Oxygen vacancy-enhanced microwave catalysis of Zn-Fe spinel for implant-related infections.

Implant-related infections (IRIs) pose a major challenge in orthopedic applications due to the persistence of biofilms, which are highly resistant to conventional antibiotics. This study introduces oxygen vacancy-engineered Zn-Fe spinel nanoparticles as microwave-responsive antibacterial agents. The oxygen vacancies in the spinel structure enhance reactive oxygen species (ROS) generation under microwave irradiation, providing a dual-mode antibacterial mechanism of thermal and oxidative stress.

Pyrite-driven denitrification by Paracoccus denitrificans: Promoted by enhanced electron transfer and extracellular polymeric substances.

Pyrite can be used in denitrification systems to improve efficiency. In this study, the role of pyrite and extracellular polymeric substances (EPS) was investigated in biological denitrification. In cultures of Paracoccus denitrificans, pyrite effectively enhanced denitrification efficiency, primarily by increasing key components of electron transport system such as cytochrome c and NADH, and upregulating the expression levels of genes involved in the synthesis of riboflavin and cytochrome c, along with denitrification-critical genes such as nosZ and napG.

Effects of variety degeneration on yield formation, quality traits and 2-acetyl-1-pyrroline biosynthesis in high-quality Japonica rice.

The main purpose of the present study was to study the degeneration of the high-quality japonica rice varieties during long-term cultivation, with a focus on changes in yield, rice quality and indices related to 2-acetyl-1-pyrroline (2-AP) biosynthesis, to provide a scientific basis for the comprehensive purification and improvement of high-quality rice varieties. By selecting the lines from the populations of Nanjing 9108 and Nanjing 46 at Liyang, it was found that the mutant lines showed significant differences in the yield and yield components, processing and appearance quality, cooking and flavor quality, rapid viscosity analyser profile characteristics and 2-AP content. Molecular marker detection can be used as a primary method for seed purity identification.

DGX: Uncovering General Behavior of Deep Graph Models with Model-level Explanation.

Deep graph learning models have recently been developed to learn from various graphs that are prevalent in describing and modeling complex systems, including those in bioinformatics. However, a versatile explanation method for uncovering the general graph patterns that guide deep graph models in making predictions remains elusive. In this paper, we propose DGX, a novel deep graph model explainer that generates explanatory graphs to explain trained, black-box deep graph models.

Interfacial Roughness-Reinforced Magnetic Nanosheet Colloidal Gels for Stable Embolization and Magnetothermal Therapy of Hepatic Tumor.

Injectable hydrogels have been developed for transcatheter arterial embolization (TAE) of hepatic tumor owing to their flexibility in injection and embolization. However, the dual requirement for high mechanical robustness and good injectability poses a fundamental challenge, as improvements in one often compromise the other. Colloidal gels offer tunable mechanical properties and feasible injectability through the bottom-up assembly of building blocks.

MEAC: A Multi-Scale Edge-Aware Convolution Module for Robust Infrared Small-Target Detection.

Infrared small-target detection remains a critical challenge in military reconnaissance, environmental monitoring, forest-fire prevention, and search-and-rescue operations, owing to the targets' extremely small size, sparse texture, low signal-to-noise ratio, and complex background interference. Traditional convolutional neural networks (CNNs) struggle to detect such weak, low-contrast objects due to their limited receptive fields and insufficient feature extraction capabilities. To overcome these limitations, we propose a Multi-Scale Edge-Aware Convolution (MEAC) module that enhances feature representation for small infrared targets without increasing parameter count or computational cost.

Pretraining-based Relevance-aware Visit Similarity Network for Drug Recommendation.

Drug recommendation based on electronic health records (EHR) relies heavily on precise patient modeling, which is more complex than conventional recommendation tasks as it requires both temporal modeling of disease progression and referencing similar patients' medication information. However, sparse visit records and vague patient similarity in EHR data pose significant challenges, often introducing noise and ambiguity. To address the above challenges, we propose RaVSNet (Relevance aware Visit Similarity Network), which improves drug recommendation by leveraging both longitudinal and transversal visit similarity and integrating medical relevance knowledge.

Spatiotemporal evolution, driving factors, and policy impacts on ecological quality in the li river basin from 1995 to 2021.

