A fully integrated microfluidic genetic analysis system with sample-in-answer-out capability

We describe a microfluidic genetic analysis system that represents a previously undescribed integrated microfluidic device capable of accepting whole blood as a crude biological sample with the endpoint generation of a genetic profile. Upon loading the sample, the glass microfluidic genetic analysis system device carries out on-chip DNA purification and PCR-based amplification, followed by separation and detection in a manner that allows for microliter samples to be screened for infectious pathogens with sample-in-answer-out results in < 30 min. A single syringe pump delivers sample/reagents to the chip for nucleic acid purification from a biological sample. Elastomeric membrane valving isolates each distinct functional region of the device and, together with resistive flow, directs purified DNA and PCR reagents from the extraction domain into a 550-nl chamber for rapid target sequence PCR amplification. Repeated pressure-based injections of nanoliter aliquots of amplicon (along with the DNA sizing standard) allow electrophoretic separation and detection to provide DNA fragment size information. The presence of Bacillus anthracis (anthrax) in 750 nl of whole blood from living asymptomatic infected mice and of Bordetella pertussis in 1 microl of nasal aspirate from a patient suspected of having whooping cough are confirmed by the resultant genetic profile.     

A trap-and-release integrated microfluidic system for dynamic microarray applications

Dynamic microarrays hold great promise for advancing research in proteomics, diagnostics and drug discovery. However, this potential has yet to be fully realized due to the lack of reliable multifunctional platforms to transport and immobilize particles, infuse reagents, observe the reaction, and retrieve selected particles. We achieved all these functions in a single integrated device through the combination of hydrodynamic and optical approaches. Hydrodynamic forces allow simultaneous transportation and immobilization of large number of particles, whereas optical-based microbubble technique for bead retrieval gives dexterity in handling individual particles without complicated circuitry. Based on the criterion derived in this paper, the device was designed, and fabricated using standard photolithography and soft lithography methods. We examined the dynamics of bubble formation and dissipation in the device, and parametric studies revealed that higher power settings at short intervals were more efficient than low power settings at longer intervals for bead retrieval. We also demonstrated the capabilities of our device and its potential as a tool for screening methods such as the "one-bead-one-compound" (OBOC) combinatorial library method. Although both approaches, hydrodynamic confinement and optical-based microbubbles, are presented in one device, they can also be separately used for other applications in microchip devices.     

A modular architecture for a driving simulator based on the FDMU approach

The present paper describes the development of a modular and easily configurable simulation platform for ground vehicles. This platform should be usable for the implementation of driving simulators employed both in training purposes and in vehicle components testing. In particular, the paper presents a first architectural model for the implementation of a simulation platform based on the Functional Digital Mock-Up approach. This platform will allow engineers to implement different kinds of simulators that integrate both physical and virtual components, thus achieving the possibility to quickly reconfigure the architecture depending on the hardware and software used and on specific test case needs. The platform has been tested by developing a case study that integrates a motion platform, some I/O devices and a simple dynamic ground vehicle model implemented in OpenModelica.     

The modular architecture of protein-protein binding interfaces

Protein-protein interactions are essential for life. Yet, our understanding of the general principles governing binding is not complete. In the present study, we show that the interface between proteins is built in a modular fashion; each module is comprised of a number of closely interacting residues, with few interactions between the modules. The boundaries between modules are defined by clustering the contact map of the interface. We show that mutations in one module do not affect residues located in a neighboring module. As a result, the structural and energetic consequences of the deletion of entire modules are surprisingly small. To the contrary, within their module, mutations cause complex energetic and structural consequences. Experimentally, this phenomenon is shown on the interaction between TEM1-beta-lactamase and beta-lactamase inhibitor protein (BLIP) by using multiple-mutant analysis and x-ray crystallography. Replacing an entire module of five interface residues with Ala created a large cavity in the interface, with no effect on the detailed structure of the remaining interface. The modular architecture of binding sites, which resembles human engineering design, greatly simplifies the design of new protein interactions and provides a feasible view of how these interactions evolved.     

Chemical cytometry on a picoliter-scale integrated microfluidic chip

An integrated microfluidic device has been fabricated for analyzing the chemical contents of a single cell (chemical cytometry). The device is designed to accomplish four different functions: (i) cell handling, (ii) metering and delivering of chemical reagents, (iii) cell lysis and chemical derivatization, and (iv) separating derivatized compounds and detecting them by laser-induced fluorescence. These functions are accomplished with only two valves, formed by multilayer soft lithography. A new kind of three-state valve and a picopipette are described; these elements are crucial for minimizing the reaction volume and ensuring optimal shape of the channel for electrophoresis injection. By using these valves, a reaction volume of approximately 70 pl is achieved for the lysis and derivitization of the contents of a single Jurkat T cell (approximately 10 microm diameter). As a demonstration of the use of this integrated microfluidic device, electropherograms of amino acids from individual Jurkat T cells are recorded and compared with those collected from a multiple-cell homogenate.     

