Deep active learning with high structural discriminability for molecular mutagenicity prediction.

The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecules. However, experimental mutagenicity testing can be time-consuming and costly.

EEG-Based Feature Classification Combining 3D-Convolutional Neural Networks with Generative Adversarial Networks for Motor Imagery.

Background: The adoption of convolutional neural networks (CNNs) for decoding electroencephalogram (EEG)-based motor imagery (MI) in brain-computer interfaces has significantly increased recently. The effective extraction of motor imagery features is vital due to the variability among individuals and temporal states.

Methods: This study introduces a novel network architecture, 3D-convolutional neural network-generative adversarial network (3D-CNN-GAN), for decoding both within-session and cross-session motor imagery.

A regression model combined convolutional neural network and recurrent neural network for electroencephalogram-based cross-subject fatigue detection.

Fatigue, one of the most important factors affecting road safety, has attracted many researchers' attention. Most existing fatigue detection methods are based on feature engineering and classification models. The feature engineering is greatly influenced by researchers' domain knowledge, which will lead to a poor performance in fatigue detection, especially in cross-subject experiment design.

Long Non-Coding RNA Mir17hg Positively Regulates Melanogenesis by Inhibiting TGFβ Receptor 2 under Psychological Stress.

Vitiligo is a common skin depigmentation disorder characterized by the patchy loss of skin color. Nowadays, it is recognized as being correlated with multiple genetic factors as well as the psychological conditions of individuals. Long noncoding RNAs have been reported to underlie the pathogenesis of vitiligo; however, the role of long noncoding RNAs in the stress-related depigmentation process remains largely unknown.

Temporal-frequency-phase feature classification using 3D-convolutional neural networks for motor imagery and movement.

Recently, convolutional neural networks (CNNs) have been widely applied in brain-computer interface (BCI) based on electroencephalogram (EEG) signals. Due to the subject-specific nature of EEG signal patterns and the multi-dimensionality of EEG features, it is necessary to employ appropriate feature representation methods to enhance the decoding accuracy of EEG. In this study, we proposed a method for representing EEG temporal, frequency, and phase features, aiming to preserve the multi-domain information of EEG signals.

A regression method for EEG-based cross-dataset fatigue detection.

Fatigue is dangerous for certain jobs requiring continuous concentration. When faced with new datasets, the existing fatigue detection model needs a large amount of electroencephalogram (EEG) data for training, which is resource-consuming and impractical. Although the cross-dataset fatigue detection model does not need to be retrained, no one has studied this problem previously.

Chemometric Discrimination of Boiss. et Huet and L. via Their Metabolic Profiling, Antioxidative, and Hypoglycemic Activities.

Boiss. et Huet (CG) and L. (CI) are widely used as the main raw material of functional food with hepatoprotective and hypoglycemic effects.

Cortical connectomic mediations on gamma band synchronization in schizophrenia.

Aberrant gamma frequency neural oscillations in schizophrenia have been well demonstrated using auditory steady-state responses (ASSR). However, the neural circuits underlying 40 Hz ASSR deficits in schizophrenia remain poorly understood. Sixty-six patients with schizophrenia spectrum disorders and 85 age- and gender-matched healthy controls completed one electroencephalography session measuring 40 Hz ASSR and one imaging session for resting-state functional connectivity (rsFC) assessments.

Research on improved intestinal image classification for LARS based on ResNet.

Low anterior rectal resection is an effective way to treat rectal cancer at present, but it is easy to cause low anterior resection syndrome after surgery; so, a comprehensive diagnosis of defecation and pelvic floor function must be carried out. There are few studies on the classification of diagnoses in the field of intestinal diseases. In response to these outstanding problems, this research will focus on the design of the intestinal function diagnosis system and the image processing and classification algorithm of the intestinal wall to verify an efficient fusion method, which can be used to diagnose the intestinal diseases in clinical medicine.

Effects of soil fauna on litter decomposition in Chinese forests: a meta-analysis.

Litter quality and climate have been presumed to be the dominant factors regulating litter decomposition rates on broad spatial scales. However, the role of soil fauna on litter decomposition is poorly understood, despite the fact that it could strongly influence decomposition by fragmentation and subsequent modification of the activities of microorganisms.In this study, we carried out a meta-analysis on the effects of soil fauna on litter decomposition rates in Chinese forests, ranging from boreal to tropical forests, based on data from 20 studies.

Tube wall delamination engineering induces photogenerated carrier separation to achieve photocatalytic performance improvement of tubular g-CN.

Morphology adjustment is a feasible method to change the physicochemical properties of photocatalysts. The issue that excessively thick tube wall of tubular g-CN is not conducive to the electron migration from inside to the surface thus inhibiting the separation of photogenerated carriers has always been ignored. Potassium ions were used to regulate the structure of the tubular supramolecular precursor by breaking hydrogen bonds, thereby promoting the synthesis of delaminated laminar tubular g-CN (K-CN), which not only shortened the transfer distance of photogenerated electrons but also provided abundant reaction active sites.

Diagnosis analysis of rectal function through using ensemble empirical mode decomposition-deep belief networks algorithm.

The rectal motility function can reflect a person's rectal health status. To diagnose the rectal motility function after artificial anal sphincter implantation, this paper proposes a rectal function diagnosis model based on ensemble empirical mode decomposition-deep belief networks (EEMD-DBNs). Because of the rectal pressure signals that are unstable and subjected to noise interferences, an EEMD framework based on EMD, which can reduce the effect of signal modal mixing, is proposed.

