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OBJECTIVE: Intracranial electroencephalogram (iEEG) signals are generally recorded using multiple channels, and channel selection is therefore a significant means in studying iEEG-based seizure prediction. For n channels, 2n-1 channel cases can be generated for selection. However, by this means, an increase in n can cause an exponential increase in computational consumption, which may result in a failure of channel selection when n is too large. Hence, it is necessary to explore reasonable channel selection strategies under the premise of controlling computational consumption and ensuring high classification accuracy. Given this, we propose a novel method of channel reordering strategy combined with dual CNN-LSTM for effectively predicting seizures. METHOD: First, for each patient with n channels, interictal and preictal iEEG samples from each single channel are input into the CNN-LSTM model for classification. Then, the F1-score of each single channel is calculated, and the channels are reordered in descending order according to the size of F1-scores (channel reordering strategy). Next, iEEG signals with an increasing number of channels are successively fed into the CNN-LSTM model for classification again. Finally, according to the classification results from n channel cases, the channel case with the highest classification rate is selected. RESULTS: Our method is evaluated on the three iEEG datasets: the Freiburg, the SWEC-ETHZ and the American Epilepsy Society Seizure Prediction Challenge (AES-SPC). At the event-based level, the sensitivities of 100%, 100% and 90.5%, and the false prediction rates (FPRs) of 0.10/h, 0/h and 0.47/h, are achieved for the three datasets, respectively. Moreover, compared to an unspecific random predictor, our method also shows a better performance for all patients and dogs from the three datasets. At the segment-based level, the sensitivities-specificities-accuracies-AUCs of 88.1%-94.0%-93.5%-0.9101, 99.1%-99.7%-99.6%-0.9935, and 69.2%-79.9%-78.2%-0.7373, are attained for the three datasets, respectively. CONCLUSION: Our method can effectively predict seizures and address the challenge of an excessive number of channels during channel selection.
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Cerebral small vessel disease (CSVD) is increasingly being recognized as a leading contributor to cognitive impairment in the elderly. However, there is a lack of effective preventative or therapeutic options for CSVD. In this exploratory study, we investigated the interplay between neuroinflammation and CSVD pathogenesis as well as the cognitive performance, focusing on NLRP3 signaling as a new therapeutic target. Spontaneously hypertensive stroke-prone (SHRSP) rats served as a CSVD model. We found that SHRSP rats showed decline in learning and memory abilities using morris water maze test. Activated NLRP3 signaling and an increased expression of the downstream pro-inflammatory factors, including IL (interleukin)-6 and tumor necrosis factor α were determined. We also observed a remarkable increase in the production of pyroptosis executive protein gasdermin D, and elevated astrocytic and microglial activation. In addition, we identify several neuropathological hallmarks of CSVD, including blood-brain barrier breakdown, white matter damage, and endothelial dysfunction. These results were in correlation with the activation of NLRP3 inflammasome. Thus, our findings reveal that the NLRP3-mediated inflammatory pathway could play a central role in the pathogenesis of CSVD, presenting a novel target for potential CSVD treatment.
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Enfermedades de los Pequeños Vasos Cerebrales , Modelos Animales de Enfermedad , Inflamasomas , Proteína con Dominio Pirina 3 de la Familia NLR , Ratas Endogámicas SHR , Animales , Enfermedades de los Pequeños Vasos Cerebrales/metabolismo , Enfermedades de los Pequeños Vasos Cerebrales/patología , Proteína con Dominio Pirina 3 de la Familia NLR/metabolismo , Ratas , Inflamasomas/metabolismo , Masculino , Enfermedades Neuroinflamatorias/metabolismo , Microglía/metabolismo , Barrera Hematoencefálica/metabolismo , Barrera Hematoencefálica/patología , Transducción de Señal/fisiologíaRESUMEN
Pathogenic Aeromonas spp. are the etiological agents of Motile Aeromonas Septicemia (MAS). This study aimed to identify the pathogen of diseased tadpoles (Quasipaa spinosa) and the antibiotic-resistance characteristics of this bacterium. A Gram-negative bacterium, named strain QST31, was isolated from the ascites of diseased tadpoles and was identified as Aeromonas media based on physiological and biochemical tests, as well as molecular identification. Artificial infection experiments showed that strain QST31 was highly virulent to tadpoles, with an LC50 of 2.56 × 107 CFU/mL. The antimicrobial susceptibility of strain QST31 was evaluated using the disk diffusion method, and the results indicated that strain QST31 was resistant to 28 antibacterial agents. In addition, the whole genome of strain QST31 was sequenced, and the presence of antimicrobial resistance genes, integron, and transposon was investigated. Genes involved in adherence, hemolysis, type II secretion system (T2SS), T6SS, iron uptake system, and quorum sensing were identified in the genome of strain QST31. More than 12 antimicrobial resistance genes were predicted in the genome of strain QST31. Interestingly, a novel Tn7709 transposon harboring sul1, aadA16, catB3, blaOXA-21, aac(6')-IIa, and tet(A) genes was identified. In conclusion, this is the first report on the isolation and identification of pathogenic A. media with multidrug resistance genes from diseased tadpoles. The results revealed that preventing and controlling aquatic animal diseases caused by multidrug resistance A. media will be a huge challenge in the future.
