Labeling Efficiency Research Articles

89Zr-leukocyte labelling for cell trafficking: in vitro and preclinical investigations

BackgroundThe non-invasive imaging of leukocyte trafficking to assess inflammatory areas and monitor immunotherapy is currently generating great interest. There is a need to develop more robust cell labelling and imaging approaches to track living cells. Positron emission tomography (PET), a highly sensitive molecular imaging technique, allows precise signals to be produced from radiolabelled moieties. Here, we developed a novel leukocyte labelling approach with the PET radioisotope zirconium-89 (89Zr, half-life of 78.4 h). Experiments were carried out using human leukocytes, freshly isolated from whole human blood.ResultsThe 89Zr-leukocyte labelling efficiency ranged from 46 to 87% after 30–60 min. Radioactivity concentrations of labelled cells were up to 0.28 MBq/1 million cells. Systemically administered 89Zr-labelled leukocytes produced high-contrast murine PET images at 1 h–5 days post injection. Murine biodistribution data showed that cells primarily distributed to the lung, liver, and spleen at 1 h post injection, and are then gradually trafficked to liver and spleen over 5 days. Histological analysis demonstrated that exogenously 89Zr-labelled human leukocytes were present in the lung, liver, and spleen at 1 h post injection. However, intravenously injected free [89Zr]Zr4+ ion showed retention only in the bone with no radioactivity in the lung at 5 days post injection, which implied good stability of radiolabelled leukocytes in vivo.ConclusionsOur study presents a stable and generic radiolabelling technique to track leukocytes with PET imaging and shows great potential for further applications in inflammatory cell and other types of cell trafficking studies.

Preparation, Radiolabeling with 68Ga/177Lu and Preclinical Evaluation of Novel Angiotensin Peptide Analog: A New Class of Peptides for Breast Cancer Targeting.

Angiotensin II (AngII) is known to play a significant part in the development of breast cancer by triggering cell propagation of breast cancer, tumor angiogenesis, and regulating tumor invasion and cell migration. AngII arbitrates its action via two G-protein-coupled receptors, AngII type 1 receptor (AT1) and AngII type 2 receptor (AT2). Overexpression of the AT1 receptor in breast cancer cells seems to promote tumor growth and angiogenesis, thus targeting the AT1 receptor using AngII peptide would facilitate the detection of breast carcinoma. We developed an AngII peptide intending to assess whether the peptide of the renin-angiotensin system holds the ability to target AT1 receptor-overexpressing breast cancer in vivo. DOTA-coupled AngII peptide was synthesized by conventional solid-phase peptide synthesis according to Fmoc/HATU chemistry. 68Ga/177Lu labeled AngII peptide was evaluated for its binding with TNBC MDA-MB-231 and ER+ MCF7 cell lines. Pharmacokinetics was studied in healthy balb/c mice and in vivo tumor targeting in nude mice with MDA-MB-231 tumors xenografts. DOTA-AngII peptide was labeled efficiently with 68Ga/177Lu with high labeling efficiency (≥90%). The stability of the radiopeptide in human plasma was found to be high. The AngII peptide analog showed nanomolar (<40 nM) AT1 receptor-specific binding affinity. The radioactivity internalized into MDA-MBA-231 and MCF7 cells were 14.97% and 11.75%, respectively. In vivo, biodistribution in balb/c mice exhibited efficient clearance of 68Ga/177Lu-DOTA-AngII peptide from the blood and elimination predominantly by the renal system due to its hydrophilic nature. A low amount of radioactivity was seen in the major organs including lungs, liver, stomach, spleen, and intestines (<3% ID/g) except the kidneys. A high renal-urinary excretion was observed for the radiotracer. In the TNBC MDA-MB-231 xenografts model, radiolabeled AngII peptide exhibited specific and effective AT1-based targeting in vivo. A rapid and efficient tumor targeting (2.18% ID/g at 45 min p.i.) together with fast renal excretion (~67% ID) highlights the tumor-targeting potential of the radiotracer. The AT1 receptor specificity of the radiotracer was validated by blocking assays. Furthermore, PET imaging provided sufficient visualization of MDA-MB-231 tumors in nude mice. Our findings suggest that 68Ga/177Lu-DOTA-AngII peptide can be useful for the theranostic application of breast carcinomas. This study suggests the potential of this innovative class of peptides for rapid and efficient targeting of tumors and warrants further evaluation.

