Biofisica
Argomenti di ricerca
Spettroscopia e Microscopia con eccitazione non lineare della fluorescenza per applicazioni biomediche
G. Chirico, M. Collini, L. D'Alfonso, L. Sironi
Development of new methods for optical non-linear microscopy to be applied to biophysics and medical physics in-vivo. In this field the Biophotonics group is developing two-photon excitation fluorescence imaging microscopy and second harmonic generation microscopy. One of the main application aims to the study of the motion of lymphocytes in lymph nodes in order to model the immune response of mice. This work is being carried out in collaboration with the Biotechnology group of our University.
Ottica adattiva per imaging in mezzi opachi e in-vivo
G. Chirico, M. Bouzin, M. Marini, L. Sironi
La creazione di immagini in mezzi opachi ha applicazioni che vanno dall’ingegneria all’elettronica e alla medicina e biotecnologie. Il fronte d’onda della luce viene fortemente modificato dalle disomogeneita’ del mezzo in cui propaga, su un ampio intervallo di frequenze spaziali. Per potere correggere questi effetti si può fare uso di vari elementi riflessivi o diffrattivi programmabili come specchi deformabili o spatial light modulators. Lo scopo delle tesi proposte è quello di accoppiare queste tecnologie, in parte mutuate dall’astronomia osservativa, a tecniche di microscopia ottica per lo studio di tessuti sia in vitro che in-vivo.
Referenze:
Pozzi et al. J. of Biomedical Optics, 19(6), 067007 (2014) https://doi.org/10.1117/1.JBO.19.6.067007
Microfabbricazione laser di idrogel per applicazioni biomediche
G. Chirico, M. Collini, A.B. Zeynali, M. Marini
La fotopolimerizzazione può essere utilizzata per fabbricare idrogel per la coltura cellulare e l'ingegneria dei tessuti. In particolare sviluppiamo photoresists a base proteica per fabbricare, mediante laser o LED UV, microstrutture ad alto rapporto assiale (da 3 a 5) e di piccole dimensioni (da 30 μm a 50 μm). Utilizziamo sia sorgenti UV (385 nm) che laser pulsati nel vicino infrarosso (ampiezza dell'impulso di femtosecondi) per ottenere una scrittura ad alta risoluzione. Il laser viene scansionato sul resist per indurre la polimerizzazione o viene utilizzata una maschera davanti al LED UV. Questi metodi vengono utilizzati per fabbricare microstrutture che possono ospitare cellule per la coltura cellulare o essere impiantate in vivo per l'ingegneria dei tessuti.
Referenze:
Metodi di Intelligenza Artificiale per la digital pathology o le scienze ambientali
La fisica dei sistemi complessi, dalla biofisica alla Fisica Ambientale, necessita l’analisi di una notevole mole di dati che dipendono da numerosi parametri. Sono perciò numerosi gli ambiti in cui metodi di Machine Learning e di Intelligenza artificiale possono essere usate vantaggiosamente per organizzare i dati ottenuti e per cercare di formulare dei modelli chimico-fisici. Oltre a questo, il tentativo di simulare numericamente sistemi complessi, come il sistema immunitario, deve passare attraverso l’uso di metodi di active learning. Le tesi offerte in questo ambito vanno dallo sviluppo di sistemi di correzione di immagini prese nell’intervallo ottico (UV-NIR) sia in microscopia di tessuti che in monitoraggio ambientale e di immagini X-ray o PET, allo sviluppo di metodi di active learning per l’analisi di simulazioni numeriche del sistema immunitario.
Characterisation of the role of prometastatic MICAL2 on nuclear envelope and genome integrity through transcriptional control of Lamin A/C
12 months post-doc position on the project.
Background. Over 90% of cancer deaths are due to metastasis, but the efficacy of adjuvant therapy in reducing metastasis provide just a few months of survival advantage. To increase our therapeutic arsenal for a more effective metastasis prevention or treatment, we need new targets. Preliminary data suggest a positive interplay between the promoters of MICAL2, of LMNA and of other proteins of the nuclear envelope (NE). However, we need extensive validation of the results.
Aim. The aim is to 1) correlate the expression of MICAL2 and LMNA in determining NE composition and mechano- transduction in cancer cells; 2) correlate spatial genome organisation and epigenetic regulation in function of MICAL2 expression;3) develop in vitro platforms for these studies that avoid the use of lab animals.
Candidate role
- development of 2D and quasi 3D platforms for cell culturing with varying rigidity
- confocal and non-linear excitation imaging on cells and study of the effect to the rigidity on their growth.
Ideal candidate
- PhD in physics, engineering, biotechnology, or related fields.
- Experience in laser optics, preferably optical scanning microscopy.
The position
The position will start ideally around January 2024, pending official project start approval. The contract is a Gross salary 24000 Euro/year. The position is initially for one year with the possibility of an extension of 1 year.
Contacts. Giuseppe Chirico, Giuseppe.chirico@unimib.it
Funded by Progetto PRIN – Ministero dell’Università e Ricerca 2022. Collaborative project of Scuola Superiore Sant’Anna, Politecnico di Milano, and Università di Milano-Bicocca.
Post – doctoral position in image reconstruction
“Multiple Emission Tomography” Project
Background
The multiple emission tomography (MET) project is a cutting-edge research initiative funded by the ministry of university and research. The aim of the project is to design and build a novel device for medical imaging that can operate as both a positron emission tomography (PET) scanner and a single photon emission tomograph (SPECT) when using a “Compton camera” mode. This innovative feature allows the device to reconstruct inter-crystal scattering events in the detector, which can enhance the image quality and resolution. Without the need for a collimator, sensitivity can be increased by a factor greater than 100.
Therefore, the MET project has the potential to revolutionize the field of theranostics, especially for applications involving high gamma energy isotopes (e.g.: > 250 keV) or positron emitting isotopes that emit a coincident third gamma.
The project is a collaborative effort between the university of Milano-Bicocca and the Torino unit of the national institute of nuclear physics (INFN). The principal investigator is Luca Presotto, from Unimib. The Torino unit is responsible for developing the electronics readout system, while Unimib is in charge of creating the crystals assembly, simulating the device performance, and developing image reconstruction algorithms.
The integration of simulations and image reconstruction algorithms will enable the evaluation of the expected final performance of the hardware, as well as the exploration of its clinical usefulness.
Candidate role
The candidate will be involved in the development of image reconstruction algorithms for the MET device.
The main tasks of the candidate will be to:
- Develop simulations of the MET hardware
- Adapt Compton camera image reconstruction algorithms to the specifics of the MET device: very high sensitivity but very low resolution, both that need to be incorporated into the reconstruction.
- Estimate the optimal spatial resolution that can be theoretically achievable, by the device as a function of the detector design
The candidate will work closely with the PI and other researchers from Unimib and INFN, and will contribute to the scientific publications and presentations of the project results.
Ideal candidate
The ideal candidate should have the following qualifications and skills:
- PhD in physics, engineering, computer science, or related fields.
- Experience in image reconstruction algorithms, preferably tomographic ones
- Proficiency in programming languages such as Python or Matlab, and familiarity with software development tools and practices.
Desirable but not essential:
- Experience in GPU coding and/or in GATE/GEANT software for Monte Carlo simulations
The position
The position will start ideally around January 2024, pending official project start approval. The contract is a 2 year “assegno di ricerca” position with 30k€/year industry cost (approx. 1700€/month after taxes).
Contact: luca.presotto@unimib.it