Emerging glucose oxidase-delivering nanomedicines for enhanced tumor therapy.

Abnormalities in glucose metabolism have been shown to characterize malignant tumors. Glucose depletion by glucose oxidase (GOD) has shown great potential in tumor therapy by causing tumor starvation. Since 2017, nanomedicines have been designed and utilized to deliver GOD for more precise and effective glucose modulation, which can overcome intrinsic limitations of different cancer therapeutic modalities by remodeling the tumor microenvironment to enhance antitumor therapy.

A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness Under the Test-Negative Design: Analysis of Québec Administrative Data.

The test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-19 vaccine surveillance, notably in Québec, Canada. Some studies have addressed the identifiability and estimation of causal parameters under the TND, but efficiency bounds for nonparametric estimators of the target parameter under the unconfoundedness assumption have not yet been investigated. Motivated by the goal of improving adjustment for measured confounders when estimating COVID-19 VE among community-dwelling people aged years in Québec, we propose a one-step doubly robust and locally efficient estimator called TNDDR (TND doubly robust), which utilizes cross-fitting (sample splitting) and can incorporate machine learning techniques to estimate the nuisance functions and thus improve control for measured confounders.

Tumor microenvironment-responsive engineered hybrid nanomedicine for photodynamic-immunotherapy via multi-pronged amplification of reactive oxygen species.

Reactive oxygen species (ROS) is promising in cancer therapy by accelerating tumor cell death, whose therapeutic efficacy, however, is greatly limited by the hypoxia in the tumor microenvironment (TME) and the antioxidant defense. Amplification of oxidative stress has been successfully employed for tumor therapy, but the interactions between cancer cells and the other factors of TME usually lead to inadequate tumor treatments. To tackle this issue, we develop a pH/redox dual-responsive nanomedicine based on the remodeling of cancer-associated fibroblasts (CAFs) for multi-pronged amplification of ROS (ZnPP@FQOS).

Predicting microbe-disease associations via graph neural network and contrastive learning.

In the contemporary field of life sciences, researchers have gradually recognized the critical role of microbes in maintaining human health. However, traditional biological experimental methods for validating the association between microbes and diseases are both time-consuming and costly. Therefore, developing effective computational methods to predict potential associations between microbes and diseases is an important and urgent task.

Cuproptosis and Serine Metabolism Blockade Triggered by Copper-Based Prussian Blue Nanomedicine for Enhanced Tumor Therapy.

Cuproptosis, a newly defined cell death process, represents a novel modality with significant therapeutic potential in cancer treatment. Nevertheless, the modest concentration and transient half-life of copper ions in the bloodstream constrain their efficient delivery into tumor cells. In this study, a copper-based prussian blue nanostructure loaded with serine metabolic inhibitor (NCT-503@Cu-HMPB) is constructed for selectively inducing cuproptosis combined with disrupting serine metabolism.

The life strategy of bacteria rather than fungi shifts in karst tiankeng island-like systems.

Unlabelled: Karst tiankeng is a typical terrestrial habitat island-like system, known as an oasis in a degraded karst landscape. However, we know little about the composition, structure, and life strategies of soil microbial communities in the karst tiankeng ecosystem. In this study, we use amplicon sequencing to investigate the soil bacteria and fungi of 26 karst tiankeng in two typical karst tiankeng groups.

High power mid-infrared side-pump combiner with good thermal stability based on the point-by-point fusion splicing technique.

High-power mid-infrared fiber lasers, featuring superior beam quality and good power-scaling ability, have a few important applications in material processing, medical surgery, and molecule spectroscopy. The high-power pump light combiner, as one of the key elements for constructing a mid-infrared fiber laser, is crucial for the laser performance. While some advanced side-pump combiners based on fluoride fiber have been reported in recent literatures, the thermal stability of the fluoride fiber combiner, which is closely-related to its power-scaling capability, is a long-living challenge.

Metal-organic frameworks-based nanozyme sensor array for the discrimination of biogenic amines and detection of histamine.

Biogenic amines (BAs) are hazardous substances found in fishery products that are closely associated with fish spoilage and threaten food safety. Traditional chromatographic methods for detecting BAs are expensive, complex, and time-consuming. In this study, we developed a nanozyme-based sensor array to efficiently discriminate between four types of BAs and sensitively detect histamine.

A multifunctional soybean protein isolates crosslinked gelatins composite mulch film: Fabrication, characterization, and application.

