Study on H

This paper studies the H- index problem. We obtain a necessary and sufficient condition of H- index larger than γ>0. A generalized differential equation is introduced and it is proved that its solvability and the feasibility of the H- index are equivalent. We extend the deterministic cases to the stochastic models. Our results can be used to fault detection filter analysis. Finally, the effectiveness of the proposed results is illustrated by an example

Model-free Reinforcement Learning for H2/H∞{H_{2}/H_{\infty}} Control of Stochastic Discrete-time Systems

This paper proposes a reinforcement learning (RL) algorithm for infinite horizon $\rm {H_{2}/H_{\infty}}$ problem in a class of stochastic discrete-time systems, rather than using a set of coupled generalized algebraic Riccati equations (GAREs). The algorithm is able to learn the optimal control policy for the system even when its parameters are unknown. Additionally, the paper explores the effect of detection noise as well as the convergence of the algorithm, and shows that the control policy is admissible after a finite number of iterations. The algorithm is also able to handle multi-objective control problems within stochastic fields. Finally, the algorithm is applied to the F-16 aircraft autopilot with multiplicative noise

Edaravone Improves the Post-traumatic Brain Injury Dysfunction in Learning and Memory by Modulating Nrf2/ARE Signal Pathway

OBJECTIVES: To investigate the molecular mechanism of edaravone (EDA) in improving the post-traumatic brain injury (TBI) dysfunction in learning and memory. METHODS: In vitro and in vivo TBI models were established using hydrogen peroxide (H2O2) treatment for hippocampal nerve stem cells (NSCs) and surgery for rats, followed by EDA treatment. WST 1 measurement, methylthiazol tetrazolium assay, and flow cytometry were performed to determine the activity, proliferation, and apoptosis of NSCs, and malondialdehyde (MDA), lactic dehydrogenase (LDH), and reactive oxygen species (ROS) detection kits were used to analyze the oxides in NSCs. RESULTS: Following EDA pretreatment, NSCs presented with promising resistance to H2O2-induced oxidative stress, whereas NSCs manifested significant increases in activity and proliferation and a decrease in apoptosis. Meanwhile, for NSCs, EDA pretreatment reduced the levels of MDA, LDH, and ROS, with a significant upregulation of Nrf2/antioxidant response element (ARE) signaling pathway, whereas for EDA-treated TBI rats, a significant reduction was observed in the trauma area and injury to the hippocampus, with improvement in memory and learning performance and upregulation of Nrf2/ARE signaling pathway. CONCLUSIONS: EDA, by regulating the activity of Nrf2/ARE signal pathway, can improve the TBI-induced injury to NSCs and learning and memory dysfunction in rats. &nbsp

Integrative Analyses Identify Potential Key Genes and Calcium-Signaling Pathway in Familial Atrioventricular Nodal Reentrant Tachycardia Using Whole-Exome Sequencing

BackgroundAtrioventricular nodal reentrant tachycardia (AVNRT) is a common arrhythmia. Growing evidence suggests that family aggregation and genetic factors are involved in AVNRT. However, in families with a history of AVNRT, disease-causing genes have not been reported.ObjectiveTo investigate the genetic contribution of familial AVNRT using a whole-exome sequencing (WES) approach.MethodsBlood samples were collected from 20 patients from nine families with a history of AVNRT and 100 control participants, and we systematically analyzed mutation profiles using WES. Gene-based burden analysis, integration of previous sporadic AVNRT data, pedigree-based co-segregation, protein-protein interaction network analysis, single-cell RNA sequencing, and confirmation of animal phenotype were performed.ResultsAmong 95 related reference genes, seven candidate pathogenic genes have been identified both in sporadic and familial AVNRT, including CASQ2, AGXT, ANK2, SYNE2, ZFHX3, GJD3, and SCN4A. Among the 37 reference genes from sporadic AVNRT, five candidate pathogenic genes were identified in patients with both familial and sporadic AVNRT: LAMC1, ryanodine receptor 2 (RYR2), COL4A3, NOS1, and ATP2C2. To identify the common pathogenic mechanisms in all AVNRT cases, five pathogenic genes were identified in patients with both familial and sporadic AVNRT: LAMC1, RYR2, COL4A3, NOS1, and ATP2C2. Considering the unique internal candidate pathogenic gene within pedigrees, three genes, TRDN, CASQ2, and WNK1, were likely to be the pathogenic genes in familial AVNRT. Notably, the core calcium-signaling pathway may be closely associated with the occurrence of AVNRT, including CASQ2, RYR2, TRDN, NOS1, ANK2, and ATP2C2.ConclusionOur pedigree-based studies demonstrate that RYR2 and related calcium signaling pathway play a critical role in the pathogenesis of familial AVNRT using the WES approach

Numerical investigation of GHz repetition rate fundamentally mode-locked all-fiber lasers

GHz repetition rate fundamentally mode-locked lasers have attracted great interest for a variety of scientific and practical applications. A passively mode-locked laser in all-fiber format has the advantages of high stability, maintenance-free operation, super compactness, and reliability. In this paper, we present numerical investigation on passive mode-locking of all-fiber lasers operating at repetition rates of 1-20 GHz. Our calculations show that the reflectivity of the output coupler, the small signal gain of the doped fiber, the total net cavity dispersion, and the modulation depth of the saturable absorber are the key parameters for producing stable fundamentally mode-locked pulses at GHz repetition rates in very short all-fiber linear cavities. The instabilities of GHz repetition rate fundamentally mode-locked all-fiber lasers with different parameters were calculated and analyzed. Compared to a regular MHz repetition rate mode-locked all-fiber laser, the pump power range for the mode-locking of a GHz repetition rate all-fiber laser is much larger due to the several orders of magnitude lower accumulated nonlinearity in the fiber cavity The presented numerical study provides valuable guidance for the design and development of highly stable mode-locked all-fiber lasers operating at GHz repetition rates.National Science Foundation Engineering Research Center for Integrated Access Networks [EEC-0812072]; Technology Research Initiative Fund (TRIF) Photonics Initiative of the University of Arizona; National Natural Science Foundation of China (NSFC) [61575075]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Inhibition of Osteoclastogenesis and Bone Resorption in vitro and in vivo by a prenylflavonoid xanthohumol from hops

Excessive RANKL signaling leads to superfluous osteoclast formation and bone resorption, is widespread in the pathologic bone loss and destruction. Therefore, targeting RANKL or its signaling pathway has been a promising and successful strategy for this osteoclast-related diseases. In this study, we examined the effects of xanthohumol (XN), an abundant prenylflavonoid from hops plant, on osteoclastogenesis, osteoclast resorption, and RANKL-induced signaling pathway using both in vitro and in vivo assay systems. In mouse and human, XN inhibited osteoclast differentiation and osteoclast formation at the early stage. Furthermore, XN inhibited osteoclast actin-ring formation and bone resorption in a dose-dependent manner. In ovariectomized-induced bone loss mouse model and RANKL-injection-induced bone resorption model, we found that administration of XN markedly inhibited bone loss and resorption by suppressing osteoclast activity. At the molecular level, XN disrupted the association of RANK and TRAF6, resulted in the inhibition of NF-κB and Ca(2+)/NFATc1 signaling pathway during osteoclastogenesis. As a results, XN suppressed the expression of osteoclastogenesis-related marker genes, including CtsK, Nfatc1, Trap, Ctr. Therefore, our data demonstrated that XN inhibits osteoclastogenesis and bone resorption through RANK/TRAF6 signaling pathways. XN could be a promising drug candidate in the treatment of osteoclast-related diseases such as postmenopausal osteoporosis

FERONIA interacts with ABI2-type phosphatases to facilitate signaling cross-talk between abscisic acid and RALF peptide in Arabidopsis

