Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness.

Objective: This study aimed to explore differences in sleep electroencephalogram (EEG) patterns in individuals with prolonged disorders of consciousness, utilizing polysomnography (PSG) to assist in distinguishing between the vegetative state (VS)/unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS), thereby reducing misdiagnosis rates and enhancing the quality of medical treatment.

Methods: A total of 40 patients with prolonged disorders of consciousness (pDOC; 27 patients in the VS/UWS and 13 in the MCS) underwent polysomnography. We analyzed differential EEG indices between VS/UWS and MCS groups and performed correlation analyses between these indices and the Coma Recovery Scale-Revised (CRS-R) scores.

[An emerging major: brain-computer interface major].

Brain-computer interface (BCI) is a revolutionizing technology that disrupts traditional human-computer interaction by establishing direct communication and control between the brain and computer, bypassing the peripheral nervous and muscular systems. With the rapid advancement of BCI technology, growing application demands, and an increasing need for specialized BCI professionals, a new academic major-BCI major-has gradually emerged. However, few studies to date have discussed the interdisciplinary nature and training framework of this emerging major.

RECK as a Potential Crucial Molecule for the Targeted Treatment of Sepsis.

Reversion inducing cysteine rich protein with kazal motifs (RECK), a Kazal motif-containing protein, regulates pro-inflammatory cytokines production, migration of inflammatory cells, vascular endothelial growth factor (VEGF) and Wnt pathways and plays critical roles in septic inflammatory storms and vascular endothelial dysfunction. Recently, RECK has been defined as the negative regulator of adisintegrin and metalloproteinases (ADAMs) and matrix metalloproteinases (MMPs), which are both membrane "molecular scissors" and aggravate the poor prognosis of sepsis. To better understand the roles of RECK and the related mechanisms, we make here a systematic and in-depth review of RECK.

Association of tea consumption with life expectancy in US adults.

Objective: The association of tea consumption with life expectancy in US adults remains unclear. This study aimed to evaluate the correlation between tea consumption and life expectancy among US adults.

Methods: Tea consumption records and available mortality data from National Health and Nutrition Examination Survey 2001 to 2018 for adults ≥ 20 years of age were used (n = 43,276).

PbAGL7-PbNAC47-PbMYB73 complex coordinately regulates PbC3H1 and PbHCT17 to promote the lignin biosynthesis in stone cells of pear fruit.

Lignification of the cell wall in pear (Pyrus) fruit results in the formation of stone cells, which affects the texture and quality of the fruit. However, it is still unclear that how different transcription factors (TFs) work together to coordinate the synthesis and deposition of lignin. Here, we examined the transcriptome of pear varieties with different stone cell contents and found a key TF (PbAGL7) that can promote the increase of stone cell contents and secondary cell wall thicknesses.

Real-Time Attention Regulation and Cognitive Monitoring Using a Wearable EEG-Based BCI.

Objective: Attention regulation is an essential ability in daily life that affects learning and work efficiency and is closely related to mental health. The effectiveness of brain-computer interface (BCI) systems in attention regulation has been proven, but most of these systems rely on bulky and expensive equipment and are still in the experimental stage. This study proposes a wearable BCI system for real-time attention regulation and cognitive monitoring.

SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection.

Emotional recognition is highly important in the field of brain-computer interfaces (BCIs). However, due to the individual variability in electroencephalogram (EEG) signals and the challenges in obtaining accurate emotional labels, traditional methods have shown poor performance in cross-subject emotion recognition. In this study, we propose a cross-subject EEG emotion recognition method based on a semi-supervised fine-tuning self-supervised graph attention network (SFT-SGAT).

Assessing Consciousness in Patients With Disorders of Consciousness Using a Musical Stimulation Paradigm and Verifiable Criteria.

Numerous studies have shown that musical stimulation can activate corresponding functional brain areas. Electroencephalogram (EEG) activity during musical stimulation can be used to assess the consciousness states of patients with disorders of consciousness (DOC). In this study, a musical stimulation paradigm and verifiable criteria were used for consciousness assessment.

Spindle Detection Based on Elastic Time Window and Spatial Pyramid Pooling.

