High-pressure homogenization transformed salmon protein filament into micelle structure: Improvement on the stability and swallowing rheology of dysphagia-oriented salmon emulsion gels.

The aging population is stimulating increased demand for dysphagia-oriented foods, yet most current options are made of ultra-processed macronutrients and lack high-quality protein and ω-3 fatty acids. This study explores the use of whole salmon fillets as a myofibrillar protein source to stabilize salmon backbone oil, creating ω-3-rich emulsion gels (50-60 vol%) for dysphasia individuals. Two-step high-pressure homogenization (HPH; 50 MPa) improved emulsion texture, storage stability, and swallowability (IDDSI level 4) by reducing oil droplet size (from 20 to 2 μm) and increasing elastic modulus by 6-8 times and viscosity by more than 10 times.

Covalent organic frameworks and related innovative materials in chiral separation and recognition.

Chiral recognition and enantioseparation are of paramount importance in various fields, including pharmaceuticals, agrochemicals, and material science. Covalent organic frameworks (COFs) have emerged as promising materials for chiral separation due to their unique structural features and tunable properties. This review provided a comprehensive overview of recent progress in the application of COFs and related innovative materials for chiral separation and recognition.

EEG-VTTCNet: A loss joint training model based on the vision transformer and the temporal convolution network for EEG-based motor imagery classification.

Brain-computer interface (BCI) is a technology that directly connects signals between the human brain and a computer or other external device. Motor imagery electroencephalographic (MI-EEG) signals are considered a promising paradigm for BCI systems, with a wide range of potential applications in medical rehabilitation, human-computer interaction, and virtual reality. Accurate decoding of MI-EEG signals poses a significant challenge due to issues related to the quality of the collected EEG data and subject variability.

Lipid Metabolism in Pregnancy Women with Hypothyroidism and Potential Influence on Pregnancy Outcome.

Thyroid hormone (TH) is essential for maintaining normal physiological processes during pregnancy, including the metabolism of energy materials in both the mother and fetus and the growth and development of fetal bone and nervous system. TH can act on the liver, fat, and other tissues and organs to participate in lipid synthesis and breakdown through multiple pathways. Consequently, abnormal thyroid function is often accompanied by lipid metabolism disorders.

Pain experience reduces social avoidance to others in pain: a c-Fos-based functional connectivity network study in mice.

Pain experience increases individuals' perception and contagion of others' pain, but whether pain experience affects individuals' affiliative or antagonistic responses to others' pain is largely unknown. Additionally, the neural mechanisms underlying how pain experience modulates individuals' responses to others' pain remain unclear. In this study, we explored the effects of pain experience on individuals' responses to others' pain and the underlying neural mechanisms.

Pathways in formulating foods for the elderly.

The growth of the elderly population worldwide is posing significant challenges to human society. The progressive physical and physiological changes occur with aging, including decreased appetite, incomplete digestion, and reduced absorption of nutrients. A common feature of many elderly people's diets is a deficiency in proteins (especially easily digestible ones) and micronutrients (e.

Investigation of interactions between Jiuzao glutelin with resveratrol, quercetin, curcumin, and azelaic and potential improvement on physicochemical properties and antioxidant activities.

The interactions among small molecular functional components (FCTs) within a food matrix have become a focal point for enhancing their stability and bioactivities. Jiuzao glutelin (JG) is a mixed plant protein within Jiuzao (a protein-rich baijiu distillation by-product). This study aimed to explore the interactions between JG and selected FCTs, including resveratrol (RES), quercetin (QUE), curcumin (CUR), and azelaic acid (AZA), and the consequential impact on stability and antioxidant activity of the complexes.

Sexually dimorphic control of affective state processing and empathic behaviors.

Recognizing the affective states of social counterparts and responding appropriately fosters successful social interactions. However, little is known about how the affective states are expressed and perceived and how they influence social decisions. Here, we show that male and female mice emit distinct olfactory cues after experiencing distress.

Classification Algorithm for fNIRS-based Brain Signals Using Convolutional Neural Network with Spatiotemporal Feature Extraction Mechanism.

Brain Computer Interface (BCI) is a highly promising human-computer interaction method that can utilize brain signals to control external devices. BCI based on functional near-infrared spectroscopy (fNIRS) is considered a relatively new and promising paradigm. fNIRS is a technique of measuring functional changes in cerebral hemodynamics.

Analysis of size-dependent optoelectronic properties of red AlGaInP micro-LEDs.

We have theoretically investigated the size-dependent optoelectronic properties of InGaP/AlGaInP-based red micro-LEDs through an electro-optical-thermal coupling model. The model considers thermal effects due to current crowding near the electrodes, non-thermal efficiency droop due to electron leakage, and etch defects on the LED sidewall. Sidewall defects reduce the carrier concentration at the light-emitting surface's edge and exacerbate the current crowding effect.

ETCNet: An EEG-based motor imagery classification model combining efficient channel attention and temporal convolutional network.

Brain-computer interface (BCI) enables the control of external devices using signals from the brain, offering immense potential in assisting individuals with neuromuscular disabilities. Among the different paradigms of BCI systems, the motor imagery (MI) based electroencephalogram (EEG) signal is widely recognized as exceptionally promising. Deep learning (DL) has found extensive applications in the processing of MI signals, wherein convolutional neural networks (CNN) have demonstrated superior performance compared to conventional machine learning (ML) approaches.

EEG-FMCNN: A fusion multi-branch 1D convolutional neural network for EEG-based motor imagery classification.

Motor imagery (MI) electroencephalogram (EEG) signal is recognized as a promising paradigm for brain-computer interface (BCI) systems and has been extensively employed in various BCI applications, including assisting disabled individuals, controlling devices and environments, and enhancing human capabilities. The high-performance decoding capability of MI-EEG signals is a key issue that impacts the development of the industry. However, decoding MI-EEG signals is challenging due to the low signal-to-noise ratio and inter-subject variability.

Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism.

Motor imagery (MI) is a brain-computer interface (BCI) technique in which specific brain regions are activated when people imagine their limbs (or muscles) moving, even without actual movement. The technology converts electroencephalogram (EEG) signals generated by the brain into computer-readable commands by measuring neural activity. Classification of motor imagery is one of the tasks in BCI.

Differences in the neural basis and transcriptomic patterns in acute and persistent pain-related anxiety-like behaviors.

Background: Both acute and persistent pain is associated with anxiety in clinical observations, but whether the underlying neural mechanisms differ is poorly understood.

Methods: We used formalin or complete Freund's adjuvant (CFA) to induce acute or persistent pain. Behavioral performance was assessed by the paw withdrawal threshold (PWT), open field (OF), and elevated plus maze (EPM) tests.

Microfluidic static droplet generated quantum dot arrays as color conversion layers for full-color micro-LED displays.

This paper presents an easy and intact process based on microfluidics static droplet array (SDA) technology to fabricate quantum dot (QD) arrays for full-color micro-LED displays. A minimal sub-pixel size of 20 μm was achieved, and the fluorescence-converted red and green arrays provide good light uniformity of 98.58% and 98.

A Nanoenzyme Constructed from Manganese and Strandberg-Type Phosphomolybdate with Versatility in Antioxidant and Modulating Conformation of A Protein Misfolding Aggregates In Vitro.

Amyloid -peptide (A) misfolding aggregates with -sheet structures and surplus reactive oxygen species (ROS) are both considered to be the culprit of neuronal toxicity in Alzheimer's disease (AD). Therefore, modulating the misfolding mode of A and inhibiting ROS simultaneous has become an important method for anti-AD. Herein, a nanoscale manganese-substituted polyphosphomolybdate (Hen)[Mn(HO)][Mn(HO)][PMoO]·14.

The Novel Fluorescent Probe Toward Yttrium(III) and its Bioimaging.

In this paper, the novel fluorescence probe XP based on Schiff-base was designed, synthesized and characterized, which could detect Yselectively and sensitively. The recognition mechanism of XP toward Y was studied by Job's plot and HRMS. It was investigated that stoichiometric ratio of the probe XP conjugated with Y was 1:2.

LncBook 2.0: integrating human long non-coding RNAs with multi-omics annotations.

LncBook, a comprehensive resource of human long non-coding RNAs (lncRNAs), has been used in a wide range of lncRNA studies across various biological contexts. Here, we present LncBook 2.0 (https://ngdc.

A MnO-nucleic acid nanoprobe with enzyme-free cascade signal amplification for ultrasensitive intracellular microRNA imaging.

A novel MnO-nucleic acid nanoprobe was constructed for catalytic imaging of microRNA in living cells based on the combination of catalytic hairpin assembly, hybridization chain reaction, and DNAzyme amplification. This nanoprobe exhibited ultrahigh sensitivity and specificity, and could distinguish tumor cells and normal cells by live cell microRNA imaging.

Therapeutic drug monitoring of perampanel in children diagnosed with epilepsy: Focus on influencing factors on the plasma concentration-to-dose ratio.

Objective: This study aimed to investigate the efficacy and tolerability of perampanel (PER) therapy and to optimize a specific plasma reference range for PER in children. Another major aim was to evaluate the potential determinators of PER concentration.

Methods: Concentrations obtained from 80 children were analyzed for routine therapeutic drug monitoring (TDM) between 2021 and 2022.

A novel label-free universal biosensing platform based on CRISPR/Cas12a for biomarker detection.

The development of a biosensing platform with high sensitivity, high specificity, and low cost for the detection of biomarkers, especially one that is programmable and universal, is critical for disease surveillance and diagnosis, yet it remains a difficulty. Herein, we combined the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system with a fluorescent label-free biosensor platform for sensitive and specific detection of disease-related protein, small molecule and nucleic acid. In this strategy, we designed an exonuclease III-mediated target cycle and released a universal trigger chain to stimulate the enzyme activity of CRISPR/Cas12a for additional signal amplification.

Strategy for Detecting Carbon Monoxide: Cu-Assisted Fluorescent Probe and Its Applications in Biological Imaging.

Herein, a novel strategy was proposed for identifying carbon monoxide (CO), which plays a crucial part in living systems. For the first time, we have managed to design, synthesize, and characterize successfully this new Cu-assisted fluorescent probe () in detecting CO. Compared with the commonly adopted Pd-mediated Tsuji-Trost reaction recognition method, such a new strategy did not engage costly palladium (II) salt and generated no leaving group, indicating a satisfactory anti-interference ability.