Due to the depletion of fossil fuels and their environmental issues, it is necessary to find energy resources which are renewable. Algal biomass becomes promising feedstock for bio-fuel production. ...They are considered as sustainable, renewable and effective biomass and bio-fuels obtained from them are more environment-friendly than fossil fuels. The aim of this work is to provide a state of the art review on pyrolysis of microalgae for generation of bio-fuels. Initially, some general aspects of biomass such as microalgae characteristics, different thermochemical processes and advantages of microalgae pyrolysis to produce bio-fuels are discussed. Then, different pyrolysis methods are explained and parameters affecting the process are addressed. Bio-fuels including gaseous, solid and liquid products have been characterized in a separate section. Finally, the technical challenges associated with microalgal pyrolysis commercialization are discussed in the last section of this article.
•Thermal behavior of co-pyrolysis of microalgae, wood and polymer was investigated.•Mixture of microalgae, wood and polymer decomposes at two stages.•Addition of polymer decreases peak temperature of ...wood and microalgae.•Co-pyrolysis of microalgae, wood and polymer shows a synergistic effect.
Thermal decomposition behavior and kinetics of microalgae Chlorella vulgaris, wood and polypropylene were investigated using thermogravimetric analysis (TGA). Experiments were carried out at heating rates of 10, 20 and 40°C/min from ambient temperature to 600°C. The results show that pyrolysis process of C. vulgaris and wood can be divided into three stages while pyrolysis of polypropylene occurs almost totally in one step. It is shown that wood can delay the pyrolysis of microalgae while microalgae can accelerate the pyrolysis of wood. The existence of polymer during the pyrolysis of microalgae or wood will lead to two divided groups of peaks in DTG curve of mixtures. The results showed that interaction is inhibitive rather than synergistic during the decomposition process of materials. Kinetics of process is studied by the Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO). The average E values obtained from FWO and KAS methods were 131.228 and 142.678kJ/mol, respectively.
Cancer stem cells are critical for cancer initiation, development, and treatment resistance. Our understanding of these processes, and how they relate to glioblastoma heterogeneity, is limited. To ...overcome these limitations, we performed single-cell RNA sequencing on 53586 adult glioblastoma cells and 22637 normal human fetal brain cells, and compared the lineage hierarchy of the developing human brain to the transcriptome of cancer cells. We find a conserved neural tri-lineage cancer hierarchy centered around glial progenitor-like cells. We also find that this progenitor population contains the majority of the cancer's cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.
Abstract
Background
While methylation of CpG dinucleotides is traditionally considered antagonistic to the DNA-binding activity of most transcription factors (TFs), recent in vitro studies have ...revealed a more complex picture, suggesting that over a third of TFs may preferentially bind to methylated sequences. Expanding these in vitro observations to in vivo TF binding preferences is challenging since the effect of methylation of individual CpG sites cannot be easily isolated from the confounding effects of DNA accessibility and regional DNA methylation. Thus, in vivo methylation preferences of most TFs remain uncharacterized.
Results
We introduce joint accessibility-methylation-sequence (JAMS) models, which connect the strength of the binding signal observed in ChIP-seq to the DNA accessibility of the binding site, regional methylation level, DNA sequence, and base-resolution cytosine methylation. We show that JAMS models quantitatively explain TF occupancy, recapitulate cell type-specific TF binding, and have high positive predictive value for identification of TFs affected by intra-motif methylation. Analysis of 2209 ChIP-seq experiments results in high-confidence JAMS models for 260 TFs, revealing a negative association between in vivo TF occupancy and intra-motif methylation for 45% of studied TFs, as well as 16 TFs that are predicted to bind to methylated sites, including 11 novel methyl-binding TFs mostly from the multi-zinc finger family.
Conclusions
Our study substantially expands the repertoire of in vivo methyl-binding TFs, but also suggests that most TFs that prefer methylated CpGs in vitro present themselves as methylation agnostic in vivo, potentially due to the balancing effect of competition with other methyl-binding proteins.
