Search

Purpose: A rapid and reliable method was developed and validated for the simultaneous analysis of 52 antibiotics (cephalosporins, penicillins, carbapenems, lincosamides, quinolones, nitroimidazoles, macrolides, sulfonamides, tetracyclines, glycopeptide) in urine and whole blood by high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). Method: Analytes were extracted by dilution or protein precipitation and analyzed on an Agilent 1260 HPLC system coupled to an Agilent 6470 Triple Quadrupole Mass Spectrometer. Results: The method attended method validation criteria. The limits of detection were equal or lower than 2.0 ng/mL, whereas the limits of quantification ranged from 0.1 to 10.0 ng/mL, from 0.1 to 5.0 ng/mL, in urine and whole blood, respectively. For all analytes, the bias and intra- and inter-day precision values were less than 14.7%. The ranges of recovery values of all antibiotics were 76.5–124.5% in whole blood and 76.3–121.8% in urine, values of the effects were lower than 25% in two matrices. No evidence of carryover was observed. The study of sample stability showed that almost all analytes were stable at 24 °C for 24 h, all analytes were stable at −20 °C for 14 days and at −80 °C for 30 days. Freeze–thaw cycles stability showed that antibiotics were stable except for imipenem. Autosampler stability study showed that all analytes were stable for 24 h, except for imipenem and amoxicillin. Applicability was proven by analyzing authentic whole blood (n = 86) and urine (n = 79) samples from patients under antibiotics treatment. Therefore, this method was applied to the analysis 3 forensic allergy cases, which were positive for at least one analyte. Conclusions: A simple, sensitive and high-throughput method for the simultaneous determination of different classes of antibiotics in urine and whole blood samples was developed and applied. This sensitive method was successfully applied to forensic cases. [ABSTRACT FROM AUTHOR]

Count time series exhibiting seasonal patterns are frequently encountered in practical scenarios. For example, the number of hospital emergency service arrivals may show seasonal behavior (Moriña et al. 2011 Stat Med 30:3125–3136). Numerous models have been proposed for the analysis of seasonal count time series with an unbounded support, yet seasonal patterns in bounded count time series, which are sometimes suffered in environmental science such as the number of monthly rainy-days and air quality level data, have not received formal attention. The contribution of this article lies in coping with the modeling challenges associated with seasonal count time series with a bounded support, which is beneficial for enhancing the applicability of environmental science data. This is achieved by introducing a seasonal structure and seasonally varying model parameters into the first-order binomial autoregressive (BAR(1)) model (McKenzie 1985 J Am Water Resour Assoc 21:645–650). The probabilistic and statistical properties, marginal distribution and some special cases of the proposed model are studied. Estimation of model parameters is conducted using the Yule-Walker, conditional least squares and maximum likelihood methods. The asymptotic normality of the estimators is also presented. To demonstrate the utility of our model in environmental data, applications are carried out on the monthly number of rainy-days in two Russian cities. [ABSTRACT FROM AUTHOR]

Non-negative integer-valued time series with a finite range are sometimes suffered in environmental science, such as the weekly number of rainy-days in European cities (Góuveia et al. in Stoch Environ Res Risk Assess 32:2495–2514, 2018) and the air quality level in Chinese cities (Liu et al. in J Time Ser Anal 43:460–478, 2022). To enhance the applicability of these environmental science data, this article employs a combination of Pegram and binomial thinning operators to develop a novel first-order mixture binomial autoregressive (BAR(1)) model. The proposed model represents an improved and generalized version of the mixture BAR(1) model introduced by Kang et al. (Stat Pap 62:745–767, 2021). The probabilistic and statistical properties, marginal distribution and some special cases of the proposed model are also studied. The conditional maximum likelihood estimation via EM algorithm and Bayesian estimation via Markov chain Monte Carlo sampling scheme are employed to estimate model parameters. Applications to the weekly number of rainy-days and air quality level counts are conducted to illustrate the usefulness of the new model in data analysis of the environmental studies. [ABSTRACT FROM AUTHOR]

Background: Anaplastic thyroid cancer (ATC) is a highly aggressive malignancy with dismal prognosis. This study aimed to identify the independent risk factors and construct a readily-to-use nomogram to predict the probability of early death in ATC patients. Method: Patients diagnosed with ATC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study for model development and internal validation. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for early death of ATC. Nomograms for predicting the probability of all-cause early death (ACED) and cancer-specific early death (CSED) of ATC were subsequently developed. The performance of the nomograms was comprehensively evaluated and validated in an internal cohort. Result: A total of 696 ATC patients were included in this study, of which 488 patients in the training cohort and 208 patients in the validation cohort. The univariate and multivariate logistic regression analyses identified five independent factors (tumor size, M stage, surgery, radiotherapy and chemotherapy) in the ACED model and six variables in the CSED (gender, tumor size, M stage, surgery, radiotherapy and chemotherapy) model for the establishment of the nomograms. Calibration curves and receiver operating characteristic (ROC) curves showed satisfactory efficacy and consistency both in the training (ACED: AUC values: 0.814 (0.776–0.852); CSED: 0.778 (0.736–0.820)) and validation sets (ACED: 0.762 (0.696–0.827); CSED: 0.745 (0.678–0.812)). In addition, the decision curve analysis (DCA) demonstrated the favorable potential of the two nomograms in clinical application. Conclusion: The two nomograms assist clinicians to identify risk factors and predict the early death probability among ATC patients, thus guide individualized treatment to improve the prognosis. [ABSTRACT FROM AUTHOR]

