35 research outputs found

    Graphical Image Rendering: Modeling, Animation of Facial or Wild Images

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    In this comparative study, we intend to analyse different methodologies to perform 3-Dimensional modeling and printing, by using raw images as input without any supervision by a human. Since the input consists of only raw images, the foundation of the methods is finding symmetry in images. But the images that seem symmetric are not symmetric due to the perspective effect and utterance of other factors. The method uses factors like depth, albedo, point of view, and lighting from the input image to formulate 3D shapes. A 3D template model with feature points is created, and by deforming the 3D template model, a 3D model of the subject is then reconstructed from orthogonal photos. The number and locations of the proper amount of feature points are derived. Procrustes Analysis and Radial Basis Functions (RBFs) are used for the deformation. Images are then mapped onto the mesh following the deformations for realistic visualization. Characterization of the input image shows an asymmetric cause of shading, lighting, and albedo rendering the symmetry of images. The experiments show that using these methods can give exact 3D shapes of objects like human faces, cars, and cats

    Papillary carcinoma breast in male patient - A rare presentation

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    Introduction - Male breast carcinoma is rare, accounting for 1% of all malignancies in men and around 1% of all cases of breast carcinoma. Intracystic papillary carcinoma accounts for 0.5–1% of all breast cancers. It generally has good prognosis in women with almost 100% reported 10 year survival rate.Similar data for male patients is not available as the disease is extremely rare.Presentation of Case - A 52 year-old male patient presented with a swelling in his left breast. Swelling had gradually increased in size. On examination, a well-circumscribed swelling was palpable in retro aerolar region with nipple retraction. Mass was not fixed to underlying pectoralis muscle.A large mobile axillary lymph node was palpable. Fine needle aspiration was done, which reported “atypical ductal hyperplasia”. A core biopsy was done which displayed features of intracystic papillary carcinoma. A left modified radical mastectomy was carried out with axillary dissection. The biopsy report of the specimen confirmed the diagnosis of intracystic papillary carcinoma, tumor deposits were seen in lymph nodes. Adjuvant chemotherapy was given postoperatively. Patient recovered well.Conclusion - Intracystic papillary carcinoma is a rare malignancy of breast .It carries an excellent prognosis with upto 100% ten years survival rates reported in females.Surgery with chemotherapy has remained mainstay of treatment but due to rarity of the male breast cancer as such and Intracystic papillary carcinoma in particular, there are no clear guidelines for its management. Further analysis of this disease is needed for its better understanding and management.

    Metformin as a potential combination therapy with existing front-line antibiotics for Tuberculosis

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    Host-response-based gene signatures for tuberculosis diagnosis: A systematic comparison of 16 signatures.

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    BackgroundThe World Health Organization (WHO) and Foundation for Innovative New Diagnostics (FIND) have published target product profiles (TPPs) calling for non-sputum-based diagnostic tests for the diagnosis of active tuberculosis (ATB) disease and for predicting the progression from latent tuberculosis infection (LTBI) to ATB. A large number of host-derived blood-based gene-expression biomarkers for diagnosis of patients with ATB have been proposed to date, but none have been implemented in clinical settings. The focus of this study is to directly compare published gene signatures for diagnosis of patients with ATB across a large, diverse list of publicly available gene expression datasets, and evaluate their performance against the WHO/FIND TPPs.Methods and findingsWe searched PubMed, Gene Expression Omnibus (GEO), and ArrayExpress in June 2018. We included all studies irrespective of study design and enrollment criteria. We found 16 gene signatures for the diagnosis of ATB compared to other clinical conditions in PubMed. For each signature, we implemented a classification model as described in the corresponding original publication of the signature. We identified 24 datasets containing 3,083 transcriptome profiles from whole blood or peripheral blood mononuclear cell samples of healthy controls or patients with ATB, LTBI, or other diseases from 14 countries in GEO. Using these datasets, we calculated weighted mean area under the receiver operating characteristic curve (AUROC), specificity at 90% sensitivity, and negative predictive value (NPV) for each gene signature across all datasets. We also compared the diagnostic odds ratio (DOR), heterogeneity in DOR, and false positive rate (FPR) for each signature using bivariate meta-analysis. Across 9 datasets of patients with culture-confirmed diagnosis of ATB, 11 signatures had weighted mean AUROC > 0.8, and 2 signatures had weighted mean AUROC ≤ 0.6. All but 2 signatures had high NPV (>98% at 2% prevalence). Two gene signatures achieved the minimal WHO TPP for a non-sputum-based triage test. When including datasets with clinical diagnosis of ATB, there was minimal reduction in the weighted mean AUROC and specificity of all but 3 signatures compared to when using only culture-confirmed ATB data. Only 4 signatures had homogeneous DOR and lower FPR when datasets with clinical diagnosis of ATB were included; other signatures either had heterogeneous DOR or higher FPR or both. Finally, 7 of 16 gene signatures predicted progression from LTBI to ATB 6 months prior to sputum conversion with positive predictive value > 6% at 2% prevalence. Our analyses may have under- or overestimated the performance of certain ATB diagnostic signatures because our implementation may be different from the published models for those signatures. We re-implemented published models because the exact models were not publicly available.ConclusionsWe found that host-response-based diagnostics could accurately identify patients with ATB and predict individuals with high risk of progression from LTBI to ATB prior to sputum conversion. We found that a higher number of genes in a signature did not increase the accuracy of the signature. Overall, the Sweeney3 signature performed robustly across all comparisons. Our results provide strong evidence for the potential of host-response-based diagnostics in achieving the WHO goal of ending tuberculosis by 2035, and host-response-based diagnostics should be pursued for clinical implementation

    Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis

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    Tuberculosis continues to be a major health challenge, warranting the need for newer strategies for therapeutic intervention and newer approaches to discover them. Here, we report the identification of efficient metabolism disruption strategies by analysis of a reactome network. Protein-protein dependencies at a genome scale are derived from the curated metabolic network, from which insights into the nature and extent of inter-protein and inter-pathway dependencies have been obtained. A functional distance matrix and a subsequent nearness index derived from this information, helps in understanding how the influence of a given protein can pervade to the metabolic network. Thus, the nearness index can be viewed as a metabolic disruptability index, which suggests possible strategies for achieving maximal metabolic disruption by inhibition of the least number of proteins. A greedy approach has been used to identify the most influential singleton, and its combination with the other most pervasive proteins to obtain highly influential pairs, triplets and quadruplets. The effect of deletion of these combinations on cellular metabolism has been studied by flux balance analysis. An obvious outcome of this study is a rational identification of drug targets, to efficiently bring down mycobacterial metabolism

    Strategies for efficient disruption of metabolism in Mycobacterium tuberculosis from network analysis

    No full text
    Tuberculosis continues to be a major health challenge, warranting the need for newer strategies for therapeutic intervention and newer approaches to discover them. Here, we report the identification of efficient metabolism disruption strategies by analysis of a reactome network. Protein–protein dependencies at a genome scale are derived from the curated metabolic network, from which insights into the nature and extent of inter-protein and inter-pathway dependencies have been obtained. A functional distance matrix and a subsequent nearness index derived from this information, helps in understanding how the influence of a given protein can pervade to the metabolic network. Thus, the nearness index can be viewed as a metabolic disruptability index, which suggests possible strategies for achieving maximal metabolic disruption by inhibition of the least number of proteins. A greedy approach has been used to identify the most influential singleton, and its combination with the other most pervasive proteins to obtain highly influential pairs, triplets and quadruplets. The effect of deletion of these combinations on cellular metabolism has been studied by flux balance analysis. An obvious outcome of this study is a rational identification of drug targets, to efficiently bring down mycobacterial metabolism

    From Genes to Geography, from Cells to Community, from Biomolecules to Behaviors: The Importance of Social Determinants of Health

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    Much scientific work over the past few decades has linked health outcomes and disease risk to genomics, to derive a better understanding of disease mechanisms at the genetic and molecular level. However, genomics alone does not quite capture the full picture of one's overall health. Modern computational biomedical research is moving in the direction of including social/environmental factors that ultimately affect quality of life and health outcomes at both the population and individual level. The future of studying disease now lies at the hands of the social determinants of health (SDOH) to answer pressing clinical questions and address healthcare disparities across population groups through its integration into electronic health records (EHRs). In this perspective article, we argue that the SDOH are the future of disease risk and health outcomes studies due to their vast coverage of a patient's overall health. SDOH data availability in EHRs has improved tremendously over the years with EHR toolkits, diagnosis codes, wearable devices, and census tract information to study disease risk. We discuss the availability of SDOH data, challenges in SDOH implementation, its future in real-world evidence studies, and the next steps to report study outcomes in an equitable and actionable way

    Kaposi sarcoma (KS) with primary effusion lymphoma in HIV infected MSM (men having sex with men) co-infected with pulmonary tuberculosis and syphilis: a case report from India

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    Abstract We describe a case of a 30-year-old MSM recently diagnosed with HIV, immunocompromised with a purplish or brown rash all over the body for 3 to 4 months. The histopathology of the cutaneous lesions and pleural effusion aspirate confirmed the diagnosis of Kaposi’s sarcoma (KS) and primary effusion lymphoma (PEL). While KS is one of the AIDS-defining illnesses seen in immunocompromised patients having low CD4 count, PEL is a rare and distinct subset of AIDS-related lymphoma. Despite the widespread availability of HIV testing, HIV diagnosis gets delayed due to stigma among MSM. This case report emphasizes the importance of early suspicion for symptoms of HIV-associated opportunistic infections in high-risk populations like MSM. The report reiterates the need for an ambient stigma-free environment for improving HIV screening in this high-risk population
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