Background: Sleep spindles have emerged as valuable biomarkers for assessing cognitive abilities and related disorders, underscoring the importance of their detection in clinical research. However, template matching-based algorithms using fixed templates may not be able to fully adapt to spindles of different durations. Moreover, inspired by the multiscale feature extraction of images, the use of multiscale feature extraction methods can be used to better adapt to spindles of different frequencies and durations.

Managing Cardiovascular Risk in Patients with Autoimmune Diseases: Insights from a Nutritional Perspective.

Purpose Of Review: Autoimmune diseases manifest as an immune system response directed against endogenous antigens, exerting a significant influence on a substantial portion of the population. Notably, a leading contributor to morbidity and mortality in this context is cardiovascular disease (CVD). Intriguingly, individuals with autoimmune disorders exhibit a heightened prevalence of CVD compared to the general population.

A Hybrid BCI Integrating EEG and Eye-Tracking for Assisting Clinical Communication in Patients With Disorders of Consciousness.

Assessing communication abilities in patients with disorders of consciousness (DOCs) is challenging due to limitations in the behavioral scale. Electroencephalogram-based brain-computer interfaces (BCIs) and eye-tracking for detecting ocular changes can capture mental activities without requiring physical behaviors and thus may be a solution. This study proposes a hybrid BCI that integrates EEG and eye tracking to facilitate communication in patients with DOC.

Individualized music induces theta-gamma phase-amplitude coupling in patients with disorders of consciousness.

Objective: This study aimed to determine whether patients with disorders of consciousness (DoC) could experience neural entrainment to individualized music, which explored the cross-modal influences of music on patients with DoC through phase-amplitude coupling (PAC). Furthermore, the study assessed the efficacy of individualized music or preferred music (PM) versus relaxing music (RM) in impacting patient outcomes, and examined the role of cross-modal influences in determining these outcomes.

Methods: Thirty-two patients with DoC [17 with vegetative state/unresponsive wakefulness syndrome (/UWS) and 15 with minimally conscious state (MCS)], alongside 16 healthy controls (HCs), were recruited for this study.

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network.

Objective: Attention decoding plays a vital role in daily life, where electroencephalography (EEG) has been widely involved. However, training a universally effective model for everyone is impractical due to substantial interindividual variability in EEG signals. To tackle the above challenge, we propose an end-to-end brain-computer interface (BCI) framework, including temporal and spatial one-dimensional (1D) convolutional neural network and domain-adversarial training strategy, namely DA-TSnet.

Design and Experiment of an Unoccupied Control System for a Tracked Grain Vehicle.

In order to enhance crop harvesting efficiency, an automatic-driving tracked grain vehicle system was designed. Based on the harvester chassis, we designed the mechanical structure of a tracked grain vehicle with a loading capacity of 4.5 m and a grain unloading hydraulic system.

Nerolidol reduces depression-like behavior in mice and suppresses microglia activation by down-regulating DNA methyltransferase 1.

Modern medicine has unveiled that essential oil made from Aquilaria possesses sedative and hypnotic effects. Among the chemical components in Aquilaria, nerolidol, a natural sesquiterpene alcohol, has shown promising effects. This study aimed to unravel the potential of nerolidol in treating depression.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC.

Impact of anemia on clinical outcomes in patients with acute heart failure: A systematic review and meta-analysis.

Anemia and acute heart failure (AHF) frequently coexist. Several published studies have investigated the association of anemia with all-cause mortality and all-cause heart failure events in AHF patients, but their findings remain controversial. This study is intended to evaluate the relationship between anemia and AHF.

RpS25 is required for sperm elongation and individualization during Drosophila spermatogenesis.

Ribosomal protein 25 (RPS25) has been related to male fertility diseases in humans. However, the role of RPS25 in spermatogenesis has yet to be well understood. RpS25 is evolutionarily highly conserved from flies to humans through sequence alignment and phylogenetic tree construction.

Few-shot EEG sleep staging based on transductive prototype optimization network.

Electroencephalography (EEG) is a commonly used technology for monitoring brain activities and diagnosing sleep disorders. Clinically, doctors need to manually stage sleep based on EEG signals, which is a time-consuming and laborious task. In this study, we propose a few-shot EEG sleep staging termed transductive prototype optimization network (TPON) method, which aims to improve the performance of EEG sleep staging.