Attention Network

Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast and unbalanced image datasets. The absence of early cancer symptoms makes the early identification process challenging. Therefore, from the perspectives of diagnosis, prevention, and therapy, cancer continues to be among the healthcare concerns that numerous researchers work to advance. It is highly essential to design an innovative breast cancer detection model by considering the complications presented in the classical techniques...

Unilateral spatial neglect (USN) results from impaired attentional networks and can affect various sensory modalities, such as visual and somatosensory. The rodent medial agranular cortex (AGm), located in the medial part of the forebrain from rostral to caudal direction, is considered a region associated with spatial attention. The AGm selectively receives multisensory input with the rostral AGm receiving somatosensory input and caudal part receiving visual input. Our previous study showed slower recovery from neglect with anterior AGm lesion using the somatosensory neglect assessment...

Bacterial cellulose (BC) is a type of extracellular polymeric nanomaterial secreted by microorganisms over the course of their growth. It has gained significant attention in the field of bone tissue engineering due to its unique structure of three-dimensional fibrous network, excellent biocompatibility, biodegradability, and exceptional mechanical properties. Nevertheless, BC still has some weaknesses, including low osteogenic activity, a lack of antimicrobial properties, small pore size, issues with the degradation rate, and a mismatch in bone tissue regeneration, limiting its standalone use in the field of bone tissue engineering...

The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs...

INTRODUCTION: Service robot technology is increasingly gaining prominence in the field of artificial intelligence. However, persistent limitations continue to impede its widespread implementation. In this regard, human motion pose estimation emerges as a crucial challenge necessary for enhancing the perceptual and decision-making capacities of service robots. METHOD: This paper introduces a groundbreaking model, YOLOv8-ApexNet, which integrates advanced technologies, including Bidirectional Routing Attention (BRA) and Generalized Feature Pyramid Network (GFPN)...

Sorafenib is an important treatment strategy for advanced hepatocellular carcinoma (HCC). Unfortunately, drug resistance has become a major obstacle in sorafenib application. In this study, whole transcriptome sequencing (WTS) was conducted to compare the paired differences between non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs, in sorafenib-resistant and parental cells. The overlap of differentially expressed ncRNAs (DENs) between the SMMC7721/S and Huh7/S cells and their parental cells was determined...

With the rapid development of international communication, the number of English courses has shown an explosive growth trend, which has caused a serious problem of information overload, resulting in poor teaching performance of recommended English courses. To solve this problem, this paper proposes a graph convolutional neural network model based on College English course texts, students' major, English foundation and network structure characteristics. First, by analyzing the relevant data of College English courses and combining with graph neural network, an English course recommendation algorithm model based on the College English learning strategy of proximity comparison is proposed...

Antifibrinolytics have gained increasing attention in minimizing blood loss and mitigating the risks associated with massive transfusions, including infection and coagulopathy in pediatric patients undergoing spine surgery. Nevertheless, the selection of optimal agent is still a matter of debate. We aim to review the utility of these agents and compare the efficacy of antifibrinolytics in pediatric and adolescent spine surgeries. A comprehensive search was performed in Scopus, Web of Science, and MEDLINE databases for relevant works...

Ischemic stroke (IS) has attracted worldwide attention due to the high mortality and disability rate. Raw rhubarb (RR) is a traditional medicinal plant and whole-food that has been used in China for its various pharmacological activities, such as antioxidant and anti-inflammatory properties. Recent pharmacological research has shown the role of RR against IS, but its mechanism of action remains unclear, particularly in the context of the brain-gut axis. To address this gap in knowledge, the present study was conducted in the middle cerebral artery occlusion/reperfusion (MCAO/R) model with the aim of investigating the effects of RR on regulating the intestinal microbiota barrier and metabolism and thereby reducing inflammatory response so as to improve the IS...

BACKGROUND: Organized sexualized and ritual abuse (ORA), a contentious issue since the 1980s, remains a polarizing topic. Although there is much debate about the existence of this phenomenon, a differentiated perspective is lacking, and no representative study has yet addressed the frequency. OBJECTIVE: This paper aims to investigate the frequency of ORA in Germany using two representative datasets. PARTICIPANTS AND SETTING: Data were collected from representative samples of the German population (N = 2522, N = 2515)...