•A model is presented describing dynamic temperature variation in a solar receiver.•Validation of the model was done for receiver radiated by two different heat sources.•A nonlinear adaptive ...controller was designed based on the developed model.•The controller adjusts the aperture size to regulate temperature of the system.•Performance of the controller was confirmed in simulations for sunny and cloudy days.
One of the main challenges of solar thermal technology is the intermittency of solar radiation which adversely affect temperature stability of the solar receiver. A promising technique to tackle this problem is the use of a variable aperture mechanism to regulate the light entry into solar receiver. Efficiency analysis confirms the advantage of this control technique over shutter adjustment method, which is also based on regulation of solar radiation entry. In order to regulate the temperature in a closed loop circuit based on aperture size adjustment, a model based control strategy was developed. To show the robustness and comprehensiveness of this control strategy, it was applied to a cavity receiver heated by two different radiative heat sources demonstrating the applicability of this control strategy consistently in most commonly practiced solar thermal systems. The first heat source studied is a solar furnace housing a parabolic dish, whereas the second one is a high flux solar simulator. For each radiative heat source, flux entering the receiver was determined using Monte Carlo ray tracing (MCRT) method. MCRT model was then coupled with energy balance equations to derive numerical model describing dynamic temperature variation in solar receiver. Comparison of simulated and experimentally measured temperatures showed appreciable accuracy of the dynamic model. Simulation results of the numerical model were then used to identify a nonlinear adaptive model for use in designing a model predictive controller (MPC). Parameters of the adaptive model were updated continuously to make the controller more robust against model mismatches and external disturbances. Simulation results for both radiative heat sources showed that the proposed controller yields faster response with less overshoot compare to proportional integral derivative (PID) controller. Results showed that this controller exhibits robust performance during sunrise and sunset times as well as passing clouds conditions where significant fluctuations in solar radiation is experienced.
Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only ∼1% of eukaryotic TFs. Broadly sampling DNA-binding domain (DBD) types from ...multiple eukaryotic clades, we determined DNA sequence preferences for >1,000 TFs encompassing 54 different DBD classes from 131 diverse eukaryotes. We find that closely related DBDs almost always have very similar DNA sequence preferences, enabling inference of motifs for ∼34% of the ∼170,000 known or predicted eukaryotic TFs. Sequences matching both measured and inferred motifs are enriched in chromatin immunoprecipitation sequencing (ChIP-seq) peaks and upstream of transcription start sites in diverse eukaryotic lineages. SNPs defining expression quantitative trait loci in Arabidopsis promoters are also enriched for predicted TF binding sites. Importantly, our motif "library" can be used to identify specific TFs whose binding may be altered by human disease risk alleles. These data present a powerful resource for mapping transcriptional networks across eukaryotes.
The abundance of mRNA is mainly determined by the rates of RNA transcription and decay. Here, we present a method for unbiased estimation of differential mRNA decay rate from RNA-sequencing data by ...modeling the kinetics of mRNA metabolism. We show that in all primary human tissues tested, and particularly in the central nervous system, many pathways are regulated at the mRNA stability level. We present a parsimonious regulatory model consisting of two RNA-binding proteins and four microRNAs that modulate the mRNA stability landscape of the brain, which suggests a new link between RBFOX proteins and Alzheimer's disease. We show that downregulation of RBFOX1 leads to destabilization of mRNAs encoding for synaptic transmission proteins, which may contribute to the loss of synaptic function in Alzheimer's disease. RBFOX1 downregulation is more likely to occur in older and female individuals, consistent with the association of Alzheimer's disease with age and gender."mRNA abundance is determined by the rates of transcription and decay. Here, the authors propose a method for estimating the rate of differential mRNA decay from RNA-seq data and model mRNA stability in the brain, suggesting a link between mRNA stability and Alzheimer's disease."
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•A two-stage process was applied to enhance lipid production in microalgae.•In stage I the highest cell growth was achieved by using sodium bicarbonate.•Sodium acetate resulted in ...highest lipid and fatty acid content during stage II.•The highest lipid productivity belonged to sodium acetate in whole process.•Molasses can be a suitable carbon source for lipid production in microalgae.
