Near-infrared Signals Research Articles

High-performing organic/quantum dot hybrid upconversion device based on a single-component near-infrared-sensitive layer

A donor/acceptor (D/A) heterojunction with an interfacial energetic offset is demonstrated to enable efficient exciton dissociation in organic photodetectors and upconversion devices (UCDs). Unfortunately, this approach usually encounters complicated optimization procedures and interfacial instability. Herein, we present an alternative strategy for achieving high-performing UCDs by utilizing an organic single-component near-infrared (NIR)-sensitive layer instead of a D/A heterojunction. The showcased UCD is constructed by vertically stacking an organic single-component Y6 NIR-detection unit and a quantum dot light-emitting unit. Due to the high dielectric constant and low exciton binding energy of the non-fullerene acceptor Y6, free carriers are directly and spontaneously generated upon NIR light excitation. As a result, the single-component UCD achieves a low light detection capability of 2.5 μW/cm2, a fast refresh rate of >3.8 × 104, and a high resolution exceeding 1100 dpi, providing a stable optical response to high-frequency NIR signals and high-quality NIR imaging.

Parathyroid gland identification and angiography classification using simple machine learning methods.

Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals. Near-infrared indocyanine green-parathyroid gland angiography video recordings (Fluobeam® LX, Fluoptics, Grenoble-part of Getinge-Göteborg) from patients undergoing endocrine cervical surgery in a high-volume unit were used for model development. Computation (MATLAB, Mathworks, Ireland) included segmentation-identification of the parathyroid gland (by autofluorescence), image stabilization (by linear translation) and adjusted time-fluorescence intensity profile generation. Relative upslope and maximum intensity ratios then trained a simple logistic regression model based on expert interpretation and outcome (including hypoparathyroidism), with subsequent unseen testing for validation. The model was trained on 37 patient videos (45 glands, 29 judged well perfused by parathyroid gland angiography experts), achieving feature data separation with 100% accuracy, and tested on 22 unseen videos (27 glands, 15 judged well perfused), including four in real time. Segmentation-guided parathyroid gland detection correctly identified all parathyroid glands during unseen testing along with three additional non-parathyroid gland regions (90% positive predictive value). Subsequent time-fluorescence intensity profile extraction with vitality prediction was shown feasible in all cases within 5 min, with a 96.3% model accuracy (sensitivity and specificity were 93.3 and 100% respectively) when compared with expert judgement. Automatic parathyroid gland perfusion quantification using simple machine learning computational methods discriminates parathyroid gland perfusion in concordance with expert surgeon interpretation, providing a means for near-infrared indocyanine green-parathyroid gland signal evaluation.

Near-infrared light-enhanced colorimetric signal amplification strategy for tumor marker detection based on MoS2/CuO/Au nanocomposite.

Anovel signal amplification strategy was developedby combining near-infrared light with MoS2/CuO/Au nanocomposite for building acolorimetric immunoassay. First, MoS2/CuO/Au nanocomposite was synthesized by precipitation and photoreduction methods and characterized by scanning electron microscopy (SEM) and X-ray powder diffraction (XRD). MoS2/CuO/Au nanocomposite has oxidase-like activity and can oxidize TMB to form a blue product (TMBox). Further, the catalytic oxidation of TMB was accelerated under near-infrared (NIR) laser radiation. The sandwich-type colorimetric immunoassay was constructed using MoS2/CuO/Au nanocomposite. Under the enhancement of near-infrared light, carcinoembryonic antigen (CEA) was sensitively detected in the range 0.1 to 40ng/mL with the limit of detection of 0.03ng/mL. Moreover, the immunosensor has excellent selectivity and anti-interference, good repeatability, and stability.

