176 research outputs found
Demographic and Socio-economic Determinants of Birth Interval Dynamics in Manipur: A Survival Analysis
The birth interval is a major determinant of levels of fertility in high fertility populations. A house-to-house survey of 1225 women in Manipur, a tiny state in North Eastern India was carried out to investigate birth interval patterns and its determinants. Using survival analysis, among the nine explanatory variables of interest, only three factors – infant mortality, Lactation and use of contraceptive devices have highly significant effect (P<0.01) on the duration of birth interval and only three factors – age at marriage of wife, parity and sex of child are found to be significant (P<0.05) on the duration variable
Characterizing MRO in atomistic models of vitreous SiO generated using ab-initio molecular dynamics
Vitreous silica is the most versatile material for scientific and commercial
applications. Although large-scale atomistic models of vitreous-SiO
(v-SiO) having medium-range order (MRO) have been successfully developed by
melt-quench through classical molecular dynamics, the MRO is not well studied
for the smaller-scale models developed by melt-quench using ab-initio molecular
dynamics (AIMD). In this study, we obtain atomistic models of v-SiO by
performing melt-quench simulation using AIMD. The final structure is compared
with the experimental data and some recent atomistic models, on the basis of
the structural properties. Since AIMD allows for the estimation of electronic
structure, a detailed study of electronic properties is also done. It shows the
presence of defect states mainly due to dangling bonds in the band-gap region
of electronic density of states, whereas the edge-shared type of defective
structures in the glassy models are found to contribute mainly in the valence
band. In addition, Oxygen and Silicon vacancies as well as bridging Oxygen type
of defects were created and their contributions to the band-gap were studied.Comment: 28 pages, 12 figures, preprin
Molecular modelling, docking and interaction studies of human-plasmogen and salmonella enolase with enolase inhibitors
Salmonella enteric serovar Typhi Ty2 is a human specific pathogen and an etiological agent for typhoid fever. Most of Salmonella
serotypes produce glycogen which has a comparatively minor role in virulence and colonization, but has a more significant role in
survival. Enzymes present in glycolytic pathway of bacteria help bacteria to survive by activating other factors inside host.
Numerous pathogenic bacteria species intervene with the plasminogen system, and this plasminogen–enolase association may play
a critical role in the virulence of S. Typhi by causing direct damage to the host cell extracellular matrix, possibly by enzymic
degradation of extracellular matrix proteins or other protein constituents. In this study, molecular modelling of enolase of
Salmonella has been accomplished in silico by comparative modelling; we have then analyzed Human alpha enolase which is a
homodimer and serves on epithelial cells with our model. Both Structures were docked by D-tartronate semialdehyde phosphate
(TSP) and 3-aminoenolpyruvate phosphate (AEP) enolase inhibitors. Our study shows that salmonella enolase and human enolase
have different active sites in their structure. This will help in development of new ligands, more suitable for inhibiting bacterial
survival inside host as vaccines for typhoid fever are not fully protective. The study also confirmed that enolase Salmonella and
Human Plasminogen suggested direct physical interaction between both of them as the activation loop of plasminogen residues
showed conformational changes similar to the tissue type plasminogen activator. Various computational biology tools were used
for our present study such as Modeller, Molegro Virtual Docker, Grommacs
Postpartum Amenorrhoea among Manipuri Women: A Survival Analysis
Among the three major components of a closed birth interval, waiting
time to conception can somehow be managed with effective contraceptives
while gestation is universally constant in its duration; the duration
of postpartum amenorrhoea (PPA) varies in complex nature. The present
study aimed to investigate the proximate factors influencing the
duration of PPA. A community-based, cross-sectional study was conducted
in four valley districts of Manipur, India, during 1 August 1231
December 2009, to analyze the differentials and determinants of
duration of PPA, applying the survival analysis technique. In total,
1,225 ever-married women were selected through two-stage cluster
sampling. The median duration of PPA was 5.7 months. Among the 11
explanatory variables of interest, only three variables\u2014place of
residence (p<0.05), infant mortality from preceding pregnancy
(p<0.01), and duration of breastfeeding (p<0.01)\u2014 had a
significant effect on the duration of PPA. The findings may be used as
baseline information for future researchers and maternal health
policy-makers
Mathematical models to define growth patterns in indigenous horses of India
The objective of the study was to define the nature of growth and to establish the standards of growth in Marwari, Manipuri and Zanskari horses. Mathematical functions for the prediction of growth in Marwari horses were derived utilising 1112 records of body weight. The body weight standards of Marwari horses from birth to 11 ½ years of age were defined and found to be close to that of Arabian horses. The Logarithmic, Power, S and Cubic functions were derived with respective R2 values of 0.955, 0.833, 0.897 and 0.980 for average body weights to explain the age-weight relationship in Marwari horses from birth to 11 ½ years of age. Looking at the distribution of observed data along the course of predicted curve and goodness of fit on average body weight, the Cubic equation Ŷ = 68.136 + 10.744 (x) - 0.12189 (x)2 + 0.00044177 (x)3 can reliably be utilized for prediction of body weight with respect to age. Similarly, the Cubic equations with R2 value of 0.965 and 0.958 were derived respectively for Manipuri and Zanskari horses. The two roots of Cubic function were derived to define the points of inflection of growth curve. The study indicated that the initial growth phase in Marwari, Manipuri and Zanskari continues up to the age of 73.22, 72 and 67.4 months respectively and there after it remains static; and the cubic function can reliably be used to explain the nature of growth in Marwari, Manipuri and Zanskari breeds of horses
