Search

Chemerin is an adipokine that contributes to metabolism regulation. Nucleus tractus solitarius (NTS) is the first relay station in the brain for accepting various visceral afferent activities for regulating cardiovascular activity. However, the roles of chemerin in the NTS in regulating sympathetic activity and blood pressure are almost unknown. This study aimed to determine the role and potential mechanism of chemerin in the NTS in modulating sympathetic outflow and blood pressure. Bilateral NTS microinjections were performed in anaesthetized adult male Sprague–Dawley rats. Renal sympathetic nerve activity (RSNA), mean arterial pressure (MAP) and heart rate (HR) were continuously recorded. Chemerin and its receptor chemokine‐like receptor 1 (CMKLR1) were highly expressed in caudal NTS (cNTS). Microinjection of chemerin‐9 to the cNTS increased RSNA, MAP and HR, which were prevented by CMKLR1 antagonist α‐NETA, superoxide scavenger tempol or N‐acetyl cysteine, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitors diphenyleneiodonium or apocynin. Chemerin‐9 increased superoxide production and NADPH oxidase activity in the cNTS. The increased superoxide production induced by chemerin‐9 was inhibited by α‐NETA. The effects of cNTS microinjection of chemerin‐9 on the RSNA, MAP and HR were attenuated by the pretreatment with paraventricular nucleus (PVN) microinjection of NMDA receptor antagonist MK‐801 rather than AMPA/kainate receptor antagonist CNQX. These results indicate that chemerin‐9 in the NTS increases sympathetic outflow, blood pressure and HR via CMKLR1‐mediated NADPH oxidase activation and subsequent superoxide production in anaesthetized normotensive rats. Glutamatergic inputs in the PVN are needed for the chemerin‐9‐induced responses. [ABSTRACT FROM AUTHOR]

Glucagon-like peptide-1 (GLP-1) and its analogs are widely used for diabetes treatment. The paraventricular nucleus (PVN) is crucial for regulating cardiovascular activity. This study aims to determine the roles of GLP-1 and its receptors (GLP-1R) in the PVN in regulating sympathetic outflow and blood pressure. Experiments were carried out in male normotensive rats and spontaneously hypertensive rats (SHR). Renal sympathetic nerve activity (RSNA) and mean arterial pressure (MAP) were recorded. GLP-1 and GLP-1R expressions were present in the PVN. PVN microinjection of GLP-1R agonist recombinant human GLP-1 (rhGLP-1) or EX-4 increased RSNA and MAP, which were prevented by GLP-1R antagonist exendin 9-39 (EX9-39) or GLP-1R antagonist 1, superoxide scavenger tempol, antioxidant N-acetylcysteine, NADPH oxidase (NOX) inhibitor apocynin, adenylyl cyclase (AC) inhibitor SQ22536 or protein kinase A (PKA) inhibitor H89. PVNmicroinjection of rhGLP-1 increased superoxide production, NADPH oxidase activity, cAMP level, AC, and PKA activity, which were prevented by SQ22536 or H89. GLP-1 and GLP-1R were upregulated in the PVN of SHR. PVN microinjection of GLP-1 agonist increased RSNA and MAP in both WKY and SHR, but GLP-1 antagonists caused greater effects in reducing RSNA and MAP in SHR than in WKY. The increased superoxide production and NADPH oxidase activity in the PVN of SHR were augmented by GLP-1R agonists but attenuated by GLP-1R antagonists. These results indicate that activation of GLP-1R in the PVN increased sympathetic outflow and blood pressure via cAMP-PKA-mediated NADPH oxidase activation and subsequent superoxide production. GLP-1 and GLP-1R upregulation in the PVN partially contributes to sympathetic overactivity and hypertension. [ABSTRACT FROM AUTHOR]

Background: As an irreversible post-translational modification, protein carbonylation is closely related to many diseases and aging. Protein carbonylation prediction for related patients is significant, which can help clinicians make appropriate therapeutic schemes. Because carbonylation sites can be used to indicate change or loss of protein function, integrating these protein carbonylation site data has been a promising method in prediction. Based on these protein carbonylation site data, some protein carbonylation prediction methods have been proposed. However, most data is highly class imbalanced, and the number of un-carbonylation sites greatly exceeds that of carbonylation sites. Unfortunately, existing methods have not addressed this issue adequately. Results: In this work, we propose a novel two-way rebalancing strategy based on the attention technique and generative adversarial network (Carsite_AGan) for identifying protein carbonylation sites. Specifically, Carsite_AGan proposes a novel undersampling method based on attention technology that allows sites with high importance value to be selected from un-carbonylation sites. The attention technique can obtain the value of each sample's importance. In the meanwhile, Carsite_AGan designs a generative adversarial network-based oversampling method to generate high-feasibility carbonylation sites. The generative adversarial network can generate high-feasibility samples through its generator and discriminator. Finally, we use a classifier like a nonlinear support vector machine to identify protein carbonylation sites. Conclusions: Experimental results demonstrate that our approach significantly outperforms other resampling methods. Using our approach to resampling carbonylation data can significantly improve the effect of identifying protein carbonylation sites. [ABSTRACT FROM AUTHOR]

Background: Cancer is one of the leading death causes around the world. Accurate prediction of its survival time is significant, which can help clinicians make appropriate therapeutic schemes. Cancer data can be characterized by varied molecular features, clinical behaviors and morphological appearances. However, the cancer heterogeneity problem usually makes patient samples with different risks (i.e., short and long survival time) inseparable, thereby causing unsatisfactory prediction results. Clinical studies have shown that genetic data tends to contain more molecular biomarkers associated with cancer, and hence integrating multi-type genetic data may be a feasible way to deal with cancer heterogeneity. Although multi-type gene data have been used in the existing work, how to learn more effective features for cancer survival prediction has not been well studied. Results: To this end, we propose a deep learning approach to reduce the negative impact of cancer heterogeneity and improve the cancer survival prediction effect. It represents each type of genetic data as the shared and specific features, which can capture the consensus and complementary information among all types of data. We collect mRNA expression, DNA methylation and microRNA expression data for four cancers to conduct experiments. Conclusions: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. Availability and implementation: https://github.com/githyr/ComprehensiveSurvival. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusion To evaluate the effect of multidisciplinary treatment (MDT) on the survival outcomes of Chinese lung cancer patients.Data from a Chinese tertiary cancer hospital of lung cancer patients were collected and divided into two groups (MDT+/−) according to whether the patients had received an MDT. The survival analysis was performed after propensity score matching (PSM).Before PSM, more patients in the MDT+ group had documented information on clinical characteristics and showed more unfavorable clinical characteristics than patients in the MDT− group. After PSM, there was no imbalance in the first‐line treatment strategies between the two groups. When the patients were analyzed separately, for patients in the MDT− group, age at diagnosis, Eastern Cooperative Oncology Group (ECOG) score, stage, smoking history, and epidermal growth factor receptor (EGFR) gene status were all significant factors for survival (p < 0.05). For patients in the MDT+ group, only age at diagnosis, stage, and comorbidities were significant factors for survival (p < 0.05). Moreover, age at diagnosis, ECOG score, stage, EGFR gene status, and MDT were all significant factors for survival for all patients (p < 0.001). The results indicate that MDT was a significant prognostic factor independent of clinical characteristics (HR: 2.095, 95% CI: 1.568–2.800, p < 0.001), with a significantly improved median survival (58.0 vs. 29.0 months, p < 0.001).Based on PSM, MDT itself did have a real favorable prognostic significance for Chinese lung cancer patients in the study. [ABSTRACT FROM AUTHOR]

