AI Creates New ‘Alarm Bells’ for Prostate Cancer Recurrence
A study by Human Technopole, the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust in London has shown that in prostate cancer the presence in the same tumour of cells with large differences in shape and genetic composition indicates an increased risk of relapse, including after a decade. The study may help doctors better tailor treatment for this disease, adopting more aggressive therapies in cases where these parameters indicate a higher risk of disease recurrence.
HT’s “Open” Technologies for the Italian Scientific Community
Human Technopole is opening its National Facilities, providing advanced equipment and technologies accessible through calls for proposals open to the Italian scientific community. Projects will be selected by a commission of international experts. Scientists will have access to five new dedicated facilities, which act as catalysts for open innovation in the life sciences sector, crucial for research and the health of Italians.
Clearer microscopy images in spatial biology
An international team of scientists led by HT researchers Magda Bienko and Nicola Crosetto developed an open-source software for deconvolution of widefield fluorescence microscopy image stacks and large tissue scans. This new tool increases the information obtained with fluorescence microscopy-based spatial omic methods.
Genetics study points to potential treatments for restless leg syndrome
HT researchers are part of an international team of scientists that discovered genetic clues to the cause of restless leg syndrome, a condition common among older adults. The finding could help identify those individuals at greatest risk of the condition and point to potential ways to treat it.
4 PhD opportunities at HT through DADS
Human Technopole (HT) is glad to announce the availability of 4 new fully funded PhD positions in the fields of Health Data Science, Population and Medical Genomics and Computational Biology. These positions aim to attract highly motivated graduates with strong academic backgrounds who are interested in cutting-edge research in data science.