Molecular imaging of bacterial outer membrane vesicles based on bacterial surface display

The important roles of bacterial outer membrane vesicles (OMVs) in various diseases and their emergence as a promising platform for vaccine development and targeted drug delivery necessitates the development of imaging techniques suitable for quantifying their biodistribution with high precision. To address this requirement, we aimed to develop an OMV specific radiolabeling technique for positron emission tomography (PET). A novel bacterial strain (E. coli BL21(DE3) ΔnlpI, ΔlpxM) was created for efficient OMV production, and OMVs were characterized using various methods. SpyCatcher was anchored to the OMV outer membrane using autotransporter-based surface display systems. Synthetic SpyTag-NODAGA conjugates were tested for OMV surface binding and 64Cu labeling efficiency. The final labeling protocol shows a radiochemical purity of 100% with a ~ 29% radiolabeling efficiency and excellent serum stability. The in vivo biodistribution of OMVs labeled with 64Cu was determined in mice using PET/MRI imaging which revealed that the biodistribution of radiolabeled OMVs in mice is characteristic of previously reported data with the highest organ uptakes corresponding to the liver and spleen 3, 6, and 12 h following intravenous administration. This novel method can serve as a basis for a general OMV radiolabeling scheme and could be used in vaccine- and drug-carrier development based on bioengineered OMVs.

18F‐Fluorination of 2‐Methyl‐6‐nitrobenzenesulfonate Ester and its Application for the Synthesis of an 18F‐Labeled Amino Acid**

AbstractIn the development of an efficient 18F‐labeling method for the synthesis of PET tracers, it is essential not only to improve the efficiency of [18F]fluorine incorporation into a carrier but also to minimize non‐radioactive side products from the precursor. Highly reactive sulfonate esters are promising precursors for 18F‐nucleophilic fluorination under mild conditions. However, the expected labeling efficiency from the precursor is often hampered by its competitive degradation due to coexisting bases during 18F‐fluorination. In this report, we designed a 2‐methyl‐6‐nitrobenzenesulfonate (2‐MeNs) ester as a precursor for 18F‐fluorination, in which the methyl group suppresses hydrolysis of the sulfonate ester via steric hindrance. An increase in labeling efficiency in the 18F‐labeling of a neopentyl labeling group was observed for the neopentyl 2‐MeNs ester compared with that of the 2‐nitrobenzenesulfonate ester. Ultimately, we achieved the automated synthesis of an 18F‐labeled amino acid using a neopentyl labeling group by using a 2‐MeNs ester as a precursor.

Indocyanine Green-Labeled Platelets for Survival and Recovery Studies

Plain Language SummaryWe developed a simple, reproducible method according to Good Manufacturing Practice guidelines for labeling of platelets from platelet concentrates (PCs) with indocyanine green (ICG) as a non-radioactive alternative. PCs are medicinal drugs that are transfused to prevent or treat bleeding. They consist of the blood cells’ platelets which are responsible for clotting processes in the body. Manufacturing procedures of PCs are continuously refined, and for in vivo testing, these platelets have to be labeled to track and to distinguish them from proband’s or patient’s own cells. Radioactive labeling, for a long time the gold standard for cell labeling, is no longer accepted. ICG is a fluorescent dye approved by the drug authorities and already used for diagnostic purposes in humans. We used ICG to label platelets from PCs. With our method, we achieved a labeling efficiency of 99.8%. We used whole blood (WB) as an ex vivo matrix to monitor the labeling stability of ICG-labeled platelets. After the addition of ICG-labeled platelets to WB, the labeling efficiency decreased to 81% after 24 h. However, we were still able to distinguish the ICG-labeled platelets from the WB platelets. We could also show that platelet function was not impaired by the labeling processes. The good tolerance of ICG indicates a short path to clinical application in healthy volunteers and investigations of novel PC-manufacturing procedures. As a read-out system, flow cytometry systems equipped with NIR lasers and filters could offer the possibility of rapid visualization, cell tracking, re-isolation, and ex vivo studies.