Integrated microfluidic bioprocessor for single-cell gene expression analysis

An integrated microdevice is developed for the analysis of gene expression in single cells. The system captures a single cell, transcribes and amplifies the mRNA, and quantitatively analyzes the products of interest. The key components of the microdevice include integrated nanoliter metering pumps, a 200-nL RT-PCR reactor with a single-cell capture pad, and an affinity capture matrix for the purification and concentration of products that is coupled to a microfabricated capillary electrophoresis separation channel for product analysis. Efficient microchip integration of these processes enables the sensitive and quantitative examination of gene expression variation at the single-cell level. This microdevice is used to measure siRNA knockdown of the GAPDH gene in individual Jurkat cells. Single-cell measurements suggests the presence of 2 distinct populations of cells with moderate (≈50%) or complete (≈0%) silencing. This stochastic variation in gene expression and silencing within single cells is masked by conventional bulk measurements.     

Simple fold composition and modular architecture of the nuclear pore complex

The nuclear pore complex (NPC) consists of multiple copies of approximately 30 different proteins [nucleoporins (nups)], forming a channel in the nuclear envelope that mediates macromolecular transport between the cytosol and the nucleus. With <5% of the nup residues currently available in experimentally determined structures, little is known about the detailed structure of the NPC. Here, we use a combined computational and biochemical approach to assign folds for approximately 95% of the residues in the yeast and vertebrate nups. These fold assignments suggest an underlying simplicity in the composition and modularity in the architecture of all eukaryotic NPCs. The simplicity in NPC composition is reflected in the presence of only eight fold types, with the three most frequent folds accounting for approximately 85% of the residues. The modularity in NPC architecture is reflected in its hierarchical and symmetrical organization that partitions the predicted nup folds into three groups: the transmembrane group containing transmembrane helices and a cadherin fold, the central scaffold group containing beta-propeller and alpha-solenoid folds, and the peripheral FG group containing predominantly the FG repeats and the coiled-coil fold. Moreover, similarities between structures in coated vesicles and those in the NPC support our prior hypothesis for their common evolutionary origin in a progenitor protocoatomer. The small number of predicted fold types in the NPC and their internal symmetries suggest that the bulk of the NPC structure has evolved through extensive motif and gene duplication from a simple precursor set of only a few proteins.     

Components of an integrated microfluidic device for continuous glucose monitoring with responsive insulin delivery

Miniaturized medical diagnostic and treatment devices are currently being developed. Microneedles and miniaturized microdialysis systems are particularly well suited to impact diabetes treatment for continuous glucose monitoring and feedback-controlled insulin delivery. Microneedles are an attractive advanced drug delivery system used to mechanically penetrate the skin and inject insulin intradermally where it is rapidly absorbed by the capillary bed into the bloodstream. The real advantage of microneedle-enhanced drug delivery lies in the fact that drug is actively injected into a patient so the dosage may be varied with time to allow complex drug delivery profiles. The delivery is independent of the drug composition and merely relies on the subsequent drug absorption into the bloodstream. A miniaturized microdialysis probe for continuous glucose sensing has also been designed. Microdialysis is based upon controlling the mass transfer rate of glucose diffusing across a semipermeable membrane into a dialysis fluid while excluding larger molecules such as proteins. Polymer microdialysis membranes are integrated with microfluidic systems. Because of the high surface area to fluid volume ratio of miniaturized fluid channels, faster recovery of glucose to increase glucose sensing frequency is expected. This work highlights recent advances made in the design and fabrication of microneedles to make them more biocompatible and more fracture resistant in order to effectively enter the biomedical market. In addition, the design of a miniaturized microdialysis system for increased glucose sampling frequency is presented. The sensing and infusion technologies may be combined into a miniaturized "artificial pancreas" for minimally invasive feedback-controlled insulin delivery.     

