Search

ObjectiveThe present study is designed to study the analgesic and sedative effect of different doses of dexmedetomidine combined with butorphanol in continuous analgesia after a cesarean section.MethodsA total of 60 puerperae undergoing a cesarean section recruited from a single center were divided into three groups according to the postoperative continuous analgesia protocol: control group (100 mL of normal saline containing 10 µg/kg fentanyl and 0.25 mg of palonosetron, 2 mL/h for continuous analgesia for 48 h), DB1 group (100 mL of normal saline containing 1.0 µg/kg dexmedetomidine, 4 mg of butorphanol, 10 µg/kg fentanyl, and 0.25 mg of palonosetron, 2 mL/h for continuous analgesia for 48 h), and DB2 group (100 mL normal saline containing 2.0 µg/kg dexmedetomidine, 4 mg of butorphanol, 10 µg/kg fentanyl, and 0.25 mg of palonosetron, 2 mL/h for continuous analgesia for 48 h). We compared the blood pressure, heart rate, oxygen saturation, VAS score, Ramsay score, and adverse reactions of puerperae among the three groups after surgery.ResultsThe baseline data all have no significant difference in the three groups (p > 0.05). Compared with those in the control group, the systolic blood pressure, diastolic blood pressure, heart rate, and VAS score of the puerperae in the DB1 group and DB2 group were significantly decreased at 6, 24, and 48 h (P 0.05).ConclusionDexmedetomidine combined with butorphanol can improve the analgesic and sedative effects in continuous analgesia after a cesarean section, and the analgesic and sedative effects of dexmedetomidine in the high-dose group are better than those in the low-dose group.

Abstract The neurocranium changes rapidly in early childhood to accommodate the growing brain. Developmental disorders and environmental factors such as sleep position may lead to abnormal neurocranial maturation. Therefore, it is important to understand how this structure develops, in order to provide a baseline for early detection of anomalies. However, its anatomy has not yet been well studied in early childhood due to the lack of available imaging databases. In hospitals, CT is typically used to image the neurocranium when a pathology is suspected, but the presence of ionizing radiation makes it harder to construct databases of healthy subjects. In this study, instead, we use a dataset of MRI data from healthy normal children in the age range of 6 months to 36 months to study the development of the neurocranium. After extracting its outline from the MRI data, we used a conformal geometry-based analysis pipeline to detect local thickness growth throughout this age span. These changes will help us understand cranial bone development with respect to the brain, as well as detect abnormal variations, which will in turn inform better treatment strategies for implicated disorders.

To improve the color stability of facial prosthesis silicone rubber, this paper studied the effect of nano titanium oxide with different surface treatments on the color stability of red pigment-colored silicone rubber. Under the simulated sunlight aging condition, this paper takes MDX4-4210 silicone rubber as the matrix, silicon aluminum-coated nano TiO2 as the shading agent, and cadmium red oil paint as the colorant, and it observes the values of silicon aluminum-coated nano-TiO2 silicone rubber film with 1 mm thickness and different concentrations (0, 0.05%, 0.10%, and 0.15%) before and after aging. The experimental results showed that in the four concentrations of silicon aluminum-coated nano-TiO2 film, the ΔE,ΔL∗, Δa∗, Δb∗ values gradually decreased with the increase of the concentration of silicon aluminum-coated nano-TiO2. The lowest was in the 0.10% group; however, it increased in the 0.15% group. There was a significant difference among the concentration groups P

Thermal decomposition kinetics and solution thermodynamics of two polymorphs, felodipine form I and form IV, were investigated. The thermal decomposition kinetics of the polymorphs, containing thermal decomposing mechanism and the kinetic parameters were studied under non-isothermal conditions using Popescu method, and the shelf life was simply calculated. The results showed that nucleation and growth (n = 3/4) of Avremi–Erofeev equation is the most probable mechanism function for form I, and the integral form is G(α) = [−ln(1 − α)]3/4; while the Mample Powel law (n = 1) is the most probable mechanism function for form IV, corresponding to G(α) = α. Notably, the individual amorphous phases of crystal felodipine form I and IV were obtained after the heating–cooling cycle of DSC tests, which were identified by TMDSC and FT-IR measurements. As the interim products before the collapse, it can be inferred that different amorphous intermediates may be the determinant for different thermal decomposition mechanisms of crystal forms I and IV. The solubility data and solution thermodynamic parameters, including enthalpy, entropy and Gibbs free energy have also been calculated by Van’t Hoff equation in ethanol aqueous. The results illustrated the polymorphic pair is enantiotropic with the transition temperature of 322.23 K and the conversion is driven by entropy.

Functional near-infrared spectroscopy (fNIRS) is widely used in brain science. The sensitivity and signal-to-noise ratio (SNR) are core parameters during the measurement. However, previous studies have not systematically analyzed the parameters in whole-brain measurements which limits its further improvement. In this paper, a noise model was established, including electronic noise, shot noise and speckle noise. Considering different brain regions and different source-detector(S-D) separation, a Monte Carlo simulation tool was utilized to simulate the photons migration inside a realistic human-brain template (Colin27). Based on the simulation, we analyzed the light fluence-rate distribution, detection-sensitivity, noise composition and SNR. The results show that sensitivity is positively correlated with S-D separations and the parietal region has the lowest sensitivity. In terms of noise, the equivalent noise power in different brain regions were consistent, and the noise proportions varied greatly under different S-D conditions and the SNR decreased by about 45 dB in the S-D range 10 mm~45 mm. Based on the results, a fNIRS system optimization strategy is proposed and in our simulation conditions, we suggest an optimal S-D in frontal, temporal, parietal and occipital lobes are 30 mm, 25 mm, 30 mm, 30 mm respectively. The systematical analysis method will contribute to guiding the optimal design of the fNIRS system.

Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. One of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research focuses in the AD pathophysiological progress. This work proposes a novel framework, Federated Morphometry Feature Selection (FMFS) model, to examine subtle aspects of hippocampal morphometry that are associated with Aβ/tau burden in the brain, measured using positron emission tomography (PET). FMFS is comprised of hippocampal surface-based feature calculation, patch-based feature selection, federated group LASSO regression, federated screening rule-based stability selection, and region of interest (ROI) identification. FMFS was tested on two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts to understand hippocampal alterations that relate to Aβ/tau depositions. Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects. Experimental results demonstrated that FMFS achieves an 89× speedup compared to other published state-of-the-art methods under five independent hypothetical institutions. In addition, the subiculum and cornu ammonis 1 (CA1 subfield) were identified as hippocampal subregions where atrophy is strongly associated with abnormal Aβ/tau. As potential biomarkers for Aβ/tau pathology, the features from the identified ROIs had greater power for predicting cognitive assessment and for survival analysis than five other imaging biomarkers. All the results indicate that FMFS is an efficient and effective tool to reveal associations between Aβ/tau burden and hippocampal morphometry.

The composition and content of sugar and acid are important indicators of organ development and the quality of horticultural products. B. juncea is an important vegetable in the cruciferous family, with a swollen fleshy stem as the edible organ. Elucidating the characteristics of sugar and acid accumulation during stem expansion of stem mustard and its regulatory mechanism could enhance stem quality. In this study, physiological indicators such as dry matter content, sugar–acid content and related enzyme activities were measured in eight stages of the tumorous stem. The results showed that the sugar and sucrose contents initially increased and then decreased during stem development: Sucrose exhibited a positive correlation with sucrose synthase and sucrose phosphate synthase, while acid content was highly positively correlated with malate dehydrogenase. Further analysis of the dynamic patterns of sugar and acid metabolite contents using metabolomics showed that 1097 metabolites were detected, including 229 organic acids and derivatives, 109 lipids, and other metabolites. Metabolic pathway enrichment analysis showed that metabolites were significantly enriched in organic acids, amino acids, glycolysis/gluconeogenesis, starch, and sucrose metabolism. Analysis of the sugar pathway and the tricarboxylic acid cycle revealed obvious differences in the content and type of metabolites, with most upregulated metabolites in S3 and S4. The expression patterns of enzyme genes associated with the biosynthesis and accumulation of sugar and acid metabolites were found based on differentially expressed genes at different developmental stages, and gene expression levels were verified by qPCR, which showed that the expression patterns of enzyme genes associated with this pathway were highly consistent with the metabolite accumulation. These results suggest that amino acids, sugars, and acids play a critical role in regulating the development of tumorous stems. Results of the present study offer a theoretical basis to improving the quality of mustard by using a metabolomics approach to determine the dynamics of metabolites and related regulatory enzymes during development and the correlation between these levels, which provides novel insights into the potential mechanisms underlying sugar and acid metabolism.

Micromixers have significant potential in the field of chemical synthesis and biological pharmaceuticals, etc. In this study, the design and numerical simulations of a passive micromixer and a novel active electroosmotic micromixer by assembling electrode pairs were both presented with a cosine channel wall. The finite element method (FEM) coupled with Multiphysics modeling was used. To propose an efficient micromixer structure, firstly, different geometrical parameters such as amplitude-to-wavelength ratio (a/c) and mixing units (N) in the steady state without an electric field were investigated. This paper aims to seek a high-quality mixing solution. Therefore, based on the optimization of the above parameters of the passive micromixer, a new type of electroosmotic micromixer with an AC electric field was proposed. The results show that the vortices generated by electroosmosis can effectively induce fluid mixing. The effects of key parameters such as the Reynolds number, the number of electrode pairs, phase shift, voltage, and electrode frequency on the mixing performance were specifically discussed through numerical analysis. The mixing efficiency of the electroosmotic micromixer is quantitatively analyzed, which can be achieved at 96%. The proposed micromixer has a simple structure that can obtain a fast response and high mixing index.

