Labeling Technique Research Articles

Trx4, a novel thioredoxin protein, is important for Toxoplasma gondii fitness

BackgroundTo successfully replicate within the host cell, Toxoplasma gondii employs several mechanisms to overcome the host cell defenses and mitigate the harmful effects of the free radicals resulting from its own metabolic processes using effectors such as thioredoxin proteins. In this study, we characterize the location and functions of a newly identified thioredoxin in T. gondii, which was named Trx4.MethodsWe characterized the functional role of Trx4 in T. gondii Type I RH and Type II Pru strains by gene knockout and studied its subcellular localization by endogenous protein HA tagging using CRISPR-Cas9 gene editing. The enzyme-catalyzed proximity labeling technique, the TurboID system, was employed to identify the proteins in proximity to Trx4.ResultsTrx4 was identified as a dense granule protein of T. gondii predominantly expressed in the parasitophorous vacuole (PV) and was partially co-localized with GRA1 and GRA5. Functional analysis showed that deletion of trx4 markedly influenced the parasite lytic cycle, resulting in impaired host cell invasion capacity in both RH and Pru strains. Mutation of Trx domains in Trx4 in RH strain revealed that two Trx domains were important for the parasite invasion. By utilizing the TurboID system to biotinylate proteins in proximity to Trx4, we identified a substantial number of proteins, some of which are novel, and others are previously characterized, predominantly distributed in the dense granules. In addition, we uncovered three novel proteins co-localized with Trx4. Intriguingly, deletion of trx4 did not affect the localization of these three proteins. Finally, a virulence assay demonstrated that knockout of trx4 resulted in a significant attenuation of virulence and a significant reduction in brain cyst loads in mice.ConclusionsTrx4 plays an important role in T. gondii invasion and virulence in Type I RH strain and Type II Pru strain. Combining the TurboID system with CRISPR-Cas9 technique revealed many PV-localized proximity proteins associated with Trx4. These findings suggest a versatile role of Trx4 in mediating the processes that occur in this distinctive intracellular membrane-bound vacuolar compartment.Graphical

Proximity-Based Labeling Identifies MHC Class II and CD37 as B Cell Receptor-Proximal Proteins with Immunological Functions.

The BCR allows for Ag-driven B cell activation and subsequent Ag endocytosis, processing, and presentation to recruit T cell help. Core drivers of BCR signaling and endocytosis are motifs within the receptor's cytoplasmic tail (primarily CD79). However, BCR function can be tuned by other proximal cellular elements, such as CD20 and membrane lipid microdomains. To identify additional proteins that could modulate BCR function, we used a proximity-based biotinylation technique paired with mass spectrometry to identify molecular neighbors of the murine IgM BCR. Those neighbors include MHC class II molecules, integrins, various transporters, and membrane microdomain proteins. Class II molecules, some of which are invariant chain-associated nascent class II, are a readily detected BCR neighbor. This finding is consistent with reports of BCR-class II association within intracellular compartments. The BCR is also in close proximity to multiple proteins involved in the formation of membrane microdomains, including CD37, raftlin, and Ig superfamily member 8. Known defects in T cell-dependent humoral immunity in CD37 knockout mice suggest a role for CD37 in BCR function. In line with this notion, CRISPR-based knockout of CD37 expression in a B cell line heightens BCR signaling, slows BCR endocytosis, and tempers formation of peptide-class II complexes. These results indicate that BCR molecular neighbors can impact membrane-mediated BCR functions. Overall, a proximity-based labeling technique allowed for identification of multiple previously unknown BCR molecular neighbors, including the tetraspanin protein CD37, which can modulate BCR function.

The role of quiescent thymic progenitors in TAL/LMO2-induced T-ALL chemotolerance

Relapse in T-cell acute lymphoblastic leukemia (T-ALL) may signify the persistence of leukemia-initiating cells (L-ICs). Ectopic TAL1/LMO expression defines the largest subset of T-ALL, but its role in leukemic transformation and its impact on relapse-driving L-ICs remain poorly understood. In TAL1/LMO mouse models, double negative-3 (DN3; CD4−CD8−CD25+CD44−) thymic progenitors harbored L-ICs. However, only a subset of DN3 leukemic cells exhibited L-IC activity, and studies linking L-ICs and chemotolerance are needed. To investigate L-IC heterogeneity, we used mouse models and applied single-cell RNA-sequencing and nucleosome labeling techniques in vivo. We identified a DN3 subpopulation with a cell cycle–restricted profile and heightened TAL1/LMO2 activity, that expressed genes associated with stemness and quiescence. This dormant DN3 subset progressively expanded throughout leukemogenesis, displaying intrinsic chemotolerance and enrichment in genes linked to minimal residual disease. Examination of TAL/LMO patient samples revealed a similar pattern in CD7+CD1a− thymic progenitors, previously recognized for their L-IC activity, demonstrating cell cycle restriction and chemotolerance. Our findings substantiate the emergence of dormant, chemotolerant L-ICs during leukemogenesis, and demonstrate that Tal1 and Lmo2 cooperate to promote DN3 quiescence during the transformation process. This study provides a deeper understanding of TAL1/LMO-induced T-ALL and its clinical implications in therapy failure.

No-tillage with straw mulching restrained the vertical transportation of chemical fertilizer N and reduced its leaching loss in Northeast China

Intensified by the pursuit of food security, nitrogen (N) source pollution caused by excessive chemical N fertilizer application has emerged as a major environmental threat, especially through nitrate N (NO3--N) leaching. While no-tillage with straw mulching is recognized for mitigating NO3--N leaching from chemical fertilizer N, its efficacy in deep soil layers remains unclear. Thus, employing the 15N isotope labeling technique in Northeast China's black soil, we investigated the impact of no-tillage and/or straw mulching on the transformation, vertical transport, and leaching loss of fertilizer N under five treatments: conventional ridge tillage (RT), and no-tillage with varying straw coverages (NT-0, NT-33, NT-67, and NT-100). Our results revealed that over 98.3% of fertilizer-derived mineral N in the soil was NO3--N, with substantial downward movement beyond 120 cm, posing a leaching risk. Three years after N fertilizer application, no-tillage and/or straw mulching with varying coverages significantly reduced fertilizer-derived NO3--N by averaging 36.3% in 0–300 cm soil profile, compared to RT with 18.36 kg ha−1 fertilizer-derived NO3--N in soil. Notably, no-tillage and/or straw mulching of 33%, 67%, and 100% coverages effectively decelerated the vertical transport of fertilizer-derived NO3--N to 140–220 cm soil deeper layers by averaging 48.4%, where NO3--N accumulates in large quantities. The percentages of fertilizer-derived NO3--N leached to applied fertilizer N varied from 3.7% to 7.2% after three years of vertical migration. No-tillage with different straw coverages remarkably decreased this leaching percentage by 42.7% and 21.9% compared with RT and NT-0, respectively. Furthermore, we found that no-tillage with straw mulching enhanced fertilizer N utilization efficiency (NUE) and crop yields with NT-33, NT-67, and NT-100 demonstrating higher accumulative NUE of 58.4%, 56.2%, and 58.8% and average yields of 13.90, 13.48, and 13.21 Mg ha−1, respectively. Therefore, we preliminarily suggest that implementing no-tillage and straw mulching with 33% and 100% coverages in Northeast China holds promise for simultaneously enhancing crop yields and NUE, and mitigating N fertilizer leaching in the form of NO3--N. These findings offer valuable insights for optimizing field management and mitigating N pollution in agriculture, contributing to the achievement of sustainable agricultural development.

Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds.

Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex environments. In this context, the present study focuses on developing an ordinal classification model in forest areas where LiDAR point clouds can be classified into four distinct ordinal classes: ground, low vegetation, medium vegetation, and high vegetation. To do so, an effective soft labeling technique based on a novel proposed generalized exponential function (CE-GE) is applied to the PointNet network architecture. Statistical analyses based on Kolmogorov-Smirnov and Student's t-test reveal that the CE-GE method achieves the best results for all the evaluation metrics compared to other methodologies. Regarding the confusion matrices of the best alternative conceived and the standard categorical cross-entropy method, the smoothed ordinal classification obtains a more consistent classification compared to the nominal approach. Thus, the proposed methodology significantly improves the point-by-point classification of PointNet, reducing the errors in distinguishing between the middle classes (low vegetation and medium vegetation).

