miR-218-2 regulates cognitive functions in the hippocampus through complement component 3-dependent modulation of synaptic vesicle release.

microRNA-218 (miR-218) has been linked to several cognition related neurodegenerative and neuropsychiatric disorders. However, whether miR-218 plays a direct role in cognitive functions remains unknown. Here, using the miR-218 knockout (KO) mouse model and the sponge/overexpression approaches, we showed that miR-218-2 but not miR-218-1 could bidirectionally regulate the contextual and spatial memory in the mice. Furthermore, miR-218-2 deficiency induced deficits in the morphology and presynaptic neurotransmitter release in the hippocampus to impair the long term potentiation. Combining the RNA sequencing analysis and luciferase reporter assay, we identified complement component 3 (C3) as a main target gene of miR-218 in the hippocampus to regulate the presynaptic functions. Finally, we showed that restoring the C3 activity in the miR-218-2 KO mice could rescue the synaptic and learning deficits. Therefore, miR-218-2 played an important role in the cognitive functions of mice through C3, which can be a mechanism for the defective cognition of miR-218 related neuronal disorders.

Application Value of Target Management Mode Based on Chronic Illness Trajectory Framework in Elderly Patients with Diabetes Mellitus and Cardiovascular Diseases.

Background: Diabetes and cardiovascular diseases represent significant global health challenges, leading to organ dysfunction and increased mortality rates. Managing these conditions is complex, especially in the elderly population. The study addresses this pressing issue by exploring the application of the Chronic Illness Trajectory Framework (CITF), aiming to improve self-care and quality of life in elderly patients with diabetes and cardiovascular diseases. Methods: A total of 127 patients with diabetes mellitus and cardiovascular diseases admitted to the hospital were enrolled between January 2020 and January 2022. According to the implementation of CITF management mode, they were divided into a control group (62 cases, non-implementation) and an observation group (65 cases, implementation). The control group was given routine intervention, while the observation group was given CITF-based target management mode for 3 months. The changes in blood glucose, blood lipid, negative emotions, self-efficacy, self-management, compliance, and quality of life before and after intervention in both groups were observed. This study was approved by the Ethics Committee of Zhujiang Hospital. Results: After intervention, levels of fasting plasma glucose (FPG), 2h plasma glucose (2hPG), hemoglobin A1c (HbA1c), total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C), scores of self-rating depression scale (SDS), self-rating anxiety scale (SAS) and Diabetes Specific Quality of Life Scale (DSQL) were decreased (P < .05), while scores of General Self-Efficacy Scale (GSES) and Scale of the Diabetes Self-Care Activities Chinese version (SDSCA), and compliance rate were increased in both groups (P < .05). The levels of FPG, 2hPG, HbA1c, TC, TG, and LDL-C, scores of SDS, SAS, and DSQL in the observation group were lower than those in the control group (P < .001), and scores of GSES and SDSCA, and compliance rate were higher than those in the control group (P < .001). These results highlight the positive role of comprehensive intervention in improving the physical and mental health of patients with diabetes and provide strong support for the application of comprehensive intervention strategies in diabetes management. Conclusion: CITF-based target management mode can alleviate negative emotions in patients with diabetes mellitus and cardiovascular diseases, improve self-management, self-efficacy, and compliance, effectively control blood glucose and lipids, and improve quality of life. The study conclusions highlight the importance of CITF management models in improving the management of patients with diabetes and cardiovascular disease. This comprehensive intervention helps reduce negative emotions, improve self-management and compliance, effectively control blood sugar and blood lipids, and improve quality of life. These results have important clinical implications and provide strong support for better care of patients with chronic diseases.

A Crowd Movement Analysis Method Based on Radar Particle Flow.

