Investigation of air bubble behaviour after gas embolism events induced in a microfluidic network mimicking microvasculature

Gas embolism is a medical condition that occurs when gas bubbles are present in veins or arteries, decreasing blood flow and potentially reducing oxygen delivery to vital organs, such as the brain. Although usually reported as rare, gas embolism can lead to severe neurological damage or death. However, presently, only limited understanding exists regarding the microscale processes leading to the formation, persistence, movement, and resolution of gas emboli, as modulated by microvasculature geometrical features and blood properties. Because gas embolism is initially a physico-chemical-only process, with biological responses starting later, the opportunity exists to fully study the genesis and evolution of gas emboli using in vitro microfluidic networks mimicking small regions of microvasculature. The microfluidics networks used in this study, which aim to mimic microvasculature geometry, comprise linear channels with T-, or Y-junction air inlets, with 20, 40, and 60 μm widths (arterial or venous), and a 30 μm width honeycombed network (arterial) with three bifurcation angles (30°, 60°, and 90°). Synthetic blood, equivalent to 46% haematocrit concentrations, and water were used to study the modulation of gas embolism-like events by liquid viscosity. Our study shows that (i) longer bubbles with lower velocity occur in narrower channels, e.g., with 20 μm width; (ii) the resistance of air bubbles to the flow increases with the higher haematocrit concentration; and lastly (iii) the propensity of gas embolism-like events in honeycomb architectures increases for more acute, e.g., 30°, bifurcation angles. A dimensionless analysis using Euler, Weber, and capillary numbers demarcated the conditions conducive to gas embolism. This work suggests that in vitro experimentation using microfluidic devices with microvascular tissue-like structures could assist medical guidelines and management in preventing and mitigating the effects of gas embolism.

Biosensing using antibody-modulated motility of actin filaments on myosin-coated surfaces

Motor proteins, such as myosin and kinesin, are biological molecular motors involved in force generation and intracellular transport within living cells. The characteristics of molecular motors, i.e., their motility over long distances, their capacity of transporting cargoes, and their very efficient energy consumption, recommend them as potential operational elements of a new class of dynamic nano-devices, with potential applications in biosensing, analyte concentrators, and biocomputation. A possible design of a biosensor based on protein molecular motor comprises a surface with immobilized motors propelling cytoskeletal filaments, which are decorated with antibodies, presented as side-branches. Upon biomolecular recognition of these branches by secondary antibodies, the 'extensions' on the cytoskeletal filaments can achieve considerable lengths (longer than several diameters of the cytoskeletal filament carrier), thus geometrically impairing or halting motility. Because the filaments are several micrometers long, this sensing mechanism converts an event in the nanometer range, i.e., antibody-antigen sizes, into an event in the micrometer range: the visualization of the halting of motility of microns-long cytoskeletal filaments. Here we demonstrate the proof of concept of a sensing system comprising heavy-mero-myosin immobilized on surfaces propelling actin filaments decorated with actin antibodies, whose movement is halted upon the recognition with secondary anti-actin antibodies. Because antibodies to the actin-myosin system are involved in several rare diseases, the first possible application for such a device may be their prognosis and diagnosis. The results also provide insights into guidelines for designing highly sensitive and very fast biosensors powered by motor proteins.

Investigating the Mechanism of Intravascular Bubble Formation in Designed Arrays of Vascularized Systems on a Chip

Vascular gas embolism is a rare medical condition, resulting from the existence of air or gas in the venous or arterial system. Gas embolism is associated with a wide range of circulatory, cardiovascular, and neurological complications that can lead to sudden and unexplained death. Despite the recent increase in related studies, gas embolism remains under-reported with a poor understanding of its genesis and pathophysiology. In this work, intravascular bubble formation is investigated in an array of biomimetic microscale systems, where the endogenous generation of gas bubbles is induced by variations in the surrounding pressure. Microfluidic devices, based on polydimethylsiloxane, are designed and fabricated as vascularized systems on a chip with one main channel at two different diameters (30 µm, and 40 µm), surrounded by a pressure chamber (200 µm) on each side, at a separation of 50 µm. Two blood-equivalent solutions, at 20% and 46% hematocrit concentrations were prepared from a glycerin and xanthan gum mixture to mimic the physicochemical characteristics of the blood. As the volume of injected air increased, the events related to gas embolism were occurring at shorter timespans with more significant characteristics, i.e., length and number of bubbles. Additionally, correlations were established between the input parameters, i.e., the vascular diameter and equivalent hematocrit concentration, and the output parameters, i.e., the bubble size, velocity, frequency, and nucleation sites.Clinical Relevance- The reported results constitute a reproducible observation and quantification of intravascular bubble formation induced by global pressure variations, where the emergence of bubbles exhibits different patterns depending on biological characteristics related to gender and medical history.

Spatially Addressable Multiplex Biodetection by Calibrated Micro/Nanostructured Surfaces

A challenge of any biosensing technology is the detection of very low concentrations of analytes. The fluorescence interference contrast (FLIC) technique improves the fluorescence-based sensitivity by selectively amplifying, or suppressing, the emission of a fluorophore-labeled biomolecule immobilized on a transparent layer placed on top of a mirror basal surface. The standing wave of the reflected emission light means that the height of the transparent layer operates as a surface-embedded optical filter for the fluorescence signal. FLIC extreme sensitivity to wavelength is also its main problem: small, e.g., 10 nm range, variations of the vertical position of the fluorophore can translate in unwanted suppression of the detection signal. Herein, we introduce the concept of quasi-circular lenticular microstructured domes operating as continuous-mode optical filters, generating fluorescent concentric rings, with diameters determined by the wavelengths of the fluorescence light, in turn modulated by FLIC. The critical component of the lenticular structures was the shallow sloping side wall, which allowed the simultaneous separation of fluorescent patterns for virtually any fluorophore wavelength. Purposefully designed microstructures with either stepwise or continuous-slope dome geometries were fabricated to modulate the intensity and the lateral position of a fluorescence signal. The simulation of FLIC effects induced by the lenticular microstructures was confirmed by the measurement of the fluorescence profile for three fluorescent dyes, as well as high-resolution fluorescence scanning using stimulated emission depletion (STED) microscopy. The high sensitivity of the spatially addressable FLIC technology was further validated on a diagnostically important target, i.e., the receptor-binding domain (RBD) of the SARS-Cov2 via the detection of RBD:anti-S1-antibody.