Accurately identifying cancer driver genes (CDGs) is crucial for guiding cancer treatment and has recently received great attention from researchers. However, the high complexity and heterogeneity of cancer gene regulatory networks limit the precition accuracy of existing deep learning models. To address this, we introduce a model called SCIS-CDG that utilizes Schur complement graph augmentation and independent subspace feature extraction techniques to effectively predict potential CDGs. Firstly, a random Schur complement strategy is adopted to generate two augmented views of gene network within a graph contrastive learning framework...

Visual symmetry activates a network of regions in the extrastriate cortex and generates an event-related potential (ERP) called the sustained posterior negativity (SPN). Previous work has found that the SPN is robust to experimental manipulations of task, spatial attention, and memory load. In the current study, we investigated whether the SPN is also robust to alcohol-induced changes in mental state. A pilot experiment (N = 13) found that alcohol unexpectedly increased SPN amplitude. We followed this unexpected result with two new experiments on separate groups, using an alcohol challenge paradigm...

BACKGROUND: Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths...

BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals from the same joint remains challenging due to their similar brain spatial distribution. NEW METHOD: We designed experiments involving three motor imagery tasks-wrist extension, wrist flexion, and wrist abduction-with six participants...

Deep cascaded networks have been extensively studied and applied to accelerate Magnetic Resonance Imaging (MRI) and have shown promising results. Most existing works employ a large cascading number for the sake of superior performances. However, due to the lack of proper guidance, the reconstruction performance can easily reach a plateau and even face degradation if simply increasing the cascading number. In this paper, we aim to boost the reconstruction performance from a novel perspective by proposing a parallel architecture called DIRECTION that fully exploits the guiding value of the reconstruction residual of each subnetwork...

The spectral database-based mass spectrometry (MS) matching strategy is versatile for structural annotating in ingredient fluctuation profiling mediated by external interferences. However, the systematic variability of MS pool attributable to aliasing peaks and inadequacy of present spectral database resulted in a substantial metabolic feature depletion. An amended procedure termed multiple-charges overlap peaks extraction algorithm (MCOP) was proposed involving identifying collision-trigged dissociation precursor ions through iteratively matching mass features of fragmentations to expand the spectral reference library...

This study examined the impact of brief mindfulness meditation (BMM) training on attention function and dispositional mindfulness in young males. 126 male participants aged 18-26 from the security industry were recruited, with 66 participants (M = 22.84, SD = 2.41) undergoing 4-week mindfulness meditation training and 60 participants (M = 23.07, SD = 2.29) in the active control group. The intervention was integrated into the participants' schedules. Measures included Five Facets Mindfulness Questionnaires (FFMQ), concentration and assignment attention tasks, Attention Network Test (ANT), and saliva cortisol concentration...

Water resources are constantly threatened by pollution of potentially toxic elements (PTEs). In efforts to monitor and mitigate PTEs pollution in water resources, machine learning (ML) algorithms have been utilized to predict them. However, review studies have not paid attention to the suitability of input variables utilized for PTE prediction. Therefore, the present review analyzed studies that employed three ML algorithms: MLP-NN (multilayer perceptron neural network), RBF-NN (radial basis function neural network), and ANFIS (adaptive neuro-fuzzy inference system) to predict PTEs in water...

BACKGROUND: Vigilance ability refers to the accuracy and speed with which a person performs a cognitive-motor task, either voluntarily (endogenous mode) or following a warning stimulus (exogenous mode). In the context of a force production task, our study focuses on the impact of the states of vigilance by proposing an original approach that allows distinguishing between good (inlier) and poor (outlier) participants. We assume that the use of an external signal and duration of the temporal preparation (foreperiod) increase the speed and the precision of motor responses...

BACKGROUND: Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. Yet, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. The current study aims to identify infant resting state functional connectivity (rsFC) associated with both parent-report and observed behavioral estimates of infant novelty-evoked distress. METHODS: Using data from the Origins of Infant Temperament (OIT) study which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress...