Sensitive Imaging Research Articles

Transmissive laser lock-in thermography for highly sensitive and online imaging of real interfacial bubbles in wafer bonding

Online and non-destructive detection of interfacial bubbles in wafer bonding is a critical approach to enhance the yield of advanced packaging. However, the commonly used scanning acoustic microscopy (SAM) is time-consuming and may cause additional risk due to soaking in water. The conventional thermography is suffering from low sensitivity and resolution. In this work, we demonstrate for the first time an effective method for highly sensitive and online imaging of real interfacial bubbles in wafer bonding using transmissive laser lock-in thermography (LLT). The transmissive LLT system projects a modulated laser beam onto target wafer surface and records the thermal image sequence on the other side. The bubbles distinctly emerge with clear edges in the extracted lock-in phase images. To enhance the detectivity, the relationship between phase image contrast and LLT parameters was explored. As a result, we can visualize and detect the bubbles larger than 500 μm at depth of 725 μm even under the interference of metal pattern with a speed of 130 mm2/10 s, which is 38% faster than that of SAM. Besides, the LLT phase images contain both bubbles and metal patterns information. The ratio between bubble depth and width reaches 1.45, which is about 2-fold of the latest infrared researches. Above all, this work paves the way for high-sensitive imaging of various tiny internal defects in advanced packaging using infrared thermography.

Exciton-Scissoring Perfluoroarenes Trigger Photomultiplication in Full Color Organic Image Sensors.

We report an unprecedented but useful functionality of perfluoroarenes to enable exciton scissoring in photomultiplication-type organic photodiodes (PM-OPDs). Perfluoroarenes that are covalently connected to polymer donors via photochemical reaction enable us to demonstrate high external quantum efficiency and B-/G-/R-selective PM-OPDs without the use of conventional acceptor molecules. We investigated the operation mechanism of the suggested perfluoroarene-driven PM-OPDs, "How can covalently bonded polymer donor:perfluoroarene PM-OPDs perform as effectively as polymer donor:fullerene blend-based PM-OPDs?". By employing a series of arenes and conducting steady-state/time-resolved photoluminescence and transient absorption spectroscopy analyses, we find that interfacial band bending between the perfluoroaryl group and polymer donor is responsible for exciton scissoring and subsequent electron trapping, which induces photomultiplication. Owing to the acceptor-free and covalently interconnected photoactive layer in the suggested PM-OPDs, superior operational and thermal stabilities were observed. Finally, we demonstrated finely patterned B-/G-/R-selective PM-OPD arrays that enable the construction of highly sensitive passive matrix-type organic image sensors. This article is protected by copyright. All rights reserved.

Depth-resolved method for attenuation coefficient calculation from optical coherence tomography data for improved biological structure visualization.

Optical coherence tomography (OCT) is a promising tool for intraoperative tissue morphology determination. Several studies suggest that attenuation coefficient derived from the OCT images, can differentiate between tissues of different morphology, such as normal and pathological structures of the brain, skin, and other tissues. In the present study, the depth-resolved method for attenuation coefficient calculation was adopted for the real-world situation of the depth-dependent OCT sensitivity and additive imaging noise with nonzero mean. It was shown that in the case of sharp focusing (~10 μm spot full width at half maximum [FWHM] or smaller at 1.3 μm central wavelength) only the proposed method for depth-dependent sensitivity compensation does not introduce misleading artifacts into the calculated attenuation coefficient distribution. At the same time, the scanning beam focus spot with FWHM greater than 10 μm at 1.3 μm central wavelength allows one to use multiple approaches to the attenuation coefficient calculation without introducing noticeable bias. This feature may hinder the need for robust corrections for the depth-resolved attenuation coefficient estimations from the community.

Imaging in spinal infections: Current status and future directions

Imaging plays an important role in the diagnosis of spinal infections. Early diagnosis is paramount in the treatment of spinal infections and leads to improved outcomes. This article reviews the imaging and relevant clinical details of infections of the spine: pyogenic spondylodiscitis, tuberculous spondylodiscitis, septic facet arthritis, epidural abscess, and subdural abscess. Though radiographs can reveal subtle changes with infections, advanced imaging modalities have increased sensitivity to aid in early diagnosis. Magnetic resonance imaging (MRI) is emphasized given it is generally the most sensitive and specific advanced imaging modality. However, nuclear medicine imaging and computer tomography (CT) play a role diagnosis in cases where MRI is not available or contra-indicated. Additionally, CT is also important for image-guided biopsy to guide antimicrobial treatment.

Integration of Ecosystem Services and Habitats into the Biodiversity Atlas Austria

The Biodiversity Atlas Austria (“Biodiversitäts-Atlas Österreich”) is a data portal to explore Austria’s biodiversity. It is based on the open-source infrastructure of the Atlas of Living Australia (ALA) and was launched with support of the Living Atlas (LA) community in late 2019 by the Biodiversity Hub of the University of Continuing Education Krems funded by the Government of Lower Austria. At present, it stores more than 8.5 million species occurrence records from various data partners and institutions and is available in both English and German. The Atlas is running on two virtual machines with 4 TB storage and is hosting many of the ALA-developed tools and services such as collectory, biocache, biodiversity information explorer, regions, spatial portal, sensitive data service, lists, images, and dashboard. In the project “ÖKOLEITA” (2021-2023), two new tools were developed within the existing LA infrastructure and will be launched in late 2023 to allow users to deal with ecosystem services and habitat data. The “ecosys”-tool will allow management, visualization, and analysis of ecosystem services by uploading different (raster or vector) TIFF files containing mapped ecosystem services to the geoserver. Users will be able to inspect various ecosystem services at a specific geolocation or compare different geolocations or a transect on their respective ecosystem service potential. The ecosystem service values are presented on the one hand as pictograms, where the value is transformed into quintiles, orienting on the work by Schreder et al. (2018), and as bar chart showing the true values. The “habitat” tool will store and manage datasets of habitat mappings (shapefiles) and allow users to spatially explore those various habitat mappings on a map. Users will be able to search for specific habitats across all datasets or a specific one and get all occurrences of this habitat type returned. Through linkage to the biocache, a click on a specific area reveals the list of species found within that habitat recording, as well as all the species occurrences within that area stored in the database. A “habitat backbone” of the most used habitat classifications in Austria will allow dealing with habitat mappings that use different classifications. Both tools are integrated into the Living Atlases infrastructure and communicate with the other tools and services of the Biodiversity Atlas Austria (Fig. 1). They share a common administration back-end but have different front-ends, where the users can explore the ecosystem services and habitats spatially and in connection with species occurrence records and other contextual information.

68Ga-bisphosphonates for the imaging of extraosseous calcification by positron emission tomography

Radiolabelled bisphosphonates (BPs) and [18F]NaF (18F-fluoride) are the two types of radiotracers available to image calcium mineral (e.g. bone), yet only [18F]NaF has been widely explored for the non-invasive molecular imaging of extraosseous calcification (EC) using positron emission tomography (PET) imaging. These two radiotracers bind calcium mineral deposits via different mechanisms, with BPs chelating to calcium ions and thus being non-selective, and [18F]NaF being selective for hydroxyapatite (HAp) which is the main component of bone mineral. Considering that the composition of EC has been reported to include a diverse range of non-HAp calcium minerals, we hypothesised that BPs may be more sensitive for imaging EC due to their ability to bind to both HAp and non-HAp deposits. We report a comparison between the 68Ga-labelled BP tracer [68Ga]Ga-THP-Pam and [18F]NaF for PET imaging in a rat model of EC that develops macro- and microcalcifications in several organs. Macrocalcifications were identified using preclinical computed tomography (CT) and microcalcifications were identified using µCT-based 3D X-ray histology (XRH) on isolated organs ex vivo. The morphological and mineral analysis of individual calcified deposits was performed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). PET imaging and ex vivo analysis results demonstrated that while both radiotracers behave similarly for bone imaging, the BP-based radiotracer [68Ga]Ga-THP-Pam was able to detect EC more sensitively in several organs in which the mineral composition departs from that of HAp. Our results strongly suggest that BP-based PET radiotracers such as [68Ga]Ga-THP-Pam may have a particular advantage for the sensitive imaging and early detection of EC by being able to detect a wider array of relevant calcium minerals in vivo than [18F]NaF, and should be evaluated clinically for this purpose.