Crowd movement analysis (CMA) is a key technology in the field of public safety. This technology provides reference for identifying potential hazards in public places by analyzing crowd aggregation and dispersion behavior. Traditional video processing techniques are susceptible to factors such as environmental lighting and depth of field when analyzing crowd movements, so cannot accurately locate the source of events. Radar, on the other hand, offers all-weather distance and angle measurements, effectively compensating for the shortcomings of video surveillance. This paper proposes a crowd motion analysis method based on radar particle flow (RPF). Firstly, radar particle flow is extracted from adjacent frames of millimeter-wave radar point sets by utilizing the optical flow method. Then, a new concept of micro-source is defined to describe whether any two RPF vectors originated from or reach the same location. Finally, in each local area, the internal micro-sources are counted to form a local diffusion potential, which characterizes the movement state of the crowd. The proposed algorithm is validated in real scenarios. By analyzing and processing radar data on aggregation, dispersion, and normal movements, the algorithm is able to effectively identify these movements with an accuracy rate of no less than 88%.

Design and Implementation of a Linear Active Disturbance Rejection Control-Based Position Servo Control System of an Electromotive Valve for Exhaust Gas Recirculation.

An exhaust gas recirculation (EGR) valve is used to quickly and dynamically adjust the amount of recirculated exhaust gas, which is critical for improving engine fuel economy and reducing emissions. To address problems relating to the precise positioning of an electromotive (EM) valve under slowly varying plant dynamics and uncertain disturbances, we propose a servo control system design based on linear active disturbance rejection control (LADRC) for the EGR EM valve driven by a limited angle torque motor (LATM). By analyzing the structure of the LATM and the transmission, the dynamic model of the system is derived. In addition, to solve the problems caused by slowly varying plant dynamics and uncertain disturbances, we combine the effects of uncertain model parameters and external disturbances as the total disturbance, which is estimated in real time by an extended state observer (ESO) and then compensated. In addition, accurate angular information is obtained using a non-contact magnetic angle measurement method, and a high-speed digital communication channel is established to help implement a closed-loop position control system with improved responsiveness and accuracy. Simulation and experimental results show that the proposed servo system design can effectively ensure the precision and real-time performance of the EM valve under slowly changing plant dynamics and uncertain disturbances. The proposed servo system design achieves a full-stroke valve control accuracy of better than 0.05 mm and a full-stroke response time of less than 100 ms. The controlled valve also has good robustness under shock-type external disturbances and excellent airflow control capability. The repeatability of the airflow control is generally within 5%, and the standard deviation is less than 0.2 m3/h.

Molecular Regulation of Porcine Skeletal Muscle Development: Insights from Research on CDC23 Expression and Function.

Cell division cycle 23 (CDC23) is a component of the tetratricopeptide repeat (TPR) subunit in the anaphase-promoting complex or cyclosome (APC/C) complex, which participates in the regulation of mitosis in eukaryotes. However, the regulatory model and mechanism by which the CDC23 gene regulates muscle production in pigs are largely unknown. In this study, we investigated the expression of CDC23 in pigs, and the results indicated that CDC23 is widely expressed in various tissues and organs. In vitro cell experiments have demonstrated that CDC23 promotes the proliferation of myoblasts, as well as significantly positively regulating the differentiation of skeletal muscle satellite cells. In addition, Gene Set Enrichment Analysis (GSEA) revealed a significant downregulation of the cell cycle pathway during the differentiation process of skeletal muscle satellite cells. The protein-protein interaction (PPI) network showed a high degree of interaction between genes related to the cell cycle pathway and CDC23. Subsequently, in differentiated myocytes induced after overexpression of CDC23, the level of CDC23 exhibited a significant negative correlation with the expression of key factors in the cell cycle pathway, suggesting that CDC23 may be involved in the inhibition of the cell cycle signaling pathway in order to promote the differentiation process. In summary, we preliminarily determined the function of CDC23 with the aim of providing new insights into molecular regulation during porcine skeletal muscle development.

Pan-cancer evidence of prognosis, immune infiltration, and immunotherapy efficacy for annexin family using multi-omics data.

The annexin superfamily (ANXA) is made up of 12 calcium (Ca2+) and phospholipid binding protein members that have a high structural homology and play a key function in cancer cells. However, little research has been done on the annexin family's function in pan-cancer. We examined the ANXA family's expression in various tumors through public databases using bioinformatics analysis, assessed the differences in ANXA expression between tumor and normal tissues in pan-cancer, and then investigated the relationship between ANXA expression and patient survival, prognosis, and clinicopathologic traits. Additionally, we investigated the relationships among TCGA cancers' mutations, tumor mutation burden (TMB), microsatellite instability (MSI), immunological subtypes, immune infiltration, tumor microenvironment, immune checkpoint genes, chemotherapeutics sensitivity, and ANXAs expression. cBioPortal was also used to uncover pan-cancer genomic anomalies in the ANXA family, study relationships between pan-cancer ANXA mRNA expression and copy number or somatic mutations, and assess the prognostic values of these variations. Moreover, we investigated the relationship between ANXAs expression and effectiveness of immunotherapy in multiple cohorts, including one melanoma (GSE78220), one renal cell carcinoma (GSE67501), and three bladder cancer cohorts (GSE111636, IMvigor210 and our own sequencing dataset (TRUCE-01)), and further analyzed the changes of ANXAs expression before and after treatment (tislelizumab combined with nab-paclitaxel) of bladder cancer. Then, we explored the biological function and potential signaling pathway of ANXAs using gene set enrichment analysis (GSEA), and first conducted immune infiltration analysis with ANXAs family genes expression, copy number, or somatic mutations of bladder cancer by TIMER 2.0. Most cancer types and surrounding normal tissues expressed ANXA differently. ANXA expression was linked to patient survival, prognosis, clinicopathologic features, mutations, TMB, MSI, immunological subtypes, tumor microenvironment, immune cell infiltration, and immune checkpoint gene expression in 33 TCGA cancers, with ANXA family members varied. The anticancer drug sensitivity analysis showed that ANXAs family members were significantly related to a variety of drug sensitivities. In addition, we also discovered that the expression level of ANXA1/2/3/4/5/7/9/10 was positively or negatively correlated with objective responses to anti-PD-1/PD-L1 across multiple immunotherapy cohorts. The immune infiltration analysis of bladder cancer further showed the significant relationships between ANXAs copy number variations or mutation status, and infiltration level of different immune cells. Overall, our analyses confirm the importance of ANXAs expression or genomic alterations in prognosis and immunological features of various cancer and identified ANXA-associated genes that may serve as potential therapeutic targets.

Synaptotagmin-7 deficiency induces mania-like behavioral abnormalities through attenuating GluN2B activity.

Synaptotagmin-7 (Syt7) probably plays an important role in bipolar-like behavioral abnormalities in mice; however, the underlying mechanisms for this have remained elusive. Unlike antidepressants that cause mood overcorrection in bipolar depression, N-methyl-d-aspartate receptor (NMDAR)-targeted drugs show moderate clinical efficacy, for unexplained reasons. Here we identified Syt7 single nucleotide polymorphisms (SNPs) in patients with bipolar disorder and demonstrated that mice lacking Syt7 or expressing the SNPs showed GluN2B-NMDAR dysfunction, leading to antidepressant behavioral consequences and avoidance of overcorrection by NMDAR antagonists. In human induced pluripotent stem cell (iPSC)-derived and mouse hippocampal neurons, Syt7 and GluN2B-NMDARs were localized to the peripheral synaptic region, and Syt7 triggered multiple forms of glutamate release to efficiently activate the juxtaposed GluN2B-NMDARs. Thus, while Syt7 deficiency and SNPs induced GluN2B-NMDAR dysfunction in mice, patient iPSC-derived neurons showed Syt7 deficit-induced GluN2B-NMDAR hypoactivity that was rescued by Syt7 overexpression. Therefore, Syt7 deficits induced mania-like behaviors in mice by attenuating GluN2B activity, which enabled NMDAR antagonists to avoid mood overcorrection.

Human Activity Recognition Method Based on FMCW Radar Sensor with Multi-Domain Feature Attention Fusion Network.

This paper proposes a human activity recognition (HAR) method for frequency-modulated continuous wave (FMCW) radar sensors. The method utilizes a multi-domain feature attention fusion network (MFAFN) model that addresses the limitation of relying on a single range or velocity feature to describe human activity. Specifically, the network fuses time-Doppler (TD) and time-range (TR) maps of human activities, resulting in a more comprehensive representation of the activities being performed. In the feature fusion phase, the multi-feature attention fusion module (MAFM) combines features of different depth levels by introducing a channel attention mechanism. Additionally, a multi-classification focus loss (MFL) function is applied to classify confusable samples. The experimental results demonstrate that the proposed method achieves 97.58% recognition accuracy on the dataset provided by the University of Glasgow, UK. Compared to existing HAR methods for the same dataset, the proposed method showed an improvement of about 0.9-5.5%, especially in the classification of confusable activities, showing an improvement of up to 18.33%.

