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Two vanadium(V) complexes derived from the bromo and chloro-substituted hydrazones N’-(4-bromo-2-hydroxybenzylidene)- 2-chlorobenzohydrazide (H2L1) and N’-(3-bromo-5-chloro-2-hydroxybenzylidene)-3-methylbenzohydrazide (H2L2) with the formula [VOL1(OCH3)(CH3OH)] (1) and [VOL2(OCH3)(CH3OH)] (2) were newly synthesized and characterized by IR, UV-Vis and 1H NMR spectroscopy. The structures of H2L1 and the complexes were further confirmed by single crystal X-ray diffraction. Both vanadium complexes are mononuclear, with the metal atoms coordinated by the hydrazone ligands, methanol ligands, and methanolate ligands, and the oxo groups, forming octahedral geometry. The hydrazones and the vanadium complexes were assayed for the antimicrobial activities on Bacillus subtilis, Staphylococcus aureus, Escherichia coli, and Pseudomonas fluorescence, and the fungi Candida albicans and Aspergillus niger. The existence of the bromo and chloro groups in the hydrazone ligands may improve the antimicrobial property.

Posttraumatic stress disorder subjects usually show impaired recall of extinction memory, leading to extinguished fear relapses. However, little is known about the neural mechanisms underlying the impaired recall of extinction memory. We show here that the activity of dorsal hippocampus (dHPC) to infralimbic (IL) cortex circuit is essential for the recall of fear extinction memory in male mice. There were functional neural projections from the dHPC to IL. Using optogenetic manipulations, we observed that silencing the activity of dHPC-IL circuit inhibited recall of extinction memory while stimulating the activity of dHPC-IL circuit facilitated recall of extinction memory. “Impairment of extinction consolidation caused by” conditional deletion of extracellular signal-regulated kinase 2 (ERK2) in the IL prevented the dHPC-IL circuit-mediated recall of extinction memory. Moreover, silencing the dHPC-IL circuit abolished the effect of intra-IL microinjection of ERK enhancer on the recall of extinction memory. Together, we identify a dHPC to IL circuit that mediates the recall of extinction memory, and our data suggest that the dysfunction of dHPC-IL circuit and/or impaired extinction consolidation may contribute to extinguished fear relapses.

The nectar of Camellia reticulata Lindl. contains sugar, amino acids and other nutritional components, suggesting that it could be developed for food and food additives. To understand the effects of the nectar on human health, we investigated its chemical constituents. Two new flavonoid glycosides, cameretiins A and B (1 and 2), and two known flavonoid glycosides, kaempferol 3-O-(2''-O-E-p-coumaroyl)-β-D-glucopyranoside (3) and tiliroside (4) were obtained from the nectar of Camellia reticulata Lindl. Their structures were determined based on analysis of their spectroscopic data and by comparison with 1D NMR spectroscopic data of known compounds reported in the literature. Compounds (1-4) were first isolated from the nectar of Camellia reticulata Lindl.

With a 10% reversible compressive strain in more than 10 deformation cycles, the shape memory polymer composites (SMPCs) could be used for deployable structure and releasing mechanism. In this paper, without traditional electro-explosive devices or motors/controllers, the deployable SMPC flexible solar array system (SMPC-FSAS) is studied, developed, ground-based tested, and finally on-orbit validated. The epoxy-based SMPC is used for the rolling-out variable-stiffness beams as a structural frame as well as an actuator for the flexible blanket solar array. The releasing mechanism is primarily made of the cyanate-based SMPC, which has a high locking stiffness to withstand 50 g gravitational acceleration and a large unlocking displacement of 10 mm. The systematical mechanical and thermal qualification tests of the SMPC-FSAS flight hardware were performed, including sinusoidal sweeping vibration, shocking, acceleration, thermal equilibrium, thermal vacuum cycling, and thermal cycling test. The locking function of the SMPC releasing mechanisms was in normal when launching aboard the SJ20 Geostationary Satellite on 27 Dec., 2019. The SMPC-FSAS flight hardware successfully unlocked and deployed on 5 Jan., 2020 on geostationary orbit. The triggering signal of limit switches returned to ground at the 139 s upon heating, which indicated the successful unlocking function of SMPC releasing mechanisms. A pair of epoxy-based SMPC rolled variable-stiffness tubes, which clapped the flexible blanket solar array, slowly deployed and finally approached an approximate 100% shape recovery ratio within 60 s upon heating. The study and on-orbit successful validation of the SMPC-FSAS flight hardware could accelerate the related study and associated productions to be used for the next-generation releasing mechanisms as well as space deployable structures, such as new releasing mechanisms with low-shocking, testability and reusability, and ultra-large space deployable solar arrays.

