A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

High accuracy decoding of electroencephalogram (EEG) signal is still a major challenge that can hardly be solved in the design of an effective motor imagery-based brain-computer interface (BCI), especially when the signal contains various extreme artifacts and outliers arose from data loss. The conventional process to avoid such cases is to directly reject the entire severely contaminated EEG segments, which leads to a drawback that the BCI has no decoding results during that certain period. In this study, a novel decoding scheme based on the combination of Lomb-Scargle periodogram (LSP) and deep belief network (DBN) was proposed to recognize the incomplete motor imagery EEG. Particularly, instead of discarding the entire segment, two forms of data removal were adopted to eliminate the EEG portions with extreme artifacts and data loss. The LSP was utilized to steadily extract the power spectral density (PSD) features from the incomplete EEG constructed by the remaining portions. A DBN structure based on the restricted Boltzmann machine (RBM) was exploited and optimized to perform the classification task. Various comparative experiments were conducted and evaluated on simulated signal and real incomplete motor imagery EEG, including the comparison of three PSD extraction methods (fast Fourier transform, Welch and LSP) and two classifiers (DBN and support vector machine, SVM). The results demonstrate that the LSP can estimate relative robust PSD features and the proposed scheme can significantly improve the decoding performance for the incomplete motor imagery EEG. This scheme can provide an alternative decoding solution for the motor imagery EEG contaminated by extreme artifacts and data loss. It can be beneficial to promote the stability, smoothness and maintain consecutive outputs without interruption for a BCI system that is suitable for the online and long-term application

Heat sealable regenerated cellulose films enabled by zein coating for sustainable food packaging

The development of green packaging materials is requested due to the growing concerns about plastic waste. As the most abundant natural polymer on earth, cellulose can be dissolved and regenerated to make transparent films. However, cellulose is not a thermoplastic, so cellulose films are usually sealed by an adhesive for packaging applications. Herein, this study aimed to endow regenerated cellulose (RC) films with heat sealability by coating a layer of zein, and the mechanical and barrier properties of the composite cellulose/zein films were characterized. The results revealed that, with a thin zein coating, all the composite films were able to be sealed by a tabletop impulse sealer without the need for high temperature or high pressure and showed larger tensile strain and better water vapor and oxygen barrier properties compared to the RC films. Moreover, it was worth noting that the blueberries packed in the heat-sealed cellulose/zein bags were protected from oxidation and spoilage during a 12-day storage period and were comparable to the ones packed by Ziploc®. Thus, this work demonstrates a facile way to fabricate cellulose-based packaging materials that are heat sealable and have potential applications in sustainable food packaging

Physiological Signal-Based Method for Measurement of Pain Intensity

The standard method for prediction of the absence and presence of pain has long been self-report. However, for patients with major cognitive or communicative impairments, it would be better if clinicians could quantify pain without having to rely on the patient's self-description. Here, we present a newly pain intensity measurement method based on multiple physiological signals, including blood volume pulse (BVP), electrocardiogram (ECG), and skin conductance level (SCL), all of which are induced by external electrical stimulation. The proposed pain prediction system consists of signal acquisition and preprocessing, feature extraction, feature selection and feature reduction, and three types of pattern classifiers. Feature extraction phase is devised to extract pain-related characteristics from short-segment signals. A hybrid procedure of genetic algorithm-based feature selection and principal component analysis-based feature reduction was established to obtain high-quality features combination with significant discriminatory information. Three types of classification algorithms—linear discriminant analysis, k-nearest neighbor algorithm, and support vector machine—are adopted during various scenarios, including multi-signal scenario, multi-subject and between-subject scenario, and multi-day scenario. The classifiers gave correct classification ratios much higher than chance probability, with the overall average accuracy of 75% above for four pain intensity. Our experimental results demonstrate that the proposed method can provide an objective and quantitative evaluation of pain intensity. The method might be used to develop a wearable device that is suitable for daily use in clinical settings

Single-nucleus transcriptome analysis reveals transcriptional profiles of circadian clock and pain related genes in human and mouse trigeminal ganglion

IntroductionClinical studies have revealed the existence of circadian rhythms in pain intensity and treatment response for chronic pain, including orofacial pain. The circadian clock genes in the peripheral ganglia are involved in pain information transmission by modulating the synthesis of pain mediators. However, the expression and distribution of clock genes and pain-related genes in different cell types within the trigeminal ganglion, the primary station of orofacial sensory transmission, are not yet fully understood.MethodsIn this study, data from the normal trigeminal ganglion in the Gene Expression Omnibus (GEO) database were used to identify cell types and neuron subtypes within the human and mouse trigeminal ganglion by single nucleus RNA sequencing analysis. In the subsequent analyses, the distribution of the core clock genes, pain-related genes, and melatonin and opioid-related genes was assessed in various cell clusters and neuron subtypes within the human and mouse trigeminal ganglion. Furthermore, the statistical analysis was used to compare the differences in the expression of pain-related genes in the neuron subtypes of trigeminal ganglion.ResultsThe present study provides comprehensive transcriptional profiles of core clock genes, pain-related genes, melatonin-related genes, and opioid-related genes in different cell types and neuron subtypes within the mouse and human trigeminal ganglion. A comparative analysis of the distribution and expression of the aforementioned genes was conducted between human and mouse trigeminal ganglion to investigate species differences.DiscussionOverall, the results of this study serve as a primary and valuable resource for exploring the molecular mechanisms underlying oral facial pain and pain rhythms

Impacts of Cropping Systems on Aggregates Associated Organic Carbon and Nitrogen in a Semiarid Highland Agroecosystem.