Early Th2 inflammation in the upper respiratory mucosa as a predictor of severe COVID-19 and modulation by early treatment with inhaled corticosteroids: a mechanistic analysis

BACKGROUND

Community-based clinical trials of the inhaled corticosteroid budesonide in early COVID-19 have shown improved patient outcomes. We aimed to understand the inflammatory mechanism of budesonide in the treatment of early COVID-19.

METHODS

The STOIC trial was a randomised, open label, parallel group, phase 2 clinical intervention trial where patients were randomly assigned (1:1) to receive usual care (as needed antipyretics were only available treatment) or inhaled budesonide at a dose of 800 μg twice a day plus usual care. For this experimental analysis, we investigated the nasal mucosal inflammatory response in patients recruited to the STOIC trial and in a cohort of SARS-CoV-2-negative healthy controls, recruited from a long-term observational data collection study at the University of Oxford. In patients with SARS-CoV-2 who entered the STOIC study, nasal epithelial lining fluid was sampled at day of randomisation (day 0) and at day 14 following randomisation, blood samples were also collected at day 28 after randomisation. Nasal epithelial lining fluid and blood samples were collected from the SARS-CoV-2 negative control cohort. Inflammatory mediators in the nasal epithelial lining fluid and blood were assessed for a range of viral response proteins, and innate and adaptive response markers using Meso Scale Discovery enzyme linked immunoassay panels. These samples were used to investigate the evolution of inflammation in the early COVID-19 disease course and assess the effect of budesonide on inflammation.

FINDINGS

146 participants were recruited in the STOIC trial (n=73 in the usual care group; n=73 in the budesonide group). 140 nasal mucosal samples were available at day 0 (randomisation) and 122 samples at day 14. At day 28, whole blood was collected from 123 participants (62 in the budesonide group and 61 in the usual care group). 20 blood or nasal samples were collected from healthy controls. In early COVID-19 disease, there was an enhanced inflammatory airway response with the induction of an anti-viral and T-helper 1 and 2 (Th1/2) inflammatory response compared with healthy individuals. Individuals with COVID-19 who clinically deteriorated (ie, who met the primary outcome) showed an early blunted respiratory interferon response and pronounced and persistent Th2 inflammation, mediated by CC chemokine ligand (CCL)-24, compared with those with COVID-19 who did not clinically deteriorate. Over time, the natural course of COVID-19 showed persistently high respiratory interferon concentrations and elevated concentrations of the eosinophil chemokine, CCL-11, despite clinical symptom improvement. There was persistent systemic inflammation after 28 days following COVID-19, including elevated concentrations of interleukin (IL)-6, tumour necrosis factor-α, and CCL-11. Budesonide treatment modulated inflammation in the nose and blood and was shown to decrease IL-33 and increase CCL17. The STOIC trial was registered with ClinicalTrials.gov, NCT04416399.

INTERPRETATION

An initial blunted interferon response and heightened T-helper 2 inflammatory response in the respiratory tract following SARS-CoV-2 infection could be a biomarker for predicting the development of severe COVID-19 disease. The clinical benefit of inhaled budesonide in early COVID-19 is likely to be as a consequence of its inflammatory modulatory effect, suggesting efficacy by reducing epithelial damage and an improved T-cell response.

FUNDING

Oxford National Institute of Health Research Biomedical Research Centre and AstraZeneca.

Epigenome erosion and SOX10 drive neural crest phenotypic mimicry in triple-negative breast cancer

Intratumoral heterogeneity is caused by genomic instability and phenotypic plasticity, but how these features co-evolve remains unclear. SOX10 is a neural crest stem cell (NCSC) specifier and candidate mediator of phenotypic plasticity in cancer. We investigated its relevance in breast cancer by immunophenotyping 21 normal breast and 1860 tumour samples. Nuclear SOX10 was detected in normal mammary luminal progenitor cells, the histogenic origin of most TNBCs. In tumours, nuclear SOX10 was almost exclusive to TNBC, and predicted poorer outcome amongst cross-sectional (p = 0.0015, hazard ratio 2.02, n = 224) and metaplastic (p = 0.04, n = 66) cases. To understand SOX10’s influence over the transcriptome during the transition from normal to malignant states, we performed a systems-level analysis of co-expression data, de-noising the networks with an eigen-decomposition method. This identified a core module in SOX10’s normal mammary epithelial network that becomes rewired to NCSC genes in TNBC. Crucially, this reprogramming was proportional to genome-wide promoter methylation loss, particularly at lineage-specifying CpG-island shores. We propose that the progressive, genome-wide methylation loss in TNBC simulates more primitive epigenome architecture, making cells vulnerable to SOX10-driven reprogramming. This study demonstrates potential utility for SOX10 as a prognostic biomarker in TNBC and provides new insights about developmental phenotypic mimicry—a major contributor to intratumoral heterogeneity.

Inhaled budesonide for COVID-19 in people at high risk of complications in the community in the UK (PRINCIPLE): a randomised, controlled, open-label, adaptive platform trial

BACKGROUND

A previous efficacy trial found benefit from inhaled budesonide for COVID-19 in patients not admitted to hospital, but effectiveness in high-risk individuals is unknown. We aimed to establish whether inhaled budesonide reduces time to recovery and COVID-19-related hospital admissions or deaths among people at high risk of complications in the community.

METHODS

PRINCIPLE is a multicentre, open-label, multi-arm, randomised, controlled, adaptive platform trial done remotely from a central trial site and at primary care centres in the UK. Eligible participants were aged 65 years or older or 50 years or older with comorbidities, and unwell for up to 14 days with suspected COVID-19 but not admitted to hospital. Participants were randomly assigned to usual care, usual care plus inhaled budesonide (800 μg twice daily for 14 days), or usual care plus other interventions, and followed up for 28 days. Participants were aware of group assignment. The coprimary endpoints are time to first self-reported recovery and hospital admission or death related to COVID-19, within 28 days, analysed using Bayesian models. The primary analysis population included all eligible SARS-CoV-2-positive participants randomly assigned to budesonide, usual care, and other interventions, from the start of the platform trial until the budesonide group was closed. This trial is registered at the ISRCTN registry (ISRCTN86534580) and is ongoing.

FINDINGS

The trial began enrolment on April 2, 2020, with randomisation to budesonide from Nov 27, 2020, until March 31, 2021, when the prespecified time to recovery superiority criterion was met. 4700 participants were randomly assigned to budesonide (n=1073), usual care alone (n=1988), or other treatments (n=1639). The primary analysis model includes 2530 SARS-CoV-2-positive participants, with 787 in the budesonide group, 1069 in the usual care group, and 974 receiving other treatments. There was a benefit in time to first self-reported recovery of an estimated 2·94 days (95% Bayesian credible interval [BCI] 1·19 to 5·12) in the budesonide group versus the usual care group (11·8 days [95% BCI 10·0 to 14·1] vs 14·7 days [12·3 to 18·0]; hazard ratio 1·21 [95% BCI 1·08 to 1·36]), with a probability of superiority greater than 0·999, meeting the prespecified superiority threshold of 0·99. For the hospital admission or death outcome, the estimated rate was 6·8% (95% BCI 4·1 to 10·2) in the budesonide group versus 8·8% (5·5 to 12·7) in the usual care group (estimated absolute difference 2·0% [95% BCI -0·2 to 4·5]; odds ratio 0·75 [95% BCI 0·55 to 1·03]), with a probability of superiority 0·963, below the prespecified superiority threshold of 0·975. Two participants in the budesonide group and four in the usual care group had serious adverse events (hospital admissions unrelated to COVID-19).

INTERPRETATION

Inhaled budesonide improves time to recovery, with a chance of also reducing hospital admissions or deaths (although our results did not meet the superiority threshold), in people with COVID-19 in the community who are at higher risk of complications.

FUNDING

National Institute of Health Research and United Kingdom Research Innovation.

Inhaled budesonide in the treatment of early COVID-19 (STOIC): a phase 2, open-label, randomised controlled trial

Background

Multiple early reports of patients admitted to hospital with COVID-19 showed that patients with chronic respiratory disease were significantly under-represented in these cohorts. We hypothesised that the widespread use of inhaled glucocorticoids among these patients was responsible for this finding, and tested if inhaled glucocorticoids would be an effective treatment for early COVID-19.

Methods

We performed an open-label, parallel-group, phase 2, randomised controlled trial (Steroids in COVID-19; STOIC) of inhaled budesonide, compared with usual care, in adults within 7 days of the onset of mild COVID-19 symptoms. The trial was done in the community in Oxfordshire, UK. Participants were randomly assigned to inhaled budsonide or usual care stratified for age (≤40 years or >40 years), sex (male or female), and number of comorbidities (≤1 and ≥2). Randomisation was done using random sequence generation in block randomisation in a 1:1 ratio. Budesonide dry powder was delivered using a turbohaler at a dose of 400 μg per actuation. Participants were asked to take two inhalations twice a day until symptom resolution. The primary endpoint was COVID-19-related urgent care visit, including emergency department assessment or hospitalisation, analysed for both the per-protocol and intention-to-treat (ITT) populations. The secondary outcomes were self-reported clinical recovery (symptom resolution), viral symptoms measured using the Common Cold Questionnare (CCQ) and the InFLUenza Patient Reported Outcome Questionnaire (FLUPro), body temperature, blood oxygen saturations, and SARS-CoV-2 viral load. The trial was stopped early after independent statistical review concluded that study outcome would not change with further participant enrolment. This trial is registered with ClinicalTrials.gov, NCT04416399.

Findings

From July 16 to Dec 9, 2020, 167 participants were recruited and assessed for eligibility. 21 did not meet eligibility criteria and were excluded. 146 participants were randomly assigned—73 to usual care and 73 to budesonide. For the per-protocol population (n=139), the primary outcome occurred in ten (14%) of 70 participants in the usual care group and one (1%) of 69 participants in the budesonide group (difference in proportions 0·131, 95% CI 0·043 to 0·218; p=0·004). For the ITT population, the primary outcome occurred in 11 (15%) participants in the usual care group and two (3%) participants in the budesonide group (difference in proportions 0·123, 95% CI 0·033 to 0·213; p=0·009). The number needed to treat with inhaled budesonide to reduce COVID-19 deterioration was eight. Clinical recovery was 1 day shorter in the budesonide group compared with the usual care group (median 7 days [95% CI 6 to 9] in the budesonide group vs 8 days [7 to 11] in the usual care group; log-rank test p=0·007). The mean proportion of days with a fever in the first 14 days was lower in the budesonide group (2%, SD 6) than the usual care group (8%, SD 18; Wilcoxon test p=0·051) and the proportion of participants with at least 1 day of fever was lower in the budesonide group when compared with the usual care group. As-needed antipyretic medication was required for fewer proportion of days in the budesonide group compared with the usual care group (27% [IQR 0–50] vs 50% [15–71]; p=0·025) Fewer participants randomly assigned to budesonide had persistent symptoms at days 14 and 28 compared with participants receiving usual care (difference in proportions 0·204, 95% CI 0·075 to 0·334; p=0·003). The mean total score change in the CCQ and FLUPro over 14 days was significantly better in the budesonide group compared with the usual care group (CCQ mean difference −0·12, 95% CI −0·21 to −0·02 [p=0·016]; FLUPro mean difference −0·10, 95% CI −0·21 to −0·00 [p=0·044]). Blood oxygen saturations and SARS-CoV-2 load, measured by cycle threshold, were not different between the groups. Budesonide was safe, with only five (7%) participants reporting self-limiting adverse events.

Interpretation

Early administration of inhaled budesonide reduced the likelihood of needing urgent medical care and reduced time to recovery after early COVID-19.

Funding

National Institute for Health Research Biomedical Research Centre and AstraZeneca.

Effect of physicochemical parameters on the stability and activity of garlic alliinase and its use for in-situ allicin synthesis

Garlic is a well-known example of natural self-defence system consisting of an inactive substrate (alliin) and enzyme (alliinase) which, when combined, produce highly antimicrobial allicin. Increase of alliinase stability and its activity are of paramount importance in various applications relying on its use for in-situ synthesis of allicin or its analogues, e.g., pulmonary drug delivery, treatment of superficial injuries, or urease inhibitors in fertilizers. Here, we discuss the effect of temperature, pH, buffers, salts, and additives, i.e. antioxidants, chelating agents, reducing agents and cosolvents, on the stability and the activity of alliinase extracted from garlic. The effects of the storage temperature and relative humidity on the stability of lyophilized alliinase was demonstrated. A combination of the short half-life, high reactivity and non-specificity to particular proteins are reasons most bacteria cannot deal with allicin's mode of action and develop effective defence mechanism, which could be the key to sustainable drug design addressing serious problems with escalating emergence of multidrug-resistant (MDR) bacterial strains.

Infection, inflammation and intervention: mechanistic modelling of epithelial cells in COVID-19

While the pathological mechanisms in COVID-19 illness are still poorly understood, it is increasingly clear that high levels of pro-inflammatory mediators play a major role in clinical deterioration in patients with severe disease. Current evidence points to a hyperinflammatory state as the driver of respiratory compromise in severe COVID-19 disease, with a clinical trajectory resembling acute respiratory distress syndrome, but how this ‘runaway train’ inflammatory response emerges and is maintained is not known. Here, we present the first mathematical model of lung hyperinflammation due to SARS-CoV-2 infection. This model is based on a network of purported mechanistic and physiological pathways linking together five distinct biochemical species involved in the inflammatory response. Simulations of our model give rise to distinct qualitative classes of COVID-19 patients: (i) individuals who naturally clear the virus, (ii) asymptomatic carriers and (iii–v) individuals who develop a case of mild, moderate, or severe illness. These findings, supported by a comprehensive sensitivity analysis, point to potential therapeutic interventions to prevent the emergence of hyperinflammation. Specifically, we suggest that early intervention with a locally acting anti-inflammatory agent (such as inhaled corticosteroids) may effectively blockade the pathological hyperinflammatory reaction as it emerges.

Lensless, reflection-based dark-field microscopy (RDFM) on a CMOS chip

We present for the first time a lens-free, oblique illumination imaging platform for on-sensor dark- field microscopy and shadow-based 3D object measurements. It consists of an LED point source that illuminates a 5-megapixel, 1.4 µm pixel size, back-illuminated CMOS sensor at angles between 0° and 90°. Analytes (polystyrene beads, microorganisms, and cells) were placed and imaged directly onto the sensor. The spatial resolution of this imaging system is limited by the pixel size (∼1.4 µm) over the whole area of the sensor (3.6×2.73 mm). We demonstrated two imaging modalities: (i) shadow imaging for estimation of 3D object dimensions (on polystyrene beads and microorganisms) when the illumination angle is between 0° and 85°, and (ii) dark-field imaging, at >85° illumination angles. In dark-field mode, a 3-4 times drop in background intensity and contrast reversal similar to traditional dark-field imaging was observed, due to larger reflection intensities at those angles. With this modality, we were able to detect and analyze morphological features of bacteria and single-celled algae clusters.

Correction to 'Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems'

[This corrects the article DOI: 10.1098/rsfs.2018.0034.].

Simple adaptive mobile phone screen illumination for dual phone differential phase contrast (DPDPC) microscopy

Phase contrast imaging is widely employed in the physical, biological, and medical sciences. However, typical implementations involve complex imaging systems that amount to in-line interferometers. We adapt differential phase contrast (DPC) to a dual-phone illumination-imaging system to obtain phase contrast images on a portable mobile phone platform. In this dual phone differential phase contrast (dpDPC) microscope, semicircles are projected sequentially on the display of one phone, and images are captured using a low-cost, short focal length lens attached to the second phone. By numerically combining images obtained using these semicircle patterns, high quality DPC images with ≈ 2 micrometer resolution can be easily acquired with no specialized hardware, circuitry, or instrument control programs.

