cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.825701
title: Enhanced screening efficiency for endocrine-disrupting chemicals in milk and powdered milk using UPLC/QTOF-MS by the introduction of dansyl chloride derivatisation

description: This study developed and validated a sensitive analytical method for simultaneous screening of four classes of endocrine-disrupting chemicals (i.e. progestogens, androgens, oestrogens and phenols) in milk and powdered milk using ultra-performance liquid chromatography (UPLC) coupled with electrospray ionisation quadrupole time-of-flight mass spectrometry (QTOF-MS). Dansylation of oestrogens and phenols enhanced the ionisation efficiency and shifted the ionisation mode from negative to positive, which allowed for the simultaneous analysis of four EDCs in one chromatographic run. An efficient sample pre-treatment minimised the matrix effects. The mass errors for the precursor and product ions for 26 target compounds varied between −2.8 and 2.3 mDa; and the limits of detection (signal-to-noise ratio = 3) for milk and powdered milk were less than 0.04 µg l<sup>−1</sup> and 0.10 µg kg<sup>−1</sup>, respectively. The proposed method was successfully used to analyse multiple types of real samples, including normal temperature whole milk, infant formula and whole powdered milk. In 11 samples, two target compounds, progesterone and androstenedione, were detected. The progesterone concentrations ranged from 8.1 to 12.7 µg l<sup>−1</sup> in milk, and from 1.2 to 32.0 µg kg<sup>−1</sup> in infant formulas and whole powdered milks. The androstenedione concentrations varied from 0.39 to 0.79 µg l<sup>−1</sup> in milks, and from 0.29 to 1.2 µg kg<sup>−1</sup> in infant formulas and whole powdered milks. Two post-target compounds, one isomer of oestriol and 5α-dihydroprogesterone, were tentatively identified by post-target analysis in two of 11 real samples.
DOI: 10.6084/m9.figshare.825701.v1
title: Enhanced screening efficiency for endocrine-disrupting chemicals in milk and powdered milk using UPLC/QTOF-MS by the introduction of dansyl chloride derivatisation

description: This study developed and validated a sensitive analytical method for simultaneous screening of four classes of endocrine-disrupting chemicals (i.e. progestogens, androgens, oestrogens and phenols) in milk and powdered milk using ultra-performance liquid chromatography (UPLC) coupled with electrospray ionisation quadrupole time-of-flight mass spectrometry (QTOF-MS). Dansylation of oestrogens and phenols enhanced the ionisation efficiency and shifted the ionisation mode from negative to positive, which allowed for the simultaneous analysis of four EDCs in one chromatographic run. An efficient sample pre-treatment minimised the matrix effects. The mass errors for the precursor and product ions for 26 target compounds varied between −2.8 and 2.3 mDa; and the limits of detection (signal-to-noise ratio = 3) for milk and powdered milk were less than 0.04 µg l<sup>−1</sup> and 0.10 µg kg<sup>−1</sup>, respectively. The proposed method was successfully used to analyse multiple types of real samples, including normal temperature whole milk, infant formula and whole powdered milk. In 11 samples, two target compounds, progesterone and androstenedione, were detected. The progesterone concentrations ranged from 8.1 to 12.7 µg l<sup>−1</sup> in milk, and from 1.2 to 32.0 µg kg<sup>−1</sup> in infant formulas and whole powdered milks. The androstenedione concentrations varied from 0.39 to 0.79 µg l<sup>−1</sup> in milks, and from 0.29 to 1.2 µg kg<sup>−1</sup> in infant formulas and whole powdered milks. Two post-target compounds, one isomer of oestriol and 5α-dihydroprogesterone, were tentatively identified by post-target analysis in two of 11 real samples.
DOI: 10.6084/m9.figshare.867687
title: Machine learning classification of cell-specific cardiac enhancers uncovers developmental subnetworks regulating progenitor cell division and cell fate specification, Supplemental Table S2

description: Supplemental Table S2 for the manuscript "Machine learning classification of cell-specific cardiac enhancers uncovers developmental subnetworks regulating progenitor cell division and cell fate specification" by 
Shaad M. Ahmad, Brian W. Busser, Di Huang, Elizabeth J. Cozart,
Sébastien Michaud, Xianmin Zhu, Neal Jeffries, Anton Aboukhalil, Martha L.
Bulyk, Ivan Ovcharenko and Alan M. Michelson
 
