Vectorial crystallization problems and collective behavior.

We propose and analyze a class of vectorial crystallization problems, with applications to crystallization of anisotropic molecules and collective behavior such as birds flocking and fish schooling. We focus on two-dimensional systems of "oriented" particles: Admissible configurations are represented by vectorial empirical measures with density in [Formula: see text]. We endow such configurations with a graph structure, where the bonds represent the "convenient" interactions between particles, and the proposed variational principle consists in maximizing their number. The class of bonds is determined by hard sphere type pairwise potentials, depending both on the distance between the particles and on the angles between the segment joining two particles and their orientations, through threshold criteria. Different ground states emerge by tuning the angular dependence in the potential, mimicking ducklings swimming in a row formation and predicting as well, for some specific values of the angular parameter, the so-called diamond formation in fish schooling.

Accelerating the experimental responses on cell behaviors: a long-term prediction of cell trajectories using Social Generative Adversarial Network.

The incremented uptake provided by time-lapse microscopy in Organ-on-a-Chip (OoC) devices allowed increased attention to the dynamics of the co-cultured systems. However, the amount of information stored in long-time experiments may constitute a serious bottleneck of the experimental pipeline. Forward long-term prediction of cell trajectories may reduce the spatial-temporal burden of video sequences storage. Cell trajectory prediction becomes crucial especially to increase the trustworthiness in software tools designed to conduct a massive analysis of cell behavior under chemical stimuli. To address this task, we transpose here the exploitation of the presence of "social forces" from the human to the cellular level for motion prediction at microscale by adapting the potential of Social Generative Adversarial Network predictors to cell motility. To demonstrate the effectiveness of the approach, we consider here two case studies: one related to PC-3 prostate cancer cells cultured in 2D Petri dishes under control and treated conditions and one related to an OoC experiment of tumor-immune interaction in fibrosarcoma cells. The goodness of the proposed strategy has been verified by successfully comparing the distributions of common descriptors (kinematic descriptors and mean interaction time for the two scenarios respectively) from the trajectories obtained by video analysis and the predicted counterparts.

The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications.

Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors' discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the computational models were experimentally confirmed by a series of video-microscopy acquisitions of co-cultures of unlabelled human cancer and immune cells embedded in 3D collagen gels within microfluidic devices. We argue that the experimental protocol of acquisition should be adapted to the specific kind of analysis involved and to the chosen descriptors in order to derive reliable conclusions and avoid biasing the interpretation of results.

Recent advances in superhydrophobic surfaces and their relevance to biology and medicine.

By mimicking naturally occurring superhydrophobic surfaces, scientists can now realize artificial surfaces on which droplets of a few microliters of water are forced to assume an almost spherical shape and an extremely high contact angle. In recent decades, these surfaces have attracted much attention due to their technological applications for anti-wetting and self-cleaning materials. Very recently, researchers have shifted their interest to investigate whether superhydrophobic surfaces can be exploited to study biological systems. This research effort has stimulated the design and realization of new devices that allow us to actively organize, visualize and manipulate matter at both the microscale and nanoscale levels. Such precise control opens up wide applications in biomedicine, as it allows us to directly manipulate objects at the typical length scale of cells and macromolecules. This progress report focuses on recent biological and medical applications of superhydrophobicity. Particular regard is paid to those applications that involve the detection, manipulation and study of extremely small quantities of molecules, and to those that allow high throughput cell and biomaterial screening.

Self-assembling of large ordered DNA arrays using superhydrophobic patterned surfaces.

In this paper we present a simple and robust method to realize highly ordered arrays of stretched and suspended DNA molecules over the millimeter length scale. To this end we used an ad hoc designed superhydrophobic surface made of high aspect-ratio silicon pillars, where we deposited a droplet containing genomic DNA. A precise positioning of DNA strands was achieved by shaping the silicon pillars so that sharpened features resembling tips were included. Such features allowed us to accurately control the droplet de-wetting dynamics, pinning DNA strands in a well-defined position above pillars. The proposed technique has the potential to positively impact on the development of novel DNA chips for genetic analysis.

Deprotonation of glutamic acid induced by weak magnetic field: an FTIR-ATR study.

It has been claimed that weak extremely low frequency electromagnetic fields (ELF-EMFs) can affect biochemical reactions and a wide-ranging body of literature is available on this topic. Nevertheless, the physical nature of these effects remains largely unknown. We investigated the influence of ELF-EMF on glutamic acid solutions using Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectra. Samples were exposed for 10, 20, or 30 min to a weak EMF generated by Helmoltz coils, and then placed in a spectrometer. After exposure, those solutions that had a pH lower than the isoelectric point tended to show a shift toward the deprotonation of the carboxylic group, while solutions having a pH greater than the isoelectric point showed the deprotonation of the residual amine group. Moreover, at low pH values, we also detected a shift of the δ(antisym) band of the amine. The effects lasted a few minutes after exposure before the native configuration was restored. The spectral modifications were observed after each independent exposure to EMFs, and the same effects were seen by varying the frequencies in the range of 0-7 kHz. Therefore, the hypothesis of the existence of a resonant frequency that has been proposed elsewhere cannot be supported by the results of this study. The most surprising characteristic of this effect is the long-lasting nature of the perturbation, which is hard to be explained in terms of short-living excitations in biological matter.

Dynamics of the ion cyclotron resonance effect on amino acids adsorbed at the interfaces.

In this study we show a reproduction of the Zhadin experiment, which consists of the transient increase of the electrolytic current flow across an aqueous solution of L-arginine and L-glutamic acid induced by a proper low frequency alternating magnetic field superimposed to a static magnetic field of higher strength. We have identified the mechanisms that were at the origin of the so-far poor reproducibility of the above effect: the state of polarization of the electrode turned out to be a key parameter. The electrochemical investigation of the system shows that the observed phenomenon involves the transitory activation of the anode due to ion cyclotron frequency effect, followed again by anode passivation due to the adsorption of amino acid and its oxidation products. The likely occurrence of similar ion cyclotron resonance (ICR) phenomena at biological membranes, the implications on ion circulation in living matter, and the consequent biological impact of environmental magnetic fields are eventually discussed.