Structural and functional characterization of extracellular domains of vascular endothelial growth factor receptor 1 and 2

Angiogenesis is the formation of new blood vessels from pre-existing vasculature and plays an essential role in normal organ development and in specific diseases in all higher organisms. Angiogenesis is therefore required already early in embryogenesis when the new blood and lymphatic systems develop. In adult organisms angiogenesis is required in numerous processes such as in vessel formation and remodeling in the female reproductive cycle, during wound healing, or in bone formation and remodeling. Aberrant excessive vessel formation, i.e. pathological angiogenesis, plays an important role in tumor progression, in diabetic retinopathy, rheumatoid arthritis or in psoriasis. The lack of angiogenesis leads to multiple vascular failure such as coronary artery disease. It is well established that the correct balance between pro- and anti-angiogenic growth factors, cytokines, and extracellular matrix components is essential for vascular homeostasis. One of the critical regulators of both physiological and pathological angiogenesis discovered more than 30 years ago is Vascular Endothelial Growth Factor (VEGF), regulating endothelial cell (EC) proliferation, migration, and survival but also vascular topology and permeability. VEGF is a family of cysteine linked dimeric growth factors consisting of five members, VEGF-A, -B, -C, -D and Placenta Growth Factor (PlGF). These soluble or matrix associated proteins bind to three type V receptor tyrosine kinases (RTKs), VEGF-receptor (VEGFR)-1 (also known as Flt1), VEGFR-2 (KDR/Flk1), and VEGFR-3 (Flt4). VEGFRs consist of an extracellular domain (ECD) built from seven immunoglobulin (Ig)-homology domains required for ligand binding and subsequent receptor dimerization. A single transmembrane (TM) helix connects the ECD to the cytoplasmic part containing a split tyrosine kinase domain. Ligand binding to VEGFR ectodomains promotes dimerization of receptor monomers, followed by receptor autophosphorylation and kinase activation. The activated receptor contains specific tyrosine residues in the kinase domain and the carboxy-terminal (C-terminal) domain acting as docking sites for a plethora of signaling proteins involved in multiple cellular signaling pathways. Ig-homology domains 1-3 (VEGFR-3) or 2-3 (VEGFR-1 or -2) of the ECD form the ligand binding site, while domains 4-7 are involved in homotypic receptor contacts fulfilling a regulatory function, which was the subject of this thesis. I used isothermal titration calorimetry (ITC) in this study to determine the thermodynamic properties of ligand binding and dimer formation. The data show that the free energy of VEGF-A binding to domains 1-3 or the full-length ECD of VEGFR-2 is entropy driven and enthalpically unfavourable. Most importantly, the Gibbs free energy of VEGF-A binding to the full length ECD is 1.12 kcal/mol higher compared to the binding energy of domains 1-3. The endothermic component arising from the homotypic receptor contacts in domains 4-7 thus reduces the overall binding affinity of the full-length VEGFR-2 ECD by about 10 fold. This suggests that the homotypic interactions in domain 4-7 play a regulatory role in ligand binding and receptor activation, e.g. by promoting conformational rearrangements of receptor monomers required for active dimer formation. This mechanism might also prevent spontaneous activation of VEGFR-2 in the absence of ligand. I also tried to crystallize the ECD of VEGFR-2 in complex with ligand. However, although I used a multitude of receptor ECD constructs, I did not obtain diffracting crystals. I therefore became involved in an accompanying project in the lab focusing on the crystal structure of the full-length VEGFR-1 ECD in complex with VEGF-A. This structure revealed distinct homotypic contacts in Ig-homology domains 5 and 7. To further characterize the contacts in domain 5 biochemically and to investigate their functional relevance in receptor activation I generated mutants disrupting specific hydrogen bonds and salt bridges involved in homotypic contact formation. The data showed a significant decrease in receptor phosphorylation activity upon stimulation with ligand. Similarly, I could show reduced receptor activity when the homologous residues were mutated in VEGFR-2. The biochemical characterization of these mutants thus document the regulatory role of domain 5 in VEGFR activation and identify domain 5 as a promising target for developing allosteric inhibitors of VEGFRs. The speciality of drugs proposed to target domain 5 lies in their ability to access the target receptor at a regulatory site in the extracellular receptor domain, which is easily accessible from the blood stream. In addition, the proposed drugs will be highly specific as compared with the currently used kinase inhibitors

A New PDAC (Parallel Encryption with Digit Arithmetic of Cover Text) Based Text Steganography Approach for Cloud Data Security

Internet Computing provides dynamic virtualization, resource pools, services and high availability servers. With rapid growth of internet computing technology, there is a high demand for data storage security on cloud. In this paper we are presenting a useful new approach of text based steganography for cloud data security. In our approach, simple addition, subtraction and multiplication of digits of ASCII code of each character of cover text is done and these new generated numeric values are used to encrypt ASCII values of our plain text. Since, in our approach, there are three basic airthmetic operations that are performed on every character of cover text, therefore, after airthmetic calculations each and every character will generate three numeric values such that, each and every numeric value will encrypt two ASCII values of plain text parallely. One from beginning of array of ASCII values of plain text and another one from ending of the very same array. In our approach, one character of cover text hides at most six characters of plain text. Thus memory allocation problem for cover text and execution time both are reduced. Using parallelism performance of our approach is enhanced. DOI: 10.17762/ijritcc2321-8169.15039

