MoB QDs/N, F-CDs for ratiometric fluorescence sensing of perfluorooctanoic acid based on fluorine‑fluorine interaction.

A dual-emission ratiometric fluorescence probe was constructed for detection of perfluorooctanoic acid (PFOA) by hybridizing MoB quantum dots (MoB QDs) and nitrogen, fluorine co-doped carbon dots (N, F-CDs). As the concentration of PFOA increased, the fluorescence emission of MoB QDs/N, F-CDs at 560 nm was quenched due to fluorine-fluorine interaction, while the fluorescence emission at 440 nm kept unchanged, resulting in the fluorescence color changing from yellow to green. A good linear relationship was observed between I/I and the concentration of PFOA in the range 0.

Shared gene signatures and molecular mechanisms link ankylosing spondylitis and rheumatoid arthritis.

Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are closely related autoimmune diseases with shared mechanisms that remain unclear. This study aims to identify shared molecular signatures and hub genes underlying the co-occurrence of AS and RA using clinical and transcriptomic data, focusing on immune dysregulation pathways. The CBC data of 23,289 patients were collected, and six machine learning algorithms were applied to develop disease prediction models for AS and RA.

Comprehensive analysis of T-2 toxin contamination in maize from Northeast China using automated immunomagnetic beads system coupled with LC-MS/MS.

This study developed an immunomagnetic beads (IMB)-based high-throughput, automated, magneto-controlled pretreatment system coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for accurate analysis of T-2 toxin in grains and feeds. The method demonstrated good linearity and sensitivity toward T-2 toxin, with detection and quantification limits of 0.13 and 0.

NIR-II Type I Photosensitizer for Efficient Cancer Therapy Through Synergistic Ferroptosis/Pyroptosis Induction and Mitophagy Inhibition.

The advancement of tumor-targeted phototheranostics requires photosensitizers (PSs) exhibiting multimodal intervention capacities, such as mitophagy regulation and programmed cell death activation. However, the rational design of such PSs remains a significant challenge in precision oncology. In this study, a mitochondria-targeted near-infrared II (NIR-II) emissive PS (MTC) is reported, which synergistically induces ferroptosis and pyroptosis while inhibiting mitophagy for precise tumor ablation.

GHSR-Foxo1 Signaling in Macrophages Promotes Liver Fibrosis via Inflammatory Response and Hepatic Stellate Cell Activation.

Liver fibrosis is a severe liver disease directly linked to chronic inflammation, in which hepatic macrophages play a key role. Growth hormone secretagogue receptor (GHSR) is the receptor of nutrient-sensing hormone ghrelin that has essential functions in metabolism, inflammation, and wound-healing. However, the role of GHSR in liver fibrosis is unknown.

CHIP mediates glucagon action on hepatic glucose production via regulating Smad3 ubiquitination.

Aims: Excessive hepatic glucose production (HGP) driven by glucagon contributes to hyperglycaemia in obesity and type 2 diabetes (T2D), yet the molecular mechanisms underlying this dysregulation remain incompletely defined. This study investigates the role of Smad3 signaling and its regulation by CHIP (Carboxy-terminus of Hsc70-interacting protein) in modulating glucagon action on HGP.

Materials And Methods: We examined glucagon signaling and HGP in primary hepatocytes and in high-fat diet (HFD)-induced obese (DIO) mice.

Network-informed analysis of a multivariate trait-space reveals optimal trait selection.

Trait-based analyses have shown great potential to advance our understanding of terrestrial ecosystem processes and functions. However, challenges remain in adequately synthesising a multidimensional and covarying trait space. Reducing the number of studied traits while identifying the most informative ones is increasingly recognized as a priority in functional ecology.

Visual Mamba UNet fusion multi-scale attention and detail infusion for unsound corn kernels segmentation.

Corn seed breeding is a global issue, and has attracted great attention in recent years. Deploying autonomous robots for corn kernel recognition and classification has great potential in terms of constructing environmentally friendly agriculture, and saving manpower. Existing segmentation methods that utilize U-shaped architectures typically operate by processing images in discrete pixel-based segments.

Immunomagnetic metal-organic frameworks based coupling-free and extraction-free sensitive detection of aflatoxin B in peanut oils.

Conventional AFB detection methods are hindered by cumbersome pretreatment procedures, primarily due to the lack of new sample pretreatment materials and technologies. This work developed a novel coupling-free synthesis strategy for the immunomagnetic metal-organic frameworks (IMMOFs), focusing on its effective and promising application in the extraction-free detection of AFB. By coupling with UPLC-FLD, a sensitive quantification detection method for AFB was developed, exhibiting a linear range of 0.

Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.

Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This study presents a lightweight convolutional neural network designed for real-time wheat flour quality monitoring using near-infrared spectroscopy.

Non-Myopic Beam Scheduling for Multiple Smart-Target Tracking in Phased Array Radar Networks.

This paper addresses beam scheduling for tracking multiple smart targets in phased array radar networks, aiming to mitigate the performance degradation in previous myopic scheduling methods and enhance the tracking performance, which is measured by a discounted cost objective related to the tracking error covariance (TEC) of the targets. The scheduling problem is formulated as a restless multi-armed bandit problem, where each bandit process is associated with a target and its TEC states evolve with different transition rules for different actions, i.e.

Integration of Sense and Control for Uncertain Systems Based on Delayed Feedback Active Inference.