ObjectiveThis study aimed to evaluate the feasibility and efficacy of ultrasound-guided percutaneous microwave ablation (MWA) in the treatment of low-risk papillary thyroid microcarcinoma (PTMC), and to observe the histopathological changes after MWA.MethodsMWA was performed under ultrasound guidance for 73 unifocal PTMC patients without clinically cervical or distant metastasis. The target ablation zone exceeded the tumor edge (judged by contrast-enhanced US) to avoid marginal residue and recurrence. Ultrasound evaluation was performed at 1 day, 1, 3, 6, 12 and 24 months after treatment, and thyroid function evaluation at the first 6 months. Repeated fine needle aspiration cytology or core needle biopsy pathology was performed at 3 or 6 months after MWA to evaluate residual tumors. Any adverse event associated with MWA was evaluated.ResultsThe follow-up after MWA lasted 6 (6, 12) months. Tumor volume decreased significantly from 0.06 mm3 (0.04, 0.11 mm3) to 0.03 mm3 (0.00, 0.06 mm3) at 12 months after MWA (P< 0.001), with a median volume reduction ratio of 80.28% (-7.43, 100%) and 16 cases (21.92%) presenting complete remission. The largest diameter, volume and ablation energy were found to be different in patients with and without complete remission 12 months after MWA. On histopathological examinations, no atypical or malignant follicular cells were identified after thermal ablation. The most common pathological characteristics were fibroblastic proliferation (34/39, 87.18%) and chronic inflammation (32/39, 82.05%), followed by infarction (21/39, 53.85%). Five patients were transferred to thyroidectomy and 4 of them were confirmed with local recurrence and/or lymph node metastasis. Serum thyrotropin decreased transiently after MWA (P< 0.01) but normalized thereafter. No serious and permanent complications were reported.ConclusionsMWA is a safe and effective treatment for low-risk PTMC. Fibroblastic proliferation and chronic inflammation are the most common pathological changes after MWA of PTMC.

This paper presents an experimental study to investigate the heat transfer limit of a micro-grooved OHP at the vertical bottom heat mode. The internal hydraulic diameter of the micro-grooved OHP is about 2.0 mm, and deionized water was used as a working fluid at volumetric filling ratios (FRs) ranging from 30% to 60%. Experimental results demonstrated that the micro-grooved OHP could significantly enhance the allowable maximum input heat flux before the occurrence of dry-out owing to the capillary action provided by micro-grooved structures to facilitate condensate backflow to the evaporator. The OHP obtained a maximum effective thermal conductivity of 41.8 kW/(m·°C) at 40% FR, corresponding to a dry-out heat flux of 36.9 W/cm2 with respect to the heat transfer limit. The allowable maximum input heat flux was found to be greater than 80 W/cm2 for 50% and 60% FRs, and could be further increased by increasing the OHP turn number. This study provides a promising option to address thermal management demand for high-density power devices.

Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that magnetic resonance imaging (MRI)-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain Aβ burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) [Accuracy (ACC) = 0.89 (ADNI)] and in cognitively unimpaired (CU) individuals [ACC = 0.79 (ADNI) and ACC = 0.81 (OASIS)]. These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.

Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps.

Wide band gap (WBG) power electronic devices, such as silicon carbide metal–oxide–semiconductor field-effect transistors (SiC MOSFETs) and gallium–nitride high-electron-mobility transistors (GaN HEMTs) have been widely used in various fields and occupied a certain share of the market with rapid momentum, owing to their excellent electrical, mechanical, and thermal properties. The reliability of WBG power electronic devices is inseparable from the reliability of power electronic systems and is a significant concern for the industry and for academia. This review attempts to summarize the recent progress in the failure mechanisms of WBG power electronic semiconductor chips, the reliability of WBG power electronic packaging, and the reliability models for predicting the remaining life of WBG devices. Firstly, the typical structures and dominant failure mechanisms of SiC MOSFETs and GaN HEMTs are discussed. This is followed by a description of power electronic packaging failure mechanisms and available packaging materials for WBG power electronic devices. In addition, the reliability models based on physics-of-failure (including time-dependent dielectric breakdown models, stress–strain models, and thermal cycling models), and data-driven models are introduced. This review may provide useful references for the reliability research of WBG power devices.

Grazing, as an important land use method in grassland, has a significant impact on the morphological and physiological traits of plants. However, little is known about how the molecular mechanism of plant responds to different grazing intensities. Here, we investigated the response of Taraxacum mongolicum to light grazing and heavy grazing intensities in comparison with a non-grazing control. Using de novo transcriptome assembly, T. mongolicum leaves were compared for the expression of the different genes under different grazing intensities in natural grassland. In total, 194,253 transcripts were de novo assembled and comprised in nine leaf tissues. Among them, 11,134 and 9058 genes were differentially expressed in light grazing and heavy grazing grassland separately, with 5867 genes that were identified as co-expression genes in two grazing treatments. The Nr, SwissProt, String, GO, KEGG, and COG analyses by BLASTx searches were performed to determine and further understand the biological functions of those differentially expressed genes (DEGs). Analysis of the expression patterns of 10 DEGs by quantitative real-time RT-PCR (qRT-PCR) confirmed the accuracy of the RNA-Seq results. Based on a comparative transcriptome analysis, the most significant transcriptomic changes that were observed under grazing intensity were related to plant hormone and signal transduction pathways, carbohydrate and secondary metabolism, and photosynthesis. In addition, heavy grazing resulted in a stronger transcriptomic response compared with light grazing through increasing the of the secondary metabolism- and photosynthesis-related genes. These changes in key pathways and related genes suggest that they may synergistically respond to grazing to increase the resilience and stress tolerance of T. mongolicum. Our findings provide important clues for improving grassland use and protection and understanding the molecular mechanisms of plant response to grazing.