Integrated isotopic labeling analysis unveils precise proportions of ammonia emissions during composting

Despite considerable research on ammonia emissions in composting, the precise proportion of these emissions remains undetermined through established technological methods. This study employs stable isotopic labeling techniques in conjunction with microbial sequencing and quantitative analysis of functional genes to assess the precise contribution and underlying causes of nitrogen loss. The results from tracking isotopic labeled amino acids reveal changes and emission characteristics in the initial nitrogen state of amino acids during composting. The most significant finding is the total nitrogen loss in composting, which amounts to 33.75 %. Within this, 21.31% is lost in the form of ammonia emissions, and 12.44 % is lost through leachate runoff. Statistical analysis of 15N in the compost pile indicates that the thermophilic stage is the primary phase for ammonia emissions. During this stage, the ammonia emission rate is 17.09% of the initial total nitrogen, constituting 80.20% of the overall ammonia emissions throughout the entire composting process. Similarly, liquid nitrogen loss exhibits the same trend. Microbiological analysis substantiates this conclusion, indicating that the reduction in ammonium ion conversion functionality (amoA gene) during the thermophilic stage leads to a significant volatilization of ammonia. The findings of this study contribute to an enhanced understanding of nitrogen loss in compost management, providing valuable insights for effective nitrogen conservation practices in composting.

THE NO TRAIN NO GAIN SYSTEM FOR O-COCOSDA AND VLSP 2022 - A-MSV SHARED TASK: ASIAN MULTILINGUAL SPEAKER VERIFICATION

This paper proposes a semi-supervised multilingual speaker verification (MSV) system submitted for the 2 tasks, MSV for the Asian language inside the training set (T01) and outside the training set (T02) in O-COCOSDA and VLSP challenge 2022.To solve the problem, our strategy is training a baseline acoustic model with given labeled data (MSV CommonVoice) andfine-tuning the trained acoustic model with both given labeled data and given unlabeled data (MSV Youtube). To achieve the fine-tuning step, the unlabeled data is converted to labeled data by pseudo labeling technique using the clustering method with the embedding vectors extracted from the trained acoustic model. Besides, we also apply test-time augmentation, back-end scoring, and score normalization with the AS-Norm technique to improve the result. When evaluated on the VLSP 2022 challenge's given test set, our best system with baseline ECAPA-TDNN achieves an equal error rate (EER) of 2.296% in T01 and 3.3296% in T02, which ranks second rank in both two tasks.

A Novel 3D Multi-Layer Convolutional Neural Networks for Lung Cancer Segmentation in CT Images

Background/Objectives: A novel three-dimensional efficient Multi-Layer Convolutional Neural Network (3D-MLCNN) is proposed for detecting lung tumors accurately using Computerized Tomography (CT) lung tumor images. The proposed K-means segmentation algorithm for labeling the tumor region automatically. This proposed K-means segmentation algorithm automatically labels the tumor regions to process with the 3D MLCNN model to predict tiny tumors and extract tumor regions accurately. Methods: The proposed 3DMLCNN network goal is to extract the tumor region in CT lung images to classify the lung tumor volume by pixel-wise segmentation model. Findings: The proposed 3D MLCNN segmentation model for detecting the segmenting tumors produces outperforming results for predicting even tiny tumors in the lung images. Experimental results demonstrated with lung cancer CT images in TCIA datasets show that the proposed model 3D-MLCNN achieved a dice coefficient (9.6%), Intersection over Union (IoU) (80%), F1-Score (9.33%), Sensitivity (17.11%), and Accuracy (98%) respectively. However, the proposed model 3D MLCNN was evaluated and compared with the existing state-of-the-art segmentation methods, which shows a 10% improvement in the segmentation process. Novelty: A novel 3D MLCNN model enhances the tumor region and predicts the tumor accurately by labeling the tumor using K-means labeling techniques. Keywords: 3D Convolutional Neural Networks, Lung Cancer CT Images, K - Means Labeling, Feature Visualization, Deep Learning