In this paper, an improved coupled-mode method is used to design a launcher for a gyrotron quasi-optical mode converter at 170 Ghz with an operating mode of TE32,9. The new method calculates 25 coupled modes, which more accurately simulates the field distribution in the launcher. The diffraction field of the launcher with a spiral cut is calculated by using the scalar diffraction integral method with fast Fourier transform. The radiation power of the launcher is 99.94%, the Gaussian mode content of the radiation beam is 98.40%, the diffraction loss of the launcher is 0.0580%, and the radiation efficiency is 98.34%. The method proposed in this paper is fast in calculation and can be applied to the large-scale high-frequency gyrotron launcher. [ABSTRACT FROM AUTHOR]

Background: As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data. Results: We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction. Conclusions: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. [ABSTRACT FROM AUTHOR]

Background: As a highly aggressive disease, cancer has been becoming the leading death cause around the world. Accurate prediction of the survival expectancy for cancer patients is significant, which can help clinicians make appropriate therapeutic schemes. With the high-throughput sequencing technology becoming more and more cost-effective, integrating multi-type genome-wide data has been a promising method in cancer survival prediction. Based on these genomic data, some data-integration methods for cancer survival prediction have been proposed. However, existing methods fail to simultaneously utilize feature information and structure information of multi-type genome-wide data. Results: We propose a Multi-type Data Joint Learning (MDJL) approach based on multi-type genome-wide data, which comprehensively exploits feature information and structure information. Specifically, MDJL exploits correlation representations between any two data types by cross-correlation calculation for learning discriminant features. Moreover, based on the learned multiple correlation representations, MDJL constructs sample similarity matrices for capturing global and local structures across different data types. With the learned discriminant representation matrix and fused similarity matrix, MDJL constructs graph convolutional network with Cox loss for survival prediction. Conclusions: Experimental results demonstrate that our approach substantially outperforms established integrative methods and is effective for cancer survival prediction. [ABSTRACT FROM AUTHOR]

Asprosin is a newly discovered adipokine that is involved in regulating metabolism. Sympathetic overactivity contributes to the pathogenesis of several cardiovascular diseases. The paraventricular nucleus (PVN) of the hypothalamus plays a crucial role in the regulation of sympathetic outflow and blood pressure. This study was designed to determine the roles and underlying mechanisms of asprosin in the PVN in regulating sympathetic outflow and blood pressure. Experiments were carried out in male adult SD rats under anesthesia. Renal sympathetic nerve activity (RSNA), mean arterial pressure (MAP), and heart rate (HR) were recorded, and PVN microinjections were performed bilaterally. Asprosin mRNA and protein expressions were high in the PVN. The high asprosin expression in the PVN was involved in both the parvocellular and magnocellular regions according to immunohistochemical analysis. Microinjection of asprosin into the PVN produced dose-related increases in RSNA, MAP, and HR, which were abolished by superoxide scavenger tempol, antioxidant N-acetylcysteine (NAC), and NADPH oxidase inhibitor apocynin. The asprosin promoted superoxide production and increased NADPH oxidase activity in the PVN. Furthermore, it increased the cAMP level, adenylyl cyclase (AC) activity, and protein kinase A (PKA) activity in the PVN. The roles of asprosin in increasing RSNA, MAP, and HR were prevented by pretreatment with AC inhibitor SQ22536 or PKA inhibitor H89 in the PVN. Microinjection of cAMP analog db-cAMP into the PVN played similar roles with asprosin in increasing the RSNA, MAP, and HR, but failed to further augment the effects of asprosin. Pretreatment with PVN microinjection of SQ22536 or H89 abolished the roles of asprosin in increasing superoxide production and NADPH oxidase activity in the PVN. These results indicated that asprosin in the PVN increased the sympathetic outflow, blood pressure, and heart rate via cAMP–PKA signaling-mediated NADPH oxidase activation and the subsequent superoxide production. [ABSTRACT FROM AUTHOR]

Few-shot class-incremental learning (FSCIL) is a challenge that requires a model to learn new classes from limited examples without forgetting the learned knowledge. A common solution freezes the parameters trained on the base task and only fine-tunes the classifier for new incremental tasks. However, this solution may not guarantee the model's generalization ability to unseen classes, resulting in model limitations in adapting to new classes. To address this issue, we propose a novel approach called sharpness-aware gradient guidance (SAGG). Specifically, the SAGG objective improves the model's generalization ability by finding parameters within flat regions of the loss landscape. We first measure the sharpness of the loss function around the current parameters by adding perturbations. Then, we jointly optimize the training loss and the perturbation loss by explicitly guiding the gradient directions. Moreover, a prototype calibration strategy is proposed to help the model adapt to new classes with limited training instances by adjusting the classifier weights. We evaluate our approach on three benchmark datasets: CIFAR100, miniImageNet, and CUB200. The empirical results show that our method significantly surpasses other competing methods in terms of average accuracy. [ABSTRACT FROM AUTHOR]

Bimetallic AgCo/g-C 3 N 4 photocatalysts were successfully prepared by a facile chemical reduction method and used to investigate their photocatalytic H 2 production performance. Bimetallic AgCo as a cocatalyst can be well matched with g-C 3 N 4 , which is beneficial for increasing the number of active reaction sites and narrowing the band gap. A possible photocatalytic mechanism was explored by XRD, FTIR, SEM, TEM, UV–vis DRS, BET, and PL characterization. The photocatalytic H 2 production activity of the optimal 5%AgCo/g-C 3 N 4 photocatalyst reached 12994.2 μmoL/g, which was 54.7 times higher than g-C 3 N 4. Owing to the close interfacial contact between bimetallic AgCo and g-C 3 N 4 , the transfer distance was shortened, and the photogenerated electron and hole pairs were effectively separated. This study provides a new strategy for the synthesis of excellent H 2 production photocatalysts using bimetallic nanoparticles. • Bimetallic AgCo were loaded on g-C 3 N 4 nanosheets via chemical reduction method. • Intimate interfacial contact was facilitated the effective separation of e−-h+ pairs. • The AgCo/g-C 3 N 4 exhibited excellent photocatalytic activity and reusability. • The photocatalytic mechanism was conducive to water spitting H 2 production. [ABSTRACT FROM AUTHOR]

