a data enhancement framework.

The aim of this study was to enhance the precision of categorization of endometrial lesions in ultrasound images via a data enhancement framework based on deep learning (DL), through addressing diagnostic accuracy challenges, contributing to future research. Ultrasound image datasets from 734 patients across six hospitals were collected. A data enhancement framework, including image features cleaning and soften label, was devised and validated across multiple DL models, including ResNet50, DenseNet169, DenseNet201, and ViT-B. A hybrid model, integrating convolutional neural network and transformer architectures for optimal performance, to predict lesion types was developed. Implementation of our novel strategies resulted in a substantial enhancement in model accuracy. The ensemble model achieved accuracy and macro-area under the receiver operating characteristic curve values of 0.809 of 0.911, respectively, underscoring the potential for use of DL in endometrial lesion ultrasound image classification. We successfully developed a data enhancement framework to accurately classify endometrial lesions in ultrasound images. Integration of anomaly detection, data cleaning, and soften label strategies enhanced the comprehension of lesion image features by the model, thereby boosting its classification capacity. Our research offers valuable insights for future studies and lays the foundation for creation of more precise diagnostic tools.

Enhancing De Novo Protein Sequencing through the C-Terminal Labeling Strategy: Resolving Isobaric Ambiguities by Electron-Transfer/Higher Energy Collision Dissociation (EThcD).

De novo protein sequencing via a bottom-up approach requires various proteases to produce overlapping peptides. However, peptides generated by proteases other than trypsin, LysC, and ArgC often yield C-terminal fragments with suboptimal ionization in positive mode mass spectrometry (MS). This study introduces a novel peptide labeling strategy that involves modifying peptides at the C-terminal and at the carboxyl groups of Aspartic and Glutamic acid with arginine methyl ester (R-met) to improve peptide fragmentation and resolve isobaric ambiguities encountered during sequencing. An amidation reaction is used with coupling reagents to conjugate R-met to the peptide's C-terminal end, introducing a functional group that enhances the detectability of C-terminal peptide fragment ions by mass spectrometry. Subsequently, selecting a charge state of +2 or higher can facilitate optimal fragmentation of the derivatized peptides using electron-transfer/higher energy collision dissociation (EThcD), thereby generating essential w-ions to resolve common isobaric ambiguities. Demonstrating this strategy across diverse protein types, including albumin and antibodies and using different proteases for digestion, highlights the unique characteristics of combining the proposed amidation reaction with the specific proteases tested.

Clean label extraction of bioactive compounds from Chenopodium album and their role in the characterization and stability of ostrich meat

The demand for clean-label products continues to rise, as consumers increasingly prioritize natural and transparent ingredient lists. Natural substances are generally deemed safe for consumption by consumers. This study was focused on the development of clean-label ostrich meat patties with Chenopodium album extract and their storage stability. To prepare C. album extract, microwave-assisted extraction (MAE) and ultrasound-assisted extraction (UAE) were employed. Ostrich meat patties were prepared using diverse combinations of extract, including 1% UAE, 2% UAE, 1% MAE, 2% MAE, 0.5% UAE+0.5% MAE, and 1% UAE + 1% MAE. The highest pH was observed for MAE in T3 on the 14th day (6.19 ± 0.03). The L* value was observed between 39.12 ± 1.09 and 44.00 ± 1.1. As storage intervals passed, the a* and b* values of ostrich meat patties decreased. After the 14th day of storage, the best results were obtained from 2% UAE (T2), with the lowest TBRAS, Peroxide value (POV), and Total of volatile basic nitrogen (TVBN) readings recorded for T2 (0.74 ± 0.02 MDA/kg, 0.56 ± 0.01 meq peroxide/kg, and 6.28 ± 0.40 mg/100 mL, respectively). At the end of the storage study, the lowest Total Microbial Count (TMC) and coliform count were recorded for T2 (8.08 ± 0.03 and 4.97 ± 0.05 cfu/mL, respectively). At the end of the storage study, T2 exhibited the highest values for total phenolic content (TPC), diphenyl-1-picrylhydrazyl (DPPH), Ferric reducing antioxidant power (FRAP), and azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assay, namely of T2 122 ± 0.28 mg GAE/100 g, 73 ± 0.27%, 5.9 ± 0.01 mmol FSE/100 g, and 83 ± 0.08 mmol/L, respectively. The current study concludes that the UAE extract of C. album incorporated into ostrich meat patties manifests improved safety, quality, and storage stability. The implementation of clean label strategies can facilitate food manufacturers to align with consumer preferences for product transparency and sustainability while ensuring product safety and quality.

