Search

Phase contrast microscope is one of the most universally used instruments to observe long-term cell movements in different solutions. Most of classic segmentation methods consider a homogeneous patch as an object, while the recorded cell images have rich details and a lot of small inhomogeneous patches, as well as some artifacts, which can impede the applications. To tackle these challenges, this paper presents a hierarchical mergence approach (HMA) to extract homogeneous patches out and heuristically add them up. Initially, the maximum region of interest (ROI), in which only cell events exist, is drawn by using gradient information as a mask. Then, different levels of blurring based on kernel or grayscale morphological operations are applied to the whole image to produce reference images. Next, each of unconnected regions in the mask is applied with Otsu method independently according to different reference images. Consequently, the segmentation result is generated by the combination of usable patches in all informative layers. The proposed approach is more than simply a fusion of the basic segmentation methods, but a well-organized strategy that integrates these basic methods. Experiments demonstrate that the proposed method outperforms previous methods within our datasets. [ABSTRACT FROM AUTHOR]

Rhododendron, one of the most famous ornamental plants in the world, is traditionally a medicinal plant. However, the potential bioactivities of native Rhododendron in Taiwan have not been completely studied. In this study, the results revealed that Rhododendron pseudochrysanthum exhibited the best antioxidant activities among 10 native Rhododendron species in Taiwan. Furthermore, based on a bioactivity-guided isolation principle, nine specific phytochemicals were isolated and identified as (2R,3S)-catechin (1), (2R,3R)-epicatechin (1'), (2R,3R)-dihydromyricetin 3-O-β-L-arabinopyranoside (2), (2S,3S)-taxifolin 3-O-β-L-arabinopyranoside (2'), (2R,3R)-taxifolin 3-O-β-L-arabinopyranoside (3), myricetin 3-O-β-d-glucopyranoside (3'), rutin (4), hyperoside (5), and quercitrin (6). Of these compounds, 2 and 3 were found to be major bioactive compounds, and their concentrations in the n-butanol (BuOH) fraction were determined to be 52.0 and 67.3 mg per gram, respectively. These results demonstrated that methanolic extracts of Rhododendron pseudochrysanthum leaves have excellent antioxidant activities and great potential as a source for natural health products. [ABSTRACT FROM AUTHOR]

For mobile radar, offset biases and attitude biases influence radar measurements simultaneously. Attitude biases generated fromthe errors of the inertial navigation system (INS) of the platform can be converted into equivalent radar measurement errors by three analytical expressions (range, azimuth, and elevation, resp.).These expressions are unique and embody the dependences between the offset and attitude biases. The dependences indicate that all the attitude biases can be viewed as and merged into some kind of offset biases. Based on this, a unified registrationmodel (URM) is proposed which only contains radar "offset biases" in the formof system variables in the registration equations, where, in fact, the "offset biases" contain the influences of the attitude biases. URM has the same formas the registrationmodel of stationary radar network where no attitude biases exist. URM can compensate radar offset and attitude biases simultaneously and has minor computation burden compared with other registration models for mobile radar network. [ABSTRACT FROM AUTHOR]

Due to the strong nonlinearity and transition dynamics between different operating points of the high purity distillation column process, it is difficult to use a single model for modeling such a process. Therefore, the multiple model based approach is introduced for modeling the high purity distillation column plant under the framework of the expectation maximization (EM) algorithm. In this paper, autoregressive exogenous (ARX) models are adopted to construct the local models of this chemical process at different operating points, and the EM algorithm is used for identification of local models as well as the probability that each local model takes effect. The global model is obtained by aggregating the local models using an exponential weighting function. Finally, the simulation performed on the high purity distillation column demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms. [ABSTRACT FROM AUTHOR]