Cassiae semen has been shown to play significant roles in reversing "liver fire" to improve vision. The systems mechanism of Cassiae semen for hepatoprotection and brightening eyes has not been fully explored. The systems pharmacology approach is proposed to dissect the potential pharmacological mechanism of Cassiae semen for hepatoprotection and brightening eyes. The results showed that 26 active components of Cassiae semen that connected with 230 targets were obtained. Gene ontology enrichment, network and pathway analysis explored that Cassiae semen is responsible for hepatoprotection and brightening eyes. The current study will contribute to the research and development of functional foods. [ABSTRACT FROM AUTHOR]

This article describes the design, testing, and space qualification of a 150-W high-power and high-efficiency GaN solid-state amplifier (SSPA) used in the BeiDou Navigation Satellite System (BDS). The SSPA, based on 0.5-μm GaN technology, includes the radio frequency unit (RFU) and electronic power conditioner unit (EPC). The power amplifier solves the problems of high efficiency, reliability, stability, and high-power thermal design for 80-W GaN HEMT onboard applications. The RFU together with the EPC is accommodated in a different box with limited volume and mass. In continuous-wave operating mode, the SSPA delivers an output power higher than 150 W at less than 3 dB of gain compression in the whole B2-band (i.e., center frequency freq = 1.191 GHz, bandwidth BW = 80 MHz). Moreover, the demonstrated gain is higher than 52 dB and power added efficiency, including the power dissipated by the EPC, is above 50%. The SSPA has completed all space qualification tests and 10 000-h accelerated life test. The space qualification tests have been approved in 2013, and the first satellite employing this SSPA has been launched in 2015. The SSPA has been applied to more than 10 BeiDou Navigation Satellites. So far, the SSPA in the first satellite has worked successfully for more than 6 years and leads to a technology readiness level more than Level 8. The large-scale application of the high-power gallium nitride solid-state power amplifier in space is reported first in this article. [ABSTRACT FROM AUTHOR]

Type Ⅱ g-C 3 N 4 /Ag 3 PO 4 photocatalysts were prepared by an in situ chemical precipitation method used to investigate the photocatalytic degradation performance. In this work, the g-C 3 N 4 /Ag 3 PO 4 (1:1) composite catalyst exhibited superior photocatalytic performance for MB and BPA degradation, the degradation rate of MB reached 100 % within 80 min, and the degradation rate of BPA reached 98.5 % within 100 min, which were 1.8 and 8.7 times higher than that of g-C 3 N 4 , respectively. Its reaction rate abided by the pseudo-first-order kinetics, kinetic rate constants (κ) were 0.0626 min−1 and 0.0419 min−1, respectively. Through a series of characterizations, it was found that the intimate interface contact between g-C 3 N 4 and Ag 3 PO 4 formed type Ⅱ heterojunction, not only shortening photogenerated carriers transfer distance and accelerating the separation of photogenerated carriers, but also enhancing the stability and reusability of the g-C 3 N 4 /Ag 3 PO 4 composite catalyst. Meanwhile, the h+ radicals and ·O 2 - radicals were main active species of photocatalytic degradation reactions by the free radical trapping experiments and ESR tests further were confirmation. A possible photocatalytic mechanism was studied by UV–vis DRS, Mott-Schottky curves, the free radical trapping experiment and ESR. This aim of this paper is to improve the efficiency of photocatalytic degradation of MB and BPA by synthesizing type Ⅱ g-C 3 N 4 /Ag 3 PO 4 photocatalysts. • Type Ⅱ g-C 3 N 4 /Ag 3 PO 4 heterojunction was prepared via chemical precipitation method. • Intimate interfacial contact was facilitated the separation and transfer of e--h+ pairs. • The degradation rates of MB and BPA by g-C 3 N 4 /Ag 3 PO 4 could reach 100 % and 98.5 %, respectively. • h+ was the main active species in the degradation of MB and BPA. • Type Ⅱ g-C 3 N 4 /Ag 3 PO 4 heterojunction had an excellent reusability after five cycles. [ABSTRACT FROM AUTHOR]

Learning an expressive representation from multi-view data is a crucial step in various real-world applications. In this paper, we propose a semi-supervised multi-view representation learning approach named Co-Embedding. Unlike conventional multi-view representation learning methods use joint to concatenate different views, which ignores information exchange between views and limits the methods' ability to utilize complementarity of multi-view data, Co-Embedding fulfills mutual help between views by coordinating and exchanging information between views. Specifically, we first build a weighted deep metric learning based multi-view representation learning framework in Co-Embedding. This framework models multi-view information through coordinate alignment, which is customized to exploit the complementary information from well-learned representations to help with modeling the under-learned representations. Then, by exploiting consensus property and neighborhood information, we design a multi-view label propagation algorithm that labels unlabeled data for Co-Embedding. Experimental results on seven benchmark multi-view datasets demonstrate the effectiveness of Co-Embedding. [ABSTRACT FROM AUTHOR]

This article considers single-machine problems in which the actual processing time of a job is a function of its position in a sequence (i.e. position-dependent deterioration effects). In this model, a job is either accepted or rejected. If the job is accepted, it is processed on a single machine, but if the job is rejected, a penalty (cost) is imposed. The goal is to minimize the sum of the given scheduling objectives, including the makespan, the total completion time, the total absolute differences in completion times and the total absolute differences in waiting times of the accepted jobs and total rejection penalty of the rejected jobs. It is illustrated that these problems remain polynomially solvable under the proposed models. Finally, computational results demonstrate that the proposed algorithms can solve instances of various size problems in attractive times. An extension to the problems is offered by assuming time-dependent deterioration effects. [ABSTRACT FROM AUTHOR]

Objective: Ultrasonography-guided radiofrequency ablation (RFA) is used to treat small low-risk papillary thyroid carcinoma (PTC) and has achieved favorable results. However, few studies have compared the outcomes of T1aN0M0 and T1bN0M0 PTC treated with ultrasonography-guided RFA. The objective of this study was to compare the outcomes of patients receiving RFA for solitary T1aN0M0 and T1bN0M0 PTC retrospectively. Methods: Patients treated with RFA for solitary T1aN0M0 or T1bN0M0 PTC between April 2014 and December 2019 were retrospectively reviewed. All patients were ineligible for or refused surgery. Our institutional review board approved this study. A total of 262 patients were included after adjustment for propensity score matching between the T1a and T1b groups. Local tumor progression (LTP), LTP-free survival, post-treatment complications, change in tumor volume, and RFA-related parameters were compared between the two groups. Results: The LTP rate was 3.82% in both groups, and the LTP and LTP-free survival rates did not significantly differ between the two groups. One patient in group T1b developed transient recurrent laryngeal nerve injury. Significant tumor shrinkage was observed during the follow-up. The rate of tumor disappearance rate was higher in group T1a than in group T1b (81.7% vs 52.7%, P < 0.001). During RFA, the output power and total energy were higher and the duration was significantly shorter in group T1b than in group T1a (P < 0.001). Conclusions: The outcomes of RFA for the treatment of T1aN0M0 and T1bN0M0 PTC were similar. Therefore, RFA may be an alternative to surgery for the treatment of T1bN0M0 and T1aN0M0 PTCs. [ABSTRACT FROM AUTHOR]