article in press, DOI: 10.1242/dev.101709
DOI: 10.6084/m9.figshare.897966
title: Molecular Dynamics Simulations of Dynamic Combinatorial Catenanes

description: Raw results of the molecular dynamics simulations performed for the paper:
<em>Catenanes from Catenanes: Quantitative Assessment of Cooperativity in Dynamic Combinatorial Catenation,</em> J. Li, P. Nowak, H. Fanlo-Virgos and S. Otto, <em>Chemical Science,</em> <strong>2014</strong>, DOI: 10.1039/C4SC01998A
This fileset contains results of MD simulations on the self-assembled tetrameric azobenzene macrocycle (4AB), beta-cyclodextrin (BCD), gamma-cyclodextrin (GCD) and [2]- and [3]catenanes formed by them. In case of [3]catenanes there are two possible orientations of the cyclodextrins - parallel and antiparallel. They are denoted by "p" and "ap" suffixes. Example: filenames containing "4AB-2BCDap" correspond to the [3]catenane composed of a single tetrameric azobenzene macrocycle and two beta-cyclodextrins oriented in an antiparallel fashion.
Files with the "-structure_" prefix are snaphots from MD simulations at the time indicated in the filename.
Files with the ".traj" extension are 40 ns trajectory files (without water box) which can be loaded into a trajectory visualisation program (e.g. VMD, http://www.ks.uiuc.edu/Research/vmd/). The corresponding topology/parameter files have the ".prmtop" extension.
Files with the "distCD_" prefix contain the distance between the center of a cyclodextrin (CD1 and CD2 for the first and the second, respectively) and the 4AB macrocycle in the function of time.
Files with the "distSS_" prefix contain the distance between the centers of the opposite disulfide bonds in the 4AB macrocycle in the function of time.
Files with the "sasa_" prefix contain the solvent accessible surface areas in the function of time. The surface was partitioned between different molecules (4AB, CD1, and CD2 suffixes) and with respect to the hydrophobicity/hydrophilicity (denoted by the suffix). Files with the "hbond_" prefix contain the number of hydrogen bonds between the 4AB macrocycle and cyclodextrins in the function of time.
File "AB2.mol2" is the azobenzene fragment used to construct the 4AB macrocycle with the leap program. It was generated using restrained electrostatic fit (RESP) with RED.III.5 program.
DOI: 10.6084/m9.figshare.897966.v1
title: Molecular Dynamics Simulations of Dynamic Combinatorial Catenanes

description: Raw results of the molecular dynamics simulations performed for the paper:
<em>Catenanes from Catenanes: Quantitative Assessment of Cooperativity in Dynamic Combinatorial Catenation,</em> J. Li, P. Nowak, H. Fanlo-Virgos and S. Otto, <em>Chemical Science,</em> <strong>2014</strong>, DOI: 10.1039/C4SC01998A
This fileset contains results of MD simulations on the self-assembled tetrameric azobenzene macrocycle (4AB), beta-cyclodextrin (BCD), gamma-cyclodextrin (GCD) and [2]- and [3]catenanes formed by them. In case of [3]catenanes there are two possible orientations of the cyclodextrins - parallel and antiparallel. They are denoted by "p" and "ap" suffixes. Example: filenames containing "4AB-2BCDap" correspond to the [3]catenane composed of a single tetrameric azobenzene macrocycle and two beta-cyclodextrins oriented in an antiparallel fashion.
Files with the "-structure_" prefix are snaphots from MD simulations at the time indicated in the filename.
Files with the ".traj" extension are 40 ns trajectory files (without water box) which can be loaded into a trajectory visualisation program (e.g. VMD, http://www.ks.uiuc.edu/Research/vmd/). The corresponding topology/parameter files have the ".prmtop" extension.
Files with the "distCD_" prefix contain the distance between the center of a cyclodextrin (CD1 and CD2 for the first and the second, respectively) and the 4AB macrocycle in the function of time.
Files with the "distSS_" prefix contain the distance between the centers of the opposite disulfide bonds in the 4AB macrocycle in the function of time.
Files with the "sasa_" prefix contain the solvent accessible surface areas in the function of time. The surface was partitioned between different molecules (4AB, CD1, and CD2 suffixes) and with respect to the hydrophobicity/hydrophilicity (denoted by the suffix). Files with the "hbond_" prefix contain the number of hydrogen bonds between the 4AB macrocycle and cyclodextrins in the function of time.
File "AB2.mol2" is the azobenzene fragment used to construct the 4AB macrocycle with the leap program. It was generated using restrained electrostatic fit (RESP) with RED.III.5 program.
DOI: 10.6084/m9.figshare.954933
title: Raw data from behavior tests and dynein protein levels

