Egg yolk-derived low-density lipoprotein: A potential drug delivery system to eradicate intracellular bacteria.

Antibiotics have limited capacities to penetrate and eliminate intracellular bacteria. This study developed a drug delivery system to surmount the cell-membrane barrier and achieve efficient intracellular antibiotic accumulation for intracellular-bacterial eradication. Ceftiofur (CEF) was encapsulated in hen egg-yolk-extracted low-density lipoproteins (heLDLs) to generate CEF-heLDLs.

Network pharmacology study and experimental validation of Xiaojianzhong decoction against gastric cancer.

Background: Cancer is one of the most serious threats to human health worldwide. Conventional treatments such as surgery and chemotherapy are associated with some drawbacks. In recent years, traditional Chinese medicine treatment has been increasingly advocated by patients and attracted attention from clinicians, and has become an indispensable part of the comprehensive treatment for gastric cancer.

Information-motivation-behavioral guided nursing for stroke patients with pulmonary dysfunction: A randomized controlled trial.

Background: Patients with stroke frequently experience pulmonary dysfunction.

Aim: To explore the effects of information-motivation-behavioral (IMB) skills model-based nursing care on pulmonary function, blood gas indices, complication rates, and quality of life (QoL) in stroke patients with pulmonary dysfunction.

Methods: We conducted a controlled study involving 120 stroke patients with pulmonary dysfunction.

Hypoxia and ferroptosis.

Ferroptosis is a novel, iron-dependent cell death characterized by the excessive accumulation of ferroptosis lipid peroxides ultimately leading to oxidative damage to the cell membrane. Iron, lipid, amino acid metabolism, and other signaling pathways all control ferroptosis. Numerous bodily tissues experience hypoxia under normal and pathological circumstances.

Parameter-Free State Estimation Based on Kalman Filter with Attention Learning for GPS Tracking in Autonomous Driving System.

GPS-based maneuvering target localization and tracking is a crucial aspect of autonomous driving and is widely used in navigation, transportation, autonomous vehicles, and other fields.The classical tracking approach employs a Kalman filter with precise system parameters to estimate the state. However, it is difficult to model their uncertainty because of the complex motion of maneuvering targets and the unknown sensor characteristics.

Location estimation based on feature mode matching with deep network models.

Introduction: Global navigation satellite system (GNSS) signals can be lost in viaducts, urban canyons, and tunnel environments. It has been a significant challenge to achieve the accurate location of pedestrians during Global Positioning System (GPS) signal outages. This paper proposes a location estimation only with inertial measurements.

The Potential of Lipid Droplet-associated Genes as Diagnostic and Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma.

Objective: The role of lipid droplets (LDs) and lipid droplet-associated genes (LD-AGs) remains unclear in head and neck squamous cell carcinoma (HNSCC). This study aimed to investigate LDs in HNSCC and identify LD-AGs essential for the diagnosis and prognosis of HNSCC patients.

Methods: The LDs in the HNSCC and normal cell lines were stained with oil red O.

Lipid droplets' functional protein caveolin-2 is associated with lipid metabolism-related molecule FABP5 and EMT marker E-cadherin in oral epithelial dysplasia.

Aims: To explore the accumulation of lipid droplets (LDs) and its relationship with lipid metabolism, and epithelial-mesenchymal transition (EMT) in the carcinogenesis processes in the oral cavity.

Methods: LDs were stained by oil red O. Forty-eight oral squamous cell carcinomas (OSCC), 78 oral potentially malignant disorders (OPMDs) and 25 normal tissue sections were included to explore the LDs surface protein caveolin-2 and perilipin-3, lipid metabolism-related molecule FABP5 and EMT biomarker E-cadherin expression by immunohistochemical staining.

Deep Spatio-Temporal Graph Network with Self-Optimization for Air Quality Prediction.

The environment and development are major issues of general concern. After much suffering from the harm of environmental pollution, human beings began to pay attention to environmental protection and started to carry out pollutant prediction research. A large number of air pollutant predictions have tried to predict pollutants by revealing their evolution patterns, emphasizing the fitting analysis of time series but ignoring the spatial transmission effect of adjacent areas, leading to low prediction accuracy.

Nanomedicines in oral cancer: inspiration comes from extracellular vesicles and biomimetic nanoparticles.

Oral cancer is a common life-threatening malignancy having high mortality and morbidity rates. During the treatment process, individuals unavoidably experience severe side effects. It is essential to develop safer and more effective strategies.

