Development of Ion Mobility-mass Spectrometry Instrumentation to Probe the Conformations and Capture the Solution to Gas Phase Transition of Electrosprayed Biomolecules

Recent progress has been made developing ion mobility-mass spectrometry (IM-MS) instruments for biophysical studies; however, experimental techniques that can probe the structure and/or dynamics of biomolecules at intermediate extents of hydration are limited and little is known about the final stages of desolvation during electrospray ionization (ESI). Here, ion optical devices, analytical methodology, and instrument platforms are developed to study the conformations of structurally labile biomolecules (i.e., peptides and proteins) produced upon ESI and provide new insight into their solution to gas phase evolution. First, fundamental principles of periodic focusing ion mobility spectrometry are comprehensively discussed. Radial ion confinement is attributed to a collisionally dampened effective potential that ultimately results in high ion transmission. Detailed equations of motion are derived that culminate into useful methodology for accurate determination of peptide and protein collision cross section values via inclusion of a mobility dampening coefficient. Second, evaporation of water from extensively hydrated protons and peptides formed by ESI is examined for the first time using a new cryogenic (80 K) IM-MS instrument platform. Key parameters that influence the cluster distributions are critically examined. In agreement with previous studies, the findings indicate that water evaporation is largely dependent upon the particular charge-carrying species within the cluster. IM-MS results for protonated water clusters suggest that the special stability of the well-known H^(+)(H_(2)O)_(n) (n = 21) “magic number” cluster is attributed to the presence of a compact clathrate cage isomer produced upon ESI. Peptide studies are also presented in which specific and nonspecific solvation is observed for gramicidin S [GS + 2H]^(2+) (H_(2)O)_(n) (n = 0 to 26) and bradykinin [BK + 2H]^(2+) (H_(2)O)_(n) (n = 0 to 73), respectively. However in the case of substance P, [SP + 3H]^(3+), the results demonstrate that a compact dehydrated conformer population (resulting from the evaporative ESI process) can be kinetically trapped on the time scale of several milliseconds, even when an extended coil conformation is energetically favorable in the gas phase

Temporal modulation of the response of sensory fibers to paired-pulse stimulation

Multi-channel nerve cuff electrode arrays can provide sensory feedback to prosthesis users. To develop efficacious stimulation protocols, an understanding of the impact that spatio-temporal patterned stimulation can have on the response of sensory fibers is crucial. We used experimental and modelling methods to investigate the response of nerve fibers to paired-pulse stimulation. Nerve cuff electrode arrays were implanted for stimulation of the sciatic nerves of rats and the sensory compound action potentials were recorded from the L4 dorsal root. A model of the nerve cuff electrode array and sciatic nerve was also developed. The experimental and modelling results were compared. Experiments showed that it took 8 ms for the sensory fibers to completely recover from a conditioning stimulus, regardless of the relative position of the electrodes used for stimulation. The results demonstrate that the electrodes on the cuff cannot be considered independent. Additionally, at 120% of the threshold, there is a large overlap in the fibers that were activated by the different electrodes. If a stimulus paradigm considered the electrodes as independent, stimuli from the different electrodes would need to be interleaved, and the intervals between the stimuli should be greater than 8 ms

New Constraints from High Redshift Supernovae and Lensing Statistics upon Scalar Field Cosmologies

We explore the implications of gravitationally lensed QSOs and high-redshift SNe Ia observations for spatially flat cosmological models in which a classically evolving scalar field currently dominates the energy density of the Universe. We consider two representative scalar field potentials that give rise to effective decaying $\Lambda$ (``quintessence'') models: pseudo-Nambu-Goldstone bosons ($V(\phi)=M^4(1+\cos (\phi /f))$) and an inverse power-law potential ($V(\phi)=M^{4+\alpha}\phi ^{-\alpha}$). We show that a large region of parameter space is consistent with current data if $\Omega_{m0} > 0.15$. On the other hand, a higher lower bound for the matter density parameter suggested by large-scale galaxy flows, $\Omega_{m0} > 0.3$, considerably reduces the allowed parameter space, forcing the scalar field behavior to approach that of a cosmological constant.Comment: 6 pages, 2 figures, submitted to PR

Constraints from High Redshift Supernovae upon Scalar Field Cosmologies

Recent observations of high-redshift Type Ia supernovae have placed stringent constraints on the cosmological constant $\Lambda$. We explore the implications of these SNe observations for cosmological models in which a classically evolving scalar field currently dominates the energy density of the Universe. Such models have been shown to share the advantages of $\Lambda$ models: compatibility with the spatial flatness predicted inflation; a Universe older than the standard Einstein-de Sitter model; and, combined with cold dark matter, predictions for large-scale structure formation in good agreement with data from galaxy surveys. Compared to the cosmological constant, these scalar field models are consistent with the SNe observations for a lower matter density, $\Omega_{m0} \sim 0.2$, and a higher age, $H_0 t_0 \gtrsim 1$. Combined with the fact that scalar field models imprint a distinctive signature on the cosmic microwave background anisotropy, they remain currently viable and should be testable in the near future.Comment: RevTex style format, 14 pages, 11 eps figures included with epsf, submitted to Phys. Rev.

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

National and regional estimates of term and preterm babies born small for gestational age in 138 low-income and middle-income countries in 2010.

BACKGROUND: National estimates for the numbers of babies born small for gestational age and the comorbidity with preterm birth are unavailable. We aimed to estimate the prevalence of term and preterm babies born small for gestational age (term-SGA and preterm-SGA), and the relation to low birthweight (<2500 g), in 138 countries of low and middle income in 2010. METHODS: Small for gestational age was defined as lower than the 10th centile for fetal growth from the 1991 US national reference population. Data from 22 birth cohort studies (14 low-income and middle-income countries) and from the WHO Global Survey on Maternal and Perinatal Health (23 countries) were used to model the prevalence of term-SGA births. Prevalence of preterm-SGA infants was calculated from meta-analyses. FINDINGS: In 2010, an estimated 32·4 million infants were born small for gestational age in low-income and middle-income countries (27% of livebirths), of whom 10·6 million infants were born at term and low birthweight. The prevalence of term-SGA babies ranged from 5·3% of livebirths in east Asia to 41·5% in south Asia, and the prevalence of preterm-SGA infants ranged from 1·2% in north Africa to 3·0% in southeast Asia. Of 18 million low-birthweight babies, 59% were term-SGA and 41% were preterm-SGA. Two-thirds of small-for-gestational-age infants were born in Asia (17·4 million in south Asia). Preterm-SGA babies totalled 2·8 million births in low-income and middle-income countries. Most small-for-gestational-age infants were born in India, Pakistan, Nigeria, and Bangladesh. INTERPRETATION: The burden of small-for-gestational-age births is very high in countries of low and middle income and is concentrated in south Asia. Implementation of effective interventions for babies born too small or too soon is an urgent priority to increase survival and reduce disability, stunting, and non-communicable diseases. FUNDING: Bill & Melinda Gates Foundation by a grant to the US Fund for UNICEF to support the activities of the Child Health Epidemiology Reference Group (CHERG)

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment