Health Research Hub
Scientific exchange and collaboration are key to successful research.
With the newly founded Health Research Hub, we establish and promote interdisciplinary research in the field of health. Embedded within the department of life sciences and facility management (LSFM) and driven by researchers from each institute, the Health Research Hub
- connects different research groups within ZHAW
- stimulates their cooperation
- and creates a network around health-related research.
The Health Research Hub promotes synergies by structuring health-related research and by supporting collaborative projects. Joining forces across institutes encourages thinking across borders and advances innovative health-related research, while being cost-efficient at the same time.
Constantly rising costs in the healthcare sector require economic action without compromising the quality of care. In this project, extensive data collected from various hospitals is examined. The resulting models in the form of Bayesian networks will allow conclusions about hidden relationships and contribute to productivity and sustainability in health institutions.
Literature Based Discovery (LBD) has become widespread, but little has been done to automate it in the field of Natural Product Drug Discovery. The goal of this project is to devise an automated LBD system for natural product drugs for new discoveries, but also to query and explore present knowledge.
Bacteriophages are bacterial viruses that are attracting increasing attention worldwide as a promising alternative to conventional antibiotics. The goal of this project is to genetically engineer bacteriophages for a better control of pathogenic Escherichia coli (E. coli) and to further develop large-scale phage production technologies.
Ticks are currently on the rise and transmit several infectious diseases. A team of ZHAW experts in geographical information systems, artificial intelligence, data science and in tick biology develop a spacio-temporal tick risk model to help reducing the risk of tick-borne diseases.
Dramatic worldwide increase in antibiotic resistance to human pathogens is of great concern. Bacteriophages selectively kill bacteria and present an alternative to antibiotics. An expert team at ZHAW investigates interactions between bacteriophages and bacteria on a molecular level.
Food safety has become a major challenge within crops in recent years: an estimated 25% of all global crops are affected by moulds. This project aims at developing solutions to reduce mycotoxins in grain through the application of functional microorganisms and / or tailored enzymes.
Bio-protection of meat and fish products (LISTprotect)
Breakfast cereals by extrusion of fermented milling by-products
By-products of the milling process are traditionally transferred to the production of feed and thus lost in the human food chain. This project is a feasability study, in which a two-phasic approach for the production of cereals dervied from milling by-products will be evaluated: 1) microbial fermentation of the ...
MycoTOF -Determining mycotoxigenic molds and mycotoxins
Food spoilage by molds is a very important issue, since molds negatively influence the food quality and safety, due to mycotoxin synthesis. Apart from being allergens or irritants, some of the health effects of mycotoxins found in animals and humans include death, identifiable diseases or health problems, or ...
Offices, Change & Health
Development of antifungal protective cultures for cocoa bean fermentation
Herter-Aeberli, Isabelle; Wehrli, Nina; Bärlocher, Kurt; Andersson, Maria; Sych, Janice Marie ,
Available from : https://doi.org/10.3390/nu12123729
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from : https://doi.org/10.21256/zhaw-21153
European Journal of Nutrition.
Available from : https://doi.org/10.1007/s00394-020-02399-7
Public Health Nutrition.
Available from : https://doi.org/10.1017/S1368980020003079
Schilling, Frank-Peter; Stadelmann, Thilo, eds. ,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Lecture Notes in Computer Science ; 12294.
Available from : https://doi.org/10.1007/978-3-030-58309-5_16
The Health Research Hub is driven by a scientific committee and supported by a programme manager: