Gene structure in the sea urchin Strongylocentrotus purpuratus based on transcriptome analysis

A comprehensive transcriptome analysis has been performed on protein-coding RNAs of Strongylocentrotus purpuratus, including 10 different embryonic stages, six feeding larval and metamorphosed juvenile stages, and six adult tissues. In this study, we pooled the transcriptomes from all of these sources and focused on the insights they provide for gene structure in the genome of this recently sequenced model system. The genome had initially been annotated by use of computational gene model prediction algorithms. A large fraction of these predicted genes were recovered in the transcriptome when the reads were mapped to the genome and appropriately filtered and analyzed. However, in a manually curated subset, we discovered that more than half the computational gene model predictions were imperfect, containing errors such as missing exons, prediction of nonexistent exons, erroneous intron/exon boundaries, fusion of adjacent genes, and prediction of multiple genes from single genes. The transcriptome data have been used to provide a systematic upgrade of the gene model predictions throughout the genome, very greatly improving the research usability of the genomic sequence. We have constructed new public databases that incorporate information from the transcriptome analyses. The transcript-based gene model data were used to define average structural parameters for S. purpuratus protein-coding genes. In addition, we constructed a custom sea urchin gene ontology, and assigned about 7000 different annotated transcripts to 24 functional classes. Strong correlations became evident between given functional ontology classes and structural properties, including gene size, exon number, and exon and intron size

Post Aerobic Digestion (PAD) is a Solids Sidestream Nutrient Removal Process that Utilizes Native Carbon: Performance and Key Operational Parameters from Two Full-Scale PAD Reactors

Nutrient management is a critical issue for Water Resource Recovery Facilities, and sidestream treatment technologies to reduce nutrient loads often focus on liquid sidestreams and require external carbon sources. Post aerobic digestion (PAD), whereby an aerobic digester follows an anaerobic digester, treats a solids stream (i.e., anaerobic digester effluent) to reduce nitrogen loads. Volatile solids reduction occurs in this process with residual organic compounds serving as a native carbon source for denitrification. While this process has been evaluated at the lab-scale, information on operational parameters that affect full-scale performance is limited. We evaluated two separate full-scale PAD reactors to determine process performance and key operational parameters. During healthy operation, ammonia removal was greater than 90%, total inorganic nitrogen removal was greater than 80%, and volatile solids reduction was approximately 10%. Low SRT values of 7–10 days, pH ranges of 6.0–7.5, temperatures from 29–38 °C (85–100 °F), and negative ORP values resulted in good performance

Combining DI-ESI–MS and NMR datasets for metabolic profiling

Metabolomics datasets are commonly acquired by either mass spectrometry (MS) or nuclear magnetic resonance spectroscopy (NMR), despite their fundamental complementarity. In fact, combining MS and NMR datasets greatly improves the coverage of the metabolome and enhances the accuracy of metabolite identification, providing a detailed and high-throughput analysis of metabolic changes due to disease, drug treatment, or a variety of other environmental stimuli. Ideally, a single metabolomics sample would be simultaneously used for both MS and NMR analyses, minimizing the potential for variability between the two datasets. This necessitates the optimization of sample preparation, data collection and data handling protocols to effectively integrate direct-infusion MS data with one-dimensional (1D) 1H NMR spectra. To achieve this goal, we report for the first time the optimization of (i) metabolomics sample preparation for dual analysis by NMR and MS, (ii) high throughput, positive-ion direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) for the analysis of complex metabolite mixtures, and (iii) data handling protocols to simultaneously analyze DI-ESI-MS and 1D 1H NMR spectral data using multiblock bilinear factorizations, namely multiblock principal component analysis (MB-PCA) and multiblock partial least squares (MB-PLS). Finally, we demonstrate the combined use of backscaled loadings, accurate mass measurements and tandem MS experiments to identify metabolites significantly contributing to class separation in MB-PLS-DA scores. We show that integration of NMR and DI-ESI-MS datasets yields a substantial improvement in the analysis of neurotoxin involvement in dopaminergic cell death