Fast DOA Estimation Algorithms via Positive Incremental Modified Cholesky Decomposition for Augmented Coprime Array Sensors.

This paper proposes a fast direction of arrival (DOA) estimation method based on positive incremental modified Cholesky decomposition atomic norm minimization (PI-CANM) for augmented coprime array sensors. The approach incorporates coprime sampling on the augmented array to generate a non-uniform, discontinuous virtual array. It then utilizes interpolation to convert this into a uniform, continuous virtual array. Based on this, the problem of DOA estimation is equivalently formulated as a gridless optimization problem, which is solved via atomic norm minimization to reconstruct a Hermitian Toeplitz covariance matrix. Furthermore, by positive incremental modified Cholesky decomposition, the covariance matrix is transformed from positive semi-definite to positive definite, which simplifies the constraint of optimization problem and reduces the complexity of the solution. Finally, the Multiple Signal Classification method is utilized to carry out statistical signal processing on the reconstructed covariance matrix, yielding initial DOA angle estimates. Experimental outcomes highlight that the PI-CANM algorithm surpasses other algorithms in estimation accuracy, demonstrating stability in difficult circumstances such as low signal-to-noise ratios and limited snapshots. Additionally, it boasts an impressive computational speed. This method enhances both the accuracy and computational efficiency of DOA estimation, showing potential for broad applicability.

LncRNA TCONS_00323213 Promotes Myogenic Differentiation by Interacting with PKNOX2 to Upregulate MyoG in Porcine Satellite Cells.

Myogenic differentiation is a complex biological process that is regulated by multiple factors, among which long noncoding RNAs (lncRNAs) play an essential role. However, in-depth studies on the regulatory mechanisms of long noncoding RNAs (lncRNAs) in myogenic differentiation are limited. In this study, we characterized the role of the novel lncRNA TCONS_00323213, which is upregulated during porcine skeletal muscle satellite cell (PSC) differentiation in myogenesis. We found that TCONS_00323213 affected the proliferation and differentiation of PSC in vitro. We performed quantitative polymerase chain reaction (qPCR), 5-ethynyl-20-deoxyuridine (EdU), western blotting, immunofluorescence staining, pull-down assays, and cleavage under targets and tagmentation (CUT and Tag) assays to clarify the effects and action mechanisms of TCONS_00323213. LncRNA TCONS_00323213 inhibited myoblast proliferation based on analyses of cell survival rates during PSC proliferation. Functional analyses revealed that TCONS_00323213 promotes cell differentiation and enhances myogenin (MyoG), myosin heavy chain (MyHC), and myocyte enhancer factor 2 (MEF2C) during myoblast differentiation. As determined by pull-down and RNA immunoprecipitation (RIP) assays, the lncRNA TCONS_00323213 interacted with PBX/Knotted Homeobox 2 (PKNOX2). CUT and Tag assays showed that PKNOX2 was significantly enriched on the MyoG promoter after lncRNA TCONS_00323213 knockdown. Our findings demonstrate that the interaction between lncRNA TCONS_00323213 and PKNOX2 relieves the inhibitory effect of PKNOX2 on the MyoG promoter, increases its expression, and promotes PSC differentiation. This novel role of lncRNA TCONS_00323213 sheds light on the molecular mechanisms by which lncRNAs regulate porcine myogenesis.

Ag23Au2 and Ag22Au3: A Model of Cocrystallization in Bimetal Nanoclusters.