The effect of nonlinear chirp combination on the enhancement of harmonic cutoff and harmonic intensity has been investigated by using a two-color chirped pulse. It is found that with the combination of 2-order chirp form, the strongest intensity enhancement of harmonic spectrum can be found. While, with the combination of 2-order and 3-order chirp forms, the largest cutoff extension of the harmonic spectrum can be obtained. Finally, by properly using the harmonic spectra driven by the above two kinds of combined pulses, the single attosecond pulses (SAPs) of 43 as and 33 as can be generated. [ABSTRACT FROM AUTHOR]

Two-dimensional surface-enhanced Raman scattering (SERS) substrates have drawn intense attention due to their excellent spectral reproducibility, high uniformity and perfect anti-interference ability. However, the inferior detection sensitivity and low enhancement have limited the practical application of two-dimensional SERS substrates. To address this issue, we propose that the interaction between the MoTe2 substrate and the analyte rhodamine 6G molecules could be remarkably enhanced by the introduced p-doping effect and lattice distortion of MoTe2 via hydrogen plasma treatment. After the treatment, the SERS is greatly improved, the enhancement factor of probe molecules reaches 1.83 × 106 as well as the limit of detection concentration reaches 10−13 M. This method is anticipated to afford new enhancement probability for other 2D materials, even non-metal oxide semiconductor SERS substrates. [ABSTRACT FROM AUTHOR]

How to obtain the high signal intensity harmonic spectra with the single harmonic radiation path contribution becomes an important issue in the investigations of the high-order harmonic generation and attosecond science. In this paper, through the nonhomogeneous multicolor laser beams optimization, the best time-spatial laser waveforms, including the positive and negative time-spatial waveforms, to produce the harmonic spectra can be found. As a result, the harmonic plateaus with the single harmonic radiation path contribution and with the enhancement of several orders of magnitudes can be obtained, which can support the generation of the isolated pulses with the durations of 29 as. The physical mechanism behind the improvement of the harmonic spectra is given by the time-spatial profile analyses of the laser pulses and the harmonic spectra. [ABSTRACT FROM AUTHOR]

This study focuses on the repair of damaged hair with the joint use of transglutaminase (TG enzyme) and keratin. We first prepared a TG-keratin repair solution with reasonable wool keratin and TG enzyme concentration, and used the soaking process to repair the damaged hair so as to modify protein fibers. We, then, measured the alkali solubility, fracture stress and strain, and swelling rate of the hair samples, before and after the treatment. The results showed that after treatment, samples' alkali solubility reduced from 16.14% to 4.92%, fracture stress increased from 0.832 N to 1.668 N, fracture strain arose from 8.81 mm to 10.17 mm, and swelling rate drops from 38.34% to 2.34%. Both Fourier transform infrared and X-ray diffraction spectroscopies further indicated that combined treatment with keratin and TG enzyme had significant repair effect on the damaged sites, where proteins were exposed with more amide bonds, higher crystallinity, increased percentage of crystalline area over the entire fiber area, and strengthened crosslink activities. Observation under both scanning electron microscope and atomic force microscope revealed smoother surface and fewer warped scales on the surface of hairs after combined treatment with keratin and TG enzyme. To our best knowledge, this is the first application of enzyme technology in damaged hair repair. It opens up a new research direction for green, environmentally friendly, and efficient biological hair care and will play a pivotal role in the application of various protein-based materials. [ABSTRACT FROM AUTHOR]

Klebsiella pneumoniae (Kpn) is an important pathogen of hospital-acquired pneumonia, which can lead to sepsis and death in severe cases. In this study, we simulated pneumonia induced by Kpn infection in mice to investigate the therapeutic effect of naringin (NAR) on bacterial-induced lung inflammation. Mice infected with Kpn exhibited increases in white blood cells (WBC) and neutrophils in the peripheral blood and pathological severe injury of the lungs. This injury was manifested by increased expression of the inflammatory cytokines interleukin (IL)− 18, IL-1β, tumor necrosis factor-α (TNF-α) and IL-6, and elevated the expression of NLRP3 protein. NAR treatment could decrease the protein expression of NLRP3, alleviate lung inflammation, and reduce lung injury in mice caused by Kpn. Meanwhile, molecular docking results suggest NAR could bind to NLRP3 and Surface Plasmon Resonance (SPR) analyses also confirm this result. In vitro trials, we found that pretreated with NAR not only inhibited nuclear translocation of nuclear factor (NF)-κB protein P65 but also attenuated the protein interaction of NLRP3, caspase-1 and ASC and inhibited the assembly of NLRP3 inflammasome in mice AMs. Additionally, NAR could reduce intracellular potassium (K+) efflux, inhibiting NLRP3 inflammasome activation. These results indicated that NAR could protect against Kpn-induced pneumonia by inhibiting the overactivation of the NLRP3 inflammasome signaling pathway. The results of this study confirm the efficacy of NAR in treating bacterial pneumonia, refine the mechanism of action of NAR, and provide a theoretical basis for the research and development of NAR as an anti-inflammatory adjuvant. [Display omitted] • NAR showed remarkable therapeutic effects on pneumonia induced by Kpn in mice. • NLRP3 was identified as a binding target of NAR by molecular docking and SPR assay. • NAR inhibited the Priming signal and Activation signal of NLRP3 inflammasome. • NAR inhibits NLRP3 complex protein interactions and assembly. [ABSTRACT FROM AUTHOR]

Background: d-Amino acids are increasingly used as building blocks to produce pharmaceuticals and fine chemicals. However, establishing a universal biocatalyst for the general synthesis of d-amino acids from cheap and readily available precursors with few by-products is challenging. In this study, we developed an efficient in vivo biocatalysis system for the synthesis of d-amino acids from l-amino acids by the co-expression of membrane-associated l-amino acid deaminase obtained from Proteus mirabilis (LAAD), meso-diaminopimelate dehydrogenases obtained from Symbiobacterium thermophilum (DAPDH), and formate dehydrogenase obtained from Burkholderia stabilis (FDH), in recombinant Escherichia coli. Results: To generate the in vivo cascade system, three strategies were evaluated to regulate enzyme expression levels, including single-plasmid co-expression, double-plasmid co-expression, and double-plasmid MBP-fused co-expression. The double-plasmid MBP-fused co-expression strain Escherichia coli pET-21b-MBP-laad/pET-28a-dapdh-fdh, exhibiting high catalytic efficiency, was selected. Under optimal conditions, 75 mg/mL of E. coli pET-21b-MBP-laad/pET-28a-dapdh-fdh whole-cell biocatalyst asymmetrically catalyzed the stereoinversion of 150 mM l-Phe to d-Phe, with quantitative yields of over 99% ee in 24 h, by the addition of 15 mM NADP+ and 300 mM ammonium formate. In addition, the whole-cell biocatalyst was used to successfully stereoinvert a variety of aromatic and aliphatic l-amino acids to their corresponding d-amino acids. Conclusions: The newly constructed in vivo cascade biocatalysis system was effective for the highly selective synthesis of d-amino acids via stereoinversion. [ABSTRACT FROM AUTHOR]

With the expansion of data, increasing imbalanced data has emerged. When the imbalance ratio (IR) of data is high, most existing imbalanced learning methods decline seriously in classification performance. In this paper, we systematically investigate the highly imbalanced data classification problem, and propose an uncorrelated cost-sensitive multiset learning (UCML) approach for it. Specifically, UCML first constructs multiple balanced subsets through random partition, and then employs the multiset feature learning (MFL) to learn discriminant features from the constructed multiset. To enhance the usability of each subset and deal with the non-linearity issue existed in each subset, we further propose a deep metric based UCML (DM-UCML) approach. DM-UCML introduces the generative adversarial network technique into the multiset constructing process, such that each subset can own similar distribution with the original dataset. To cope with the non-linearity issue, DM-UCML integrates deep metric learning with MFL, such that more favorable performance can be achieved. In addition, DM-UCML designs a new discriminant term to enhance the discriminability of learned metrics. Experiments on eight traditional highly class-imbalanced datasets and two large-scale datasets indicate that: the proposed approaches outperform state-of-the-art highly imbalanced learning methods and are more robust to high IR. [ABSTRACT FROM AUTHOR]

Background: The role of hemoglobin (HGB) in common malignant tumors remains unclear. Methods: A retrospective analysis was conducted to identify the correlation between HGB levels and risk of 15 malignant tumors using 50,085 samples from the National Health and Nutrition Examination Survey. Mendelian Randomization analyses (MRAs) were performed based on genome-wide association study data to assess the causal relationship between HGB levels and these malignant tumors using more than 700,000 samples. The robustness of the MRA results was confirmed through various analytical methods. Fifty-six in-house samples were used to investigate the correlation between HGB levels and the prognosis in prostate cancer (PRCA) using the Kaplan-Meier curve. Results: High HGB levels were associated with a higher risk for patients with cervix cancer, melanoma, and non-melanoma skin cancer (OR > 1.000, p < 0.05). It served as a protective factor for colon cancer, esophagus cancer, stomach cancer, bone cancer, lung cancer, renal cancer, and PRCA (OR < 1.000, p < 0.05). Furthermore, MRAs suggested that elevated HGB levels were correlated with a reduced risk of PRCA (OR = 0.869, p < 0.05), with no significant association observed between this marker and the remaining 14 malignant tumors. No pleiotropy or heterogeneity was found in the ultimate results for MRAs (p-values > 0.05), suggesting the robustness of the results. The results derived from the in-house data revealed a relationship between higher HGB values and a more favorable prognosis in PRCA (p < 0.05). Conclusion: High circulating HGB levels may play a protective prognostic role for PRCA and serve as a protective factor against the occurrence of PRCA. [ABSTRACT FROM AUTHOR]

Cross‐project defect prediction (CPDP) technology refers to the constructing prediction model to predict the instance label of the target project by utilising labelled data from an external project. The challenge of CPDP methods is the distribution difference between the data from different projects. Transfer learning can transfer the knowledge from the source domain to the target domain with the aim to minimise the domain difference between different domains. However, most existing methods reduce the distribution discrepancy in the original feature space, where the features are high‐dimensional and non‐linear, which makes it hard to reduce the distribution distance between different projects. Moreover, previous works mainly consider marginal distribution or conditional distribution difference. In this study, the authors proposed a manifold embedded distribution adaptation (MDA) approach to narrow the distribution gap in manifold feature subspace. MDA maps source and target project data to manifold subspace and then joint distribution adaptation of conditional and marginal distributions is performed on manifold subspace. To evaluate the effectiveness of MDA, the authors perform extensive experiments on 20 public projects with three indicators. The experiment results show that MDA improves the average performance, but the improvement is not statistically significant in comparison to HYDRA (one of the baselines). [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to identify all relevant randomized controlled trials (RCT) and prospective non-RCTs to further investigate whether percutaneous vertebral augmentation (PVA) was associated with clinical and radiological subsequent fractures on unoperated levels. Methods: We systematically searched PubMed, EMBASE, Cochrane library, Google Scholar, web of science, and ClinicalTrial.gov from the establishment of the database to January 2020. All eligible studies comparing subsequent fractures after PVA with those after conservative treatment (CT) were incorporated. The pooled risk ratio (RR) with its 95% confidence intervals (95% CIs) was used. Heterogeneity, sensitivity, and publication bias analyses were performed. Results: In all, 32 studies were included in the study: 82/512 patients (16.02%) and 58/433 patients (13.39%) had clinical subsequent fractures in the PVA group and CT group, respectively. No significant differences were observed between the two groups [RR = 1.22, 95% CI 0.70–2.12, P = 0.49]. Further, 175/837 patients (20.91%) in the PVA group and 160/828 patients (19.32%) in the CT group had radiological subsequent fractures. No significant difference was observed between groups [RR = 0.91, 95% CI 0.71–2.12, P = 1.16]. Further, no statistical difference was observed on subgroup analysis between RCTs and non-RCTs or PVP and PKP. Conclusion: Our systematic review revealed that subsequent fractures on unoperated levels were not associated with PVA, regardless of whether they were clinical or radiological subsequent fractures. [ABSTRACT FROM AUTHOR]

Heat shock proteins (HSPs) are ubiquitous in living organisms. HSPs are an essential component for cell growth and survival; the main function of HSPs is controlling the folding and unfolding process of proteins. According to molecular function and mass, HSPs are categorized into six different families: HSP20 (small HSPS), HSP40 (J-proteins), HSP60, HSP70, HSP90, and HSP100. In this paper, improved methods for HSP prediction are proposed—the split amino acid composition (SAAC), the dipeptide composition (DC), the conjoint triad feature (CTF), and the pseudoaverage chemical shift (PseACS) were selected to predict the HSPs with a support vector machine (SVM). In order to overcome the imbalance data classification problems, the syntactic minority oversampling technique (SMOTE) was used to balance the dataset. The overall accuracy was 99.72% with a balanced dataset in the jackknife test by using the optimized combination feature SAAC+DC+CTF+PseACS, which was 4.81% higher than the imbalanced dataset with the same combination feature. The Sn, Sp, Acc, and MCC of HSP families in our predictive model were higher than those in existing methods. This improved method may be helpful for protein function prediction. [ABSTRACT FROM AUTHOR]

