Investigating the clinical use of structured light plethysmography to assess lung function in children with neuromuscular disorders

BackgroundChildren and young people with neuromuscular disorders (NMD), such as Duchenne Muscular Dystrophy (DMD), develop progressive respiratory muscles weakness and pulmonary restriction. Pulmonary function monitoring of the decline in lung function allows for timely intervention with cough assist techniques and nocturnal non-invasive ventilation (NIV). NMD may find the measurement of lung function difficult using current techniques. Structured Light Plethysmography (SLP) has been proposed as a novel, non-contact, self-calibrating, non-invasive method of assessing lung function. The overarching aim of this study was to investigate the use of SLP as a novel method for monitoring respiratory function in children with neuromuscular disease.MethodsSLP thoraco-abdominal (TA) displacement was correlated with forced vital capacity measurements recorded by spirometry and the repeatability of the measurements with both methods examined. SLP tidal breathing parameters were investigated to assess the range and repeatability of regional right and left side TA displacement and rib cage and abdominal wall displacement.ResultsThe comparison of the FVC measured with SLP and with spirometry, while having good correlation (R = 0.78) had poor measurement agreement (95% limits of agreement: -1.2 to 1.2L) The mean relative contribution of right and left TA displacement in healthy controls was 50:50 with a narrow range. Repeatability of this measure with SLP was found to be good in healthy controls and moderate in NMD children with/without scoliosis but with a wider range. The majority of the control group displayed a predominant rib cage displacement during tidal breathing and those who displayed predominant abdominal wall displacement showed displacement of both regions close to 50:50 with similar results for the rib cage and abdomen. In comparison, children with NMD have a more variable contribution for all of these parameters. In addition, SLP was able to detect a reduction in abdominal contribution to TA displacement with age in the DMD group and detect paradoxical breathing in children with NMD. Using SLP tracings during tidal breathing we were able to identify three specific patterns of breathing amongst healthy individuals and in children with NMD.ConclusionsSLP is a novel method for measuring lung function that requires limited patient cooperation and may be especially useful in children with neuromuscular disorders. Measuring the relative contributions of the right and left chest wall and chest versus abdominal movements allows a more detailed assessment

The Green Bank Ammonia Survey (GAS): First Results of NH3 mapping the Gould Belt

We present an overview of the first data release (DR1) and first-look science from the Green Bank Ammonia Survey (GAS). GAS is a Large Program at the Green Bank Telescope to map all Gould Belt star-forming regions with $A_V \gtrsim 7$ mag visible from the northern hemisphere in emission from NH$_3$ and other key molecular tracers. This first release includes the data for four regions in Gould Belt clouds: B18 in Taurus, NGC 1333 in Perseus, L1688 in Ophiuchus, and Orion A North in Orion. We compare the NH$_3$ emission to dust continuum emission from Herschel, and find that the two tracers correspond closely. NH$_3$ is present in over 60\% of lines-of-sight with $A_V \gtrsim 7$ mag in three of the four DR1 regions, in agreement with expectations from previous observations. The sole exception is B18, where NH$_3$ is detected toward ~ 40\% of lines-of-sight with $A_V \gtrsim 7$ mag. Moreover, we find that the NH$_3$ emission is generally extended beyond the typical 0.1 pc length scales of dense cores. We produce maps of the gas kinematics, temperature, and NH$_3$ column densities through forward modeling of the hyperfine structure of the NH$_3$ (1,1) and (2,2) lines. We show that the NH$_3$ velocity dispersion, ${\sigma}_v$, and gas kinetic temperature, $T_K$, vary systematically between the regions included in this release, with an increase in both the mean value and spread of ${\sigma}_v$ and $T_K$ with increasing star formation activity. The data presented in this paper are publicly available.Comment: 33 pages, 27 figures, accepted to ApJS. Datasets are publicly available: https://dataverse.harvard.edu/dataverse/GAS_DR

Droplets I: Pressure-Dominated Sub-0.1 pc Coherent Structures in L1688 and B18

We present the observation and analysis of newly discovered coherent structures in the L1688 region of Ophiuchus and the B18 region of Taurus. Using data from the Green Bank Ammonia Survey (GAS), we identify regions of high density and near-constant, almost-thermal, velocity dispersion. Eighteen coherent structures are revealed, twelve in L1688 and six in B18, each of which shows a sharp "transition to coherence" in velocity dispersion around its periphery. The identification of these structures provides a chance to study the coherent structures in molecular clouds statistically. The identified coherent structures have a typical radius of 0.04 pc and a typical mass of 0.4 Msun, generally smaller than previously known coherent cores identified by Goodman et al. (1998), Caselli et al. (2002), and Pineda et al. (2010). We call these structures "droplets." We find that unlike previously known coherent cores, these structures are not virially bound by self-gravity and are instead predominantly confined by ambient pressure. The droplets have density profiles shallower than a critical Bonnor-Ebert sphere, and they have a velocity (VLSR) distribution consistent with the dense gas motions traced by NH3 emission. These results point to a potential formation mechanism through pressure compression and turbulent processes in the dense gas. We present a comparison with a magnetohydrodynamic simulation of a star-forming region, and we speculate on the relationship of droplets with larger, gravitationally bound coherent cores, as well as on the role that droplets and other coherent structures play in the star formation process.Comment: Accepted by ApJ in April, 201