The field of cocrystalline nanoclusters stabilized by thiolates is in a period of rapid development. However, the types of cocrystallization have been limited to a few reported until now, so it is of great importance to investigate and understand the novel cocrystallographic structures. Herein, we design and synthesize a new type of cocrystallization, [Ag23Au2(2-EBT)18Ag22Au3(2-EBT)18]2-[2(PPh4)]2+, characterized by thermogravimetric analysis, X-ray photoelectron spectroscopy, and single-crystal X-ray crystallography. Interestingly, both of the cocrystallized nanoclusters show the same outer-shell geometric structure but diffenent cores (Ag11Au2 vs Ag10Au3). The cocrystal lattice exhibits a multilayer structure in which both of the cocrystallized nanoclusters and the counterion assemble in a layer-by-layer model. Meanwhile, the counterion is found to be critical for formation and stabilization of the target cocrystal. In addition, the target cocrystal shows high thermal stability, and this result possibly originates from the electrostatic and weak interactions in the cocrystals.

Face Manipulation Detection Based on Supervised Multi-Feature Fusion Attention Network.

Nowadays, faces in videos can be easily replaced with the development of deep learning, and these manipulated videos are realistic and cannot be distinguished by human eyes. Some people maliciously use the technology to attack others, especially celebrities and politicians, causing destructive social impacts. Therefore, it is imperative to design an accurate method for detecting face manipulation. However, most of the existing methods adopt single convolutional neural network as the feature extraction module, causing the extracted features to be inconsistent with the human visual mechanism. Moreover, the rich details and semantic information cannot be reflected with single feature, limiting the detection performance. Therefore, this paper tackles the above problems by proposing a novel face manipulation detection method based on a supervised multi-feature fusion attention network (SMFAN). Specifically, the capsule network is used for face manipulation detection, and the SMFAN is added to the original capsule network to extract details of the fake face image. Further, the focal loss is used to realize hard example mining. Finally, the experimental results on the public dataset FaceForensics++ show that the proposed method has better performance.

An Overdispersed Black-Box Variational Bayesian-Kalman Filter with Inaccurate Noise Second-Order Statistics.

Aimed at the problems in which the performance of filters derived from a hypothetical model will decline or the cost of time of the filters derived from a posterior model will increase when prior knowledge and second-order statistics of noise are uncertain, a new filter is proposed. In this paper, a Bayesian robust Kalman filter based on posterior noise statistics (KFPNS) is derived, and the recursive equations of this filter are very similar to that of the classical algorithm. Note that the posterior noise distributions are approximated by overdispersed black-box variational inference (O-BBVI). More precisely, we introduce an overdispersed distribution to push more probability density to the tails of variational distribution and incorporated the idea of importance sampling into two strategies of control variates and Rao-Blackwellization in order to reduce the variance of estimators. As a result, the convergence process will speed up. From the simulations, we can observe that the proposed filter has good performance for the model with uncertain noise. Moreover, we verify the proposed algorithm by using a practical multiple-input multiple-output (MIMO) radar system.

An Adaptive Ellipse Distance Density Peak Fuzzy Clustering Algorithm Based on the Multi-target Traffic Radar.

In the multi-target traffic radar scene, the clustering accuracy between vehicles with close driving distance is relatively low. In response to this problem, this paper proposes a new clustering algorithm, namely an adaptive ellipse distance density peak fuzzy (AEDDPF) clustering algorithm. Firstly, the Euclidean distance is replaced by adaptive ellipse distance, which can more accurately describe the structure of data obtained by radar measurement vehicles. Secondly, the adaptive exponential function curve is introduced in the decision graph of the fast density peak search algorithm to accurately select the density peak point, and the initialization of the AEDDPF algorithm is completed. Finally, the membership matrix and the clustering center are calculated through successive iterations to obtain the clustering result.The time complexity of the AEDDPF algorithm is analyzed. Compared with the density-based spatial clustering of applications with noise (DBSCAN), k-means, fuzzy c-means (FCM), Gustafson-Kessel (GK), and adaptive Euclidean distance density peak fuzzy (Euclid-ADDPF) algorithms, the AEDDPF algorithm has higher clustering accuracy for real measurement data sets in certain scenarios. The experimental results also prove that the proposed algorithm has a better clustering effect in some close-range vehicle scene applications. The generalization ability of the proposed AEDDPF algorithm applied to other types of data is also analyzed.

Discovery of a microbial transglutaminase enabling highly site-specific labeling of proteins.