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Aquatic fishes are threatened by the strong pathogenic bacterium Nocardia seriolae, which challenges the current prevention and treatment approaches. This study introduces luminogens with aggregation-induced emission (AIE) as an innovative and non-antibiotic therapy for N. seriolae. Specifically, the AIE photosensitizer, TTCPy-3 is employed against N. seriolae. We evaluated the antibacterial activity of TTCPy-3 and investigated the killing mechanism against N. seriolae, emphasizing its ability to aggregate within the bacterium and produce reactive oxygen species (ROS). TTCPy-3 could effectively aggregate in N. seriolae, generate ROS, and perform real-time imaging of the bacteria. A bactericidal efficiency of 100% was observed while concentrations exceeding 4 µM in the presence of white light irradiation for 10 min. In vivo, evaluation on zebrafish (Danio rerio) confirmed the superior therapeutic efficacy induced by TTCPy-3 to fight against N. seriolae infections. TTCPy-3 offers a promising strategy for treating nocardiosis of fish, paving the way for alternative treatments beyond traditional antibiotics and potentially addressing antibiotic resistance.
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Técnicas Biosensibles , Enfermedades de los Peces , Nocardiosis , Nocardia , Animales , Pez Cebra , Especies Reactivas de Oxígeno , Nocardiosis/tratamiento farmacológico , Nocardiosis/veterinaria , Nocardiosis/microbiología , Peces/microbiología , Enfermedades de los Peces/tratamiento farmacológico , Enfermedades de los Peces/microbiologíaRESUMEN
Agronomic traits are key components in variety protection, cultivar development, and the formulation of DUS (distinct, uniform, and stable) test guidelines. P. giganteus is an increasingly popular and commercially promising edible macrofungi. In this study, both mycelial performance and fruiting body characters of 15 Pleurotus giganteus strains were investigated. The temperature gradient culture test indicated that, although most of the strains achieved optimal mycelial growth between 24 and 28 °C, a statistical difference in mycelial growth rates and temperature adaptability among strains were found, supporting that this trait has the potential to be adopted as an indicator in distinguishing strains. In the fruiting performance tests, the coefficient of variation (CV) of tested traits ranged from 5.30% (pileus diameter) to 18.70% (individual mushroom weight). The mushroom yields ranged from 103.37 g/bag (strain No. 15) to 275.76 g/bag (strain No. 9). The large divergence observed in individual mushroom weight tested strains, ranging from 40.88 g to 78.39 g (with median between 37.69 and 79.395 g), make it highly selective and a potential indicator in variety development. Strain No. 9 had the advantages of forming larger, heavier fruiting bodies and a more obvious funnel shape, which also exhibited the highest biological efficiency (15.61%). The results suggested some morphological traits showed high variety difference, such as pileus diameter (55.75 mm to 66.48 mm), stipe length (92.59 mm to 177.51 mm), stipe diameter (16.14 mm to 23.52 mm), and pileus thickness (13.38 mm to 19.75 mm). In the cluster analysis, the tested strains were grouped into four clusters based on agronomic traits: cluster â comprised six strains (No. 6, No. 11, No. 8, No. 1, No. 14, and No. 9) with high mushroom yield; cluster â ¡ included four strains (No. 3, No. 10, No. 7, and No. 4) with large pileus diameter and short stipe; cluster â ¡I consisted of four strains (No. 5, No. 12, No. 13, and No. 15) with relatively lower yields; and cluster â £ included only strain No. 2 which was low in yield, individual mushroom weight, and biological efficiency, accompanied by smaller pileus size and shorter stipe. The results of the correlation analysis indicated three traits, including individual mushroom weight, stipe length, and pileus weight, were positively associated with high yield. This study suggested P. giganteus germplasm resources are of high abundance and their agronomic diversity is useful in distinguishing and developing different varieties. The findings of this work provide knowledge on the agronomic traits and cultivation performance of various P. giganteus strains, laying a foundation for the development of its DUS test guidelines and variety protection, as well as providing reference for the breeding and phenotype selection of high-quality cultivars.