Asa result of the time lag in transmission, the data obtained by the sensor is delayed and does not reflect the state at the current moment. The effects of input delay are often overlooked in active inference (AIF), which may lead to significant deviations in state estimation and increased prediction errors, particularly when the system is subjected to a sudden external stimulus. In this paper, a theoretical framework of delayed feedback active inference (DAIF) is proposed to enhance the applicability of AIF to real systems.

An Improved Multi-Scale Feature Extraction Network for Rice Disease and Pest Recognition.

In the process of rice production, rice pests are one of the main factors that cause rice yield reduction. To implement prevention and control measures, it is necessary to accurately identify the types of rice pests and diseases. However, the application of image recognition technologies focused on the agricultural field, especially in the field of rice disease and pest identification, is relatively limited.

A Novel Hypersonic Target Trajectory Estimation Method Based on Long Short-Term Memory and a Multi-Head Attention Mechanism.

To address the complex maneuvering characteristics of hypersonic targets in adjacent space, this paper proposes an LSTM trajectory estimation method combined with the attention mechanism and optimizes the model from the information-theoretic perspective. The method captures the target dynamics by using the temporal processing capability of LSTM, and at the same time improves the efficiency of information utilization through the attention mechanism to achieve accurate prediction. First, a target dynamics model is constructed to clarify the motion behavior parameters.

Cascaded Aggregation Convolution Network for Salient Grain Pests Detection.

Pest infestation poses significant threats to grain storage due to pests' behaviors of feeding, respiration, excretion, and reproduction. Efficient pest detection and control are essential to mitigate these risks. However, accurate detection of small grain pests remains challenging due to their small size, high variability, low contrast, and cluttered background.

ZnPP-laden nanoparticles improve glucose homeostasis and chronic inflammation during obesity.

Background And Purpose: Chronic inflammation plays a pivotal role in the development of Type 2 diabetes mellitus (T2DM). Previous studies have shown that haem oxygenase-1 (HO-1) plays a proinflammatory role during metabolic stress, suggesting that HO-1 inhibition could be an effective strategy to treat T2DM. However, the application of HO-1 inhibitors is restricted due to solubility-limited bioavailability.

An estrogen receptor α-derived peptide improves glucose homeostasis during obesity.

Estrogen receptor α (ERα) plays a crucial role in regulating glucose and energy homeostasis during type 2 diabetes mellitus (T2DM). However, the underlying mechanisms remain incompletely understood. Here we find a ligand-independent effect of ERα on the regulation of glucose homeostasis.

Long-term exposure to dietary emulsifier Tween 80 promotes liver lipid accumulation and induces different-grade inflammation in young and aged mice.

With the advent of industrialization, there has been a substantial increase in the production and consumption of ultra-processed foods (UPFs). These processed foods often contain artificially synthesized additives, such as emulsifiers. Emulsifiers constitute approximately half of the total amount of food additives, with Tween 80 being a commonly used emulsifier in the food industry.

TGF-β1 Signaling Impairs Metformin Action on Glycemic Control.

Hyperglycemia is a hallmark of type 2 diabetes (T2D). Metformin, the first-line drug used to treat T2D, maintains blood glucose within a normal range by suppressing hepatic glucose production (HGP). However, resistance to metformin treatment is developed in most T2D patients over time.

Nutrient-sensing growth hormone secretagogue receptor in macrophage programming and meta-inflammation.

Objective: Obesity-associated chronic inflammation, aka meta-inflammation, is a key pathogenic driver for obesity-associated comorbidity. Growth hormone secretagogue receptor (GHSR) is known to mediate the effects of nutrient-sensing hormone ghrelin in food intake and fat deposition. We previously reported that global Ghsr ablation protects against diet-induced inflammation and insulin resistance, but the site(s) of action and mechanism are unknown.

Joint Denoising-Demosaicking Network for Long-Wave Infrared Division-of-Focal-Plane Polarization Images With Mixed Noise Level Estimation.

Denoising and demosaicking long-wave infrared (LWIR) division-of-focal-plane (DoFP) polarization images are crucial for various vision applications. However, existing methods rely on the sequential application of individual denoising and demosaicking processes, which may result in the accumulation of errors produced by each process. To address this issue, we propose a joint denoising and demosaicking method for LWIR DoFP images based on a three-stage progressive deep convolutional neural network.

Hepatocyte FoxO1 Deficiency Protects From Liver Fibrosis via Reducing Inflammation and TGF-β1-mediated HSC Activation.

Background & Aims: The O-class of the forkhead transcription factor FoxO1 is a crucial factor mediating insulin→PI3K→Akt signaling and governs diverse cellular processes. However, the role of hepatocyte FoxO1 in liver fibrosis has not been well-established. In his study, we investigated the role of hepatocyte FoxO1 in liver fibrosis and uncovered the underlying mechanisms.

Variational Bayesian Algorithms for Maneuvering Target Tracking with Nonlinear Measurements in Sensor Networks.

The variational Bayesian method solves nonlinear estimation problems by iteratively computing the integral of the marginal density. Many researchers have demonstrated the fact its performance depends on the linear approximation in the computation of the variational density in the iteration and the degree of nonlinearity of the underlying scenario. In this paper, two methods for computing the variational density, namely, the natural gradient method and the simultaneous perturbation stochastic method, are used to implement a variational Bayesian Kalman filter for maneuvering target tracking using Doppler measurements.

Suppression of FOXO1 attenuates inflamm-aging and improves liver function during aging.

The liver is a key metabolic organ that maintains whole-body nutrient homeostasis. Aging-induced liver function alterations contribute to systemic susceptibility to aging-related diseases. However, the molecular mechanisms of liver aging remain insufficiently understood.