With the development of power modules for high voltage, high temperature, and high power density, their size is becoming smaller, and the packaging insulation experiences higher electrical, thermal, and mechanical stress. Packaging insulation needs to meet the requirement that internal electric field, temperature, and mechanical stress should be as low as possible. Focusing on the coupling principles and optimization design among electrical, thermal, and mechanical stresses in the power module packaging insulation, a multi-objective optimization design method based on Spice circuit, finite element field numerical calculation, and multi-objective gray wolf optimizer (MOGWO) is proposed. The packaging insulation optimal design of a 1.2 kV SiC MOSFET half-bridge power module is presented. First, the high field conductivity characteristics of the substrate ceramic and encapsulation silicone of the packaging insulation material were tested at different temperatures and external field strengths, which provided the key insulation parameters for the calculation of electric field distribution. Secondly, according to the mutual coupling principles among electric–thermal–mechanical stress, the influence of packaging structure parameters on the electric field, temperature, and mechanical stress distribution of packaging insulation was studied by finite element calculation and combined with Spice circuit analysis. Finally, the MOGWO algorithm was used to optimize the electric field, temperature, and mechanical stress in the packaging insulation. The optimal structural parameters of the power module were used to fabricate the corresponding SiC MOSFET module. The fabricated module is compared with a commercial module by the double-pulse experiment and partial discharge experiment to verify the feasibility of the proposed design method.

Background and purpose: Adaptive radiation planning for pancreatic adenocarcinoma (PA) relies on accurate treatment response assessment, while traditional response evaluation criteria inefficiently characterize tumors with complex morphological features or intrinsically low metabolism. To better assess treatment response of PA, we quantify and compare regional morphological and metabolic features of the 3D pre- and post-radiation therapy (RT) tumor models. Materials and methods: Thirty-one PA patients with pre and post-RT Positron emission tomography/computed tomography (PET/CT) scans were evaluated. 3D meshes of pre- and post-RT tumors were generated and registered to establish vertex-wise correspondence. To assess tumor response, Mahalanobis distances (Mdist|Fusion) between pre- and post-RT tumor surfaces with anatomic and metabolic fused vectors were calculated for each patient. Mdist|Fusion was evaluated by overall survival (OS) prediction and survival risk classification. As a comparison, the same analyses were conducted on traditional imaging/physiological predictors, and distances measurements based on metabolic and morphological features only. Results: Among all the imaging/physiological parameters, Mdist|Fusion was shown to be the best predictor of OS (HR = 0.52, p = 0.008), while other parameters failed to reach significance. Moreover, Mdist|Fusion outperformed traditional morphologic and metabolic measurements in patient risk stratification, either alone (HR = 11.51, p

Operational optimization is essential in modern industry and unsuitable operations will deteriorate the performance of industrial processes. Since measuring error and multiple working conditions are inevitable in practice, it is necessary to reduce their negative impacts on operational optimization under the case-based reasoning (CBR) framework. In this paper, a local density-based abnormal case removal method is proposed to remove the abnormal cases in a case retrieval step, so as to prevent performance deterioration in industrial operational optimization. More specifically, the reasons as to why classic CBR would retrieve abnormal cases are analyzed from the perspective of case retrieval in industry. Then, a local density-based abnormal case removal algorithm is designed based on the Local Outlier Factor (LOF), and properly integrated into the traditional case retrieval step. Finally, the effectiveness and the superiority of the local density-based abnormal case removal method was tested by a numerical simulation and an industrial case study of the cut-made process of cigarette production. The results show that the proposed method improved the operational optimization performance of an industrial cut-made process by 23.5% compared with classic CBR, and by 13.3% compared with case-based fuzzy reasoning.

Background/Aims: Lung cancer is the leading cause of cancer-related deaths worldwide. The outcome of patients with non-small cell lung cancer remains poor; the 5-year survival rate for stage IV non-small cell lung cancer is only 1.0%. KIF15 is a tetrameric kinesin spindle motor that has been investigated for its regulation of mitosis. While the roles of kinesin motor proteins in the regulation of mitosis and their potentials as therapeutic targets in pancreatic cancer have been described previously, the role of KIF15 in lung cancer development remains unknown. Methods: Paired lung carcinoma specimens and matched adjacent normal tissues were used for protein analysis. Clinical data were obtained from medical records. We first examined KIF15 messenger RNA expression in The Cancer Genome Atlas database, and then determined KIF15 protein levels using immunohistochemistry and western blotting. Differences between the groups were analyzed using repeated measures analysis of variance. Overall survival was analyzed using the Kaplan–Meier method. Cell-cycle and proliferation assays were conducted using A549, NCI-H1299, and NCI-H226 cells. Results: KIF15 was significantly upregulated at both the messenger RNA and protein levels in human lung tumor tissues. In patients with lung adenocarcinoma, KIF15 expression was positively associated with disease stages; high KIF15 expression predicted a poor prognosis. KIF15 knockdown using short hairpin RNA in two human lung adenocarcinoma cell lines induced G1/S phase cell cycle arrest and inhibited cell growth, but there was no effect in human lung squamous cell carcinoma. Conclusion: Our findings show that KIF15 is involved in lung cancer carcinogenesis. KIF15 could therefore serve as a specific prognostic marker for patients with lung adenocarcinoma.

