Bone Tumors: Types and Treatments

The tumors associated with bone are mostly of mesenchymal origin and contribute to approximately 1% of all the known tumors. These could be primary/benign tumors (that originate in the bone), secondary tumors (that originate in some other tissue/organ and metastasize to the bone), or malignant primary bone tumors (that originate in bone and metastasize to distant tissue). These tumors are majorly due to defects in the regulation of tumor suppressor genes and oncogenes and/or misregulation of signal transduction pathways. Chemotherapy and radiotherapy used for the treatment have several side effects. During the recent years, therapeutic strategies involving hormone deprivation (estrogen, androgen), hormone replacements (estrogen analogs), hormone receptor modulators (SERMs), growth factors and cytokines, small-molecule inhibitors, and gene therapy have emerged as a promising alternative to chemo- and radiotherapy. In the present chapter, we have provided an extensive account of tumors associated with the bone and various therapeutic options related to hormone deprivation, hormone replacements, hormone receptor modulators, and hormone inhibition

Prophylactic anticoagulation to prevent venous thromboembolism in traumatic intracranial hemorrhage: a decision analysis

Abstract Introduction Patients with intracranial hemorrhage due to traumatic brain injury are at high risk of developing venous thromboembolism including deep vein thrombosis (DVT) and pulmonary embolism (PE). Thus, there is a trade-off between the risks of progression of intracranial hemorrhage (ICH) versus reduction of DVT/PE with the use of prophylactic anticoagulation. Using decision analysis modeling techniques, we developed a model for examining this trade-off for trauma patients with documented ICH. Methods The decision node involved the choice to administer or to withhold low molecular weight heparin (LMWH) anticoagulation prophylaxis at 24 hours. Advantages of withholding therapy were decreased risk of ICH progression (death, disabling neurologic deficit, non-disabling neurologic deficit), and decreased risk of systemic bleeding complications (death, massive bleed). The associated disadvantage was greater risk of developing DVT/PE or death. Probabilities for each outcome were derived from natural history studies and randomized controlled trials when available. Utilities were obtained from accepted databases and previous studies. Results The expected value associated with withholding anticoagulation prophylaxis was similar (0.90) to that associated with the LMWH strategy (0.89). Only two threshold values were encountered in one-way sensitivity analyses. If the effectiveness of LMWH at preventing DVT exceeded 80% (range from literature 33% to 82%) our model favoured this therapy. Similarly, our model favoured use of LMWH if this therapy increased the risk of ICH progression by no more than 5% above the baseline risk. Conclusions Our model showed no clear advantage to providing or withholding anticoagulant prophylaxis for DVT/PE prevention at 24 hours after traumatic brain injury associated with ICH. Therefore randomized controlled trials are justifiable and needed to guide clinicians

Highly time-resolved chemical speciation and source apportionment of organic aerosol components in Delhi, India, using extractive electrospray ionization mass spectrometry

In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winter. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the total AMS SOA (i.e. MO-OOA + LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major SOA component during the daytime, with a 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during the nighttime. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during the daytime and 36.1 % of total SOA mass (11.2 % of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass (11.7 % and 8.5 % of total OA mass), respectively, during the daytime and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass), respectively, during the nighttime. A simple dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the daytime suggests an increased OA toxicity and health-related consequences for the general public.</p

The performance of "Virtual Phase" CCDs as detectors of minimum-ionizing particles

The Texas Instruments "Virtual Phase" CCD has been the basis of an ambitious design for a precision vertex detector to be used at the Stanford Linear Collider. The performance of this chip shows promise for future use in electron linear colliders. Experimental results are reported in addition to description of the electronic readout and preliminary mechanical design.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26549/1/0000088.pd

The Atacama Cosmology Telescope: Cosmological parameters from three seasons of data

We present constraints on cosmological and astrophysical parameters from high-resolution microwave background maps at 148 GHz and 218 GHz made by the Atacama Cosmology Telescope (ACT) in three seasons of observations from 2008 to 2010. A model of primary cosmological and secondary foreground parameters is fit to the map power spectra and lensing deflection power spectrum, including contributions from both the thermal Sunyaev-Zeldovich (tSZ) effect and the kinematic Sunyaev-Zeldovich (kSZ) effect, Poisson and correlated anisotropy from unresolved infrared sources, radio sources, and the correlation between the tSZ effect and infrared sources. The power ell^2 C_ell/2pi of the thermal SZ power spectrum at 148 GHz is measured to be 3.4 +\- 1.4 muK^2 at ell=3000, while the corresponding amplitude of the kinematic SZ power spectrum has a 95% confidence level upper limit of 8.6 muK^2. Combining ACT power spectra with the WMAP 7-year temperature and polarization power spectra, we find excellent consistency with the LCDM model. We constrain the number of effective relativistic degrees of freedom in the early universe to be Neff=2.79 +\- 0.56, in agreement with the canonical value of Neff=3.046 for three massless neutrinos. We constrain the sum of the neutrino masses to be Sigma m_nu < 0.39 eV at 95% confidence when combining ACT and WMAP 7-year data with BAO and Hubble constant measurements. We constrain the amount of primordial helium to be Yp = 0.225 +\- 0.034, and measure no variation in the fine structure constant alpha since recombination, with alpha/alpha0 = 1.004 +/- 0.005. We also find no evidence for any running of the scalar spectral index, dns/dlnk = -0.004 +\- 0.012.Comment: 26 pages, 22 figures. This paper is a companion to Das et al. (2013) and Dunkley et al. (2013). Matches published JCAP versio

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

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