Microbial transglutaminases (MTGs) catalyze the formation of Gln-Lys isopeptide bonds and are widely used for the cross-linking of proteins and peptides in food and biotechnological applications (e.g. to improve the texture of protein-rich foods or in generating antibody-drug conjugates). Currently used MTGs have low substrate specificity, impeding their biotechnological use as enzymes that do not cross-react with nontarget substrates (i.e. as bio-orthogonal labeling systems). Here, we report the discovery of an MTG from Kutzneria albida (KalbTG), which exhibited no cross-reactivity with known MTG substrates or commonly used target proteins, such as antibodies. KalbTG was produced in Escherichia coli as soluble and active enzyme in the presence of its natural inhibitor ammonium to prevent potentially toxic cross-linking activity. The crystal structure of KalbTG revealed a conserved core similar to other MTGs but very short surface loops, making it the smallest MTG characterized to date. Ultra-dense peptide array technology involving a pool of 1.4 million unique peptides identified specific recognition motifs for KalbTG in these peptides. We determined that the motifs YRYRQ and RYESK are the best Gln and Lys substrates of KalbTG, respectively. By first reacting a bifunctionalized peptide with the more specific KalbTG and in a second step with the less specific MTG from Streptomyces mobaraensis, a successful bio-orthogonal labeling system was demonstrated. Fusing the KalbTG recognition motif to an antibody allowed for site-specific and ratio-controlled labeling using low label excess. Its site specificity, favorable kinetics, ease of use, and cost-effective production render KalbTG an attractive tool for a broad range of applications, including production of therapeutic antibody-drug conjugates.

Genome-wide DNA polymorphism in the indica rice varieties RGD-7S and Taifeng B as revealed by whole genome re-sequencing.

Next-generation sequencing technologies provide opportunities to further understand genetic variation, even within closely related cultivars. We performed whole genome resequencing of two elite indica rice varieties, RGD-7S and Taifeng B, whose F1 progeny showed hybrid weakness and hybrid vigor when grown in the early- and late-cropping seasons, respectively. Approximately 150 million 100-bp pair-end reads were generated, which covered ∼86% of the rice (Oryza sativa L. japonica 'Nipponbare') reference genome. A total of 2,758,740 polymorphic sites including 2,408,845 SNPs and 349,895 InDels were detected in RGD-7S and Taifeng B, respectively. Applying stringent parameters, we identified 961,791 SNPs and 46,640 InDels between RGD-7S and Taifeng B (RGD-7S/Taifeng B). The density of DNA polymorphisms was 256.8 SNPs and 12.5 InDels per 100 kb for RGD-7S/Taifeng B. Copy number variations (CNVs) were also investigated. In RGD-7S, 1989 of 2727 CNVs were overlapped in 218 genes, and 1231 of 2010 CNVs were annotated in 175 genes in Taifeng B. In addition, we verified a subset of InDels in the interval of hybrid weakness genes, Hw3 and Hw4, and obtained some polymorphic InDel markers, which will provide a sound foundation for cloning hybrid weakness genes. Analysis of genomic variations will also contribute to understanding the genetic basis of hybrid weakness and heterosis.

Anti-tumor activity evaluation of novel chrysin-organotin compound in MCF-7 cells.

Chrysin (5,7-dihydroxylflavone, Chry) is a natural flavonoid extracted from plants and propolis. In this work, a novel chrysin-organotin (Chry-Sn) compound with enhanced anticancer activities was synthesized by the reaction of chrysin and triphenyltin chloride, and its potential anticancer effects against cancer cells were measured using various methods. Sulforhodamine B (SRB) results showed that chrysin and Chry-Sn had significant inhibition effects on the proliferation of MCF-7, A549 and HeLa human cancer cell lines in a dose- and time- dependent manner. These results suggested that Chry-Sn possessed enhanced anticancer effects. Hoechst 33258 staining and acridine orange staining results showed apoptosis and nuclei fragments significantly increased after being treated with chrysin and Chry-Sn respectively. Moreover, chrysin and Chry-Sn significantly increased ROS levels in MCF-7 cells. Western blot results showed that chrysin and Chry-Sn activated caspase 3 and induced autophagy by increasing LC3-II level. All results showed collectively that Chry-Sn could be a more promising drug than chrysin in anticancer treatment.

Barriers to HPV immunization among blacks and latinos: a qualitative analysis of caregivers, adolescents, and providers.