Abstract 3798: Advancements in multiplexed spatial phenotyping

Abstract Spatial omics is an expanding research area focused on integrating spatial knowledge of tissue with transcriptomics (RNA) and proteomics (protein). Understanding the complexity of the biological structure(s) is an important biological process in cancer immunotherapy research which requires accurate target classification. Translational profiling of 4+ targets on a single sample at one time can be difficult in many ways, such as, panel design, staining protocols, and data analysis. Furthermore, to design a reliable multi-target biomarker panel, there are many parts to overcome, such as protein abundance and localization, fluorophore compatibility, varying tissue types, and data characterization, to name a few. To address the needs of high target multiplex ability, labeling methods have advanced in cyclic detection enabling iterative labeling and detection using automated fluidics, however these approaches suffer from low simultaneous target throughput. Thermo Fisher Scientific can now provide a streamline process for tissue labelling; a process that enables sufficient labelling of high multiplexed panels completed within a couple of hours. We show successful detection of a wide range of various protein markers across numerous tissue organs used in various biological research applications with our uniform technique of labelling. Citation Format: Leticia Montoya, Scott Clarke, Austin Harvey, Jen Serafin, Mae Voeun. Advancements in multiplexed spatial phenotyping [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 3798.

Abstract 5768: Proximity labeling with molecular signal sensing of oncogenic PIK3CA

Abstract PIK3CA mutations are major oncogenic drivers for oncogenesis. Mutant PIK3CA continuously activates the PI3K pathway, transmitting oncogenic signals within the transformed cells. Despite decades of efforts focused on targeting oncogenic PIK3CA for cancer therapy, the precise molecular and functional machinery remains incomplete due to the molecular complexity of the PI3K pathway. Mapping of proximity proteins in the oncogenic PI3K pathway and identifying mutant signals will signify a deep understanding of oncogenesis and a broad range of therapeutic applications. In this study, we hypothesize that PIK3CA mutant cancer cells establish a unique molecular program networking with distinct proteins, which differs from that of cancer cells with wild-type (WT) PIK3CA. To test this hypothesis, we have developed a novel bioengineering approach to decode protein-protein interactions of oncogenic PIK3CA and identify key molecular partners, potentially providing therapeutic vulnerabilities in cancer cells. First, we applied the proximity labeling technique, based on the fusion of a promiscuous protein ligase to a targeting protein of interest (POI), featuring proximity-dependent biotinylation of interacting and neighboring proteins. The promiscuous biotin ligases, BioID and BioID2, were utilized to integrate WT PIK3CA or gain-of-function hotspot mutations in at E545K or H1047R residues. To optimize the labeling protocol and biotinylation conditions, the BioID and BioID2 plasmids were fused with each POI, incorporating multiple combinations of protein tags, including myc, HA, and red fluorescence protein. Lamin A was used as the positive control, and a total of 15 plasmids were constructed in pcDNA3.1 mammalian expression vector. The sizes of the plasmids and the gene sequences were validated by PCR amplification and Sanger sequencing. Next, we employed a programmable nuclease, the prokaryotic Argonaute (pAgo), assisted by fluorescence resonance energy transfer technology, to detect oncogenic signals derived from mutant PIK3CA in cell-free conditions. To test our methods, we engineered two cancer cell lines (DHSA-1426 and COSB) derived from naturally occurring hemangiosarcoma in dogs, to induce PIK3CA H1047R mutations using CRISPR/Cas9. Our technical approach enables temporal and spatial molecular sensing of oncogenic PIK3CA and its functional interactome in living cancer cells by integrating high-resolution molecular mapping with a pAgo-based detection system. Our ongoing work involves the standardization and optimization of proximity labeling for oncogenic PIK3CA across ontogenetically distinct cancer cells. Furthermore, we will determine the sensitivity and specificity of the integrated approach to achieve proximity labeling with programmable detection of molecular signals from oncogenic PIK3CA. Citation Format: Rong Li, Donghee Lee, Md Abdullah, Jong Hyuk Kim. Proximity labeling with molecular signal sensing of oncogenic PIK3CA [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 5768.

