COMPARATIVE STUDY OF TADAGJAL (ARTIFICIAL LAKE WATER) AND HANSODAKA (NATURALLY PURIFIED WATER IN SHARAD RITU) FROM THE SAME TADAG WITH RESPECT TO CHEMICAL PROPERTIES

Ayurveda is an ancient science dealing with attaining health and curing diseases of ill. Good health makes our life happy. For that one has to take Wholesome of food which includes pure water also. We should always use the pure water to maintain health. Our Rishis have mentioned regarding Hansodaka in Samhitas. Hansodaka is purified water in Sharad ritu by natural resources like Sunrays, Moonrays and an additional effects of Agasti star rays at night and Kalprabhav of Sharad ritu. This Hansodaka is pure water and ideal for drinking purpose. So to check this statement of our Rishis, efforts are made here to compare such Hansodaka and simple Tadagjal in view of chemical properties, considering W.H.O. guideline in present era. Aims and Objective: To compare chemical properties of Simple Tadagjal and Hansodaka to check its suitability for drinking purpose. Materials and Methods: Total four samples were collected. Two were Simple Tadadjal and Two were Hansodaka. All Water samples were analyzed in standard laboratory for chemical properties. Reports were collected and analyzed. Results and Conclusion: Hansodaka is better than simple Tadagjal with respect to chemical properties. It may be due to combine effect of sunrays, moon rays and Agasti star rays in Sharad ritu. But Hansodaka is not suitable for drinking purpose as per W.H.O. guideline. it may be due to increased population, pollution, industrialization in present era as compared to ancient era. Hence we can say water purification by other methods is must in present era

A bioinformatics approach reveals novel interactions of the OVOL transcription factors in the regulation of epithelial – mesenchymal cell reprogramming and cancer progression

Abstract Background Mesenchymal to Epithelial Transition (MET) plasticity is critical to cancer progression, and we recently showed that the OVOL transcription factors (TFs) are critical regulators of MET. Results of that work also posed the hypothesis that the OVOLs impact MET in a range of cancers. We now test this hypothesis by developing a model, OVOL Induced MET (OI-MET), and sub-model (OI-MET-TF), to characterize differential gene expression in MET common to prostate cancer (PC) and breast cancer (BC). Results In the OI-MET model, we identified 739 genes differentially expressed in both the PC and BC models. For this gene set, we found significant enrichment of annotation for BC, PC, cancer, and MET, as well as regulation of gene expression by AP1, STAT1, STAT3, and NFKB1. Focusing on the target genes for these four TFs plus the OVOLs, we produced the OI-MET-TF sub-model, which shows even greater enrichment for these annotations, plus significant evidence of cooperation among these five TFs. Based on known gene/drug interactions, we prioritized targets in the OI-MET-TF network for follow-on analysis, emphasizing the clinical relevance of this work. Reflecting these results back to the OI-MET model, we found that binding motifs for the TF pair AP1/MYC are more frequent than expected and that the AP1/MYC pair is significantly enriched in binding in cancer models, relative to non-cancer models, in these promoters. This effect is seen in both MET models (solid tumors) and in non-MET models (leukemia). These results are consistent with our hypothesis that the OVOLs impact cancer susceptibility by regulating MET, and extend the hypothesis to include mechanisms not specific to MET. Conclusions We find significant evidence of the OVOL, AP1, STAT1, STAT3, and NFKB1 TFs having important roles in MET, and more broadly in cancer. We prioritize known gene/drug targets for follow-up in the clinic, and we show that the AP1/MYC TF pair is a strong candidate for intervention.http://deepblue.lib.umich.edu/bitstream/2027.42/109509/1/12918_2013_Article_1293.pd

LRpath analysis reveals common pathways dysregulated via DNA methylation across cancer types