In this research, a two-stage process consisting of cultivation in nutrient rich and nitrogen starvation conditions was employed to enhance lipid production in Chlorella vulgaris algal biomass. The effect of supplying different organic and inorganic carbon sources on cultivation behavior was investigated. During nutrient sufficient condition (stage I), the highest biomass productivity of 0.158±0.011g/L/d was achieved by using sodium bicarbonate followed by 0.130±0.013, 0.111±0.005 and 0.098±0.003g/L/d for sodium acetate, carbon dioxide and molasses, respectively. Cultivation under nitrogen starvation process (stage II) indicated that the lipid and fatty acid content increased continuously to a maximum value at day 2. Using carbon dioxide resulted in highest cell density, while using sodium acetate led to the highest fatty acid content. Molasses was not as effective as other carbon sources, but by taking into account its lower price, it can be considered as a suitable carbon source for algal lipid productivity.
Harnessing solar energy for thermochemical processing is an exciting and fast emerging research area with significant potential for reducing CO2 emissions. However, maintenance of a uniform ...temperature distribution as well as avoidance of hot spots in solar cavity receivers are challenges of present technology which are adversely affecting the process efficiency. This study presents a model based methodology as a design tool for iterative creation of optimum solar receiver geometry. Several discrete solutions are demonstrated as case studies via experimental testing of a solar receiver radiated by a 7 kW solar simulator. Experimental observations are compared with the results of the numerical analysis based on two-dimensional (2D) numerical model that couples the fluid flow and heat transfer mechanisms in the solar receiver. A Monte-Carlo ray tracing method was used to model the incoming radiation from the solar simulator and radiative exchange between the inner surfaces of the cavity receiver. Comparison of the simulation results to experimentally measured steady state temperatures at different points of the solar receiver shows 6.68% average absolute error confirming appreciable accuracy of the model. The results also show that reversing the gas flow direction and increasing the insulation layer do not improve the temperature distribution in the receiver. However, reducing the front flange dimensions and decreasing the inner receiver radius do enhance the temperature distribution and increase the average receiver temperature. Numerical results show that these changes can increase the average temperature of the inner cavity cylinder walls by 27%, and increase the temperature uniformity index by 58%. These findings provide essential insight for solar reactor design to reduce hot spot problems and improve temperature uniformity.
•Adverse effects of non-unifrom heat flux on solar thermal systems been addressed.•Discrete solutions via experimental testing of a solar receiver presented.•2D numerical model coupling the fluid flow and heat transfer mechanism demonstrated.•Hot spot formation addressed by improving temperature distribution via new design.•27% increase in temperature, 58% increase in temperature uniformity index achieved.
Identifying causal variants from genome-wide association studies (GWAS) is challenging due to widespread linkage disequilibrium (LD) and the possible existence of multiple causal variants in the same ...genomic locus. Functional annotations of the genome may help to prioritize variants that are biologically relevant and thus improve fine-mapping of GWAS results. Classical fine-mapping methods conducting an exhaustive search of variant-level causal configurations have a high computational cost, especially when the underlying genetic architecture and LD patterns are complex. SuSiE provided an iterative Bayesian stepwise selection algorithm for efficient fine-mapping. In this work, we build connections between SuSiE and a paired mean field variational inference algorithm through the implementation of a sparse projection, and propose effective strategies for estimating hyperparameters and summarizing posterior probabilities. Moreover, we incorporate functional annotations into fine-mapping by jointly estimating enrichment weights to derive functionally-informed priors. We evaluate the performance of SparsePro through extensive simulations using resources from the UK Biobank. Compared to state-of-the-art methods, SparsePro achieved improved power for fine-mapping with reduced computation time. We demonstrate the utility of SparsePro through fine-mapping of five functional biomarkers of clinically relevant phenotypes. In summary, we have developed an efficient fine-mapping method for integrating summary statistics and functional annotations. Our method can have wide utility in understanding the genetics of complex traits and increasing the yield of functional follow-up studies of GWAS. SparsePro software is available on GitHub at https://github.com/zhwm/SparsePro.
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