Quantitative proteomics and phosphoproteomics profiling of meiotic divisions in the fission yeast Schizosaccharomyces pombe

In eukaryotes, chromosomal DNA is equally distributed to daughter cells during mitosis, whereas the number of chromosomes is halved during meiosis. Despite considerable progress in understanding the molecular mechanisms that regulate mitosis, there is currently a lack of complete understanding of the molecular mechanisms regulating meiosis. Here, we took advantage of the fission yeast Schizosaccharomyces pombe, for which highly synchronous meiosis can be induced, and performed quantitative proteomics and phosphoproteomics analyses to track changes in protein expression and phosphorylation during meiotic divisions. We compared the proteomes and phosphoproteomes of exponentially growing mitotic cells with cells harvested around meiosis I, or meiosis II in strains bearing either the temperature-sensitive pat1-114 allele or conditional ATP analog-sensitive pat1-as2 allele of the Pat1 kinase. Comparing pat1-114 with pat1-as2 also allowed us to investigate the impact of elevated temperature (25 °C versus 34 °C) on meiosis, an issue that sexually reproducing organisms face due to climate change. Using TMTpro 18plex labeling and phosphopeptide enrichment strategies, we performed quantification of a total of 4673 proteins and 7172 phosphosites in S. pombe. We found that the protein level of 2680 proteins and the rate of phosphorylation of 4005 phosphosites significantly changed during progression of S. pombe cells through meiosis. The proteins exhibiting changes in expression and phosphorylation during meiotic divisions were represented mainly by those involved in the meiotic cell cycle, meiotic recombination, meiotic nuclear division, meiosis I, centromere clustering, microtubule cytoskeleton organization, ascospore formation, organonitrogen compound biosynthetic process, carboxylic acid metabolic process, gene expression, and ncRNA processing, among others. In summary, our findings provide global overview of changes in the levels and phosphorylation of proteins during progression of S. pombe cells through meiosis at normal and elevated temperatures, laying the groundwork for further elucidation of the functions and importance of specific proteins and their phosphorylation in regulating meiotic divisions in this yeast.

Impact of site-specific conjugation strategies on the pharmacokinetics of antibody conjugated radiotherapeutics

Antibody radionuclide conjugates are an emerging modality for targeted imaging and potent therapy of disseminated disease. Coupling of radionuclides to monoclonal antibodies (mAbs) is typically achieved by applying non-site-specific labelling techniques. With the ambition of reducing variability, increasing labelling efficacy and stability, several site-specific conjugation strategies have been developed in recent years for toxin- and fluorophore-mAb conjugates. In this study, we studied two site-specific labelling strategies for the conjugation of the macrocyclic chelating agent, DOTA, to the anti-Leucine Rich Repeat Containing 15 (LRRC15) mAb DUNP19. Specifically, one approach utilized a DOTA-bearing peptide (FcIII) with a strong affinity for the fragment crystallizable (Fc) domain of the human IgG1 of DUNP19 (DUNP19LF-FcIII-DOTASS), while the other leveraged a chemo-enzymatic technique to substitute the N-linked bi-antennary oligosaccharides in the human IgG1 Fc domain with DOTA (DUNP19LF-gly-DOTASS). To assess if these methods impact the antibody's binding properties and targeting efficacy, comparative in vitro and in vivo studies of the generated DUNP19-conjugates were performed. While the LRRC15 binding of both radioimmunoconjugates remained intact, the conjugation methods had different impacts on their abilities to interact with FcRn and FcγRs. In vitro assessments of DUNP19LF-FcIII-DOTASS and DUNP19LF-gly-DOTASS demonstrated markedly decreased affinity for FcRn and FcγRIIIa (CD16), respectively. DUNP19LF-FcIII-DOTASS demonstrated increased blood and tissue kinetics in vivo, confirming loss of FcRn binding. While the ablated FcγR interaction of DUNP19LF-gly-DOTASS had no immediate impact on in vivo biodistribution, reduced immunotherapeutic effect can be expected in future studies as a result of reduced NK-cells interaction. In conclusion, our findings underscore the necessity for meticulous consideration and evaluation of mAb labelling strategies, extending beyond mere conjugation efficiency and radiolabeling yields. Notably, site-specific labelling methods were found to significantly influence the immunological impact of Fc interactions. Therefore, it is of paramount importance to consider the intended diagnostic or therapeutic application of the construct and to adopt conjugation strategies that ensure the preservation of critical pharmacological properties and functionality of the antibody in use.