Dual mechanisms by which MiR-125b represses IRF4 to induce myeloid and B cell leukemias

The oncomir microRNA-125b (miR-125b) is up-regulated in a variety of human neoplastic blood disorders and constitutive up-regulation of miR-125b in mice can promote myeloid and B cell leukemia. We found that miR-125b promotes myeloid and B cell neoplasm by inducing tumorigenesis in hematopoietic progenitor cells. Our study demonstrates that miR-125b induces myeloid leukemia by enhancing myeloid progenitor output from stem cells as well as inducing immortality, self-renewal, and tumorigenesis in myeloid progenitors. Through functional and genetic analyses, we demonstrated that miR-125b induces myeloid and B cell leukemia by inhibiting IRF4 but through distinct mechanisms; it induces myeloid leukemia through repressing IRF4 at the mRNA level without altering the genomic DNA and induces B cell leukemia via genetic deletion of the gene encoding IRF4

Granulovirus PK-1 kinase activity relies on a side-to-side dimerization mode centered on the regulatory αC helix

The life cycle of Baculoviridae family insect viruses depends on the viral protein kinase, PK-1, to phosphorylate the regulatory protein, p6.9, to induce baculoviral genome release. Here, we report the crystal structure of Cydia pomenella granulovirus PK-1, which, owing to its likely ancestral origin among host cell AGC kinases, exhibits a eukaryotic protein kinase fold. PK-1 occurs as a rigid dimer, where an antiparallel arrangement of the αC helices at the dimer core stabilizes PK-1 in a closed, active conformation. Dimerization is facilitated by C-lobe:C-lobe and N-lobe:N-lobe interactions between protomers, including the domain-swapping of an N-terminal helix that crowns a contiguous β-sheet formed by the two N-lobes. PK-1 retains a dimeric conformation in solution, which is crucial for catalytic activity. Our studies raise the prospect that parallel, side-to-side dimeric arrangements that lock kinase domains in a catalytically-active conformation could function more broadly as a regulatory mechanism among eukaryotic protein kinases

The Green Bank Ammonia Survey: First Results of NH3 Mapping of the Gould Belt

We present an overview of the first data release (DR1) and first-look science from the Green Bank Ammonia Survey (GAS). GAS is a Large Program at the Green Bank Telescope to map all Gould Belt star-forming regions with {A}{{V}}≳ 7 mag visible from the northern hemisphere in emission from NH3 and other key molecular tracers. This first release includes the data for four regions in the Gould Belt clouds: B18 in Taurus, NGC 1333 in Perseus, L1688 in Ophiuchus, and Orion A North in Orion. We compare the NH3 emission to dust continuum emission from Herschel and find that the two tracers correspond closely. We find that NH3 is present in over 60% of the lines of sight with {A}{{V}}≳ 7 mag in three of the four DR1 regions, in agreement with expectations from previous observations. The sole exception is B18, where NH3 is detected toward ̃40% of the lines of sight with {A}{{V}}≳ 7 mag. Moreover, we find that the NH3 emission is generally extended beyond the typical 0.1 pc length scales of dense cores. We produce maps of the gas kinematics, temperature, and NH3 column densities through forward modeling of the hyperfine structure of the NH3 (1, 1) and (2, 2) lines. We show that the NH3 velocity dispersion, {σ }v, and gas kinetic temperature, T K, vary systematically between the regions included in this release, with an increase in both the mean value and the spread of {σ }v and T K with increasing star formation activity. The data presented in this paper are publicly available (https://dataverse.harvard.edu/dataverse/GAS_DR1).Astronom