description: Dataset 1 Raw data of modified open field test.
Two indexes, the time to get down from the platform and the number of grids crossed, are indicated.
Dataset 2 Original western blot images of dynein.
Western blot images of dynein in the midbrain and striatum are shown. In the top panel, the left 3 lanes are from the nTg group and the right 3 lanes are from the A53T group. In the middle panel, the left 2 lanes are from the nTg group and the right 2 lanes are from the A53T group. In the bottom panel, the left 3 lanes are from the nTg group and the right 3 lanes are from the A53T group.
Dataset 3 Quantitation spreadsheet of dynein western blot data.
The ratio of dynein to β-actin was calculated and normalized by the averaged value of nTg group.
Dataset 4 Quantitation spreadsheet of dynein immunohistochemistry data.
The optical density of dynein-ir in the substantia nigra and striatum was quantified and normalized by the averaged value of nTg group.
DOI: 10.6084/m9.figshare.960574
title: Covariance-Guided Mixture Probabilistic Principal Component Analysis (C-MPPCA)

description: To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional visualization is often insufficient for capturing all or most interesting structures in complex high-dimensional datasets. For this reason, Tipping and Bishop developed mixture probabilistic principal component analysis (MPPCA) that separates data into multiple groups and enables a unique projection per group; that is, one probabilistic principal component analysis (PPCA) data visualization per group. Because the group labels are assigned to observations based on their high-dimensional coordinates, MPPCA works well to reveal homoscedastic structures in data that differ spatially. In the presence of heteroscedasticity, however, MPPCA may still mask noteworthy data structures. We propose a new method called covariance-guided MPPCA (C-MPPCA) that groups subsets of observations based on covariance, not locality, and, similar to MPPCA, displays them using PPCA. PPCA projects data in the dimensions with the highest variances, thus grouping by covariance makes sense and enables some data structures to be visible that were masked originally by MPPCA. We demonstrate the performance of C-MPPCA in an extensive simulation study. We also apply C-MPPCA to a real world dataset. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.960574.v1
title: Covariance-Guided Mixture Probabilistic Principal Component Analysis (C-MPPCA)

description: To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional visualization is often insufficient for capturing all or most interesting structures in complex high-dimensional data sets. For this reason, Tipping and Bishop [1999a] developed Mixture Probabilistic Principal Component Analysis (MPPCA) that separates data into multiple groups and enables a unique projection per group; i.e., one Probabilistic Principal Component Analysis (PPCA) data visualization per group. Because the groups labels are assigned to observations based on their high-dimensional coordinates, MPPCA works well to reveal homoskedastic structures in data that differ spatially. In the presence of heteroskedasticity, however, MPPCA may still mask noteworthy data structures. We propose a new method called Covariance-guided MPPCA (C-MPPCA) that groups subsets of observations based on covariance, not locality, and, similar to MPPCA, displays them using PPCA. PPCA projects data in the dimensions with the highest variances, thus grouping by covariance makes sense and enables some data structures to be visible that were masked originally by MPPCA. We demonstrate the performance of C-MPPCA in an extensive simulation study. We also apply C-MPPCA to a real world dataset.
DOI: 10.6084/m9.figshare.960574.v2
title: Covariance-Guided Mixture Probabilistic Principal Component Analysis (C-MPPCA)

description: To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional visualization is often insufficient for capturing all or most interesting structures in complex high-dimensional datasets. For this reason, Tipping and Bishop developed mixture probabilistic principal component analysis (MPPCA) that separates data into multiple groups and enables a unique projection per group; that is, one probabilistic principal component analysis (PPCA) data visualization per group. Because the group labels are assigned to observations based on their high-dimensional coordinates, MPPCA works well to reveal homoscedastic structures in data that differ spatially. In the presence of heteroscedasticity, however, MPPCA may still mask noteworthy data structures. We propose a new method called covariance-guided MPPCA (C-MPPCA) that groups subsets of observations based on covariance, not locality, and, similar to MPPCA, displays them using PPCA. PPCA projects data in the dimensions with the highest variances, thus grouping by covariance makes sense and enables some data structures to be visible that were masked originally by MPPCA. We demonstrate the performance of C-MPPCA in an extensive simulation study. We also apply C-MPPCA to a real world dataset. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.960574.v3
title: Covariance-Guided Mixture Probabilistic Principal Component Analysis (C-MPPCA)