A bubble-driven microfluidic transport element for bioengineering

Microfluidics typically uses channels to transport small objects by actuation forces such as an applied pressure difference or thermocapillarity. We propose that acoustic streaming is an alternative means of directional transport at small scales. Microbubbles on a substrate establish well controlled fluid motion on very small scales; combinations ("doublets") of bubbles and microparticles break the symmetry of the motion and constitute flow transport elements. We demonstrate the principle of doublet streaming and describe the ensuing transport. Devices based on doublet flow elements work without microchannels and are thus potentially cheap and highly parallelizable.     

An integrated architecture for deploying a virtual private medical network over the web

In this paper we describe a pilot architecture aiming at protecting Web-based medical applications through the development of a virtual private medical network. The basic technology, which is utilized by this integrated architecture, is the Trusted Third Party (TTP). In specific, a TTP is used to generate, distribute, and revoke digital certificates to/from medical practitioners and healthcare organizations wishing to communicate in a secure way. Digital certificates and digital signatures are, in particular, used to provide peer and data origin authentication and access control functionalities. We also propose a logical Public Key Infrastructure (PKI) architecture, which is robust, scalable, and based on standards. This architecture aims at supporting large-scale healthcare applications. It supports openness, scalability, flexibility and extensibility, and can be integrated with existing TTP schemes and infrastructures offering transparency and adequate security. Finally, it is demonstrated that the proposed architecture enjoys all desirable usability characteristics, and meets the set of criteria, which constitutes an applicable framework for the development of trusted medical services over the Web.     

A modular computational framework for medical digital twins

This paper presents a modular software design for the construction of computational modeling technology that will help implement precision medicine. In analogy to a common industrial strategy used for preventive maintenance of engineered products, medical digital twins are computational models of disease processes calibrated to individual patients using multiple heterogeneous data streams. They have the potential to help improve diagnosis, prognosis, and personalized treatment for a wide range of medical conditions. Their large-scale development relies on both mechanistic and data-driven techniques and requires the integration and ongoing update of multiple component models developed across many different laboratories. Distributed model building and integration requires an open-source modular software platform for the integration and simulation of models that is scalable and supports a decentralized, community-based model building process. This paper presents such a platform, including a case study in an animal model of a respiratory fungal infection.

Type I diabetics now have available a medical device, an “artificial pancreas.” It is based on a mathematical model of glucose metabolism calibrated to an individual patient. The model, running on a smartphone-like device, receives real-time blood glucose levels from a sensor in the patient, calculates required insulin needs, and drives a pump attached to the patient that injects the appropriate dose of insulin (1). The patient gains quality of life and is less likely to end up in an emergency room with an insulin overdose. The artificial pancreas is an example of a medical digital twin, in analogy to a common strategy in industry. As an example, airplane engines are designed using a complex mathematical model. This model is then calibrated to an individual engine using real-time performance data continuously streamed to the manufacturer, becoming that specific engine’s digital twin. The manufacturer, in consultation with the airline, can use the digital twin for purposes such as preventive maintenance recommendations. Human beings are far more complex than airplane engines, but the digital twin concept has a clear analogy in medicine despite our incomplete understanding of the determinants of health and disease. In cardiology, prediction using personalized computational models informs interventions (2). For other examples, see refs. 3–8.Digital twins in biomedicine need to evolve continuously to represent the current state of knowledge and data. A large-scale implementation of the digital twin paradigm for human health requires the construction and execution of highly complex models composed of several component models which span multiple spatial and temporal scales. To realize the full potential of the digital twin concept, a flexible software development platform is needed that enables multidisciplinary and distributed teams to work together, supports reproducibility, and facilitates the integration of data and component models. Design patterns common to “traditional” model implementations impair the development of integrative digital twins. Some of these patterns include the following: 1) lack of transparency in the implementation of computational models, 2) intertwined component models and simulation processes dependent on each other, 3) use of incompatible data structures and computer languages, 4) brittle architectures that do not easily accommodate extensions of a model, and 5) software environments that do not easily support distributed collaboration. Solutions to these challenges are still largely lacking, not only in biomedicine (9).To address these problems, we have developed an approach based on an open-source, highly modularized computational representation of a digital twin architecture. While the concept of modular design of models and software is well established, the way modules are assembled generally suffers from the shortcomings listed above. The central principle of the architecture we have developed is the separation of computational algorithms for the different dynamic processes, eliminating dependencies that make model modifications and extensions cumbersome or impossible in complex models. It also features the separation of computational algorithms from data, in the sense that all data describing the global model state, including model parameters, are separate from the individual computational modules in a “hub-and-spoke” transparent architecture optimally designed to facilitate extension and modification and web enabled for distributed collaboration. This approach differs fundamentally from the conventional approach to building and simulating such models in biomedicine, as described below.We demonstrate this design approach and its advantages by applying it to the published model in ref. 10 of the early immune response to a respiratory infection by the fungus Aspergillus fumigatus, a dimorphic fungus that is ubiquitous and causes difficult-to-treat infections in immunocompromised patients, with high mortality. The emergence of strains resistant to first-line antifungal drugs makes the development of host-centric interventions a high priority. The agent-based model in ref. 10 could form the basis for a digital twin of some relevant functions of lung immunity used to simulate interventions personalized by data characterizing a patient’s immune status. We restructure this model using the modular design approach. Altogether, the technology we have developed makes it possible to design, calibrate, validate, and use multiscale computational models by a distributed team. Additionally, the principles developed are transferable to many other complex digital twin modeling scenarios.     

