Temporal Dysynchrony in brain connectivity gene expression following hypoxia

List of K-means cluster analysis of connectivity genes across development during hypoxia. Relative log2 fold change compared to the developmental average is provided. (XLSX 197 kb

Comparing statistical methods in assessing the prognostic effect of biomarker variability on time-to-event clinical outcomes

BACKGROUND: In recent years there is increasing interest in modeling the effect of early longitudinal biomarker data on future time-to-event or other outcomes. Sometimes investigators are also interested in knowing whether the variability of biomarkers is independently predictive of clinical outcomes. This question in most applications is addressed via a two-stage approach where summary statistics such as variance are calculated in the first stage and then used in models as covariates to predict clinical outcome in the second stage. The objective of this study is to compare the relative performance of various methods in estimating the effect of biomarker variability. METHODS: A joint model and 4 different two-stage approaches (naïve, landmark analysis, time-dependent Cox model, and regression calibration) were illustrated using data from a large multi-center randomized phase III trial, the Ocular Hypertension Treatment Study (OHTS), regarding the association between the variability of intraocular pressure (IOP) and the development of primary open-angle glaucoma (POAG). The model performance was also evaluated in terms of bias using simulated data from the joint model of longitudinal IOP and time to POAG. The parameters for simulation were chosen after OHTS data, and the association between longitudinal and survival data was introduced via underlying, unobserved, and error-free parameters including subject-specific variance. RESULTS: In the OHTS data, joint modeling and two-stage methods reached consistent conclusion that IOP variability showed no significant association with the risk of POAG. In the simulated data with no association between IOP variability and time-to-POAG, all the two-stage methods (except the naïve approach) provided a reliable estimation. When a moderate effect of IOP variability on POAG was imposed, all the two-stage methods underestimated the true association as compared with the joint modeling while the model-based two-stage method (regression calibration) resulted in the least bias. CONCLUSION: Regression calibration and joint modelling are the preferred methods in assessing the effect of biomarker variability. Two-stage methods with sample-based measures should be used with caution unless there exists a relatively long series of longitudinal measurements and/or strong effect size (NCT00000125)

Structural and Functional Characterization of the FadR Regulatory Protein from Vibrio alginolyticus

The structure of Vibrio cholerae FadR (VcFadR) complexed with the ligand oleoyl-CoA suggests an additional ligand-binding site. However, the fatty acid metabolism and its regulation is poorly addressed in Vibrio alginolyticus, a species closely-related to V. cholerae. Here, we show crystal structures of V. alginolyticus FadR (ValFadR) alone and its complex with the palmitoyl-CoA, a long-chain fatty acyl ligand different from the oleoyl-CoA occupied by VcFadR. Structural comparison indicates that both VcFadR and ValFadR consistently have an additional ligand-binding site (called site 2), which leads to more dramatic conformational-change of DNA-binding domain than that of the E. coli FadR (EcFadR). Isothermal titration calorimetry (ITC) analyses defines that the ligand-binding pattern of ValFadR (2:1) is distinct from that of EcFadR (1:1). Together with surface plasmon resonance (SPR), electrophoresis mobility shift assay (EMSA) demonstrates that ValFadR binds fabA, an important gene of unsaturated fatty acid (UFA) synthesis. The removal of fadR from V. cholerae attenuates fabA transcription and results in the unbalance of UFA/SFA incorporated into membrane phospholipids. Genetic complementation of the mutant version of fadR (Δ42, 136-177) lacking site 2 cannot restore the defective phenotypes of ΔfadR while the wild-type fadR gene and addition of exogenous oleate can restore them. Mice experiments reveals that VcFadR and its site 2 have roles in bacterial colonizing. Together, the results might represent an additional example that illustrates the Vibrio FadR-mediated lipid regulation and its role in pathogenesis