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Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancer. Anti-PD-1/PD-L1 treatment for advanced TNBC is still limited to PD-L1-positive patients. Ataxia telangiectasia mutated (ATM) is a switch molecule for homologous recombination and repair. In this study, we found a significant negative correlation between ATM and PD-L1 in 4 TNBC clinical specimens by single-cell RNA sequencing (scRNA-seq), which was confirmed by immunochemical staining in 86 TNBC specimens. We then established ATM knockdown TNBC stable cell lines to perform in vitro studies and animal experiments, proving the negative regulation of PD-L1 by ATM via suppression of tumor necrosis factor-alpha (TNF-α), which was confirmed by cytokine array analysis of TNBC cell line and analysis of clinical specimens. We further found that ATM inhibits TNF-α via inactivating JNK/c-Jun by scRNA-seq, Western blot and luciferase reporter assays. Finally, we identified a negative correlation between changes in phospho-ATMS1981 and PD-L1 levels in TNBC post- and pre-neoadjuvant therapy. This study reveals a novel mechanism by which ATM negatively regulates PD-L1 by downregulating JNK/c-Jun/TNF-α in TNBC, shedding light on the wide application of immune checkpoint blockade therapy for treating multi-line-resistant TNBC.
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Ataxia Telangiectasia , Neoplasias de la Mama Triple Negativas , Animales , Humanos , Proteínas de la Ataxia Telangiectasia Mutada/genética , Proteínas de la Ataxia Telangiectasia Mutada/metabolismo , Antígeno B7-H1/metabolismo , Citocinas/metabolismo , Neoplasias de la Mama Triple Negativas/tratamiento farmacológico , Neoplasias de la Mama Triple Negativas/genética , Neoplasias de la Mama Triple Negativas/patología , Factor de Necrosis Tumoral alfa/metabolismoRESUMEN
Pleurotus giganteus is a commercially cultivated high-temperature mushroom. Investigating the molecular mechanism of fruiting body development will help us to better understand the regulation of substrates and energy in this process. However, little information has been reported on the development and nutrients of the P. giganteus fruiting body. In the present study, P. giganteus is cultivated in a climate chamber, and comparative transcriptome, proteome, and nutritional analysis of P. giganteus fruiting bodies were performed. Our results revealed that Cytochrome P450 monooxygenases and hydrophobin proteins play important roles during the differentiation in the elongation stage. Later, carbon metabolism dominate the fruiting body metabolism and genes related to the carbohydrate metabolic process, glycolytic process, and gluconeogenesis were up-regulated in the mature fruiting bodies. The up-regulation of carbohydrate substrates utilization CAZymes genes and inconsistent protein expression in pileus indicated a reverse transportation of mRNA from the fruiting body to vegetative mycelia. In addition, protein concentration in the pileus is higher than that in the stem, while the stem is the major nitrogen metabolic and amino acid synthetic location. The integrated transcriptomic, proteomic, and nutritional analysis indicated a two-way transportation of substrates and mRNAs in P. giganteus. Stem synthesizes amino acids and transported them to pileus with reducing sugars, while pileus induces the expression of substrate degradation mRNA according to the needs of growth and development and transports them in the other direction.