Efficiency of the flagellar propulsion of Escherichia coli in confined microfluidic geometries

Bacterial movement in confined spaces is routinely encountered either in a natural environment or in artificial structures. Consequently, the ability to understand and predict the behavior of motile bacterial cells in confined geometries is essential to many applications, spanning from the more classical, such as the management complex microbial networks involved in diseases, biomanufacturing, mining, and environment, to the more recent, such as single cell DNA sequencing and computation with biological agents. Fortunately, the development of this understanding can be helped by the decades-long advances in semiconductor microfabrication, which allow the design and the construction of complex confining structures used as test beds for the study of bacterial motility. To this end, here we use microfabricated channels with varying sizes to study the interaction of Escherichia coli with solid confining spaces. It is shown that an optimal channel size exists for which the hydrostatic potential allows the most efficient movement of the cells. The improved understanding of how bacteria move will result in the ability to design better microfluidic structures based on their interaction with bacterial movement.

Dual-phone illumination-imaging system for high resolution and large field of view multi-modal microscopy

In this paper we present for the first time a system comprised of two mobile phones, one for illumination and the other for microscopy, as a portable, user-friendly, and cost-effective microscopy platform for a wide range of applications. Versatile and adaptive illumination is made with a Retina display of an Apple mobile phone device. The phone screen is used to project various illumination patterns onto the specimen being imaged, each corresponding to a different illumination mode, such as bright-field, dark-field, point illumination, Rheinberg illumination, and fluorescence microscopy. The second phone (a Nokia phone) is modified to record microscopic images about the sample. This imaging platform provides a high spatial resolution of at least 2 μm, a large field-of-view of 3.6 × 2.7 mm, and a working distance of 0.6 mm. We demonstrate the performance of this platform for the visualization of microorganisms within microfluidic devices to gather qualitative and quantitative information regarding microorganism morphology, dimension, count, and velocity/trajectories in the x-y plane.

Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems

On-chip network-based computation, using biological agents, is a new hardware-embedded approach which attempts to find solutions to combinatorial problems, in principle, in a shorter time than the fast, but sequential electronic computers. This analytical review starts by describing the underlying mathematical principles, presents several types of combinatorial (including NP-complete) problems and shows current implementations of proof of principle developments. Taking the subset sum problem as example for in-depth analysis, the review presents various options of computing agents, and compares several possible operation 'run modes' of network-based computer systems. Given the brute force approach of network-based systems for solving a problem of input size C, 2C solutions must be visited. As this exponentially increasing workload needs to be distributed in space, time, and per computing agent, this review identifies the scaling-related key technological challenges in terms of chip fabrication, readout reliability and energy efficiency. The estimated computing time of massively parallel or combinatorially operating biological agents is then compared to that of electronic computers. Among future developments which could considerably improve network-based computing, labelling agents 'on the fly' and the readout of their travel history at network exits could offer promising avenues for finding hardware-embedded solutions to combinatorial problems.

Environmental factors in breast cancer invasion: a mathematical modelling review

This review presents a brief overview of breast cancer, focussing on its heterogeneity and the role of mathematical modelling and simulation in teasing apart the underlying biophysical processes. Following a brief overview of the main known pathophysiological features of ductal carcinoma, attention is paid to differential equation-based models (both deterministic and stochastic), agent-based modelling, multi-scale modelling, lattice-based models and image-driven modelling. A number of vignettes are presented where these modelling approaches have elucidated novel aspects of breast cancer dynamics, and we conclude by offering some perspectives on the role mathematical modelling can play in understanding breast cancer development, invasion and treatment therapies.

Molecularly imprinted polymer membranes and thin films for the separation and sensing of biomacromolecules

This review describes recent advances associated with the development of surface imprinting methods for the synthesis of polymeric membranes and thin films, which possess the capability to selectively and specifically recognize biomacromolecules, such as proteins and single- and double-stranded DNA, employing "epitope" or "whole molecule" approaches. Synthetic procedures to create different molecularly imprinted polymer membranes or thin films are discussed, including grafting/in situ polymerization, drop-, dip-, or spin-coating procedures, electropolymerization as well as micro-contact or stamp lithography imprinting methods. Highly sensitive techniques for surface characterization and analyte detection are described, encompassing luminescence and fluorescence spectroscopy, X-ray photoelectron spectroscopy, FTIR spectroscopy, surface-enhanced Raman spectroscopy, atomic force microscopy, quartz crystal microbalance analysis, cyclic voltammetry, and surface plasmon resonance. These developments are providing new avenues to produce bioelectronic sensors and new ways to explore through advanced separation science procedures complex phenomena associated with the origins of biorecognition in nature.

Protein patterning by microcontact printing using pyramidal PDMS stamps

Micro-contact printing, μCP, is a well-established soft-lithography technique for printing biomolecules. μCP uses stamps made of Poly(dimethylsiloxane), PDMS, made by replicating a microstructured silicon master fabricated by semiconductor manufacturing processes. One of the problems of the μCP is the difficult control of the printing process, which, because of the high compressibility of PDMS, is very sensitive to minute changes in the applied pressure. This over-sensitive response leads to frequent and/or uncontrollable collapse of the stamps with high aspect ratios, thus decreasing the printing accuracy and reproducibility. Here we present a straightforward methodology of designing and fabricating PDMS structures with an architecture which uses the collapse of the stamp to reduce, rather than enlarge the variability of the printing. The PDMS stamp, organized as an array of pyramidal micro-posts, whose ceiling collapses when pressed on a flat surface, replicates the structure of the silicon master fabricated by anisotropic wet etching. Upon application of pressure, depending on the size of, and the pitch between, the PDMS pyramids, an air gap is formed surrounding either the entire array, or individual posts. The printing technology, which also exhibits a remarkably low background noise for fluorescence detection, may find applications when the clear demarcation of the shapes of protein patterns and the distance between them are critical, such as microarrays and studies of cell patterning.