A Fluorogenic Chemogenetic pH Sensor for Imaging Protein Exocytosis.

Fluorescent protein-based pH biosensors enable the tracking of pH changes during protein trafficking and, in particular, exocytosis. The recent development of chemogenetic reporters combining synthetic fluorophores with self-labeling protein tags offers a versatile alternative to fluorescent proteins that combines the diversity of chemical probes and indicators with the selectivity of the genetic encoding. However, this hybrid protein labeling strategy does not avoid common drawbacks of organic fluorophores such as the risk of off-target signal due to unbound molecules. Here, we describe a novel fluorogenic and chemogenetic pH sensor based on a cell-permeable molecular pH indicator called pHluo-Halo-1, whose fluorescence can be locally activated in cells by reaction with HaloTag, ensuring excellent signal selectivity in wash-free imaging experiments. pHluo-Halo-1 was selected out of a series of four fluorogenic molecular rotor structures based on protein chromophore analogues. It displays good pH sensitivity with a pKa of 6.3 well-suited to monitor pH variations during exocytosis and an excellent labeling selectivity in cells. It was applied to follow the secretion of CD63-HaloTag fusion proteins using TIRF microscopy. We anticipate that this strategy based on the combination of a tunable and chemically accessible fluorogenic probe with a well-established protein tag will open new possibilities for the development of versatile alternatives to fluorescent proteins for elucidating the dynamics and regulatory mechanisms of proteins in living cells.

Site-Specific Location of Black Phosphorus Quantum Dot Cluster-Based Nanocomplexes for Synergistic Ion Channel Therapy and Hypoxic Microenvironment Activated Chemotherapy.

The spatiotemporal regulation of ion transport in living cell membrane channels has immense potential for providing novel therapeutic approaches for the treatment of currently intractable diseases. So far, most strategies suffer from uncontrolled ion transport and limited tumor therapy effects. On the premise of low toxicity to healthy tissues, enhancing the degree of ion overloading and the effect of tumor treatment still remains a challenging concern. Herein, an innovative strategy for synergistic ion channel therapy and hypoxic microenvironment activated chemotherapy is proposed. Biocompatible AQ4N/black phosphorus quantum dot clusters@liposomes (AQ4N/BPCs@Lip) nanocomplexes are site-specifically immobilized on the living cell membrane by a metabolic labeling strategy, eliminating the need for modifying or genetically encoding channel structures. Ascribing to the localized temperature increase of BPCs under NIR light irradiation, Ca2+ overinflux can be remotely controlled and the overloading degree was increased; moreover, the local released AQ4N can only be activated in the tumor cell, while it has no toxicity to normal cells. Compared with single intracellular Ca2+ overloading, the tumor cell viabilities decrease 2-fold with synergetic Ca2+ overloading-induced ion channel therapy and hypoxic microenvironment activated chemotherapeutics. Our study demonstrates the example of a remote-controlled ion influx and drug delivery system for tumor therapy.

Optimizing Object Detection Algorithms for Congenital Heart Diseases in Echocardiography: Exploring Bounding Box Sizes and Data Augmentation Techniques.

Congenital heart diseases (CHDs), particularly atrial and ventricular septal defects, pose significant health risks and common challenges in detection via echocardiography. Doctors often employ the cardiac structural information during the diagnostic process. However, prior CHD research has not determined the influence of including cardiac structural information during the labeling process and the application of data augmentation techniques. This study utilizes advanced artificial intelligence (AI)-driven object detection frameworks, specifically You Look Only Once (YOLO)v5, YOLOv7, and YOLOv9, to assess the impact of including cardiac structural information and data augmentation techniques on the identification of septal defects in echocardiographic images. The experimental results reveal that different labeling strategies substantially affect the performance of the detection models. Notably, adjustments in bounding box dimensions and the inclusion of cardiac structural details in the annotations are key factors influencing the accuracy of the model. The application of deep learning techniques in echocardiography enhances the precision of detecting septal heart defects. This study confirms that careful annotation of imaging data is crucial for optimizing the performance of object detection algorithms in medical imaging. These findings suggest potential pathways for refining AI applications in diagnostic cardiology studies.