[EN] Receptor-like kinase FERONIA (FER) plays a crucial role in plant response to small molecule hormones [e.g., auxin and abscisic acid (ABA)] and peptide signals [e.g., rapid alkalinization factor (RALF)]. It remains unknown how FER integrates these different signaling events in the control of cell growth and stress responses. Under stress conditions, increased levels of ABA will inhibit cell elongation in the roots. In our previous work, we have shown that FER, through activation of the guanine nucleotide exchange factor 1 (GEF1)/4/10-Rho of Plant 11 (ROP11) pathway, enhances the activity of the phosphatase ABA Insensitive 2 (ABI2), a negative regulator of ABA signaling, thereby inhibiting ABA response. In this study, we found that both RALF and ABA activated FER by increasing the phosphorylation level of FER. The FER loss-of-function mutant displayed strong hypersensitivity to both ABA and abiotic stresses such as salt and cold conditions, indicating that FER plays a key role in ABA and stress responses. We further showed that ABI2 directly interacted with and dephosphorylated FER, leading to inhibition of FER activity. Several other ABI2-like phosphatases also function in this pathway, and ABA-dependent FER activation required PYRABACTIN RESISTANCE (PYR)/PYR1-LIKE (PYL)/REGULATORY COMPONENTS OF ABA RECEPTORS (RCAR)-A-type protein phosphatase type 2C (PP2CA) modules. Furthermore, suppression of RALF1 gene expression, similar to disruption of the FER gene, rendered plants hypersensitive to ABA. These results formulated a mechanism for ABA activation of FER and for cross-talk between ABA and peptide hormone RALF in the control of plant growth and responses to stress signals.We thank Dr. Alice Cheung, Dr. Daniel Moura, Grossniklaus Ueli, Dr. Jigang Li, and Dr. Nieng Yan for providing plant, ABI1 antibody, or plasmid materials, and Dr. Legong Li for assistance in laser confocal microscopy. This work was supported by grants from National Natural Science Foundation of China (NSFC-31400232, 31571444), the State Key Laboratory of Molecular Developmental Biology (2015-MDB-KF-12), the Fundamental Research Funds for the Central Universities of China, and a grant from the National Science Foundation.Chen, J.; Yu, F.; Liu, Y.; Du, C.; Li, X.; Zhu, S.; Wang, X.... (2016). FERONIA interacts with ABI2-type phosphatases to facilitate signaling cross-talk between abscisic acid and RALF peptide in Arabidopsis. Proceedings of the National Academy of Sciences. 113(37):E5519-E5527. https://doi.org/10.1073/pnas.1608449113SE5519E55271133

Diagnostic Accuracy of Deep Learning and Radiomics in Lung Cancer Staging: A Systematic Review and Meta-Analysis

BackgroundArtificial intelligence has far surpassed previous related technologies in image recognition and is increasingly used in medical image analysis. We aimed to explore the diagnostic accuracy of the models based on deep learning or radiomics for lung cancer staging.MethodsStudies were systematically reviewed using literature searches from PubMed, EMBASE, Web of Science, and Wanfang Database, according to PRISMA guidelines. Studies about the diagnostic accuracy of radiomics and deep learning, including the identifications of lung cancer, tumor types, malignant lung nodules and lymph node metastase, were included. After identifying the articles, the methodological quality was assessed using the QUADAS-2 checklist. We extracted the characteristic of each study; the sensitivity, specificity, and AUROC for lung cancer diagnosis were summarized for subgroup analysis.ResultsThe systematic review identified 19 eligible studies, of which 14 used radiomics models and 5 used deep learning models. The pooled AUROC of 7 studies to determine whether patients had lung cancer was 0.83 (95% CI 0.78–0.88). The pooled AUROC of 9 studies to determine whether patients had NSCLC was 0.78 (95% CI 0.73–0.83). The pooled AUROC of the 6 studies that determined patients had malignant lung nodules was 0.79 (95% CI 0.77–0.82). The pooled AUROC of the other 6 studies that determined whether patients had lymph node metastases was 0.74 (95% CI 0.66–0.82).ConclusionThe models based on deep learning or radiomics have the potential to improve diagnostic accuracy for lung cancer staging.Systematic Review Registrationhttps://inplasy.com/inplasy-2022-3-0167/, identifier: INPLASY202230167