Aim of study: To investigate how the cross section of a drip-irrigation tape affects local head loss. Area of study: The work was carried out in the laboratory of Irrigation hydraulics, College of Water Conservancy and Environment, Three Gorges University, Yichang, Hubei province. Material and methods: Tapes with six different wall thicknesses were studied experimentally to determine the relationship between cross-section deformation, wall thickness, and pressure. Based on the experimental results, we determined the factors that influence local head loss in drip-irrigation tapes by numerical simulation and dimensional analysis. Main results: The cross-sectional shape of the drip-irrigation tape varied with pressure: under low pressure, the cross section was nearly elliptical. The cross-sectional shape of the tape strongly influenced the local head loss, which was inversely proportional to the 0.867th power of the flattening coefficient of the drip irrigation tape. We expressed the local head loss of a drip-irrigation tape equipped with integrated in-line emitters by considering the deformation of the cross section. Under the conditions used in this study, when the cross section is circular, the ratio of local head loss to frictional head loss was about 10% but, when the cross section is elliptical, this ratio increased to 15%. Research highlights: The shape of the cross section of a drip-irrigation tape is nearly elliptical under low pressure. Local head loss is inversely proportional to the 0.867th power of that is the flatting coefficient of the drip-irrigation tape. Local head loss is about 1.5 times for elliptical tape than circular tape.

Pseudorabies (PR), also known as Aujeszky's disease, is an acute infectious disease of pigs, resulting in significant economic losses to the pig industry in many countries. Since 2011, PR outbreaks have occurred in many Bartha-K61-vaccinated pig farms in China. The emerging pseudorabies virus (PRV) variants possess higher pathogenicity in pigs and mice than the strains isolated before. Here, a recombinant PRV (rPRVTJ-NLuc) stably expressing the NanoLuc (NLuc) luciferase fusion with the red fluorescent protein (DsRed) was constructed to trace viral replication and spread in mice. Moreover, both DsRed and NLuc luciferases were stably expressed in the infected cells, and there was no significant difference between wild-type and recombinant viruses in both growth kinetics and pathogenicity. Seven-week-old BALB/c mice were infected with 103 50% tissue culture infective dose rPRVTJ-NLuc and subjected to daily imaging. The mice infected with rPRVTJ-NLuc displayed robust bioluminescence that started 4 days postinfection (dpi), bioluminescence signal increased over time, peaked at 5 dpi, remained detectable for at least 6 dpi, and disappeared at 7 dpi, meanwhile, the increased flux accompanied by the spread of the virus from the injection site to the superior respiratory tract. However, the signal was also observed in the spinal cord, trigeminal ganglion, and partial region of the brain from separated tissues, not in living mice. Our results depicted a new approach to rapidly access the replication and pathogenicity of emerging PRVs in mice.

Background: In the pathogenesis of Alzheimer's disease (AD), microglia play an increasingly important role. Molecular imaging of neuroinflammatory targeting microglia activation and the high expression of 18-kDa translocator protein (TSPO) has become a hot topic of research in recent years. Dynamic monitoring neuroinflammation is crucial for discovering the best time point of anti-inflammatory therapy. Motivated by this, Positron emission tomography (PET) imaging in an APP/PS1 mouse model of AD, using 18F-labeled DPA-714 to monitor microglia activation and neuroinflammation, were performed in this paper.Methods: We prepared [18F]DPA714 and tested the biological characteristics of the molecular probe in normal mice. To obtain a higher radiochemical yield, we improved the [18F]-fluorination conditions in the precursor dosage, reaction temperature, and synthesis time. We performed [18F]DPA714 PET scanning on APP/PS1 mice at 6–7, 9–10, 12–13, and 15–16 months of age, respectively. The same experiments were conducted in Wild-type (Wt) mice as a control. Referring to the [18F]DPA714 concentrated situation in the brain, we performed blocking experiments with PK11195 (1 mg/kg) in 12–13-months-old APP/PS1 mice to confirm the specificity of [18F]DPA714 for TSPO in the APP/PS1 mice. Reconstructed brain PET images, fused with the Magnetic Resonance Imaging (MRI) template atlas, and the volumes of interests (VOIs) of the hippocampus and cortex were determined. The distribution of [18F]DPA714 in the brain tissues of 15–16-months-old APP/PS1 and Wt mice were studied by immunofluorescence staining.Results: Through the reaction of 18F, with 2 mg precursor dissolved in 300 ul acetonitrile at 105°C for 10 min, we obtained the optimal radiochemical yield of 42.3 ± 5.1% (non-decay correction). Quantitative analysis of brain PET images showed that the [18F]DPA714 uptake in the cortex and hippocampus of 12–13-months-old APP/PS1 mice was higher than that of the control mice of the same age (cortex/muscle: 2.77 ± 0.13 vs. 1.93 ± 0.32, p = 0.0014; hippocampus/muscle: 3.33 ± 0.10 vs. 2.10 ± 0.35, p = 0.0008). The same significant difference was found between 15- and 16-months-old APP/PS1 mice (cortex/muscle: 2.64 ± 0.14 vs. 1.86 ± 0.52, p=0.0159; hippocampus/muscle: 2.89 ± 0.53 vs. 1.77 ± 0.48, p = 0.0050). Immunofluorescence staining showed that the activation of microglia and the level of TSPO expression in the cortex and hippocampus of APP/PS1 mice were significantly higher than Wt mice.Conclusion: [18F]DPA714, a molecular probe for targeting TSPO, showed great potential in monitoring microglia activation and neuroinflammation, which can be helpful in discovering the best time point for anti-inflammatory therapy in AD.