Quantitative Proteomic Analysis Identifying and Evaluating TRAF6 and IL-8 as Potential Diagnostic Biomarkers in Neonatal Patients with Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a common gastrointestinal complication in premature infants, resulting in high morbidity and mortality, and its early detection is crucial for accurate treatment and outcome prediction. Extensive research has demonstrated a clear correlation between NEC and extremely low birth weight, degree of preterm, formula feeding, infection, hypoxic/ischemic damage, and intestinal dysbiosis. The development of noninvasive biomarkers of NEC from stool, urine, and serum has attracted a great deal of interest because to these clinical connections and the quest for a deeper knowledge of disease pathophysiology. Therefore, this study aims to identify protein expression patterns in NEC and discover innovative diagnostic biomarkers. In this study, we recruited five patients diagnosed with NEC and paired necrotic segments of intestinal tissue with adjacent normal segments of intestine to form experimental and control groups. Quantitative proteomics tandem mass tagging (TMT) labeling technique was used to detect and quantify the proteins, and the expression levels of the candidate biomarkers in the intestinal tissues were further determined by quantitative polymerase chain reaction (RT-qPCR), Western blot analysis, Immunofluorescence methods and enzyme-linked immunosorbent assay (ELISA). A total of 6880 proteins were identified and quantified in patients with NEC. A significant disparity in protein expression was observed between necrotic and normal segments of intestinal tissue in NEC patients. A total of 55 proteins were found to be upregulated, and 40 proteins were found to be downregulated in NEC patients when using a p-value of < 0.05, and an absolute fold change of > 1.2 for analysis. GO function enrichment analysis showed the positive regulation of significant biological processes such as mitochondrial organization, vasoconstriction, rRNA catabolism, fluid shear stress response, and glycerol ether biosynthesis processes. Enrichment analysis also revealed essential functions such as ligand-gated ion channel activity, potassium channel activity, ligand-gated cation channel activity, ligand-gated ion channel activity, and ligand-gated channel activity, including molecular functions such as ligand-gated ion channel activity and mitotic events in this comparative group. Significant changes were found in endomembrane protein complex, membrane fraction, mitochondrial membrane fraction, membrane components, membrane intrinsic components, and other localized proteins. Additional validation of intestinal tissue and serum revealed a substantial increase in TRAF6 (tumor necrosis factor receptor-associated factor 6) and IL-8(Interleukin-8, CXCL8). The quantitative proteomic TMT method can effectively detect proteins with differential expression in the intestinal tissues of NEC patients. Proteins TRAF6 and CXCL8/IL-8 are significantly upregulated in the intestinal tissues and serum samples of patients and may serve as valuable predictor factors for NEC's early diagnosis.

Comparative Analysis of Fluorescent Labeling Techniques for Tracking Canine Amniotic Stem Cells.

The utmost aim of regenerative medicine is to promote the regeneration of injured tissues using stem cells. Amniotic mesenchymal stem cells (AmMSCs) have been used in several studies mainly because of their easy isolation from amniotic tissue postpartum and immunomodulatory and angiogenic properties and the low level of rejection. These cells share characteristics of both embryonic/fetal and adult stem cells and are particularly advantageous because they do not trigger tumorigenic activity when injected into immunocompromised animals. The large-scale use of AmMSCs for cellular therapies would greatly benefit from fluorescence labeling studies to validate their tracking in future therapies. This study evaluated the fluorophore positivity, fluorescence intensity, and longevity of canine AmMSCs. For this purpose, canine AmMSCs from the GDTI/USP biobank were submitted to three labeling conditions, two commercial fluorophores [CellTrace CFSE Cell Proliferation kit - CTrace, and CellTracker Green CMFDA - CTracker (CellTracker Green CMFDA, CT, #C2925, Molecular Probes®; Life Technologies)] and green fluorescent protein (GFP) expression after lentiviral transduction, to select the most suitable tracer in terms of adequate persistence and easy handling and analysis that could be used in studies of domestic animals. Fluorescence was detected in all groups; however, the patterns were different. Specifically, CTrace and CTracker fluorescence was detected 6 h after labeling, while GFP was visualized no earlier than 48 h after transduction. Flow cytometry analysis revealed more than 70% of positive cells on day 7 in the CTrace and CTracker groups, while fluorescence decreased significantly to 10% or less on day 20. Variations between repetitions were observed in the GFP group under the present conditions. Our results showed earlier fluorescence detection and more uniform results across repetitions for the commercial fluorophores. In contrast, fluorescence persisted for more extended periods in the GFP group. These results indicate a promising direction for assessing the roles of canine AmMSCs in regenerative medicine without genomic integration.