description: To extract information from high-dimensional data efficiently, visualization tools based on data projection methods have been developed and shown useful. However, a single two-dimensional visualization is often insufficient for capturing all or most interesting structures in complex high-dimensional datasets. For this reason, Tipping and Bishop developed mixture probabilistic principal component analysis (MPPCA) that separates data into multiple groups and enables a unique projection per group; that is, one probabilistic principal component analysis (PPCA) data visualization per group. Because the group labels are assigned to observations based on their high-dimensional coordinates, MPPCA works well to reveal homoscedastic structures in data that differ spatially. In the presence of heteroscedasticity, however, MPPCA may still mask noteworthy data structures. We propose a new method called covariance-guided MPPCA (C-MPPCA) that groups subsets of observations based on covariance, not locality, and, similar to MPPCA, displays them using PPCA. PPCA projects data in the dimensions with the highest variances, thus grouping by covariance makes sense and enables some data structures to be visible that were masked originally by MPPCA. We demonstrate the performance of C-MPPCA in an extensive simulation study. We also apply C-MPPCA to a real world dataset. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.962945
title: Neurosurgical approach to the cerebral cortex for acute and chronic cortical simulation and recording studies in minipigs and sheep

description: Comparison of the neuroanatomy of the minipig, the pig and the sheep with respect to a neurosurgical approach to the cerebral cortex.
DOI: 10.6084/m9.figshare.962945.v1
title: Neurosurgical approach to the cerebral cortex for acute and chronic cortical simulation and recording studies in minipigs and sheep

description: Comparison of the neuroanatomy of the minipig, the pig and the sheep with respect to a neurosurgical approach to the cerebral cortex.
DOI: 10.6084/m9.figshare.963134.v1
title: Investigating Motorists’ Behaviors in Response to Supplementary Traffic Control Devices at Land Surveying Work Sites

description: <b>Objective:</b> Since land surveyors working alongside live traffic encounter unique safety challenges there is a great need for innovative and effective traffic control devices (TCDs) that alert motorists approaching short-term land surveying work sites. Unlike the volume of research that has been completed on traditional work zones, however, there is a limited amount of information that has been collected on how motorists respond to TCDs at land surveying work sites. This article aims to fill the void by investigating motorists’ behaviors in response to the use of 2 supplementary TCDs at land surveying work sites: portable plastic rumble strips (PPRS) and warning lights.
 
 <b>Method:</b> Extensive field tests were conducted at various land surveying work sites on 2-lane 2-way urban roadways in New Jersey. Scenarios with and without the use of the supplemental TCDs were designed. Motorists’ behavior changes were then statistically examined by using surrogate safety measures including mean speed, speed variance, speed limit compliance, and braking action.
 
 <b>Results:</b> Statistical analyses showed that the traffic speed variations did not significantly increase when the selected supplemental TCD was used; rather, motorists significantly reduced their driving speed. When warning lights and PPRS were separately deployed at the land surveying work sites the average reduction in mean speed was 6.7 and 15.2 percent, respectively. The mean speed was reduced by 19.7 percent when both of these supplementary TCDs were used. Logistic regression models developed to examine the speeding and braking behavior also showed that motorists were more likely to comply with the speed limit and increase their braking rate when the selected TCDs were used.
 
 <b>Conclusion:</b> The use of supplemental TCDs can greatly contribute to the changes in motorists’ behaviors at surveying work sites. The changes in motorists’ driving behaviors imply that the motorists reacted favorably to the deployed TCDs at the land-surveying work sites.
DOI: 10.6084/m9.figshare.963333
title: VARIATION OF SULFORAPHANE LEVELS IN BROCCOLI (<i>BRASSICA OLERACEA</i> VAR. <i>ITALICA</i>) DURING FLOWER DEVELOPMENT AND THE ROLE OF GENE <i>AOP2</i>

