Applications

The efficient delivery of therapeutic proteins to tumor sites is a promising cancer treatment modality. Hydrogen-bonded organic frameworks (HOFs) have been successfully used for the protective encapsulation of proteins; however, easy precipitation and lack of controlled release of existing HOFs limit their further application for protein delivery in vivo. In this study, a hypoxia-responsive HOF, self-assembled from azobenzenedicarboxylate/polyethylene glycol-conjugated azobenzenedicarboxylate and tetrakis(4-amidiniumphenyl)methane through charge-assisted hydrogen-bonding, is developed for systemic protein delivery to tumor cells...

This study addresses a gap in the literature by exploring the longitudinal effects of hassles in mediating the relationship between neuroticism and the tripartite model of depression and anxiety. The research investigates these associations in a large sample of university students, utilising baseline and 6-month follow-up data. Initial assessments involved participants completing measures for neuroticism, depression and anxiety symptoms, and the occurrence of stress, followed by monthly assessments of stress, anxiety symptom and mood symptoms over a 6-month period...

The application of transition metal complexes for antimicrobial photodynamic therapy (PDT) has emerged as an attractive alternative in mitigating a broad range of bacterial pathogens, including multidrug-resistant pathogens. In view of their photostability, long excited-state lifetimes, and tunable emission properties, transition metal complexes also contribute as bioimaging agents. In the present work, we designed mono and trinuclear cyclometalated iridium(III) complexes to explore their imaging application and antibacterial potential...

A better understanding of the aggregation states of adhesive molecules in the interfacial region with an adherend is crucial for controlling the adhesion strength and is of great inherent academic interest. The adhesion mechanism has been described through four theories: adsorption, mechanical, diffusion, and electronic. While interfacial characterization techniques have been developed to validate the aforementioned theories, that related to the electronic theory has not yet been thoroughly studied. We here directly detected the electronic interaction between a commonly used thermosetting adhesive, cured epoxy of diglycidyl ether of bisphenol A (DGEBA) and 4,4'-diaminodiphenylmethane (DDM), and copper (Cu)...

The complex resonance of dielectric quality factor Q , combined with a capacitance tunability n higher than 3:1 without any dispersion, was achieved in the voltage-tunable interdigital capacitors (IDCs) based on epitaxial Ba0.8 Sr0.2 TiO3 ferroelectric thin films across the microwave L (1-2 GHz), S (2-4 GHz), and C (4-8 GHz) bands at room temperature. The resonant Q and n features were driven by the microwave responses of the ferroelectric nanodomains engineered in the films. To promote their application in space radiation environments, the evolutions of Q and n both as functions of frequency f (1-8 GHz) and applied electric field E (0-240 kV/cm) were systematically investigated under a series of gamma-ray irradiations up to 100 kGy...

We endeavor on a rarely explored task named thermal infrared video denoising. Perception in the thermal infrared significantly enhances the capabilities of machine vision. Nonetheless, noise in imaging systems is one of the factors that hampers the large-scale application of equipment. Existing thermal infrared denoising methods, primarily focusing on the image level, inadequately utilize time-domain information and insufficiently conduct investigation of system-level mixed noise, presenting the inferior ability in the video-recorded era; while video denoising methods, commonly applied to RGB cameras, exhibit uncertain effectiveness owing to substantial dissimilarities in the noise models and modalities between RGB and thermal infrared images...

Majority voting is a simple mathematical function that returns the most frequently occurring value within a given set. As a popular decision fusion technique (DFT), the majority voting function (MVF) finds applications in resolving conflicts, where several independent voters report their opinions on a classification problem. Despite its importance and its various applications in ensemble learning, data crowdsourcing, remote sensing, and data oracles for blockchains, the accuracy of the MVF for the general multiclass classification problem has remained unknown...

Contrastive learning (CL) has emerged as a powerful approach for self-supervised learning. However, it suffers from sampling bias, which hinders its performance. While the mainstream solutions, hard negative mining (HNM) and supervised CL (SCL), have been proposed to mitigate this critical issue, they do not effectively address graph CL (GCL). To address it, we propose graph positive sampling (GPS) and three contrastive objectives. The former is a novel learning paradigm designed to leverage the inherent properties of graphs for improved GCL models, which utilizes four complementary similarity measurements, including node centrality, topological distance, neighborhood overlapping, and semantic distance, to select positive counterparts for each node...

High-efficiency deep learning (DL) models are necessary not only to facilitate their use in devices with limited resources but also to improve resources required for training. Convolutional neural networks (ConvNets) typically exert severe demands on local device resources and this conventionally limits their adoption within mobile and embedded platforms. This brief presents work toward utilizing static convolutional filters generated from the space of local binary patterns (LBPs) and Haar features to design efficient ConvNet architectures...

Graph neural networks (GNN) suffer from severe inefficiency due to the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multiple simple modules for more efficient training, which is comprised of classical forward training (FT) and designed backward training (BT). Under the proposed framework, each module can be trained efficiently in FT by stochastic algorithms without distortion of graph information owing to its simplicity...

In virtual reality applications, in addition to visual feedback, real objects can be used as props for virtual objects to provide passive haptic feedback, which greatly enhances user immersion. Usually, real object props are not one-to-one correspondence with virtual objects. Haptic retargeting technique is proposed to establish the virtual-real correspondence by introducing an offset between the virtual hand and the real hand. Sometimes, the offset is too large to cause user discomfort, and it is necessary to introduce a reset between two haptic retargeting operations to force the virtual hand and the real hand to coincide in order to eliminate the offset...

Emotion recognition from electroencephalogram (EEG) signals is a critical domain in biomedical research with applications ranging from mental disorder regulation to human-computer interaction. In this paper, we address two fundamental aspects of EEG emotion recognition: continuous regression of emotional states and discrete classification of emotions. While classification methods have garnered significant attention, regression methods remain relatively under-explored. To bridge this gap, we introduce MASA-TCN, a novel unified model that leverages the spatial learning capabilities of Temporal Convolutional Networks (TCNs) for EEG emotion regression and classification tasks...

Human activity recognition has played a crucial role in healthcare information systems due to the fast adoption of artificial intelligence (AI) and the internet of thing (IoT). Most of the existing methods are still limited by computational energy, transmission latency, and computing speed. To address these challenges, we develop an efficient human activity recognition in-memory computing architecture for healthcare monitoring. Specifically, a mechanism-oriented model of Ag/a-Carbon/Ag memristor is designed, serving as the core circuit component of the proposed in-memory computing system...

Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight...

This study presents a facile fabrication of 58S bioactive glass (BG)-polymer composite coatings on a 316L stainless steel (SS) substrate using the electrophoretic deposition technique. The suspension characteristics and deposition kinetics of BG, along with three different polymers, namely ethylcellulose (EC), poly(acrylic acid) (PAA), and polyvinylpyrrolidone (PVP), have been utilized to fabricate the coatings. Among all coatings, 58S BG and EC polymers are selected as the final composite coating (EC6) owing to their homogeneity and good adhesion...

In response to decreasing numbers of individuals entering into nephrology fellowships, the American Society of Nephrology launched Kidney TREKS (Tutored Research and Education for Kidney Scholars) to stimulate interest in nephrology among medical students, graduate students, and postdoctoral fellows. The program combines a one-week intensive exposure to kidney physiology with a longitudinal mentorship program at the participants' home institutions. Ten years in, an analysis was conducted to assess its effectiveness...

Mesenchymal stem cells (MSCs) have demonstrated potent immunomodulatory properties that have shown promise in the treatment of autoimmune diseases, including rheumatoid arthritis (RA). However, the inherent heterogeneity of MSCs triggered conflicting therapeutic outcomes, raising safety concerns and limiting their clinical application. This study aimed to investigate the potential of extracellular vesicles derived from human gingival mesenchymal stem cells (GMSC-EVs) as a therapeutic strategy for RA. Through in vivo experiments using an experimental RA model, our results demonstrated that GMSC-EVs selectively homed to inflamed joints and recovered Treg and Th17 cells balance, resulting in the reduction of arthritis progression...

BACKGROUND: Improving access to mental health data to accelerate research and improve mental health outcomes is a potentially achievable goal given the substantial data that can now be collected from mobile devices. Smartphones can provide a useful mechanism for collecting mental health data from young people, especially as their use is relatively ubiquitous in high-resource settings such as the United Kingdom and they have a high capacity to collect active and passive data. This raises the interesting opportunity to establish a large bank of mental health data from young people that could be accessed by researchers worldwide, but it is important to clarify how to ensure that this is done in an appropriate manner aligned with the values of young people...

Peptide mapping with mass spectrometry (MS) is an important tool for protein characterization in the biopharmaceutical industry. Historically, peptide mapping monitors post-translational modifications (PTMs) of protein products and process intermediates during development. Multi-attribute monitoring (MAM) methods have been used previously in commercial release and stability testing panels to ensure control of selected critical quality attributes (CQAs). Our goal is to use MAM methods as part of an overall analytical testing strategy specifically focused on CQAs, while removing or replacing historical separation methods that do not effectively distinguish CQAs from non-CQAs due to co-elution...

BACKGROUND: The relationship between lymph node (LN) status and survival outcome in hepatocellular carcinoma (HCC) is a highly controversial topic. The aim of this study was to investigate the prognostic factors in patients without LN metastasis (LNM) and to construct a nomogram to predict cancer-specific survival (CSS) in this group of patients. METHODS: We screened 6840 eligible HCC patients in the Surveillance, Epidemiology and End Results（SEER）database between 2010 and 2019 and randomized them into a training cohort and an internal validation cohort, and recruited 160 patients from Zhongnan Hospital of Wuhan University as an external validation cohort...