Dcc Regulates Asymmetric Outgrowth of Forebrain Neurons in Zebrafish

The guidance receptor DCC (deleted in colorectal cancer) ortholog UNC-40 regulates neuronal asymmetry development in Caenorhabditis elegans, but it is not known whether DCC plays a role in the specification of neuronal polarity in vertebrates. To examine the roles of DCC in neuronal asymmetry regulation in vertebrates, we studied zebrafish anterior dorsal telencephalon (ADt) neuronal axons. We generated transgenic zebrafish animals expressing the photo-convertible fluorescent protein Kaede in ADt neurons and then photo-converted Kaede to label specifically the ADt neuron axons. We found that ADt axons normally project ventrally. Knock down of Dcc function by injecting antisense morpholino oligonucleotides caused the ADt neurons to project axons dorsally. To examine the axon projection pattern of individual ADt neurons, we labeled single ADt neurons using a forebrain-specific promoter to drive fluorescent protein expression. We found that individual ADt neurons projected axons dorsally or formed multiple processes after morpholino knock down of Dcc function. We further found that knock down of the Dcc ligand, Netrin1, also caused ADt neurons to project axons dorsally. Knockdown of Neogenin1, a guidance receptor closely related to Dcc, enhanced the formation of aberrant dorsal axons in embryos injected with Dcc morpholino. These experiments provide the first evidence that Dcc regulates polarized axon initiation and asymmetric outgrowth of forebrain neurons in vertebrates

DNA-Immobilized Special Conformation Recognition of L-Penicillamine Using a Chiral Molecular Imprinting Technique

A new chiral molecularly imprinted polymer (MIP) sensor with dual recognition ability was developed for the highly selective separation of enantiomers with toxic side effects in drugs. The sensor contains double-stranded deoxyribonucleic acid (dsDNA) as the element that immobilizes the chiral molecular conformation: the dsDNA enables the imprinted cavities to match the three-dimensional structure and functional groups from the chiral molecule. By embedding the spatial orientation of dsDNA in MIPs, one can accurately capture and immobilize the molecular conformation, eliminating the influence of interfering analogues. Herein, L-penicillamine (L-Pen) was selected as the chiral template molecule and embedded into dsDNA to form dsDNA-L-Pen complex, which was then embedded into the MIPs by electropolymerization. After elution, the stereo-selective imprinted cavities were obtained. The ATATATATATAT-TATATATATATA base sequence showed a high affinity for the embedded L-Pen, which endowed the imprinted cavities with a larger number of sites and improved the selectivity toward Pen enantiomers. Under the optimal working conditions, the current response of the MIP/dsDNA sensor exhibited a positive linear relationship with the logarithm of the L-Pen concentration in the range of 3.0 × 10−16 to 3.0 × 10−13 mol/L, and the detection limit was 2.48 × 10−16 mol/L. After the introduction of dsDNA into the MIP, the selectivity of the sensor toward D-Pen increased by 6.4 times, and the sensor was successfully applied in the analysis of L-Pen in penicillamine tablets

Effect of composition on microstructure and mechanical properties of TA15 titanium alloy

To analyze the relationship between composition, microstructure and mechanical properties of TA15 titanium alloys, the quasi-static tensile properties and dynamic properties at room temperature of four kinds of TA15 titanium alloys were studied by the electronic universal tensile testing machine and split hopkinson pressure bar (SHPB). The results reveal that the Zr content has little effect on the tensile strength at room temperature, moreover, with the increase of content of main alloy elements Al, V and Mo, the content of primary α phase decreases and the lamella width of secondary α phase is thinner which provide higher strength and lower plasticity. Slight changes in alloy composition have little effect on dynamic mechanical properties within the critical strain rate range. Increasing the content of main alloy elements Al, Zr, V and Mo is beneficial to improve the critical strain rate, at which the alloy has excellent dynamic mechanical properties. For equiaxed TA15 titanium alloys obtained under air cooling condition, the smaller volume fraction of primary α phase and thinner lamella of secondary α phase can improve the tensile strength, critical strain rate and dynamic mechanical properties at room temperature

Proteomic analysis of differential anther development from sterile/fertile lines in Capsicum annuum L.