The use of artificial intelligence to detect parathyroid tissue on ex vivo specimens during thyroidectomy and parathyroidectomy procedures using near-infrared autofluorescence signals

In thyroidectomy and parathyroidectomy procedures, diagnostic dilemmas related to whether an index tissue is of parathyroid or nonparathyroid origin frequently arise. Current options of frozen section and parathyroid aspiration are time-consuming. Parathyroid glands appear brighter than surrounding tissues on near-infrared autofluorescence imaging. The aim of this study was to develop an artificial intelligence model differentiating parathyroid tissue on surgical specimens based on near-infrared autofluorescence. With institutional review board approval, an image library of exvivo specimens obtained in thyroidectomy and parathyroidectomy procedures was created between November 2019 and April 2023 at a single academic center. Exvivo autofluorescence images of surgically removed parathyroid glands, thyroid glands, lymph nodes, and thymic tissue were uploaded into an artificial intelligence platform. Two different models were trained, with the first model using autofluorescence images from all specimens, including thyroid, and the second model excluding thyroid, to prevent the effect of specimen size on the results. Deep-learning models were trained to detect autofluorescence signals specific to parathyroid glands. Randomly chosen 80% of data were used for training, 10% for validation, and 10% for testing. Recall, precision, and area under the curve of models were calculated. Surgical procedures included 377 parathyroidectomies, 239 total thyroidectomies, 97 thyroid lobectomies, and 32 central neck dissections. For the development of the model, 1151 images from a total of 678 procedures were used. The dataset comprised 648 parathyroid, 379 thyroid, 104 lymph node, and 20 thymic tissue images. The overall precision, recall, and area under the curve of the model to detect parathyroid tissue were 96.5%, 96.5%, and 0.985, respectively. False negatives were related to dark and large parathyroid glands. The visual deep-learning model developed to identify parathyroid tissue in exvivo specimens during thyroidectomy and parathyroidectomy demonstrated a high sensitivity and positive predictive value. This suggests potential utility of near-infrared autofluorescence imaging to improve intraoperative efficiency by reducing the need for frozen sections and parathyroid hormone aspirations to confirm parathyroid tissue.

The potential of deep learning to counter the matrix effect for assessment of honey quality and monoflorality

The complexity of biological matrices affects Near-infrared (NIR) signals. Honey, a complex food matrix, changes in chemical and physical properties over time indicating strong matrix effects when capturing NIR spectra. The varied floral sources in most honeys also contribute to this effect. A real dataset of 1656 honey samples spanning eight geographic districts of the North Island of New Zealand captured by NIR hyperspectral camera was analyzed with machine learning and deep learning models to assess mānuka honey quality and identity. One-dimensional neural network (1D-CNN) showed high capacity to accommodate the complexity of the honey matrix, better than did linear machine learning models, particularly for prediction of a trademarked continuous quality score of mānuka honey, known as Unique Mānuka Factor (UMFTM). Monofloral mānuka honey was distinguished well from multi-floral and non-mānuka when classified with 1D-CNN, achieving > 90 % class accuracy, better than conventional classifiers. Interestingly, 1D-CNN models could precisely identify important spectral regions such as Visible (666–725 nm) & NIR (991 and 1435 nm) supporting the evaluation of mānuka honey quality and determining botanical origin as Leptospermum scoparium. Both are useful for future model development and application to automated assessment of honey quality and monoflorality before lumped extraction.

A novel lysosome-targeting BODIPY-based fluorescent probe with two near-infrared channel signals for ratiometric detection of HClO and its application in diabetes mice model