Combining DI-ESI–MS and NMR datasets for metabolic profiling

Metabolomics datasets are commonly acquired by either mass spectrometry (MS) or nuclear magnetic resonance spectroscopy (NMR), despite their fundamental complementarity. In fact, combining MS and NMR datasets greatly improves the coverage of the metabolome and enhances the accuracy of metabolite identification, providing a detailed and high-throughput analysis of metabolic changes due to disease, drug treatment, or a variety of other environmental stimuli. Ideally, a single metabolomics sample would be simultaneously used for both MS and NMR analyses, minimizing the potential for variability between the two datasets. This necessitates the optimization of sample preparation, data collection and data handling protocols to effectively integrate direct-infusion MS data with one-dimensional (1D) 1H NMR spectra. To achieve this goal, we report for the first time the optimization of (i) metabolomics sample preparation for dual analysis by NMR and MS, (ii) high throughput, positive-ion direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) for the analysis of complex metabolite mixtures, and (iii) data handling protocols to simultaneously analyze DI-ESI-MS and 1D 1H NMR spectral data using multiblock bilinear factorizations, namely multiblock principal component analysis (MB-PCA) and multiblock partial least squares (MB-PLS). Finally, we demonstrate the combined use of backscaled loadings, accurate mass measurements and tandem MS experiments to identify metabolites significantly contributing to class separation in MB-PLS-DA scores. We show that integration of NMR and DI-ESI-MS datasets yields a substantial improvement in the analysis of neurotoxin involvement in dopaminergic cell death

Metabolic Investigations of the Molecular Mechanisms Associated with Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by fibrillar cytoplasmic aggregates of α-synuclein (i.e., Lewy bodies) and the associated loss of dopaminergic cells in the substantia nigra. Mutations in genes such as α-synuclein (SNCA) account for only 10% of PD occurrences. Exposure to environmental toxicants including pesticides and metals (e.g., paraquat (PQ) and manganese (Mn)) is also recognized as an important PD risk factor. Thus, aging, genetic alterations, and environmental factors all contribute to the etiology of PD. In fact, both genetic and environmental factors are thought to interact in the promotion of idiopathic PD, but the mechanisms involved are still unclear. In this study, we summarize our findings to date regarding the toxic synergistic effect between α-synuclein and paraquat treatment. We identified an essential role for central carbon (glucose) metabolism in dopaminergic cell death induced by paraquat treatment that is enhanced by the overexpression of α-synuclein. PQ "hijacks" the pentose phosphate pathway (PPP) to increase NADPH reducing equivalents and stimulate paraquat redox cycling, oxidative stress, and cell death. PQ also stimulated an increase in glucose uptake, the translocation of glucose transporters to the plasma membrane, and AMP-activated protein kinase (AMPK) activation. The overexpression of α-synuclein further stimulated an increase in glucose uptake and AMPK activity, but impaired glucose metabolism, likely directing additional carbon to the PPP to supply paraquat redox cycling

Increased Risk of Non-Q Wave Myocardial Infarction After Directional Atherectomy Is Platelet Dependent: Evidence From the EPIC Trial