It has become one of the major environmental problems for people worldwide to be exposed to high arsenic concentrations through contaminated drinking water, and even the long-term intake of small doses of arsenic has a carcinogenic effect. As an efficient and economic approach for the purification of arsenic-containing water, the adsorbents in adsorption processes have been widely studied. Among a variety of adsorbents reported, the metal oxide heterostructures with high surface area and specific affinity for arsenic adsorption from aqueous systems have demonstrated a promising performance in practical applications. This review paper aims to summarize briefly the metal oxide heterostructures in arsenic removal from contaminated water, so as to provide efficient, economic, and robust solutions for water purification. [ABSTRACT FROM AUTHOR]

We use a great deal of wireless sensor nodes to detect target signal that is more accurate than the traditional single radar detection method. Each local sensor detects the target signal in the region of interests and collects relevant data, and then it sends the respective data to the data fusion center (DFC) for aggregation processing and judgment making whether the target signal exists or not. However, the current judgment fusion rules such as Counting Rule (CR) and Clustering-Counting Rule (C-CR) have the characteristics on high energy consumption and low detection precision. Consequently, this paper proposes a novel Weight-based Clustering Decision Fusion Algorithm (W-CDFA) to detect target signal in wireless sensor network. It first introduces the clustering method based on tree structure to establish the precursor-successor relationships among the clusters in the region of interests and then fuses the decision data along the direction from the precursor clusters to the successor clusters gradually, and DFC (i.e., tree root) makes final determination by overall judgment values from subclusters and ordinary nodes. Simulation experiments show that the fusion rule can obtain more satisfactory system level performance at the environment of low signal to noise compared with CR and C-CR methods. [ABSTRACT FROM AUTHOR]

The concept of "network target" has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented. [ABSTRACT FROM AUTHOR]

Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1) chemical interaction between drugs, (2) protein interactions between drugs' targets, and (3) target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations. [ABSTRACT FROM AUTHOR]

A drug side effect is an undesirable effect which occurs in addition to the intended therapeutic effect of the drug. The unexpected side effects that many patients suffer from are the major causes of large-scale drug withdrawal. To address the problem, it is highly demanded by pharmaceutical industries to develop computational methods for predicting the side effects of drugs. In this study, a novel computational method was developed to predict the side effects of drug compounds by hybridizing the chemical-chemical and protein-chemical interactions. Compared to most of the previous works, our method can rank the potential side effects for any query drug according to their predicted level of risk. A training dataset and test datasets were constructed from the benchmark dataset that contains 835 drug compounds to evaluate the method. By ajackknife test on the training dataset, the 1st order prediction accuracy was 86.30%, while it was 89.16% on the test dataset. It is expected that the new method may become a useful tool for drug design, and that the findings obtained by hybridizing various interactions in a network system may provide useful insights for conducting in-depth pharmacological research as well, particularly at the level of systems biomedicine. [ABSTRACT FROM AUTHOR]

Objective. To examine the biocompatibility of a novel nanohydroxyapatite/poly[lactic-co-glycolic acid] (nHA/PLGA) composite and evaluate its feasibility as a scaffold for cartilage tissue engineering. Methods. Chondrocytes of fetal rabbit were cultured with nHA/PLGA scaffold in vitro and the cell viability was assessed by MTT assay first. Cells adhering to nHA/PLGA scaffold were then observed by inverted microscope and scanning electron microscope (SEM). The cell cycle profile was analyzed by flow cytometry. Results. The viability of the chondrocytes on the scaffold was not affected by nHA/PLGA comparing with the control group as it was shown by MTT assay. Cells on the surface and in the pores of the scaffold increased in a time-dependent manner. Results obtained from flow cytometry showed that there was no significant difference in cell cycle profiles between the coculture group and control (P > 0.05). Conclusion. The porous nHA/PLGA composite scaffold is a biocompatible and good kind of scaffold for cartilage tissue engineering. [ABSTRACT FROM AUTHOR]

Most drugs have beneficial as well as adverse effects and exert their biological functions by adjusting and altering the functions of their target proteins. Thus, knowledge of drugs target proteins is essential for the improvement of therapeutic effects and mitigation of undesirable side effects. In the study, we proposed a novel prediction method based on drug/compound ontology information extracted from ChEBI to identify drugs target groups from which the kind of functions of a drug may be deduced. By collecting data in KEGG, a benchmark dataset consisting of 876 drugs, categorized into four target groups, was constructed. To evaluate the method more thoroughly, the benchmark dataset was divided into a training dataset and an independent test dataset. It is observed by jackknife test that the overall prediction accuracy on the training dataset was 83.12%, while it was 87.50% on the test dataset--the predictor exhibited an excellent generalization. The good performance of the method indicates that the ontology information of the drugs contains rich information about their target groups, and the study may become an inspiration to solve the problems of this sort and bridge the gap between ChEBI ontology and drugs target groups. [ABSTRACT FROM AUTHOR]

As an important constituent of wireless network planning, location area planning (LAP) directly affects the stability, security, and performance of wireless network. This work proposes a novel evolutionary algorithm(EA) to solve the LAP problem. The difference between the proposed algorithm and the previous EA is mainly how to encode. The new coding method is inspired by the famous four-color theorem in graph theory. Only four numbers are needed to encode all chromosomes by this method. The encoding and decoding process is fast and easy to implement. What is more, illegal solutions can be processed easily in the process of decoding. The design of effective and efficient genetic operators can also benefit from this coding method. The modified evolutionary algorithm with this coding method is especially effective for LAP problem. The use of the principle of fuzzy clustering in initialization can effectively compress the search space in this new algorithm. The computer simulation has been conducted, and the quality of proposed algorithm is confirmed by comparing the results of proposed algorithm with EA and simulated annealing (SA). [ABSTRACT FROM AUTHOR]

In the design of wireless sensor networks (WSNs), it is important to reduce energy consumption and extend the service life of the sensors. Selecting one of the minimum sensor combinations (MSCs) that can monitor all areas, while the other MSCs are asleep, can effectively extend the lifetime of WSNs. This paper proposes two algorithms based on Formal Concept Analysis (FCA) for extracting some MSCs, to minimize the energy consumption and meet the coverage requirement. These two methods firstly extract the concept lattice from a monitor-areas context, and then it is simple to extract sensor nodes monitoring the overlapping area from the concept lattice. The algorithms consist of three steps as follows: the first step is to transform sensors and monitoring areas into a context, the second is to extract the concept lattice and implications among areas, and the third is to extract some different MSCs that can monitor all areas. Thus, some strategies are designed to awaken different MSCs to achieve the purpose of reducing energy consumption. Experimental results show that these methods have played a positive effect on extracting different MSCs and extending the lifetime of sensor networks. [ABSTRACT FROM AUTHOR]

Airway mucus hypersecretion (AMH) is a key pathophysiological feature of chronic airway inflammatory diseases such as bronchial asthma, cystic fibrosis, and chronic obstructive pulmonary disease. AMH contributes to the pathogenesis of chronic airway inflammatory diseases, and it is associated with reduced lung function and high rates of hospitalization and mortality. It has been suggested that AMH should be a target in the treatment of chronic airway inflammatory diseases. Recent evidence suggests that a key regulator of airway inflammation, hyperresponsiveness, and remodeling is peroxisome proliferator-activated receptor gamma (PPARγ), a ligand-activated transcription factor that regulates adipocyte differentiation and lipid metabolism. PPARγ is expressed in structural, immune, and inflammatory cells in the lung. PPARγ is involved in mucin production, and PPARγ agonists can inhibit mucin synthesis both in vitro and in vivo. These findings suggest that PPARγ is a novel target in the treatment of AMH and that further work on this transcription factor may lead to new therapies for chronic airway inflammatory diseases. [ABSTRACT FROM AUTHOR]