Dye-sensitized rare-earth-doped nanoprobe for simultaneously enhanced NIR-II imaging and precise treatment of bacterial infection

Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for causing life-threatening infections that result in high morbidity and mortality rates. The development of advanced imaging and therapeutic methods for in vivo diagnosis and treatment of MRSA infections remains challenging. Here, we develop a hybrid nanoplatform based on rare-earth-doped nanoparticles (RENPs) sensitized by a moiety-engineered near-infrared (NIR) TPEO-820 dye and with a ZIF-8 layer that incorporates CysNO, a photochemically triggered nitric oxide donor. We then use the hybrid for both NIR-II bioimaging and photoactivatable treatment of MRSA-infected wounds. We show that the NIR dye sensitization leads to an 8.5-fold enhancement of the downshifting emission and facilitates deep-tissue NIR-II imaging of bacterial infections. Moreover, the sensitization strategy enhances the UV emission of RENPs by two orders of magnitude, leading to the efficiently controllable release of nitric oxide for effective disinfection of MRSA in vitro and in vivo. The hybrid nanoplatform thus offers promising opportunities for simultaneous localization and controllable treatment of MRSA. Statement of SignificanceEarly detection and treatment of MRSA infections are crucial for reducing public health risks. It is a significant challenge that develops sensitive in vivo diagnosis and complete elimination of drug-resistant bacterial infections. Herein, a nanoplatform has been developed for photoactivatable therapy of MRSA infections and deep tissue NIR-II imaging. This platform utilizes lanthanide-doped rare earth nanoparticles (RENPs) that are sensitized by a moiety-engineered near-infrared (NIR) dye TPEO-820. The TPEO-820 sensitized RENPs exhibit 5 times increase in the release of NO concentration for MRSA treatment compared to unsensitized RENPs, enabling precise therapy of MRSA infection both in vitro and in vivo. Moreover, the platform demonstrates NIR-II luminescence in vivo, allowing for sensitive imaging in deep tissue for MRSA infection.

The diamagnetic component map from quantitative susceptibility mapping (QSM) source separation reveals pathological alteration in Alzheimer’s disease-driven neurodegeneration

A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.

Current and Future of "Turn-On" Based Small-Molecule Copper Probes for Cuproptosis.

Increasing evidence shows that abnormal copper (Cu) metabolism is highly related to many diseases, such as Alzheimer's disease, Wilson's disease, hematological malignancies and Menkes disease. Very recently, cuproptosis, a Cu-dependent, programmed cell death was firstly described by Tsvetkov et al. in 2022. Their findings may provide a new perspective for the treatment of related diseases. However, the concrete mechanisms of these diseases, especially cuproptosis, remain completely unclear, the reason of which may be a lack of reliable tools to conduct highly selective, sensitive and high-resolution imaging of Cu in complex life systems. So far, numerous small-molecular fluorescent probes have been designed and utilized to explore the Cu signal pathway. Among them, fluorescence turn-on probes greatly enhance the resolution and accuracy of imaging and may be a promising tool for research of investigation into cuproptosis. This review summarizes the probes developed in the past decade which have the potential to study cuproptosis, focusing on the design strategies, luminescence mechanism and biological-imaging applications. Besides, we put forward some ideas concerning the design of next-generation probes for cuproptosis, aiming to tackle the main problems in this new field. Furthermore, the prospect of cuproptosis in the treatment of corresponding diseases is also highlighted.

