Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (9/9 displayed)

  • 2023Interactions between Iron and Nickel in Fe-Ni Nanoparticles on Y Zeolite for Co-Processing of Fossil Feedstock with Lignin-Derived Isoeugenol13citations
  • 2023Characterization and Energy Densification of Mayhaw Jelly Production Wastes Using Hydrothermal Carbonization2citations
  • 2023Immunohistochemical Surrogates for Molecular Stratification in Medulloblastoma2citations
  • 2020Transformation of industrial steel slag with different structure-modifying agents for synthesis of catalysts10citations
  • 2019Synthesis and Characterization of Novel Catalytic Materials Using Industrial Slag:Influence of Alkaline Pretreatment, Synthesis Time and Temperature16citations
  • 2019Synthesis and Characterization of Novel Catalytic Materials Using Industrial Slag16citations
  • 2017A Study on Mechanical Properties and Strengthening Mechanisms of AA5052/ZrB2 In Situ Composites48citations
  • 2017High-Temperature Tribology of AA5052/ZrB2 PAMCs26citations
  • 2014Synthesis and characterization of polypyrrole/H-Beta zeolite nanocomposites15citations

Places of action

Chart of shared publication
Lindén, Johan
1 / 6 shared
Vajglová, Zuzana
1 / 2 shared
Eränen, Kari
1 / 3 shared
Simakova, Irina L.
1 / 2 shared
Murzin, Dmitry Yu
4 / 14 shared
Peurla, Markus
1 / 4 shared
Doronkin, Dmitry E.
1 / 3 shared
Lassfolk, Robert
1 / 1 shared
Mäki-Arvela, Päivi
1 / 10 shared
Prosvirin, Igor P.
1 / 1 shared
Huhtinen, Hannu
1 / 14 shared
Paturi, Petriina
1 / 20 shared
Wärnå, Johan
1 / 2 shared
Gauli, Bibesh
1 / 1 shared
Hardin, Meilan
1 / 1 shared
Sagar, Viral
1 / 1 shared
Madan, Renu
1 / 1 shared
Radotra, Bishan Dass
1 / 1 shared
Gupta, Nalini
1 / 1 shared
Chinnam, Dheeraj
1 / 1 shared
Saraswati, Aastha
1 / 1 shared
Gupta, Kirti
1 / 1 shared
Kiran, Tanvi
1 / 1 shared
Salunke, Pravin
1 / 1 shared
Jogunoori, Swathi
1 / 1 shared
Verma, Aanchal
1 / 1 shared
Lehtonen, Juha
3 / 8 shared
Salonen, Jarno
3 / 13 shared
Perula, Marcus
3 / 3 shared
Kholkina, Ekaterina
3 / 3 shared
Ohra-Aho, Taina
3 / 7 shared
Peltonen, Janne
3 / 3 shared
Lindfors, Christian
3 / 8 shared
Mohan, Sunil
2 / 7 shared
Gautam, Rakesh Kumar
2 / 4 shared
Mohan, Anita
2 / 7 shared
Gautam, Gaurav
2 / 4 shared
Yu, Kai
1 / 1 shared
Roine, Jorma
1 / 1 shared
Pesonen, Markus
1 / 6 shared
Ivaska, Ari
1 / 3 shared
Chart of publication period
2023
2020
2019
2017
2014

Co-Authors (by relevance)