Kinetics and mechanism of oxidation of leucine and alanine by Ag(III) complex were studied spectrophotometrically in alkaline medium at constant ion strength. The reaction was in first order with respect to Ag(III) complex and amino acids (leucine, alanine). The second-order rate constant, k-, decreased with the increasing in [OH-] and [IO4-]. A plausible mechanism was proposed from the kinetics study, and the rate equations derived from mechanism can explain all experimental phenomena. The activation parameters were calculated at 298.2 K. [ABSTRACT FROM AUTHOR]

The sorption of radiocaesium onto Na-rectorite as a function of pH value under ambient conditions was studied by batch and capillary methods. The results indicated that the sorption of Cs+ ions was dependent on the ionic strength and, to a lesser extent, on the pH value. The distribution coefficients for Cs+ ion sorption onto powdered rectorite (as determined via the batch technique) were much higher than those of Cs+ ions onto compacted rectorite (as determined by capillary test), thereby suggesting that the sorption of Cs+ ions onto rectorite was strongly dependent on the density of rectorite, i.e. the interlaminary space of the compacted rectorite contributes significantly on Cs+ ion sorption. The distribution coefficients calculated from theoretical calculations, experimental measurements and the diffusion coefficients of Cs+ ions were compared and discussed in detail. The sorption and diffusion mechanisms in compacted rectorite were also discussed. [ABSTRACT FROM AUTHOR]

Objective. To investigate the differences in the awareness, knowledge, and management of osteoporosis from a cohort of medical staff after educational intervention. Methods. A total of 653 medical workers from different departments related to the prevention and treatment of osteoporosis from 7 hospitals in Ningxia were enrolled. Information was collected using a designed questionnaire. Results. After 5 years of educational intervention and follow-up, medical staff had an increased understanding of osteoporosis diagnosis, including dual-energy X-ray, ultrasound bone sonometer, fragility fracture history, biochemistry markers, and the awareness of the susceptible population. However, there was no improvement in the cognition of single/dual photo absorptiometry, symptoms and signs, and bone turnover index. Their understanding of antiosteoporosis drugs, especially the application of calcitonin, diphosphates, and vitamin D, was significantly promoted, while the perception of indicators and time in follow-up, some adverse drug reactions, and exercise therapy remained unchanged. Medical staff were remarkably less aware of the management of follow-up for osteoporosis, exercise and diet therapy, and bone turnover markers. Conclusion. A great gap was identified in the perception of osteoporosis among medical staff in the Ningxia region. After the educational intervention, the knowledge regarding some aspects of osteoporosis generally improved. Much more effort should be made to strengthen the training and learning on the special detection methods of osteoporosis, medications and exercise therapy, and follow-up management. [ABSTRACT FROM AUTHOR]

