ALBERT

Description: Background: Recently, several studies have drawn attention to the determination of a minimum set of driver proteins that are important for the control of the underlying protein-protein interaction (PPI) networks. In general, the minimum dominating set (MDS) model is widely adopted. However, because the MDS model does not generate a unique MDS configuration, multiple different MDSs would be generated when using different optimization algorithms. Therefore, among these MDSs, it is difficult to find out the one that represents the true driver set of proteins. Results: To address this problem, we develop a centrality-corrected minimum dominating set (CC-MDS) model which includes heterogeneity in degree and betweenness centralities of proteins. Both the MDS model and the CC-MDS model are applied on three human PPI networks. Unlike the MDS model, the CC-MDS model generates almost the same sets of driver proteins when we implement it using different optimization algorithms. The CC-MDS model targets more high-degree and high-betweenness proteins than the uncorrected counterpart. The more central position allows CC-MDS proteins to be more important in maintaining the overall network connectivity than MDS proteins. To indicate the functional significance, we find that CC-MDS proteins are involved in, on average, more protein complexes and GO annotations than MDS proteins. We also find that more essential genes, aging genes, disease-associated genes and virus-targeted genes appear in CC-MDS proteins than in MDS proteins. As for the involvement in regulatory functions, the sets of CC-MDS proteins show much stronger enrichment of transcription factors and protein kinases. The results about topological and functional significance demonstrate that the CC-MDS model can capture more driver proteins than the MDS model. Conclusions: Based on the results obtained, the CC-MDS model presents to be a powerful tool for the determination of driver proteins that can control the underlying PPI networks. The software described in this paper and the datasets used are available at https://github.com/Zhangxf-ccnu/CC-MDS.

Description: In this paper, the noninvasive and real-time plasmon waveguide resonance (PWR) thermometry is reported theoretically and demonstrated experimentally. Owing to the enhanced evanescent field and thermal shield effect of its dielectric layer, a PWR thermometer permits accurate temperature sensing and has a wide dynamic range. A temperature measurement sensitivity of 9.4 × 10−3 °C is achieved and the thermo optic coefficient nonlinearity is measured in the experiment. The measurement of water cooling processes distributed in one dimension reveals that a PWR thermometer allows real-time temperature sensing and has potential to be applied for thermal gradient analysis. Apart from this, the PWR thermometer has the advantages of low cost and simple structure, since our transduction scheme can be constructed with conventional optical components and commercial coating techniques.

Description: Nesprin-1-giant (1008kD) is a protein of the outer nuclear membrane that links nuclei to the actin cytoskeleton via amino-terminal calponin homology domains. The short nesprin-1 isoform, nesprin-1-α2, is prese...

Description: Background: Plants have evolved a complicated resistance system and exhibit a variety of defense patterns in response to different attackers. Previous studies have shown that responses of plants to chewing insects and phloem-feeding insects are significantly different. Less is known, however, regarding molecular responses to leafminer insects. To investigate plant transcriptome response to leafminers, we selected the leafminer Liriomyza huidobrensis, which has a special feeding pattern more similar to pathogen damage than that of chewing insects, as a model insect, and Arabidopsis thaliana as a response plant. Results: We first investigated local and systemic responses of A. thaliana to leafminer feeding using an Affymetrix ATH1 genome array. Genes related to metabolic processes and stimulus responses were highly regulated. Most systemically-induced genes formed a subset of the local response genes. We then downloaded gene expression data from online databases and used hierarchical clustering to explore relationships among gene expression patterns in A. thaliana damaged by different attackers. Conclusions: Our results demonstrate that plant response patterns are strongly coupled to damage patterns of attackers.