Enhancing Extracellular Vesicle Analysis by Integration of Large-Volume Sample Stacking in Capillary Electrophoresis with Asymmetrical Flow Field-Flow Fractionation.

Extracellular vesicles (EVs) play important roles in cell-cell communication and pathological development. Cargo profiling for the EVs present in clinical specimens can provide valuable insights into their functions and help discover effective EV-based markers for diagnostic and therapeutic purposes. However, the highly abundant and complex matrix components pose significant challenges for specific identification of low-abundance EV cargos. Herein, we combine asymmetrical flow field-flow fractionation (AF4) with large-volume sample stacking and capillary electrophoresis (LVSS/CE), to attain EVs with high purity for downstream protein profiling. This hyphenated system first separates the EVs from the contamination of smaller serum proteins by AF4, and second resolves the EVs from the coeluted, nonvesicular matrix components by CE following LVSS. The optimal LVSS condition permits the injection of 10-fold more EVs into CE compared to the nonstacking condition without compromising separation resolution. Collection and downstream analysis of the highly pure EVs after CE separation were demonstrated in the present work. The high EV purity yields a much-improved labeling efficiency when detected by fluorescent antibodies compared to those collected from the one-dimension separation of AF4, and permits the identification of more EV-specific cargos by LC-MS/MS compared to those isolated by ultracentrifugation (UC), the exoEasy Maxi Kit, and AF4. Our results strongly support that AF4-LVSS/CE can improve EV isolation and cargo analysis, opening up new opportunities for understanding EV functions and their applications in the biomedical fields.

Head-to-head comparison of three chelates reveals DOTAGA promising for 225 Ac labeling of anti-FZD10 antibody OTSA101.

To select the most suitable chelate for 225 Ac radiolabeling of the anti-FZD10 antibody OTSA101, we directly compared three chelates: S-2-(4-isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-SCN-Bn-DOTA), 2,2',2″-(10-(1-carboxy-4-((4-isothiocyanatobenzyl)amino)-4-oxobutyl)-1,4,7,10-tetraazacyclododecane-1,4,7-triyl) triacetic acid (p-SCN-Bn-DOTAGA), and 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid mono-N-hydroxysuccinimide ester (DO3A-NHS-ester). We evaluated the binding affinity of the chelate-conjugated OTSA101 antibodies, as well as the labeling efficiency and stability in murine serum of 225 Ac-labeled OTSA101 as in vitro properties. The biodistribution, intratumoral distribution, absorbed doses, and therapeutic effects of the chelate-conjugated OTSA101 antibodies were assessed in the synovial sarcoma mouse model SYO-1. Of the three conjugates, DOTAGA conjugation had the smallest impact on the binding affinity (p < 0.01). The labeling efficiencies of DOTAGA-OTSA101 and DO3A-OTSA101 were 1.8-fold higher than that of DOTA-OTSA101 (p < 0.01). The stabilities were similar between 225 Ac-labeled DOTA-OTSA101, DOTAGA-OTSA101, and DO3A-OTSA101in serum at 37 and 4°C. The dosimetric analysis based on the biodistribution revealed significantly higher tumor-absorbed doses by 225 Ac-labeled DOTA-OTSA101 and DOTAGA-OTSA101 compared with 225 Ac-DO3A-OTSA101 (p < 0.05). 225 Ac-DOTAGA-OTSA101 exhibited the highest tumor-to-bone marrow ratio, with bone marrow being the dose-limiting tissue. The therapeutic and adverse effects were not significantly different between the three conjugates. Our findings indicate that among the three evaluated chelates, DOTAGA appears to be the most promising chelate to produce 225 Ac-labeled OTSA101 with high binding affinity and high radiochemical yields while providing high absorbed doses to tumors and limited absorbed doses to bone marrow.

Weakly Supervised Concept Map Generation through Task-Guided Graph Translation.

Recent years have witnessed the rapid development of concept map generation techniques due to their advantages in providing well-structured summarization of knowledge from free texts. Traditional unsupervised methods do not generate task-oriented concept maps, whereas deep generative models require large amounts of training data. In this work, we present GT-D2G (Graph Translation-based Document To Graph), an automatic concept map generation framework that leverages generalized NLP pipelines to derive semantic-rich initial graphs, and translates them into more concise structures under the weak supervision of downstream task labels. The concept maps generated by GT-D2G can provide interpretable summarization of structured knowledge for the input texts, which are demonstrated through human evaluation and case studies on three real-world corpora. Further experiments on the downstream task of document classification show that GT-D2G beats other concept map generation methods. Moreover, we specifically validate the labeling efficiency of GT-D2G in the label-efficient learning setting and the flexibility of generated graph sizes in controlled hyper-parameter studies.

Preparation and evaluation of 111In-labeled liposomes containing phosphatidylglycerol for detection of macrophages in atherosclerotic plaques

Macrophage infiltration is a characteristic feature of atherosclerotic plaque progression. Since liposomes containing 1,2-distearoyl-sn-glycero-3-phosphoglycerol (DSPG) are efficiently phagocytosed by macrophages, we deduced that radiolabeled liposomes containing DSPG could potentially be used for nuclear imaging of vulnerable atherosclerotic plaques. Indium-111 (111In)-labeled liposomes containing different ratios of DSPG were developed with a high labeling efficiency. 111In-labeled liposomes with higher DSPG content showed higher uptake by macrophage-like RAW264 cells. A biodistribution study demonstrated rapid blood clearance and selective accumulation in the liver and spleen, especially in normal mice injected with 111In-labeled liposomes with higher DSPG content. Accumulation in atherosclerotic plaques was evaluated using 111In-labeled DSPG liposomes, which had the highest DSPG content among the studied liposomes. 111In-labeled DSPG liposomes accumulated in the plaques and the radioactive regions were mostly consistent with the distribution of macrophages. The target-to-non-target ratio of 111In-labeled DSPG liposomes was higher than that of 111In-labeled control liposomes without DSPG. These results suggest that 111In-labeled liposomes containing DSPG are useful for nuclear medical diagnosis of atherosclerotic plaques.

An experimental comparison between primer and nucleotide labelling to produce RPA-amplicons used for multiplex detection of antibiotic resistance genes

Direct labelling of amplification products using isothermal amplification is currently done most frequently by incorporating previously labelled primer. Although this method is well proven and widely used, it is not a universal solution due to some weaknesses. Alternatively, labelled nucleotides could be used, whose application and functionality have been already partially demonstrated. It remains to be determined how this method performs in comparison to traditional labelling, in particular combined with isothermal amplification methods. In this work, we show a detailed analysis of the labelling efficiency under different conditions and compare the results with the traditional primer-labelling method in the context of RPA amplification. Impressively, our results showed that using Cy5-labelled dUTPs can achieve much more efficient labelling for fragments above 200 bp, while using them for smaller fragments does not bring any relevant disadvantages, but also no major benefit. Furthermore, this work successfully demonstrate for the first time a quadruplex microarray for the detection of resistance genes using RPA and direct labelling with Cy5-dUTP as a potential application scenario. The sensitivities achieved here extend to SNP discovery for the detection of the proper blaKPC variant.

Radiolabeled Human Serum Albumin Nanoparticles Co-Loaded with Methotrexate and Decorated with Trastuzumab for Breast Cancer Diagnosis.