Generalized Venous Prominence on Susceptibility-Weighted Imaging Correlates With Global Cerebral Blood Flow Decline.

Objective This study investigated the global correlation between cerebral blood flow (CBF) decline and increased venous prominence, utilizing arterial spin labeling (ASL) and susceptibility-weighted imaging (SWI) MRI techniques. Methods The study was conducted at the Department of Diagnostic Imaging, St. Marina University Hospital, Varna, Bulgaria. Through a retrospective analysis, we examined data from 115 patients undergoing neurological assessment. CBF decline was assessed through ASL MRI, while global venous visibility was evaluated using SWI MRI. Results The analysis revealed a significant positive correlation between CBF decline and venous prominence (Spearman's rho = 0.261, p = 0.005), indicating a systemic interaction between cerebral perfusion and the venous system. Logistic regression further underscored CBF decline as a significant predictive factor for increased venous visibility (odds ratio (OR) = 1.690, p = 0.004). The assessments' high inter-rater reliability (Cohen's kappa = 0.82) supports the consistency and validity of our findings. Conclusion The integration of ASL and SWI MRI provides critical insights into cerebral hemodynamics, emphasizing the significance of these imaging modalities in both neurovascular research and clinical practice. Our findings suggest a systemic relationship between CBF decline and venous system alterations, underscoring the potential for these techniques to enhance our understanding of neurovascular disorders. Future studies should pursue longitudinal and quantitative analyses to deepen our comprehension of these relationships and their clinical implications.

Spermidine enhances parthenocarpic fruit formation in cucumber by promoting efficient distribution of soluble sugars and photosynthates

Parthenocarpic fruit formation is one of the most important traits which determines the production of cucumber. For improving the parthenocarpy, some kind of plant growth regulators were applied. However, the effect of spermidine (spd) on parthenocarpic fruit formation is unknown. In the presented study, 4 cucumber lines with different parthenocarpic ability were treated with spd to identify its role in parthenocarpy fruit formation. The results indicated that 0.25–1 mmol/L spd efficiently induced parthenocarpic fruit induction. The fruit development of YN (non-parthenocarpy line) was significantly enhanced by 1 mmol/L spd, while the fruit development of EP-6 (parthenocarpy line) was significantly inhibited by spd inhibitor MGBG (methylglyoxal-bis(guanylhydrazone)). The mechanism of spd-induced parthenocarpy was further identified by 14C isotope labeling technique. In comparison with non-pollinated fruit of YN, the sugar contents in spd-treated YN and non-pollinated EP-6 were higher. The spd enhanced output of 14C photosynthates from source leaf and accumulation in fruit of YN, while MGBG inhibited these processes in EP-6. In addition, the 14C photosynthates were mainly accumulated in the pulp of fruits. These results indicate that spd-induced parthenocarpic fruit formation is dependent on sugars and photosynthates accumulation in fruits.

Image-based novel fault detection with deep learning classifiers using hierarchical labels

One important characteristic of modern fault classification systems is the ability to flag the system when faced with previously unseen fault types. This work considers the unknown fault detection capabilities of deep neural network-based fault classifiers. Specifically, we propose a methodology on how, when available, labels regarding the fault taxonomy can be used to increase unknown fault detection performance without sacrificing model performance. To achieve this, we propose to utilize soft label techniques to improve the state-of-the-art deep novel fault detection techniques during the training process and novel hierarchically consistent detection statistics for online novel fault detection. Finally, we demonstrated increased detection performance on novel fault detection in inspection images from the hot steel rolling process, with results well replicated across multiple scenarios and baseline detection methods.

