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Defect engineering has proven to be one of the most effective approaches for the design of high-performance electrocatalysts. Current methods to create defects typically follow a top-down strategy, cutting down the pristine materials into fragmented pieces with surface defects yet also heavily destroying the framework of materials that imposes restrictions on the further improvements in catalytic activity. Herein, we describe a bottom-up strategy to prepare free-standing NiFe layered double hydroxide (LDH) nanoplatelets with abundant internal defects by controlling their growth behavior in acidic conditions. Our best-performing nanoplatelets exhibited the lowest overpotential of 241 mV and the lowest Tafel slope of 43 mV/dec for the oxygen evolution reaction (OER) process, superior to the pristine LDHs and other reference cation-defective LDHs obtained by traditional etching methods. Using both material characterization and density functional theory (DFT) simulation has enabled us to develop relationships between the structure and electrochemical properties of these catalysts, suggesting that the enhanced electrocatalytic activity of nanoplatelets mainly results from their defect-abundant structure and stable layered framework with enhanced exposure of the (001) surface.

Contrast-enhanced ultrasound (CEUS) offers the exciting prospect of retaining the ease of ultrasound imaging while enhancing imaging clarity, diagnostic specificity, and theranostic capability. To advance the capabilities of CEUS, the synthesis and understanding of new ultrasound contrast agents (UCAs) is a necessity. Many UCAs are nano- or micro-scale materials composed of a perfluorocarbon (PFC) and stabilizer that synergistically induce an ultrasound response that is both information-rich and easily differentiated from natural tissue. In this work, we probe the extent to which CEUS is modulated through variation in a PFC stabilized with fluorine-modified polydopamine nanoparticles (PDA NPs). The high level of synthetic tunability in this system allows us to study signal as a function of particle aggregation and PFC volatility in a systematic manner. Separation of aggregated and non-aggregated nanoparticles lead to a fundamentally different signal response, and for this system, PFC volatility has little effect on CEUS intensity despite a range of over 50 °C in boiling point. To further explore the imaging tunability and multimodality, Fe3+-chelation was employed to generate an enhanced photoacoustic (PA) signal in addition to the US signal. In vitro and in vivo results demonstrate that PFC-loaded PDA NPs show stronger PA signal than the non-PFC ones, indicating that the PA signal can be used for in situ differentiation between PFC-loading levels. In sum, these data evince the rich role synthetic chemistry can play in guiding new directions of development for UCAs.

Transvaginal ultrasound is widely used for ovarian cancer screening but has a high false positive rate. Photoacoustic imaging provides additional optical contrast to supplement ultrasound and might be able to improve the accuracy of screening. Here, we report two copper sulfide (CuS) nanoparticles types (nanodisks and triangular nanoprisms) as the photoacoustic contrast agents for imaging ovarian cancer. Both CuS nanoprisms and nanodisks were ~6 nm thick and ~26 nm wide and were coated with poly(ethylene glycol) to make them colloidally stable in phosphate buffered saline (PBS) for at least 2 weeks. The CuS nanodisks and nanoprisms revealed strong localized surface plasmon resonances with peak maxima at 1145 nm and 1098 nm, respectively. Both nanoparticles types had strong and stable photoacoustic intensity with detection limits below 120 pM. The circular CuS nanodisk remained in the circulation of nude mice (n=4) and xenograft 2008 ovarian tumors (n=4) 17.9-fold and 1.8-fold more than the triangular nanoprisms, respectively. Finally, the photoacoustic intensity of the tumors from the mice (n=3) treated with CuS nanodisks was 3.0-fold higher than the baseline. The tumors treated with nanodisks had a characteristic peak at 920 nm in the spectrum to potentially differentiate the tumor from adjacent tissues.

The preclinical landscape of photoacoustic imaging has experienced tremendous growth in the past decade. This non-invasive imaging modality augments the spatiotemporal capabilities of ultrasound with optical contrast. While it has principally been investigated for diagnostic applications, many recent reports have described theranostic delivery systems and drug monitoring strategies using photoacoustics. Here, we provide an overview of the progress to date while highlighting work in three specific areas: theranostic nanoparticles, real-time drug monitoring, and stem cell ("living drug") tracking. Additionally, we discuss the challenges that remain to be addressed in this burgeoning field.

Heparin is an indispensable drug in anticoagulation therapy but with a narrow therapeutic window, which dictates regular testing and dose adjustment. However, current monitoring tools have a long turnaround time or are operator intensive. In this work, we describe a cellulose-based photoacoustic sensor for heparin. The sensors have a turnaround time of 6 min for whole blood samples and 3 min for plasma samples regardless of heparin concentration. These sensors have a limit of detection of 0.28 U/ml heparin in human plasma and 0.29 U/ml in whole blood with a linear response (Pearson's r = 0.99) from 0 to 2 U/ml heparin in plasma and blood samples. The relative standard deviation was