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Based on six offspring with different mitochondrial (M) and parental nuclear (N) genotypes, the multi-stage morphological characteristics and nuclear transcriptomes of Lentinula edodes were compared to investigate morphogenesis mechanisms during cultivation, the key reason for cultivar resistance to genotype changes, and regulation related to biparental role changes. Six offspring had specific transcriptomic data and morphological characteristics that were mainly regulated by the two parental nuclei, followed by the cytoplasm, at different growth stages. Importing a wild N genotype easily leads to failure or instability of fruiting; however, importing wild M genotypes may improve cultivars. Major facilitator superfamily (MFS) transporter genes encoding specific metabolites in spawns may play crucial roles in fruiting body formation. Pellets from submerged cultivation and spawns from sawdust substrate cultivation showed different carbon metabolic pathways, especially in secondary metabolism, degradation of lignin, cellulose and hemicellulose, and plasma membrane transport (mainly MFS). When the stage of small young pileus (SYP) was formed on the surface of the bag, the spawns inside were mainly involved in nutrient accumulation. Just broken pileus (JBP) showed a different expression of plasma membrane transporter genes related to intracellular material transport compared to SYP and showed different ribosomal proteins and cytochrome P450 functioning in protein biosynthesis and metabolism than near spreading pileus (NSP). Biparental roles mainly regulate offspring metabolism, growth, and morphogenesis by differentially expressing specific genes during different vegetative growth stages. Additionally, some genes encoding glycine-rich RNA-binding proteins, F-box, and folliculin-interacting protein repeat-containing proteins may be related to multi-stage morphogenesis. KEY POINTS: ⢠Replacement of nuclear genotype is not suitable for cultivar breeding of L. edodes. ⢠Some genes show a biparental role-divergent expression at mycelial growth stage. ⢠Transcriptomic changes of some sawdust substrate cultivation stages have been elucidated.
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With increasing acreage of cash crops, the use of their by-products as supplements for livestock feed becomes an important factor. Marigold (Tagetes erecta L.) account for more than half of the world's loose flower production. However, there is no precedent for the abundantly available marigold crop residue (MCR) being used as feed in agricultural production, probably because of its strong pungent taste. This study aimed to evaluate the biotransformation of the volatile organic compounds (VOCs) of MCR by mixed ensilage and assess its palatability by cattle. Caryophyllene, the most prevalent VOC in MCR, decreased by 29.11% (P < 0.05), 38.85% (P < 0.05), 37.15% (P < 0.05), and 28.36% (P < 0.05) ensilage with corn meal (CM), bran (BR), crop corn (CC), and straw (ST), respectively. The acetic acid content increased by 686.05% (P < 0.05), 1337.21% (P < 0.05), 1244.19% (P < 0.05), and 1795.34% (P < 0.05) after mixed ensilage with CM, BR, CC, and ST, respectively. The total amount of alcoholic VOCs followed an overall increasing trend during mixed storage and 10 new alcohols were obtained. Over seven days, feed intake of mixed ensilage MCR by cattle differed significantly (P < 0.05) among treatments compared with MCR and was highest in MCRCM. Combined with palatability trials, the best MCR feed intake was achieved with MCRCM. The findings shed light on how feed odor can be improved and how degradation of terpenes can be enhanced in practical applications by mixed ensilage.
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Calendula , Tagetes , Compuestos Orgánicos Volátiles , Animales , Bovinos , Tagetes/química , Compuestos Orgánicos Volátiles/análisis , Flores/química , Zea mays , Suplementos DietéticosRESUMEN
Networks play an important role in studying structure or functional connection of various brain areas, and explaining mechanism of emotion. However, there is a lack of comprehensive analysis among different construction methods nowadays. Therefore, this paper studies the impact of different emotions on connection of functional brain networks (FBNs) based on electroencephalogram (EEG). Firstly, we defined electrode node as brain area of vicinity of electrode to construct 32-node small-scale FBN. Pearson correlation coefficient (PCC) was used to construct correlation-based FBNs. Phase locking value (PLV) and phase synchronization index (PSI) were utilized to construct synchrony-based FBNs. Next, global properties and effects of emotion of different networks were compared. The difference of synchrony-based FBN concentrates in alpha band, and the number of differences is less than that of correlation-based FBN. Node properties of different small-scale FBNs have significant differences, offering a new basis for feature extraction of recognition regions in emotional FBNs. Later, we made partition of electrode nodes and 10 new brain areas were defined as regional nodes to construct 10-node large-scale FBN. Results show the impact of emotion on network clusters on the right forehead, and high valence enhances information processing efficiency of FBN by promoting connections in brain areas.
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Encéfalo , Emociones , Electroencefalografía/métodos , Mapeo Encefálico/métodos , ElectrodosRESUMEN
Grassland health refers to the degree to which the integrity of soil and ecological processes is maintained, which primarily reflects the health status and productivity of grasslands. Evaluating the degree of grassland health is vital for the sustainable develop of grasslands. There are many methods for evaluating grassland health, with advantages and disadvantages for each one. However, there is still a lack of systematic literature offering an overview of methods of grassland health assessment and their applicability. We summarized 10 methods of grassland health assessment, including vigor-organization-resilience (VOR) index evaluation model, condition-vigor-organization-resilience (CVOR) index evaluation model, principal component analysis method, analytic hierarchy process, cluster analysis method, grey relational analysis, pressure-state-response evaluation model, fuzzy comprehensive evaluation method, comprehensive evaluation model of grassland health, and evaluation model using remote sensing technology. The advantages, disadvantages, and applicability of these methods were discussed, aiming to provide scientific basis for selecting more suitable methods of grassland health assessment for different scenarios in the future.
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Pradera , Suelo , Tecnología de Sensores Remotos , EcosistemaRESUMEN
Anthracnose is a disease caused by Colletotrichum species. They are well known as major plant pathogens, and a black stem disease, specifically caused by Colletotrichum truncatum and primarily infecting sword bean (Canavalia gladiata), was observed in the Yunnan province, China. To aid disease management and to determine pathogenic characteristics, the species causing the leaf spot disease of hairy vetch was verified as C. truncatum. A sequence analysis of the ITS, ACT, GAPDH, and HIS3 genes was conducted, as well as morphological and cultural characteristics, to identify this Colletotrichum species, which has curved conidia. C. truncatum isolates from sword bean formed a distinctive group among Colletotrichum species, including those that infect other forage and field crops. Artificially inoculated sword bean seedlings showed typical symptoms of anthracnose, which were similar to field observations. To the best of our knowledge, this is the first report of C. truncatum causing black stem disease on sword beans in China.
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Due to the poor visibility of the deep-sea environment, acoustic signals are often collected and analyzed to explore the behavior of marine species. With the progress of underwater signal-acquisition technology, the amount of acoustic data obtained from the ocean has exceeded the limit that human can process manually, so designing efficient marine-mammal classification algorithms has become a research hotspot. In this paper, we design a classification model based on a multi-channel parallel structure, which can process multi-dimensional acoustic features extracted from audio samples, and fuse the prediction results of different channels through a trainable full connection layer. It uses transfer learning to obtain faster convergence speed, and introduces data augmentation to improve the classification accuracy. The k-fold cross-validation method was used to segment the data set to comprehensively evaluate the prediction accuracy and robustness of the model. The evaluation results showed that the model can achieve a mean accuracy of 95.21% while maintaining a standard deviation of 0.65%. There was excellent consistency in performance over multiple tests.
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Algoritmos , Redes Neurales de la Computación , Acústica , Humanos , SonidoRESUMEN
Most of the sequenced wood-rotting edible mushroom produce fruiting body at relatively low temperatures. Little information has been known about the high-temperature wood-rotting mushroom. Here, we performed de novo sequencing and assembly of the genome of a high-temperature edible mushroom Pleurotus giganteus from a monokaryotic strain zhudugu2 using the Illumina and Pac-Bio CLR sequencing technologies. P. giganteus, also known as Zhudugu in China, is a well-known culinary edible mushroom that has been widely distributed and cultivated in China, Southeast Asia, and South Asia. The genome consists of 40.00 Mb in 27 contigs with a contig N50 of 4.384 Mb. Phylogenetic analysis reveals that P. giganteus and other strains in Pleurotus clustered in one clade. Phylogenetic analysis and average nucleotide identity analysis indicated that the P. giganteus genome showed a closer relationship with other Pleurotus species. Chromosome collinearity analysis revealed a high level of collinearity between P. ostreatus and P. giganteus. There are 12,628 protein-coding genes annotated in this monoploid genome. A total of 481 enzymes accounting for 514 carbohydrate-active enzymes (CAZymes) terms were identified in the P. giganteus genome, including 15 laccases and 10 class II peroxidases predicted in the genome, which revealed the robustness of lignocellulose degradation capacity of P. giganteus. The mating-A type locus of P. giganteus consisted of a pair of homeodomain mating-type genes HD1 and HD2. The mating-B type locus of P. giganteus consisted of at least four pheromone receptor genes and three pheromone genes. The genome is not only beneficial for the genome-assisted breeding of this mushroom but also helps us to understand the high-temperature tolerance of the edible mushroom.
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BACKGROUND: Wilson's disease (WD) currently lacks a promising indicator that could reflect neurological impairment and monitor treatment outcome. We aimed to investigate whether serum neurofilament light chain (sNfL) functions as a candidate for disease assessment and treatment monitoring of WD. METHODS: We assessed preclinical and manifested WD patients' sNfL levels compared to controls and analyzed the differences between patients with various clinical symptoms. We then explored the correlation between clinical scales and sNfL levels. And repeated measurements were performed in 34 patients before and after treatment. RESULTS: WD patients with neurological involvement had significantly higher sNfL levels than both hepatic patients and controls. Positive correlations were found between Unified Wilson's Disease Rating Scale scores and sNfL and between semiquantitative magnetic resonance imaging scales and sNfL levels in WD patients. However, in the treatment follow-up analysis, the trend of sNfL before and after treatment disaccorded with clinical response. CONCLUSION: These findings suggest that sNfL levels can be an ideal indicator for the severity of neurological involvement but fail to evaluate change in disease condition after treatment. © 2022 International Parkinson and Movement Disorder Society.
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Degeneración Hepatolenticular , Biomarcadores , Degeneración Hepatolenticular/diagnóstico , Degeneración Hepatolenticular/terapia , Humanos , Filamentos Intermedios , Imagen por Resonancia Magnética , Resultado del TratamientoRESUMEN
Objective: Epilepsy is a chronic disease that places a heavy burden on caregivers. Previous studies have shown that caregivers of epilepsy patients often experience anxiety and depression; however, few comprehensive studies have assessed their sleep quality and family function. Based on the current understanding of the anxiety and depression state of caregivers in children with epilepsy, we further explored the caregivers' sleep and family function and evaluated the predictors of the depression state of caregivers. Methods: In this cross-sectional online anonymous survey, we sent an online questionnaire to the caregivers of children with epilepsy who visited our hospital. The QR code of the questionnaire was scanned at the follow-up course to conduct an online survey. The questionnaire contained questions about sociodemographic and clinical information, the Self-rating Anxiety Scale, Self-rating Depression Scale, Pittsburgh Sleep Quality Index, and the Family Assessment Device. Results: A total of 308 caregivers of children with epilepsy aged 0-12 years were included in this study. The mean age of children with epilepsy was 4.8 ± 3.18 years, and the average illness duration was 34.2 ± 29.18 months. Further, 47.1% of the children took three or more anti-seizure medications, and 43.2% were on ketogenic diet therapy. We found that in 77.9% of the cases, the subjects were the mothers, in 89% there was more than one co-caregiver, and in 51.9%, financial help was required. Further, 63.6% of the caregivers thought they could not get enough access to disease knowledge education, and 83.7% perceived epilepsy was a terrible disease. Our results also showed that 65.6% of the caregivers were in depression status, 41.9% were in anxiety status, and 49.0% had poor sleep quality. The proportion of unhealthy family functioning in each subscale was 45.1-96.1%, and the unhealthy behavior control function accounted for 96.1%. Binary logistic regression analysis of the data showed that without co-caregivers [odds ratio (OR), 5.193], free of anxiety status (OR, 0.063), good sleep quality (OR, 0.446), healthy family role dimension (OR, 0.344), and healthy family general functional dimension (OR, 0.259) were predictors of depression status in caregivers of children with epilepsy. Conclusion: Anxiety and depression status are common in caregivers of children with epilepsy, with depression status being more prominent. Moreover, a considerable proportion of caregivers had poor sleep quality and unhealthy family function. The caregivers' anxiety status, sleep quality, family role dimension, family general function dimension, and the number of co-caregivers were predictors of depression status in caregivers. In clinical practice, caregivers' anxiety and depression status, poor sleep quality, and unhealthy family functioning should be addressed along with the treatment of children with epilepsy.
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Vine tea has been used as an herbal tea by several ethnic minorities for hundreds of years in China. Flavonoids, a kind of indispensable component in a variety of nutraceutical, pharmaceutical and cosmetic applications, are identified to be the major metabolites and bioactive ingredients in vine tea. Interestingly, vine tea exhibits a wide range of significant bioactivities including anti-oxidant, anti-inflammatory, anti-tumor, antidiabetic, neuroprotective and other activities, but no toxicity. These bioactivities, to some extent, enrich the understanding about the role of vine tea in disease prevention and therapy. The health benefits of vine tea, particularly dihydromyricetin and myricetin, are widely investigated. However, there is currently no comprehensive review available on vine tea. Therefore, this report summarizes the most recent studies investigating bioactive constituents, pharmacological effects and possible mechanisms of vine tea, which will provide a better understanding about the health benefits and preclinical assessment of novel application of vine tea.
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As the intensity of work increases, many of us sit for long hours while working in the office. It is not easy to sit properly at work all the time and sitting for a long time with wrong postures may cause a series of health problems as time goes by. In addition, monitoring the sitting posture of patients with spinal disease would be beneficial for their recovery. Accordingly, this paper designs and implements a sitting posture recognition system from a flexible array pressure sensor, which is used to acquire pressure distribution map of sitting hips in a real-time manner. Moreover, an improved self-organizing map-based classification algorithm for six kinds of sitting posture recognition is proposed to identify whether the current sitting posture is appropriate. The extensive experimental results verify that the performance of ISOM-based sitting posture recognition algorithm (ISOM-SPR) in short outperforms that of four kinds of traditional algorithms including decision tree-based (DT), K-means-based (KM), back propagation neural network-based (BP), self-organizing map-based (SOM) sitting posture recognition algorithms. Finally, it is proven that the proposed system based on ISOM-SPR algorithm has good robustness and high accuracy.
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Sedestación , Aprendizaje Automático no Supervisado , Algoritmos , Humanos , Redes Neurales de la Computación , PosturaRESUMEN
Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76-81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuous wave (FMCW) radar was built at first, realizing the noncontact measurement of vital signs. Secondly, the energy intensity and threshold of respiration signal during each period were calculated by using the rectangular window, and the accurate judgment of apnea was realized via numerical comparison. Thirdly, the features of respiratory and heart rate signals, the number of peaks and valleys, the difference between peaks and valleys, the average and the standard deviation of normalized short-term energy, and the average and the standard deviation and the minimum of instantaneous frequency, were extracted and analyzed. Finally, support vector machine (SVM) and K-nearest neighbor (KNN) were used to classify the extracted features, and the accuracy was 98.25% and 88.75%, respectively. The classification and recognition of respiratory patterns have been successfully realized.
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Radar , Procesamiento de Señales Asistido por Computador , Algoritmos , Humanos , Frecuencia Respiratoria , Tecnología , Signos VitalesRESUMEN
A novel compressed air energy storage (CAES) system has been developed, which is innovatively integrated with a coal-fired power plant based on its feedwater heating system. In the hybrid design, the compression heat of the CAES system is transferred to the feedwater of the coal power plant, and the compressed air before the expanders is heated by the feedwater taken from the coal power plant. Furthermore, the exhaust air of the expanders is employed to warm partial feedwater of the coal power plant. Via the suggested integration, the thermal energy storage equipment for a regular CAES system can be eliminated and the performance of the CAES system can be improved. Based on a 350 MW supercritical coal power plant, the proposed concept was thermodynamically evaluated, and the results indicate that the round-trip efficiency and exergy efficiency of the new CAES system can reach 64.08% and 70.01%, respectively. Besides, a sensitivity analysis was conducted to examine the effects of ambient temperature, air storage pressure, expander inlet temperature, and coal power load on the performance of the CAES system. The above work proves that the novel design is efficient under various conditions, providing important insights into the development of CAES technology.