Deep Open Representative Learning for Image and Text Classification

Title from PDF of title page viewed November 5, 2020Dissertation advisor: Yugyung LeeVitaIncludes bibliographical references (pages 257-289)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020An essential goal of artificial intelligence is to support the knowledge discovery process from data to the knowledge that is useful in decision making. The challenges in the knowledge discovery process are typically due to the following reasons: First, the real-world data are typically noise, sparse, or derived from heterogeneous sources. Second, it is neither easy to build robust predictive models nor to validate them with such real-world data. Third, the `black-box' approach to deep learning models makes it hard to interpret what they produce. It is essential to bridge the gap between the models and their support in decisions with something potentially understandable and interpretable. To address the gap, we focus on designing critical representatives of the discovery process from data to the knowledge that can be used to perform reasoning. In this dissertation, a novel model named Class Representative Learning (CRL) is proposed, a class-based classifier designed with the following unique contributions in machine learning, specifically for image and text classification, i) The unique design of a latent feature vector, i.e., class representative, represents the abstract embedding space projects with the features extracted from a deep neural network learned from either images or text, ii) Parallel ZSL algorithms with class representative learning; iii) A novel projection-based inferencing method uses the vector space model to reconcile the dominant difference between the seen classes and unseen classes; iv) The relationships between CRs (Class Representatives) are represented as a CR Graph where a node represents a CR, and an edge represents the similarity between two CRs.Furthermore, we designed the CR-Graph model that aims to make the models explainable that is crucial for decision-making. Although this CR-Graph does not have full reasoning capability, it is equipped with the class representatives and their inter-dependent network formed through similar neighboring classes. Additionally, semantic information and external information are added to CR-Graph to make the decision more capable of dealing with real-world data. The automated semantic information's ability to the graph is illustrated with a case study of biomedical research through the ontology generation from text and ontology-to-ontology mapping.Introduction -- CRL: Class Representative Learning for Image Classification -- Class Representatives for Zero-shot Learning using Purely Visual Data -- MCDD: Multi-class Distribution Model for Large Scale Classification -- Zero Shot Learning for Text Classification using Class Representative Learning -- Visual Context Learning with Big Data Analytics -- Transformation from Publications to Ontology using Topic-based Assertion Discovery -- Ontology Mapping Framework with Feature Extraction and Semantic Embeddings -- Conclusion -- Appendix A. A Comparative Evaluation with Different Similarity Measure

Chemical Composition and In Vitro Cytotoxic Activity of Essential Oil of Leaves of Malus domestica Growing in Western Himalaya (India)

Light pale-colored volatile oil was obtained from fresh leaves of Malus domestica tree, growing in Dhauladhar range of Himalaya (Himachal Pradesh, India), with characteristic eucalyptol dominant fragrance. The oil was found to be a complex mixture of mono-, sesqui-, di-terpenes, phenolics, and aliphatic hydrocarbons. Seventeen compounds accounting for nearly 95.3% of the oil were characterized with the help of capillary GC, GC-MS, and NMR. Major compounds of the oil were characterized as eucalyptol (43.7%), phytol (11.5%), α-farnesene (9.6%), and pentacosane (7.6%). Cytotoxicity of essential oil of leaves of M. domestica was evaluated by sulforhodamine B (SRB) assays. The essential oil of leaves of M. domestica, tested against three cancer cell lines, namely, C-6 (glioma cells), A549 (human lung carcinoma), CHOK1 (Chinese hamster ovary cells), and THP-1 (human acute monocytic leukemia cell). The highest activity showed by essential oil on C-6 cell lines (98.2%) at concentration of 2000 μg/ml compared to control. It is the first paper in literature to exploit the chemical composition and cytotoxic activity of leaves essential oil of M. domestica

An HIV1/2 point of care test on sputum for screening TB/HIV co-infection in central India – Will it work?

AbstractObjectiveTo determine whether the OraQuick® HIV-1/2 Assay (OraSure Technologies, Inc., Bethlehem, PA, USA) in sputum is a valid tool for HIV surveillance among TB patients.MethodsA cross sectional study was carried out on sputa of patients diagnosed with tuberculosis. Sputa were tested for antibodies to HIV using OraQuick® HIV-1/2 Assay (OraSure Technologies, Inc., Bethlehem, PA, USA). The results were compared with results of serum ELISA.ResultsCompared to serum ELISA, the OraQuick® HIV-1/2 Assay in sputum specimens reported 90% sensitivity (9/10) and 100% specificity (307/307), with a positive predictive value of 100% (95% CI: 66.37%–100.00%) and a negative predictive value of 99.68% (95% CI: 98.20%–99.99%).ConclusionsThis testing method may provide a useful strategy for conducting HIV surveillance in possible co-infected TB patients at peripheral centres. Since there is no investment on infrastructure, it may be possible for paramedical health professionals to carry out the test, particularly in areas with low HIV endemicity

An Improved Method for High Quality Metagenomics DNA Extraction from Human and Environmental Samples

To explore the natural microbial community of any ecosystems by high-resolution molecular approaches including next generation sequencing, it is extremely important to develop a sensitive and reproducible DNA extraction method that facilitate isolation of microbial DNA of sufficient purity and quantity from culturable and uncultured microbial species living in that environment. Proper lysis of heterogeneous community microbial cells without damaging their genomes is a major challenge. In this study, we have developed an improved method for extraction of community DNA from different environmental and human origin samples. We introduced a combination of physical, chemical and mechanical lysis methods for proper lysis of microbial inhabitants. The community microbial DNA was precipitated by using salt and organic solvent. Both the quality and quantity of isolated DNA was compared with the existing methodologies and the supremacy of our method was confirmed. Maximum recovery of genomic DNA in the absence of substantial amount of impurities made the method convenient for nucleic acid extraction. The nucleic acids obtained using this method are suitable for different downstream applications. This improved method has been named as the THSTI method to depict the Institute where the method was developed