Through controlling the charge resonance enhanced ionization process of the isotope molecules of hydrogen molecular ion, deuterium molecular ion and tritium molecular ion, the intense single harmonic emission event has been produced, which is beneficial to generate the single attosecond pulse. Moreover, the optimal laser parameter combinations for producing the intense harmonic spectra and attosecond pulses have been shown from 4 × 1014 W/cm2 to 7 × 1014 W/cm2. Further, by properly adding a half-cycle unipolar pulse, the selected single harmonic emission event can be further extended, which can support the shorter attosecond pulse with higher photon energy. Finally, by superposing these harmonics, a number of intense attosecond pulses shorter than 40 as can be obtained. [ABSTRACT FROM AUTHOR]

Recently, person re-identification (PR-ID) has attracted numerous of research interest because of its broad applications. However, most of the existing PR-ID models always follow the supervised framework, which requires substantial labeled data. In fact, it is often very hard to get enough labeled training samples in many practical application scenarios. To overcome this limitation, some semi-supervised PR-ID methods have been presented more recently. Although some of these semi-supervised models achieve satisfied results, there is still much space to improve. In this paper, we propose a novel semi-supervised PR-ID by similarity-embedded cycle GANs (SECGAN). Our SECGAN model can learn cross-view features with limited labeled data by using cycle GANs. Simultaneously, to further enhance the ability of cycle GANs so that it can extract more discriminative and robust features, similarity metric subnet and specific features extracting subnet are embedded into cycle GANs. Extensive experiments have been conducted on three public PR-ID benchmark datasets, and the experimental results show that our proposed SECGAN approach outperforms several typical supervised methods and the existing state-of-the-art semi-supervised methods including traditional and deep learning semi-supervised methods. [ABSTRACT FROM AUTHOR]

Application programming interface (API) is an important form of software reuse. API documentations, such as API specifications, tutorials, and online forums, are valuable learning resources for reusing the APIs. In recent years, many data‐driven API documentation mining (ADM) methods have been proposed. These methods mine API documentations and return API‐related information to help developers better understand and reuse APIs. These methods treat documentations as unstructured data and apply various data mining techniques to analyze the documentation data. Currently, there is no comprehensive review of the data‐driven approach to API documentation mining. This review aims to fill in this gap by analyzing and discussing the state of the art ADM papers. We survey 32 representative papers published in prominent software engineering journals and conferences in recent 5 years (January 2014–July 2019). We analyze their mining tasks, mined data, problems, data mining techniques, and evaluation metrics. Based on the survey results, we point out research challenges and future research directions in this area. This article is categorized under:Application Areas > Science and Technology [ABSTRACT FROM AUTHOR]

Video-based person re-identification (re-id), which aims to match people through videos captured by non-overlapping camera views, has attracted lots of research interest recently. In this paper, we first propose a novel hybrid 2D and 3D convolution-based recurrent neural network (HCRN) for video-based person re-id task. Specifically, the 3D convolutional module can explore the local short-term fast-varying motion information, while the recurrent layer can leverage the global long-term spatial–temporal information. Based on HCRN, we design a scale-fusion framework to make full use of features of different scales to further improve the performance of video-based person re-id. More concretely, the scale-fusion framework preserves a complete subnetwork similar to HCRN for each scale to extract features and exchanges information between all subnetworks at several stages of the framework. Besides, we propose a training method called species invasion to further improve the performance of HCRN and scale-fusion framework by utilizing a large amount of unlabeled data. Experimental results on the publicly available PRID 2011, iLIDS-VID and MARS multi-shot pedestrian re-id datasets demonstrate the effectiveness of the proposed HCRN, scale-fusion framework and species invasion training method. [ABSTRACT FROM AUTHOR]

Background: There has been an increasing number of children with congenital heart disease that undergo primary or second systemic-pulmonary shunt, while there are few reports on the second systemic-pulmonary shunt. Therefore, this study summarizes the experience of second systemic-pulmonary shunt for congenital heart disease in our hospital.Methods and Results: Sixty-five children with congenital heart disease who underwent systemic-pulmonary shunt for the second time in our hospital were analyzed. At the early stage after the operation, cyanosis improved and SpO2 significantly increased. One patient died in hospital (1.54%) and the causes of death were aggravated atrioventricular regurgitation, low cardiac output syndrome, and liver failure. Early complications occurred in 18 patients (27.7%). All the children were rechecked in our hospital every 3-6 months and the McGoon index significantly increased.Conclusion: Systemic-pulmonary artery shunt can promote pulmonary vascular development, improve cyanosis symptoms, and increase the chance of radical treatment in children with pulmonary vascular dysplasia. [ABSTRACT FROM AUTHOR]

Oral squamous cell carcinoma (OSCC) is the most common malignancy in the oral cavity, which accounts for >90% of all diagnosed oral cancers. 2-phenylethynesulfonamide (PES) was known as a selective heat shock protein 70 (Hsp70) function inhibitor, which induced cytotoxic effects on various tumor cell types, but showed to be less toxic to normal cells. However, no associated evaluation of PES on OSCC was found. In the present study, the proliferation of OSCC cells treated with PES was analyzed using a CCK-8 assay. The effects of PES on the cell cycle and apoptosis of OSCC cells were determined by flow cytometric analyses. Expression of associated protein was determined by Western blot analysis. The results of the present study showed that PES inhibited the proliferation of OSCC cell lines in vivo and in vitro. PES induced apoptosis and arrested the cell cycle of OSCC cells. PES inhibited the expression of X-linked inhibitor of apoptosis protein (XIAP), baculoviral IAP repeat containing 2 (c-IAP1), phosphorylated AKT (p-AKT), and phosphorylated extracellular signal-regulated kinase (p-ERK). Additionally, knockdown of Hsp70 enhanced the effects of PES. By contrast, overexpression of Hsp70 attenuated the inhibitory effects of PES on cell viability. PES disrupted the interaction between Hsp70 and XIAP. In conclusion, the present study demonstrated that PES suppresses the growth of OSCC cells through Hsp70-dependent mechanism. [ABSTRACT FROM AUTHOR]

In this study, the authors study the problem of tensor completion, in particular for three‐dimensional arrays such as visual data. Previous works have shown that the low‐rank constraint can produce impressive performances for tensor completion. These works are often solved by means of Tucker rank. However, Tucker rank does not capture the intrinsic correlation of the tensor entries. Therefore, the authors propose a new proximal operator for the approximation of tensor nuclear norms based on tensor‐train rank‐1 decomposition via the singular value decomposition. The proximal operator will perform a soft‐thresholding operation on tensor singular values. In addition, the low‐rank constraint can capture the global structure of data well, but it does not exploit local smooth of visual data. Therefore, they integrate total variation as a regularisation term into low‐rank tensor completion. Finally, they use a primal–dual splitting to achieve optimisation. Experimental results have shown that the proposed method, can preserve the multi‐dimensional nature inherent in the data, and thus provide superior results over many state‐of‐the‐art tensor completion techniques. [ABSTRACT FROM AUTHOR]