BACKGROUND: Despite recommendations that 11-12-year-olds receive the full three-shot Human papillomavirus (HPV) vaccine series, national HPV immunization coverage rates remain low. Disparities exist, with Blacks and Latinos being less likely than Whites to complete the series. We aimed to identify and compare barriers to HPV immunization perceived by healthcare providers, Black and Latino adolescents, and their caregivers to inform a clinic-based intervention to improve immunization rates. METHODS: We conducted semi-structured interviews between March and July 2014 with Black and Latino adolescents (n = 24), their caregivers (n = 24), and nurses (n = 18), and 2 focus groups with 18 physicians recruited from two pediatric primary care clinics. Qualitative protocol topics included: general perceptions and attitudes towards vaccines; HPV knowledge; and perceived individual and systems-level barriers affecting vaccine initiation and completion. RESULTS: Themes were identified and organized by individual and systems-level barriers to HPV immunization. Adolescents and their caregivers, particularly Blacks, expressed concerns about HPV being an untested, "newer" vaccine. All families felt they needed more information on HPV and found it difficult to return for multiple visits to complete the vaccine series. Providers focused on challenges related to administering multiple vaccines simultaneously, and perceptions of parental reluctance to discuss sexually transmitted infections. CONCLUSIONS: Optimizing HPV immunization rates may benefit from a multi-pronged approach to holistically address provider, structural, and individual barriers to care. Further research should examine strategies for providing multiple modalities of support for providers, including a routinized system of vaccine promotion and delivery, and for addressing families' concerns about vaccine safety and efficacy.

Combination of intratypic and intertypic recombinant events in EV71: a novel evidence for the "triple-recombinant" strains of genotype A viruses in Mainland China from 2008 to 2010.

The first Enterovirus 71 (EV71) strain isolated in 1969 was classified as genotype A. It is interesting that the genotype A disappeared nearly 40 years until its re-emergence in mainland China in 2008-2010. Few studies on genetic characterization of the re-emerged genotype A viruses have been reported. In this study, a series of analyses were performed on molecular epidemiology and genome recombination of genotype A viruses in China. Phylogenetic analysis indicated that except for 17 reported genotype A strains and 3 orphan strains (C0, C3 and B5), almost all EV71 strains in mainland China were belonging to subgenotype C4 during 1987-2011. The subgenotype C4 was further divided into 3 clades C4a1, C4a2, and C4b. The genotype A viruses co-circulated with the predominant clade C4a2 and the re-emerged clade C4b both in eastern and central China in 2008-2009. Moreover, comprehensive recombination analysis showed that the genotype A viruses were "triple-recombinant" by combination of intratypic and intertypic recombination. Intertypic recombination between the oldest C4b strain (SHZH98) and Coxsackievirus A5 (CVA5) and intratypic recombination between the SHZH98 and C1 strains both with one junction in 5'-UTR were observed for some specific C4a2 strains and the re-emerged C4b strain, respectively. And intratypic recombination between the re-emerged C4b strain and the specific C4a2 strains with one junction in 5'-UTR was observed for the Chinese genotype A viruses. Taken together, these results provided potential explanations for the genesis of Chinese genotype A viruses which were significant for preventing and controlling outbreaks.

A novel double-image encryption scheme based on cross-image pixel scrambling in gyrator domains.

Recently, a number of double-image cryptosystems have been developed. However, there are notable security performance differences between the two encryption channels in these algorithms. This weakness downgrades the security level and practicability of these cryptosystems, as the cryptosystems cannot guarantee all the input images be transmitted in the channel with higher security level. In this paper, we propose a novel double-image encryption scheme based on cross-image pixel scrambling in gyrator domains. The two input images are firstly shuffled by the proposed cross-image pixel scrambling approach, which can well balance the pixel distribution across the input images. The two scrambled images will be encoded into the real and imaginary parts of a complex function, and then converted into gyrator domains. An iterative architecture is designed to enhance the security level of the cryptosystem, and the cross-image pixel scrambling operation is performed to the real and imaginary parts of the generated complex encrypted data in each round. Numerical simulation results prove that a satisfactory and balanced security performance can be achieved in both channels.