Polymer surface properties control the function of heavy meromyosin in dynamic nanodevices

The actin-myosin system, responsible for muscle contraction, is also the force-generating element in dynamic nanodevices operating with surface-immobilized motor proteins. These devices require materials that are amenable to micro- and nano-fabrication, but also preserve the bioactivity of molecular motors. The complexity of the protein-surface systems is greatly amplified by those of the polymer-fluid interface; and of the structure and function of molecular motors, making the study of these interactions critical to the success of molecular motor-based nanodevices. We measured the density of the adsorbed motor protein (heavy meromyosin, HMM) using quartz crystal microbalance; and motor bioactivity with ATPase assay, on a set of model surfaces, i.e., nitrocellulose, polystyrene, poly(methyl methacrylate), and poly(butyl methacrylate), poly(tert-butyl methacrylate). A higher hydrophobicity of the adsorbing material translates in a higher total number of HMM molecules per unit area, but also in a lower uptake of water, and a lower ratio of active per total HMM molecules per unit area. We also measured the motility characteristics of actin filaments on the model surfaces, i.e., velocity, smoothness and deflection of movement, determined via in vitro motility assays. The filament velocities were found to be controlled by the relative number of active HMM per total motors, rather than their absolute surface density. The study allowed the formulation of the general engineering principles for the selection of polymeric materials for the manufacturing of dynamic nanodevices using protein molecular motors.

Confinement of water droplets on rectangular micro/nano-arrayed surfaces

Micro-patterned surfaces with alternate hydrophilic and hydrophobic rectangular areas effectively confine water droplets down to attolitre volumes. The contact angle, volume, and geometry of the confined droplets as a function of the geometry and physico-chemical properties of the confining surfaces have been determined by phenomenological simulations, validated by atomic force microscopy measurements. The combination between experiments and simulations can be used for the purposeful design of arrays with surface-addressable hydrophobicity employed in digital microfluidics and high-throughput screening nanoarrays.

Optimal Fungal Space Searching Algorithms

Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.

Surface-Controlled Properties of Myosin Studied by Electric Field Modulation

The efficiency of dynamic nanodevices using surface-immobilized protein molecular motors, which have been proposed for diagnostics, drug discovery, and biocomputation, critically depends on the ability to precisely control the motion of motor-propelled, individual cytoskeletal filaments transporting cargo to designated locations. The efficiency of these devices also critically depends on the proper function of the propelling motors, which is controlled by their interaction with the surfaces they are immobilized on. Here we use a microfluidic device to study how the motion of the motile elements, i.e., actin filaments propelled by heavy mero-myosin (HMM) motor fragments immobilized on various surfaces, is altered by the application of electrical loads generated by an external electric field with strengths ranging from 0 to 8 kVm(-1). Because the motility is intimately linked to the function of surface-immobilized motors, the study also showed how the adsorption properties of HMM on various surfaces, such as nitrocellulose (NC), trimethylclorosilane (TMCS), poly(methyl methacrylate) (PMMA), poly(tert-butyl methacrylate) (PtBMA), and poly(butyl methacrylate) (PBMA), can be characterized using an external field. It was found that at an electric field of 5 kVm(-1) the force exerted on the filaments is sufficient to overcome the frictionlike resistive force of the inactive motors. It was also found that the effect of assisting electric fields on the relative increase in the sliding velocity was markedly higher for the TMCS-derivatized surface than for all other polymer-based surfaces. An explanation of this behavior, based on the molecular rigidity of the TMCS-on-glass surfaces as opposed to the flexibility of the polymer-based ones, is considered. To this end, the proposed microfluidic device could be used to select appropriate surfaces for future lab-on-a-chip applications as illustrated here for the almost ideal TMCS surface. Furthermore, the proposed methodology can be used to gain fundamental insights into the functioning of protein molecular motors, such as the force exerted by the motors under different operational conditions.

Mapping hydrophobicity on the protein molecular surface at atom-level resolution

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 Å, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced "leopard skin"-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism.

Protein molecular surface mapped at different geometrical resolutions

Many areas of biochemistry and molecular biology, both fundamental and applications-orientated, require an accurate construction, representation and understanding of the protein molecular surface and its interaction with other, usually small, molecules. There are however many situations when the protein molecular surface gets in physical contact with larger objects, either biological, such as membranes, or artificial, such as nanoparticles. The contribution presents a methodology for describing and quantifying the molecular properties of proteins, by geometrical and physico-chemical mapping of the molecular surfaces, with several analytical relationships being proposed for molecular surface properties. The relevance of the molecular surface-derived properties has been demonstrated through the calculation of the statistical strength of the prediction of protein adsorption. It is expected that the extension of this methodology to other phenomena involving proteins near solid surfaces, in particular the protein interaction with nanoparticles, will result in important benefits in the understanding and design of protein-specific solid surfaces.

The selection of DNA aptamers for two different epitopes of thrombin was not due to different partitioning methods

Nearly all aptamers identified so far for any given target molecule have been specific for the same binding site (epitope). The most notable exception to the 1 aptamer per target molecule rule is the pair of DNA aptamers that bind to different epitopes of thrombin. This communication refutes the suggestion that these aptamers exist because different partitioning methods were used when they were selected. The possibility that selection of these aptamers was biased by conflicting secondary structures was also investigated and found not to contribute. The preparation of protein-coated magnetic beads for systematic evolution of ligands by exponential enrichment (SELEX) and the different specificities of the thrombin aptamers for the α and β forms of thrombin are also reported.

Actin filament motility induced variation of resonance frequency and rigidity of polymer surfaces studied by quartz crystal microbalance

This contribution reports on the quantification of the parameters of the motility assays for actomyosin system using a quartz crystal microbalance (QCM). In particular, we report on the difference in the observed resonance frequency and dissipation of a quartz crystal when actin filaments are stationary as opposed to when they are motile. The changes in QCM measurements were studied for various polymer-coated surfaces functionalized with heavy meromyosin (HMM). The results of the QCM experiments show that the HMM-induced sliding velocity of actin filaments is modulated by a combination of the viscoelastic properties of the polymer layer including the HMM motors.