Introduction Diabetic patients are often accompanied by complications of diabetic vascular disease, which could lead to heart failure or stroke. In this work, we explored the role of miR-503/Apelin-12 in diabetic angiopathy (DA) in vitro. Methods ELISA and qPCR were applied to assess the expression of miR-503 and Apelin-12 in high glucose (HG)-treated microvascular endothelial cells (HMEC-1). The effects of miR-503 on apoptosis, inflammation and oxidative stress were assessed by flow cytometry, western blotting, qPCR, and ELISA. The interaction between miR-503 and Apelin-12 was evaluated by dual-luciferase reporter assay, qPCR and ELISA, respectively. Western blotting was performed to examine the function of miR-503/Apelin-12 on JNK and p38MAPK activation. Results MiR-503 was markedly increased and Apelin-12 was decreased in HG-treated HMEC-1 cells. MiR-503 inhibitor significantly assuaged apoptosis, inflammation and oxidative stress in HMEC-1 cells. MiR-503 could specifically bind to the 3′UTR of Apelin and inversely downregulate Apelin-12 expression. Furthermore, Apelin-12 suppressed apoptosis, inflammation and oxidative stress. Inhibition of Apelin-12 could partially reverse the decrease of p-JNK and p-p38 expression levels induced by miR-503 suppression. Conclusion In HG-induced microvascular cells injury, miR-503/Apelin-12 enhances inflammation and oxidative stress by regulating JNK and p38MAPK pathway, suggesting a potential therapeutic target for DA.

Current methods can illuminate the genome-wide activity of CRISPR–Cas9 nucleases, but are not easily scalable to the throughput needed to fully understand the principles that govern Cas9 specificity. Here we describe ‘circularization for high-throughput analysis of nuclease genome-wide effects by sequencing’ (CHANGE-seq), a scalable, automatable tagmentation-based method for measuring the genome-wide activity of Cas9 in vitro. We applied CHANGE-seq to 110 single guide RNA targets across 13 therapeutically relevant loci in human primary T cells and identified 201,934 off-target sites, enabling the training of a machine learning model to predict off-target activity. Comparing matched genome-wide off-target, chromatin modification and accessibility, and transcriptional data, we found that cellular off-target activity was two to four times more likely to occur near active promoters, enhancers and transcribed regions. Finally, CHANGE-seq analysis of six targets across eight individual genomes revealed that human single-nucleotide variation had significant effects on activity at ~15.2% of off-target sites analyzed. CHANGE-seq is a simplified, sensitive and scalable approach to understanding the specificity of genome editors. The genome-wide activity of Cas9 is measured in unprecedented detail.

We put forward and demonstrate a angle-of-arrival (AOA) based visible-light-positioning (VLP) system using quadrant-solar-cell (QSC) and third-order ridge regression machine learning (RRML) to improve the positioning accuracy.

In order to improve the management of nitrogen (N) fertilization in pear orchards, we investigated the effects of application timing on the distribution, storage, and remobilization of N in mature pear trees in a field experiment at Jingtai County, Gansu Province, China. Nine trees were selected for the experiment and each received equal aliquots of 83.33 g N in the autumn, spring, and summer, with 15N-labeled (NH4)2SO4 used in one of the aliquots each season. Results showed that the (15N H4)2SO4 applied in the autumn remained in the soil during the winter. In the following spring this N was absorbed and rapidly remobilized into each organ, especially new organs (leaves, fruit and new shoots). The 15N supplied in spring was rapidly transported to developing fruit between the young fruit and fruit enlargement stages. 15N from the summer application of fertilizer was mainly stored in the coarse roots over the winter, then was mobilized to support growth of new organs in spring. In conclusion, for pear trees we recommend that the autumn application of N-fertilizer be soon after fruit harvest in order to increase N stores in fine roots. Spring application should be between full bloom and the young fruit stages to meet the high N demands of developing fruit. Summer application of fertilizer at the fruit enlargement stage does not contemporaneously affect the growth of pears, but increases the N stored in coarse roots, and in turn the amount available for remobilization in spring.