Cobalt (Co), with its low resistivity, superior adhesion property, and void-free seamless fill ability, is being considered by the industry as a promising candidate to replace the conventional tungsten contact plugs for middle-of-the-line and the wiring metal copper interconnects for back-end-of-the-line. Chemical mechanical polishing (CMP), whose demand is greatly increasing as device dimensions shrink to 7-nm node, has been recognized as one of the indispensable manufacturing approaches for the fabrication of multilevel metal interconnection structures. In addition to meeting the appropriate removal rates and removal selection of heterogeneous materials, excellent wafer surface quality and minimized residual particles, also have become the criteria in the developing process of CMP slurries for Co interconnects. This work investigates the optimization process of the final CMP step for Co interconnects by introducing surfactants in hydrogen peroxide based slurries. Various types of surfactants having different functional groups were employed and compared thoroughly by material removal rates (MRRs) and selectivity. The chemical and mechanical mechanisms of various surfactants during CMP process have been clearly revealed by various approaches, including polishing and static etching experiments, electrochemical analysis, tests of absolute zeta potentials, and particle sizes, as well as wafer surface energy measurements. Research results show that Co MRRs are directly correlated with functional groups of various surfactants. Moreover, absolute zeta potentials of abrasive particles can be deeply influenced by different types of surfactants, where the correlation between absolute zeta potentials and Co MRRs presents strong negative. On the other hand, direct positive correlation between oxide MRRs and particle sizes affected by corresponding surfactants can be summarized. Meanwhile, no obvious corresponding relationship between contact angles and MRRs was found, indicating MRRs were barely affected by wettability of wafer surfaces. At last, the selected surfactants were applied to 12-inch wafers for verification, including MRRs, removal selectivity, defects and surface roughness. Each of these surfactants could make Co and TEOS surface Ra maintain at around below 0.7 nm and 0.3 nm, with a number of residual particles lower than 600 particle/wafer. [ABSTRACT FROM AUTHOR]

Cells remodel glycerophospholipid acyl chains via the Lands cycle to adjust membrane properties. Membrane-bound O-acyltransferase (MBOAT) 7 acylates lyso-phosphatidylinositol (lyso-PI) with arachidonyl-CoA. MBOAT7 mutations cause brain developmental disorders, and reduced expression is linked to fatty liver disease. In contrast, increased MBOAT7 expression is linked to hepatocellular and renal cancers. The mechanistic basis of MBOAT7 catalysis and substrate selectivity are unknown. Here, we report the structure and a model for the catalytic mechanism of human MBOAT7. Arachidonyl-CoA and lyso-PI access the catalytic center through a twisted tunnel from the cytosol and lumenal sides, respectively. N-terminal residues on the ER lumenal side determine phospholipid headgroup selectivity: swapping them between MBOATs 1, 5, and 7 converts enzyme specificity for different lyso-phospholipids. Finally, the MBOAT7 structure and virtual screening enabled identification of small-molecule inhibitors that may serve as lead compounds for pharmacologic development. Wang et al. report a structure for human MBOAT7, the enzyme responsible for remodeling acyl chains of phosphatidylinositol. The structure enabled the identification of MBOAT7 inhibitors and provides insights into substrate specificity among MBOATs. [ABSTRACT FROM AUTHOR]

Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of machines. Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the fault diagnosis field. However, existing studies suffer from two weaknesses. First, the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault types. Second, the localization for multi-source faults is seldom investigated, although locating the anomaly variable over multivariate sensing data for certain types of faults is desirable. This article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations (MSRs). First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition results. Second, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault sources are therefore determined. The proposed method is demonstrated by experiments on an induction motor and a centrifugal pump. Results show the proposed method’s validity in diagnosing fault types and sources. [ABSTRACT FROM AUTHOR]

This article introduces a new version of first-order binomial autoregressive (BAR(1)) process with zero-and-one inflated binomial marginals using the idea of hidden Markov models, which contains the BAR(1) and other existing processes as special cases. Stochastic properties of the new model are investigated and model parameters are estimated by the probability-based, quasi-maximum likelihood, maximum likelihood and Bayesian methods. A binomial one-inflation index is constructed and further utilized to develop a method to test whether zero and/or one inflation with respect to a BAR(1) model. We also give the asymptotic distribution of the corresponding test statistics under the null hypothesis. Applications to rainy-days and assaults-on-officers counts are conducted, which shows that the proposed model can accurately capture zero-inflation, one-inflation and overdispersion characteristics of the data. The predictive distributions are employed to identify the occurrence of anomalies and then establish early warning system of risk. [ABSTRACT FROM AUTHOR]

Equidispersed, underdispersed and overdispersed count data are commonly encountered in practice. To better describe these data characteristics, this paper develops two classes of INAR(1) processes, which not only can model a wide range of overdispersion and underdispersion, but also have ability to describe the zero-inflated and zero-deflated characteristics of the count data. The probabilistic and statistical properties of the two processes are studied. Estimators of the model parameters are derived by using conditional maximum likelihood (CML) and modified conditional least squares (MCLS) methods. Some asymptotic properties and numerical results of the estimators are investigated. Three real examples are given to show the flexibility and usefulness of the proposed models. [ABSTRACT FROM AUTHOR]

Background and Aims: Recent studies have shown that changes in the intestinal microbiota contribute to the pathogenesis of irritable bowel syndrome (IBS). This study aimed to investigate the characteristics of the fecal and intestinal mucosal microbiota in IBS patients, and the correlation between microbiota and clinical manifestations. Methods: Fecal and intestinal mucosal samples were collected from 14 constipation-predominant IBS (IBS-C) patients, 20 diarrhea-predominant IBS (IBS-D) patients, and 20 healthy controls (HCs). 16S rRNA gene sequencing and fluorescence in situ hybridization were used for the analysis of samples. Results: Community richness and diversity of the fecal microbiota in IBS patients were significantly reduced compared with the HCs. The mucosal samples in IBS patients showed decreased Bifidobacterium and increased Bacteroides caccae compared with HCs; Eubacterium and Roseburia were decreased in IBS-C patients and increased in IBS-D patients. A comparison of the fecal and mucosal microbiota in IBS patients showed significantly increased Bifidobacterium in fecal samples and a decrease in mucosal samples in IBS-C patients; Bacteroides caccae and Roseburia were significantly reduced in fecal samples and increased in mucosal samples of IBS patients. A correlation between microbiota and clinical manifestations in IBS patients showed that Bacteroides caccae and Roseburia in fecal samples and Bifidobacterium and Eubacterium in mucosal samples were associated with abdominal pain and distention. Conclusions: Distinct differences exist between the fecal and intestinal mucosal microbiota in IBS patients, with the changes in the latter appearing more consistent with the pathophysiology of IBS. Changes in intestinal microbiota were associated with the clinical manifestations in IBS. [ABSTRACT FROM AUTHOR]

This paper studies a deconvolved Chebyshev beamforming (Dcv-Che-BF) method. Compared with other deconvolution beamforming methods, Dcv-Che-BF can preset sidelobe levels according to the actual situation, which can achieve higher resolution performance. However, the performance of Dcv-Che-BF was not necessarily better with a lower preset sidelobe level in the presence of noise. Instead, it was much better when the preset side lobe level matched the signal to noise ratio of the signal. The performance of the Dcv-Che-BF method with different preset sidelobe levels was analyzed using simulation. The Dcv-Che-BF method achieved a lower sidelobe level and better resolution capability when the preset sidelobe level was slightly greater than the noise background level. To validate the feasibility and performance of the proposed method, computer simulations and sea trials were analyzed. The results show that the Dcv-Che-BF method is a robust high-resolution beamforming method that can achieve a narrow mainlobe and low sidelobe. [ABSTRACT FROM AUTHOR]

The prediction and control of COVID-19 is critical for ending this pandemic. In this paper, a nonlocal SIHRDP (S-susceptible class, I-infective class (infected but not hospitalized), H-hospitalized class, R-recovered class, D-death class and P-isolated class) epidemic model with long memory is proposed to describe the multi-wave peaks for the spread of COVID-19. Based on the basic reproduction number R 0 , which is completely controlled by fractional order, the stability of the proposed system is studied. Furthermore, the numerical simulation is conducted to gauge the performance of the proposed model. The results on Hunan, China, reveal that R 0 < 1 suggests that the disease-free equilibrium point is globally asymptotically stable. Likewise, the situation of the multi-peak case in China is presented, and it is clear that the nonlocal epidemic system has a superior fitting effect than the classical model. Finally an adaptive impulsive vaccination is introduced based on the proposed system. Then employing the real data of France, India, the USA and Argentina, parameters identification and short-term forecasts are carried out to verify the effectiveness of the proposed model in describing the case of multiple peaks. Moreover, the implementation of vaccine control is expected once the hospitalized population exceeds 20 % of the total population. Numerical results of France, Indian, the USA and Argentina shed light on the varied effect of vaccine control in different countries. According to the vaccine control imposed on France, no obvious effect is observed even consider reducing human contact. As for India, although there will be a temporary increase in hospitalized admissions after execution of vaccination control, COVID-19 will eventually disappear. Results on the USA have seen most significant effect of vaccine control, the number of hospitalized individuals drops off and the disease is eventually eradicated. In contrast to the USA, vaccine control in Argentina has also been very effective, but COVID-19 cannot be completely eradicated. [ABSTRACT FROM AUTHOR]

A cost-effective approach was applied to prepare hierarchical porous carbons by simple carbonization and NaCl activation of Artemisia argyi rod at different temperatures. The obtained Artemisia argyi rod–based porous carbon (AARC)-700 material possesses high specific surface area of 1141.8 m2 g−1 and has a hierarchical structure with rich micro-, meso-, and macropores. As electrode for supercapacitor, AARC-700 shows an outstanding electrochemical performance of 348.4 F g−1 at 1 A g−1 in 6 M KOH electrolyte and a superior capacitance of 140 F g−1 at 100 A g−1. At a wide voltage window of 2.0 V, the energy density of the assembled symmetric supercapacitor (AARC-700//AARC-700) at a power density of 2.0 kW kg−1 in 1.0 M Na2SO4 aqueous electrolyte is as high as 32.06 Wh kg−1. Even at a high power density of 40 kW kg−1, a high energy density of 16.67 Wh kg−1 can be achieved. Moreover, the symmetric supercapacitor shows capacitance retention of 99.7% after 20,000 continual charge/discharge cycles at a high current density of 5 A g−1. The results indicate that AARC-700 has bright prospect for application as an electrode material for energy storage. [ABSTRACT FROM AUTHOR]

A new zinc complex [Zn(L1)Cl2]2‧CH3OH‧2H2O (complex 1), where L1 stands for 2,6-Bis{[(4-ethylphenyl)imino]ethyl}pyridine (L1) has been synthesized and characterized. The crystal structure of L1 and complex 1 have been determined by single-crystal X-ray diffraction. Both compounds crystallize in the monoclinic P21/c space group. For the ligand L1, the crystal parameters are a = 16.7487(7) Å, b = 5.8177(3) Å, c = 21.8427(10) Å, β = 104.1350(10)° and Z = 4. For complex 1, the crystal parameters are a = 8.0216(14) Å, b = 13.433(2) Å, c = 24.640(4) Å, β = 90.223(3)° and Z = 2. In the crystal structure of complex 1, L1 acts as a tridentate ligand and coordinated with Zn1 with three nitrogen atoms. Together with two chlorine atoms, Zn1 atom is five-coordinated in a trigonal bipyramidal geometry. Hydrogen bonds play great role in the crystal structure of complex 1 and form a two-dimensional network. Furthermore, the DNA-binding property of complex 1 with fish sperm DNA (FS-DNA) has been investigated by electronic absorption titration. The result suggests that complex 1 might interact with FS-DNA via groove binding mode. The single crystals of 2,6-Bis{[(4-ethylphenyl)imino]ethyl}pyridine (L1) and it's Zinc(II) complex [Zn(L1)Cl2]‧CH3OH‧H2O (1) were determined. In the crystal structure of complex 1, Zn1 atom is five-coordinated in a trigonal bipyramidal geometry. A two-dimensional network is formed by hydrogen bonds. DNA-binding study indicated that complex 1 interact with FS-DNA via groove binding mode. [ABSTRACT FROM AUTHOR]

Objective: We aim to develop and validate a three-dimensional convolutional neural network (3D-CNN) model for automatic liver segment segmentation on MRI images. Methods: This retrospective study evaluated an automated method using a deep neural network that was trained, validated, and tested with 367, 157, and 158 portal venous phase MR images, respectively. The Dice similarity coefficient (DSC), mean surface distance (MSD), Hausdorff distance (HD), and volume ratio (RV) were used to quantitatively measure the accuracy of segmentation. The time consumed for model and manual segmentation was also compared. In addition, the model was applied to 100 consecutive cases from real clinical scenario for a qualitative evaluation and indirect evaluation. Results: In quantitative evaluation, the model achieved high accuracy for DSC, MSD, HD and RV (0.920, 3.34, 3.61 and 1.01, respectively). Compared to manual segmentation, the automated method reduced the segmentation time from 26 min to 8 s. In qualitative evaluation, the segmentation quality was rated as good in 79% of the cases, moderate in 15% and poor in 6%. In indirect evaluation, 93.4% (99/106) of lesions could be assigned to the correct segment by only referring to the results from automated segmentation. Conclusion: The proposed model may serve as an effective tool for automated anatomical region annotation of the liver on MRI images. [ABSTRACT FROM AUTHOR]

Screen contents have become a popular image type driven by the growing market for transferring display screen between devices, especially mobile devices. Due to the ultra-high quality display featured in most of nowadays mobile devices, lossless screen content coding (SCC) is usually required or preferred. Mobile devices also require ultra-low power consumption in all tasks including SCC. To address these issues, this paper proposes an ultra-low coding complexity technique based on string matching for high efficiency lossless SCC. The technique covers three major coding phases of fast searching, prediction, and entropy coding. Condensed hash table (CHT) based fast searching is proposed to speed-up reference string searching process. Coplanar prediction (CP) and predictor-dependent residual (PDR) are presented to first efficiently predict an unmatchable pixel using multiple neighboring pixels and then further reduce the entropy of prediction residuals. To achieve a good trade-off between coding complexity and efficiency, 4-bit-aligned variable length code (4bVLC) and byte-aligned multi-variable-length-code (BMVLC) are proposed to code the prediction residuals and three string matching parameters, respectively. For 184 screen content images commonly used, compared with X265 and PNG in the default configuration and lossless mode, the proposed technique achieves 35.67% less total compressed bytes with only 0.96% encoding and 1.54% decoding runtime, and 10.04% less total compressed bytes with only 6.83% encoding and 24.32% decoding runtime, respectively. The proposed technique also outperforms X265 and PNG in all other configurations. For twelve HEVC-SCC CTC images, compared with PNG in fast, default and slow configurations and X265 in ultrafast and default configurations, the proposed technique shows significant advantage with both high coding efficiency and ultra-low coding complexity. [ABSTRACT FROM AUTHOR]

Background: DEAD-Box Helicase 3 X-Linked (DDX3X) is a member of the DEAD-box helicases that play a crucial role in RNA metabolism. Although DDX3X has been shown to contribute to tumorigenesis, the detailed mechanisms by which DDX3X functions in pancreatic ductal adenocarcinoma (PDAC) biogenesis remain poorly understood. Aims: The goal of the present study was to elucidate the molecular mechanisms by which DDX3X contributes to tumorigenesis in PDAC. Methods: Kaplan–Meier curves, the log-rank test, t test and Cox regression were used to analyze the relationship between DDX3X expression and the clinicopathological features of PDAC patients. DDX3X and p62 expression in human PDAC tissues was analyzed by immunohistochemistry. Monolayer scratch healing assays, cell migration assays and nude mouse lung metastasis models were used to evaluate the effect of DDX3X on metastasis in vitro and in vivo. Western blot analysis was used to assess the expression of proteins in the signaling pathway. Results: We authenticated high DDX3X expression was associated with a poor prognosis in PDAC. The loss of DDX3X attenuated the migratory capacity of PDAC cells in vitro and in vivo. DDX3X was shown to facilitate epithelial-mesenchymal transition (EMT) and the phosphorylation of p65 and eIF2α. Moreover, DDX3X displayed oncogenic activity by promoting p62 accumulation. Conclusions: Our results demonstrated that DDX3X activates NF-κB and promotes metastasis by inducing EMT via p62. [ABSTRACT FROM AUTHOR]

In the end of 2019, a new type of coronavirus first appeared in Wuhan. Through the real-data of COVID-19 from January 23 to March 18, 2020, this paper proposes a fractional SEIHDR model based on the coupling effect of inter-city networks. At the same time, the proposed model considers the mortality rates (exposure, infection and hospitalization) and the infectivity of individuals during the incubation period. By applying the least squares method and prediction-correction method, the proposed system is fitted and predicted based on the real-data from January 23 to March 18 - m where m represents predict days. Compared with the integer system, the non-network fractional model has been verified and can better fit the data of Beijing, Shanghai, Wuhan and Huanggang. Compared with the no-network case, results show that the proposed system with inter-city network may not be able to better describe the spread of disease in China due to the lock and isolation measures, but this may have a significant impact on countries that has no closure measures. Meanwhile, the proposed model is more suitable for the data of Japan, the USA from January 22 and February 1 to April 16 and Italy from February 24 to March 31. Then, the proposed fractional model can also predict the peak of diagnosis. Furthermore, the existence, uniqueness and boundedness of a nonnegative solution are considered in the proposed system. Afterward, the disease-free equilibrium point is locally asymptotically stable when the basic reproduction number R 0 ≤ 1 , which provide a theoretical basis for the future control of COVID-19. [ABSTRACT FROM AUTHOR]

The population genetic structure of plants is affected by both genetic and geo-environmental factors. Dissecting the relationship between these factors is important for conservation and breeding applications of plant natural resources. Lycium chinense Mill., is a perennial shrub long-term used as both medicinal herbs and vegetables. Here we investigated the population genetic variation and structure of L. chinense (including two varieties L. chinense var. chinense and L. chinense var. potaninii Pojark. A. M. Lu) and its closely related species Lycium barbarum L. using EST-SSR markers. We found a moderate level of genetic variation presented in the L. chinense populations, which was lower than that of L. barbarum. Both STRUCTURE and PCoA analyses showed that the variety of L. chinense var. potaninii samples was potentially hybrid derived with possible donor parents of L. chinense var. chinense and L. barbarum. We also found positive relationships presented between the genetic and geographical distance, as well as between the genetic distance and annual mean temperature in populations of L. chinense and in populations only from L. chinense var. chinense, suggesting potentially isolation by distance and isolation by adaptation effects. A core collection of L. chinense that included 37 accessions was finally constructed. Hybridization and introgression has affected genetic variation of L. chinense populations. The population genetic structure of L. chinense has been driven by both hybridization and geo-environmental factors. This genetic information and core collection will facilitate the conservation and breeding of L. chinense in future. [ABSTRACT FROM AUTHOR]

Laryngeal papillomas (LP) is a difficult disease to manage due to its frequent recurrence, airway compromise, and risk of cancer. Recently, growing evidence indicates the aberrant expression of OGFPD1, a stress granule protein, links closely to the development of tumorigenesis; however, little is known about its role in LP progression. Here, we investigated the tumor promoting action of OGFOD1 in LP. The transcriptional and translational levels of OGFOD1 were significantly up-regulated in LP tissues and cells. Moreover, OGFOD1 promoted viability and proliferation, and inhibited LP cells apoptosis. We further revealed that OGFOD1 was directly targeted by miR-1224-5p, which was significantly down-regulated in LP. Overexpression of the miR-1224-5p suppressed OGFOD1-induced cell proliferation and viability, and promoted apoptosis of LP. In accordance, knockdown of miR-1224-5p inversed the inhibitory effects. In confederation of the central involvement of OGFOD1 in LP progression, targeting the miR-1224-5p/OGFOD1 pathway might provide a novel strategy for LP treatment. [ABSTRACT FROM AUTHOR]

Trans-polyisoprene rubber is produced in the tissues of leaves, bark, and fruit of Eucommia ulmoides and is considered an important energy source. Transcript profiles of two tissues from E. ulmoides cv. Qinzhong No. 3, leaf and fruit, were analysed using the Illumina HiSeq 2000 system. In total, 104 million clean reads were obtained and assembled into 58,863 unigenes. Through gene functional classification, 28,091 unigenes (47.72%) were annotated and 65 unigenes have been hypothesized to encode proteins involved in terpenoid biosynthesis. In addition, 10,041 unigenes were detected as differentially expressed unigenes, and 29 of them were putatively related to terpenoid biosynthesis. The synthesis of trans-polyisoprene rubbers in E. ulmoides was hypothesised to be dominated by the mevalonate pathway. Farnesyl diphosphate synthase 2 (FPPS2) was considered a key component in the biosynthesis of trans-polyprenyl diphosphate. Rubber elongation factor 3 (REF3) might be involved in stabilising the membrane of rubber particles in E. ulmoides. To date, 351 simple sequence repeats (SSRs) were validated as polymorphisms from eight E. ulmoides plants (two parent plants and six F1 individuals), and these could act as molecular markers for genetic map density increase and breeding improvement of E. ulmoides. [ABSTRACT FROM AUTHOR]

Condition monitoring of piston pumps has great significance to ensure the reliability and security of hydraulic systems. However, the complex working conditions of the integrated electromechanical systems make the fault mechanism unclear which is difficult for fault diagnosis by feature matching techniques. In this paper, a novel minimum entropy deconvolution (MED)-based convolutional neural network (CNN) is presented to classify faults in axial piston pumps. Firstly, the collected raw signals are preprocessed using the MED technique. Then, the filtered signals are used to construct training samples and testing samples. Finally, the constructed samples are fed into the CNN to classify the multi-faults of axial piston pumps. With the convolution and subsampling operations, the present model can automatically obtain data features via iterative learning processes, which is suitable for the unknown fault mechanism problems. The learned features are visualized by t-distributed stochastic neighbor embedding technique. A benchmark data simulation of mechanical transmission systems and an experimental data investigation of an axial piston pump are performed to manifest the superiority of the present method by comparing with the traditional CNN. [ABSTRACT FROM AUTHOR]

Ventilator-associated pneumonia (VAP) is one of the most severe complications in patients with traumatic brain injury (TBI) and is considered a risk factor for poor outcomes. However, the incidence of VAP among patients with TBI reported in studies varies widely. What is more, the risk factors and outcomes of VAP are controversial. This study estimates the incidence, risk factors, and outcomes of VAP in patients with TBI and provides evidence for prevention and treatment. PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched from the earliest records to May 2018. Data involving the incidence, risk factors, and outcomes were extracted for meta-analysis. The results showed that the incidence of VAP was 36% (95% confidence interval (CI) 31-41%); risk factors analyses showed that smoking [odds ratio (OR) 2.13; 95% CI 1.16-3.92], tracheostomy (OR 9.55; 95% CI 3.24-28.17), blood transfusion on admission (OR 2.54; 95% CI 1.24-5.18), barbiturate infusion (OR 3.52; 95% CI 1.68-7.40), injury severity score (OR 4.65; 95% CI 1.96-7.34), and head abbreviated injury scale (OR 2.99; 95% CI 1.66-5.37) were related to the occurrence of VAP. When patients developed VAP, mechanical ventilation time (OR 5.45; 95% CI 3.78-7.12), ICU length of stay (OR 6.85; 95% CI 4.90-8.79), and hospital length of stay (OR 10.92; 95% CI 9.12-12.72) were significantly increased. However, VAP was not associated with an increased risk of mortality (OR 1.28; 95% CI 0.74-2.21). VAP is common in patients with TBI. It is affected by a series of factors and has a poor prognosis. [ABSTRACT FROM AUTHOR]

Accurate and rapid identification of Staphylococcus aureus (S. aureus) is of great significance for controlling the food poisoning and infectious diseases caused by S. aureus. In this study, a novel strategy that combines lysin cell-binding domain (CBD)-based magnetic separation with fluorescence detection was developed for the specific and sensitive quantification of S. aureus in authentic samples. The S. aureus cells were separated from the sample matrix by lysin CBD-functionalized magnetic beads. Following lysis by lysostaphin, intracellular catalase was released from S. aureus cells and detected by a fluorometric system composed of horseradish peroxidase (HRP), hydrogen peroxide (H2O2), and Amplex Red. S. aureus was quantified via the inhibitory effect of the released intracellular catalase on the fluorometric system since the catalase could decompose the H2O2. Optimized conditions afforded a calibration curve for S. aureus ranging from 1.0 × 102 to 1.0 × 107 CFU mL−1. The detection limit was as low as 78 CFU mL−1 in phosphate-buffered saline (PBS), and the total detection process could be completed in less than 50 min. Other bacteria associated with common food-borne and nosocomial infections negligibly interfered with S. aureus detection, except for Staphylococcus epidermidis, which may have slightly interfered. Moreover, the potential of this proposed method for practical applications has been demonstrated by detection assays of sterilized milk and human serum. [ABSTRACT FROM AUTHOR]

Fucoxanthin is a xanthophyll-type carotenoid that provides many benefits to human health. However, the mechanism by which fucoxanthin interacts with microbes and inhibits pathogenic bacteria is unknown. In this study, we investigated the effects of fucoxanthin isolated from the edible seaweed Undaria pinnatifida on pathogenic bacteria Escherichia coli and lactobacilli both in vitro and in vivo. Fucoxanthin strongly inhibited the growth of Gram-positive pathogenic bacteria but was less effective against Gram-negative bacteria. Fucoxanthin extracted from the crude mixture had a recovery rate of 93.38% and a purity of 82.70%, which were higher than those of fucoxanthin extracted using a previous method. Fucoxanthin also promoted the growth of intestinal microbes in mice. Fucoxanthinol, a metabolite of fucoxanthin, was generated in the culture media. Fucoxanthin can be deacetylated into fucoxanthinol not only by conventional digestive enzymes in the digestive tract, but also by E. coli and lactobacilli in the intestine. These results indicate that fucoxanthin interacts with and influences E. coli and lactobacilli in the intestine. Therefore, fucoxanthin isolated from Undaria pinnatifida possibly can be applied in human health maintenance. [ABSTRACT FROM AUTHOR]