Fluorescence biosensing micropatterned surfaces based on immobilized human acetylcholinesterase

Human acetylcholinesterase (AChE) is a widely studied target enzyme in drug discovery for Alzheimer's disease (AD). In this paper we report evaluation of the optimum structure and chemistry of the supporting material for a new AChE-based fluorescence sensing surface. To achieve this objective, multilayered silicon wafers with spatially controlled geometry and chemical diversity were fabricated. Specifically, silicon wafers with silicon oxide patterns (SiO(2)/Si wafers), platinum-coated silicon wafers with SiO(2) patterns (SiO(2)/Pt/Ti/Si wafers), and Pt-coated wafers coated with different thicknesses of TiO(2) and SiO(2) (SiO(2)/TiO(2)/Pt/Ti/Si wafers) were labelled with the fluorescent conjugation agent HiLyte Fluor 555. Selection of a suitable material and the optimum pattern thickness required to maximize the fluorescence signal and maintain chemical stability was performed by confocal laser-scanning microscopy (CLSM). Results showed that the highest signal-to-background ratio was always obtained on wafers with 100 nm thick SiO(2) features. Hence, these wafers were selected for covalent binding of human AChE. Batch-wise kinetic studies revealed that enzyme activity was retained after immobilization. Combined use of atomic-force microscopy and CLSM revealed that AChE was homogeneously and selectively distributed on the SiO(2) microstructures at a suitable distance from the reflective surface. In the optimum design, efficient fluorescence emission was obtained from the AChE-based biosensing surface after labelling with propidium, a selective fluorescent probe of the peripheral binding site of AChE.

Conformational spread in the flagellar motor switch: a model study

The reliable response to weak biological signals requires that they be amplified with fidelity. In E. coli, the flagellar motors that control swimming can switch direction in response to very small changes in the concentration of the signaling protein CheY-P, but how this works is not well understood. A recently proposed allosteric model based on cooperative conformational spread in a ring of identical protomers seems promising as it is able to qualitatively reproduce switching, locked state behavior and Hill coefficient values measured for the rotary motor. In this paper we undertook a comprehensive simulation study to analyze the behavior of this model in detail and made predictions on three experimentally observable quantities: switch time distribution, locked state interval distribution, Hill coefficient of the switch response. We parameterized the model using experimental measurements, finding excellent agreement with published data on motor behavior. Analysis of the simulated switching dynamics revealed a mechanism for chemotactic ultrasensitivity, in which cooperativity is indispensable for realizing both coherent switching and effective amplification. These results showed how cells can combine elements of analog and digital control to produce switches that are simultaneously sensitive and reliable.

Kinetic characterization of amyloid-beta 1-42 aggregation with a multimethodological approach

Extensive evidence suggests that the self-assembly of amyloid-beta peptide (Aβ) is a nucleation-dependent process that involves the formation of several oligomeric intermediates. Despite neuronal toxicity being recently related to Aβ soluble oligomers, results from aggregation studies are often controversial, mainly because of the low reproducibility of several experimental protocols. Here a multimethodological study that included atomic force microscopy (AFM), transmission electron microscopy (TEM), fluorescence microscopy (FLM), mass spectrometry techniques (matrix-assisted laser desorption/ionization time-of-flight [MALDI-TOF] and electrospray ionization quadrupole time-of-flight [ESI-QTOF]), and direct thioflavin T (ThT) fluorescence spectroscopy were enabled to set up a reliable and highly reproducible experimental protocol for the characterization of the morphology and dimension of Aβ 1-42 (Aβ42) aggregates along the self-assembly pathway. This multimethodological approach allowed elucidating the diverse assembly species formed during the Aβ aggregation process and was applied to the detailed investigation of the mechanism of Aβ42 inhibition by myricetin. In particular, a very striking result was the molecular weight determination of the initial oligomeric nuclei by MALDI-TOF, composed of up to 10 monomers, and their morphology by AFM.

Probing the growth dynamics of Neurospora crassa with microfluidic structures

Despite occupying physically and chemically heterogeneous natural environments, the growth dynamics of filamentous fungi is typically studied on the surface of homogeneous laboratory media. Fungal exploration and exploitation of complex natural environments requires optimal survival and growth strategies at the colony, hyphal, and intra hyphal level, with hyphal space-searching strategies playing a central role. We describe a new methodology for the characterisation and analysis of hyphal space-searching strategies, which uses purposefully designed three-dimensional microfluidics structures mimicking some of the characteristics of natural environments of the fungi. We also demonstrate this new methodology by running a comparative examination of two Neurospora crassa strains, i.e., the wild type of N. crassa -- a commonly used model organism for the study of filamentous fungi -- and the N. crassa ro-1 mutant strain -- which is deficient in hyphal and mycelial growth. Continuous live imaging showed that both strains responded actively to the geometrically confined microstructured environments without any detectable temporal delay or spatial adjustment. While both strains navigated the test structures exhibiting similar geometry-induced space-searching mechanisms, they presented fundamentally different growth patterns that could not be observed on geometrically unconfined, flat agar surfaces.

