112 research outputs found
Safe use of proton pump inhibitors in patients with cirrhosis
Aims: Proton pump inhibitors (PPIs) belong to the most frequently used drugs, also in patients with cirrhosis. PPIs are extensively metabolized by the liver, but practice guidance on prescribing in cirrhosis is lacking. We aim to develop practical guidance on the safe use of PPIs in patients with cirrhosis. Methods: A systematic literature search identified studies on the safety (i.e. adverse events) and pharmacokinetics of PPIs in cirrhotic patients. This evidence and data from the product information was reviewed by an expert panel who classified drugs as safe; no additional risks known; additional risks known; unsafe; or unknown. Guidance was aimed at the oral use of PPIs and categorized by the severity of cirrhosis, using the Child–Turcotte–Pugh (CTP) classification. Results: A total of 69 studies were included. Esomeprazole, omeprazole and rabeprazole were classified as having ‘no additional risks known’. A reduction in maximum dose of omeprazole and rabeprazole is recommended for CTP A and B patients. For patients with CTP C cirrhosis, the only PPI advised is esomeprazole at a maximum dosage of 20 mg per day. Pantoprazole and lansoprazole were classified as unsafe because of 4- to 8-fold increased exposure. The use of PPIs in cirrhotic patients has been associated with the development of infections and hepatic encephalopathy and should be carefully considered. Conclusions: We suggest using esomeprazole, omeprazole or rabeprazole in patients with CTP A or B cirrhosis and only esomeprazole in patients with CTP C. Pharmacokinetic changes are also important to consider when prescribing PPIs to vulnerable, cirrhotic patients
Magnetic Reconnection in Extreme Astrophysical Environments
Magnetic reconnection is a basic plasma process of dramatic rearrangement of
magnetic topology, often leading to a violent release of magnetic energy. It is
important in magnetic fusion and in space and solar physics --- areas that have
so far provided the context for most of reconnection research. Importantly,
these environments consist just of electrons and ions and the dissipated energy
always stays with the plasma. In contrast, in this paper I introduce a new
direction of research, motivated by several important problems in high-energy
astrophysics --- reconnection in high energy density (HED) radiative plasmas,
where radiation pressure and radiative cooling become dominant factors in the
pressure and energy balance. I identify the key processes distinguishing HED
reconnection: special-relativistic effects; radiative effects (radiative
cooling, radiation pressure, and Compton resistivity); and, at the most extreme
end, QED effects, including pair creation. I then discuss the main
astrophysical applications --- situations with magnetar-strength fields
(exceeding the quantum critical field of about 4 x 10^13 G): giant SGR flares
and magnetically-powered central engines and jets of GRBs. Here, magnetic
energy density is so high that its dissipation heats the plasma to MeV
temperatures. Electron-positron pairs are then copiously produced, making the
reconnection layer highly collisional and dressing it in a thick pair coat that
traps radiation. The pressure is dominated by radiation and pairs. Yet,
radiation diffusion across the layer may be faster than the global Alfv\'en
transit time; then, radiative cooling governs the thermodynamics and
reconnection becomes a radiative transfer problem, greatly affected by the
ultra-strong magnetic field. This overall picture is very different from our
traditional picture of reconnection and thus represents a new frontier in
reconnection research.Comment: Accepted to Space Science Reviews (special issue on magnetic
reconnection). Article is based on an invited review talk at the
Yosemite-2010 Workshop on Magnetic Reconnection (Yosemite NP, CA, USA;
February 8-12, 2010). 30 pages, no figure
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
A First Search for coincident Gravitational Waves and High Energy Neutrinos using LIGO, Virgo and ANTARES data from 2007
We present the results of the first search for gravitational wave bursts
associated with high energy neutrinos. Together, these messengers could reveal
new, hidden sources that are not observed by conventional photon astronomy,
particularly at high energy. Our search uses neutrinos detected by the
underwater neutrino telescope ANTARES in its 5 line configuration during the
period January - September 2007, which coincided with the fifth and first
science runs of LIGO and Virgo, respectively. The LIGO-Virgo data were analysed
for candidate gravitational-wave signals coincident in time and direction with
the neutrino events. No significant coincident events were observed. We place
limits on the density of joint high energy neutrino - gravitational wave
emission events in the local universe, and compare them with densities of
merger and core-collapse events.Comment: 19 pages, 8 figures, science summary page at
http://www.ligo.org/science/Publication-S5LV_ANTARES/index.php. Public access
area to figures, tables at
https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p120000
Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.
Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy
New insights into the genetic etiology of Alzheimer's disease and related dementias
Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment
The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma
Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival
Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types
Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis
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