We put forward and experimentally demonstrate a second order machine-learning (ML) based visible-light-positioning (VLP) system using simple linear interpolation algorithm to reduce the training samples required in the ML algorithm. Algorithms of the second order regression ML model using 2,430 training samples; and using the reduced training samples of 570 with and without the proposed linear interpolation are compared and discussed. We can observe that the positioning accuracy of using training samples of 570 with the proposed interpolation can have similar performance when compared with using 2,430 training samples. The training samples are reduced by ~76.5%. Here, off-the-shelf LED lamps and low bandwidth electrical and optical components are employed; and the system is cost-effective. Good quality on-off keying (OOK) identifier (ID) signals are retrieved after frequency down-conversion from 20 kHz, 40 kHz and 60 kHz without and with optical background noises respectively.

We present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7 km × 7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions ("baselines") consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter ("FLExKF") system and with TM5-4DVAR inversions at 1° × 1° resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km × 7 km resolution allow to better reproduce the observations than the TM5 4DVAR simulations at 1° × 1°. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the United Kingdom and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.

Purpose: This retrospective study aimed to determine the most suitable cut-off value of Ki-67 expression and further explore the prognostic effect of Ki-67 in hormone receptor positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer;Methods: We assessed the Ki-67 expression of 956 patients with HR+/HER2 breast cancer diagnosed in General Hospital of Ningxia Medical University from 2015 to 2019 by immunohistochemistry, The disease-free survival (DFS) was defined as the time from postoperative to the first local recurrence, distant metastasis or death of the disease. Results: 22.5% was used as the cut-off for low/high Ki-67 expression in HR+/HER2- breast cancer; compared with the commonly used threshold value of Ki-67(14%) in clinic at present, the consistency of the two value is moderate (Kappa = 0.484, PPPConclusions: The cut-off value of Ki-67 expression in HR+/HER2- breast cancer is 22.5%; The patients with Ki-67 ≥ 22.5% had a 2.937 higher risk of early recurrence and metastasis than the patients with Ki-67 < 22.5%.

New reports provide further insight into the role of the transcription factor BATF in pivoting the differentiation of CD8+ T cells away from T cell exhaustion and facilitating the transition of these cells into potent effectors.

Several studies have indicated possible associations between age and the prognosis of breast cancer (BC), but limited data are available from hospital-based multicenter studies in China. This study aimed to explore the associations between age at initial diagnosis of BC and the risk of recurrence or metastasis among Chinese women with newly diagnosed advanced breast cancer (ABC) and provide treatment decision support for BC patients of different ages to medical workers.The medical records of patients newly diagnosed with ABC were obtained from 21 hospitals in seven geographic regions in China from 2012 to 2014. Patients' general information, clinicopathological features at first diagnosis, treatment information, and prognosis were retrospectively collected based on the self-designed case report form (CRF). Cox proportional hazards regression models were used to determine hazard ratios (HR) and 95% confidence intervals (CI) for the associations between age groups and the risk of recurrence and metastasis.A total of 1,852 cases were included in the final analysis. Age at initial diagnosis was shown to be significantly related to hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, molecular subtypes, and the number of lymph node metastasis (all P0.05). Patients aged35 years were more likely to have bone metastasis (45.6%). Patients aged ≥65 years had a lower percentage of receiving surgery (87.1%), adjuvant chemotherapy (61.3%), adjuvant radiotherapy (35.5%), and adjuvant endocrine therapy (30.6%) than the other groups (all P0.05). Compared with patients aged35 years, the risk of recurrence or metastasis in those aged 55-64 years was significantly higher (HRAge at initial diagnosis is related to the clinicopathological characteristics and treatment pattern. Although the risk of site-specific metastasis varies by age, age is not an independent factor influencing the risk of total recurrence and metastasis. In accordance with current clinical practice guidelines for BC, however, precise treatment shall be chosen personally for patients whose ages at initial diagnosis are different.

