Highly integrated polymeric microliquid flow controller for droplet microfluidics

Microfluidic applications demand accurate control and measurement of small fluid flows and volumes, and the majority of approaches found in the literature involve materials and fabrication methods not suitable for a monolithic integration of different microcomponents needed to make a complex Lab-on-a-Chip (LoC) system. The present work leads to a design and manufacturing approach for problem-free monolithic integration of components on thermoplastics, allowing the production of excellent quality devices either as stand-alone components or combined in a complex structures. In particular, a polymeric liquid flow controlling system (LFCS) at microscale is presented, which is composed of a pneumatic microvalve and an on-chip microflow sensor. It enables flow regulation between 30 and 230 μl/min with excellent reproducibility and accuracy (error lower than 5%). The device is made of a single Cyclic Olefin Polymer (COP) piece, where the channels and cavities are hot-embossed, sealed with a single COP membrane by solvent bonding and metalized, after sealing, to render a fully functional microfluidic control system that features on-chip flow sensing. In contrast with commercially available flow control systems, the device can be used for high-quality flow modulation in disposable LoC devices, since the microfluidic chip is low cost and replaceable from the external electronic and pneumatic actuators box. Functionality of the LFCS is tested by connecting it to a microfluidic droplet generator, rendering highly stable flow rates and allowing generation of monodisperse droplets over a wide range of flow rates. The results indicate the successful performance of the LFCS with significant improvements over existing LFCS devices, facing the possibility of using the system for biological applications such as generating distinct perfusion modes in cell culture, novel digital microfluidics. Moreover, the integration capabilities and the reproducible fabrication method enable straightforward transition from prototype to product in a way that is lean, cost-effective and with reduced risk

3-D polymeric microfluidic devices for BioMOEMS applications

11 páginas, 12 figuras.-- Trabajo presentado en la conferencia "Bioengineered and Bioinspired Systems II"; Sevilla (España); 09-Mayo-2005; Editores: Ricardo A. Carmona, Gustavo Linan-Cembrano.This paper describes the fabrication, packaging and characterization of novel multilayer polymer microfluidic systems fabricated by a CMOS compatible process. These microfluidic devices were specially designed for BioMOEMS applications. Embedded multilayer rectangular smooth and uniform microchannels, 50 to 150 mm wide and 18mm deep were studied. Steady-state flow rates and pressure driven flow control were measured in the laminar flow regime. Flow rates ranging from 1 to 100 µl/min, at pressure drop ranging from 10 to 600 kPa, were obtained. These flow rates yield Reynolds numbers (Re) up to 20. Results indicate that the experimental Re and the flow friction coefficient (f) are in good agreement with the laminar flow theory. These experimental results facilitate the future designs of different microfluidic devices designed by using classical fluidic theory. We also present two different methods developed for macro/microfluidic packaging in order to connect these microfluidic devices to the macroscopic world. The microsystem packaging can withstand pressure drops up from 500 to 2000 kPa with any liquid leakage.This research is sponsored by the Basque and Spanish Governments, under the Torres Quevedo Spanish Fellowship for industrial research and the strategic research program on micro and nanotechnologies (MICROGUNE).Peer reviewe

Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia

This paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available

Lab-on-a-chip platforms based on highly sensitive nanophotonic Si biosensors for single nucleotide DNA testing

In order to solve the drawbacks of sensitivity and portability in optical biosensors we have developed ultrasensitive and miniaturized photonic silicon sensors able to be integrated in a "lab-on-a-chip" microsystem platform. The sensors are integrated Mach-Zehnder interferometers based on TIR optical waveguides (Si/SiO2/Si3N4) of micro/nanodimensions. We have applied this biosensor for DNA testing and for detection of single nucleotide polymorphisms at BRCA-1 gene, involved in breast cancer development, without target labeling. The oligonucleotide probe is immobilized by covalent attachment to the sensor surface through silanization procedures. The hybridization was performed for different DNA target concentrations showing a lowest detection limit at 10 pM. Additionally, we have detected the hybridization of different concentrations of DNA target with two mismatching bases corresponding to a mutation of the BRCA-1 gene. Following the way of the lab-on-a-chip microsystem, integration with the microfluidics has been achieved by using a novel fabrication method of 3-D embedded microchannels using the polymer SU-8 as structural material. The optofluidic chip shows good performances for biosensing

