Dual-Induced Directed Deposition Mechanism Based on Anionic Surfactants Enables Long Cycle Aqueous Zinc Ion Batteries.

Aqueous zinc-ion battery has low cost, and environmental friendliness, emerging as a promising candidate for next-generation battery systems. However, it still suffers from a limited cycling life, caused by dendritic Zn growth and severe side reactions. Recent research highlights that the Zn (002) crystal plane exhibits superior anti-corrosive properties and a horizontal growth pattern.

Innovative Lipid Nanoparticles Co-Delivering Hydroxychloroquine and siRNA for Enhanced Rheumatoid Arthritis Therapy.

Rheumatoid arthritis (RA) is a debilitating autoimmune disorder characterized by chronic inflammation and joint damage. Despite advancements in treatment, complete remission remains elusive. In this study, we introduce a novel lipid nanoparticle formulation co-delivering hydroxychloroquine (HCQ) and siRNA targeting TNF-α (si) using microfluidic technology, marking the first use of such a combination for RA therapy.

Atomistic dynamics of elimination and substitution driven by entrance channel.

E2 elimination and SN2 substitution reactions are of central importance in preparative organic synthesis due to their stereospecificity. Herein, atomistic dynamics of a prototype reaction of ethyl chloride with hydroxide ion are uncovered that show strikingly distinct features from the case with fluoride anion. Chemical dynamics simulations reproduce the experimental reaction rate and reveal that the E2 proceeding through a direct elimination mechanism dominates over SN2 for the hydroxide ion reaction.

H1N1 swine influenza viruses upregulate NEU1 expression through histone H3 acetylation regulated by HDAC2.

Mammalian membrane sialic acid is the key receptor for influenza virus. Sialidases, the main type of enzyme that can hydrolyze membrane sialic acids in mammalian cells, have the potential to affect the invasion process of influenza viruses, including H1N1. For the first time, this study focused on the regulation mechanism of sialidase NEU1 expression, and revealed that swine-origin influenza (H1N1) virus infection can promote NEU1 expression through histone H3 acetylation, which is regulated by HDAC2 in host cells.

Photothermal Catalytic Degradation of VOCs: Mode, System and Application.

Human production and living processes emit excessive VOCs into the atmosphere, posing significant threats to both human health and the environment. The photothermal catalytic oxidation process is an organic combination of photocatalysis and thermocatalysis. Utilizing photothermal catalytic degradation of VOCs can achieve better catalytic activity at lower temperatures, resulting in more rapid and thorough degradation of these compounds.

Innovative nebulization delivery of lipid nanoparticle-encapsulated siRNA: a therapeutic advance for Staphylococcus aureus-induced pneumonia.

Background: Integrin α5β1 plays a crucial role in the invasion of nonphagocytic cells by Staphylococcus aureus (S. aureus), thereby facilitating infection development. Lipid nanoparticles (LNPs) serve as an effective vehicle for delivering small interfering ribonucleic acids (siRNA) that represent a method to knockdown integrin α5β1 in the lungs through nebulization, thereby potentially mitigating the severity of S.

Dual-Grained Lightweight Strategy.

Removing redundant parameters and computations before the model training has attracted a great interest as it can effectively reduce the storage space of the model, speed up the training and inference of the model, and save energy consumption during the running of the model. In addition, the simplification of deep neural network models can enable high-performance network models to be deployed to resource-constrained edge devices, thus promoting the development of the intelligent world. However, current pruning at initialization methods exhibit poor performance at extreme sparsity.

An open dataset for oracle bone character recognition and decipherment.

Oracle bone script, one of the earliest known forms of ancient Chinese writing, presents invaluable research materials for scholars studying the humanities and geography of the Shang Dynasty, dating back 3,000 years. The immense historical and cultural significance of these writings cannot be overstated. However, the passage of time has obscured much of their meaning, presenting a significant challenge in deciphering these ancient texts.

A one-stop integrated natural antimicrobial microneedles with anti-inflammatory, pro-angiogenic and long-term moisturizing properties to accelerate diabetic wound healing.

