TREE-D-SEEK: A Framework for Retrieving Three-Dimensional Scenes

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds. With ongoing improvements in computer hardware and 3D technology, the cost associated with the acquisition, production and deployment of 3D scenes is decreasing. As a consequence, there is a need for efficient 3D retrieval systems for the increasing number of 3D scenes in corpora. An efficient 3D retrieval system provides several benefits such as enhanced sharing and reuse of 3D scenes and 3D content. Existing 3D retrieval systems are closed systems and provide search solutions based on a predefined set of indexing and matching algorithms Existing 3D search systems and search solutions cannot be customized for specific requirements, type of information source and information level. In this research, TREE-D-SEEK—an open, extensible framework for retrieving 3D scenes—is proposed. The TREE-D-SEEK framework is capable of retrieving 3D scenes based on indexing low level content to high-level semantic metadata. The TREE-D-SEEK framework is discussed from a software architecture perspective. The architecture is based on a common process flow derived from indexing disparate information sources. Several indexing and matching algorithms are implemented. Experiments are conducted to evaluate the usability and performance of the framework. Retrieval performance of the framework is evaluated using benchmarks and manually collected corpora. A generic, semantic annotation model is proposed for indexing a 3D scene. The primary objective of using the semantic annotation model in the TREE-D-SEEK framework is to improve retrieval relevance and to support richer queries within a 3D scene. The semantic annotation model is driven by an ontology. The ontology is derived from a 3D rapid prototyping framework. The TREE-D-SEEK framework supports querying by example, keyword based and semantic annotation based query types for retrieving 3D scenes

Serum small extracellular vesicles proteome of tuberculosis patients demonstrated deregulated immune response

Purpose: Detailed understanding of host pathogen interaction in tuberculosis is an important avenue for identifying novel therapeutic targets. Small extracellular vesicles (EVs) like exosomes that are rich in proteins, nucleic acids and lipids, act as messengers and may show altered composition in disease conditions. Experimental design: In this case control study, small EVs are isolated from serum of 58 subjects (all male, 33 (15–70) in years) including drug naïve active tuberculosis (ATB: n = 22), non-tuberculosis (NTB: n = 18), and healthy subjects (n = 18). Serum small EVs proteome analysis is carried out using isobaric tag for relative and absolute quantification (iTRAQ) experiments and an independent sample (n = 36) is used for validation. Results: A set of 132 and 68 proteins are identified in iTRAQ-I (ATB/Healthy) and iTRAQ-II (ATB/NTB) experiments, respectively. Four proteins (KYAT3, SERPINA1, HP, and APOC3) show deregulation (log2-fold change > ±0.48, p < 0.05) in ATB with respect to healthy controls and Western blot data corroborated mass spectrometry findings. Conclusions and clinical relevance: These important proteins, involved in neutrophil degranulation, plasma heme scavenging, kynurenine, and lipid metabolism, show deregulation in ATB patients. Identification of such a protein panel in circulating small EVs besides providing novel insights into their role in tuberculosis may prove to be useful targets to develop host-directed therapeutic intervention

Sputum Proteomics Reveals a Shift in Vitamin D-binding Protein and Antimicrobial Protein Axis in Tuberculosis Patients

Abstract Existing understanding of molecular composition of sputum and its role in tuberculosis patients is variously limited to its diagnostic potential. We sought to identify infection induced sputum proteome alteration in active/non tuberculosis patients (A/NTB) and their role in altered lung patho-physiology. Out of the study population (n = 118), sputum proteins isolated from discovery set samples (n = 20) was used for an 8-plex isobaric tag for relative and absolute concentration analysis. A minimum set of protein with at least log2(ATB/NTB) >±1.0 in ATB was selected as biosignature and validated in 32 samples. Predictive accuracy was calculated from area under the receiver operating characteristic curve (AUC of ROC) using a confirmatory set (n = 50) by Western blot analysis. Mass spectrometry analysis identified a set of 192 sputum proteins, out of which a signature of β-integrin, vitamin D binding protein:DBP, uteroglobin, profilin and cathelicidin antimicrobial peptide was sufficient to differentiate ATB from NTB. AUC of ROC of the biosignature was calculated to 0.75. A shift in DBP-antimicrobial peptide (AMP) axis in the lungs of tuberculosis patients is observed. The identified sputum protein signature is a promising panel to differentiate ATB from NTB groups and suggest a deregulated DBP-AMP axis in lungs of tuberculosis patients