Wearable Electrochemical Sensors: Toward Biochemical Lab on the Body
Wearable sensors have received a major recent attention owing to their considerable promise for monitoring the wearer’s health and wellness [1,2]. These devices have the potential to continuously and non-invasively collect vital and rich information from a person’s body and provide this information in a timely fashion. Capture such continuous molecular data from the human body will provide guidance towards optimal personal health and nutrition. This presentation will discuss our recent efforts toward filling the gaps toward obtaining biochemical information, beyond that given by common wrist-watch mobility trackers. Such real-time molecular information is achieved using advanced wearable electrochemical biosensors integrated directly on the epidermis or within the mouth. The design, operation and applications of such wearable bioelectronic sensors will be described, along with future prospects and challenges.
REFERENCES
[1] “Wearable Chemical Sensors: Present Challenges and Future Prospects” A. J. Bandodkar, I. Jeerapan, J. Wang, ACS Sensors, 2016, 1, 464.
[2] “Wearable biosensors for healthcare monitoring”, J. Kim, A. S. Campbell, B. Esteban-Fernández de Ávila, and J. Wang, Nature Biotechnology, 2019, 37, 389.
The importance of Machine Learning in the exploitation of Organ-on-chip experiments
A fascinating technological solution for conducting novel, reproducible, and massive biological experiments is represented by Organ-on-Chips (OoCs) microfluidic devices where specific aspects or characteristics of tissues or organs are mimicked. However, the difficulty of managing the vast amount of information available for this kind of device often limits its usefulness [1,2]. To accelerate the uptake of OoCs and lead to quantitative and reliable findings, an approach exploiting machine learning algorithms coupled with time-lapse microscopy and microfluidic devices is introduced. In this talk, we will discuss its potentialities through various case studies [2,3], corroborated by the investigation of robustness to external sources of variability related to technological set-up, to heterogeneity of the samples, and subjectivity due to operator-dependent procedures.
References:
[1] “Mencattini, A., Mattei, F., Schiavoni, G., Gerardino, A., Businaro, L., Di Natale, C., Martinelli, E.”, From petri dishes to organ on chip platform: The increasing importance of machine learning and image analysis, 2019, Frontiers in Pharmacology, 10, 100
[2]”Mencattini, A., Di Giuseppe, D., Comes, M.C., Casti, P., Corsi, F., Bertani, F.R., Ghibelli, L., Businaro, L., Di Natale, C., Parrini, M.C., Martinelli, E.”, Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments, 2020, Scientific Reports, 10, 1, 7653.
[3] “Comes, M.C., Filippi, J., Mencattini, A., Casti, P., Cerrato, G., Sauvat, A., Vacchelli, E., De Ninno, A., Di Giuseppe, D., D’Orazio, M., Mattei, F., Schiavoni, G., Businaro, L., Di Natale, C., Kroemer, G., Martinelli, E.”, Multi-scale generative adversarial network for improved evaluation of cell–cell interactions observed in organ-on-chip experiments, 2021, Neural Computing and Applications, 33, 8, 3671-3689.
Endoscopic Luminescent Imaging for Oncologic Surgery: the ELIOS project
ELIOS is a project funded by the French Foundation ARC (Association for Cancer Research). The focus of the ELIOS project is the optimization of radical removal of cancer of the gastrointestinal tract and the reduction of surgical complications by means of optical imaging. Innovations are targeted at various levels: 1) new smart dyes, 2) innovative hardware, and 3) innovative machine-learning and deep-learning powered image analysis. Additionally, an extensive activity on education and dissemination around intraoperative optical imaging is being carried out, with the aim to increase the widespread adoption of optical imaging and to standardize the procedures with the creation of patient registry and the organization of consensus conferences.
Optical Fiber Sensors for Various Applications
Due to light weight/small size, high sensitivity/large band width, long range operation, and harsh environment capability, optical fiber has gained immense attention in sensor field. The optical fiber sensor can be either intrinsic or extrinsic type considering the passage of light and optical modulation mechanism can be by intensity, phase, wavelength and polarization. It has been used to measure various chemical and physical properties, such as temperature, pH, pressure, humidity, flow rate, gas concentration, liquid level, radiation, displacement, vibration, and chemical species.
My group has developed optical fiber sensors for 5 applications: (1) Aerosol (2) VOCs (3) Biomolecule, (4) Radiation and (5) Force.
(1) To detect aerosol, TEOS and thymol blue (TB) were used for the preparation of silica cladding on optical fiber core. The coated optical fiber is found to be sensitive to composition of aerosol based on evanescent wave absorption. Moreover, conductive polymer, polypyrrole (PPy) thin film coated optical fiber was used for NaCl, PSL, and BC aerosol sensing. (2) PPy thin film coated optical fiber was used for VOCs sensor. Its detection limit is ~1 ppm level. Similarly, DNA and metal ion-modified DNA (M-DNA) coated on quart plate was used for VOCs sensor based on surface change. M-DNA is more sensitive than DNA for sensing. Additionally, Graphene oxide (GO) and reduced-GO (rGO) were coated on tip of optical fiber and used for detecting 8 kinds of VOCs. (3) Reusable PDMS waveguide-graphene FET hybrid sensor was developed for bio-molecular interaction monitoring. Its sensing mechanism is based on changing evanescent field. Moreover, graphene was used as a novel surface plasmon supporting material for highly sensitive biosensors. Graphene was also employed as composite material with MoS2 for synergetic effect. The MoS2-graphene composite was used for electrochemical sensor with increasing sensitivity of PTH hormone. (4) Alpha radiation can induce tracks on the surface of CR 39/ LR 115 film. These tracks can be detected by the change of reflection light intensity. Blue light (450 nm) was used for real-time measurement of radiation damage of the surface and compared with AFM measurement. Similarly, DNA this film was utilized to observe the damage of its surface by 241Am (Alpha radiation source) for radiation sensor. (5) Finally, FBG (Fiber Bragg Grating) was used for force sensor with flexure structure and its wavelength change was used for changing force and it can be applied to catheterization.
In this lecture, I will review previous results from my group and discuss about the future direction.