Abstract Background The relative contribution of epigenetic mechanisms to carcinogenesis is not well understood, including the extent to which epigenetic dysregulation and somatic mutations target similar genes and pathways. We hypothesize that during carcinogenesis, certain pathways or biological gene sets are commonly dysregulated via DNA methylation across cancer types. The ability of our logistic regression-based gene set enrichment method to implicate important biological pathways in high-throughput data is well established. Results We developed a web-based gene set enrichment application called LRpath with clustering functionality that allows for identification and comparison of pathway signatures across multiple studies. Here, we employed LRpath analysis to unravel the commonly altered pathways and other gene sets across ten cancer studies employing DNA methylation data profiled with the Illumina HumanMethylation27 BeadChip. We observed a surprising level of concordance in differential methylation across multiple cancer types. For example, among commonly hypomethylated groups, we identified immune-related functions, peptidase activity, and epidermis/keratinocyte development and differentiation. Commonly hypermethylated groups included homeobox and other DNA-binding genes, nervous system and embryonic development, and voltage-gated potassium channels. For many gene sets, we observed significant overlap in the specific subset of differentially methylated genes. Interestingly, fewer DNA repair genes were differentially methylated than expected by chance. Conclusions Clustering analysis performed with LRpath revealed tightly clustered concepts enriched for differential methylation. Several well-known cancer-related pathways were significantly affected, while others were depleted in differential methylation. We conclude that DNA methylation changes in cancer tend to target a subset of the known cancer pathways affected by genetic aberrations.http://deepblue.lib.umich.edu/bitstream/2027.42/112789/1/12864_2012_Article_4373.pd

Blunted cardiomyocyte remodeling response in exercise-resistant rats

Increasing a subject’s aerobic exercise capacity with training decreases cardiovascular morbidity and mortality. Of major concern is the key observation that up to 20% of subjects demonstrate little or no change in maximal oxygen consumption (VO2max) with exercise training (1) and can be considered exercise resistant. Our goal with the current research was to test the hypothesis that variation in training response is associated with cardiomyocyte functional response to training

Literature-based discovery of diabetes- and ROS-related targets

Abstract Background Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. A web-based literature mining tool, SciMiner, was applied to 1,154 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature-derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 1,154 biomedical papers (http://jdrf.neurology.med.umich.edu/ROSDiabetes/). Fifty-three targets were significantly over-represented in the ROS-diabetes literature compared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and non-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the pathogenesis of diabetic neuropathy.http://deepblue.lib.umich.edu/bitstream/2027.42/78315/1/1755-8794-3-49.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/2/1755-8794-3-49-S7.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/3/1755-8794-3-49-S10.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/4/1755-8794-3-49-S8.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/5/1755-8794-3-49-S3.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/6/1755-8794-3-49-S1.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/7/1755-8794-3-49-S4.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/8/1755-8794-3-49-S2.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/9/1755-8794-3-49-S12.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/10/1755-8794-3-49-S11.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/11/1755-8794-3-49-S9.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/12/1755-8794-3-49-S5.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/13/1755-8794-3-49-S6.XLShttp://deepblue.lib.umich.edu/bitstream/2027.42/78315/14/1755-8794-3-49.pdfPeer Reviewe