Current researches on default mode network (DMN) in normal elderly have mainly focused on finding some dysfunctional areas with decreased or increased connectivity. The global network dynamics of apolipoprotein E (APOE) e4 allele group is rarely studied. In our previous brain network study, we have demonstrated the advantage of persistent homology. It can distinguish robust and noisy topological features over multiscale nested networks, and the derived properties are more stable. In this study, for the first time we applied persistent homology to analyze APOE-related effects on whole-brain functional network. In our experiments, the risk allele group exhibited lower network radius and modularity in whole brain DMN based on graph theory, suggesting the abnormal organization structure. Moreover, two suggested measures from persistent homology detected significant differences between groups within the left hemisphere and in the whole brain in two datasets. They were more statistically sensitive to APOE genotypic differences than standard graph-based measures. In summary, we provide evidence that the e4 genotype leads to distinct DMN functional alterations in the early phases of Alzheimer’s disease using persistent homology approach. Our study offers a novel insight to explore potential biomarkers in healthy elderly populations carrying APOE e4 allele.

Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage.

Projection regression is an important tool for process soft sensing in order to eliminate redundant information and obtain proper data features. As most industrial process is intrinsically nonlinear and process variables are collected in random noise environment, it is significant to adopt probabilistic nonlinear latent variable model to carry out dimension reduction for feature extraction before regression modeling. Generative topographic mapping (GTM) is such a probabilistic nonlinear model. However, GTM is an unsupervised method, in which the extracted features may include irrelevant ones with the output information. Thus, it may result in inaccuracy of soft sensor performance. To deal with this problem, a generative topographic mapping regression is developed based on supervised GTM in this paper, which incorporates the output information to guide feature extraction and projection regression. By utilizing the output to jointly generate the latent variables, output-related features can be extracted for output prediction. The effectiveness and flexibility of the proposed method are validated on a numerical example and an industrial process.

This paper proposes a flotation performance recognition system based on a hierarchical classification of froth images using both local dynamic and static features, which includes a series of functions in image extraction, processing, and classification. Within the integrated system, to identify the abnormal working condition with poor flotation performance (NB it could be significantly different with the dynamic features of the froth in abnormal working condition), it is functioned first with building up local dynamic features of froth image from the information including froth velocity, disorder degree, and burst rate. To enhance the dynamic feature extraction and matching, this system introduces a scale-invariant feature transform method to cope with froth motion and the noise induced by dust and illumination. For the performance subdividing under normal working conditions, bag-of-words (BoW) description is utilized to fill the semantic gap in performance recognition when images are directly described by global image features. Accordingly typical froth status words are extracted to form a froth status glossary so that the froth status words of each patch form the BoW description of an image. A Bayesian probabilistic model is built to establish a froth image classification reference with the BoW description of images as the input. An expectation-maximization algorithm is used for training the model parameters. Data obtained from a real plant are selected to verify the proposed approach. It is noted that the proposed system can reduce the negative effects of image noise, and has high accuracy in flotation performance recognition.

In industrial processes, it is of great significance to carry out steady-state detection (SSD) for effective system modeling, operation optimization, performance evaluation, and process monitoring. Traditional SSD approaches often need to identify process state for each variable and obtain a composite index with sliding window technique, which ignores the variable correlations and is time consuming. Moreover, they can only provide the state of each whole window that slides along data series. To deal with these problems, a novel sliding window principal component analysis-improved polynomial fitting based method is proposed for steady-state detection. In the proposed framework, principal component analysis is first used to eliminate the data correlations and variable noises. Then, the size of sliding window is automatically determined by the data series of the first principal component. After that, SSD is carried out for each selected principal component by 2nd-order improved polynomial fitting. At last, the overall process state is determined by the weighted combination of the SSD results of selected principal components, in which the weight of each principal component is determined by its corresponding contribution of variance. The effectiveness and flexibility of the proposed SSD framework is validated on an industrial hydrocracking process.