Description: Background: The identification of protein-protein interactions contributes greatly to the understanding of functional organization within cells. With the development of affinity purification-mass spectrometry (AP-MS) techniques, several computational scoring methods have been proposed to detect protein interactions from AP-MS data. However, most of the current methods focus on the detection of co-complex interactions and do not discriminate between direct physical interactions and indirect interactions. Consequently, less is known about the precise physical wiring diagram within cells. Results: In this paper, we develop a Binary Interaction Network Model (BINM) to computationally identify direct physical interactions from co-complex interactions which can be inferred from purification data using previous scoring methods. This model provides a mathematical framework for capturing topological relationships between direct physical interactions and observed co-complex interactions. It reassigns a confidence score to each observed interaction to indicate its propensity to be a direct physical interaction. Then observed interactions with high confidence scores are predicted as direct physical interactions. We run our model on two yeast co-complex interaction networks which are constructed by two different scoring methods on a same combined AP-MS data. The direct physical interactions identified by various methods are comprehensively benchmarked against different reference sets that provide both direct and indirect evidence for physical contacts. Experiment results show that our model has a competitive performance over the state-of-the-art methods. Conclusions: According to the results obtained in this study, BINM is a powerful scoring method that can solely use network topology to predict direct physical interactions from AP-MS data. This study provides us an alternative approach to explore the information inherent in AP-MS data. The software can be downloaded from https://github.com/Zhangxf-ccnu/BINM.

Description: Sensors, Vol. 18, Pages 976: Ultra-Long-Distance Hybrid BOTDA/Ф-OTDR Sensors doi: 10.3390/s18040976 Authors: Yun Fu Zinan Wang Richeng Zhu Naitian Xue Jialin Jiang Chongyu Lu Bin Zhang Le Yang David Atubga Yunjiang Rao In the distributed optical fiber sensing (DOFS) domain, simultaneous measurement of vibration and temperature/strain based on Rayleigh scattering and Brillouin scattering in fiber could have wide applications. However, there are certain challenges for the case of ultra-long sensing range, including the interplay of different scattering mechanisms, the interaction of two types of sensing signals, and the competition of pump power. In this paper, a hybrid DOFS system, which can simultaneously measure temperature/strain and vibration over 150 km, is elaborately designed via integrating the Brillouin optical time-domain analyzer (BOTDA) and phase-sensitive optical time-domain reflectometry (Ф-OTDR). Distributed Raman and Brillouin amplifications, frequency division multiplexing (FDM), wavelength division multiplexing (WDM), and time division multiplexing (TDM) are delicately fused to accommodate ultra-long-distance BOTDA and Ф-OTDR. Consequently, the sensing range of the hybrid system is 150.62 km, and the spatial resolution of BOTDA and Ф-OTDR are 9 m and 30 m, respectively. The measurement uncertainty of the BOTDA is ± 0.82 MHz. To the best of our knowledge, this is the first time that such hybrid DOFS is realized with a hundred-kilometer length scale.

Description: Complete mitochondrial (mt) genomes have been used extensively to test hypotheses about microevolution and to study population structure, phylogeography, and phylogenetic relationships of Anura at various taxo...

Description: Sensors, Vol. 17, Pages 2761: A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers Sensors doi: 10.3390/s17122761 Authors: Guanwen Huang Zhiwei Qin Qin Zhang Le Wang Xingyuan Yan Lihong Fan Xiaolei Wang The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services.

Description: Several recent studies have used the Minimum Dominating Set (MDS) model to identify driver nodes, which provide the control of the underlying networks, in protein interaction networks. There may exist multiple...

Description: Background and Purpose: Fatigue is one of the most common symptoms reported in several studies; but few studies have concentrated on the male population, especially for the middle-aged and older men who are exposed to greater fatigue risk. The purpose of this study was to explore the prevalence of fatigue and identify the risk factors of fatigue among men aged 45 and older in China. Methods: This study was part of a cross-sectional study on community health in Shunde (Guangdong Province, China). A total sample of 1158 men aged 45 and older were included. Sociodemographic characteristics, health and lifestyle factors and the Chalder Fatigue Scale (CFS) were measured by structured questionnaires through face-to-face interviews. Multivariate logistic regression was applied to determine the risk factors of fatigue. Results: Approximately 30% of participants experienced fatigue. Older age (≥75 years: adjusted OR 3.88, 95% CI 2.09–7.18), single marital status (1.94, 1.04–3.62), unemployed status (1.68, 1.16–2.43), number of self-reported chronic diseases (≥2 chronic diseases: 2.83, 1.86–4.31), number of individuals’ children (≥4 children: 2.35, 1.33–4.15), hospitalization in the last year (1.61, 1.03–2.52) were all significantly associated with increased risk of fatigue, while regular exercise (0.46, 0.32–0.65) was a protective factor against fatigue. Conclusions: Fatigue was usual in males and several factors were associated with the fatigue. These findings may have implication in risk assessment of fatigue and help in developing and implementing targeted interventions in middle-aged and elderly males.