Mindfulness's moderating role applied on online SEL education.

Introduction: Mild to moderate depression, anxiety, and stress imbalances are prevalent emotional issues among college students and are primary factors leading to deficiencies in social-emotional skills within this population. Without timely intervention, these mild to moderate emotional issues may escalate into more severe conditions. Social-Emotional Learning (SEL) programs are effective for building social-emotional skills.

In Vivo Self-Sorting of Peptides via Assembly Evolution.

Despite significant progress achieved in artificial self-sorting in solution, operating self-sorting in the body remains a considerable challenge. Here, we report an in vivo self-sorting peptide system via an in situ assembly evolution for combined cancer therapy. The peptide consists of two disulfide-connected segments, and , capable of independent assembly into twisted or flat nanoribbons.

Fine-Tuning Electron Transfer for Nanozyme Design.

Nanozymes, with their versatile composition and structural adaptability, present distinct advantages over natural enzymes including heightened stability, customizable catalytic activity, cost-effectiveness, and simplified synthesis process, making them as promising alternatives in various applications. Recent advancements in nanozyme research have shifted focus from serendipitous discovery toward a more systematic approach, leveraging machine learning, theoretical calculations, and mechanistic explorations to engineer nanomaterial structures with tailored catalytic functions. Despite its pivotal role, electron transfer, a fundamental process in catalysis, has often been overlooked in previous reviews.

Multihierarchical Regulation To Achieve Quantum Dot Nanospheres with a Photoluminescence Quantum Yield Close to 100.

Quantum dots (QDs) exhibit superior brightness and photochemical stability, making them the preferred option for highly sensitive single-molecule detection compared with fluorescent dyes or proteins. Nevertheless, their high surface energy leads to nonspecific adsorption and poor colloidal stability. In the past decades, we have found that QD-based fluorescent nanoparticles (FNs) can not only address these limitations but also enhance detection sensitivity.

[Effect of Integrated Landscape Characteristics Around Chaohu Lake on River Water Quality Based on Watershed Units].

Considering the impact of differences in watershed characteristics on river water quality, with the Chaohu Lake Basin as the research object, based on the data of water quality, meteorology, topography, soil, and remote sensing images of the river monitoring points from October 2019 to September 2020, the watershed unit at each monitoring point was divided through digital terrain analysis, and the comprehensive landscape characteristics based on the watershed unit were explored through the comprehensive use of correlation analysis, redundancy analysis, and multiple regression analysis to investigate the influence of comprehensive landscape characteristics based on watershed units (including land use, climate, topography, soil, etc.) on the water quality of rivers around Chaohu Lake. The results showed that:① the water quality of rivers around Chaohu Lake had large spatial differences, with the main pollutants being total nitrogen and ammonia nitrogen.

Enhancing Circularly Polarized Luminescence in Quantum Dots through Chiral Coordination-Mediated Growth at the Liquid/Liquid Interface.

Here, we develop a novel methodology for synthesizing chiral CdSe@ZnS quantum dots (QDs) with enhanced circularly polarized luminescence (CPL) by incorporating l-/d-histidine (l-/d-His) ligands during ZnS shell growth at the water/oil interface. The resulting chiral QDs exhibit exceptional absolute photoluminescence quantum yield of up to 67.2%, surpassing the reported limits of 40.

Acid-Resistant Near-Infrared II AgSe Quantum Dots for Gastrointestinal Imaging.

With the development of near-infrared II (NIR-II) fluorescence imaging, AgSe quantum dots (QDs) have become promising label candidates due to their negligible toxicity and narrow band gap. Despite their potential for gastrointestinal (GI) imaging, the application of AgSe QDs still presents significant challenges due to issues such as fluorescence extinction or poor stability in the complex digestive microenvironment. Herein, we have proposed a novel approach to the continuous production of Se precursors using glutathione (GSH) as the reductant under acidic conditions, realizing the continuous growth of water-dispersible AgSe QDs.

Capture of small clusters by ligand-solvent interaction.

Clusters are considered to become increasingly significant for elaborating the nanocrystal's formation mechanism. However, capturing the clusters with high chemical potential is challenging because of the lack of effective strategies. In this work, the key role of ligand-solvent interaction has been revealed for the stabilization of clusters in silver telluride synthesis.

Identifying Liver Metastasis-Related Genes Through a Coexpression Network to Construct a 5-Gene Model for Predicting Pancreatic Ductal Adenocarcinoma Patient Prognosis.

Objectives: This study aimed to develop a liver metastasis-related gene prognostic index (LMPI) for pancreatic ductal adenocarcinoma prognosis and therapy.

Methods: The Cancer Genome Atlas data set was used to identify liver metastasis-related hub genes via weighted gene coexpression network analysis. The core genes were identified to construct an LMPI by using the Cox regression method.

Diarylheptanoid 35d overcomes EGFR TKI resistance by inducing hsp70-mediated lysosomal degradation of EGFR in EGFR-mutant lung adenocarcinoma.

Epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma (LUAD) patients often respond to EGFR tyrosine kinase inhibitors (TKIs) initially but eventually develop resistance to TKIs. The switch of EGFR downstream signaling from TKI-sensitive to TKI-insensitive is a critical mechanism-driving resistance to TKIs. Identification of potential therapies to target EGFR effectively is a potential strategy to treat TKI-resistant LUADs.

Redox Imbalance Triggered Intratumoral Cascade Reaction for Tumor "turn on" Imaging and Synergistic Therapy.

The redox homeostasis in tumors enhances their antioxidant defense ability, limiting reactive oxygen species mediated tumor therapy efficacy. The development of strategies for specific and continuous disruption of the redox homeostasis in tumor cells facilitates the improvement of the cancer therapeutic effect by promoting the apoptosis of tumor cells. Herein, a responsively biodegradable targeting multifunctional integrated nanosphere (HDMn-QDs/PEG-FA) is designed to enhance the anti-tumor efficacy by triggering intratumoral cascade reactions to effectively disrupt intracellular redox homeostasis.

Artificially regulated synthesis of nanocrystals in live cells.

Live cells, as reservoirs of biochemical reactions, can serve as amazing integrated chemical plants where precursor formation, nucleation and growth of nanocrystals, and functional assembly, can be carried out accurately following an artificial program. It is crucial but challenging to deliberately direct intracellular pathways to synthesize desired nanocrystals that cannot be produced naturally in cells, because the relevant reactions exist in different spatiotemporal dimensions and will never encounter each other spontaneously. This article summarizes the progress in the introduction of inorganic functional nanocrystals into live cells via the 'artificially regulated space-time-coupled live-cell synthesis' strategy.

Immunoprofiling of Severity and Stage of Bacterial Infectious Diseases by Ultrabright Fluorescent Nanosphere-Based Dyad Test Strips.

Bacterial infectious diseases are common clinical diseases that seriously threaten human health, especially in countries and regions with poor environmental hygiene. Due to the lack of characteristic clinical symptoms and signs, it is a challenge to distinguish a bacterial infection from other infections, leading to misdiagnosis and antibiotic overuse. Therefore, there is an urgent need to develop a specific method for detection of bacterial infections.

Self-Sorting Peptide Assemblies in Living Cells for Simultaneous Organelle Targeting.

Self-sorting is a common phenomenon in eukaryotic cells and represents one of the versatile strategies for the formation of advanced functional materials; however, developing artificial self-sorting assemblies within living cells remains challenging. Here, we report on the GSH-responsive self-sorting peptide assemblies within cancer cells for simultaneous organelle targeting to promote combinatorial organelle dysfunction and thereby cell death. The self-sorting system was created the design of two peptides E3C16E6 and EVM derived from lipid-inspired peptide interdigitating amphiphiles and peptide bola-amphiphiles, respectively.

In-Sequence High-Specificity Dual-Reporter Unlocking of Fluorescent Probe Enables the Precise Identification of Atherosclerotic Plaques.

The formation of atherosclerotic plaques is the root cause of various cardiovascular diseases (CVDs). Effective CVD interventions thus call for precise identification of the plaques to aid clinical assessment, diagnosis, and treatment of such diseases. In this study, we introduce a dual-target sequentially activated fluorescence reporting system, termed in-sequence high-specificity dual-reporter unlocking (iSHERLOCK), to precisely identify the atherosclerotic plaques in vivo and ex vivo.

Domain-Adversarial-Guided Siamese Network for Unsupervised Cross-Domain 3-D Object Retrieval.