The development of sustainable agriculture has boosted an increase in demand for biodegradable and multifunctional biomass-based mulch films. Herein, a sort of eco-friendly and multifunctional soybean protein isolates crosslinked gelatins (SPI-c-Gel) composite mulch films were elaborately designed through the Schiff base reaction. The formation of physical entanglement and chemical cross-linking between the molecular chains of SPI and Gel could effectively dissipate the loading energy and thereby strengthen the resistance of the composite mulch films to water penetration.

Associations between Life's Essential 8 and gallstones among US adults: A cross-sectional study from NHANES 2017-2018.

Background: Cardiovascular illness and gallstones are closely related. Our goal was to determine whether gallstones and the updated LE8 score, which measures cardiovascular health among US adults, are related.

Methods: 3,570 adults participated in the 2017-2018 National Health and Nutrition Examination Survey, which provided the data for our study.

Number of involved nodal stations predicts survival in small cell lung cancer.

Background: In small cell lung cancer (SCLC), the pathological N category is identical to it in non-small cell lung cancer (NSCLC) and remains unchanged over a decade. Here we verified the discriminability of number of involved nodal stations (nS) in SCLC and compared its efficacy in predicting survival with currently used pathological nodal (pN) staging.

Methods: We retrospectively analyzed the patients who received operations and were pathologically diagnosed as SCLC at Shanghai Pulmonary Hospital between 2009 and 2019.

Manganese-arginine nanozymes as oxidase mimics for smartphone-based intelligent detection of 4'-O-methylpyridoxine.

By self-assembly of MnCl and arginine under alkaline conditions, ultra-small MnArg nanoparticles were successfully constructed as oxidase (OXD) mimics for intelligent detection of the Ginkgo toxin 4'-O-methylpyridoxal (MPN). The obtained MnArg nanozymes possessed excellent OXD-like activity and thermal stability. Based on the inhibitory effect of MPN for the catalytic activity of MnArg, this system was utilized for the colorimetric sensing of MPN with a low limit of detection (LOD) of 2.

RILP Induces Cholesterol Accumulation in Lysosomes by Inhibiting Endoplasmic Reticulum-Endolysosome Interactions.

Endoplasmic reticulum (ER)-endolysosome interactions regulate cholesterol exchange between the ER and the endolysosome. ER-endolysosome membrane contact sites mediate the ER-endolysosome interaction. VAP-ORP1L (vesicle-associated membrane protein-associated protein- OSBP-related protein 1L) interaction forms the major contact site between the ER and the lysosome, which is regulated by Rab7.

Multilevel metabolic engineering for enhanced synthesis of S-adenosylmethionine by Bacillus amyloliquefaciens.

Objectives: To enhance the de novo synthesis of SAM, the effects of several key genes on SAM synthesis were examined based on modular strategy, and the key genes were manipulated to obtain an engineered strain with high SAM production.

Results: In Bacillus amyloliquefaciens HSAM6, the deletion of argG gene to block aspartic acid branching degradation increased SAM titer to 254.78 ± 15.

Potential biases in test-negative design studies of COVID-19 vaccine effectiveness arising from the inclusion of asymptomatic individuals.

The test-negative design (TND) is a popular method for evaluating vaccine effectiveness (VE). A "classical" TND study includes symptomatic individuals tested for the disease targeted by the vaccine to estimate VE against symptomatic infection. However, recent applications of the TND have attempted to estimate VE against infection by including all tested individuals, regardless of their symptoms.

Examination of the Expression Profile of Resistance Genes in Yuanjiang Common Wild Rice ().

The rice blight poses a significant threat to the rice industry, and the discovery of disease-resistant genes is a crucial strategy for its control. By exploring the rich genetic resources of Yuanjiang common wild rice () and analyzing their expression patterns, genetic resources can be provided for molecular rice breeding. The target genes' expression patterns, subcellular localization, and interaction networks were analyzed based on the annotated disease-resistant genes on the 9th and 10th chromosomes in the rice genome database using fluorescent quantitative PCR technology and bioinformatics tools.

A permutable MLP-like architecture for disease prediction from gut metagenomic data.

Metagenomic data plays a crucial role in analyzing the relationship between microbes and diseases. However, the limited number of samples, high dimensionality, and sparsity of metagenomic data pose significant challenges for the application of deep learning in data classification and prediction. Previous studies have shown that utilizing the phylogenetic tree structure to transform metagenomic abundance data into a 2D matrix input for convolutional neural networks (CNNs) improves classification performance.

Natural shellac-based microcapsules as lipase carriers for recyclable efficient Pickering interfacial biocatalysis.

Enzyme is an important class of catalyst. However, the efficiency of enzyme-catalyzed reactions is constrained by the limited contact between the enzyme and its substrate. In this study, to overcome this challenge, lipase-loaded microcapsules were prepared from natural shellac and nanoparticles using the emulsion template method.