Objective. The risk factors for the most common adverse reactions of two types of antiosteoporosis drugs in the first treatment of postmenopausal osteoporosis were analyzed to investigate the relationship between the occurrence of adverse reactions and different bone transition states and vitamin D levels. Methods. A total of 381 postmenopausal women who were diagnosed with osteoporosis in the Osteoporosis Clinic of Ningxia Medical University General Hospital from January 2017 to June 2020 were enrolled. A telephone follow-up survey was conducted on the mentioned subjects. According to the survey results, the mentioned subjects were selected according to their first use of antiosteoporosis drugs. They were divided into zoledronic acid and teriparatide acetate groups. The subjects in the two groups were divided into two groups according to the presence or absence of adverse reactions after medication and according to vitamin D level and P1NP level, and the correlation between the two factors and the occurrence of adverse reactions was analyzed. Results. Among the 307 patients treated with zoledronic acid for antiosteoporosis, 99 patients developed acute phase adverse reactions (APR+), accounting for 32.2% of the total subjects. 56.7 percent of the subjects had vitamin D deficiency. The 25(OH)D level of the APR + subjects was 16.75 ± 9.20 ng/mL, significantly lower than that of the APR− patients (23.68 ± 10.67 ng/mL). Serological P1NP level in APR+ patients was 73.95 ± 34.50 ng/ml, significantly higher than that of APR− patients with 55.80 ± 36.91 ng/ml. Musculoskeletal symptoms were observed in 14 of the 74 subjects treated with teriparatide acetate, accounting for 18.9% of the total subjects. The 25(OH)D level was deficient in 59.5% of the subjects. The 25(OH)D level of the subjects with musculoskeletal symptoms was 15.96 ± 8.17 ng/ml, while that of the subjects without musculoskeletal symptoms was 20.86 ± 8.52 ng/ml, which showed no statistical significance. The reason was considered to be related to the small sample size included in the study. The P1NP level of subjects with musculoskeletal symptoms was 96.85 ± 58.52 ng/ml, significantly higher than the P1NP level of subjects without musculoskeletal symptoms (55.28 ± 27.87 ng/ml). Conclusions. The 25(OH)D level in vivo was negatively correlated with the acute phase adverse reactions after the first infusion of zoledronic acid. When the rate of bone formation is increased and osteoblasts are active, the risk of acute phase adverse reactions is increased with the use of zoledronic acid as antiosteoporosis therapy. There was no significant correlation between 25(OH)D levels and musculoskeletal symptoms after teriparatide acetate treatment of osteoporosis. When the rate of bone formation is increased and osteoblasts are active, the risk of adverse reactions to musculoskeletal symptoms is increased with antiosteoporosis treatment with teriparatide acetate. [ABSTRACT FROM AUTHOR]

Objective. To investigate the changes of UCP1 protein in brown fat by establishing a model of gestational diabetes mellitus through intervention of high fat and carbohydrate diet. To explore the changes of UCP1 protein in brown fat in gestational diabetic mice, and analyze the characteristics of abnormal glucose metabolism in gestational diabetic mice and its relationship with changes in adipocyte morphology and insulin resistance. Methods. Eighty C57BL/6J pregnant mice were randomly divided into a normal control group and a high-fat and high-sugar feeding group. The normal control group was fed a normal diet, while the high-fat and high-sugar group was fed a high-fat and high-sugar diet to establish a gestational diabetes mellitus (GDM) model. On the pregnancy days 0, 10, and 18, the weight and fasting glucose were measured. On the pregnancy day 18, the triglycerides (TG), the total cholesterol (TC), free fatty acid (FFA), insulin levels, and insulin resistance index (HOMA-IR) were measured or calculated. At the same time, brown fat UCP1 protein of the two groups of pregnant mice were measured using Western blot Observed the Adipose tissue pathological changes by staining HE. The adipocyte was observed, and the correlation was analyzed. Results. Twenty-one pregnant mice reach the level of gestational diabetes diagnosis (FBG ≥ 5.1 mmol/L) in the high-fat and high-sugar diet group. On the pregnancy day 10 and 18, the fasting plasma glucose and the body weight significantly increased (P < 0.05). The total cholesterol, triglycerides, free fatty acid, insulin level, and insulin resistance index of the GDM group were also higher compared with that of the control group (P < 0.05). The adipocyte size significantly increased in the GDM mice. TG, TC, FFA, and body weight at 18 days of gestation were significantly correlated with HOMA-IR and single-adipocyte area in the GDM mice. HOMA-IR was significantly correlated with a single-adipocyte area. Compared with the normal control group, the UCP1 proteins of GDM mice decreased significantly and negatively correlated with body weight increase. Conclusion. Feeding C57BL/6J pregnant mice with high fat and high sugar to establish a gestational diabetes mouse model has good stability and is similar to human gestational diabetes. The reduction of brown fat UCP1 protein in GDM mice has a certain correlation with obesity tendency and obvious insulin resistance. [ABSTRACT FROM AUTHOR]

