A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection.

This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master-slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices' multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis.

A Regression Approach to Model Refractive Index Measurements of Novel 3D Printable Photocurable Resins for Micro-Optofluidic Applications.

In this work, a quadratic polynomial regression model was developed to aid practitioners in the determination of the refractive index value of transparent 3D printable photocurable resins usable for micro-optofluidic applications. The model was experimentally determined by correlating empirical optical transmission measurements (the dependent variable) to known refractive index values (the independent variable) of photocurable materials used in optics, thus obtaining a related regression equation. In detail, a novel, simple, and cost-effective experimental setup is proposed in this study for the first time for collecting the transmission measurements of smooth 3D printed samples (roughness ranging between 0.04 and 2 µm). The model was further used to determine the unknown refractive index value of novel photocurable resins applicable in vat photopolymerization (VP) 3D printing techniques for manufacturing micro-optofluidic (MoF) devices. In the end, this study proved how knowledge of this parameter allowed us to compare and interpret collected empirical optical data from microfluidic devices made of more traditional materials, i.e., Poly(dimethylsiloxane) (PDMS), up to novel 3D printable photocurable resins suitable for biological and biomedical applications. Thus, the developed model also provides a quick method to evaluate the suitability of novel 3D printable resins for MoF device fabrication within a well-defined range of refractive index values (1.56; 1.70).

Cell counting and velocity algorithms for hydrodynamic study of unsteady biological flows in micro-channels.

In this paper, the combination of two algorithms, a cell counting algorithm and a velocity algorithm based on a Digital Particle Image Velocimetry (DPIV) method, is presented to study the collective behavior of micro-particles in response to hydrodynamic stimuli. A wide experimental campaign was conducted using micro-particles of different natures and diameters (from 5 to 16 µ m ), such as living cells and silica beads. The biological fluids were injected at the inlet of a micro-channel with an external oscillating flow, and the process was monitored in an investigated area, simultaneously, through a CCD camera and a photo-detector. The proposed data analysis procedure is based on the DPIV-based algorithm to extrapolate the micro-particles velocities and a custom counting algorithm to obtain the instantaneous micro-particles number. The counting algorithm was easily integrated with the DPIV-based algorithm, to automatically run the analysis to different videos and to post-process the results in time and frequency domain. The performed experiments highlight the difference in the micro-particles hydrodynamic responses to external stimuli and the possibility to associate them with the micro-particles physical properties. Furthermore, in order to overcome the hardware and software requirements for the development of a real-time approach, it was also investigated the possibility to detect the flows by photo-detector signals as an alternative to camera acquisition. The photo-detector signals were compared with the velocity trends as a proof of concept for further simplification and speed-up of the data acquisition and analysis. The algorithm flexibility underlines the potential of the proposed methodology to be suitable for real-time detection in embedded systems.

Cortical networks underlying successful control of nociceptive processing using real-time fMRI.

Real-time fMRI (rt-fMRI) enables self-regulation of neural activity in localized brain regions through neurofeedback. Previous studies showed successful up- and down-regulation of neural activity in the anterior cingulate cortex (ACC) and the insula (Ins) during nociceptive stimulation. Such self-regulation capacity is, however, variable across subjects, possibly related to the ability of cognitive top-down control of pain. Moreover, how specific brain areas interact to enable successful regulation of nociceptive processing and neurofeedback-based brain modulation is not well understood. A connectivity analysis framework in the frequency domain was used to examine the up- or down-regulation in the ACC and Ins and pain intensity and unpleasantness ratings were assessed. We found that successful up- and down-regulation was mediated by the ACC and by its functional connectivity with the Ins and secondary somatosensory cortex. There was no significant relationship between successful up- or downregulation and pain ratings. These findings demonstrate functional interactions between brain areas involved in nociceptive processing during regulation of ACC and Ins activity, and the relevance of the frequency domain connectivity analysis for real-time fMRI. Moreover, despite successful neural regulation, there was no change in pain ratings, suggesting that pain is a complex perception, which may be more difficult to modify than other sensory or emotional processes.

3D Printing Manufacturing of Polydimethyl-Siloxane/Zinc Oxide Micro-Optofluidic Device for Two-Phase Flows Control.

Tailored ZnO surface functionalization was performed inside a polydimethyl-siloxane (PDMS) microchannel of a micro-optofluidic device (mofd) to modulate its surface hydrophobicity to develop a method for fine tuning the fluid dynamics inside a microchannel. The wetting behavior of the surface is of particular importance if two different phases are used for system operations. Therefore, the fluid dynamic behavior of two immiscible fluids, (i) air-water and (ii) air-glycerol/water in PDMS mofds and ZnO-PDMS mofds was investigated by using different experimental conditions. The results showed that air-glycerol/water fluid was always faster than air-water flow, despite the microchannel treatment: however, in the presence of ZnO microstructures, the velocity of the air-glycerol/water fluid decreased compared with that observed for the air-water fluid. This behavior was associated with the strong ability of glycerol to create an H-bond network with the exposed surface of the zinc oxide microparticles. The results presented in this paper allow an understanding of the role of ZnO functionalization, which allows control of the microfluidic two-phase flow using different liquids that undergo different chemical interactions with the surface chemical terminations of the microchannel. This chemical approach is proposed as a control strategy that is easily adaptable for any embedded micro-device.

3D-Printed micro-optofluidic device for chemical fluids and cells detection.

In this work, it is presented a micro-optofluidic flow detector used for on-chip biological and chemical samples investigation. It is made in Poly-dimethyl-siloxane using a master-slave approach based on the 3D-Printing techniques. The micro-optofluidic device is made by assembling a microfluidic T-junction with a micro-optical section that consists of two optical fiber insertions and a PDMS gold-spattered micro-waveguide. The working principle in the detection is based on a different light transmission correlated to the fluid interfering with the laser beam in a micro-channel section. The proposed solution allows to realize a PDMS micro-device taking the advantage of 3D- Printing and goes beyond the restriction in the material selection. The device's performances were tested in the fluids detection and in the evaluation of the cell concentrations. Additionally, the micro-device was used as a real-time two-phase fluids flow detector. The two-phases flows were successfully monitored in different experimental conditions, varying both hydrodynamic and optical external stimuli.

Real-Time Detection of Slug Velocity in Microchannels.

Microfluidics processes play a central role in the design of portable devices for biological and chemical samples analysis. The bottleneck in this technological evolution is the lack of low cost detection systems and control strategies easily adaptable in different operative conditions, able to guarantee the processes reproducibility and reliability, and suitable for on-chip applications. In this work, a methodology for velocity detection of two-phase flow is presented in microchannels. The approach presented is based on a low-cost optical signals monitoring setup. The slug flow generated by the interaction of two immiscible fluids {air and water} in two microchannels was investigated. To verify the reliability of the detection systems, the flow nonlinearity was enhanced by using curved geometries and microchannel diameter greater than 100 µ m . The optical signals were analyzed by using an approach in a time domain, to extract the slug velocity, and one in the frequency domain, to compute the slug frequency. It was possible to distinguish the water and air slugs velocity and frequency. A relation between these two parameters was also numerically established. The results obtained represent an important step in the design of non-invasive, low-cost portable systems for micro-flow analysis, in order to prove that the developed methodology was implemented to realize a platform, easy to be integrated in a System-on-a-Chip, for the real-time slug flow velocity detection. The platform performances were successfully validated in different operative conditions.

Time trend prevalence of artificial nutrition counselling in a university hospital.

OBJECTIVES: The negative effects of malnutrition on the prognosis of hospitalized patients are well documented; however, less known is the awareness and knowledge of health care professionals about this complication. The aim of this study was to evaluate the trend of the requests for nutritional consultation in years and the prescription of artificial nutrition (AN), for adult patients at a university hospital in southern Italy in the years 2004, 2008, 2012, and 2016 to assess the progress of medical teams concerning awareness of hospital malnutrition. METHODS: This was a retrospective study that evaluated the time trend of nutritional consultation requests and related prescription of AN, for adult patients at a university hospital in southern Italy in the years 2004, 2008, 2012, and 2016. Of 112 233 inpatients, 2505 received a nutritional consultation with the prescription of AN. RESULTS: The number of patients on AN increased from 507 of 33 240 (1.52%) in 2004 to 730 of 29 195 (2.5%) in 2008 (P < 0.001), remaining almost stable in 2012 and 2016. The request for AN was quite equally distributed between surgical (51.5%) and medical wards (48.5%), with a prevalence among patients with oncologic diseases (806 patients [65.6%]). As for nononcologic diseases, 20.4% involved the gastrointestinal tract and 6.3% the nervous system. Throughout the 12 y of observation, parenteral nutrition was the main prescribed support (59.8%) followed by oral nutritional supplements (26.1%) and enteral nutrition (9.3%). Mean nutritional intervention duration was 11 d (±10.8 d). CONCLUSIONS: The request of AN for hospitalized patients increased over time, probably owing to improved medical consciousness of the potential risks for malnutrition and the availability of a specialized clinical nutrition team.