Breast cancer is a leading cause of cancer-related mortality among women worldwide, with millions of new cases diagnosed yearly. Addressing the burden of breast cancer mortality requires a comprehensive approach involving early detection, accurate diagnosis, effective treatment, and equitable access to healthcare services. In this direction, nano-radiopharmaceuticals have shown potential for enhancing breast cancer diagnosis by combining the benefits of nanoparticles and radiopharmaceutical agents. These nanoscale formulations can provide improved imaging capabilities, increased targeting specificity, and enhanced sensitivity for detecting breast cancer lesions. In this study, we developed and evaluated a novel nano-radio radiopharmaceutical, technetium-99m ([99mTc]Tc)-labeled trastuzumab (TRZ)-decorated methotrexate (MTX)-loaded human serum albumin (HSA) nanoparticles ([99mTc]-TRZ-MTX-HSA), for the diagnosis of breast cancer. In this context, HSA and MTX-HSA nanoparticles were prepared. Conjugation of MTX-HSA nanoparticles with TRZ was performed using adsorption and covalent bonding methods. The prepared formulations were evaluated for particle size, PDI value, zeta (ζ) potential, scanning electron microscopy analysis, encapsulation efficiency, and loading capacity and cytotoxicity on MCF-7, 4T1, and MCF-10A cells. Finally, the nanoparticles were radiolabeled with [99mTc]Tc using the direct radiolabeling method, and cellular uptake was performed with the nano-radiopharmaceutical. The results showed the formation of spherical nanoparticles, with a particle size of 224.1 ± 2.46 nm, a PDI value of 0.09 ± 0.07, and a ζ potential value of -16.4 ± 0.53 mV. The encapsulation efficiency of MTX was found to be 32.46 ± 1.12%, and the amount of TRZ was 80.26 ± 1.96%. The labeling with [99mTc]Tc showed a high labeling efficiency (>99%). The cytotoxicity studies showed no effect, and the cellular uptake studies showed 97.54 ± 2.16% uptake in MCF-7 cells at the 120th min and were found to have a 3-fold higher uptake in cancer cells than in healthy cells. In conclusion, [99mTc]Tc-TRZ-MTX-HSA nanoparticles are promising for diagnosing breast cancer and evaluating the response to treatment in breast cancer patients.

CLSSL-ResNet: Predicting malignancy of solitary pulmonary nodules from CT images by chimeric label with self-supervised learning.

Pulmonary granulomatous nodules (GN) with spiculation or lobulation have a similar morphological appearance to solid lung adenocarcinoma (SADC) under computed tomography (CT). However, these two kinds of solid pulmonary nodules (SPN) have different malignancies and are sometimes misdiagnosed. This study aims to predict malignancies of SPNs by a deep learning model automatically. A chimeric label with self-supervised learning (CLSSL) is proposed to pre-train a ResNet-based network (CLSSL-ResNet) for distinguishing isolated atypical GN from SADC in CT images. The malignancy, rotation, and morphology labels are integrated into a chimeric label and utilized to pre-train a ResNet50. The pre-trained ResNet50 are then transferred and fine-tuned to predict the malignancy of SPN. Two image datasets of 428 subjects (Dataset1, 307; Dataset2, 121) from different hospitals are collected. Dataset1 is divided into training, validation, and test data by a ratio of 7:1:2 to develop the model. Dataset2 is utilized as an external validation dataset. CLSSL-ResNet achieves an area under the ROC curve (AUC) of 0.944 and an accuracy (ACC) of 91.3%, which was much higher than that of the consensus of two experienced chest radiologists (77.3%). CLSSL-ResNet also outperforms other self-supervised learning models and many counterparts of other backbone networks. In Dataset2, AUC and ACC of CLSSL-ResNet are 0.923 and 89.3%, respectively. Additionally, the ablation experiment result indicates higher efficiency of the chimeric label. CLSSL with morphology labels can increase the ability of feature representation by deep networks. As a non-invasive method, CLSSL-ResNet can distinguish GN from SADC via CT images and may support clinical diagnoses after further validation.