Diabetic ulcers present a formidable obstacle in diabetes management, typically leading to high mortality and amputation rates. To overcome traditional monotherapy drawbacks, We developed a novel microneedle strategy for combined antimicrobial action: ingeniously integrating quercetin with Platelet-derived Growth Factor-BB(PDGF-BB) and Sucrose Octasulfate(SOS) into the microneedle system(QPS MN). This method allows to penetrate through biofilms, administering quercetin nanocrystals and PDGF-BB deep into the tissue to combat microbial infection, mitigate inflammation, and promote angiogenesis.

Pure tone audiogram classification using deep learning techniques.

Objective: Pure tone audiometry has played a critical role in audiology as the initial diagnostic tool, offering vital insights for subsequent analyses. This study aims to develop a robust deep learning framework capable of accurately classifying audiograms across various commonly encountered tasks.

Design, Setting, And Participants: This single-centre retrospective study was conducted in accordance with the STROBE guidelines.

Engineering the protein corona: Strategies, effects, and future directions in nanoparticle therapeutics.

Nanoparticles (NPs) serve as versatile delivery systems for anticancer, antibacterial, and antioxidant agents. The manipulation of protein-NP interactions within biological systems is crucial to the application of NPs in drug delivery and cancer nanotherapeutics. The protein corona (PC) that forms on the surface of NPs is the interface between biomacromolecules and NPs and significantly influences their pharmacokinetics and pharmacodynamics.

Turning a CLIP Model Into a Scene Text Spotter.

We exploit the potential of the large-scale Contrastive Language-Image Pretraining (CLIP) model to enhance scene text detection and spotting tasks, transforming it into a robust backbone, FastTCM-CR50. This backbone utilizes visual prompt learning and cross-attention in CLIP to extract image and text-based prior knowledge. Using predefined and learnable prompts, FastTCM-CR50 introduces an instance-language matching process to enhance the synergy between image and text embeddings, thereby refining text regions.

Exosomes in Glioma: Unraveling Their Roles in Progression, Diagnosis, and Therapy.

Gliomas, the most prevalent primary malignant brain tumors, present a challenging prognosis even after undergoing surgery, radiation, and chemotherapy. Exosomes, nano-sized extracellular vesicles secreted by various cells, play a pivotal role in glioma progression and contribute to resistance against chemotherapy and radiotherapy by facilitating the transportation of biological molecules and promoting intercellular communication within the tumor microenvironment. Moreover, exosomes exhibit the remarkable ability to traverse the blood-brain barrier, positioning them as potent carriers for therapeutic delivery.

Focalizing regions of biomarker relevance facilitates biomarker prediction on histopathological images.

Image-based AI has thrived as a potentially revolutionary tool for predicting molecular biomarker statuses, which aids in categorizing patients for appropriate medical treatments. However, many methods using hematoxylin and eosin-stained (H&E) whole-slide images (WSIs) have been found to be inefficient because of the presence of numerous uninformative or irrelevant image patches. In this study, we introduced the region of biomarker relevance (ROB) concept to identify the morphological areas most closely associated with biomarkers for accurate status prediction.

SPTS v2: Single-Point Scene Text Spotting.

End-to-end scene text spotting has made significant progress due to its intrinsic synergy between text detection and recognition. Previous methods commonly regard manual annotations such as horizontal rectangles, rotated rectangles, quadrangles, and polygons as a prerequisite, which are much more expensive than using single-point. Our new framework, SPTS v2, allows us to train high-performing text-spotting models using a single-point annotation.

SAN: Side Adapter Network for Open-Vocabulary Semantic Segmentation.

This article concentrates on open-vocabulary semantic segmentation, where a well optimized model is able to segment arbitrary categories that appear in an image. To achieve this goal, we present a novel framework termed Side Adapter Network, or SAN for short. Our design principles are three-fold: 1) Recent large-scale vision-language models (e.

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare policies. Assessed at 3-, 6-, 12-, and 18-month postdischarge, we described the temporal change of IgG levels in 450 individuals with moderate to critical COVID-19 infection.

CycMuNet+: Cycle-Projected Mutual Learning for Spatial-Temporal Video Super-Resolution.

Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate high-quality videos with higher resolution (HR) and higher frame rate (HFR). Quite intuitively, pioneering two-stage based methods complete ST-VSR by directly combining two sub-tasks: Spatial Video Super-Resolution (S-VSR) and Temporal Video Super-Resolution (T-VSR) but ignore the reciprocal relations among them. 1) T-VSR to S-VSR: temporal correlations help accurate spatial detail representation; 2) S-VSR to T-VSR: abundant spatial information contributes to the refinement of temporal prediction.

Content-Adaptive Auto-Occlusion Network for Occluded Person Re-Identification.

The occluded person re-identification (ReID) aims to match person images captured in severely occluded environments. Current occluded ReID works mostly rely on auxiliary models or employ a part-to-part matching strategy. However, these methods may be sub-optimal since the auxiliary models are constrained by occlusion scenes and the matching strategy will deteriorate when both query and gallery set contain occlusion.

PRSS2 regulates EMT and metastasis via MMP-9 in gastric cancer.

Serine protease 2 (PRSS2) is upregulated in gastric cancer tissues, correlates with poor prognosis and promotes migration and invasion of gastric cancer cells. However, the exact mechanism by which PRSS2 promotes metastasis in gastric cancer is unclear. We examined serum PRSS2 levels in healthy controls and gastric cancer patients by enzyme linked immunosorbent assay (ELISA) and analyzed the correlation between PRSS2 serum level with the clinicopathological characteristics of gastric cancer patients and matrix metalloproteinase-9 (MMP-9) expression.

A transformable nanoplatform with multiple therapeutic and immunostimulatory properties for treatment of advanced cancers.

Cancer is a complex pathological phenomenon that needs to be treated from different aspects. Herein, we developed a size/charge dually transformable nanoplatform (PDR NP) with multiple therapeutic and immunostimulatory properties to effectively treat advanced cancers. The PDR NPs exhibit three different therapeutic modalities (chemotherapy, phototherapy and immunotherapy) that can be used to effectively treat primary and distant tumors, and reduce recurrent tumors; the immunotherapy is simultaneously activated by three major pathways, including toll-like receptor, stimulator of interferon genes and immunogenic cell death, effectively suppresses the tumor development in combination with an immune checkpoint inhibitor.

Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation.

Vessel segmentation is crucial in many medical image applications, such as detecting coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high pixel-wise accuracy, complete topology structure and robustness to various contrast variations are critical and challenging, and most existing methods focus only on achieving one or two of these aspects. In this paper, we present a novel approach, the affinity feature strengthening network (AFN), which jointly models geometry and refines pixel-wise segmentation features using a contrast-insensitive, multiscale affinity approach.

EPNet++: Cascade Bi-Directional Fusion for Multi-Modal 3D Object Detection.

Recently, fusing the LiDAR point cloud and camera image to improve the performance and robustness of 3D object detection has received more and more attention, as these two modalities naturally possess strong complementarity. In this paper, we propose EPNet++ for multi-modal 3D object detection by introducing a novel Cascade Bi-directional Fusion (CB-Fusion) module and a Multi-Modal Consistency (MC) loss. More concretely, the proposed CB-Fusion module enhances point features with plentiful semantic information absorbed from the image features in a cascade bi-directional interaction fusion manner, leading to more powerful and discriminative feature representations.

Hierarchical BiOCl flowerlike microspheres a room-temperature solid-state chemical reaction as a new anode for rechargeable magnesium-ion batteries.

Rechargeable magnesium-ion batteries (MIBs) have received much attention in recent years, but their development remains limited due to a lack of anode materials with high capacity and fast diffusion kinetics. Herein, for the first time, hierarchical BiOX (X = Cl, Br, I) flowerlike microspheres composed of interleaved nanosheets are constructed a simple room-temperature solid-state chemical reaction as the anode for MIBs. Among them, BiOCl flowerlike microspheres deliver good cycling stability (110 mA h g after 100 cycles) and a superior rate capacity (134 mA h g at 500 mA g).

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools.

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling.