Exploring the mechanism of fatty acids to improve 3D printing precision of cassava starch gel.

Understanding the printability and underlying mechanisms of starch food systems is crucial for the industrial application of 3D food printing. This work investigated the effect of fatty acids with various degrees of unsaturation and chain lengths on the three-dimensional (3D) food printing precision of cassava starch (CS) gel and its mechanism. Results showed that fatty acids with shorter chain lengths and higher unsaturation levels improved printing precision.

Neutrophils: Linking Inflammation to Thrombosis and Unlocking New Treatment Horizons.

Neutrophils play a key role in inflammatory responses and thrombosis, but their complex interactions in disease pathogenesis are not fully understood. This review examines the multifaceted roles of neutrophils, focusing on their activation, cytokine release, and formation of neutrophil extracellular traps (NETs), which contribute to host defense and thrombosis. We discuss the interaction between inflammation and coagulation, the direct effect of neutrophils on thrombus stability, and their involvement in pathological thrombotic diseases.

SS-MSDA: Streamlined Sample-level Multi-source Domain Adaptation for EEG Emotion Recognition.

Affective EEG-based Brain-Computer Interface (BCI) offers extensive prospects. Yet, it grapples with notable challenges in consistently achieving accurate emotion recognition among new subjects. Mitigating this matter, Multi-Source Domain Adaptation (MSDA) has been advanced.

Narrowband-Enhanced Method for Improving Frequency Recognition in SSVEP-BCIs.

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCI) provide a non-invasive and effective means for communication and control, which fundamentally rely on the feature of frequency information. However, filter banks in conventional spatial filter classification methods do not effectively utilize narrowband information. This study proposed a narrowband-enhanced filter bank canonical correlation analysis (NE-FBCCA) to integrate narrowband signal processing with a broadband filter bank analysis.

Enhancing Detection of SSVEP-based BCIs Using Adjacent Frequencies Fusion Method.

Brain-computer interfaces (BCIs) have emerged as transformative technologies, enabling direct communication between the human brain and external devices. Steady-state visual evoked potentials (SSVEP) have gained particular attention due to their potential in BCIs. Current decoding algorithms do not take advantage of the correlation coefficients of adjacent frequencies.

A Novel SSVEP Modulation Method Utilizing VR-Based Binocular Vision.

This paper presents a novel method for modulating steady-state visual evoked potentials (SSVEP) based on binocular vision in virtual reality (VR). The method involves displaying monocular frequencies in the left and right view of VR to encode nine binocular targets using only two frequencies. We constructed a VR-BCI system and validated the effectiveness of this binocular-encoded paradigm through the task-related component analysis (TRCA) algorithm, which is a supervised approach based on individual templates.

Enhancing Word-Level Imagined Speech BCI Through Heterogeneous Transfer Learning.

In this study, we proposed a novel heterogeneous transfer learning approach named Focused Speech Feature Transfer Learning (FSFTL), aimed at enhancing the performance of electroencephalogram (EEG)-based word-level Imagined Speech (IS) Brain-Computer Interface (BCI). In IS BCI, the classification accuracy for imagining specific words is relatively low due to the inherent complexity in high-level feature variations. However, the binary classification accuracy for IS/rest is significantly higher.

EEG Emotion Recognition Based on 3D-CTransNet.

Emotion recognition is of great significance for brain-computer interface and emotion computing, and EEG plays a key role in this field. However, the current design of brain computer interface deep learning model is faced with algorithmic or structural constraints, and it is difficult to recognize the complex features in EEG signals with long-term dynamic changes. To solve this issue, a hybrid CNN-Transformer structure using 3D data input is proposed and named 3D-CTransNet in this paper, which solves the problem of performance degradation of the traditional CNN-LSTM hybrid structure in the recognition of long sequence signals.

Random Subset Multi-domain Feature Extraction for Attentional State Recognition.

Existing attentional state recognition methods achieve good results by utilizing frequency domain features, but spatial information has not been fully considered. In this paper, a random subset multi-domain feature extraction method is proposed. To exploit the spatial information, the training data is first divided into several non-overlapping subsets, and independent Riemannian manifolds are constructed within each subset.

Amplitude Modulation Depth Coding Method for SSVEP-based Brain-computer Interfaces.

In steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), the limited availability of frequency resources inherently constrains the scale of the instruction set, presenting a substantial challenge for efficient communication. As the number of stimuli increases, the comfort level of the stimulus interface also becomes increasingly demanding due to the expanded flickering area. To address these issues, we proposed a novel amplitude modulation depth coding (AMDC) method that employs Amplitude Shift Keying (ASK) technique to modulate the luminance level of stimuli dynamically.

Bioassay-Guide Preparative Separation of Hypoglycemic Components from (L.) DC by Conventional and pH-Zone Refining Countercurrent Chromatography.

(L.) DC is a long-used medicinal and edible plant in China folk. Its hyperglycemic effects have garnered increasing public attention in recent years.

Insights into the improved cold-water solubility and digestibility of alkaline-alcohol modified cassava starch: A discussion from the perspective of fine structure.

Multi-objective optimization of starch for higher solubility and lower glycemic index is a challenge. In this study, we investigated the molecular structure evolution of cold water-soluble starch (CWS) and its correlation mechanism with solubility and digestibility by alkali-alcohol treatment of cassava starch. As NaOH concentration increased, the average molecular size of CWS gradually decreased, and the medium-long amylose (AM) chains (X ~ 1000-10,000) decreased sharply.

Quantitative research on aesthetic value of the world heritage karst based on UGC data: A case study of Huangguoshu Scenic Area.

The World Natural Heritage is a rare and irreplaceable natural landscape recognized by all mankind, with outstanding significance and universal value. Among them, the World Heritage Karst sites(WHKs) holds an important position due to its special natural beauty and aesthetic value. In the field of landscape evaluation, interdisciplinary and interdisciplinary cooperation using different methods has always been a research focus.

Comprehensive evaluation of compound Kushen injection combined with zoledronic acid in treating bone metastasis cancer pain based on meta-analysis and decision tree model.

Objective: To evaluate the safety, efficacy, and cost-effectiveness of combining Compound Kushen Injection (CKI) with zoledronic acid in the treatment of bone metastasis-induced cancer pain in malignant tumors.

Methods: A comprehensive search of Chinese and English databases identified randomized controlled trials (RCTs) investigating CKI combined with zoledronic acid for bone metastases in malignancies. Methodological quality assessments were performed on all included studies, and a meta-analysis was conducted using RevMan 5.

Teacher support and secondary school students' learning engagement: A moderated mediation model.

Learning engagement has attracted increasing interest in recent years, with teacher support, academic self-efficacy, psychological resilience, and positive academic emotion identified as key factors. However, the moderated mediating mechanisms between teacher support and learning engagement remain unexplored. This study aimed to investigate the roles of academic self-efficacy and psychological resilience as mediators, and positive academic emotion as a moderator, in the relationship between teacher support and secondary school students' learning engagement, from the perspective of the Self-determination Theory and Emotion Regulation Theory.

Myeloid dendritic cells and periodontal disease association: integrated study of single-cell sequencing and Mendelian randomization analysis.

Background: Periodontal disease is a widespread inflammatory condition that compromises the supporting structures of the teeth, potentially resulting in tooth loss if left untreated. Despite advancements in therapeutic interventions and an enhanced understanding of its pathophysiology, emerging techniques such as single-cell RNA sequencing (scRNA-seq) and Mendelian randomization (MR) present new opportunities for precision medicine in the management of periodontal disease.

Methods: Data derived from the GSE152042 dataset underwent rigorous quality control, normalization, and dimensionality reduction using Seurat and the MonacoImmuneData framework.

Effect of Stress Aging on Strength, Toughness and Corrosion Resistance of Al-10Zn-3Mg-3Cu Alloy.

