Integration of microalgae-based bioenergy production into a petrochemical complex: Techno-economic assessment

The rapid development of modern society has resulted in an increased demand for energy, mainly from fossil fuels. The use of this source of energy has led to the accumulation of carbon dioxide (CO2) in the atmosphere. In this context, microalgae culturing may be an effective solution to reduce the CO2 concentration in the atmosphere, since these microorganisms can capture CO2 and, simultaneously, produce bioenergy. This work consists of a techno-economic assessment of a microalgal production facility integrated in a petrochemical complex, in which established infrastructure allows efficient material and energy transport. Seven different scenarios were considered regarding photosynthetic, lipids extraction and anaerobic digestion efficiencies. This analysis has demonstrated six economically viable scenarios able to: (i) reduce CO2 emissions from a thermoelectric power plant; (ii) treat domestic wastewaters (which were used as culture medium); and (iii) produce lipids and electrical and thermal energy. For a 100-ha facility, considering a photosynthetic efficiency of 3%, a lipids extraction efficiency of 75% and an anaerobic digestion efficiency of 45% (scenario 3), an economically viable process was obtained (net present value of 22.6 million euros), being effective in both CO2 removal (accounting for 1.1 × 104 t per year) and energy production (annual energy produced was 1.6 × 107 kWh and annual lipids productivity was 1.9 × 103 m3). (c) 2016 by the authors

A Diagnostic Algorithm for Posterior Fossa Tumors in Children: A Validation Study

BACKGROUND AND PURPOSE: Primary posterior fossa tumors comprise a large group of neoplasias with variable aggressiveness and short and long-term outcomes. This study aimed to validate the clinical usefulness of a radiologic decision flow chart based on previously published neuroradiologic knowledge for the diagnosis of posterior fossa tumors in children. MATERIALS AND METHODS: A retrospective study was conducted (from January 2013 to October 2019) at 2 pediatric referral centers, Children's Hospital of Philadelphia, United States, and Great Ormond Street Hospital, United Kingdom. Inclusion criteria were younger than 18 years of age and histologically and molecularly confirmed posterior fossa tumors. Subjects with no available preoperative MR imaging and tumors located primarily in the brain stem were excluded. Imaging characteristics of the tumors were evaluated following a predesigned, step-by-step flow chart. Agreement between readers was tested with the Cohen κ, and each diagnosis was analyzed for accuracy. RESULTS: A total of 148 cases were included, with a median age of 3.4 years (interquartile range, 2.1-6.1 years), and a male/female ratio of 1.24. The predesigned flow chart facilitated identification of pilocytic astrocytoma, ependymoma, and medulloblastoma sonic hedgehog tumors with high sensitivity and specificity. On the basis of the results, the flow chart was adjusted so that it would also be able to better discriminate atypical teratoid/rhabdoid tumors and medulloblastoma groups 3 or 4 (sensitivity = 75%-79%; specificity = 92%-99%). Moreover, our adjusted flow chart was useful in ruling out ependymoma, pilocytic astrocytomas, and medulloblastoma sonic hedgehog tumors. CONCLUSIONS: The modified flow chart offers a structured tool to aid in the adjunct diagnosis of pediatric posterior fossa tumors. Our results also establish a useful starting point for prospective clinical studies and for the development of automated algorithms, which may provide precise and adequate diagnostic tools for these tumors in clinical practice

Coordinated modular functionality and prognostic potential of a heart failure biomarker-driven interaction network

<p>Abstract</p> <p>Background</p> <p>The identification of potentially relevant biomarkers and a deeper understanding of molecular mechanisms related to heart failure (HF) development can be enhanced by the implementation of biological network-based analyses. To support these efforts, here we report a global network of protein-protein interactions (PPIs) relevant to HF, which was characterized through integrative bioinformatic analyses of multiple sources of "omic" information.</p> <p>Results</p> <p>We found that the structural and functional architecture of this PPI network is highly modular. These network modules can be assigned to specialized processes, specific cellular regions and their functional roles tend to partially overlap. Our results suggest that HF biomarkers may be defined as key coordinators of intra- and inter-module communication. Putative biomarkers can, in general, be distinguished as "information traffic" mediators within this network. The top high traffic proteins are encoded by genes that are not highly differentially expressed across HF and non-HF patients. Nevertheless, we present evidence that the integration of expression patterns from high traffic genes may support accurate prediction of HF. We quantitatively demonstrate that intra- and inter-module functional activity may be controlled by a family of transcription factors known to be associated with the prevention of hypertrophy.</p> <p>Conclusion</p> <p>The systems-driven analysis reported here provides the basis for the identification of potentially novel biomarkers and understanding HF-related mechanisms in a more comprehensive and integrated way.</p