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

GENOME-SCALE STUDIES OF DYNAMIC DNA METHYLATION IN MAMMALIAN BRAIN CELLS

Developmental processes, genes and environmental factors interact to produce changes in cognition and behavior over the lifespan of an individual. However, the underlying molecular genetic mechanisms that mediate these changes remain to be fully elucidated. DNA methylation is an epigenetic mechanism that defines cell identity and helps regulate gene expression. DNA methylation is dynamic over development and has been shown to mediate experience-dependent changes, including those resulting from learning and memory and early life adversity. Although methylation mainly occurs at genomic cytosines in the CG dinucleotide context, methylation at non-CG sites was recently found in brain tissue. Non-CG methylation is specifically enriched in neurons and accumulates during the early childhood stages of brain development. The biological impact of non-CG methylation in regulating gene expression and regulating cellular function, if any, remains unclear. A major challenge for addressing this question is the complexity and scale of the DNA methylation landscape, which includes nearly one billion cytosines throughout the genome that are potential sites of modification in every cell. Targeted studies of specific candidate genes and genomic loci do not elucidate the overall configuration of the cellular epigenome. Techniques for comprehensively mapping the genome-wide distribution of DNA methylation are powerful, but they require sophisticated new computational methods of analysis that can reliably distinguish and statistically validate epigenomic differences related to developmental and environmental factors.In this thesis we develop new approaches to comprehensively analyze DNA methylation throughout the genome and with single base resolution in order to better characterize the role of CG methylation and elucidate the potential role of CH methylation in mammalian brain cells. First, we consider the impact of enriched early life (peri-pubertal) experience on DNA methylation and gene expression in the dentate gyrus of the hippocampus. In addition to its role in experience-dependent gene regulation, DNA methylation also plays a key role in innate developmental processes, including female X chromosome inactivation. We provide the first allele-specific DNA methylomes from the active and inactive X chromosomes in female brain, and use comprehensive genomic analyses to gain insight into the functional relationship between allele-specific DNA methylation and transcription. These two studies provide new evidence of the dynamic changes in DNA methylation in whole brain tissue caused by environmental and innate developmental factors. However, they do not address the heterogeneity of brain cell types, a hallmark of mammalian brain organization. To address the role of DNA methylation in brain cell diversity, we develop computational methods to analyze data from a new assay that measures single cell methylomes. Using these data, we show that brain cell methylomes can be clustered and used to assess neuronal heterogeneity in the frontal cortex of mouse and human. Upon clustering cells, we are able to gain insight into the role of methylation in the establishment and maintenance of cellular identity in neuronal types.Overall, this thesis adds to the increasing evidence that DNA methylation is a cell type-specific, dynamic epigenomic modification of brain cells that is impacted by, and may in turn help to regulate, neuronal development and adaptation. In addition, this thesis provides new computational methods for analyzing large-scale, whole-genome DNA methylation data sets and demonstrates their use in uncovering new insights into the mammalian brain epigenome

Genome-Scale Studies of Dynamic DNA Methylation in Mammalian Brain Cells

Developmental processes, genes and environmental factors interact to produce changes in cognition and behavior over the lifespan of an individual. However, the underlying molecular genetic mechanisms that mediate these changes remain to be fully elucidated. DNA methylation is an epigenetic mechanism that defines cell identity and helps regulate gene expression. DNA methylation is dynamic over development and has been shown to mediate experience-dependent changes, including those resulting from learning and memory and early life adversity. Although methylation mainly occurs at genomic cytosines in the CG dinucleotide context, methylation at non-CG sites was recently found in brain tissue. Non-CG methylation is specifically enriched in neurons and accumulates during the early childhood stages of brain development. The biological impact of non-CG methylation in regulating gene expression and regulating cellular function, if any, remains unclear. A major challenge for addressing this question is the complexity and scale of the DNA methylation landscape, which includes nearly one billion cytosines throughout the genome that are potential sites of modification in every cell. Targeted studies of specific candidate genes and genomic loci do not elucidate the overall configuration of the cellular epigenome. Techniques for comprehensively mapping the genome-wide distribution of DNA methylation are powerful, but they require sophisticated new computational methods of analysis that can reliably distinguish and statistically validate epigenomic differences related to developmental and environmental factors. In this thesis we develop new approaches to comprehensively analyze DNA methylation throughout the genome and with single base resolution in order to better characterize the role of CG methylation and elucidate the potential role of CH methylation in mammalian brain cells. First, we consider the impact of enriched early life (peri-pubertal) experience on DNA methylation and gene expression in the dentate gyrus of the hippocampus. In addition to its role in experience-dependent gene regulation, DNA methylation also plays a key role in innate developmental processes, including female X chromosome inactivation. We provide the first allele-specific DNA methylomes from the active and inactive X chromosomes in female brain, and use comprehensive genomic analyses to gain insight into the functional relationship between allele-specific DNA methylation and transcription. These two studies provide new evidence of the dynamic changes in DNA methylation in whole brain tissue caused by environmental and innate developmental factors. However, they do not address the heterogeneity of brain cell types, a hallmark of mammalian brain organization. To address the role of DNA methylation in brain cell diversity, we develop computational methods to analyze data from a new assay that measures single cell methylomes. Using these data, we show that brain cell methylomes can be clustered and used to assess neuronal heterogeneity in the frontal cortex of mouse and human. Upon clustering cells, we are able to gain insight into the role of methylation in the establishment and maintenance of cellular identity in neuronal types. Overall, this thesis adds to the increasing evidence that DNA methylation is a cell type-specific, dynamic epigenomic modification of brain cells that is impacted by, and may in turn help to regulate, neuronal development and adaptation. In addition, this thesis provides new computational methods for analyzing large-scale, whole-genome DNA methylation data sets and demonstrates their use in uncovering new insights into the mammalian brain epigenome