Clickable X-ray Nanoprobes for Nanoscopic Bioimaging of Cellular Structures.

Synchrotron-based X-ray microscopy (XRM) has garnered widespread attention from researchers due to its high spatial resolution and excellent energy (element) resolution. Existing molecular probes suitable for XRM include immune probes and genetic labeling probes, enabling the precise imaging of various biological targets within cells. However, immune labeling techniques are prone to cross-interference between antigens and antibodies. Genetic labeling technologies have limited systems that allow express markers independently, and moreover, genetically encoded labels based on catalytic polymerization lack a fixed morphology. When applied to cell imaging, this can result in reduced localization accuracy due to the diffusion of labels within the cells. Therefore, both techniques face challenges in simultaneously labeling multiple biotargets within cells and achieving high-precision imaging. In this work, we applied the click reaction and developed a third category of imaging probes suitable for XRM, termed clickable X-ray nanoprobes (Click-XRN). Click-XRN consists of two components: an X-ray-sensitive multicolor imaging module and a particle-size-controllable morphology module. Efficient identification of intra- and extracellular biotargets is achieved through click reactions between the probe and biomolecules. Click-XRN possesses a controllable particle size, and its loading of various metal ions provides distinctive signals for imaging under XRM. Based on this, we optimized the imaging energy of Click-XRN with different particle sizes, enabling single-color and two-color imaging of the cell membrane, cell nucleus, and mitochondria with nanoscale spatial nanometers. Our work provides a potent molecular tool for investigating cellular activities through XRM.

SEMANTIC LABELING OF 3D BUILDINGS BY USING GRAPH NEURAL NETWORK (GNN)

Abstract. Understanding building semantics is crucial for comprehending their structure, components, and functions. This study investigates the utilization of Graph Neural Networks (GNN) to semantically label 3D building models, aiming to optimize these labels' output within Geographic Information Systems (GIS). The methodology leverages diverse datasets comprising 3D building models, utilizing BuildingGNN algorithms to iteratively refine the labeling process. The resultant labeled components, after thorough validation, are translated into the CityGML format. The generated CityGML dataset holds promise for a wide array of 3D city model applications, heightening the utility of labeled components within GIS analyses. While exploring GNN's capabilities may reduce manual effort and time and provide standardized data representation, this study also addresses challenges in ensuring output reliability. While automation remains a goal, future research endeavors may focus on refining automatic labeling techniques and semantic translation processes to further improve accuracy and applicability.

Elucidating uptake and metabolic fate of dipeptides in CHO cell cultures using 13C labeling experiments and kinetic modeling

The rapidly growing market of biologics including monoclonal antibodies has stimulated the need to improve biomanufacturing processes including mammalian host systems such as Chinese Hamster Ovary (CHO) cells. Cell culture media formulations continue to be enhanced to enable intensified cell culture processes and optimize cell culture performance. Amino acids, major components of cell culture media, are consumed in large amounts by CHO cells. Due to their low solubility and poor stability, certain amino acids including tyrosine, leucine, and phenylalanine can pose major challenges leading to suboptimal bioprocess performance. Dipeptides have the potential to replace amino acids in culture media. However, very little is known about the cleavage, uptake, and utilization kinetics of dipeptides in CHO cell cultures. In this study, replacing amino acids, including leucine and tyrosine by their respective dipeptides including but not limited to Ala-Leu and Gly-Tyr, supported similar cell growth, antibody production, and lactate profiles. Using 13C labeling techniques and spent media studies, dipeptides were shown to undergo both intracellular and extracellular cleavage in cultures. Extracellular cleavage increased with the culture duration, indicating cleavage by host cell proteins that are likely secreted and accumulate in cell culture over time. A kinetic model was built and for the first time, integrated with 13C labeling experiments to estimate dipeptide utilization rates, in CHO cell cultures. Dipeptides with alanine at the N-terminus had a higher utilization rate than dipeptides with alanine at the C-terminus and dipeptides with glycine instead of alanine at N-terminus. Simultaneous supplementation of more than one dipeptide in culture led to reduction in individual dipeptide utilization rates indicating that dipeptides compete for the same cleavage enzymes, transporters, or both. Dipeptide utilization rates in culture and cleavage rates in cell-free experiments appeared to follow Michaelis-Menten kinetics, reaching a maximum at higher dipeptide concentrations. Dipeptide utilization behavior was found to be similar in cell-free and cell culture environments, paving the way for future testing approaches for dipeptides in cell-free environments prior to use in large-scale bioreactors. Thus, this study provides a deeper understanding of the fate of dipeptides in CHO cell cultures through an integration of cell culture, 13C labeling, and kinetic modeling approaches providing insights in how to best use dipeptides in media formulations for robust and optimal mammalian cell culture performance.

Direct TAMRA-dUTP labeling of M. tuberculosis genes using loop-mediated isothermal amplification (LAMP)

Fluorescent molecule-based direct labeling of amplified DNA is a sensitive method employed across diverse DNA detection and diagnostics systems. However, using pre-labeled primers only allows for the attachment of a single fluorophore to each DNA strand and any modifications of the system are less flexible, requiring new sets of primers. As an alternative, direct labeling of amplified products with modified nucleotides is available, but still poorly characterized. To address these limitations, we sought a direct and adaptable approach to label amplicons produced through Loop-mediated isothermal amplification (LAMP), using labeled nucleotides (dUTPs) rather than primers. The focus of this study was the development and examination of a direct labeling technique of specific genes, including those associated with drug resistance in Mycobacterium tuberculosis. We used 5-(3-Aminoallyl)-2′-deoxyuridine-5′triphosphate, tagged with 5/6-TAMRA (TAMRA-dUTP) for labeling LAMP amplicons during the amplification process and characterized amplification and incorporation efficiency. The optimal TAMRA-dUTP concentration was first determined based on amplification efficiency (0.5% to total dNTPs). Higher concentrations of modified nucleotides reduced or completely inhibited the amplification yield. Target size also showed to be determinant to the success of amplification, as longer sequences showed lower amplification rates, thus less TAMRA incorporated amplicons. Finally, we were able to successfully amplify all four M. tuberculosis target genes using LAMP and TAMRA-modified dUTPs.

Methodology of ICG marking technique in modern pelvic surgery: applied aspects (Literature review)

The article is devoted to a review of scientific publications on the use of the Indocyanine green (ICG) labeling technique in modern pelvic surgery. This dye was developed by Kodak Research Laboratories in 1955 and approved for clinical use in 1959, but has only recently come into widespread use. ICG-enhanced near-infrared fluorescence is introduced to improve visualization and provide more detailed anatomical localization during surgery.The dye binds to blood plasma proteins, it is quickly excreted from the organism and is non-toxic and has no found complications after its administration. Many studies have been conducted on the use of this technique: visualization of sentinel lymph nodes (SLN) in various oncogynecological diseases; visualization of ureters, lymphatic drainage, tissue perfusion, vessels of various sizes, colorectal blood circulation, etc. The high detection rate of SLN (unilateral and bilateral) with ICG compared with other dyes such as radiocolloid and patent blue suggests its effectiveness.The condition of SLN has an important prognostic and therapeutic value, based on the obtained results, a more correct further adjuvant treatment can be prescribed. A sentinel lymph node labeling procedure was performed as an alternative to systemic lymphadenectomy to assess the status of lymphovascular invasion. The use of ICG-marking allows to reduce the risk of intraoperative and postoperative complications. Many experimental studies have been conducted in relation to the assessment of uterine vascularization, preservation of individual vessels, their identification and measurement of blood flow.The article provides data from scientists on the use of the ICG-marking technique in endometrial, cervical, vulva, vaginal, ovarian cancer, as well as in endometriosis and for visualization of the ureters. This technique causes active discussions in the scientific community, requires further research and should be more widely used in various directions of surgical interventions.