SU-8 Based Microdevices to Study Self-Induced Chemotaxis in 3D Microenvironments

Tissues are complex three-dimensional structures in which cell behavior is frequently guided by chemotactic signals. Although starvation and nutrient restriction induce many different chemotactic processes, the recreation of such conditions in vitro remains difficult when using standard cell culture equipment. Recently, microfluidic techniques have arisen as powerful tools to mimic such physiological conditions. In this context, microfluidic three-dimensional cell culture systems require precise control of cell/hydrogel location because samples need to be placed within a microchamber without obstruction of surrounding elements. In this article, SU-8 is studied as structural material for the fabrication of complex cell culture microdevices due to its good mechanical properties and sensor integration capacity. Moreover, SU-8 physical properties and their effect on a successful design for precise control of hydrogel location within microfluidic devices are studied. In particular, this manuscript presents a SU-8 based microdevice designed to create “self-induced” medium starvation, based on the combination of nutrient restriction and natural cell metabolism. Results show a natural migratory response toward nutrient source, showing how cells adapt to their own microenvironment modifications. The presented results demonstrate the SU-8 potential for microdevice fabrication applied to cell culture

Hybrid MSRM-based deep learning and multitemporal Sentinel 2-based machine learning algorithm detects near 10k archaeological tumuli in north-western Iberia

This is the final version. Available on open access from MDPI via the DOI in this record.Data Availability Statement: All relevant material has been made available as Supplementary MaterialsThis paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available.European Union Horizon 2020Spanish Ministry of Science, Innovation and UniversitiesFundación BBV

Glioblastoma on a microfluidic chip: Generating pseudopalisades and enhancing aggressiveness through blood vessel obstruction events

Background: Glioblastoma (GBM) is one of the most lethal tumor types. Hypercellular regions, named pseudo- palisades, are characteristic in these tumors and have been hypothesized to be waves of migrating glioblastoma cells.These “waves” of cells are thought to be induced by oxygen and nutrient depletion caused by tumor-induced blood vessel occlusion. Although the universal presence of these structures in GBM tumors suggests that they may play an instrumental role in GBM’s spread and invasion, the recreation of these structures in vitro has remained challenging. Methods: Here we present a new microfluidic model of GBM that mimics the dynamics of pseudopalisade forma- tion.To do this, we embedded U-251 MG cells within a collagen hydrogel in a custom-designed microfluidic device. By controlling the medium flow through lateral microchannels, we can mimic and control blood-vessel obstruction events associated with this disease. Results: Through the use of this new system, we show that nutrient and oxygen starvation triggers a strong migratory process leading to pseudopalisade generation in vitro.These results validate the hypothesis of pseudo- palisade formation and show an excellent agreement with a systems-biology model based on a hypoxia-driven phenomenon. Conclusions: This paper shows the potential of microfluidic devices as advanced artificial systems capable of mod- eling in vivo nutrient and oxygen gradients during tumor evolution

Severity dependent distribution of impairments in PSP and CBS: Interactive visualizations

BACKGROUND: Progressive supranuclear palsy (PSP) -Richardson's Syndrome and Corticobasal Syndrome (CBS) are the two classic clinical syndromes associated with underlying four repeat (4R) tau pathology. The PSP Rating Scale is a commonly used assessment in PSP clinical trials; there is an increasing interest in designing combined 4R tauopathy clinical trials involving both CBS and PSP. OBJECTIVES: To determine contributions of each domain of the PSP Rating Scale to overall severity and characterize the probable sequence of clinical progression of PSP as compared to CBS. METHODS: Multicenter clinical trial and natural history study data were analyzed from 545 patients with PSP and 49 with CBS. Proportional odds models were applied to model normalized cross-sectional PSP Rating Scale, estimating the probability that a patient would experience impairment in each domain using the PSP Rating Scale total score as the index of overall disease severity. RESULTS: The earliest symptom domain to demonstrate impairment in PSP patients was most likely to be Ocular Motor, followed jointly by Gait/Midline and Daily Activities, then Limb Motor and Mentation, and finally Bulbar. For CBS, Limb Motor manifested first and ocular showed less probability of impairment throughout the disease spectrum. An online tool to visualize predicted disease progression was developed to predict relative disability on each subscale per overall disease severity. CONCLUSION: The PSP Rating Scale captures disease severity in both PSP and CBS. Modelling how domains change in relation to one other at varying disease severities may facilitate detection of therapeutic effects in future clinical trials