Background Pepper (Capsicum annuum L.) is a major cash crop throughout the world. Male sterility is an important characteristic in crop species that leads to a failure to produce functional pollen, and it has crucial roles in agricultural breeding and the utilization of heterosis. Objectives In this study, we identified many crucial factors and important components in metabolic pathways in anther and pollen development, and elucidated the molecular mechanism related to pollen abortion in pepper. Methods Pepper pollen was observed at different stages to detect the characteristics associated with male sterility and fertility. The phytohormone and oxidoreductase activities were detected in spectrophotometric and redox reaction assays, respectively. Proteins were extracted from male sterile and fertile pepper lines, and identified by TMT/iTRAQ (tandem mass tags/isobaric tags for relative and absolute quantitation) and LC-MS/MS (liquid chromatograph-mass spectrometer) analysis. Differentially abundant proteins (DAPs) were analyzed based on Gene Ontology annotations and the Kyoto Encyclopedia of Genes and Genomes database according to |fold change)| > 1.3 and P value < 0.05. DAPs were quantified in the meiosis, tetrad, and binucleate stages by parallel reaction monitoring (PRM). Results In this study, we screened and identified one male sterile pepper line with abnormal cytological characteristics in terms of pollen development. The peroxidase and catalase enzyme activities were significantly reduced and increased, respectively, in the male sterile line compared with the male fertile line. Phytohormone analysis demonstrated that the gibberellin, jasmonic acid, and auxin contents changed by different extents in the male sterile pepper line. Proteome analysis screened 1,645 DAPs in six clusters, which were mainly associated with the chloroplast and cytoplasm based on their similar expression levels. According to proteome analysis, 45 DAPs were quantitatively identified in the meiosis, tetrad, and binucleate stages by PRM, which were related to monoterpenoid biosynthesis, and starch and sucrose metabolism pathways. Conclusions We screened 1,645 DAPs by proteomic analysis and 45 DAPs were related to anther and pollen development in a male sterile pepper line. In addition, the activities of peroxidase and catalase as well as the abundances of phytohormones such as gibberellin, jasmonic acid, and auxin were related to male sterility. The results obtained in this study provide insights into the molecular mechanism responsible for male sterility and fertility in pepper

Comparing statistical methods in assessing the prognostic effect of biomarker variability on time-to-event clinical outcomes

Abstract Background In recent years there is increasing interest in modeling the effect of early longitudinal biomarker data on future time-to-event or other outcomes. Sometimes investigators are also interested in knowing whether the variability of biomarkers is independently predictive of clinical outcomes. This question in most applications is addressed via a two-stage approach where summary statistics such as variance are calculated in the first stage and then used in models as covariates to predict clinical outcome in the second stage. The objective of this study is to compare the relative performance of various methods in estimating the effect of biomarker variability. Methods A joint model and 4 different two-stage approaches (naïve, landmark analysis, time-dependent Cox model, and regression calibration) were illustrated using data from a large multi-center randomized phase III trial, the Ocular Hypertension Treatment Study (OHTS), regarding the association between the variability of intraocular pressure (IOP) and the development of primary open-angle glaucoma (POAG). The model performance was also evaluated in terms of bias using simulated data from the joint model of longitudinal IOP and time to POAG. The parameters for simulation were chosen after OHTS data, and the association between longitudinal and survival data was introduced via underlying, unobserved, and error-free parameters including subject-specific variance. Results In the OHTS data, joint modeling and two-stage methods reached consistent conclusion that IOP variability showed no significant association with the risk of POAG. In the simulated data with no association between IOP variability and time-to-POAG, all the two-stage methods (except the naïve approach) provided a reliable estimation. When a moderate effect of IOP variability on POAG was imposed, all the two-stage methods underestimated the true association as compared with the joint modeling while the model-based two-stage method (regression calibration) resulted in the least bias. Conclusion Regression calibration and joint modelling are the preferred methods in assessing the effect of biomarker variability. Two-stage methods with sample-based measures should be used with caution unless there exists a relatively long series of longitudinal measurements and/or strong effect size (NCT00000125)

A Decision-Support Model for the Generation of Marine Green Tide Disaster Emergency Disposal Plans

Green tide is a harmful marine ecological phenomenon caused by the explosive proliferation or high aggregation of some macroalgae, and can cause significant impacts on ecological environments and economies. An effective emergency disposal plan can significantly improve disposal capacity and reduce total costs. At present, the formulation of emergency disposal plans for green tide disasters usually depends on subjective experience. The primary purpose of this paper is to develop a decision-support model based on intelligent algorithms to optimize the type and number of resources when making emergency disposal plans so as to improve the reliability and efficiency of decision making. In order to simulate the decision-making environment more realistically, the drift motion of green tide is considered in this model. Two intelligent algorithms, the Genetic Algorithm (GA) and the improved Non-Dominated Sorting Genetic Algorithm-II (IMNSGA-II), are used to solve the model and find appropriate emergency disposal plans. Finally, a case study on the green tide disaster that occurred in Qingdao (Yellow Sea, China) is conducted to demonstrate the effectiveness and optimization of the proposed model. Through the model proposed in this paper, the overall response time and cost can be reduced in green tide disaster emergency operations