A broad-spectrum substrate-imprinted adsorption and crosslinking double immobilized pectinase (SDP) was prepared using a universal modified pectin obtained through enzymatic hydrolysis as the imprinting substrate. Its structure was characterized by infrared spectroscopy, circular dichroism, and scanning electron microscopy. The results showed that 1) cross-linking increased the Schiff base in SDP, 2) immobilization barely changed the secondary structure such as α-helix and β-sheet of SDP, and 3) adhesives were evenly distributed on the surface after immobilization. Studies on the enzymatic properties of SDP showed that the substrate imprinting significantly improved heat resistance and neutralization resistance of SDP. For example, the relative activity of SDP at 35 to 75 °C and at pH 4.4 to 6.5 was 5% and 15% more than that of the adsorption and crosslinking double immobilized pectinase (DP), respectively. In addition, after 8 cycles of use, the relative enzyme activity of SDP still reached 39.5%. Moreover, use of SDP decreased the cation demand in whitewater by 10% compared with DP. Overall, the use of a broad-spectrum substrate for imprinting to obtain SDP provides a new idea and method for using pectinase in in complex systems such as juice clarification and wastewater treatment. [ABSTRACT FROM AUTHOR]

• We have proposed a Hard and Easy Negative samples mining based Distance learning (HEND) approach for person re-identification. • We have designed a symmetric triplet constraint for the proposed HEND approach. • We have proposed a Projection based HEND (PHEND) approach, which simultaneously learns a projection matrix and a distance metric. • We have conducted extensive experiments in this paper to evaluate our approaches. Distance learning is an effective technique for person re-identification. In practice, the hard negative samples usually contain more discriminative information than the easy negative samples. Therefore, it's necessary to investigate how to make full use of the discriminative information conveyed by different types of negative samples in the distance learning process. In this paper, we propose a H ard and E asy N egative samples mining based D istance learning (HEND) approach for person re-identification, which learns the distance metric by designing different objective functions for hard and easy negative samples, such that the discriminative information contained in negative samples can be exploited more effectively. Moreover, considering that there usually exist large differences between the images captured by different cameras, we further propose a projection-based HEND approach to reduce the influence of between-camera differences to the re-identification. Experimental results on seven pedestrian image datasets demonstrate the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

Person re-identification (re-id) plays an important role in video surveillance and forensics applications. In many cases, person re-id should be conducted between video clips, i.e., given a query pedestrian video from one camera, the re-id system should retrieve the video clips containing the same person from other cameras. However, person re-id between videos, which we call video-based person re-id, has not been well studied. In this paper, we propose a visual-appearance-level and spatial-temporal-level dictionary learning (VSDL) approach for video-based person re-id. Specifically, we first employ two kinds of models to represent each walking cycle in the video, i.e., visual-appearance features of all frames within the walking cycle, and a spatial-temporal feature vector. By separately learning a visual-appearance-level dictionary and a spatial-temporal-level dictionary from two kinds of representations, each walking cycle can be represented as a coding coefficient. To enhance the discriminative ability of the obtained coding coefficients, we design a representation coefficient discriminant term for VSDL. Experiments on the public iLIDS-VID and PRID 2011 datasets demonstrate the effectiveness of VSDL. [ABSTRACT FROM AUTHOR]

To assess outcomes in obese patients with chronic obstructive pulmonary disease (COPD) who sustained an osteoporotic vertebral compression fracture (OVCF) treated by percutaneous vertebroplasty (PVP) in the improved prone position and right lateral position. Between January 2015 and May 2016, a total of 60 patients were enrolled in this randomized controlled study. Patients in group A were placed in the improved prone position for a bilateral transpedicular technique, and those in group B were placed in the right lateral position for a left transverse process-pedicle approach. Clinical and radiologic outcomes were assessed and compared between the 2 groups during the 12-month follow-up period. All operations were successfully completed without any serious sequelae. The operation time, fluoroscopic time, scores for respiratory condition during the operation, intravertebral cement volume, and incidence of cement leakage were significantly greater in group A compared with group B (P < 0.01). During the follow-up period, all patients in both groups experienced significant improvement in pain relief. Satisfactory functional improvement was obtained at 3 months postoperatively. Treatment of obese patients with COPD suffering from painful OVCF by PVP in both the improved prone position with a bilateral technique and the right lateral position with a unilateral technique was relatively safe and effective. However, unilateral PVP in the right lateral position was associated with a shorter operation time, limited fluoroscopic time, and minimal cement leakage. [ABSTRACT FROM AUTHOR]

Single-ion polymer electrolytes (SIPEs) with high Li-ion transference number (t Li +≈1) are promising candidates for inhibiting the growth of lithium dendrites in lithium metal batteries (LMBs). However, it remains challenging to develop SIPEs applicable to high-performance LMBs due to their relatively low ionic conductivity and poor mechanical strength. Herein, an aromatic single-ion conductor (LiPSBI) with high Li-ion concentration is elaborately designed, yielding porous and mechanically robust SIPE membranes (NSIPM) when mixed with aliphatic poly (vinylidene fluoride-hexafluoropropylene) P(VDF-HFP) binder via "structural self-assembly" method. As expected, the as-prepared NSIPM porous membranes can simultaneously exhibit a high porosity of 41.4%, a considerable organic solvent uptake of 181.0%, and excellent mechanical strength of 20.5 MPa. Notably, the LiPSBI-based gel NSIPM demonstrates an ionic conductivity of 8.15 × 10−5 S cm−1 at 25 °C, which is almost twice that of the single-ion electrolyte with low Li-ion concentration (4.74 × 10−5 S cm−1). Consequently, the Li||LiFePO 4 cells using the gel NSIPM display remarkable cycling durability for several hundred cycles while delivering high discharge specific capacities of 148.4 mA h g−1 and 122.9 mA h g−1 at 0.2C and 1 C, respectively. In addition, the Li/Li symmetric cells assembling the gel NSIPM can effectively alleviate concentration polarization and inhibit the lithium dendrites growth, which is responsible for an exceptionally steady striping/plating process with a low overpotential over 1300 h at 2.5 mA cm−1 at 25 °C. This work provides a new strategy to prepare high-performance SIPEs by increasing the concentration of charge carriers. [Display omitted] • A new single-ion conductor containing high Li-ion concentration is well-designed. • The SIPE-based porous membranes are prepared via structural self-assembly method. • Ionic conductivity and mechanical strength of the gel SIPEs are highly improved. • Li.||LiFePO 4 cells with the gel SIPEs run stably at 1 C for 1000 cycles at 25 °C [ABSTRACT FROM AUTHOR]