Multifunctional Near-Infrared Dye IR-817 Encapsulated in Albumin Nanoparticles for Enhanced Imaging and Photothermal Therapy in Melanoma.

Near-infrared cyanine dyes have high sensitivity and spatial resolution imaging capabilities, but they also have unavoidable drawbacks such as photobleaching, low water solubility, fluorescence quenching, and toxic side effects. As an effective biologic drug carrier, albumin combines with cyanine dyes to form albumin@dye nanoparticles. These nanoparticles can alleviate the aforementioned issues and are widely used in tumor imaging and photothermal therapy. Herein, a newly synthesized near-infrared dye IR-817 was combined with bovine serum albumin (BSA) to create BSA@IR-817 nanoparticles. Through the detection of fluorescence emission and absorption, the optimal concentration and ratio of BSA and IR-817 were determined. Subsequently, dynamic light scattering (DLS) measurements and scanning electron microscopy (SEM) were used for the physical characterization of the BSA@IR-817 nanoparticles. Finally, in vitro and in vivo experiments were conducted to assess the fluorescence imaging and photothermal therapeutic potential of BSA@IR-817 nanoparticles. IR-817 was adsorbed onto the BSA carrier by covalent conjugation and supramolecular encapsulation, resulting in the formation of dispersed, homogeneous, and stable nanoparticles with a particle size range of 120-220 nm. BSA@IR-817 not only improved the poor water solubility, fluorescence quenching, and toxic side effects of IR-817 but also enhanced the absorption and fluorescence emission peaks in the near-infrared region, as well as the fluorescence in the visible spectrum. In addition, BSA@IR-817 combined with laser 808 irradiation was able to convert light energy into heat energy with temperatures exceeding 50 °C. By creating a mouse model of subcutaneous melanoma, it was discovered that the tumor inhibition rate of BSA@IR-817 was greater than 99% after laser irradiation and that it achieved nearly complete tumor ablation without causing significant toxicity. Our research, therefore, proposes the use of safe and effective photothermal nanoparticles for the imaging, diagnosis, and treatment of melanoma, and offers a promising strategy for future biomedical applications.

Automatic Transformation Search Against Deep Leakage From Gradients.

Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their training sets. However, recent works discovered that an adversary can fully recover the sensitive training samples from the shared gradients. Such reconstruction attacks pose severe threats to collaborative learning. Hence, effective mitigation solutions are urgently desired. In this paper, we systematically analyze existing reconstruction attacks and propose to leverage data augmentation to defeat these attacks: by preprocessing sensitive images with carefully-selected transformation policies, it becomes infeasible for the adversary to extract training samples from the corresponding gradients. We first design two new metrics to quantify the impacts of transformations on data privacy and model usability. With the two metrics, we design a novel search method to automatically discover qualified policies from a given data augmentation library. Our defense method can be further combined with existing collaborative training systems without modifying the training protocols. We conduct comprehensive experiments on various system settings. Evaluation results demonstrate that the policies discovered by our method can defeat state-of-the-art reconstruction attacks in collaborative learning, with high efficiency and negligible impact on the model performance.

Multielement Z-tag imaging by X-ray fluorescence microscopy for next-generation multiplex imaging

Rapid, highly multiplexed, nondestructive imaging that spans the molecular to the supra-cellular scale would be a powerful tool for tissue analysis. However, the physical constraints of established imaging methods limit the simultaneous improvement of these parameters. Whole-organism to atomic-level imaging is possible with tissue-penetrant, picometer-wavelength X-rays. To enable highly multiplexed X-ray imaging, we developed multielement Z-tag X-ray fluorescence (MEZ-XRF) that can operate at kHz speeds when combined with signal amplification by exchange reaction (SABER)-amplified Z-tag reagents. We demonstrated parallel imaging of 20 Z-tag or SABER Z-tag reagents at subcellular resolution in cell lines and multiple human tissues. We benchmarked MEZ-XRF against imaging mass cytometry and demonstrated the nondestructive multiscale repeat imaging capabilities of MEZ-XRF with rapid tissue overview scans, followed by slower, more sensitive imaging of low-abundance markers such as immune checkpoint proteins. The unique multiscale, nondestructive nature of MEZ-XRF, combined with SABER Z-tags for high sensitivity or enhanced speed, enables highly multiplexed bioimaging across biological scales.