Abstract Background In recent years, proinflammatory cytokine interleukin-1β (IL-1β) was considered to play a critical role in the pathogenesis of depression. In addition, P2X7 receptor (P2X7R), a member of the purinergic receptor family, which is predominantly present on microglia, as well as on astrocytes and neurons in lesser amounts in the central nervous system, was suggested to be involved in the processing and releasing of IL-1β. Here, we investigated the role of P2X7R in the pathogenesis of depression. Methods Male Sprague-Dawley rats were subjected to chronic unpredictable stressors (CUS) for 3 weeks. At the end of week 1, 2, and 3, extracellular ATP, caspase 1, IL-1β, and components and activation of NLRP3 inflammasome (nucleotide-binding, leucine-rich repeat, pyrin domain containing 3) were evaluated as biomarker of neuroinflammation. In separate experiments, the rats were microinjected with P2X7R agonists ATP, BzATP, and saline into the hippocampus, respectively, or exposed to CUS combined with hippocampal microinjection with P2X7R antagonist, BBG and A438079, and saline, respectively, for 3 weeks, followed by exposed to forced swimming test and open-field test. Moreover, we also evaluated the depressive and anxiety-like behavior of P2X7-null mice in forced swimming test, open-field test, and elevated plus maze. Results Along with stress accumulation, extracellular ATP, cleaved-caspase 1, IL-1β, and ASC were significantly enhanced in the hippocampus, but P2X7R and NLRP3 were not. Immunoprecipitation assay indicated that along with the accumulation of stress, assembly of NLRP3 inflammasome and cleaved caspase 1 in NLRP3 inflammasome were significantly increased. Moreover, antagonists of P2X7R, either BBG or A438079, prevented the development of depressive-like behaviors induced by chronic unpredictable stress in rats. Meanwhile, we could not observe any depressive-like or anxiety-like behaviors of P2X7-null mice after they had been exposed to CUS. The results implied that P2X7 knockout could impede the development of depressive-like and anxiety-like behaviors induced by CUS. In contrast, chronic administration of agonists of P2X7R, either ATP or BzATP, could induce depressive-like behaviors. Conclusions The activation of P2X7R and subsequent NLRP3 inflammasome in hippocampal microglial cells could mediate depressive-like behaviors, which suggests a new therapeutic target for the prevention and treatment of depression.

Understanding the extent to which vascular disease and its risk factors are associated with prodromal dementia, notably Alzheimer's disease (AD), may enhance predictive accuracy as well as guide early interventions. One promising avenue to determine this relationship consists of looking for reliable and sensitive in-vivo imaging methods capable of characterizing the subtle brain alterations before the clinical manifestations. However, little is known from the imaging perspective about how risk factors such as vascular disease influence AD progression. Here, for the first time, we apply an innovative T1 and DTI fusion analysis of 3D corpus callosum (CC) on mild cognitive impairment (MCI) populations with different levels of vascular profile, aiming to de-couple the vascular factor in the prodromal AD stage. Our new fusion method successfully increases the detection power for differentiating MCI subjects with high from low vascular risk profiles, as well as from healthy controls. MCI subjects with high and low vascular risk profiles showed differed alteration patterns in the anterior CC, which may help to elucidate the inter-wired relationship between MCI and vascular risk factors.

The strategy of producing rapid initial growth and establishing early in the growing season is important, and it is employed by invasive macrophytes. Elodea nuttallii and Egeria densa, two Hydrocharitaceae species, became weeds after invading many countries in recent years. Comparative studies on their invasive traits in relation to native species during winter and spring are limited. In the present study, we compared the growth performance of these two exotic species with a perennial native species, Potamogeton maackianus, in different water depths (1, 2, and 3 m) during winter (January and February) and spring (March and April). Three morphological traits (shoot number, root number and shoot length), total biomass, relative growth rate (RGR) and two physiological photosynthetic traits (total chlorophyll content and the maximum quantum yield of PSII [Fv/Fm]) were measured for each macrophyte. All three species could overwinter as entirely leafy plants. Biomass, RGR, morphological traits and physiological traits were all different among species. However, water depths had a significant effect only on morphological traits. At all water depths, E. nuttallii had significantly higher values for morphological traits, total biomass and RGR than P. maackianus, while E. densa had significantly fewer roots and a lower total chlorophyll content than P. maackianus. Except for Fv/Fm at a 3 m water depth, morphological and physiological photosynthetic traits, biomass and RGR of E. nuttallii were significantly higher than those of E. densa. In addition, a large number of adventitious roots developed from E. nuttallii but not from the other two species. These results indicate that the advantages of E. nuttallii to grow in winter and spring may make it more prone to expansion than E. densa in China.