Recent advances in 3-D sensors and 3-D modeling have led to the availability of massive amounts of 3-D data. It is too onerous and time consuming to manually label a plentiful of 3-D objects in real applications. In this article, we address this issue by transferring the knowledge from the existing labeled data (e.

Host-cell-assisted construction of a folate-engineered nanocarrier based on viral light particles for targeted cancer therapy.

Targeted cancer therapy has aroused the broad interest of researchers due to its accuracy in specific tumor targeting and its few side effects on normal cells. In the last decades, oncolytic viral light particles (L-particles) have been transformed into smart nanocarriers for targeted drug delivery. However, these L-particles, similar to the oncolytic viruses that they are derived from, can only recognize tumor cells expressing corresponding receptors, severely limiting their universal application.

A Novel Multiple-View Adversarial Learning Network for Unsupervised Domain Adaptation Action Recognition.

Abstract-domain adaptation action recognition is a hot research topic in machine learning and some effective approaches have been proposed. However, samples in the target domain with label information are often required by these approaches. Moreover, domain-invariant discriminative feature learning, feature fusion, and classifier module learning have not been explored in an end-to-end framework.

Breaking through the Size Control Dilemma of Silver Chalcogenide Quantum Dots via Trialkylphosphine-Induced Ripening: Leading to AgTe Emitting from 950 to 2100 nm.

AgTe is one of the most promising semiconductors with a narrow band gap and low toxicity; however, it remains a challenge to tune the emission of AgTe quantum dots (QDs) precisely and continuously in a wide range. Herein, AgTe QDs emitting from 950 to 2100 nm have been synthesized via trialkylphosphine-controlled growth. Trialkylphosphine has been found to induce the dissolution of small-sized AgTe QDs due to its stronger ability to coordinate to the Ag ion than that of 1-octanethiol, predicated by the density functional theory.

Toward Region-Aware Attention Learning for Scene Graph Generation.

Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues. For example, to infer the relationship between man and horse, the interaction between human leg and horseback can provide strong visual evidence to predict the predicate ride.

Detection of SARS-CoV-2 by CRISPR/Cas12a-Enhanced Colorimetry.

The outbreak of COVID-19 caused a worldwide public health crisis. Large-scale population screening is an effective means to control the spread of COVID-19. Reverse transcription-polymerase chain reaction (RT-qPCR) and serology assays are the most available techniques for SARS-CoV-2 detection; however, they suffer from either less sensitivity and accuracy or low instrument accessibility for screening.

Monocular Image-Based 3-D Model Retrieval: A Benchmark.

Monocular image-based 3-D model retrieval aims to search for relevant 3-D models from a dataset given one RGB image captured in the real world, which can significantly benefit several applications, such as self-service checkout, online shopping, etc. To help advance this promising yet challenging research topic, we built a novel dataset and organized the first international contest for monocular image-based 3-D model retrieval. Moreover, we conduct a thorough analysis of the state-of-the-art methods.

Spatio-Temporal Mitosis Detection in Time-Lapse Phase-Contrast Microscopy Image Sequences: A Benchmark.

In this paper, we report the results of the first international contest on mitosis detection in phase-contrast microscopy image sequences (https://www.iti-tju.org/mitosisdetection), which was held at the workshop of computer vision for microscopy image analysis (CVMI) in CVPR 2019.

Pairwise Two-Stream ConvNets for Cross-Domain Action Recognition With Small Data.

In this work, we target cross-domain action recognition (CDAR) in the video domain and propose a novel end-to-end pairwise two-stream ConvNets (PTC) algorithm for real-life conditions, in which only a few labeled samples are available. To cope with the limited training sample problem, we employ pairwise network architecture that can leverage training samples from a source domain and, thus, requires only a few labeled samples per category from the target domain. In particular, a frame self-attention mechanism and an adaptive weight scheme are embedded into the PTC network to adaptively combine the RGB and flow features.

A Pairwise Attentive Adversarial Spatiotemporal Network for Cross-Domain Few-Shot Action Recognition-R2.

- Action recognition is a popular research topic in the computer vision and machine learning domains. Although many action recognition methods have been proposed, only a few researchers have focused on cross-domain few-shot action recognition, which must often be performed in real security surveillance. Since the problems of action recognition, domain adaptation, and few-shot learning need to be simultaneously solved, the cross-domain few-shot action recognition task is a challenging problem.