• We propose a novel method which takes advantage of the depth data in the source domain and handles the domain distribution mismatch under label inequality scenario simultaneously. • Different from conventional unsupervised domain adaptation (UDA), we present a new scenario called unequal UDA, which can improve the recognition performance when the source categories are more than the target ones. • The empirical results demonstrate that proposed method can achieve the state-of-the-art performance than other methods on five real-world domain adaptation image dataset pairs. Most recent unsupervised domain adaptation (UDA) approaches concentrate on single RGB source to single RGB target task. They have to face the real-world scenario, where the source domain can be collected from multiple modalities, e.g. , RGB data and depth data. Our work focuses on a more practical and challenging scenario which recognizes RGB images by learning from RGB-D data under the label inequality scenario. We are confronted with three challenges: multiple modalities in the source domain, domain shifting problem and unequal label numbers. To address the aforementioned settings, a novel method, referred to as Domain depth Embedding Transfer (DdET) is proposed, which takes advantage of the depth data in the source domain and handles the domain distribution mismatch under label inequality scenario simultaneously. We conduct comprehensive experiments on five cross domain image classification tasks and observe that DdET can perform favorably against state-of-the-art methods, especially under label inequality scenario. [ABSTRACT FROM AUTHOR]

To explore the effect of houttuyn berberine on the biological behavior of nasopharyngeal carcinoma cells by regulating circ-SMARCA5/microRNA-346 pathway. Nasopharyngeal carcinoma cells C666-1 were divided into control group, houttuyn berberine (1, 2, 4 µg/ml) group, plasmid cloning deoxyribonucleic acid group-circ-SMARCA5 group, houttuyn berberine+si-circ-SMARCA5 group, and houttuyn berberine+microRNA-346 group. Real-time quantitative polymerase chain reaction detected the expression levels of circ-SMARCA5 and microRNA-346. Cell counting kit, plate cloning experiment, flow cytometry, wound healing assays and Transwell assays were performed to assess the cell viability, clone formation, apoptosis, migration and invasion ability of C666-1. The targeting relationship between circ-SMARCA5 and microRNA-346 was verified with the aid of dual luciferase experiment. In comparison with the control group, the cell viability of C666-1 cells, microRNA-346 expression, wound healing rate, clone formation numbers, invasive numbers in the houttuyn berberine (1, 2, 4 µg/ml) group were increased, and the expression of circ-SMARCA5 and apoptosis rate were increased (p<0.05). Compared with plasmid cloning deoxyribonucleic acid group, the cell viability of C666-1 cells, wound healing rate, microRNA-346 expression in the plasmid cloning deoxyribonucleic acidcirc-SMARCA5 group were reduced, the apoptosis rate was increased, invasive numbers and clone formation numbers were reduced (p<0.05). Circ-SMARCA5 directly bound to microRNA-346. Compared with the houttuyn berberine group, the cell viability of C666-1 cells, clone formation numbers and invasive numbers were increased in the houttuyn berberine+si-circ-SMARCA5 group and houttuyn berberine+microRNA-346 group, the apoptotic rate was decreased, and the wound healing rate was increased (p<0.05). Houttuyn berberine could inhibit nasopharyngeal carcinoma cells' malignant proliferation, migration and invasion, and induce cell apoptosis. The mechanism is associated with the up-regulation of circ-SMARCA5/microRNA-346 pathway. [ABSTRACT FROM AUTHOR]

There are about 500,000 species of plants on the earth, and their growing conditions differ. Making good use of these data can help achieve high-quality and high-yield agriculture. However, until now there is not yet a satisfied method to match suitable plants growing conditions with natural environment factors that plants live by. Thus this paper innovatively proposes a solution to the problem making use of the huge database formed by a variety of natural environment and plants growing conditions adopting matching algorithm based on weighted multidimensional tree. First, an auxin model is constructed. Then, based on it a weighted multidimensional tree is built for search purpose. The weighted multidimensional tree is an M-tree, which regional search first locates a certain area through key auxins, and then realizes accurate matching by means of similarity matching. The analysis and simulation results show that the proposed model is superior in efficiency to KD- tree and SV3- tree in the big data environment. Thus the mode proposed is ideal for searching in big data environments. [ABSTRACT FROM AUTHOR]

Highlights • Fear memory extinction was impaired in adolescent mice. • Unable to deal with the fear memory was accompanied by depressive-like behaviors. • Non-coping with these fear memories may result from the facilitation of LTP induction. • Presynaptic mechanisms may be involved in the process of impaired fear memory extinction. Abstract Fear is the emotion that is best understood in terms of brain mechanisms. And the management of fear memories is important when facing mental health disorders such as post-traumatic stress. Adolescence is a transitional stage of physical and psychological human development and the ability to deal with the fear memory in adolescence may be a potent factor for developing mental disorders in adulthood. However, little is known about the direct relationship between the ability to deal with the fear memory and appearance of depressive-like behaviors. To assess this, we used a model of associative learning to induce the fear memories and evaluated the depressive-related behaviors in the fear memory extinction process and its underlying cellular mechanisms from adolescent and adult mice. We found that, compared with adult mice, the adolescent mice exhibited impaired fear memory extinction in contextual fear conditioning extinction process. Meanwhile, impaired fear memory extinction was accompanied by more immobility time in forced swimming test, which was used to assess the depressive-like state. Consistent with this, we observed that long-term potentiation (LTP) induction in the hippocampal CA1 region of adolescent mice persistently larger in extinction process in adolescent mice, which was involved the presynaptic mechanism. Together, our results suggest that adolescent mice exhibited a disability to extinct the fear memory, and that this may lead to the depressive-like behaviors via presynaptic-mediated synaptic plasticity. These findings may give us a new insight in the knowledge of some mental disorders caused by persistent unpleasant memories. [ABSTRACT FROM AUTHOR]

Introduction: This single-centre, retrospective study aimed to assess the efficacy and safety of flexible ureteroscopy (FURS) combined with holmium laser lithotripsy in treating children with upper urinary tract stones. Methods: From June 2014 to October 2015, a total of 100 children (74 boys and 26 girls) with upper urinary tract stones were treated using FURS. A 4.7 Fr double-J stent was placed two weeks before operation. Patients were considered stone-free when the absence of residual fragments was observed on imaging studies. The preoperative, operative, and postoperative data of the patients were retrospectively analyzed. Results: A total of 100 pediatric patients with a mean age of 3.51±1.82 years underwent 131 FURS and holmium laser lithotripsy. Mean stone diameter was 1.49±0.92 cm. Average operation time was 30.8 minutes (range 15-60). The laser power was controlled between 18 and 32 W, and the energy maintained between 0.6 and 0.8 J at any time; laser frequency was controlled between 30 and 40 Hz. Complications were observed in 69 (69.0 %) patients and classified according to the Clavien system. Postoperative hematuria (Clavien I) occurred in 64 (64.0 %) patients. Postoperative urinary tract infection with fever (Clavien II) was observed in 8/113 (7.1%) patients. No ureteral perforation and mucosa avulsion occurred. The overall stone-free rate of single operation was 89/100 (89%). Stone diameter and staghorn calculi were significantly associated with stone-free rate. Conclusions: FURS and holmium laser lithotripsy is effective and safe in treating children with upper urinary tract stones. [ABSTRACT FROM AUTHOR]