Novel quorum sensing inhibitor Echinatin as an antibacterial synergist against .

A new antibacterial strategy based on inhibiting bacterial quorum sensing (QS) has emerged as a promising method of attenuating bacterial pathogenicity and preventing bacterial resistance to antibiotics. In this study, we screened Echinatin (Ech) with high-efficiency anti-QS from 13 flavonoids through the AI-2 bioluminescence assay. Additionally, crystal violet (CV) staining combined with confocal laser scanning microscopy (CLSM) was used to evaluate the effect of anti-biofilm against .

Glaucocalyxin A impairs tumor growth via amplification of the ATF4/CHOP/CHAC1 cascade in human oral squamous cell carcinoma.

Ethnopharmacological Relevance: The natural extract glaucocalyxin A (GLA), purified from the aboveground sections of the Chinese traditional medicinal herb Rabdosia japonica (Burm. f.) Hara var.

Modeling and Analysis of Data-Driven Systems through Computational Neuroscience Wavelet-Deep Optimized Model for Nonlinear Multicomponent Data Forecasting.

Complex time series data exists widely in actual systems, and its forecasting has great practical significance. Simultaneously, the classical linear model cannot obtain satisfactory performance due to nonlinearity and multicomponent characteristics. Based on the data-driven mechanism, this paper proposes a deep learning method coupled with Bayesian optimization based on wavelet decomposition to model the time series data and forecasting its trend.

The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods.

State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems' development, sensors can obtain more and more signals and store them.

Hypoxia protects H9c2 cells against Ferroptosis through SENP1-mediated protein DeSUMOylation.

Hypoxia affects proliferation, differentiation, as well as death of cardiomyocyte, and plays an important role in the development of myocardial ischemia. However, the detailed mechanisms through which hypoxia regulates cardiomyocyte ferroptosis have not been explored. In this study, we revealed that hypoxia suppresses the proliferation, migration, and erastin-induced ferroptosis of H9c2 cells.

Distributed Deep Fusion Predictor for a Multi-Sensor System Based on Causality Entropy.

Trend prediction based on sensor data in a multi-sensor system is an important topic. As the number of sensors increases, we can measure and store more and more data. However, the increase in data has not effectively improved prediction performance.

Knockdown of ectodysplasin-A receptor-associated adaptor protein exerts a tumor-suppressive effect in tongue squamous cell carcinoma cells.

Tongue squamous cell carcinoma (TSCC) is a common malignancy in oral cancer with a high mortality and morbidity. The ectodysplasin-A receptor-associated adaptor protein (EDARADD) is a death domain-containing adaptor protein that interacts with the TNF family ligand ectodysplasin A receptor. It is known that EDARADD has an effect on the development of ectodermal derivative tissues, such as hair and teeth.

Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model.

Smart agricultural sensing has enabled great advantages in practical applications recently, making it one of the most important and valuable systems. For outdoor plantation farms, the prediction of climate data, such as temperature, wind speed, and humidity, enables the planning and control of agricultural production to improve the yield and quality of crops. However, it is not easy to accurately predict climate trends because the sensing data are complex, nonlinear, and contain multiple components.

Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis.

Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requirement in atmospheric management. Firstly, the spatio-temporal analysis framework was designed, in which the process of data monitoring, correlation calculation, and result presentation were defined.

A Neuron-Based Kalman Filter with Nonlinear Autoregressive Model.

The control effect of various intelligent terminals is affected by the data sensing precision. The filtering method has been the typical soft computing method used to promote the sensing level. Due to the difficult recognition of the practical system and the empirical parameter estimation in the traditional Kalman filter, a neuron-based Kalman filter was proposed in the paper.

Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network.

The monitoring-blind area exists in the industrial park because of private interest and limited administrative power. As the atmospheric quality in the blind area impacts the environment management seriously, the prediction and inference of the blind area is explored in this paper. Firstly, the fusion network framework was designed for the solution of "Circumjacent Monitoring-Blind Area Inference".

A NeuroD1 AAV-Based Gene Therapy for Functional Brain Repair after Ischemic Injury through In Vivo Astrocyte-to-Neuron Conversion.

Adult mammalian brains have largely lost neuroregeneration capability except for a few niches. Previous studies have converted glial cells into neurons, but the total number of neurons generated is limited and the therapeutic potential is unclear. Here, we demonstrate that NeuroD1-mediated in situ astrocyte-to-neuron conversion can regenerate a large number of functional new neurons after ischemic injury.