Microfabricated structures for integrated DNA analysis.

Photolithographic micromachining of silicon is a candidate technology for the construction of high-throughput DNA analysis devices. However, the development of complex silicon microfabricated systems has been hindered in part by the lack of a simple, versatile pumping method for integrating individual components. Here we describe a surface-tension-based pump able to move discrete nanoliter drops through enclosed channels using only local heating. This thermocapillary pump can accurately mix, measure, and divide drops by simple electronic control. In addition, we have constructed thermal-cycling chambers, gel electrophoresis channels, and radiolabeled DNA detectors that are compatible with the fabrication of thermocapillary pump channels. Since all of the components are made by conventional photolithographic techniques, they can be assembled into more complex integrated systems. The combination of pump and components into self-contained miniaturized devices may provide significant improvements in DNA analysis speed, portability, and cost. The potential of microfabricated systems lies in the low unit cost of silicon-based construction and in the efficient sample handling afforded by component integration.     

A sensitive,versatile microfluidic assay for bacterial chemotaxis

We have developed a microfluidic assay for bacterial chemotaxis in which a gradient of chemoeffectors is established inside a microchannel via diffusion between parallel streams of liquid in laminar flow. The random motility and chemotactic responses to L-aspartate, L-serine, L-leucine, and Ni(2+) of WT and chemotactic-mutant strains of Escherichia coli were measured. Migration of the cells was quantified by counting the cells accumulating in each of 22 outlet ports. The sensitivity of the assay is attested to by the significant response of WT cells to 3.2 nM L-aspartate, a concentration three orders of magnitude lower than the detection limit in the standard capillary assay. The response to repellents was as robust and easily recorded as the attractant response. A surprising discovery was that L-leucine is sensed by Tar as an attractant at low concentrations and by Tsr as a repellent at higher concentrations. This assay offers superior performance and convenience relative to the existing assays to measure bacterial tactic responses, and it is flexible enough to be used in a wide range of different applications.     

Innovative assembly process for modular train and feasibility analysis in virtual environment

The present paper deals with the manufacturing process of a railway carriage. In the first part of the paper, the authors focus on a “virtual railway factory” that uses a very innovative assembly cycle, if compared to the traditional manufacturing processes in the railway field. The case study refers to a railway carriage consisting of four modules, that are singularly set up of furnishings and other systems in dedicated workplaces. On one hand, the virtual simulation has highlighted several critical aspects to be improved, in order to achieve a greater feasibility and to reduce time and cost. On the other hand, the designers have been able to evaluate the movements of the parts and the assembly sequences of the components, by considering each geometric, functional and technological constraint and also some safety requirements. The second part of the paper deals with the simulation of the assembling operations and the analysis of tolerance chains, which have been performed through a Computer Aided Tolerancing system. In particular, the precision requirements have been also evaluated and we have compared the accumulation of dimensional and geometric deviations when using both rivets and traditional welds to fasten the modules.     

A feedforward architecture accounts for rapid categorization

Primates are remarkably good at recognizing objects. The level of performance of their visual system and its robustness to image degradations still surpasses the best computer vision systems despite decades of engineering effort. In particular, the high accuracy of primates in ultra rapid object categorization and rapid serial visual presentation tasks is remarkable. Given the number of processing stages involved and typical neural latencies, such rapid visual processing is likely to be mostly feedforward. Here we show that a specific implementation of a class of feedforward theories of object recognition (that extend the Hubel and Wiesel simple-to-complex cell hierarchy and account for many anatomical and physiological constraints) can predict the level and the pattern of performance achieved by humans on a rapid masked animal vs. non-animal categorization task.     