Diabetes is an endocrine and metabolic disease characterized by hyperglycemia, which can lead to a variety of serious complications. Hypochlorous acid (HClO), one of the significant members of reactive oxygen species (ROS), is essential for various physiological processes, and the acidic lysosomes of phagocytes are one of its main sources. The related studies suggest that abnormal levels of HClO in the body have a strong association with diabetic process, but the pathological mechanisms of HClO on diabetic diseases are still unclear. Here, a novel ratiometric lysosome-targeted BODIPY-based fluorescence probe Lyso-HClO was designed for specific recognition of HClO. Lyso-HClO could rapidly sense HClO within 20 s, and its limit of detection was calculated as low as 45 nM. Both the emission wavelengths of Lyso-HClO before and after reaction of HClO reached the near-infrared region, which effectively reduced tissue damage and eliminated background interference from organisms to achieve more accurate analysis. Lyso-HClO was successfully employed for fluorescence imaging of both exogenous and endogenous HClO in RAW264.7 cells, HepG2 cells, and zebrafish. Additionally, it was effectively utilized to monitor the HClO fluctuations in diabetic mice, exhibiting a 15-fold increase in the fluorescence signal ratio (I650/I685). Therefore, the probe Lyso-HClO has enormous potential for the early diagnosis and prevention of diabetes and its complications.

Comparative analysis of NIR point source and surface array probes in two-phase flow measurement model

As one of the most significant parameters, phase fraction is of great importance for ensuring the accuracy of two-phase flow measurement. Although near-infrared (NIR) technology has been widely used, its accuracy remains limited. Two methods have been proposed to reduce the energy loss of near-infrared light transmission signal in two-phase flow: the point light source method, which shortens optical path and the array light source method for increasing light source area. Experiments were conducted on single phase flow and gas–liquid two-phase flow, and the results indicated that the signal transmission effect of the point source near-infrared device was better. Using the experimental results from the point source near-infrared device, phase fraction models for bubble flow, annular flow, and slug flow were established. Validation results demonstrate that the relative measurement error of the three phase fraction models is within ± 4.96 %.

NIR-activated water-soluble molecular probe based on Cu(ii) ion quenching mechanisms and substituted strategies: For in vitro/in vivo H2S detection

Human health, environmental contamination, and food safety are tightly associated with hydrogen sulfide (H2S). The safe and highly sensitive monitoring of H2S in tissues, organs, and blood has presented ongoing challenges. Herein, a novel near-infrared (NIR)-activated water-soluble molecular probe, denoted as IR820-TPY-Cu was developed for detecting hydrogen sulfide. This probe is built upon the fluorescent molecule IR820, a derivative of Indocyanine green (ICG). Upon reacting with H2S, IR820-TPY-Cu exhibits active fluorescence (670–750 nm), which is attributed to the Cu (II) ion quenching mechanism and substitution strategy. IR820-TPY-Cu exhibits selectively activated near-infrared fluorescence signal changes, a low detection limit of 0.114 μM, and a rapid in vitro response (3 min) for H2S detection. Moreover, the biocompatible probe IR820-TPY-Cu not only quantitatively monitors H2S in environmental water and various food specimens (red wine, beer, meat, milk, and sweet potato) through colorimetric sensing but also successfully images endogenous and exogenous H2S in living cells, zebrafish, and mice. This research provides a promising approach for monitoring H2S in environmental contamination, ensuring food safety, and studying living systems.

Albumin-mediated molecular competition of supramolecular photosensitizers for NIR-II imaging-guided phototherapy

Heptamethine cyanines (Cy7) typically exhibit strong near-infrared (NIR) fluorescence signals when in monodisperse states, but their distinctive π-conjugated structure leads to limited solubility in aqueous solutions, ultimately resulting in inherent fluorescence self-quenching. Enhancing the fluorescence quantum yield of these agents within aqueous environments, in order to achieve high-resolution biological imaging, presents a significant challenge. Herein, a benzothiazole-based Cy7-derivative (Cy7-BTH) is developed, exhibiting unique H-aggregation properties in aqueous solutions. Bovine serum albumin (BSA) binds to Cy7-BTH (BSA@Cy7-BTH) to modulate its molecular stacking and energy transfer, boosting its fluorescence accompanied by bright NIR-II tail emission. The competitive binding alters the planarity of Cy7-BTH, restricting its intramolecular rotation, and simutaneously changes the conformation of BSA, leading to BSA@Cy7-BTH aggregation to form hierarchical-structured nanoparticles. Notably, the BSA@Cy7-BTH nanoparticles significantly enhanced photothermal response of Cy7-BTH while maintaining its controlled reactive oxygen species (ROS) generation, offering NIR-II imaging-guided surgical removal of primary tumors, and simultaneously inhibiting cancer cell metastasis by synergistic PDT/PTT dissection of metastatic tumor cells in sentinel lymph nodes (SLNs). This study provides an innovative but facile strategy for their potential clinical applications by precisely regulating the intermolecular competitive interactions of NIR theranostic agents.

