173 research outputs found
Long-Term Mortality in Patients with Tuberculous Meningitis: A Danish Nationwide Cohort Study
Background: With high short-term mortality and substantial excess morbidity among survivors, tuberculous meningitis (TBM) is the most severe manifestation of extra-pulmonary tuberculosis (TB). The objective of this study was to assess the long-term mortality and causes of death in a TBM patient population compared to the background population. Methods: A nationwide cohort study was conducted enrolling patients notified with TBM in Denmark from 1972–2008 and alive one year after TBM diagnosis. Data was extracted from national registries. From the background population we identified a control cohort of individuals matched on gender and date of birth. Kaplan-Meier survival curves and Cox regression analysis were used to estimate mortality rate ratios (MRR) and analyse causes of death. Findings: A total of 55 TBM patients and 550 individuals from the background population were included in the study. Eighteen patients (32.7%) and 107 population controls (19.5%) died during the observation period. The overall MRR was 1.79 (95%CI: 1.09–2.95) for TBM patients compared to the population control cohort. TBM patients in the age group 31–60 years at time of diagnosis had the highest relative risk of death (MRR 2.68; 95%CI 1.34–5.34). The TBM patients had a higher risk of death due to infectious disease, but not from other causes of death. Conclusion: Adult TBM patients have an almost two-fold increased long-term mortality and the excess mortality stems fro
Ultra-Sharp Nanowire Arrays Natively Permeate, Record, and Stimulate Intracellular Activity in Neuronal and Cardiac Networks
Intracellular access with high spatiotemporal resolution can enhance our
understanding of how neurons or cardiomyocytes regulate and orchestrate network
activity, and how this activity can be affected with pharmacology or other
interventional modalities. Nanoscale devices often employ electroporation to
transiently permeate the cell membrane and record intracellular potentials,
which tend to decrease rapidly to extracellular potential amplitudes with time.
Here, we report innovative scalable, vertical, ultra-sharp nanowire arrays that
are individually addressable to enable long-term, native recordings of
intracellular potentials. We report large action potential amplitudes that are
indicative of intracellular access from 3D tissue-like networks of neurons and
cardiomyocytes across recording days and that do not decrease to extracellular
amplitudes for the duration of the recording of several minutes. Our findings
are validated with cross-sectional microscopy, pharmacology, and electrical
interventions. Our experiments and simulations demonstrate that individual
electrical addressability of nanowires is necessary for high-fidelity
intracellular electrophysiological recordings. This study advances our
understanding of and control over high-quality multi-channel intracellular
recordings, and paves the way toward predictive, high-throughput, and low-cost
electrophysiological drug screening platforms.Comment: Main manuscript: 33 pages, 4 figures, Supporting information: 43
pages, 27 figures, Submitted to Advanced Material
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.
We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition
Correlations in a Many-Body Calculation of Li
A many-body calculation of Li is presented where the only input is the
well-tested, finite-range {\it D1S} effective interaction of {\it Gogny}.
Pairing correlations are included in a constrained Hartree-Fock-Bogolyubov
calculation, while long-range collective correlations are introduced using a
GCM derived calculation. Correlations are found to play an important role in
describing Li. A substantive underlying Li core of Li is
found, which has a different density profile than a free Li nucleus. This
may have significant implications in the use of a three-body framework in
studies of Li.Comment: 23 pages typeset in revtex 2.0 with 8 postscript figures in
accompanying uuencoded fil
Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.
Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis
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
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
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
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
Time-Resolved Transcriptome Analysis of Bacillus subtilis Responding to Valine, Glutamate, and Glutamine
Microorganisms can restructure their transcriptional output to adapt to environmental conditions by sensing endogenous metabolite pools. In this paper, an Agilent customized microarray representing 4,106 genes was used to study temporal transcript profiles of Bacillus subtilis in response to valine, glutamate and glutamine pulses over 24 h. A total of 673, 835, and 1135 amino-acid-regulated genes were identified having significantly changed expression at one or more time points in response to valine, glutamate, and glutamine, respectively, including genes involved in cell wall, cellular import, metabolism of amino-acids and nucleotides, transcriptional regulation, flagellar motility, chemotaxis, phage proteins, sporulation, and many genes of unknown function. Different amino acid treatments were compared in terms of both the global temporal profiles and the 5-minute quick regulations, and between-experiment differential genes were identified. The highlighted genes were analyzed based on diverse sources of gene functions using a variety of computational tools, including T-profiler analysis, and hierarchical clustering. The results revealed the common and distinct modes of action of these three amino acids, and should help to elucidate the specific signaling mechanism of each amino acid as an effector
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