AbstractObjectives. We sought to determine the effects of platelet glycoprotein IIb/IIIa receptor blockade on adverse outcomes, especially non-Q wave myocardial infarction, in patients undergoing directional atherectomy in the Evaluation of c7E3 for the Prevention of Ischemic Complications (EPIC) trial.Background. Randomized trials comparing directional atherectomy with percutaneous transluminal coronary angioplasty (PTCA) have demonstrated modest benefits favoring atherectomy but at a cost of increased acute ischemic complications, notably non-Q wave myocardial infarction. The mechanism for this excess risk is unknown.Methods. Of 2,038 high risk patients undergoing coronary intervention in the EPIC trial, directional atherectomy was performed in 197 (10%). Patients randomly received the chimeric glycoprotein IIb/IIIa antibody 7E3 (c7E3), as a bolus or a bolus and 12-h infusion or placebo. Study end points included death, myocardial infarction, repeat intervention or bypass surgery.Results. Patients undergoing directional atherectomy had a lower baseline risk for acute complications but had a higher incidence of any myocardial infarction (10.7% vs. 6.3%, p = 0.021) and non-Q wave myocardial infarction (9.6% vs. 4.9%, p = 0.006). Bolus and infusion of c7E3 reduced non-Q wave myocardial infarctions by 71% after atherectomy (15.4% for placebo vs. 4.5% for bolus and infusion, p = 0.046). Non-Q wave myocardial infarction rates after PTCA were not affected by c7E3, although Q wave myocardial infarctions were reduced from 2.6% to 0.8% (p = 0.017).Conclusions. The EPIC trial confirmed the increased risk of non-Q wave myocardial infarction with directional atherectomy use compared with PTCA. A bolus and 12-h infusion of the glycoprotein IIb/IIIa receptor inhibitor c7E3 abolished this excess risk. Directional atherectomy-related non-Q wave myocardial infarction appears to be platelet aggregation dependent

The Grizzly, May 1, 2003

Political Theorist Discusses Democracy and Terrorism • Ursinus Students Celebrate Spring with a Fling • Opinions: More Responses to Berliner\u27s Article; Greek Week a Blast! • New in Berman • Annual Student Exhibition 2003 Award Recipients • UC Women\u27s LAX Fall to Washington, Invest in Bulletproof Jackets • Dr. D Says Farewell with a Fantastic Finish • Men\u27s Tennis Looks to Rebound Next Season • UC Baseball Wins Eight Straight • Men\u27s Lax Records Two Wins • Women\u27s Golf Hurt by Weather, Injuries • Final Exam Schedulehttps://digitalcommons.ursinus.edu/grizzlynews/1537/thumbnail.jp

Mechanism of benefit of combination thrombolytic therapy for acute myocardial infarction: A quantitative angiographic and hematologic study

AbstractObjectives. The goal of this study was to lend insight into the mechanisms responsible for the beneficial effects of combination thrombolytic therapy.Background. Combination thrombolytic therapy for acute myocardial infarction bas been associated with less reocclusion and fewer in-hospital clinical events than has monotherapy.Methods. Infarct-related quantitative coronary dimensions and hemostatic protein levels were evaluated in 287 patients with acute myocardial infarction during the early (90-min) and convalescent (7-day) phases after administration of recombinant tissue-type plasminogen activator (rt-PA), urokinase or combination rt-PA and urokinase.Results. Minimal lumen diameter was similar in the 90-min and 7-day phases after treatment with rt-PA, urokinase and combination rt-PA and urokinase (0.72 ± 0.45 mm, 0.62 ± 0.53 mm and 0.75 ± 0.58 mm, respectively, at 90 min, p = 0.16; and 1.05 ± 0.56 mm, 1.12 ± 0.72 mm and 0.94 ± 0.54 mm, respectively, at 7 days, p = 0.22). In-hospital clinical event and reocclusion rates were less frequent in patients receiving combination therapy than in those receiving monotherapy (25% vs. 38% and 32% for rt-PA and urokinase, respectively, p = 0.084; and 3% vs. 13% and 9% for rt-PA and urokinase, respectively, p = 0.03), but these events were unrelated to early or late coronary dimensions. Patients receiving combination therapy or urokinase monotherapy had significantly higher peak fibrin degradation products (1,307 ± 860 and 1,285 ± 898 μg/ml vs. 435 ± 717 μg/ml, respectively, p < 0.0001) and lower nadir fibrinogen levels (0.85 ± 1.00 and 0.75 ± 0.53 g/liter vs. 1.90 ± 0.86 g/liter, respectively, p < 0.0001) than did those receiving rt-PA monotherapy. Peak fibrinogen degradation products indirectly correlated (p = 0.004) and baseline (p = 0.026) and nadir (p = 0.089) fibrinogen levels directly correlated with reocclusion.Conclusions. Lower in-hospital clinical event and reocclusion rates observed with combination thrombolytic therapy may relate to systemic hematologic factors rather than to the residual lumen obstruction after thrombolysis