description: Sulforaphane is abundant in broccoli (<i>Brassica oleracea</i> var. <i>italica</i>) and has been widely studied since it may reduce the risk of several types of cancer. Here, the variation of sulforaphane levels during different stages of broccoli flower bud development was studied by high-performance liquid chromatography (HPLC). At the same time, the expressions of gene <i>AOP2</i> in all the materials were studied by real-time Polymerase chain reaction (RT-PCR), and the purpose was to reveal the correlation of <i>AOP2</i> and sulforaphane contents in different organs of broccoli flower bud development. Sulforaphane levels were evaluated in broccoli florets, buds in bolting, flowers, and ripe seed. The results showed that there was a good linear equation, Y = 3754.22X − 2072.47, R<sup>2</sup> = 0.9991, and sulforaphane levels increased during development from florets to young buds in bolting plants, thereafter decreased gradually in older buds to flowers. The ripe seed was the highest organ (13.35g/kg DW (dry weight)) with sulforaphane content in all the materials. RT-PCR result showed an opposite relationship of sulforaphane contents and the expression levels of gene <i>AOP2</i> from young buds to flowers in bolting period. The study demonstrated that the over-expression of the gene <i>AOP2</i> leads to a peak level of sulforaphane content in organs of broccoli.
DOI: 10.6084/m9.figshare.963333.v2
title: VARIATION OF SULFORAPHANE LEVELS IN BROCCOLI (<i>BRASSICA OLERACEA</i> VAR. <i>ITALICA</i>) DURING FLOWER DEVELOPMENT AND THE ROLE OF GENE <i>AOP2</i>

description: Sulforaphane is abundant in broccoli (<i>Brassica oleracea</i> var. <i>italica</i>) and has been widely studied since it may reduce the risk of several types of cancer. Here, the variation of sulforaphane levels during different stages of broccoli flower bud development was studied by high-performance liquid chromatography (HPLC). At the same time, the expressions of gene <i>AOP2</i> in all the materials were studied by real-time Polymerase chain reaction (RT-PCR), and the purpose was to reveal the correlation of <i>AOP2</i> and sulforaphane contents in different organs of broccoli flower bud development. Sulforaphane levels were evaluated in broccoli florets, buds in bolting, flowers, and ripe seed. The results showed that there was a good linear equation, Y = 3754.22X − 2072.47, R<sup>2</sup> = 0.9991, and sulforaphane levels increased during development from florets to young buds in bolting plants, thereafter decreased gradually in older buds to flowers. The ripe seed was the highest organ (13.35g/kg DW (dry weight)) with sulforaphane content in all the materials. RT-PCR result showed an opposite relationship of sulforaphane contents and the expression levels of gene <i>AOP2</i> from young buds to flowers in bolting period. The study demonstrated that the over-expression of the gene <i>AOP2</i> leads to a peak level of sulforaphane content in organs of broccoli.
DOI: 10.6084/m9.figshare.963333.v1
title: VARIATION OF SULFORAPHANE LEVELS IN BROCCOLI (<i>BRASSICA OLERACEA</i> VAR. <i>ITALICA</i>) DURING FLOWER DEVELOPMENT AND THE ROLE OF GENE <i>AOP2</i>

description: Sulforaphane is abundant in broccoli (Brassica oleracea var. italica) and has been widely studied since it may reduce the risk of several types of cancer. Here, the variation of sulforaphane levels during different stages of broccoli flower bud development was studied by high-performance liquid chromatography (HPLC). At the same time, the expressions of gene AOP2in all the materials were studied by real-time Polymerase chain reaction (RT-PCR), and the purpose was to reveal the correlation of AOP2 and sulforaphane contents in different organs of broccoli flower bud development. Sulforaphane levels were evaluated in broccoli florets, buds in bolting, flowers, and ripe seed. The results showed that there was a good linear equation, <i>Y</i> = 3754.22X − 2072.47, <i>R</i><sup>2</sup> = 0.9991, and sulforaphane levels increased during development from florets to young buds in bolting plants, thereafter decreased gradually in older buds to flowers. The ripe seed was the highest organ (13.35g/kg DW (dry weight)) with sulforaphane content in all the materials. RT-PCR result showed an opposite relationship of sulforaphane contents and the expression levels of gene AOP2 from young buds to flowers in bolting period. The study demonstrated that the over-expression of the gene AOP2 leads to a peak level of sulforaphane content in organs of broccoli.
DOI: 10.6084/m9.figshare.963385
title: The aggressive behavior in the TAP

description: The average punishment selection by the participants in the TAP under the high and low provocation.
DOI: 10.6084/m9.figshare.963385.v1
title: The aggressive behavior in the TAP

description: The average punishment selection by the participants in the TAP under the high and low provocation.