Development Of Hardware and Software For A NonInvasive Glucometer Based On A Microcontroller

In modern medical practice, there is a tendency to widely use non-invasive methods of monitoring and diagnosing patients. Diabetes is known to be the main cause of many types of severe diseases and if the patient is not properly taken care of in a timely manner, it eventually leads to death. This disease occurs when blood glucose levels exceed a threshold value. Therefore, regular monitoring of blood glucose levels is a prerequisite for caring for patients with diabetes. Current methods for testing blood glucose levels are invasive methods that rely on needles that are inserted into a person's body to take a blood sample from the body, which is then transferred to disposable test strips for a chemical treatment to determine the amount of glucose present. However, attempts to relieve patient pain and discomfort have led to the development of non-invasive methods for controlling sugar levels. These methods use a near-infrared sensor to detect glucose levels from your fingertip without the use of needles or test strips. A near-infrared (NIR) optical signal is transmitted through one side of the fingertip and then received at the other side, which predicts the molecular count of blood glucose by analyzing the change in intensity of the received signal after its passage. In this work, we developed such a system using a microcontroller and other electronic parts. Before this, we developed a simulation model in the Proteus environment

Using ICG navigation in resection of a horseshoe kidney

BACKGROUND: In this publication, we present a new area of application of indocyanine green (ICG) imaging in pediatric surgery. We used this advanced method to evaluate the resection margins of a functional segment of the horseshoe kidney after intravenous indocyanine green. CLINICAL CASE DESCRIPTION: The article presents a case of treatment of a horseshoe kidney complicated by vesicorenal reflux in the left segment and loss of function of the left segment. Resection of the left half of the horseshoe kidney was performed using fluoroscopic control with intravenous administration of indocyanine green. The surgery was performed using the RUBINA™ endovideosurgical system manufactured by KARL STORZ (Germany). RUBINA™ components offer a variety of ICG in near-infrared fluorescence signal imaging modes. Depending on the surgeon and the application, ICG in near-infrared fluorescence data can be used in different modes: image overlay mode, backup mode, color mapping mode. After confirming the boundaries of the perfused part of the kidney, laparoscopic resection of the functional half was performed at the level of the isthmus. The use of ICG imaging was very important in identifying healthy tissue that stained intensely green 2 minutes after intravenous indocyanine green administration. This margin check verifies the functioning renal parenchyma and allows the correct selection of the nephrectomy margin. The next day after the operation, an ultrasound examination of the renal remnant and perinephric space was performed — the rotation to the right hour of the horseshoe-shaped kidney was good and no accumulation of fluid was detected in the bed of the removed segment. A control ultrasound examination 6 months after the operation showed the preservation of the parenchyma of the right half of the kidney, which indicates the positive effect of the surgical procedure. CONCLUSION: ICG navigation is a promising method for noninvasive assessment of resection margins in patients with horseshoe kidneys.

Two-Photon Microscopy for the Study of Tendons.

Two-photon microscopy has emerged as a potent tool for evaluating deep tissue cells and characterizing the alignment of the extracellular matrix (ECM) in various biological systems. This technique relies on nonlinear light-matter interactions to detect two distinct signals: the second harmonic generated (SHG) diffusion signal, which facilitates the visualization of collagen fibers and their orientation, and the near-infrared excitation signal for imaging ultraviolet excited autofluorescence. SHG imaging proves especially effective in visualizing collagen fibers due to the non-centrosymmetric crystalline structure of fibrillar collagen I. Given that tendons are matrix-rich tissues with a limited number of cells, their high collagen content makes them ideal candidates for analysis using two-photon microscopy. Consequently, two-photon microscopy offers a valuable means to analyze and characterize collagen abnormalities in tendons. Its application extends to studying tendon development, injuries, healing, and aging, enabling the comprehensive characterization of tendon cells and their interactions with the ECM under various conditions using two-photon microscopy tools. This protocol outlines the use of two-photon microscopy in tendon biology and presents an adapted methodology to achieve effective imaging and characterization of tendon cells during development and after injury. The method allows the utilization of thin microscopic sections to create a comprehensive image of the ECM within tendons and the cells that interact with this matrix. Most notably, the article showcases a technique to generate 3D images using two-photon microscopy in animal models.

Capturing accurate kelp canopy extent: integrating tides, currents, and species-level morphology in kelp remote sensing

Surface-canopy forming kelps (Macrocystis pyrifera and Nereocystis luetkeana) can be monitored along the Northeast Pacific coast using remote sensing. These kelp canopies can be submerged by tides and currents, making it difficult to accurately determine their extent with remote sensing techniques. Further, both species have morphologically distinct canopies, each made up of structures with differing buoyancies, and it is not well understood whether the differing buoyancies between these species’ canopies affects their detectability with remote sensing technologies. Here, we collected in situ above-water spectral signatures for the surface-canopies of Nereocystis and Macrocystis, providing the first direct hyperspectral comparison between the structures that make up the canopies of these species. Additionally, we compare the strength of their red-edge and near-infrared band signals, as well as the normalized difference red-edge (NDRE) and normalized difference vegetation index (NDVI) values. At the bed level, we compare detection of kelp canopy extent using both NDRE and NDVI classified unoccupied aerial vehicle imagery. We also characterized how changing tides and currents submerge the canopies of both species, providing insights that will allow remote sensors to more accurately determine the extent of kelp canopy in remote sensing imagery. Observations of canopy structures paired with in situ hyperspectral data and simulated multispectral data showed that more buoyant kelp structures had higher reflectance in the near-infrared wavelengths, but even slightly submerged canopy structures had a higher reflectance in the red-edge rather than the near-infrared. The higher red-edge signal was also evident at the bed level in the UAV imagery, resulting in 18.0% more canopy classified with NDRE than with NDVI. The area of detected canopy extent decreased by an average of 22.5% per meter of tidal increase at low current speeds (<10 cm/s), regardless of the species present. However, at higher current speeds (up to 19 cm/s), Nereocystis canopy decreased at nearly twice the average rate of kelp beds in low-current conditions. Apart from the strong differences in high-current regions, a robust linear relationship exists between kelp canopy extent and tidal height, which can aid in understanding the errors associated with remote sensing imagery collected at different tidal heights.

Fluorophore Label-Free Light-up Near Infrared Deoxyribonucleic Acid Nanosensor for Monitoring Extracellular Potassium Levels.

Fluorescent DNA nanosensors have been widely used due to their unique advantages, among which the near-infrared (NIR) imaging mode can provide deeper penetration depth and lower biological background for the nanosensors. However, efficient NIR quenchers require ingenious design, complex synthesis, and modification, which severely limit the development of NIR DNA nanosensors. Label-free strategies based on G-quadruplex (G4) and NIR G4 dyes were first introduced into in situ extracellular imaging, and a novel NIR sensing strategy for the specific detection of extracellular targets is proposed. The strategy avoids complex synthesis and site-specific modification by controlling the change of the NIR signal through the formation of a G4 nanostructure. A light-up NIR DNA nanosensor based on potassium ion (K+)-sensitive G4 chain PS2.M was constructed to verify the strategy. PS2.M forms a stable G4 nanostructure in the presence of K+ and activates the NIR G4 dye CSTS, thus outputting NIR signals. The nanosensor can rapidly respond to K+ with a linear range of 5-50 mM and has good resistance to interference. The nanosensor with cholesterol can provide feedback on the changes in extracellular K+ concentration in many kinds of cells, serving as a potential tool for the study of diseases such as epilepsy and cancer, as well as the development of related drugs. The strategy can be potentially applied to the NIR detection of a variety of extracellular targets with the help of functional DNAs such as aptamer and DNAzyme.

Surface plasmon resonance assisted donor–acceptor type covalent polymeric framework for hybrid photodetectors

In this paper, a surface plasmon resonance assisted hybrid photodetector (PD) made of a low bandgap covalent polymeric framework material is experimentally demonstrated. The PD demonstrated a broadband photodetection capability ranging between 350 and 1550 nm with subsecond transients. The fabricated hybrid PD offered a remarkable responsivity and external quantum efficiency of 42.87 A/W and 11 873% at 410 nm, respectively. The peak detectivity is recorded to be 7.43×1013 Jones at 400 nm. Up to 1550 nm, the hybrid PD offered a responsivity > 0.4 A/W, thereby showcasing its efficacy even for the near-infrared signals. The time-dependent photoresponse study estimated the rise time and fall time of the fabricated PD to be approximately 0.31 and 0.22 s, respectively.

Signal Amplification and Near-Infrared Translation of Enzymatic Reactions by Nanosensors.

Enzymatic reactions are used to detect analytes in a range of biochemical methods. To measure the presence of an analyte, the enzyme is conjugated to a recognition unit and converts a substrate into a (colored) product that is detectable by visible (VIS) light. Thus, the lowest enzymatic turnover that can be detected sets a limit on sensitivity. Here, we report that substrates and products of horseradish peroxidase (HRP) and β-galactosidase change the near-infrared (NIR) fluorescence of (bio)polymer modified single-walled carbon nanotubes (SWCNTs). They translate a VIS signal into a beneficial NIR signal. Moreover, the affinity of the nanosensors leads to a higher effective local concentration of the reactants. This causes a non-linear sensor-based signal amplification and translation (SENSAT). We find signal enhancement up to ≈120x for the HRP substrate p-phenylenediamine (PPD), which means that reactions below the limit of detection in the VIS can be followed in the NIR (≈1000 nm). The approach is also applicable to other substrates such as 3,3'-5,5'-tetramethylbenzidine (TMB). An adsorption-based theoretical model fits the observed signals and corroborates the sensor-based enhancement mechanism. This approach can be used to amplify signals, translate them into the NIR and increase sensitivity of biochemical assays.

Signalverstärkung und Nah‐Infrarot Übersetzung von Enzymatischen Reaktionen mit Nanosensoren**

AbstractEnzymatische Reaktionen kommen in zahlreichen biochemischen Verfahren zum Nachweis von Analyten zum Einsatz. Um das Vorhandensein eines Analyten zu messen, werden die Enzyme an eine Erkennungseinheit konjugiert und wandeln ein Substrat in ein (farbiges) Produkt um, das im sichtbaren Bereich (VIS) des Spektrums nachgewiesen werden kann. Der niedrigste nachweisbare enzymatische Umsatz stellt somit eine Grenze für die Empfindlichkeit dar. Hier zeigen wir, dass Substrate und Produkte der Meerrettichperoxidase (HRP) und der β‐Galaktosidase die Fluoreszenz im nahen Infrarot (NIR) von einwandigen Kohlenstoffnanoröhren (SWCNTs) verändern, wenn diese mit (Bio−)Polymeren modifiziert sind. Durch die Fluoreszenz im NIR übersetzen die SWCNTs ein VIS‐Signal in ein NIR‐Signal. Zudem führt die Affinität der Nanosensoren zu einer höheren effektiven lokalen Konzentration der Reaktanten. Dies bewirkt eine nichtlineare sensorbasierte Signalverstärkung und ‐übersetzung (SENSAT). Für das HRP‐Substrat p‐Phenylendiamin (PPD) ergibt sich eine bis zu ≈120‐fache Signalverstärkung, die es erlaubt, Reaktionen unterhalb der VIS Nachweisgrenze im NIR (≈1000 nm) zu verfolgen. Der Ansatz ist auch auf andere Substrate wie 3,3‐5,5′‐Tetramethylbenzidin (TMB) anwendbar. Ein Adsorptionsmodell erklärt die beobachteten Signaländerung und bestätigt den Verstärkungsmechanismus. Mit Hilfe dieses Ansatzes lassen sich Signale von chromogenen enzymatischen Reaktionsprodukten verstärken, in den NIR‐Bereich übertragen und die Empfindlichkeit biochemischer Assays erhöhen.

