PřF:SumSci Summer Internships - Course Information

SumSci Summer Internships in laboratories of Faculty of Science

Extent and Intensity

0/0/40. 20 credit(s). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).

Teacher(s)

Mgr. Michaela Kuchynka, Ph.D. (seminar tutor)
RNDr. Iva Sovadinová, Ph.D. (seminar tutor)
Ioannis Spyroglou, Ph.D. (seminar tutor)

Guaranteed by

prof. RNDr. Luděk Bláha, Ph.D.
Faculty of Science
Contact Person: Bc. Klára Sylla
Supplier department: Faculty of Science

Course Enrolment Limitations

The course is offered to students of any study field.

Syllabus (in Czech)

• Mgr. Michaela Kuchynka, Ph.D. - Department of Chemistry, Faculty of Science, Department of Applied Pharmacy
  Topic: Study the effectiveness of anticancer drugs
  Description of the Project: This project is focused on imaging of elements/metals in biological tissues by a unique method - laser ablation with inductively coupled plasma and mass spectrometry (LA-ICP-MS) after anticancer drug treatment. In the last decades increased interest in imaging of these elements/metals distribution, mainly in pharmaceutical, biomedicine research, or life science with application to specific problem/disease. The effectiveness of treatment concerning e.g. targeted release of drug will be investigated by the determination and imaging of the amount of metals from metal-based drugs in tumor tissues.
  Requirements: some experience work in a chemical laboratory, interest in research activities

• RNDr. Iva Sovadinová, Ph.D. - RECETOX
  Topic: 3D models for chronic liver toxicity assessment
  Description of the Project: Nonalcoholic fatty liver disease (NAFLD), fat accumulation in the liver caused by factors other than alcohol, is the most common metabolic disease, which afflicts 20%–30% of people in the global population and having a 50% prevalence in obese people. NAFLD can result in life-threatening conditions such as cirrhosis and liver cancer. Therefore, an understanding of factors that promote its development and pathological progression is needed. Chemical exposures represent one class of environmental risk factors that might promote NAFLD. In vitro cultures of mammalian cells provide a valuable tool for assessment of chemical effects and their links to adverse health outcomes. Three-dimensional (3D) cultures, which more closely mimic in vivo like microenvironment due to more intense cell-cell and cell-extracellular matrix interactions, have been recognized as a successful strategy to improve physiological relevance of liver in vitro models. Within this project, an advanced 3D liver in vitro model will be used for screening chemicals that are able to induce chronic liver toxicity and contribute to the development of chronic liver diseases, namely hepatic steatosis, an accumulation of fat in the liver. This research project will be directly connected with the currently running H2020 project OBERON (“An integrative strategy of testing systems for identification of EDs related to metabolic disorders”) and national GACR project (GA19-19143S). Both projects focus on the role of toxic exposures in development of chronic liver toxicities and diseases. The internship is planned with the goal to acquire original experimental results, which could be eventually presented at an international conference and submitted for publication with the student listed as a co-author.
  RECETOX, the department of Faculty of Science, Masaryk University, where the project will be undertaken, is internationally recognized for the research on the impact of chemical exposures on human health. RECETOX has excellent facilities and infrastructure to offer a first-rate environment for training and transfer of knowledge to the student. Assoc. Prof. Pavel Babica is an internationally recognized scientist and expert in the research and development of in vitro models and their use for studying health-related effects of chemicals with an extensive international experience. He is leading the research group “Cell and Tissue Toxicology” at the RECETOX. His students routinely travel for internships into collaborating labs, while his research group is often hosting students from other Czech or international universities.
  The student will be a part of the research group “Cell and Tissue Toxicology” (secantox.weebly.com) and will be actively involved in the process of scientific inquiry and discovery. She/he will have wide-ranging opportunities to gain theoretical as well as hands-on experiences with sterile cell culturing, hepatospheroid preparation and characterization, toxicity assessment using 3D in vitro models, and microscopy and image-based analysis. She/he will work with a current PhD candidate in the lab and weekly will discuss her/his progress with the supervisor and consultant.
  Requirements:
  • Highly motivated student with interest in toxicology and/or in vitro biomedical research
  • Students from biology, chemistry or ecology and similar fields of study are welcome
  

• Ioannis Spiroglou, Ph.D. - CEITEC
  Topic: Biostatistics and bioinformatics methods in phenotypic data analysis in biology and agriculture
  Description of the Project: Biostatistical and bioinformatics research.
  Advanced biostatistical data evaluation in plant phenotyping.
  The main focus of the work will be formulating biological relevant conclusions based on the detailed statistical analysis of any kind of plant datasets (phenotypic data, chemical kinetics, fluorescence and chlorophyll data, agricultural data, genomics, and others) generated by breeding companies and automated plant phenotyping facility.
  The last food crisis in the '60s was successfully overcome via the innovative use of plant breeding, also called ‘the 1st green revolution’. Considering the recent prognosis predicting a substantial deficit of food production as soon as from 2027, the ‘2nd green revolution’ which will be based on artificial intelligence and data mining must not be postponed. Possible model plants that are examined are Arabidopsis Thaliana and wheat. Some of the methods that can be used among others to analyse data are:
  Machine Learning methods, Regression analysis, ANOVA, Mixed regression models, Bayesian analysis, Clustering.
  During and after this project, the trainee will be able to:
  • perform simple and complex statistical analysis of various types of data,
  • improve R and Matlab/Python programming skills.
  • produce scientific outcomes based on statistical analysis.
  • To interpret prediction models.
  • Substantially improve knowledge on probabilities and statistics.
  Requirements:
  • Interest in computational statistics
  • Basic programming experience preferably with R/Matlab/Python
  • Strong English language skills – both spoken and written
  • Highly motivated to achieve a scientific goal
  

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught only once.
Information on the per-term frequency of the course: 14.6. - 30.7. 2021.
The course is taught: in blocks.
Note related to how often the course is taught: 14.6. - 30.7. 2021.

• Enrolment Statistics (Spring 2021, recent)
  
• Permalink: https://is.muni.cz/course/sci/spring2021/SumSci