Rosai-Dorfman disease (RDD), also known as sinus histiocytosis with massive lymphadenopathy, is an uncommon histiocytic disease with idiopathic etiology and unique pathology. Extra-nodal RDD that occurs in the nasal cavity is extremely unusual and the characteristic clinical features are unknown. Herein, we report a case of nasal septum RDD, with intermittent epistaxis from the left nasal cavity, which led to collapse of the nasal bridge. The patient underwent surgical biopsy, and a diagnosis of nasal septum RDD was established. No further treatment was performed. An enlarged mass was found in the second postoperative year which was treated by surgical excision in the third postoperative year. To improve the current diagnostic and therapeutic approach of extra-nodal RDD, we incorporate previous reports from the literature to discuss the pathological characteristics, pathogenesis, clinical manifestations, diagnosis, and therapy for this rare disease. [ABSTRACT FROM AUTHOR]

The personal ultraviolet (UV) dosimeter is a useful measurement tool to prevent UV induced dermal damages; however, conventional digital dosimeters are either bulky or require external power sources. Here, a wearable, colorimetric UV film dosimeter that provides color transition, from purple to transparent, is reported to indicate the UV dose. The film dosimeter is made of a purple photodegradable dye ((2Z,6Z)-2,6-bis(2-(2,6-diphenyl-4H-thiopyran-4-ylidene)ethylidene)cyclohexanone or DTEC) blended in low density polyethylene film. The DTEC film discolored 3.3 times more under the exposure of UV light (302 nm) than visible light (543 nm), and a UV bandpass filter is developed to increase this selectivity to UV light. The DTEC film completely discolors to transparency in 2 h under an AM 1.5 solar simulator, suggesting the potential as an indicator for individuals with types I-VI skin to predict interventions to avoid sunburn. Finally, the DTEC film is integrated with the UV bandpass filter on a wristband to function as a wearable dosimeter for low cost and convenient monitoring of sunlight exposure.

Ultrasound is critical in many areas of medicine including obstetrics, oncology, and cardiology with emerging applications in regenerative medicine. However, one critical limitation of ultrasound is the low contrast of target tissue over background. Here, we describe a novel cup-shaped silica nanoparticle that is reminiscent of exosomes and that has significant ultrasound impedance mismatch for labelling stem cells for regenerative medicine imaging. These exosome-like silica nanoparticles (ELS) were created through emulsion templating and the silica precursors bis(triethoxysilyl)ethane (BTSE) and bis(3-trimethoxysilyl-propyl)amine (TSPA). We found that 40% TSPA resulted in the exosome like-morphology and a positive charge suitable for labelling mesenchymal stem cells. We then compared this novel structure to other silica structures used in ultrasound including Stober silica nanoparticles (SSN), MCM-41 mesoporous silica nanoparticles (MSN), and mesocellular foam silica nanoparticles (MCF) and found that the ELS offered enhanced stem cell signal due to its positive charge to facilitate cell uptake as well as inherently increased echogenicity. The in vivo detection limits were

Landslide disasters pose significant threats to human life and property; therefore, accurate and effective detection and area extraction methods are crucial in environmental monitoring and disaster management. In our study, we address the critical tasks of landslide detection and area extraction in remote sensing images using advanced deep learning techniques. For landslide detection, we propose an enhanced dual-channel model that leverages EfficientNetB7 for feature extraction and incorporates spatial attention mechanisms (SAMs) to enhance important features. Additionally, we utilize a deep separable convolutional neural network with a Transformers module for feature extraction from digital elevation data (DEM). The extracted features are then fused using a variational autoencoder (VAE) to mine potential features and produce final classification results. Experimental results demonstrate impressive accuracy rates of 98.92% on the Bijie City landslide dataset and 94.70% on the Landslide4Sense dataset. For landslide area extraction, we enhance the traditional Unet++ architecture by incorporating Dilated Convolution to expand the receptive field and enable multi-scale feature extraction. We further integrate the Transformer and Convolutional Block Attention Module to enhance feature focus and introduce multi-task learning, including segmentation and edge detection tasks, to efficiently extract and refine landslide areas. Additionally, conditional random fields (CRFs) are applied for post-processing to refine segmentation boundaries. Comparative analysis demonstrates the superior performance of our proposed model over traditional segmentation models such as Unet, Fully Convolutional Network (FCN), and Segnet, as evidenced by improved metrics: IoU of 0.8631, Dice coefficient of 0.9265, overall accuracy (OA) of 91.53%, and Cohen's kappa coefficient of 0.9185 on the Bijie City landslide dataset; and IoU of 0.8217, Dice coefficient of 0.9021, overall accuracy (OA) of 96.68%, and Cohen's kappa coefficient of 0.8835 on the Landslide4Sense dataset. These findings highlight the effectiveness and robustness of our proposed methodologies in addressing critical challenges in landslide detection and area extraction tasks, with significant implications for enhancing disaster management and risk assessment efforts in remote sensing applications. [ABSTRACT FROM AUTHOR]

Stem cell therapy (SCT) has shown very promising preclinical results in a variety of regenerative medicine applications. Nevertheless, the complete utility of this technology remains unrealized. Imaging is a potent tool used in multiple stages of SCT and this review describes the role that imaging plays in cell harvest, cell purification, and cell implantation, as well as a discussion of how imaging can be used to assess outcome in SCT. We close with some perspective on potential growth in the field.