Acidosis is a hallmark of ischemic stroke and a promising neuroprotective target for preventing neuronal injury. Previously, genetic manipulations showed that blockade of acid-sensing ion channel 1a (ASIC1a)-mediated acidotoxicity could dramatically alleviate the volume of brain infarct and restore neurological function after cerebral ischemia. However, few pharmacological candidates have been identified to exhibit efficacy on ischemic stroke through inhibition of ASIC1a. In this work, we examined the ability of a toxin-inspired compound 5b (C5b), previously found to effectively inhibit ASIC1a in vitro, to exert protective effects in animal models of ischemic stroke in vivo. We found that C5b exerts significant neuroprotective effects not only in acid-induced neuronal death in vitro but also ischemic brain injury in vivo, suggesting that ASIC1a is a druggable target for therapeutic development. More importantly, C5b is able to cross the blood brain barrier and significantly reduce brain infarct volume when administered intravenously in the ischemic animal model, highlighting its systemic availability for therapies against neurodegeneration due to acidotoxicity. Together, our data demonstrate that C5b is a promising lead compound for neuroprotection through inhibiting ASIC1a, which warrants further translational studies.

We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and δ13C of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH4 and δ13C measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δ13C data, and assimilating δ13C data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85 % of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5∘ N and 23.5∘ S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δ13C data. We find that at global and continental scales, δ13C data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current δ13C measurement coverage. Finally, we find that the largest uncertainty in using δ13C data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink.

Dental calculus is a potential material that can be used for assessing chronic exposure to trace heavy metals in oral cavity as it is a long-term reservoir. The aim of this study was to investigate the correlation between dental calculus copper levels and risk of oral submucous fibrosis (OSF) due to chewing dried areca-nut quids in Mainland China. This study included 34 OSF (grade 1) sufferers with dried areca-nut quids chewing as the patient group and 23 healthy individuals without areca-nut chewing as the control group. The dental calculus sample was obtained from all 57 participants and evaluated by inductively coupled plasma mass spectrometry (ICP-MS) for dental calculus level of copper. This work revealed that the mean copper level of dental calculus was significantly higher in OSF (grade 1) sufferers with areca-nut chewing than those in healthy individuals without areca-nut chewing (p 0.001). This work provided an evidence to support that there may be a positive correlation between elevated levels of copper in dental calculus caused by chewing dried areca-nut quids and an increased risk of developing OSF in Mainland China.

This study proposes a novel bidirectional-switched-capacitor-based interleaved converter. In view of the shortcomings of the two well-known unidirectional-switched-capacitor-based interleaved converters, this study improves such converters through combining the novel structure of a switched capacitor circuit. The first effort was to overcome the drawback of the Cockcroft–Walton-based interleaved converter, whose circuit impedance and ripple cause a serious output voltage drop. The second was to solve the Dickson-based interleaved converter with its capacitors subjected to high-voltage stress. The third was to relax the unidirectional boost function of the Cockcroft–Walton- or Dickson-based interleaved converter. This study avoided not only high-circuit impedance and ripple, as in the case of the Cockcroft–Walton converter, but also it had lower component stress than the Dickson converter. In addition, this study redesigned the unidirectional boost function of the Cockcroft–Walton- or Dickson-based interleaved converter, such that the switch-capacitor-based interleaved converters became bidirectional DC-DC converters. Finally, the experimental results are provided to verify the feasibility of the proposed method.

Paris polyphylla var. yunnanensis, a medicinal plant that originated in Yunnan (China), has been over-harvested in the wild population, resulting in its artificial cultivation. Given the negative environmental impacts of the excessive use of phosphorus (P) fertilization, the application of organophosphate-degrading bacteria (OPDB) is a sustainable approach for improving the P use efficiency in Paris polyphylla var. yunnanensis production. The present work aimed to analyze the effects of three organic phosphate-solubilizing bacteria of Bacillus on the yield and quality of P. polyphylla var. yunnanensis and the P concentrations in the soil. All the inoculation treatments distinctly increased the rhizome biomass, steroidal, and total saponin concentrations of the rhizomes and the Olsen-P and organic P in the soil. The highest growth rate of rhizomes biomass, steroidal saponins, available phosphorus, and total phosphorus content was seen in the S7 group, which was inoculated with all three OPDB strains, showing increases of 134.58%, 132.56%, 51.64%, and 17.19%, respectively. The highest total saponin content was found in the group inoculated with B. mycoides and B. wiedmannii, which increased by 33.68%. Moreover, the highest organic P content was seen in the group inoculated with B. wiedmannii and B. proteolyticus, which increased by 96.20%. In addition, the rhizome biomass was significantly positively correlated with the saponin concentration, together with the positive correlation between the Olsen-P and organic P and total P. It is concluded that inoculation with organophosphate-degrading bacteria improved the biomass and medicinal ingredients of the rhizome in P. polyphylla var. yunnanensis, coupled with increased soil P fertility, with a mixture of the three bacteria performing best.