Measuring Photosynthesis of Entire Tree Crowns and Pulse Label Trees in Large Closed Chamber with 13CO2 in the Field: Design and Testing

Measuring the photosynthesis of entire tree crowns and pulse labelling trees with 13CO2 are valuable approaches to study carbon acquisition, transfer, and allocation; however, it is challenging for trees in the field. The objective was to develop and field test large chambers (35 - 45 m3) that enclosed the entire crown of a tree, provided a reliable estimate of tree crown photosynthesis, and ensured efficient 13CO2 labelling. The chambers, made of transparent polyethylene film pulled tightly over a frame, were equipped with an air conditioner, fans, and air blowers. Air temperature, relative humidity, and photosynthetic photon flux density were measured outside and inside each chamber. Six of 4-year-old rubber trees (Hevea brasiliensis) were pulsed-labelled with 18 L of 13CO2 in June and October 2016. The mean air temperature inside the chambers was 1.2 °C higher and the relative humidity 8 % lower than the outside air. The crown photosynthesis, calculated from the decrease in the CO2 concentration inside the chamber, was in the range 140 - 249 µmol s–1 and was significantly related to photosynthetic photon flux density, total leaf area of the tree, and average net CO2 assimilation at leaf level. The labelling efficiency, estimated as the ratio of the amount of 13C recovered in the foliage immediately after labelling divided by the amount of 13C delivered to the tree, was in the range 43 - 68 %. The designed chamber was suitable to estimate crown photosynthesis and perform 13CO2 pulse labelling of 5-m-tall trees in the field. HIGHLIGHTS Measuring carbon acquisition, transfer, and allocation of entire trees in the field is a challenge The paper describes in detail the system including a 45 m3 chamber that was developed and tested to measure crown photosynthesis and to label trees 5 - 6 m tall with 13CO2 The system and methodology proved efficient in controlling the chamber temperature and providing appropriate conditions for leaf gas exchanges The rates of crown photosynthesis were consistent with measurements at the leaf and ecosystem levels, providing a clear relationship with photosynthetic photon flux density More than 1-half the injected 13CO2 was recovered in the leaves after the end of labelling, showing that the design of the chamber and the labelling protocol were effective for studying C allocation within the tree GRAPHICAL ABSTRACT

Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics.

Although tandem mass tag (TMT)-based isobaric labeling has become a powerful approach for multiplexed protein quantitation, automating the workflow for this technique has not been easy to achieve for widespread adoption. This is because preparation of TMT-labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction, and alkylation to tryptic digestion, desalting, labeling, and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic, especially with large-scale clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for an automated proteomic workflow employing TMT labeling with the manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using an automated platform and a conventional manual protocol. Single-shot liquid chromatography with tandem mass spectrometry analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiency of tryptic digestion, alkylation, and TMT labeling were similar in both manual and automated processes. In addition, comparison of quantitation accuracy and precision showed similar performance in an automated workflow compared to manual sample preparation by an expert. Overall, we demonstrated that the automated platform performs at a level similar to a manual process performed by an expert for TMT-based proteomics. We anticipate that this automated workflow will increasingly replace manual pipelines and has the potential to be applied to large-scale TMT-based studies, providing robust results and high sample throughput.

Photoactivatable Carbo- and Silicon-Rhodamines and Their Application in MINFLUX Nanoscopy.

New photoactivatable fluorescent dyes (rhodamine, carbo- and silicon-rhodamines [SiR]) with emission ranging from green to far red have been prepared, and their photophysical properties studied. The photocleavable 2-nitrobenzyloxycarbonyl unit with an alpha-carboxyl group as a branching point and additional functionality was attached to a polycyclic and lipophilic fluorescent dye. The photoactivatable probes having the HaloTagTM amine (O2) ligand bound with a dye core were obtained and applied for live-cell staining in stable cell lines incorporating Vimentin (VIM) or Nuclear Pore Complex Protein NUP96 fused with the HaloTag. The probes were applied in 2D (VIM, NUP96) and 3D (VIM) MINFLUX nanoscopy, as well as in superresolution fluorescence microscopy with single fluorophore activation (VIM, live-cell labeling). Images of VIM and NUPs labeled with different dyes were acquired and their apparent dimensions and shapes assessed on a lower single-digit nanometer scale. Applicability and performance of the photoactivatable dye derivatives were evaluated in terms of photoactivation rate, labeling and detection efficiency, number of detected photons per molecule and other parameters related to MINFLUX nanoscopy.

Photoactivatable Carbo‐ and Silicon‐Rhodamines and Their Application in MINFLUX Nanoscopy

AbstractNew photoactivatable fluorescent dyes (rhodamine, carbo‐ and silicon‐rhodamines [SiR]) with emission ranging from green to far red have been prepared, and their photophysical properties studied. The photocleavable 2‐nitrobenzyloxycarbonyl unit with an alpha‐carboxyl group as a branching point and additional functionality was attached to a polycyclic and lipophilic fluorescent dye. The photoactivatable probes having the HaloTagTM amine (O2) ligand bound with a dye core were obtained and applied for live‐cell staining in stable cell lines incorporating Vimentin (VIM) or Nuclear Pore Complex Protein NUP96 fused with the HaloTag. The probes were applied in 2D (VIM, NUP96) and 3D (VIM) MINFLUX nanoscopy, as well as in superresolution fluorescence microscopy with single fluorophore activation (VIM, live‐cell labeling). Images of VIM and NUPs labeled with different dyes were acquired and their apparent dimensions and shapes assessed on a lower single‐digit nanometer scale. Applicability and performance of the photoactivatable dye derivatives were evaluated in terms of photoactivation rate, labeling and detection efficiency, number of detected photons per molecule and other parameters related to MINFLUX nanoscopy.

A Semi-Supervised Stacked Autoencoder Using the Pseudo Label for Classification Tasks.

The efficiency and cognitive limitations of manual sample labeling result in a large number of unlabeled training samples in practical applications. Making full use of both labeled and unlabeled samples is the key to solving the semi-supervised problem. However, as a supervised algorithm, the stacked autoencoder (SAE) only considers labeled samples and is difficult to apply to semi-supervised problems. Thus, by introducing the pseudo-labeling method into the SAE, a novel pseudo label-based semi-supervised stacked autoencoder (PL-SSAE) is proposed to address the semi-supervised classification tasks. The PL-SSAE first utilizes the unsupervised pre-training on all samples by the autoencoder (AE) to initialize the network parameters. Then, by the iterative fine-tuning of the network parameters based on the labeled samples, the unlabeled samples are identified, and their pseudo labels are generated. Finally, the pseudo-labeled samples are used to construct the regularization term and fine-tune the network parameters to complete the training of the PL-SSAE. Different from the traditional SAE, the PL-SSAE requires all samples in pre-training and the unlabeled samples with pseudo labels in fine-tuning to fully exploit the feature and category information of the unlabeled samples. Empirical evaluations on various benchmark datasets show that the semi-supervised performance of the PL-SSAE is more competitive than that of the SAE, sparse stacked autoencoder (SSAE), semi-supervised stacked autoencoder (Semi-SAE) and semi-supervised stacked autoencoder (Semi-SSAE).

Interactive medical image annotation using improved Attention U-net with compound geodesic distance

Accurate and massive medical image annotation data is crucial for diagnosis, surgical planning, and deep learning in the development of medical images. However, creating large annotated datasets is challenging because labeling medical images is complicated, laborious, and time-consuming and requires expensive and professional medical skills. To significantly reduce the cost of labeling, an interactive image annotation framework based on composite geodesic distance is proposed, and medical images are labeled through segmentation. This framework uses Attention U-net to obtain initial segmentation based on adding user interaction to indicate incorrect segmentation. Another Attention U-net takes the user's interaction with the initial segmentation as input. It uses a composite geodesic distance transform to convert the user's interaction into constraints, giving accurate segmentation results. To further improve the labeling efficiency for large datasets, this paper validates the proposed framework against the segmentation background of a self-built prostate MRI image datasets. Experimental results show that the proposed method achieves higher accuracy in less interactive annotation and less time than traditional interactive annotation methods with better Dice and Jaccard results. This has important implications for improving medical diagnosis, surgical planning, and the development of deep-learning models in medical imaging.

