Cell response to exogenous cues is the result of a complex integration of multiple biochemical/biophysical signals, which might occur simultaneously and might be characterized by specific spatial and temporal patterns. Among these signals, surface topography plays an important role in affecting cell functions and fate. However, the current understanding of the interplay between cells and topography relies on static environment. Here the intrinsic light-responsive properties of azopolymers and the versatility of laser-based confocal microscope technique is exploited, aiming to induce spatio-temporal dynamic topographic changes in situ during cell culture. Diverse patterns can be designed on cell-populated azopolymer films with high control on time, space, and on-off signal modification. The technique proposed in this study enables the development of synthetic platforms that finely control cell orientation and migration both in time and space. The results may pave the way to unravel complex processes involved in cell-topography interactions, thus allowing to define the spatio-temporal features that most effectively influence cell functions

Biophysical and biochemical signals of material surfaces potently regulate cell functions and fate. In particular, micro- and nano-scale patterns of adhesion signals can finely elicit and affect a plethora of signaling pathways ultimately affecting gene expression, in a process known as mechanotransduction. Our fundamental understanding of cell-material signals interaction and reaction is based on static culturing platforms, i.e., substrates exhibiting signals whose configuration is time-invariant. However, cells in-vivo are exposed to arrays of biophysical and biochemical signals that change in time and space and the way cells integrate these might eventually dictate their behavior. Advancements in fabrication technologies and materials engineering, have recently enabled the development of culturing platforms able to display patterns of biochemical and biophysical signals whose features change in time and space in response to external stimuli and according to selected programmes. These dynamic devices proved to be particularly helpful in shedding light on how cells adapt to a dynamic microenvironment or integrate spatio-temporal variations of signals. In this work, we present the most relevant findings in the context of dynamic platforms for controlling cell functions and fate in vitro. We place emphasis on the technological aspects concerning the fabrication of platforms displaying micro- and nano-scale dynamic signals and on the physical-chemical stimuli necessary to actuate the spatio-temporal changes of the signal patterns. In particular, we illustrate strategies to encode material surfaces with dynamic ligands and patterns thereof, topographic relieves and mechanical properties. Additionally, we present the most effective, yet cytocompatible methods to actuate the spatio-temporal changes of the signals. We focus on cell reaction and response to dynamic changes of signal presentation. Finally, potential applications of this new generation of culturing systems for in vitro and in vivo applications, including regenerative medicine and cell conditioning are presented.

Material signals in the form of surface topographies, proved to be potent regulators of cell functions and fate, through mechanotransduction pathways. While a wealth of data is related to regular topographic patterns, i.e., lines, pit, or protrusions, there are comparatively few studies addressing the effects of circular, concentric patterns. Yet, curvatures affecting cell shape dramatically alter cell contractility and behavior. Additionally, the vast majority of patterned surfaces are static in nature and this prevents to understand how cells perceive and respond to the topographic patterns. Here, a technique is exploited for dynamically embossing micrometerscale circular pattern on azopolymeric substrates using a confocal laser microscope and it is analyzed how NIH‐3T3 reacts to the underlying topography in terms of changes in shape and mechanical properties. A characteristic pattern arrangement is found which most effectively alters cell morphology and orientation. Cells perceive the concentric pattern and reconfigure as fast as 2 h after pattern inscription. The changes in morphology also reflect dramatic changes in cell mechanics and cytoskeletal arrangements. The reported method is useful to manipulate cell shape and mechanics in a facile and cost‐effective manner and most importantly enables investigate mechanotransduction events dynamically.

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision.

<abstract> <p>The use of different types of Clinical Decision Support Systems (CDSS) makes possible the improvement of the quality of the therapeutic and diagnostic efficiency in health field. Those systems, properly implemented, are able to simulate human expert clinician reasoning in order to suggest decisions on treatment of patients. In this paper, we exploit fuzzy inference machines to improve the quality of the day-by-day clinical care of type-2 diabetic patients of Anti-Diabetes Centre (CAD) of the Local Health Authority ASL Naples 1 (Naples, Italy). All the designed functionalities were developed thanks to the experience on the field, through different phases (data collection and adjustment, Fuzzy Inference System development and its validation on real cases) executed by an interdisciplinary research team comprising doctors, clinicians and IT engineers. The proposed approach also allows the remote monitoring of patients' clinical conditions and, hence, can help to reduce hospitalizations.</p> </abstract>

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