Signatures of Drug Sensitivity in Nonsmall Cell Lung Cancer
We profiled receptor tyrosine kinase pathway activation and key gene mutations in eight human lung tumor cell lines and 50 human lung tumor tissue samples to define molecular pathways. A panel of eight kinase inhibitors was used to determine whether blocking pathway activation affected the tumor cell growth. The HER1 pathway in HER1 mutant cell lines HCC827 and H1975 were found to be highly activated and sensitive to HER1 inhibition. H1993 is a c-MET amplified cell line showing c-MET and HER1 pathway activation and responsiveness to c-MET inhibitor treatment. IGF-1R pathway activated H358 and A549 cells are sensitive to IGF-1R inhibition. The downstream PI3K inhibitor, BEZ-235, effectively inhibited tumor cell growth in most of the cell lines tested, except the H1993 and H1650 cells, while the MEK inhibitor PD-325901 was effective in blocking the growth of KRAS mutated cell line H1734 but not H358, A549 and H460. Hierarchical clustering of primary tumor samples with the corresponding tumor cell lines based on their pathway signatures revealed similar profiles for HER1, c-MET and IGF-1R pathway activation and predict potential treatment options for the primary tumors based on the tumor cell lines response to the panel of kinase inhibitors
Highly sensitive proximity mediated immunoassay reveals HER2 status conversion in the circulating tumor cells of metastatic breast cancer patients
<p>Abstract</p> <p>Background</p> <p>The clinical benefits associated with targeted oncology agents are generally limited to subsets of patients. Even with favorable biomarker profiles, many patients do not respond or acquire resistance. Existing technologies are ineffective for treatment monitoring as they provide only static and limited information and require substantial amounts of tissue. Therefore, there is an urgent need to develop methods that can profile potential therapeutic targets with limited clinical specimens during the course of treatment.</p> <p>Methods</p> <p>We have developed a novel proteomics-based assay, Collaborative Enzyme Enhanced Reactive-immunoassay (CEER) that can be used for analyzing clinical samples. CEER utilizes the formation of unique immuno-complex between capture-antibodies and two additional detector-Abs on a microarray surface. One of the detector-Abs is conjugated to glucose oxidase (GO), and the other is conjugated to Horse Radish Peroxidase (HRP). Target detection requires the presence of both detector-Abs because the enzyme channeling event between GO and HRP will not occur unless both Abs are in close proximity.</p> <p>Results</p> <p>CEER was able to detect single-cell level expression and phosphorylation of human epidermal growth factor receptor 2 (HER2) and human epidermal growth factor receptor 1 (HER1) in breast cancer (BCa) systems. The shift in phosphorylation profiles of receptor tyrosine kinases (RTKs) and other signal transduction proteins upon differential ligand stimulation further demonstrated extreme assay specificity in a multiplexed array format. HER2 analysis by CEER in 227 BCa tissues showed superior accuracy when compared to the outcome from immunohistochemistry (IHC) (83% vs. 96%). A significant incidence of HER2 status alteration with recurrent disease was observed via circulating tumor cell (CTC) analysis, suggesting an evolving and dynamic disease progression. HER2-positive CTCs were found in 41% (7/17) while CTCs with significant HER2-activation without apparent over-expression were found in 18% (3/17) of relapsed BCa patients with HER2-negative primary tumors. The apparent 'HER2 status conversion' observed in recurrent BCa may have significant implications on understanding breast cancer metastasis and associated therapeutic development.</p> <p>Conclusion</p> <p>CEER can be multiplexed to analyze pathway proteins in a comprehensive manner with extreme specificity and sensitivity. This format is ideal for analyzing clinical samples with limited availability.</p
Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays
Research has shown that turner vascular markers (TVMs) may serve as potential OCa biomarkers for prognosis prediction. One such TVM is ESM-1, which can be visualized by staining ovarian Tissue Microarrays (TMA) with in antibody to ESM-1. The ability to quickly and quantitatively estimate vascular stained regions may yield an image based metric linked to disease survival and outcome. Automated segmentation of the vascular stained regions on the TMAs. however, is hindered by the presence of spuriously stained false positive regions. In this paper, we present a general, robust and efficient unsupervised segmentation algorithm, termed Hierarchical Normalized Cuts (HNCut), and show its application in precisely quantifying the presence and extent of a TVM on OCa TMAs. The strength of HNCut is in the use of a hierarchically represented data structure that bridges the mean shift (MS) and the normalized cuts (NCut,) algorithms. This allows HNCut to efficiently traverse a pyramid of the input image at various color resolutions, efficiently and accurately segmenting the object class of interest (in this case ESM-1. vascular stained regions) by simply annotating half a, dozen pixels belonging to the target; class. Quantitative and qualitative analysis of our results, using 100 pathologist annotated samples across multiple studies, prove the superiority of our method (sensitivity 81%, Positive predictive value (PPV), 80%) versus a popular supervised learning technique, Probabilistic Boosting Trees (sensitivity, PPV of 76% and 66%)
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