The influence of engine speed, torque, oil temperature, and piston liner clearance on the block vibration was studied with experimental test and wavelet packet decomposition method (WPD). The wavelet packet function of db10 and decomposition level of four was confirmed based on the Shannon entropy. The frequency analysis of the block vibration measured at motor-driven condition showed that the spectrum energy was mainly concentrated in the range of 4–5, 10–15, and 20–25 kHz. The energy of each frequency band obtained from WPD was contrasted at different engine speed, torque, oil temperature, and piston-liner clearance conditions. On this basis, the interaction between different factors was further investigated. The sensitive frequency band of block vibration was confirmed for different factors.

The accurate prediction of wind power has a huge impact on the grid connection and dispatching of the power system. In order to make the prediction accuracy of wind power higher, this paper proposes a combined forecasting model based on the combination of numerical weather prediction (NWP) and wind power time series, called gray wolf algorithm-wavelet neural network-variational mode decomposition-long short-term memory-Q-learning (GWO-WNN-VMD-LSTM-Q-learning). First, the wind power prediction (WPP) is implemented based on the NWP, and prediction result 1 is obtained. In this stage, the wavelet neural network (WNN), which is optimized by the gray wolf algorithm (GWO), is used for prediction. Then, the historical time series of wind power is subjected to variational mode decomposition (VMD), and the decomposed sub-sequences are predicted by long short-term memory (LSTM) networks, respectively, and the prediction results of each sub-sequence are summed to obtain the prediction result 2. Finally, the Q-learning algorithm is used to superimpose prediction result 1 and result 2 on the basis of optimal weight and get the final WPP results. The simulation results demonstrate that this model's prediction accuracy is high and that it has a substantially greater predictive impact than other traditional models that merely take time series or numerical weather forecasts into account.

PurposeTo evaluate whether multiparametric magnetic resonance imaging (MRI)-based logistic regression models can facilitate the early prediction of chemoradiotherapy response in patients with residual brain gliomas after surgery.Patients and MethodsA total of 84 patients with residual gliomas after surgery from January 2015 to September 2020 who were treated with chemoradiotherapy were retrospectively enrolled and classified as treatment-sensitive or treatment-insensitive. These patients were divided into a training group (from institution 1, 57 patients) and a validation group (from institutions 2 and 3, 27 patients). All preoperative and postoperative MR images were obtained, including T1-weighted (T1-w), T2-weighted (T2-w), and contrast-enhanced T1-weighted (CET1-w) images. A total of 851 radiomics features were extracted from every imaging series. Feature selection was performed with univariate analysis or in combination with multivariate analysis. Then, four multivariable logistic regression models derived from T1-w, T2-w, CET1-w and Joint series (T1+T2+CET1-w) were constructed to predict the response of postoperative residual gliomas to chemoradiotherapy (sensitive or insensitive). These models were validated in the validation group. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were applied to compare the predictive performances of these models.ResultsFour models were created and showed the following areas under the ROC curves (AUCs) in the training and validation groups: Model-Joint series (AUC, 0.923 and 0.852), Model-T1 (AUC, 0.835 and 0.809), Model-T2 (AUC, 0.784 and 0.605), and Model-CET1 (AUC, 0.805 and 0.537). These results indicated that the Model-Joint series had the best performance in the validation group, followed by Model-T1, Model-T2 and finally Model-CET1. The calibration curves indicated good agreement between the Model-Joint series predictions and actual probabilities. Additionally, the DCA curves demonstrated that the Model-Joint series was clinically useful.ConclusionMultiparametric MRI-based radiomics models can potentially predict tumor response after chemoradiotherapy in patients with postoperative residual gliomas, which may aid clinical decision making, especially to help patients initially predicted to be treatment-insensitive avoid the toxicity of chemoradiotherapy.