The effect of cropping system on the distribution of organic carbon (OC) and nitrogen (N) in soil aggregates has not been well addressed, which is important for understanding the sequestration of OC and N in agricultural soils. We analyzed the distribution of OC and N associated with soil aggregates in three unfertilized cropping systems in a 27-year field experiment: continuously cropped alfalfa, continuously cropped wheat and a legume-grain rotation. The objectives were to understand the effect of cropping system on the distribution of OC and N in aggregates and to examine the relationships between the changes in OC and N stocks in total soils and in aggregates. The cropping systems increased the stocks of OC and N in total soils (0-40 cm) at mean rates of 15.6 g OC m-2 yr-1 and 1.2 g N m-2 yr-1 relative to a fallow control. The continuous cropping of alfalfa produced the largest increases at the 0-20 cm depth. The OC and N stocks in total soils were significantly correlated with the changes in the >0.053 mm aggregates. 27-year of cropping increased OC stocks in the >0.053 mm size class of aggregates and N stocks in the >0.25 mm size class but decreased OC stocks in the 0.25 mm aggregate size class accounted for more than 97% of the total increases in the continuous wheat and the legume-grain rotation systems. These results suggested that long-term cropping has the potential to sequester OC and N in soils and that the increases in soil OC and N stocks were mainly due to increases associated with aggregates >0.053 mm

Non-coding RNA methylation modifications in hepatocellular carcinoma: interactions and potential implications

Abstract RNA methylation modification plays a crucial role as an epigenetic regulator in the oncogenesis of hepatocellular carcinoma (HCC). Numerous studies have investigated the molecular mechanisms underlying the methylation of protein-coding RNAs in the progression of HCC. Beyond their impact on mRNA, methylation modifications also influence the biological functions of non-coding RNAs (ncRNAs). Here, we present an advanced and comprehensive overview of the interplay between methylation modifications and ncRNAs in HCC, with a specific focus on their potential implications for the tumor immune microenvironment. Moreover, we summarize promising therapeutic targets for HCC based on methylation-related proteins. In the future, a more profound investigation is warranted to elucidate the effects of ncRNA methylation modifications on HCC pathogenesis and devise valuable intervention strategies. Video Abstrac

PTBP1 plays an important role in the development of gastric cancer

Abstract Background Polypyrimidine tract binding protein 1 (PTBP1) has been found to play an important role in the occurrence and development of various tumors. At present, the role of PTBP1 in gastric cancer (GC) is still unknown and worthy of further investigation. Methods We used bioinformatics to analyze the expression of PTBP1 in patients with GC. Cell proliferation related experiments were used to detect cell proliferation after PTBP1 knockdown. Skeleton staining, scanning electron microscopy and transmission electron microscopy were used to observe the changes of actin skeleton. Proliferation and actin skeleton remodeling signaling pathways were detected by Western Blots. The relationship between PTBP1 and proliferation of gastric cancer cells was further detected by subcutaneous tumor transplantation. Finally, tissue microarray data from clinical samples were used to further explore the expression of PTBP1 in patients with gastric cancer and its correlation with prognosis. Results Through bioinformatics studies, we found that PTBP1 was highly expressed in GC patients and correlated with poor prognosis. Cell proliferation and cycle analysis showed that PTBP1 down-regulation could significantly inhibit cell proliferation. The results of cell proliferation detection related experiments showed that PTBP1 down-regulation could inhibit the division and proliferation of GC cells. Furthermore, changes in the morphology of the actin skeleton of cells showed that PTBP1 down-regulation inhibited actin skeletal remodeling in GC cells. Western Blots showed that PTBP1 could regulate proliferation and actin skeleton remodeling signaling pathways. In addition, we constructed PTBP1 Cas9-KO mouse model and performed xenograft assays to further confirm that down-regulation of PTBP1 could inhibit the proliferation of GC cells. Finally, tissue microarray was used to further verify the close correlation between PTBP1 and poor prognosis in patients with GC. Conclusions Our study demonstrates for the first time that PTBP1 may affect the proliferation of GC cells by regulating actin skeleton remodeling. In addition, PTBP1 is closely related to actin skeleton remodeling and proliferation signaling pathways. We suppose that PTBP1 might be a potential target for the treatment of GC. Graphical abstrac