Upconverting Nanoparticle-Based Photoactive Probes for Highly Efficient Labeling and Isolation of Target Proteins.

Photoaffinity labeling (PAL) has blossomed into a powerful and versatile tool for capture and identification of biomolecular targets. However, low labeling efficiency for specific targets such as lectins, the tedious process for protein purification, inevitable cellular photodamage, and less tissue penetration of UV light are significant challenges. Herein, we reported a near-infrared (NIR) light-driven photoaffinity labeling approach using upconverting nanoparticle (UCNP)-based photoactive probes, which were constructed by assembling photoactive groups and ligands onto NaYF4:Yb,Tm nanoparticles. The novel probes were easily prepared and functionalized, and the labeled proteins can be isolated and purified through simple centrifugation and washing. The advantages of this approach were demonstrated by labeling and isolation of peanut agglutinin (PNA), asialoglycoprotein receptor (ASGPR), and human carbonic anhydrase II (hCAII) from mixed proteins or cell lysates with good selectivity and efficiency, especially for PNA and ASGPR, two lectins that showed low binding affinity to their ligands. More importantly, successful labeling of PNA through pork tissues and ASGPR in mice strongly proved the good tissue penetrating capacity of NIR light and the application potential of UCNP-based photoactive probes for protein labeling in vivo. Biosafety of this approach was experimentally validated by enzyme, cell, and animal work, and we demonstrated that NIR light caused minimal photodamage to enzyme activity compared to UV light, and the UCNP-based photoactive probe presents good biosafety both in vitro and in vivo. We believe that this novel PAL approach will provide a promising tool for study of ligand-protein interactions and identification of biomolecular targets.

Observing Extracellular Vesicles Originating from Endothelial Cells in Vivo Demonstrates Improved Astrocyte Function Following Ischemic Stroke via Aggregation-Induced Emission Luminogens.

Extracellular vesicles (EVs) obtained from endothelial cells (ECs) have significant therapeutic potential in the clinical management of individuals with ischemic stroke (IS) because they effectively treat ischemic stroke in animal models. However, because molecular probes with both high labeling efficiency and tracer stability are lacking, monitoring the actions of EC-EVs in the brain remains difficult. The specific intracellular targets in the brain that EC-EVs act on to produce their protective effects are still unknown, greatly impeding their use in clinical settings. For this research, we created a probe that possessed aggregation-induced emission (AIE) traits (namely, TTCP), enabling the effective labeling of EC-EVs while preserving their physiological properties. In vitro, TTCP simultaneously had a higher EC-EV labeling efficiency and better tracer stability than the commercial EV tags PKH-67 and DiI. In vivo, TTCP precisely tracked the actions of EC-EVs in a mouse IS model without influencing their protective effects. Furthermore, through the utilization of TTCP, it was determined that astrocytes were the specific cells affected by EC-EVs and that EC-EVs exhibited a safeguarding impact on astrocytes following cerebral ischemia-reperfusion (I/R) injury. These protective effects encompassed the reduction of the inflammatory reaction and apoptosis as well as the enhancement of cell proliferation. Further analysis showed that miRNA-155-5p carried by EC-EVs is responsible for these protective effects via regulation of the c-Fos/AP-1 pathway; this information provided a strategy for IS therapy. In conclusion, TTCP has a high EC-EV labeling efficiency and favorable in vivo tracer stability during IS therapy. Moreover, EC-EVs are absorbed by astrocytes during cerebral I/R injury and promote the restoration of neurological function through the regulation of the c-Fos/AP-1 signaling pathway.