Observing what phenotype the overexpression or knockdown of gene can cause is the basic method of investigating gene functions. Many advanced biotechnologies, such as RNAi, were developed to study the gene phenotype. But there are still many limitations. Besides the time and cost, the knockdown of some gene may be lethal which makes the observation of other phenotypes impossible. Due to ethical and technological reasons, the knockdown of genes in complex species, such as mammal, is extremely difficult. Thus, we proposed a new sequence-based computational method called NNA-based method for gene phenotypes prediction. Different to the traditional sequence-based computational method, our method regards the multiphenotype as a whole network which can rank the possible phenotypes associated with the query protein and shows a more comprehensive view of the protein's biological effects. According to the prediction result of yeast, we also find some more related features, including GO and KEGG information, which are making more contributions in identifying protein phenotypes. This method can be applied in gene phenotype prediction in other species. [ABSTRACT FROM AUTHOR]

Colorectal cancer is generally categorized into the following four stages according to its development or serious degree: Dukes A, B, C, and D. Since different stage of colorectal cancer actually corresponds to different activated region of the network, the transition of different network states may reflect its pathological changes. In view of this, we compared the gene expressions among the colorectal cancer patients in the aforementioned four stages and obtained the early and late stage biomarkers, respectively. Subsequently, the two kinds of biomarkers were both mapped onto the protein interaction network. If an early biomarker and a late biomarker were close in the network and also if their expression levels were correlated in the Dukes BandC patients, then a signal propagation path from the early stage biomarker to the late one was identified. Many transition genes in the signal propagation paths were involved with the signal transduction, cell communication, and cellular process regulation. Some transition hubs were known as colorectal cancer genes. The findings reported here may provide useful insights for revealing the mechanism of colorectal cancer progression at the cellular systems biology level. [ABSTRACT FROM AUTHOR]

Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). In this work, a computational method was proposed for identifying lung-cancerrelated genes with a shortest path approach in a protein-protein interaction (PPI) network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra's algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutation P value less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results. [ABSTRACT FROM AUTHOR]

Purpose. To evaluate the relationship between the aqueous humor levels of VEGF, TNF-a, IL-10, IL-6, IL-12, MCP-1, and IP-10 with DR/DME. Methods. PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang databases were searched up to October 2018. Systematic review and meta-analysis were conducted. Results. 18 studies comprising 362 cases with DR (100 with DME) and 620 controls without DR were included in this meta-analysis. There was a significant association between VEGF levels in the aqueous humor and DR (standardized mean difference (SMD) 1.94 (95% CI 1.05-2.83)) and DME (1.07 (0.71, 1.42)). Furthermore, a significant correlation was observed between levels of IL-6 and DR (3.53 (0.37, 6.69)), and similarly correlation with DME (1.26 (0.30, 2.21)). The relationship between MCP-1 and DR and DME was significant, in which the SMD was (0.49 (0.09, 0.89)) and (1.49 (0.78, 2.20)), respectively. However, IL-12, IP-10, and TNF-a had no correlation with DR and DME, whereas there was a significant relationship between IL-8 and DME (1.68 (0.97, 2.40)). Conclusion. Elevated levels of VEGF, IL-6, and MCP-1 in the aqueous humor were associated with the risk for the presence of DR, and levels of VEGF, IL-6, IL-8, and MCP-1 were associated with the risk of DME. Furthermore, these biomarkers may be used as potential predictors or therapeutic targets for DR/DME. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) is an important treatment for male infertility, and its application to therapy is dependent on differentiation of TCM syndromes. This study aims to investigate the changes in metabolites and metabolic pathways in infertile males with Kidney-Yang Deficiency syndrome (KYDS) via metabolomics approaches. Seminal plasma samples were collected from 18 infertile males with KYDS and 18 fertile males. Liquid chromatography and mass spectrometry were used to characterize metabolomics profiles. Principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pathway analysis were used for pattern recognition and metabolite identification. PCA and PLS-DA results differentiated the two groups of patients. Forty-one discriminating metabolites (18 in positive mode and 23 in negative mode) were identified. Seven metabolites were related to five potential metabolic pathways associated with biosynthesis and metabolism of aromatic amino acids, tricarboxylic acid cycle, and sphingolipid metabolism. The changes in metabolic pathways may play an important role in the origin of KYDS-associated male infertility. Metabolomics analysis of seminal plasma may be used to differentiate TCM syndromes of infertile males, but further research must be conducted. [ABSTRACT FROM AUTHOR]

Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-relatedmacular degeneration (AMD) is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes. [ABSTRACT FROM AUTHOR]

This study attempted to find novel age-related macular degeneration (AMD) related genes based on 36 known AMD genes. The well-known shortest path algorithm, Dijkstra's algorithm, was applied to find the shortest path connecting each pair of known AMD related genes in protein-protein interaction (PPI) network. The genes occurring in any shortest path were considered as candidate AMD related genes. As a result, 125 novel AMD genes were predicted. The further analysis based on betweenness and permutation test indicates that there are 10 genes involved in the formation or development of AMD and may be the actual AMD related genes with high probability. We hope that this contribution would promote the study of age-related macular degeneration and discovery of novel effective treatments. [ABSTRACT FROM AUTHOR]

One of the most important and challenging problems in biomedicine is how to predict the cancer related genes. Retinoblastoma (RB) is the most common primary intraocular malignancy usually occurring in childhood. Early detection of RB could reduce the morbidity and promote the probability of disease-free survival. Therefore, it is of great importance to identify RB genes. In this study, we developed a computational method to predict RB related genes based on Dagging, with the maximum relevance minimum redundancy (mRMR) method followed by incremental feature selection (IFS). 119 RB genes were compiled from two previous RB related studies, while 5,500 non-RB genes were randomly selected from Ensemble genes. Ten datasets were constructed based on all these RB and non-RB genes. Each gene was encoded with a 13,126-dimensional vector including 12,887 Gene Ontology enrichment scores and 239 KEGG enrichment scores. Finally, an optimal feature set including 1061 GO terms and 8 KEGG pathways was obtained. Analysis showed that these features were closely related to RB. It is anticipated that the method can be applied to predict the other cancer related genes as well. [ABSTRACT FROM AUTHOR]

Substantial evidence implicates 𝛽-amyloid (A𝛽) peptides in the etiology of Alzheimer’s disease (AD). A𝛽 is produced by the proteolytic cleavage of the amyloid precursor protein by 𝛽- and 𝛾-secretase suggesting that 𝛾-secretase inhibition may provide therapeutic benefit for AD. Although many 𝛾-secretase inhibitors have been shown to be potent at lowering A𝛽, some have also been shown to have side effects following repeated administration. All of these side effects can be attributed to altered Notch signaling, another 𝛾-secretase substrate. Here we describe the in vivo characterization of the novel 𝛾-secretase inhibitor SCH 697466 in rodents. Although SCH 697466 was effective at lowering A𝛽, Notch-related side effects in the intestine and thymus were observed following subchronic administration at doses that provided sustained and complete lowering of A𝛽. However, additional studies revealed that both partial but sustained lowering of A𝛽 and complete but less sustained lowering of A𝛽 were successful approaches for managing Notch-related side effects. Further, changes in several Notch-related biomarkers paralleled the side effect observations. Taken together, these studies demonstrated that, by carefully varying the extent and duration of A𝛽 lowering by 𝛾-secretase inhibitors, it is possible to obtain robust and sustained lowering of A𝛽 without evidence of Notch-related side effects. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is associated with abnormal inflammation and high oxidative stress. Studies suggest that oxidized low density lipoprotein (ox-LDL) is involved in diseases associated with oxidative stress and inflammation. However, no data on the possible relationship between COPD and ox-LDL are available. This study compared serum levels of ox-LDL in 48 COPD patients and 32 health controls and correlated them with lung function, systematic inflammation, and oxidative stress. Serum levels of ox-LDL, C-reactive protein (CRP), and oxidative stress (measured by reactive oxygen species, ROS) were analyzed using commercial kits. Mean levels of serum ox-LDL were significantly higher in COPD patients than in controls (18.62 ± 7.56 versus 12.57 ± 5.90 mU/L, P < 0.05). Serum levels of CRP and ROS were also significantly higher in COPD patients. Serum levels of ox-LDL in COPD patients correlated inversely with FEV1% predicted, an index of lung function (r = -0.347, P = 0.016), while they correlated positively with CRP and ROS levels. These results suggest that serum levels of ox-LDL are increased in COPD patients and that these levels are associated with lung function, inflammation, and oxidative stress in COPD. Future studies are needed to determine whether and how ox-LDL plays a role in COPD. [ABSTRACT FROM AUTHOR]