On social networks, investigating how the influence is propagated is crucial in understanding the network evolution and the social impact of different topics. In previous study, the influence propagation is either modeled based on the static network structure, or the infection between two connected users is recovered from some given event cascades. Unfortunately, existing solutions are incapable of identifying the user susceptibility delivered by user generated content. In this paper, we propose RegInfoIbp, a general regularized learning framework for modeling topic-aware influence propagation in dynamic network structures. Specifically, the observed time-sequential user topic preference and user adjacency information are factorized by the prior information reflected by a user-influential bipartite relation graph. The influence propagation is approximated with a nonparametric regularized Bayesian matrix factorization model with tractable polynomial complexity. and the influential users are identified by several sampling algorithms with slightly different approximation qualities. To further model dynamic temporal evolution, we construct Markov conditional probabilistic model on the compact latent feature representation. By integrating both topic and structure information into the regularized non-parametric probabilistic learning process, RegInfoIbp is more efficient and accurate in discovering the key factors in the content and influential users in dynamic network structure. Extensive experiments demonstrate that RegInfoIbp better adapts to real data, and achieves better approximation in influence propagation over existing approaches. [ABSTRACT FROM AUTHOR]

The phenomenal growth of the usage of mobile devices (e.g., mobile phones and tablet PCs) opens up a new service, namely mobile visual recognition, which has been widely used in many areas, such as mobile shopping and augmented reality. The rich contextual information (e.g., location, time and direction information), easily acquired by the mobile devices, provides useful clues to facilitate mobile visual recognition, including speeding up the recognition time and improving the recognition performance. This survey focuses on recent advances in Context-Aware Mobile Visual Recognition (CAMVR) and reviews related work regarding to different contextual information, recognition methods, recognition types, and various application scenarios. Finally, we discuss future research directions in this field. [ABSTRACT FROM AUTHOR]

Offspring from families with multiple cases of alcohol dependence have a greater likelihood of developing alcohol dependence and related substance use disorders. Greater susceptibility for these disorders may be related to cerebellar morphology. Because posterior regions of the cerebellum are associated with cognitive abilities, we investigated whether high-risk offspring would display regionally specific differences in cerebellar morphology and whether these would be related to working memory performance. The relationship to externalizing and internalizing psychopathology was of interest because cerebellar morphology has previously been associated with a cognitive affective syndrome. A total of 131 participants underwent magnetic resonance imaging (MRI) with volumes of the cerebellar lobes obtained with manual tracing. These individuals were from high-risk (HR) for alcohol dependence families ( N = 72) or from low-risk (LR) control families ( N = 59). All were enrolled in a longitudinal follow-up that included repeated clinical assessments during childhood and young-adulthood prior to the scan that provided information on Axis I psychopathology. The Working Memory Index of the Wechsler Memory Scale was given at the time of the scan. Larger volumes of the corpus medullare and inferior posterior lobes and poorer working memory performance were found for the HR offspring relative to LR controls. Across all subjects, a significant positive association between working memory and total volume of corpus of the cerebellum was seen, controlling for familial risk. Presence of an internalizing or externalizing disorder interacting with familial risk was also associated with volume of the corpus medullare. [ABSTRACT FROM AUTHOR]

Background: Multiple brainstem manifestations have been rarely reported during the same attack in neuromyelitis optica spectrum disorders (NMOSD).Case Presentation: We describe a 39-year-old Asian woman presenting multiple brainstem manifestations including intractable nausea and vomiting, vertigo, diplopia, facial palsy, hypogeusia, ophthalmoplegia, hemiplegia, dysphagia and tonic spasm during the same attack. Hypogeusia was transient and recovered without any immunotherapy. The brain MRIs showed progressive multiple lesions in the brainstem. NMO-IgG (aquaporin4-antibody, AQP4-Ab) were positive in both serum and cerebral spinal fluid. The symptoms and signs were controlled after immunosuppressive therapy. No relapse happened during the 15-month follow-up.Conclusion: This report emphasizes multiple brainstem manifestations during the same attack in NMOSD and the most characteristic symptom was reversible hypogeusia. [ABSTRACT FROM AUTHOR]

Computer screens are rich in discontinuous-tone content besides traditional continuous-tone content. Thus, new video coding tools coherently united into traditional hybrid coding tools are needed to effectively compress screen contents. This paper proposes a Pseudo-2D-matching (P2M) coder based enhancement to High Efficiency Video Coding for screen contents. An input Largest Coding Unit (LCU) is simultaneously fed into a P2M coder and a traditional hybrid coder. The coder minimizing rate-distortion is selected as the final coder for the LCU. The P2M coder breaks an LCU into many horizontal or vertical line segments and searches matching line segments in the searching-window consisting of previously coded pixels. Since the searching-window is large (a few kilobytes to megabytes) to increase the chance to find a good matching, a hash-table is used to speedup the search. In the P2M coder, three matching modes are used: 1) vertically scanned string matching; 2) horizontally scanned 2D-shape-preserved matching; and 3) vertically scanned 2D-shape-preserved matching. All three matching modes are used to code an LCU and the mode minimizing rate-distortion is selected in the P2M coder. The P2M based enhancement achieves significant Bitrate-distortion rate (BD-rate) and subjective visual quality improvement over traditional hybrid coding for screen contents. [ABSTRACT FROM AUTHOR]

Most of our learning comes from other people or from our own experience. For instance, when a taxi driver is seeking passengers on an unknown road in a large city, what should the driver do? Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows (e.g., hotel taxi rank)? This is an interesting problem that arises everyday in cities all over the world. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood of finding passengers on a road that is new to him (as he has not picked up or dropped off passengers there before). Our observation from large scale taxi driver trace data is that a driver not only learns from his own experience but through interactions with other drivers. In this paper, we first formally define this problem as socialized information learning (SIL), second we propose a framework including a series of models to study how a taxi driver gathers and learns information in an uncertain environment through the use of his social network. Finally, the large scale real life data and empirical experiments confirm that our models are much more effective, efficient and scalable that prior work on this problem. [ABSTRACT FROM AUTHOR]

Multiple image features and multiple semantic concepts from the images have intrinsic and complex relations. These relations influence the effectiveness of image semantic analysis methods, especially on the large scale problems. In this paper, a framework of generating polysemious image representation through three levels of feature aggregation is proposed. In the codebook level aggregation, visual dictionaries are learned for each feature type, and each image feature can be reconstructed with this dictionary. In the semantic level aggregation, the multiple concept distributions are learned with each feature codebook by using the improved local anchor embedding. Then the polysemious representation for for single feature type can be established after this level. In the multiple feature level aggregation, final image polysemious representation is obtained through multiple feature fusion with a weighted pooling approach. Through the proposed framework, multiple feature fusion and multiple semantic descriptions are both achieved in an integrated way. Experimental evaluations on large scale image dataset validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A cold-induced gene of 669 bp in length without introns, PicW, was cloned from Picea. wilsonii, a cold tolerant conifer species. Sequence analysis showed that it was a member of the dehydrin family because of its conserved amino acid constitution and protein secondary structure. The protein was rich in hydrophilic amino acids such as alanine, lysine, glutamic acid, glutamine and threonine, but devoid of two hydrophobic amino acids, cysteine and tryptophan. The PicW gene contained five repeated motifs homologous to the core K-segment in dehydrins. Protein secondary structure prediction showed that PicW comprised 29 % α-helix, mostly in the K-homologous segment, and random coils. The PicW gene was cloned into the expression vector PEZR(K)-LC under the 35S promoter and transformed into tobacco plants. After treatment at −5 °C for 3 h, all of the tobacco plants were wilting. However, the transgenic plants showed better growth performance than wild-type plants. Further tests of physiological indexes including relative electrolyte leakage and malondialdehyde content, proline and soluble sugar content also revealed significant differences between the wild-type and transgenic tobacco plants. It was concluded that the PicW gene could be an important gene resource for freezing-tolerant plant breeding. [ABSTRACT FROM AUTHOR]

This paper proposes a compound image coding method named united coding (UC). In UC, several lossless coding tools such as dictionary-entropy coders, run-length encoding (RLE), Hextile, and a few filters used in portable network graphics (PNG) format are united into H.264 like intraframe hybrid video coding. The basic coding unit (BCU) has a size typically between 16 × 16 pixels to 64 × 64 pixels. All coders in UC are used to code each BCU. Then, the lossless coder that generates minimum bit-rate (R) is chosen as the optimal lossless coder. Finally, the final optimal coder is chosen from the lossy intraframe hybrid coder and the optimal lossless coder using R-D cost based optimization criterion. Moreover, the data coded by one lossless coder can be used as the dictionary of other lossless coders. Experimental results demonstrate that compared with H.264, UC achieves up to 20 dB PSNR improvement and better visual picture quality for compound images with mixed text, graphics and natural picture. Compared with lossless coders such as gzip and PNG, UC can achieve 2-5 times higher compression ratio with just a minor loss and keep partial-lossless picture quality. The partial-lossless nature of UC is indispensable for some typical applications, such as cloud computing and rendering, cloudlet-screen computing and remote desktop, where lossless coding of partial image regions is demanded. On the other hand, the implementation complexity and cost increment of UC is moderate, typically less than 25 % of a traditional hybrid coder such as H.264. [ABSTRACT FROM AUTHOR]

Cross-domain visual matching aims at finding visually similar images across a wide range of visual domains, and has shown a practical impact on a number of applications. Unfortunately, the state-of-the-art approach, which estimates the relative importance of the single feature dimensions still suffers from low matching accuracy and high time cost. To this end, this paper proposes a novel cross-domain visual matching framework leveraging multiple feature representations. To integrate the discriminative power of multiple features, we develop a data-driven, query specific feature fusion model, which estimates the relative importance of the individual feature dimensions as well as the weight vector among multiple features simultaneously. Moreover, to alleviate the computational burden of an exhaustive subimage search, we design a speedup scheme, which employs hyperplane hashing for rapidly collecting the hard-negatives. Extensive experiments carried out on various matching tasks demonstrate that the proposed approach outperforms the state-of-the-art in both accuracy and efficiency. [ABSTRACT FROM AUTHOR]

An oxyethylene chain (-CH-CH-O-) grafted polymer (P(MMA-MAh)-PEGME) was synthesized by reacting poly(ethylene glycol) monomethyl ether (PEGME) with the copolymer of poly(methyl metacrylate-maleic anhydride) (P(MMA-MAh)) and endcapping the residual carboxylic acid with methanol. Rectorite modified with dodecyl benzyl dimethyl ammonium chloride (OREC) was used as a filler additive to modify gel polymer electrolytes (GPE) that consisted of P(MMA-MAh)-PEGME used as polymer matrix, propylene carbonate (PC) as plasticizer and LiClO as lithium ion producer. Characterization of interaction of the polar group of C=O or C-O-C in PC and grafted polymer with Li and OH group on OREC surface has been thoroughly examined using Fourier transform infrared (FTIR), respectively. The quantitative analysis of FTIR shows that the absorptivity coefficients ( a) of polymer/LiClO, PC/LiClO, PC/OREC and polymer/OREC are 0.705, 0.113, 0.430 and 0.500, respectively, which means that the Li or OH bonded polar group of C=O and C-O-C is more sensitive than free C=O and C-O-C in FTIR spectra. The limited values of bonded C=O and C-O-C equivalent fraction of polymer/LiClO, PC/LiClO, PC/OREC and polymer/OREC are 33%, 94%, 60% and 22%, respectively, which implies that the interaction within the components is reversible and the intensity of interaction is ordered as PC/LiClO, PC/OREC, polymer/OREC and polymer/LiClO. [ABSTRACT FROM AUTHOR]

The clinical use of Pseudomonas exotoxin A (PE)-based immunotoxins is limited by the toxicity and immunogenicity of PE. To overcome the limitations, we have developed PE38KDEL-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles conjugated with Fab′ fragments of a humanized anti-HER2 monoclonal antibody (rhuMAbHER2). The PE38KDEL-loaded nanoparticles-anti-HER2 Fab′ bioconjugates (PE-NP-HER) were constructed modularly with Fab′ fragments of rhuMAbHER2 covalently linked to PLGA nanoparticles containing PE38KDEL. Compared with nontargeted nanoparticles that lack anti-HER2 Fab′, PE-NP-HER specifically bound to and were sequentially internalized into HER2 overexpressing breast cancer cells, which result in significant cytotoxicity in vitro. In HER2 overexpressing tumor xenograft model system, administration of PE-NP-HER showed a superior efficacy in inhibiting tumor growth compared with PE-HER referring to PE38KDEL conjugated directly to rhuMAbHER2. Moreover, PE-NP-HER was well tolerated in mice with a higher LD50 (LD50 of 6.86 ± 0.47 mg/kg vs. 2.21 ± 0.32 mg/kg for PE-NP-HER vs. PE-HER (mean ± SD); n = 3), and had no influence on the plasma level of plasma alanine aminotransferase (ALT) of animals when injected at a dose of 1 mg/kg where PE-HER caused significant increase of serum ALT in the treated mice. Notably, PE-NP-HER was of low immunogenicity in development of anti-PE38KDEL neutralizing antibodies and was less susceptible to inactivation by anti-PE38KDEL antibodies compared with PE-HER. This novel bioconjugate, PE-NP-HER, may represent a useful strategy for cancer treatment. [ABSTRACT FROM AUTHOR]

A simple and specific high performance liquid chromatographic (HPLC) method with UV detection using picroside II as the internal standard was developed and validated to determine the concentration of paeoniflorin in rat plasma and study its pharmacokinetics after an single intravenous administration of 40 mg kg−1 paeoniflorin to Wistar rats. The analytes of interest were extracted from rat plasma samples by ethyl acetate after acidification with 0.05 mol L−1 NaH2PO4 solution (pH 5.0). Chromatographic separation was achieved on an Agilent XDB C18 column (250 × 4.6 mm I.D., 5 μm) with a Shim-pack GVP-ODS C18 guard column (10 × 4.6 mm I.D., 5 μm) using a mobile phase consisting of acetonitrile–water–acetic acid (18:82:0.4, v/v/v) at a flow rate of 1.0 mL min−1. The UV detection was performed at a wavelength of 230 nm. The linear calibration curves were obtained in the concentration range of 0.05–200.0 μg mL−1 in rat plasma with the lower limit of quantification (LLOQ) of 0.05 μg mL−1. The intra- and inter-day precisions in terms of % relative standard deviation (RSD) were lower than 5.7 and 8.2% in rat plasma, respectively. The accuracy in terms of % relative error (RE) ranged from −1.9 to 2.6% in rat plasma. The extraction recoveries of paeoniflorin and picroside II were calculated to be 69.7 and 56.9%, respectively. This validated method was successfully applied to the pharmacokinetic study of a new paeoniflorin frozen dry power formulation. After single intravenous administration, the main pharmacokinetic parameters t 1/2, AUC0-∞, CLTOT, V Z, MRT0-∞ and V ss were 0.739 ± 0.232 h, 43.75 ± 6.90 μg h mL−1, 15.50 ± 2.46 L kg−1 h−1, 1.003 ± 0.401 L kg−1, 0.480 ± 0.055 h and 0.444 ± 0.060 L kg−1, respectively. [ABSTRACT FROM AUTHOR]

In order to develop a new vaccine candidate for equine infectious anemia virus (EIAV), gag gene of Chinese donkey leukocyte attenuated strain (EIAV DLV) and its parental virulent strain (EIAV LN) were inserted respectively into the TK region of the Tiantan strain (VV) of vaccinia virus by homologous recombination and the positive clone was confirmed by blue plaque assay. Protein expression was examined by Western blot. Prime and prime-boost procedures were used to immunize mice with two DNA vectors and two recombinant vaccinia viruses expressing EIAV Gag proteins. The results showed that the specific lysis of CTL responses in the DNA+rVV groups was stronger than those in the DNA groups, amounting to 31%. Although the levels of specific antibodies were not significantly different, we could conclude that the recombinant vaccinia virus could boost the cellular responses following DNA vector priming. There was no detectable difference between the immune responses induced by DLV and LN Gag proteins. This data demonstrates that the combined immunity of DNA vector and recombinant vaccinia virus expressing EIAV gag proteins, utilizing the prime-boost procedure, can drive immunized mice to produce powerful cellular responses. These results lay an important foundation for the development of a new EIAV genetic engineering vaccine. [ABSTRACT FROM AUTHOR]

NOx (NO2 and NO) plays an important role in controlling stratospheric ozone. Understanding the change in stratospheric NOx and its global pattern is important for predicting future changes in ozone and the corresponding implications on the climate. Stratospheric NOx is mainly produced by the reaction of N2O with the photochemically produced O(1D) and, therefore, it is expected to vary with changes in solar UV irradiance during the solar cycle. Previous studies on this topic, often limited by the relatively short continuous data, show puzzling results. The effect of the 1991 Pinatubo eruption might have caused interference in the data analysis. In this study, we examine the NO2 vertical column density (VCD) data from the Network for the Detection of Atmospheric Composition Change (NDACC). Data collected at 16 stations with continuous long-term observations covering the most recent Solar Cycles 23 and 24 were analyzed. We found positive correlations between changes in NO2 VCD and solar Lyman- α over nine stations (mostly in the Northern Hemisphere) and negative correlations over three stations (mostly in the Southern Hemisphere). The other four stations do not show significant NO2 solar-cycle signal. The varying NO2 responses from one location to another are likely due to different geo-locations (latitude and altitude). In particular, two high-altitude stations show the strongest positive NO2 solar-cycle signals. Our 1D chemical-transport model calculations help explain the altitude dependence of NO2 response to the solar cycle. NO2 solar-cycle variability is suggested to play an important role controlling O3 at an altitude range from ≈ 20 km to near 60 km, while OH solar-cycle variability controls O3 at 40 – 90 km. While observations show both positive and negative NO2 responses to solar forcing, the 1D model predicts negative NO2 responses to solar UV changes throughout the middle atmosphere. 3D global model results suggest complex roles of dynamics in addition to photochemistry. The energetic particle-induced NO2 variabilities could also contribute significantly to the NO2 variability during solar cycles. [ABSTRACT FROM AUTHOR]