Characterizing the Dynamics of CD4+ T Cell Priming within a Lymph Node

Generating adaptive immunity postinfection or immunization requires physical interaction within a lymph node T zone between Ag-bearing dendritic cells (DCs) and rare cognate T cells. Many fundamental questions remain regarding the dynamics of DC-CD4+ T cell interactions leading to priming. For example, it is not known how the production of primed CD4+ T cells relates to the numbers of cognate T cells, Ag-bearing DCs, or peptide-MHCII level on the DC. To address these questions, we developed an agent-based model of a lymph node to examine the relationships among cognate T cell frequency, DC density, parameters characterizing DC-T cell interactions, and the output of primed T cells. We found that the output of primed CD4+ T cells is linearly related to cognate frequency, but nonlinearly related to the number of Ag-bearing DCs present during infection. This addresses the applicability of two photon microscopy studies to understanding actual infection dynamics, because these types of experiments increase the cognate frequency by orders of magnitude compared with physiologic levels. We found a trade-off between the quantity of peptidemajor histocompatibility class II on the surface of individual DCs and number of Ag-bearing DCs present in the lymph node in contributing to the production of primed CD4+ T cells. Interestingly, peptide-major histocompatibility class II t 1/2 plays a minor, although still significant, role in determining CD4+ T cell priming, unlike the primary role that has been suggested for CD8+ T cell priming. Finally, we identify several pathogen-targeted mechanisms that, if altered in their efficiency, can significantly effect the generation of primed CD4+ T cells. The Journal of Immunology, 2010, 184: 000-000. T he adaptive immune response to pathogen infection is dependent on generation of primed CD4+ T cells in the lymph node (LN). Dendritic cells (DCs) in tissues take up pathogens and present antigenic peptides on their surface in the context of major histocompatibility class II molecules (peptide-MHCII complexes [pMHCII]) (1-3). These Ag-bearing DCs migrate via afferent lymphatics to the closest tissue-draining LN. T cells constantly transit between the circulatory and lymphatic systems, entering individual LNs via high endothelial venules and re-entering the circulatory system via the thoracic duct from efferent lymphatics (4). Generation of primed CD4+ T cells requires contact between these Ag-bearing DCs and specific (cognate) CD4+ T cells; their successful binding leads to CD4+ T cell priming (5). Whereas DCs rarely leave the LN, primed CD4+ T cells exit the LN and return to the site of infection to participate in the immune response. Despite a wealth of information on the immune response, including studies on the dynamics of DC-T cell interactions in a LN via two-photon microscopy (2PM) (3, 6, 7), many fundamental questions remain regarding the functioning of the LN. For example, it is not known how the production of primed CD4+ T cells is related to the numbers of cognate CD4+ T cells, Ag-bearing DCs, or pMHCII level on the DC surface. Will doubling the number of cognate CD4+ T cells or Ag-bearing DCs double the primed CD4+ T cell output? Experimental preparations such as 2PM often increase the density of cognate CD4+ T cells or DCs beyond the physiologic range to facilitate observation (8, 9), so answering this question will indicate how information from these studies can be interpreted. Do high numbers of DCs with fewer pMHCIIs give equivalent CD4+ T cell priming as low numbers of DCs with more pMHCIIs? Answering this question would give insight into the relationship between Ag dose and T cell priming. A few recent studies have explored these questions for CD8+ T cells (10, 11). However, CD8+ T cells recognize Ag presented on DCs in the context of peptide-MHC class I (pMHCI) molecules. The t 1/2 of pMHCI is on the order of a few hours; it is not surprising then that pMHCI t 1/2 profoundly affects the extent and dynamics of CD8+ T cell priming (10, 11). Interestingly, the t 1/2 of pMHCII is on the order of days (12-14)-that is, it is extended beyond the lifespan of the DC in most cases. Therefore, additional processes and parameters might play important and undiscovered roles in driving CD4+ T cell priming dynamics. Several recent computational studies have focused on the details of cell movement within a lymphoid organ Pathogenic microbes can interfere with the immune response via several mechanisms related to DC-T cell interactions (e.g., reduction of pMHCII on the DC surface during infection with Mycobacterium tuberculosis or interference with trafficking of DCs to the LN

LRpath analysis reveals common pathways dysregulated via DNA methylation across cancer types

Abstract Background The relative contribution of epigenetic mechanisms to carcinogenesis is not well understood, including the extent to which epigenetic dysregulation and somatic mutations target similar genes and pathways. We hypothesize that during carcinogenesis, certain pathways or biological gene sets are commonly dysregulated via DNA methylation across cancer types. The ability of our logistic regression-based gene set enrichment method to implicate important biological pathways in high-throughput data is well established. Results We developed a web-based gene set enrichment application called LRpath with clustering functionality that allows for identification and comparison of pathway signatures across multiple studies. Here, we employed LRpath analysis to unravel the commonly altered pathways and other gene sets across ten cancer studies employing DNA methylation data profiled with the Illumina HumanMethylation27 BeadChip. We observed a surprising level of concordance in differential methylation across multiple cancer types. For example, among commonly hypomethylated groups, we identified immune-related functions, peptidase activity, and epidermis/keratinocyte development and differentiation. Commonly hypermethylated groups included homeobox and other DNA-binding genes, nervous system and embryonic development, and voltage-gated potassium channels. For many gene sets, we observed significant overlap in the specific subset of differentially methylated genes. Interestingly, fewer DNA repair genes were differentially methylated than expected by chance. Conclusions Clustering analysis performed with LRpath revealed tightly clustered concepts enriched for differential methylation. Several well-known cancer-related pathways were significantly affected, while others were depleted in differential methylation. We conclude that DNA methylation changes in cancer tend to target a subset of the known cancer pathways affected by genetic aberrations.</p