Air Toxic Emissions Distribution and Performance Analysis of the CMAQ Air Toxic Model - A Case Study of Houston Area, Texas

Air quality models have been used in the past to predict the ambient air toxic concentration but CMAQ air toxics model, used in this thesis, is the first air quality model, which accounts the toxic chemical reactions in the ambient atmosphere. The main objective of this thesis was to analyze the distribution of air toxics emission in the Houston region, Texas using an emission processing tool and to determine the performance of the advanced air toxics model (CMAQ) used. Each year large amount of air toxics are emitted in the state of Texas, particularly in the Houston region. A study on the hourly distribution of major toxics species emitted in the region would help the emission reduction policy makers to focus on the counties and areas within the counties which emit large amount of toxics in the region. The Texas toxic inventory and the national emissions were processed using an EPA developed emission processing tool and the output from the tool was used to analyze the distribution of toxic emissions in the region. The latest air toxic model developed by the EPA is exclusively developed for air toxic species. The model has a detailed mechanism for chemical speciation in the atmosphere and has the ability to process most of major air toxic species. The output from the processing tool was also used to study the performance of this latest third generation air toxics model. The model was used to predict the concentration of major air toxics species for the year 2000 and the predicted concentration was compared with the monitored values in the region. A detailed analysis on the performance of the model was made and a conclusion on the effectiveness of the model was drawn

Modular architecture in biological networks

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007.Includes bibliographical references (p. 201-207).In the past decade, biology has been revolutionized by an explosion in the availability of data. Translating this new wealth of information into meaningful biological insights and clinical breakthroughs will require a complete overhaul both in the questions being asked, and the methodologies used to answer them. One of the largest challenges in organizing and understanding the data coming from genome sequencing, microarray experiments, and other high-throughput measurements, will be the ability to find large-scale structure in biological systems. Ideally, this would lead to a simplified representation, wherein the thousands of genes in an organism can be viewed as a much smaller number of dynamic modules working in concert to accomplish cellular functions. Toward demonstrating the importance of higher-level, modular structure in biological systems, we have performed the following analyses: 1. Using computational techniques and pre-existing protein-protein interaction (PPI) data, we have developed general tools to find and validate modular structure. We have applied these approaches to the PPI networks of yeast, fly, worm, and human.(cont.) 2. Utilizing a modular scaffold, we have generated predictions that attempt to explain existing system-wide experiments as well as predict the function of otherwise uncharacterized proteins. 3. Following the example of comparative genomics, we have aligned biological networks at the modular level to elucidate principles of how modules evolve. We show that conserved modular structure can further aid in functional annotation across the proteome. In addition to the detection and use of modular structure for computational analyses, experimental techniques must be adapted to support top-down strategies, and the targeting of entire modules with combinations of small-molecules. With this in mind, we have designed experimental strategies to find sets of small-molecules capable of perturbing fimctional modules through a variety of distinct, but related, mechanisms. As a first test, we have looked for classes of small-molecules targeting growth signaling through the phosphatidyl-inositol-3-kinase (PI3K) pathway. This provides a platform for developing new screening techniques in the setting of biology relevant to diabetes and cancer. In combination, these investigations provide an extensible computational approach to finding and utilizing modular structure in biological networks, and experimental approaches to bring them toward clinical endpoints.by Gopal Ramachandran.Ph.D

Effect of Non-Coding RNA on Post-Transcriptional Gene Silencing of Alzheimer Disease

A large amount of hidden biological information is contained in the human genome, which is not expressed or revealed in the form of proteins; the usual end product form of gene expression. Instead, most of such information is in the form of non-coding RNAs (ncRNAs). ncRNAs correspond to genes that are transcribed, but do not get translated into proteins. This part of the genome was, till recently, considered as ‘junk’. The term ‘junk’ implied lack of any discernible function of these RNA. More than 98% of the human genomic size encompasses these non-coding RNAs. But, recent research has evidently brought out the indispensible contribution of non-coding RNA in controlling and regulating gene expression. ncRNA such as siRNAs and microRNAs have been reported to greatly help in causing post-transcriptional gene silencing (PTGS) in cells through RNA interference (RNAi) pathway. In this work, we have investigated the possibility of using siRNAs and microRNAs to aid in gene silencing of early onset Alzheimer’s disease genes. 
Alzheimer’s disease specific mutations and their corresponding positions in mRNA have been identified for six genes; Presenilin-1, Presenilin-2, APP (amyloid beta precursor protein), APBB3, BACE-1 and PSENEN. 

Small interfering RNAs (siRNAs) that can cause PTGS through RNA interference pathway have been designed. RNA analysis has been done to verify complementarity of antisense siRNA sequence with target mRNA sequence. Interaction studies have been done computationally between these antisense siRNA strands and seven Argonaute proteins. From the interaction studies, only one of the seven Argonaute proteins; 1Q8K, was found to have interaction with the siRNAs indicating the importance and uniqueness of this particular protein in RISC (RNA induced silencing complex). 

The interaction studies have been carried out for the microRNAs also. Out of the 700 mature human microRNAs collected, 394 microRNAs have been identified to show partial complementarity with their target sequence on PSEN-1 mRNA. Of these 394, five microRNAs have shown partial complementarity to early onset Alzheimer’s disease specific mutations in PSEN-1 mRNA. Interaction studies have been done between these microRNAs and Argonaute proteins. Thus, design, characterization and analysis of ncRNAs that contribute to post transcriptional gene silencing of Alzheimer’s disease have been achieved.
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Imaging in turbid media using quasi-ballistic photons

We study by means of experiments and Monte Carlo simulations, the scattering of light in random media, to determine the distance upto which photons travel along almost undeviated paths within a scattering medium, and are therefore capable of casting a shadow of an opaque inclusion embedded within the medium. Such photons are isolated by polarisation discrimination wherein the plane of linear polarisation of the input light is continuously rotated and the polarisation preserving component of the emerging light is extracted by means of a Fourier transform. This technique is a software implementation of lock-in detection. We find that images may be recovered to a depth far in excess of what is predicted by the diffusion theory of photon propagation. To understand our experimental results, we perform Monte Carlo simulations to model the random walk behaviour of the multiply scattered photons. We present a new definition of a diffusing photon in terms of the memory of its initial direction of propagation, which we then quantify in terms of an angular correlation function. This redefinition yields the penetration depth of the polarisation preserving photons. Based on these results, we have formulated a model to understand shadow formation in a turbid medium, the predictions of which are in good agreement with our experimental results.Comment: LaTex 19 pages, 10 ps figures and 8 eps figures. psfig.sty included. (submitted to Optics Commumications

Glycerol conversion to 1, 3-Propanediol is enhanced by the expression of a heterologous alcohol dehydrogenase gene in Lactobacillus reuteri

In this work, Lactobacillus reuteri has been metabolically engineered for improving 1, 3-propanediol (1, 3-PD) production by the expression of an Escherichia coli alcohol dehydrogenase, yqhD, that is known to efficiently convert the precursor 3-hydroxypropionaldehyde (3-HPA) to 1, 3-PD. The engineered strain exhibited significantly altered formation rates for the product and other metabolites during the fermentation. An increase in the 1, 3-PD specific productivity of 34% and molar yield by 13% was achieved in the clone, relative to the native strain. A concomitant decrease in the levels of toxic intermediate, 3-HPA, was observed, with the specific productivity levels being 25% lesser than that of the native strain. Interestingly, the recombinant strain exhibited elevated rates of lactate and ethanol formation as well as reduced rate of acetate production, compared to the native strain. The preferential utilization of NADPH by YqhD with a possible decrease in the native 1, 3-PD oxidoreductase (NADH-dependent) activity, could have resulted in the diversion of surplus NADH towards increased lactate and ethanol productivities