Apolipoprotein E (APOE) e4 is the major genetic risk factor for late-onset Alzheimer's disease (AD). The dose-dependent impact of this allele on hippocampal volumes has been documented, but its influence on general hippocampal morphology in cognitively unimpaired individuals is still elusive. Capitalizing on the study of a large number of cognitively unimpaired late middle aged and older adults with two, one and no APOE-e4 alleles, the current study aims to characterize the ability of our automated surface-based hippocampal morphometry algorithm to distinguish between these three levels of genetic risk for AD and demonstrate its superiority to a commonly used hippocampal volume measurement. We examined the APOE-e4 dose effect on cross-sectional hippocampal morphology analysis in a magnetic resonance imaging (MRI) database of 117 cognitively unimpaired subjects aged between 50 and 85 years (mean = 57.4, SD = 6.3), including 36 heterozygotes (e3/e4), 37 homozygotes (e4/e4) and 44 non-carriers (e3/e3). The proposed automated framework includes hippocampal surface segmentation and reconstruction, higher-order hippocampal surface correspondence computation, and hippocampal surface deformation analysis with multivariate statistics. In our experiments, the surface-based method identified APOE-e4 dose effects on the left hippocampal morphology. Compared to the widely-used hippocampal volume measure, our hippocampal morphometry statistics showed greater statistical power by distinguishing cognitively unimpaired subjects with two, one, and no APOE-e4 alleles. Our findings mirrored previous studies showing that APOE-e4 has a dose effect on the acceleration of brain structure deformities. The results indicated that the proposed surface-based hippocampal morphometry measure is a potential preclinical AD imaging biomarker for cognitively unimpaired individuals. Keywords: APOE-e4, Hippocampal morphometry, Magnetic resonance imaging (MRI), Alzheimer's disease, Cognitively unimpaired

During the pathogenesis of retinitis pigmentosa (RP), the roles of retinal microglial cells after activation have not been fully elucidated. Herein, experimental RP was induced in Sprague Dawley rats by intraperitoneal injection of N-methyl-N-nitrosourea (MNU) at 50 mg/kg, and the effects of MNU on the retinas were evaluated, respectively, by retinal histology and electroretinography recordings at serial time points. Time-dependent and gradual loss of photoreceptor cells, disrupted arrangement of the outer nuclear layer (ONL), and significant reductions in both a-wave and b-wave amplitudes were observed. Morphology changes were observed in retinal microglial cells; meanwhile, with time, the number of Iba1-positive microglia and their infiltration into the ONL gradually increased. Furthermore, physical interaction of microglial-Müller cell processes following microglial activation was observed after MNU injection. In addition, Müller cells increased CX3CL1 secretion, enhanced microglial cell migration, and upregulated the CX3CR1 expression of the latter. Our observations implied that, during the pathogenesis of RP by MNU, microglial cells exhibit a prominent morphology change and Müller cells can induce activated microglia infiltration by increasing secretion of the chemotaxis factor, CX3CL1, and promoting the migration of retinal microglial cells. This novel finding highlights a potential therapeutic target aimed at regulating the microglial response.

Harmful cyanobacterial blooms frequently occur in shallow eutrophic lakes and usually cause the decline of submerged vegetation. Therefore, artificial aquatic plants (AAPs) were introduced into enclosures in the eutrophic Dianchi Lake to investigate whether or not they could reduce cyanobacterial blooms and promote the growth of submerged macrophytes. On the 60th day after the AAPs were installed, the turbidity, total nitrogen (TN), total phosphorous (TP), and the cell density of phytoplankton (especially cyanobacteria) of the treated enclosures were significantly reduced as compared with the control enclosures. The adsorption and absorption of the subsequently formed periphyton biofilms attached to the AAPs effectively decreased nutrient levels in the water. Moreover, the microbial diversity and structure in the water changed with the development of periphyton biofilms, showing that the dominant planktonic algae shifted from Cyanophyta to Chlorophyta. The biodiversity of both planktonic and attached bacterial communities in the periphyton biofilm also gradually increased with time, and were higher than those of the control enclosures. The transplanted submerged macrophyte (Elodea nuttallii) in treated enclosures recovered effectively and reached 50% coverage in one month while those in the control enclosures failed to grow. The application of AAPs with incubated periphyton presents an environmentally-friendly and effective solution for reducing nutrients and controlling the biomass of phytoplankton, thereby promoting the restoration of submerged macrophytes in shallow eutrophic waters.

The apolipoprotein E (APOE) e4 genotype is a powerful risk factor for late-onset Alzheimer's disease (AD). In the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, we previously reported significant baseline structural differences in APOE e4 carriers relative to non-carriers, involving the left hippocampus more than the right--a difference more pronounced in e4 homozygotes than heterozygotes. We now examine the longitudinal effects of APOE genotype on hippocampal morphometry at 6-, 12- and 24-months, in the ADNI cohort. We employed a new automated surface registration system based on conformal geometry and tensor-based morphometry. Among different hippocampal surfaces, we computed high-order correspondences, using a novel inverse-consistent surface-based fluid registration method and multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance. At each time point, using Hotelling's T(2) test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the full cohort as well as in the non-demented (pooled MCI and control) subjects at each follow-up interval. In the complete ADNI cohort, we found greater atrophy of the left hippocampus than the right, and this asymmetry was more pronounced in e4 homozygotes than heterozygotes. These findings, combined with our earlier investigations, demonstrate an e4 dose effect on accelerated hippocampal atrophy, and support the enrichment of prevention trial cohorts with e4 carriers.