The 7000 series aluminum alloy represented by Al-Zn-Mg-Cu has good strength and toughness and is widely used in the aerospace field. However, its high Zn content results in poor corrosion resistance, limiting its application in other fields. In order to achieve the synergistic improvement of both strength and corrosion resistance, this study examines the response of strength, toughness and corrosion resistance of a high-strength aluminum alloy tail frame under aging conditions with external stresses of 135 MPa, 270 MPa and 450 MPa.

Key Node Identification Method Based on Multilayer Neighbor Node Gravity and Information Entropy.

In the field of complex network analysis, accurately identifying key nodes is crucial for understanding and controlling information propagation. Although several local centrality methods have been proposed, their accuracy may be compromised if interactions between nodes and their neighbors are not fully considered. To address this issue, this paper proposes a key node identification method based on multilayer neighbor node gravity and information entropy (MNNGE).

MP: A steady-state visual evoked potential dataset based on multiple paradigms.

In the field of steady-state visual evoked potential (SSVEP), stimulus paradigms are regularly arranged or mimic the style of a keyboard with the same size. However, stimulation paradigms have important effects on the performance of SSVEP systems, which correlate with the electroencephalogram (EEG) signal amplitude and recognition accuracy. This paper provides MP dataset that was acquired using a 12-target BCI speller.

Non vertical ionization-dissociation model for strong IR induced dissociation dynamics of [Formula: see text].

Electron-nuclear coupling plays a crucial role in strong laser induced molecular dissociation dynamics. The interplay between electronic and nuclear degrees of freedom determines the pathways and outcomes of molecular fragmentation. However, a full quantum mechanical treatment of electron-nuclear dynamics is computationally intensive.

Integration of volatilomics and microbiome diversity reveals key flavor-related metabolic pathways in semi-dried large yellow croaker (Pseudosciaena crocea).

A complex microbial community is critical for developing unique flavors in semi-dried large yellow croaker (Pseudosciaena crocea). Volatilomics analysis identified hexanal, heptanal, nonanal, phenylacetaldehyde, 1-octen-3-ol, and butanoic acid were identified as the key flavor compounds in the fish. Clostridium sensu stricto was the dominant genus, with a relative abundance of 79.

CMAP prediction and experimental validation of Forskolin as a podocyte protective and anti-proteinuric drug for nephrotoxic serum-treated mice.

Podocyte injury leads to proteinuria and glomerular diseases. Different podocyte injuries have distinct mechanisms. It is desirable to use a regimen that targets the mechanism of a given podocyte injury for a specific and improved result.

Li[AlPOF(OH)](HO) and [Al(PO)F(HO)]( = K, Rb): Counter Cation Templates Derived Three Polar Alkaline Metal Fluoroaluminophosphates.

Three novel alkali metal fluoroaluminophosphates, Li[AlPOF(OH)](HO) and [Al(PO)F(HO)]( = K, Rb), were designed and synthesized by using low-temperature flux methods. They crystallized in polar space groups and 222, respectively. Li[AlPOF(OH)](HO) features a unique two-dimensional layered structure of fluoroaluminophosphate [AlPOF(OH)], composed of alternately connected AlFO octahedra and PO tetrahedra.

Methylophiopogonanone A Inhibits Ferroptosis in H9c2 Cells: An Experimental and Molecular Simulation Study.

In this study, homoisoflavone methylophiopogonanone A (MOA) was investigated for its inhibitory effect on ferroptosis of H9c2 cells using a set of cellular assays, such as BODIPY-probed and HDCFDA-probed flow cytometry analyses, cell counting kit-8 analysis (CCK-8), and lactate dehydrogenase (LDH) release analysis. All these cellular assays adopted Fer-1 as the positive control. Subsequently, MOA and Fer-1 were subjected to two antioxidant assays, i.

Design, synthesis and biological evaluation of new SIRT3 activators for the treatment of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) represents a highly malignant subtype of breast cancer with limited therapeutic options. In this study, we designed and synthesized a series of 1,4-DHP derivatives by structure-based strategy, 43 was documented to be a potent SIRT3 activator and exhibited profound anti-proliferative activity in BT-549 and MDA-MB-231 cells with low toxicity over normal cells. Additionally, 43 displayed the ability of direct binding to SIRT3 with a K value of 51.