Influence of mammographic density and compressed breast thickness on true mammographic sensitivity: a cohort study

Understanding the detectability of breast cancer using mammography is important when considering nation-wide screening programmes. Although the role of imaging settings on image quality has been studied extensively, their role in detectability of cancer at a population level is less well studied. We wish to quantify the association between mammographic screening sensitivity and various imaging parameters. Using a novel approach applied to a population-based breast cancer screening cohort, we specifically focus on sensitivity as defined in the classical diagnostic testing literature, as opposed to the screen-detected cancer rate, which is often used as a measure of sensitivity for monitoring and evaluating breast cancer screening. We use a natural history approach to model the presence and size of latent tumors at risk of detection at mammography screening, and the screening sensitivity is modeled as a logistic function of tumor size. With this approach we study the influence of compressed breast thickness, x-ray exposure, and compression pressure, in addition to (percent) breast density, on the screening test sensitivity. When adjusting for all screening parameters in addition to latent tumor size, we find that percent breast density and compressed breast thickness are statistically significant factors for the detectability of breast cancer. A change in breast density from 6.6 to 33.5% (the inter-quartile range) reduced the odds of detection by 61% (95% CI 48–71). Similarly, a change in compressed breast thickness from 46 to 66 mm reduced the odds by 42% (95% CI 21–57). The true sensitivity of mammography, defined as the probability that an examination leads to a positive result if a tumour is present in the breast, is associated with compressed breast thickness after accounting for mammographic density and tumour size. This can be used to guide studies of setups aimed at improving lesion detection. Compressed breast thickness—in addition to breast density—should be considered when assigning complementary screening modalities and personalized screening intervals.

Privacy-Preserving Convolutional Bi-LSTM Network for Robust Analysis of Encrypted Time-Series Medical Images

Deep learning (DL) algorithms can improve healthcare applications. DL has improved medical imaging diagnosis, therapy, and illness management. The use of deep learning algorithms on sensitive medical images presents privacy and data security problems. Improving medical imaging while protecting patient anonymity is difficult. Thus, privacy-preserving approaches for deep learning model training and inference are gaining popularity. These picture sequences are analyzed using state-of-the-art computer aided detection/diagnosis techniques (CAD). Algorithms that upload medical photos to servers pose privacy issues. This article presents a convolutional Bi-LSTM network to assess completely homomorphic-encrypted (HE) time-series medical images. From secret image sequences, convolutional blocks learn to extract selective spatial features and Bi-LSTM-based analytical sequence layers learn to encode time data. A weighted unit and sequence voting layer uses geographical with varying weights to boost efficiency and reduce incorrect diagnoses. Two rigid benchmarks—the CheXpert, and the BreaKHis public datasets—illustrate the framework’s efficacy. The technique outperforms numerous rival methods with an accuracy above 0.99 for both datasets. These results demonstrate that the proposed outline can extract visual representations and sequential dynamics from encrypted medical picture sequences, protecting privacy while attaining good medical image analysis performance.