The flavonoid myricetin is found in several sedative herbs, for example, the St. John's Wort, but its influence on sedation and its possiblemechanism of action are unknown.Using patch-clamp technique on a brain slice preparation, the present study found that myricetin promoted GABAergic activity in the neurons of hypothalamic paraventricular nucleus (PVN) by increasing the decay time and frequency of the inhibitory currentsmediated by GABAA receptor. This effect ofmyricetin was not blocked by the GABAA receptor benzodiazepine- (BZ-) binding site antagonist flumazenil, but by KN-62, a specific inhibitor of the Ca2+/calmodulinstimulated protein kinase II (Ca MK-II). Patch clamp and live Ca2+ imaging studies found that myricetin could increase Ca2+ current and intracellular Ca2+ concentration, respectively, via T- and L-type Ca2+ channels in rat PVN neurons and hypothalamic primary culture neurons. Immunofluorescence staining showed increased phosphorylation of Ca MK-II aftermyricetin incubation in primary culture of rat hypothalamic neurons, and the myricetin-induced Ca MK-II phosphorylation was further confirmed by Western blotting in PC-12 cells. The present results suggest that myricetin enhances GABAA receptor activity via calcium channel/Ca MK-II dependent mechanism, which is distinctively different from that of most existing BZ-binding site agonists of GABAA receptor. [ABSTRACT FROM AUTHOR]

Ketamine is a broadly used anaesthetic for analgosedation. Accumulating clinical evidence shows that ketamine causes pulmonary edema with unknown mechanisms. We measured the effects of ketamine on alveolar fluid clearance in human lung lobes ex vivo. Our results showed that intratracheal instillation of ketamine markedly decreased the reabsorption of 5% bovine serum albumin instillate. In the presence of amiloride (a specific ENaC blocker), fluid resolution was not further decreased, suggesting that ketamine could decrease amiloride-sensitive fraction of AFC associated with ENaC. Moreover, we measured the regulation of amiloride-sensitive currents by ketamine in A549 cells using whole-cell patch clamp mode. Our results suggested that ketamine decreased amiloride-sensitive Na+ currents (ENaC activity) in a dose-dependent fashion. These data demonstrate that reduction in lung ENaC activity and lung fluid clearance following administration of ketamine may be the crucial step of the pathogenesis of resultant pulmonary edema. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSNET) can support various types of queries. The energy resource of sensors constrains the total number of query responses, called query capacity, received by the sink. There are four problems in the existing approaches for energy-efficient query processing in WSNETs: 1. the fact that sensors near the sink drain their energy much faster than distant sensors has been overlooked, 2. routing trees (RT) are rooted at the sink, and therefore, aggregative queries are less energy-efficient, 3. data reception cost has been ignored, and 4. flooding is used in query distribution or RT construction. In this paper, we propose a Broadcasting-Based query Scheme (BBS) to address the above problems. BBS reduces the energy depletion rate of sensors near the sink, builds different localized RTs for different query types, and eliminates the flooding cost of query distribution. Compared to the existing approaches, simulation studies show that BBS produces significant improvement in the query capacity for non-holistic queries (10%-100% capacity improvement) and holistic queries (up to an order of magnitude of capacity improvement). [ABSTRACT FROM AUTHOR]