Methylation mediated silencing of TMS1/ASC gene in prostate cancer

BACKGROUND: Transcriptional silencing associated with aberrant promoter methylation has been established as an alternate pathway for the development of cancer by inactivating tumor suppressor genes. TMS1 (Target of Methylation induced Silencing), also known as ASC (Apoptosis Speck like protein containing a CARD) is a tumor suppressor gene which encodes for a CARD (caspase recruitment domain) containing regulatory protein and has been shown to promote apoptosis directly and by activation of downstream caspases. This study describes the methylation induced silencing of TMS1/ASC gene in prostate cancer cell lines. We also examined the prevalence of TMS1/ASC gene methylation in prostate cancer tissue samples in an effort to correlate race and clinico-pathological features with TMS1/ASC gene methylation. RESULTS: Loss of TMS1/ASC gene expression associated with complete methylation of the promoter region was observed in LNCaP cells. Gene expression was restored by a demethylating agent, 5-aza-2'deoxycytidine, but not by a histone deacetylase inhibitor, Trichostatin A. Chromatin Immunoprecipitation (ChIP) assay showed enrichment of MBD3 (methyl binding domain protein 3) to a higher degree than commonly associated MBDs and MeCP2. We evaluated the methylation pattern in 66 prostate cancer and 34 benign prostatic hyperplasia tissue samples. TMS1/ASC gene methylation was more prevalent in prostate cancer cases than controls in White patients (OR 7.6, p 0.002) while no difference between the cases and controls was seen in Black patients (OR 1.1, p 0.91). CONCLUSION: Our study demonstrates that methylation-mediated silencing of TMS1/ASC is a frequent event in prostate cancer, thus identifying a new potential diagnostic and prognostic marker for the treatment of the disease. Racial differences in TMS1/ASC methylation patterns implicate the probable role of molecular markers in determining in susceptibility to prostate cancer in different ethnic groups

Revealing Complex Traits with Small Molecules and Naturally Recombinant Yeast Strains

SummaryHere we demonstrate that natural variants of the yeast Saccharomyces cerevisiae are a model system for the systematic study of complex traits, specifically the response to small molecules. As a complement to artificial knockout collections of S. cerevisiae widely used to study individual gene function, we used 314- and 1932-member libraries of mutant strains generated by meiotic recombination to study the cumulative, quantitative effects of natural mutations on phenotypes induced by 23 small-molecule perturbagens (SMPs). This approach reveals synthetic lethality between SMPs, and genetic mapping studies confirm the involvement of multiple quantitative trait loci in the response to two SMPs that affect respiratory processes. The systematic combination of natural variants of yeast and small molecules that modulate evolutionarily conserved cellular processes can enable a better understanding of the general features of complex traits

Applications of Circular Dichroism for Structural Analysis of Gelatin and Antimicrobial Peptides

Circular dichroism (CD) is a useful technique for monitoring changes in the conformation of antimicrobial peptides or gelatin. In this study, interactions between cationic peptides and gelatin were observed without affecting the triple helical content of the gelatin, which was more strongly affected by anionic surfactant. The peptides did not adopt a secondary structure in the presence of aqueous solution or Tween 80, but a peptide secondary structure formed upon the addition of sodium dodecyl sulfate (SDS). The peptides bound to the phosphate group of lipopolysaccharide (LPS) and displayed an alpha-helical conformation while (KW)4 adopted a folded conformation. Further, the peptides did not specifically interact with the fungal cell wall components of mannan or laminarin. Tryptophan blue shift assay indicated that these peptides interacted with SDS, LPS, and gelatin but not with Tween 80, mannan, or laminarin. The peptides also displayed antibacterial activity against P. aeruginosa without cytotoxicity against HaCaT cells at MIC, except for HPA3NT3-analog peptide. In this study, we used a CD spectroscopic method to demonstrate the feasibility of peptide characterization in numerous environments. The CD method can thus be used as a screening method of gelatin-peptide interactions for use in wound healing applications

Bioinformatics in crosslinking chemistry of collagen with selective cross linkers

<p>Abstract</p> <p>Background</p> <p>Identifying the molecular interactions using bioinformatics tools before venturing into wet lab studies saves the energy and time considerably. The present study summarizes, molecular interactions and binding energy calculations made for major structural protein, collagen of Type I and Type III with the chosen cross-linkers, namely, coenzyme Q₁₀, dopaquinone, embelin, embelin complex-1 & 2, idebenone, 5-O-methyl embelin, potassium embelate and vilangin.</p> <p>Results</p> <p>Molecular descriptive analyses suggest, dopaquinone, embelin, idebenone, 5-O-methyl embelin, and potassium embelate display nil violations. And results of docking analyses revealed, best affinity for Type I (- 4.74 kcal/mol) and type III (-4.94 kcal/mol) collagen was with dopaquinone.</p> <p>Conclusions</p> <p>Among the selected cross-linkers, dopaquinone, embelin, potassium embelate and 5-O-methyl embelin were the suitable cross-linkers for both Type I and Type III collagen and stabilizes the collagen at the expected level.</p

CMFRI Marine Fisheries Policy Series No.18; Streamlining the Supply Chain of Marine Fish in Kerala: COVID-19 and Beyond

Streamlining the Supply Chain of Marine Fish in Kerala: COVID-19 and Beyon