Improving Phrap-Based Assembly of the Rat Using “Reliable” Overlaps

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of “reliable” overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our “reliable-overlap” algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps

Nano-porosity in GaSb induced by swift heavy ion irradiation

Nano-porous structures form in GaSb after ion irradiation with 185 MeV Au ions. The porous layer formation is governed by the dominant electronic energy loss at this energy regime. The porous layer morphology differs significantly from that previously reported for low-energy, ion-irradiated GaSb. Prior to the onset of porosity, positron annihilation lifetime spectroscopy indicates the formation of small vacancy clusters in single ion impacts, while transmission electron microscopy reveals fragmentation of the GaSb into nanocrystallites embedded in an amorphous matrix. Following this fragmentation process, macroscopic porosity forms, presumably within the amorphous phase.The authors thank the Australian Research Council for support and the staff at the ANU Heavy Ion Accelerator Facility for their continued technical assistance. R.C.E. acknowledges the support from the Office of Basic Energy Sciences of the U.S. DOE (Grant No. DE-FG02-97ER45656)

Interactions of asbestos-activated macrophages with an experimental fibrosarcoma

Supernatants from in vivo asbestos-activated macrophages failed to show any cytostatic activity against a syngeneic fibrosarcoma cell line in vitro. UICC chrysotile-induced peritoneal exudate cells also failed to demonstrate any growth inhibitory effect on the same cells in Winn assays of tumor growth. Mixing UICC crocidolite with inoculated tumor cells resulted in a dose-dependent inhibition of tumor growth; this could, however, be explained by a direct cytostatic effect on the tumor cells of high doses of crocidolite, which was observed in vitro

Direct regional microvascular monitoring and assessment of blood brain barrier function following cerebral ischemia-reperfusion injury

Evans Blue (EB) is often used to evaluate Blood-Brain Barrier Damage (BBB) in cerebral ischemia, frequently by dye extraction. Herein we present a method that allows assessing regional brain microvasculature, distribution of EB and Fluorescent Isothiocyanate-Labeled Red Blood Cells (FITC-RBCs) in a rat model of acute cerebral Ischemia-Reperfusion (I-R). Wistar rats were subjected to 3 h of middle cerebral artery occlusion and then reperfused. At ~2.5 h of reperfusion, BBB opening was assessed by contrast enhanced magnetic resonance imaging. It was followed by injections of EB and FITC-RBCs that circulated for either 5 or 20 min. Regional microvasculature and tracer distributions were assessed by laser scanning confocal microscopy. Microvascular networks in stroke-affected regions networks were partially damaged with apparent EB extravasation. Brain regions were affected in the following order: preoptic area (PoA)\u3estriatum (Str)\u3ecortex (Ctx). EB leakage increased with circulation time in Str. Cells around the leakage sites sequestered EB. An inverse correlation was observed between low CBF rates recorded during MCA occlusion and post-reperfusion EB extravasation patterns. Accordingly, this approach provided data on brain regional microvascular status, extravascular tracer distribution and its cellular uptake. It may be useful to evaluate model-dependent variations in vascular injury and efficacy of putative vascular protective drugs in stroke

Measurement of rat brain tumor kinetics using an intravascular MR contrast agent and DCE‐MRI nested model selection

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109323/1/jmri24469.pd

Combination of vatalanib and a 20-HETE synthesis inhibitor results in decreased tumor growth in an animal model of human glioma

BACKGROUND: Due to the hypervascular nature of glioblastoma (GBM), antiangiogenic treatments, such as vatalanib, have been added as an adjuvant to control angiogenesis and tumor growth. However, evidence of progressive tumor growth and resistance to antiangiogenic treatment has been observed. To counter the unwanted effect of vatalanib on GBM growth, we have added a new agent known as N-hydroxy-N\u27-(4-butyl-2 methylphenyl)formamidine (HET0016), which is a selective inhibitor of 20-hydroxyeicosatetraenoic acid (20-HETE) synthesis. The aims of the studies were to determine 1) whether the addition of HET0016 can attenuate the unwanted effect of vatalanib on tumor growth and 2) whether the treatment schedule would have a crucial impact on controlling GBM. METHODS: U251 human glioma cells (4×10(5)) were implanted orthotopically. Two different treatment schedules were investigated. Treatment starting on day 8 (8-21 days treatment) of the tumor implantation was to mimic treatment following detection of tumor, where tumor would have hypoxic microenvironment and well-developed neovascularization. Drug treatment starting on the same day of tumor implantation (0-21 days treatment) was to mimic cases following radiation therapy or surgery. There were four different treatment groups: vehicle, vatalanib (oral treatment 50 mg/kg/d), HET0016 (intraperitoneal treatment 10 mg/kg/d), and combined (vatalanib and HET0016). Following scheduled treatments, all animals underwent magnetic resonance imaging on day 22, followed by euthanasia. Brain specimens were equally divided for immunohistochemistry and protein array analysis. RESULTS: Our results demonstrated a trend that HET0016, alone or in combination with vatalanib, is capable of controlling the tumor growth compared with that of vatalanib alone, indicating attenuation of the unwanted effect of vatalanib. When both vatalanib and HET0016 were administered together on the day of the tumor implantation (0-21 days treatment), tumor volume, tumor blood volume, permeability, extravascular and extracellular space volume, tumor cell proliferation, and cell migration were decreased compared with that of the vehicle-treated group. CONCLUSION: HET0016 is capable of controlling tumor growth and migration, but these effects are dependent on the timing of drug administration. The addition of HET0016 to vatalanib may attenuate the unwanted effect of vatalanib

An Unsupervised Autoencoder Developed from Dynamic Contrast-Enhanced (DCE)-MRI Datasets for Classification of Acute Tumor Response in an Animal Model

Purpose/Objective(s): Recent studies have shown that vascular parameters of brain tumors derived from DCE-MRI may act as potential biomarkers for radiation-induced acute effects. However, accurate characterization of the spatial regions affected by radiation therapy (RT) remains challenging. Here, we introduce an unsupervised adaptive model for classification and ranking of the RT-affected regions in an animal model of cerebral U-251n tumors. Materials/Methods: Twenty-three immune-compromised-RNU rats were implanted with human U251n cancer cells to form an orthotopic glioma (IACUC #1509). For each rat, 28 days after implantation, two DCE-MRI studies (Dual Gradient Echo, DGE, FOV: 32 × 32 mm2, TR/(TE1-TE2) = 24 ms/(2 ms-4 ms), flip angle = 18°, 400 acquisitions, 1.55 sec interval with Magnevist contrast agent, CA injection at ∼ 24 sec) were performed 24h apart using a 7T MRI scanner. A single 20 Gy stereotactic radiation exposure was performed before the second MRI, which was acquired 1-6.5 hrs after RT. DCE-MRI analysis was done using a model selection technique to distinguish three different brain regions as follows: Normal vasculature (Model 1: No leakage, only plasma volume, vp, is estimated), leaky tumor tissues with no back-flux to the vasculature (Model 2: vp and forward volumetric transfer constant, Ktrans, are estimated), and leaky tumor tissues with back-flux (Model 3: vp, Ktrans, and interstitial volume fraction, ve, are estimated). Normalized time traces of DCE-MRI information (24 pre, and 24 post-RT for each rat, total of 64108 training datasets) of tumors and their soft surrounding normal tissues were extracted from the 3 different model regions. To eliminate high-dimensional data similarity, an unsupervised autoencoder (AE) was trained to map out the model-derived data into a feature space (latent variables, N=10). For each model, the pre and post RT latent variables were compared (by appropriate tests of significance: ANOVA/Welch, CI=95%) to reveal RT-discriminant features. Pearson correlation coefficients were used to compare the decoded data to rank the effect of RT on different models. Results: The time trace of DCE-MRI information of rat brain in normal (Model 1, non-leaky) and highly permeable (Model 3) regions are less impacted by RT (Higher correlation between pre and post RT: r= 0.8518, p\u3c0.0001 and r= 0.9040, p\u3c0.0001 for Model 1 and Model 3, respectively) compared to the peritumoral regions pertaining to Model 2 (r= 0.8077, p\u3c0.0001). Conclusion: This pilot study suggests that among different brain regions, peritumoral zones (infiltrative tumor borders with enhanced rim) are highly affected by RT. Spatial assessment of RT-affected brain regions can play a key role in optimization of treatment planning in cancer patients, but presents a challenging task in conventional DCE-MRI. This study represents an important step toward classification and ranking the RT-affected brain spatial regions according to their vascular response following hypofractionated RT

Model selection for DCE‐T1 studies in glioblastoma

Dynamic contrast enhanced T 1 ‐weighted MRI using the contrast agent gadopentetate dimeglumine (Gd‐DTPA) was performed on 10 patients with glioblastoma. Nested models with as many as three parameters were used to estimate plasma volume or plasma volume and forward vascular transfer constant ( K trans ) and the reverse vascular transfer constant ( k ep ). These constituted models 1, 2, and 3, respectively. Model 1 predominated in normal nonleaky brain tissue, showing little or no leakage of contrast agent. Model 3 predominated in regions associated with aggressive portions of the tumor, and model 2 bordered model 3 regions, showing leakage at reduced rates. In the patient sample, v p was about four times that of white matter in the enhancing part of the tumor. K trans varied by a factor of 10 between the model 2 (1.9 ↔ 10 −3 min −1 ) and model 3 regions (1.9 ↔ 10 −2 min −1 ). The mean calculated interstitial space (model 3) was 5.5%. In model 3 regions, excellent curve fits were obtained to summarize concentration‐time data (mean R 2 = 0.99). We conclude that the three parameters of the standard model are sufficient to fit dynamic contrast enhanced T 1 data in glioblastoma under the conditions of the experiment. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91323/1/23211_ftp.pd

Semantic network analysis of vaccine sentiment in online social media.

OBJECTIVE: To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. BACKGROUND: Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. METHODS: We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. RESULTS: The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. CONCLUSION: Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States

Decay constants and mixing parameters in a relativistic model for q\barQ system

We extend our recent work, in which the Dirac equation with a ``(asymptotically free) Coulomb + (Lorentz scalar $\gamma_0\sigma r$) linear '' potential is used to obtain the light quark wavefunction for $q\bar Q$ mesons in the limit $m_Q\to \infty$, to estimate the decay constant $f_P$ and the mixing parameter $B$ of the pseudoscalar mesons. We compare our results for the evolution of $f_P$ and $B$ with the meson mass $M_P$ to the non-relativistic formulas for these quantities and show that there is a significant correction in the subasymptotic region. For $\sigma =0.14{{\rm ~GeV}}^{-2}$ and \lms =0.240{\rm ~GeV} we obtain: $f_D =0.371\; ,\; f_{D_s}=0.442\; ,\; f_B=0.301\; ,\; f_{B_s}=0.368 {\rm ~GeV}$ and $B_D=0.88\; ,\; B_{D_s}=0.89\; ,\; B_B=0.95\; ,\; B_{B_s}=0.96\; ,\;$ and $B_K=0.60$.Comment: 13 pages, Latex, 3 figures (included