Exaggerated cortical representation of speech in older listeners: mutual information analysis.

Aging is associated with an exaggerated representation of the speech envelope in auditory cortex. The relationship between this age-related exaggerated response and a listener's ability to understand speech in noise remains an open question. Here, information-theory-based analysis methods are applied to magnetoencephalography recordings of human listeners, investigating their cortical responses to continuous speech, using the novel nonlinear measure of phase-locked mutual information between the speech stimuli and cortical responses.

Advances in the application, toxicity and degradation of carbon nanomaterials in environment: A review.

Carbon nanomaterials (CNMs) are novel nanomaterials with excellent physicochemical properties, which are widely used in biomedicine, energy and sensing. Besides, CNMs also play an important role in environmental pollution control, which can absorb heavy metals, antibiotics and harmful gases. However, CNMs are inevitably entering the environment while they are rapidly developing.

Mutual information analysis of neural representations of speech in noise in the aging midbrain.

Younger adults with normal hearing can typically understand speech in the presence of a competing speaker without much effort, but this ability to understand speech in challenging conditions deteriorates with age. Older adults, even with clinically normal hearing, often have problems understanding speech in noise. Earlier auditory studies using the frequency-following response (FFR), primarily believed to be generated by the midbrain, demonstrated age-related neural deficits when analyzed with traditional measures.

Adaptive Efficient Coding of Correlated Acoustic Properties.

Natural sounds such as vocalizations often have covarying acoustic attributes, resulting in redundancy in neural coding. The efficient coding hypothesis proposes that sensory systems are able to detect such covariation and adapt to reduce redundancy, leading to more efficient neural coding. Recent psychoacoustic studies have shown the auditory system can rapidly adapt to efficiently encode two covarying dimensions as a single dimension, following passive exposure to sounds in which temporal and spectral attributes covaried in a correlated fashion.

Research of improved fast independent component analysis algorithm in rectal diagnosis signal preprocessing.

With the maturity of artificial organ technology, the use of artificial anal sphincters was proposed to help patients who suffered anal incontinence for various causes reconstruct rectal perception, monitor rectal pressure and diagnose rectal lesion. Aimed at the lack of signal pretreatment in the artificial anal sphincter system, we find a way to solve it, that is, the multi-dimensional reconstruction of the intestinal one-dimensional pressure signal sequence by using phase space reconstruction, and the separation of the reconstructed signal by using the improved fast independent component analysis algorithm. We did some relevant experiments, further extracted the features of the isolated rectal signal, and used back propagation neural network to diagnose the rectal lesions.

Implicit Memory for Complex Sounds in Higher Auditory Cortex of the Ferret.

Responses of auditory cortical neurons encode sound features of incoming acoustic stimuli and also are shaped by stimulus context and history. Previous studies of mammalian auditory cortex have reported a variable time course for such contextual effects ranging from milliseconds to minutes. However, in secondary auditory forebrain areas of songbirds, long-term stimulus-specific neuronal habituation to acoustic stimuli can persist for much longer periods of time, ranging from hours to days.

New KF-PP-SVM classification method for EEG in brain-computer interfaces.

Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated.

Assessment and in vitro experiment of artificial anal sphincter system based on rebuilding the rectal sensation function.

In this paper, a novel artificial anal sphincter (AAS) system based on rebuilding the rectal sensation function is proposed to treat human fecal incontinence. The executive mechanism of the traditional AAS system was redesigned and integrated for a simpler structure and better durability. The novel executive mechanism uses a sandwich structure to simulate the basic function of the natural human anal sphincter.

Electromagnetic assessment of embedded micro antenna for a novel sphincter in the human body.

This paper presents a wireless, miniaturized, bi-directional telemetric artificial anal sphincter system that can be used for controlling patients' anal incontinence. The artificial anal sphincter system is mainly composed of an executive mechanism, a wireless power supply system and a wireless communication system. The wireless communication system consists of an internal RF transceiver, an internal RF antenna, a data transmission pathway, an external RF antenna and an external RF control transceiver.

Electromagnetic effects on the biological tissue surrounding a transcutaneous transformer for an artificial anal sphincter system.

This paper reports on the electromagnetic effects on the biological tissue surrounding a transcutaneous transformer for an artificial anal sphincter. The coupling coils and human tissues, including the skin, fat, muscle, liver, and blood, were considered. Specific absorption rate (SAR) and current density were analyzed by a finite-length solenoid model.

A new type of medical micropump for an endoscopic robot.

Researchers have developed a new type of medical micropump for an endoscopic robot, which is driven by a linear actuator based on a direct current (DC) motor. This micropump consists of two active one-way valves and a cylindrical air drum. The overall size of the pump prototype is 12.

Biomechanical modeling of the rectum for the design of a novel artificial anal sphincter.

This paper discusses biomechanical issues that are related to the option of a novel artificial anal sphincter around the human rectum. The prosthesis consists of a compression cuff system inside and a reservoir cuff system outside, which is placed around the debilitated sphincter muscle. The micropump shifts fluid between the cuffs and thus takes over the expansion and compression function of the sphincter muscle.

Modeling of human colonic blood flow for a novel artificial anal sphincter system.

A novel artificial anal sphincter system has been developed to simulate the normal physiology of the human anorectum. With the goal of engineering a safe and reliable device, the model of human colonic blood flow has been built and the relationship between the colonic blood flow rate and the operating occlusion pressure of the anorectum is achieved. The tissue ischemia is analyzed based on constitutive relations for human anorectum.