Fibrin architecture in clots: A quantitative polarized light microscopy analysis

Fibrin plays a vital structural role in thrombus integrity. Thus, the ability to assess fibrin architecture has a potential to provide insight into thrombosis and thrombolysis. Fibrin has an anisotropic molecular structure, which enables it to be seen with polarized light. Therefore, we aimed to determine if automated polarized light microscopy methods of quantifying two structural parameters; fibrin fiber bundle orientation and fibrin's optical retardation (OR: a measure of molecular anisotropy) could be used to assess thrombi. To compare fibrin fiber bundle orientation we analyzed picrosirius red-stained sections obtained from clots formed: (A) in vitro, (B) in injured and stenotic coronary arteries, and (C) in surgically created aortic aneurysms (n = 6 for each group). To assess potential changes in OR, we examined fibrin in picrosirius red-stained clots formed after ischemic preconditioning (10 min ischemia + 10 min reflow; a circumstance shown to enhance lysability) and in control clots (n = 8 each group). The degree of fibrin organization differed significantly according to the location of clot formation; fibrin was most aligned in the aneurysms and least aligned in vitro whereas fibrin in the coronary clots had an intermediate organization. The OR of fibrin in the clots formed after ischemic preconditioning was lower than that in controls (2.9 ± 0.5 nm versus 5.4 ± 1.0 nm, P < 0.05). The automated polarized light analysis methods not only enabled fibrin architecture to be assessed, but also revealed structural differences in clots formed under different circumstances.     

Ascites analysis by a microfluidic chip allows tumor-cell profiling

Ascites tumor cells (ATCs) represent a potentially valuable source of cells for monitoring treatment of ovarian cancer as it would obviate the need for more invasive surgical biopsies. The ability to perform longitudinal testing of ascites in a point-of-care setting could significantly impact clinical trials, drug development, and clinical care. Here, we developed a microfluidic chip platform to enrich ATCs from highly heterogeneous peritoneal fluid and then perform molecular analyses on these cells. We evaluated 85 putative ovarian cancer protein markers and found that nearly two-thirds were either nonspecific for malignant disease or had low abundance. Using four of the most promising markers, we prospectively studied 47 patients (33 ovarian cancer and 14 control). We show that a marker set (ATC_dx) can sensitively and specifically map ATC numbers and, through its reliable enrichment, facilitate additional treatment-response measurements related to proliferation, protein translation, or pathway inhibition.Ovarian cancer is the deadliest of gynecologic cancers, with fewer than 50% of women surviving at 5 y following diagnosis (1). Unfortunately, this statistic has changed little over the years, and most patients are still treated with a one-size-fits-all approach (2). Such a treatment strategy does not account for the broad genomic and proteomic diversity evident within ovarian tumors. Accurate measurement of protein markers will be critical in distinguishing effective from ineffective therapies. Despite the current push for biopsy-driven clinical trials, there are no minimally invasive tests or reliable biomarker panels capable of identifying ovarian cancer treatment failures before radiographic evidence of progression. The reasons are severalfold, including heterogeneity of disease (3), variable expression levels of single biomarkers (4, 5), and markers that fail to distinguish malignant from benign disease (6, 7). However, an expanding pipeline of targeted therapies and increased appreciation for the molecular drivers within ovarian cancers have spawned a number of novel approaches for detection and treatment monitoring; these approaches include primarily blood tests for circulating tumor cells (8), tumor-derived exosomes (9), stem/progenitor cells (10), and soluble tumor markers (11, 12), as well as the use of genomic (13, 14) or proteomic information (15). Lacking, however, are practical yet highly effective point-of-care (POC) platforms that can improve currently limited clinical practices (16). We hypothesized that peritoneal fluid rather than blood might be a superior source of study material for “liquid biopsy” analyses.Excess peritoneal fluid accumulation (ascites) in ovarian cancer is routinely drained (paracentesis) for symptomatic relief. Although often discarded, ascites could provide a source of abundant cellular material and potentially be preferable over blood samples. The precise cellular composition of ascites tends to vary across patients; the fraction of ascites tumor cells (ATCs) is generally believed to be <0.1% of harvested cells, with the remainder being host cells (37% lymphocytes, 29% mesothelial cells, and 32% macrophages) (17). The hurdle lies in reliably identifying and isolating ATCs from their highly heterogeneous environment. To help overcome these challenges, we developed a microfluidic chip platform to enrich ATCs directly from ascites and then perform molecular analyses on these cells. We evaluated 85 putative ovarian cancer protein markers and found that a reduced marker set (ATC_dx) can map ATC numbers. This approach is poised to expand the utility of analyzing ATCs during cytotoxic and/or molecularly targeted therapy ovarian-cancer trials.