Institution
Manipal University
Education•Manipal, Karnataka, India•
About: Manipal University is a education organization based out in Manipal, Karnataka, India. It is known for research contribution in the topics: Population & Medicine. The organization has 9525 authors who have published 11207 publications receiving 110687 citations.
Topics: Population, Medicine, Computer science, Health care, Cancer
Papers published on a yearly basis
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TL;DR: The data demonstrate that MSC from the two different sources respond similarly to inductive cues to differentiate terminally to a DA cell type, and the neuronal plasticity of human WJ MSC is comparable with that of BM MSC.
66 citations
Journal Article•
TL;DR: Niosomes of sumatriptan succinate were prepared using lipid hydration method and evaluated for entrapment efficiency, size analysis and in vitro release studies, and for nasal absorption using an ex vivo animal model.
Abstract: Niosomes of sumatriptan succinate were prepared using lipid hydration method. The prepared niosomes were evaluated for entrapment efficiency, size analysis and in vitro release studies. Further, the niosomes were evaluated for nasal absorption using an ex vivo animal model. The entrapment efficiency was found to be 57.9 ± 0.96 %. The niosomes released 58.71% of sumatriptan succinate over a period of 6 h and 78.1% of the drug was absorbed from the nasal mucosa ex vivo.
66 citations
TL;DR: Results indicate that there was no statistically significant difference between allele and genotype frequencies of refractory and drug responsive epilepsy patients, and the predicted haplotypes frequencies of the three polymorphisms did not showsignificant difference between cases and controls.
66 citations
TL;DR: A novel attempt to explore the loss to follow-up (LTF) rate among NHS studies, reasons for LTF and strategies to reduce LTF can act as a basis for planning and execution of effective NHS programs.
66 citations
TL;DR: The spectral analysis and classification for discrimination among normal, premalignant, and malignant conditions were performed using principal component analysis (PCA) and artificial neural network (ANN) separately on the same set of spectral data.
Abstract: Pulsed laser-induced autofluorescence spectroscopic studies of pathologically certified normal, premalignant, and malignant oral tissues were carried out at 325 nm excitation. The spectral analysis and classification for discrimination among normal, premalignant, and malignant conditions were performed using principal component analysis (PCA) and artificial neural network (ANN) separately on the same set of spectral data. In case of PCA, spectral residuals, Mahalanobis distance, and scores of factors were used for discrimination among normal, premalignant, and malignant cases. In ANN, parameters like mean, spectral residual, standard deviation, and total energy were used to train the network. The ANN used in this study is a classical multiplayer feed-forward type with a back-propagation algorithm for the training of the network. The specificity and sensitivity were determined in both classification schemes. In the case of PCA, they are 100 and 92.9%, respectively, whereas for ANN they are 100 and 96.5% for the data set considered.
66 citations
Authors
Showing all 9740 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| John J.V. McMurray | 178 | 1389 | 184502 |
| Ashok Kumar | 151 | 5654 | 164086 |
| Zhanhu Guo | 128 | 886 | 53378 |
| Vijay P. Singh | 106 | 1699 | 55831 |
| Michael Walsh | 102 | 963 | 42231 |
| Akhilesh Pandey | 100 | 529 | 53741 |
| Vivekanand Jha | 94 | 958 | 85734 |
| Manuel Hidalgo | 92 | 538 | 41330 |
| Madhukar Pai | 89 | 522 | 33349 |
| Ravi Kumar | 82 | 571 | 37722 |
| Vijay V. Kakkar | 60 | 470 | 17731 |
| G. Münzenberg | 58 | 336 | 9837 |
| Abhishek Sharma | 52 | 426 | 9715 |
| Ramesh R. Bhonde | 49 | 223 | 8397 |
| Chandra P. Sharma | 48 | 325 | 12100 |