Construction of a novel aminofluorene-based ratiometric near-infrared fluorescence probe for detecting carboxylesterase activity in living cells.

Herein, we constructed a novel aminofluorene-based fluorescence probe (FEN-CE) for the detection of carboxylesterase (CE) in living cells by a ratiometric near-infrared (NIR) fluorescence signal. FEN-CE with NIR emission (650 nm) could be hydrolyzed specifically by CE and transformed to FENH with the release of the self-immolative group, which exhibited a red-shifted emission peak of 680 nm. In addition, FEN-CE showed high selectivity for CE and was successfully used in the detection of CE activity in living cells through its ratiometric NIR fluorescence signals.

Aza-BODIPY-based polymeric nanoparticles for photothermal cancer therapy in a chicken egg tumor model.

A new push-pull aza-BODIPY (AZB-CF3) derivative comprised of dimethylamino groups and trifluoromethyl moieties was successfully synthesized. This derivative exhibited broad absorption in the near-infrared region in the range from 798 to 832 nm. It also exhibited significant near-infrared (NIR) signals in low-polar solvents with emission peaks around 835-940 nm, while non-fluorescence in high-polar environments due to the twisted intramolecular charge transfer (TICT) phenomenon. The nanoprecipitation of this compound with phospholipid-based polyethylene glycol (DSPE-PEG) yielded AZB-CF3@DSPE-PEG nanoparticles (NPs) with a hydrodynamic size of 70 nm. The NPs exhibited good photostability, colloidal stability, biocompatibility, and excellent photothermal (PTT) competence with a conversion efficiency (η) of 44.9%. These NPs were evaluated in vitro and in ovo in a 4T1 breast cancer cell line for NIR light-trigger photothermal therapy. Proven in the chicken egg tumor model, AZB-CF3@DSPE-PEG NPs induced severe vascular damage (∼40% vascular destruction), showed great anticancer efficacy (∼75% tumor growth inhibition), and effectively inhibited distant metastasis via photothermal treatment. As such, this PTT-based nanocarrier system could be a potential candidate for a clinical cancer therapy approach.

A near-infrared fluorescent probe with a substantial Stokes shift designed for the detection and imaging of β-galactosidase within living cells and animals

β-Galactosidase serves as a pivotal biomarker for both cancer and cellular aging. The advancement of fluorescent sensors for tracking β-galactosidase activity is imperative in the realm of cancer diagnosis. We have designed a near-infrared fluorescent probe (PTA-gal) for the detection of β-galactosidase in living systems with large Stokes shifts. PTA-gal exhibits remarkable sensitivity and selectivity in detecting β-galactosidase, producing near-infrared fluorescent signals with a remarkably low detection limit (2.2 × 10-5 U/mL) and a high quantum yield (0.30). Moreover, PTA-gal demonstrates biocompatibility and can effectively detect β-galactosidase in cancer cells as well as within living animals.