  • Lindén, Johan
  • Vajglová, Zuzana
  • Eränen, Kari
  • Simakova, Irina L.
  • Murzin, Dmitry Yu
  • Peurla, Markus
  • Doronkin, Dmitry E.
  • Lassfolk, Robert
  • Mäki-Arvela, Päivi
  • Prosvirin, Igor P.
  • Huhtinen, Hannu
  • Paturi, Petriina
  • Wärnå, Johan
  • Gauli, Bibesh
  • Hardin, Meilan
  • Sagar, Viral
  • Madan, Renu
  • Radotra, Bishan Dass
  • Gupta, Nalini
  • Chinnam, Dheeraj
  • Saraswati, Aastha
  • Gupta, Kirti
  • Kiran, Tanvi
  • Salunke, Pravin
  • Jogunoori, Swathi
  • Verma, Aanchal
  • Lehtonen, Juha
  • Salonen, Jarno
  • Perula, Marcus
  • Kholkina, Ekaterina
  • Ohra-Aho, Taina
  • Peltonen, Janne
  • Lindfors, Christian
  • Mohan, Sunil
  • Gautam, Rakesh Kumar
  • Mohan, Anita
  • Gautam, Gaurav
  • Yu, Kai
  • Roine, Jorma
  • Pesonen, Markus
  • Ivaska, Ari
OrganizationsLocationPeople

article

Immunohistochemical Surrogates for Molecular Stratification in Medulloblastoma

  • Madan, Renu
  • Radotra, Bishan Dass
  • Gupta, Nalini
  • Chinnam, Dheeraj
  • Kumar, Narendra
  • Saraswati, Aastha
  • Gupta, Kirti
  • Kiran, Tanvi
  • Salunke, Pravin
  • Jogunoori, Swathi
  • Verma, Aanchal
Abstract

<jats:sec><jats:title>Background:</jats:title><jats:p>The WHO classification of central nervous system neoplasms (2016) recognized 4 histologic variants and genetically defined molecular subgroups within medulloblastoma (MB). Further, in the 2021 classification, new subtypes have been provisionally added within the existing subgroups reflecting the biological diversity. YAP1, GAB1, and β-catenin were conventionally accepted as surrogate markers to identify these genetic subgroups.</jats:p></jats:sec><jats:sec><jats:title>Objectives:</jats:title><jats:p>We aimed to stratify MB into molecular subgroups using 3 immunohistochemical markers. <jats:italic toggle="yes">TP53</jats:italic> mutation was also assessed in Wingless (WNT), and Sonic Hedgehog (SHH) subgroups. Demographic profiles, imaging details, and survival outcomes were compared within these molecular subgroups.</jats:p></jats:sec><jats:sec><jats:title>Patients and methods:</jats:title><jats:p>Our cohort included 164 MB cases diagnosed over the last 10 years. The histologic variants were identified on histology, and tumors were molecularly stratified using YAP1, GAB1, and β-catenin. Further, <jats:italic toggle="yes">TP53</jats:italic> mutation was assessed using immunohistochemical in WNT and SHH subgroups. The clinical details and survival outcomes were retrieved from the records, and the mentioned correlates were evaluated statistically.</jats:p></jats:sec><jats:sec><jats:title>Results:</jats:title><jats:p>The age ranged from 1 to 52 years with M:F ratio of 2:1. Group 3/group 4 constituted the majority (48.4%), followed by SHH (45.9%) and WNT subgroups (5.7%). Desmoplastic/nodular and MB with extensive nodularity had the best survival, whereas large cell/anaplastic had the worst. The follow-up period ranged from 1 to 129 months. The best outcome was observed for the WNT subgroup, followed by the SHH subgroup; group 3/group 4 had the worst. Among the SHH subgroup, <jats:italic toggle="yes">TP53</jats:italic> mutant tumors had a significantly poorer outcome compared with <jats:italic toggle="yes">SHH-TP53</jats:italic> wildtype.</jats:p></jats:sec><jats:sec><jats:title>Conclusions:</jats:title><jats:p>Molecular stratification significantly contributes to prognostication, and a panel of 3 antibodies is helpful in stratifying MB into its subgroups in centers where access to advanced molecular testing is limited. Our study reinforces the efficacy of incorporating this cost-effective, minimal panel into routine practice for stratification. Further, we propose a 3-risk stratification grouping, incorporating morphology and molecular markers.</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • morphology
  • size-exclusion chromatography