Ecological quality (EQ) protection constitutes a cornerstone of sustainable development. This study develops a Remote Sensing Ecological Index (RSEI) via the Google Earth Engine (GEE) platform, integrating Theil-Sen slope estimation, spatial autocorrelation, GeoDetector, geographically weighted regression (GWR), and text mining to investigate EQ dynamics in the Li River Basin (1995-2021). Key findings reveal: (1) The basin exhibited a "low-central, high-peripheral" RSEI pattern with a fluctuating upward EQ trend that peaked in 2003 (forest conservation and urban green policies) and 2009 (accelerated farmland-to-forest conversion and energy-saving initiatives).

Improving neuronal recovery in spinal cord injury with NEP1-40-modified neural stem cells through RhoA/ROCK signaling pathway modulation.

To evaluate the therapeutic potential of NEP1-40-expressing neural stem cells (NSCs) in improving outcomes in spinal cord injury (SCI) by modulating the RhoA/ROCK signaling pathway. NEP1-40 was overexpressed by transfecting isolated NSCs with NEP1-40 lentivirus, and their differentiation following Nogo-A treatment was assessed via Tuj-1 immunofluorescence. The effects of NEP1-40 overexpression on axonal damage of differentiated NSCs and DRG neurons were examined using Tuj-1 and F-actin immunofluorescence, along with Western blotting for GAP-43, MAP-2, and APP.

Promoting effect of polylactic acid biodegradable plastic on denitrification and co-metabolic degradation of quinoline.

Quinoline is a typical refractory nitrogen heterocyclic organic matter found in industrial wastewater. Our previous studies have shown that poly lactic acid (PLA) could increase the abundance of denitrifying microorganisms in the short term, based on which we hypothosized that they could improve the anaerobic degradation efficiency of quinoline by enhancing the denitrification co-metabolism process. To test this hypothesis, we explored the performance of PLA and magnetically modified PLA (FeO@PLA) fillers in enhancing the anaerobic degradation of quinoline.

Perioperative the BTLA inhibitor (tifcemalimab) combined with toripalimab and chemotherapy for resectable locally advanced thoracic esophageal squamous cell carcinoma trial (BT-NICE trial): a prospective, single-arm, exploratory study.

Background: The treatment of cancer has brought about a paradigm shift with the introduction of immune checkpoint blockade (ICB) therapy, which is mostly dependent on inhibiting PD-1/PD-L1 and CTLA-4. However, recent studies have shown limited efficacy of this treatment in esophageal squamous cell carcinoma (ESCC). Preliminary studies have found that tifcemalimab (the world's first anti-BTLA blocking monoclonal antibody) combined with toripalimab (PD-1) and chemotherapy has shown favorable safety and efficacy in several solid cancers.

thermal-responsive hydrogels for combined photothermal therapy and chemotherapy of pancreatic cancer.

Pancreatic cancer is a malignancy with a poor prognosis and high mortality. Survival outcomes remain very poor despite significant advances in molecular diagnostics and therapeutics in clinical practice. Surgical resection is the only potentially curative treatment, but the tumor is often diagnosed at an advanced stage, and most cancers recur after surgery.

Micro-Nano Fractal Metal Grids as Transparent Conductive Electrodes for Highly Efficient and Stable Perovskite Solar Cells.

Metal mesh-based transparent electrodes possess several notable advantages, including exceptional flexibility, high electrical conductivity, and excellent light transmittance, making them the focus of increasing research interest. However, their widespread application in perovskite solar cells (PSCs) remains a significant challenge due to the susceptibility of the metal grids to corrosion and their inherently rough surface. In this study, we report environmentally stable, low surface roughness transparent conductive electrodes by integrated micro-nano fractal metal grid transparent conductive electrodes (MNF-TCEs) and PH1000.

Characteristics of phosphorus transformation from vivianite mediated by sulphide.

The release of phosphorus (P) from anaerobic sediments becomes the dominant source of P loading with effective control of external P pollution. As a crucial component responsible for binding P, vivianite (Fe(PO)·8HO) in sediment inevitably impacts the P level and transformation. The release of P from vivianite mediated by sulphide was investigated using simulated overlying water-sediment and chemical reaction systems.

Role of VDAC1 in hepatocyte apoptosis during acute liver injury in rats induced by obstructive jaundice.

Objectives: Exploring the role of VDAC1 in hepatocyte apoptosis during acute liver injury induced by obstructive jaundice.

Materials And Methods: Animal and cell models were established to investigate possible mechanisms during acute liver injury induced by OJ. Blood was collected for liver function assessment.

Associations between long-term exposure to fine particulate matter and its constituents with lung cancer incidence: Evidence from a prospective cohort study in Beijing, China.

Association between long-term exposure to ambient fine particulate matter (PM) and lung cancer incidence is well-documented. However, the role of different PM constituents [black carbon (BC), ammonium (NH), nitrate (NO), organic matter (OM), and inorganic sulfate (SO)] remain unclear. The study aimed to specify the associations between PM constituents and lung cancer incidence.

Identifying major depressive disorder based on cerebral blood flow and brain structure: An explainable multimodal learning study.

Magnetic resonance imaging (MRI) offers non-invasive assessments of brain structure and function for analyzing brain disorders. With the increasing accumulation of multimodal MRI data in recent years, integrating information from various modalities has become an effective strategy for improving the detection of brain disorders. This study focuses on identifying major depressive disorder (MDD) by using arterial spin labeling (ASL) perfusion MRI in conjunction with structural MRI data.

Elastocaloric Thermal Battery: Ultrahigh Heat-Storage Capacity Based on Generative Learning-Designed Phase-Change Alloys.

An elastocaloric thermal battery based on generative learning-designed phase-change alloys is developed to facilitate the efficient recycling of low-temperature waste heat. This battery stores thermal energy as latent heat in a phase-change alloy and releases it on demand through applied stress at ambient temperature. Alloy compositions and corresponding processing parameters, tailored to desired transformation characteristics, are efficiently discovered through a generative learning-enabled inverse design framework, which converts the hand-drawn target heat flow curve into tangible compositional and processing designs.

Effects of Extracellular Matrix Changes Induced by a High-Fat Diet on Gallbladder Smooth Muscle Dysfunction.

Background: Gallstone formation is a common digestive ailment, with unclear mechanisms underlying its development. Dysfunction of the gallbladder smooth muscle (GSM) may play a crucial role, particularly with a high-fat diet (HFD). This study aimed to investigate the effects of an HFD on GSM and assess how it alters contractility through changes in the extracellular matrix (ECM).

Integration of network pharmacology, metabolomics and lipidomics for clarifying the role of sphingolipid metabolism in the treatment of liver cancer by regorafenib.

Aims: Regorafenib, an FDA-approved drug for advanced primary liver cancer (PLC), could provide survival benefits for patients. However, markers for its therapeutic sensitivity are lacking. This study seeks to identify sensitive targets of regorafenib in PLC from the perspective of small molecular metabolites.

Loss of USP10 promotes hepatocellular carcinoma proliferation by regulating the serine synthesis pathway through inhibition of LKB1 activity.

Metabolic dysregulation is emerging as a critical factor in tumorigenesis, and reprogramming of serine metabolism has been identified as an essential factor in the progression of hepatocellular carcinoma (HCC). Studies have shown that LKB1 deficiency can activate mTOR to upregulate the serine synthesis pathway (SSP) and promote tumor progression. Our team discovered that ubiquitin-specific protease 10 (USP10) can inhibit HCC proliferation through mTOR, but its relationship with SSP needs further investigation.

Spatio-temporal learning and explaining for dynamic functional connectivity analysis: Application to depression.

Background: Functional connectivity has been shown to fluctuate over time. The present study aimed to identifying major depressive disorders (MDD) with dynamic functional connectivity (dFC) from resting-state fMRI data, which would be helpful to produce tools of early depression diagnosis and enhance our understanding of depressive etiology.

Methods: The resting-state fMRI data of 178 subjects were collected, including 89 MDD and 89 healthy controls.

BrainNPT: Pre-Training Transformer Networks for Brain Network Classification.

Deep learning methods have advanced quickly in brain imaging analysis over the past few years, but they are usually restricted by the limited labeled data. Pre-trained model on unlabeled data has presented promising improvement in feature learning in many domains, such as natural language processing. However, this technique is under-explored in brain network analysis.

A genome-wide association study of panicle blast resistance to in rice.

Unlabelled: Rice blast, caused by (), is one of the most serious diseases worldwide. Developing blast-resistant rice varieties is an effective strategy to control the spread of rice blast and reduce the reliance on chemical pesticides. In this study, 477 sequenced rice germplasms from 48 countries were inoculated and assessed at the booting stage.