A simple and robust nanosystem for photoacoustic imaging of bladder cancer based on α5β1-targeted gold nanorods

BackgroundEarly detection and removal of bladder cancer in patients is crucial to prevent tumor recurrence and progression. Because current imaging techniques may fail to detect small lesions of in situ carcinomas, patients with bladder cancer often relapse after initial diagnosis, thereby requiring frequent follow-up and treatments.ResultsIn an attempt to obtain a sensitive and high-resolution imaging modality for bladder cancer, we have developed a photoacoustic imaging approach based on the use of PEGylated gold nanorods (GNRs) as a contrast agent, functionalized with the peptide cyclic [CphgisoDGRG] (Iso4), a selective ligand of α5β1 integrin expressed by bladder cancer cells. This product (called GNRs@PEG-Iso4) was produced by a simple two-step procedure based on GNRs activation with lipoic acid-polyethyleneglycol(PEG-5KDa)-maleimide and functionalization with peptide Iso4. Biochemical and biological studies showed that GNRs@PEG-Iso4 can efficiently recognize purified integrin α5β1 and α5β1-positive bladder cancer cells. GNRs@PEG-Iso4 was stable and did not aggregate in urine or in 5% sodium chloride, or after freeze/thaw cycles or prolonged exposure to 55 °C, and, even more importantly, do not settle after instillation into the bladder. Intravesical instillation of GNRs@PEG-Iso4 into mice bearing orthotopic MB49-Luc bladder tumors, followed by photoacoustic imaging, efficiently detected small cancer lesions. The binding to tumor lesions was competed by a neutralizing anti-α5β1 integrin antibody; furthermore, no binding was observed to healthy bladders (α5β1-negative), pointing to a specific targeting mechanism.ConclusionGNRs@PEG-Iso4 represents a simple and robust contrast agent for photoacoustic imaging and diagnosis of small bladder cancer lesions.Graphical

PP-JPEG: A Privacy-Preserving JPEG Image-Tampering Localization.

The widespread availability of digital image-processing software has given rise to various forms of image manipulation and forgery, which can pose a significant challenge in different fields, such as law enforcement, journalism, etc. It can also lead to privacy concerns. We are proposing that a privacy-preserving framework to encrypt images before processing them is vital to maintain the privacy and confidentiality of sensitive images, especially those used for the purpose of investigation. To address these challenges, we propose a novel solution that detects image forgeries while preserving the privacy of the images. Our method proposes a privacy-preserving framework that encrypts the images before processing them, making it difficult for unauthorized individuals to access them. The proposed method utilizes a compression quality analysis in the encrypted domain to detect the presence of forgeries in images by determining if the forged portion (dummy image) has a compression quality different from that of the original image (featured image) in the encrypted domain. This approach effectively localizes the tampered portions of the image, even for small pixel blocks of size 10×10 in the encrypted domain. Furthermore, the method identifies the featured image's JPEG quality using the first minima in the energy graph.

Three-dimensional spatial quantitative analysis of cardiac lymphatics in the mouse heart.

Three-dimensional (3D) microscopy and image data analysis are necessary for studying the morphology of cardiac lymphatic vessels (LyVs) and their association with other cell types. We aimed to develop a methodology for 3D multiplexed lightsheet microscopy and highly sensitive and quantitative image analysis to identify pathological remodeling in the 3D morphology of LyVs in young adult mouse hearts with familial hypertrophic cardiomyopathy (HCM). We developed a 3D lightsheet microscopy workflow providing a quick turn-around (as few as 5-6 days), multiplex fluorescence detection, and preservation of LyV structure and epitope markers. Hearts from non-transgenic and transgenic (TG) HCM mice were arrested in diastole, retrograde perfused, immunolabeled, optically cleared, and imaged. We built an image-processing pipeline to quantify LyV morphological parameters at the chamber and branch levels. Chamber-specific pathological alterations of LyVs were identified, and significant changes were seen in the right atrium (RA). TG hearts had a higher volume percent of ER-TR7+ fibroblasts and reticular fibers. In the RA, we found associations between ER-TR7+ volume percent and both LyV segment density and median diameter. This workflow and study enabled multi-scale analysis of pathological changes in cardiac LyVs of young adult mice, inviting ideas for research on LyVs in cardiac disease.

Developing fluorescence-improved fluoran dyes and applying for a copper selective and sensitive fluorescent probe and cell imaging

Developing fluoran dyes for fluorescent material is significant but challenging because they are notorious for terrible luminescent efficiency. In this manuscript, two fluoran dyes (F3 and F4) were synthesized by the introduction of thiazole and indazole into the fluoran skeleton, which showed colored and fluorescent spirolactone opening form in a wide pH range (F3: 1–10, F4: 1–13). In addition, the absorption and emission spectra of methyl esterification products F3Me and F4Me showed large Stokes shifts (over 75 nm) in water and achieved an improved fluorescence quantum yield of 30.1% in CHCl3. Based on the dye F4Me, a new fluorescent probe F4HP was developed, which showed high selectivity and high sensitivity (LOD of 2.0 nM) to copper ions in H2O/CH3CN (v/v, 3/2) system. Moreover, the sensing experiment was allowed in the pH range of 4.0–7.5. Furthermore, the F4HP exhibits suitable cell cytotoxicity and can be applied for imaging intracellular copper ions by confocal fluorescence imaging technology.

Hypoxia-Responsive T2-to-T1 Dynamically Switchable Extremely Small Iron Oxide Nanoparticles for Sensitive Tumor Imaging In Vivo.

To realize the accurate diagnosis of tumors by magnetic resonance imaging (MRI), switchable magnetic resonance contrast agents (CAs) between T1 and T2 contrast enhancement that are constructed based on extremely small iron oxide nanoparticles (ESIONPs) have been developed in recent years. We herein report, for the first time, a novel ESIONP-based nanocluster (named EAmP), which exhibited hypoxia responsiveness to the tumor microenvironment and offered a T2-to-T1-switchable contrast enhancement function, effectively distinguishing between the normal tissue and tumor tissue. In detail, active perfluorophenyl ester-modified ESIONPs with a diameter of approximately 3.6 nm were initially synthesized, and then 4,4'-azodianiline was used as a cross-linker to facilitate the formation of nanoclusters from ESIONPs through the reaction between the active ester and amine. Finally, poly(ethylene glycol) was further modified onto nanoclusters by utilizing the remaining active ester residues. The resulting EAmP demonstrated satisfactory colloidal stability and favorable biosafety and exhibited a desired T2-to-T1-switchable function, as evidenced by conversion from nanocluster to the dispersed state and a significant decrease in the r2/r1 ratio from 14.86 to 1.61 when exposed to a mimical hypoxic environment in the solution. Moreover, EAmP could decompose into dispersed ESIONPs at the tumor region, resulting in a switch from T2 to T1 contrast enhancement. This T2-to-T1-switchable contrast agent offers high sensitivity and signal-to-noise ratio to realize the accurate diagnosis of tumors. In conclusion, hypoxia-responsive EAmP is a potential MRI nanoprobe for improving the diagnostic accuracy of solid tumors.

Hairpin cascade circuits on programmable DNA-nucleated spherical nucleic acid for intracellular targeted microRNA imaging

DNA molecular probes have been increasingly used for biological imaging and tumor theranostics. In particular, live-cell imaging of low abundance microRNA (miRNA) with high accuracy and efficiency was extremely important for understanding functions and dynamics of miRNA. Herein, an easy-to-obtain DNA-nucleated spherical nucleic acid (DSNA) was constructed by one pair of hairpin probes “sticked” on self-assembled three-dimensional (3D) urchin-like DNA nanostructures (UDNs) to realize sensitive imaging of tumor-related miRNA in living cells. UDNs were prepared through four short single-stranded DNA by a simple “one-pot” annealing process that took only a few minutes. Moreover, sticking the reactants of hairpin probes on the UDNs not only sped up the reaction kinetic rate, but also improved the sensitivity and efficiency of miRNA-triggered hairpin cascade circuits. Compared with traditional AuNP-based spherical nucleic acid, the DSNA possessed superb biocompatibility and stability, excellent cell internalization capability and accessibility, which endowed them tremendous advantages for the monitoring of miRNA in living cells. Therefore, our developed strategy exhibited great potential in sensitive imaging of intracellular miRNA, offering a new avenue for early tumor diagnosis and related biomedical research.