Design of transfections: Implementation of design of experiments for cell transfection fine tuning.

Transfection is the process by which nucleic acids are introduced into eukaryotic cells. This is fundamental in basic research for studying gene function and modulation of gene expression as well as for many bioprocesses in the manufacturing of clinical-grade recombinant biologics from cells. Transfection efficiency is a critical parameter to increase biologics' productivity; the right protocol has to be identified to ensure high transfection efficiency and therefore high product yield. Design of experiments (DoE) is a mathematical method that has become a key tool in bioprocess development. Based on the DoE method, we developed an operational flow that we called "Design of Transfections" (DoT) for specific transfection modeling and identification of the optimal transfection conditions. As a proof of principle, we applied the DoT workflow to optimize a cell transfection chemical protocol for neural progenitors, using polyethyleneimine (PEI). We simultaneously varied key influencing factors, namely concentration and type of PEI, DNA concentration, and cell density. The transfection efficiency was measured by fluorescence imaging followed by automatic counting of the green fluorescent transfected cells. Taking advantage of the DoT workflow, we developed a new simple, efficient, and economically advantageous PEI transfection protocol through which we were able to obtain a transfection efficiency of 34%.

A computational framework for the standardization of motion analysis exploiting wearable inertial sensors.

Movement analysis is a powerful tool for the diagnosis of neurological conditions, as well as patient assessment and follow-up during rehabilitation programs. In spite of the available systems allowing a quantitative analysis of a subject's movement control performances, the clinical assessment and diagnostic approach still relies mostly on non-quantitative exams, such as clinical scales. Further, studying balance control, gait and activities of daily living poses relevant technical challenges, which greatly limit the availability of testing facilities. The goal of our project was therefore to develop a new system based on wearable sensors for movement analysis and scoring of performances. A prototype 3-sensors system was tested on a group of 4 normal subjects while carrying out a set of full body movement exercises drawn by clinical scales for the assessment of movement and balance control.

Predicting losses of balance during upright stance: evaluation of a novel approach based on wearable accelerometers.

The study of postural sway during quiet stance has proved to be a useful approach to investigate the function of the balance system. Recent studies have suggested that providing information on postural sway to vestibular patients through biofeedback may improve their balance awareness and therefore reduce their risk of falling. One drawback common to these approaches is related to timing: informing a patient about current balance conditions may not allow enough time to react and avoid a fall. Here we propose a new technique for predicting relevant balance related events based on the recording of inertial information on trunk and thigh movement using wearable devices. We have developed a regressive model for the prediction of quiet stance dynamics of the center of body mass (CM), based on these sensory data. Our preliminary results show that, with careful signal processing, such approach may allow to learn quiet stance dynamics based on the inverted pendulum model and use it in predicting critical balance conditions with a few hundreds of milliseconds advance. When these predictions are then used for event-detection the system provides accurate results and is thus promising for the development of a fall prevention device.