Protein immobilisation on micro/nanostructures fabricated by laser microablation

The performance of biomedical microdevices requires the accurate control of the biomolecule concentration on the surface, as well as the preservation of their bioactivity. This desideratum is even more critical for proteins, which present a significant propensity for surface-induced denaturation, and for microarrays, which require high multiplexing. We have previously proposed a method for protein immobilisation on micro/nanostructures fabricated via laser ablation of a thin metal layer deposited on a transparent polymer. This study investigates the relationship between the properties of the micro/nanostructured surface, i.e., topography and physico-chemistry, and protein immobilisation, for five, molecularly different proteins, i.e., lysozyme, myoglobin, α-chymotrypsin, human serum albumin, and human immunoglobulin. Protein immobilisation on microstructures has been characterised using quantitative fluorescence measurements and atomic force microscopy. It has been found that the sub-micrometer-level, combinatorial nature of the microstructure translates in a 3-10-fold amplification of protein adsorption, as compared to flat, chemically homogenous polymeric surfaces. This amplification is more pronounced for smaller proteins, as they can capitalize better on the newly created surface and variability of the nano-environments.

Conformational spread as a mechanism for cooperativity in the bacterial flagellar switch

The bacterial flagellar switch that controls the direction of flagellar rotation during chemotaxis has a highly cooperative response. This has previously been understood in terms of the classic two-state, concerted model of allosteric regulation. Here, we used high-resolution optical microscopy to observe switching of single motors and uncover the stochastic multistate nature of the switch. Our observations are in detailed quantitative agreement with a recent general model of allosteric cooperativity that exhibits conformational spread--the stochastic growth and shrinkage of domains of adjacent subunits sharing a particular conformational state. We expect that conformational spread will be important in explaining cooperativity in other large signaling complexes.

Directional persistence and the optimality of run-and-tumble chemotaxis

E. coli does chemotaxis by performing a biased random walk composed of alternating periods of swimming (runs) and reorientations (tumbles). Tumbles are typically modelled as complete directional randomisations but it is known that in wild type E. coli, successive run directions are actually weakly correlated, with a mean directional difference of approximately 63 degrees. We recently presented a model of the evolution of chemotactic swimming strategies in bacteria which is able to quantitatively reproduce the emergence of this correlation. The agreement between model and experiments suggests that directional persistence may serve some function, a hypothesis supported by the results of an earlier model. Here we investigate the effect of persistence on chemotactic efficiency, using a spatial Monte Carlo model of bacterial swimming in a gradient, combined with simulations of natural selection based on chemotactic efficiency. A direct search of the parameter space reveals two attractant gradient regimes, (a) a low-gradient regime, in which efficiency is unaffected by directional persistence and (b) a high-gradient regime, in which persistence can improve chemotactic efficiency. The value of the persistence parameter that maximises this effect corresponds very closely with the value observed experimentally. This result is matched by independent simulations of the evolution of directional memory in a population of model bacteria, which also predict the emergence of persistence in high-gradient conditions. The relationship between optimality and persistence in different environments may reflect a universal property of random-walk foraging algorithms, which must strike a compromise between two competing aims: exploration and exploitation. We also present a new graphical way to generally illustrate the evolution of a particular trait in a population, in terms of variations in an evolvable parameter.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Models of protein linear molecular motors for dynamic nanodevices

Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices.

Microbeads on microposts: an inverted architecture for bead microarrays

The rapid development of genomics and proteomics requires accelerated improvement of the microarrays density, multiplexing, readout capabilities and cost-effectiveness. The bead arrays are increasingly attractive because of their self-assembly-based fabrication, which alleviates many problems of top-down microfabrication. Here we present a simple, reliable, robust and modular technique for the fabrication of bead microarrays, which combines the directed assembling of beads in microstructures and PDMS-based replica molding. The beads are first self-assembled in pyramidal microwells fabricated by anisotropic etching of silicon substrates, then transferred on the apex of PDMS pyramids that replicate the silicon microstructures. The arrays are chemically and biochemically robust; they are spatially addressable and have the potential for being informationally addressable; and they appear to offer better readout capabilities than the classical microarrays.

Surface hydrophobicity modulates the operation of actomyosin-based dynamic nanodevices

We studied the impact of surface hydrophobicity on the motility of actin filaments moving on heavy-meromyosin (HMM)-coated surfaces. Apart from nitrocellulose (NC), which is the current standard for motility assays, all materials tested are good candidates for microfabrication: hydrophilic and hydrophobic glass, poly(methyl methacrylate) (PMMA), poly(tert-butyl methacrylate) (PtBuMA), and a copolymer of O-acryloyl acetophenone oxime with a 4-acryloyloxybenzophenone (AAPO). The most hydrophilic (hydrophilic glass, contact angle 35 degrees) and the most hydrophobic (PtBuMA, contact angle 78 degrees) surfaces do not maintain the motility of actin filaments, presumably because of the low density of adsorbed HMM protein or its high levels of denaturation, respectively. The velocity of actin filaments presents higher values in the middle of this "surface hydrophobicity motility window" (NC, PMMA), and a bimodal distribution, which is more apparent at the edges of this motility window (hydrophobic glass and AAPO). A molecular surface analysis of HMM and its S1 units suggests that the two very different, temporally separated conformations of the HMM heads could exacerbate the surface-modulated protein behavior, which is common to all microdevices using surface-immobilized proteins. An explanation for the above behavior proposes that the motility of actin filaments on HMM-functionalized surfaces is the result of the action of three populations of motors, each in a different surface-protein conformation, that is, HMM with both heads working (high velocities), working with one head (low velocities), and fully denatured HMM (no motility). It is also proposed that the molecularly dynamic nature of polymer surfaces amplifies the impact of surface hydrophobicity on protein behavior. The study demonstrates that PMMA is a good candidate for the fabrication of future actomyosin-driven dynamic nanodevices because it induces the smoothest motility of individual nano-objects with velocities comparable with those obtained on NC.

Modelling and simulation techniques for membrane biology

One of the most important aspects of Computational Cell Biology is the understanding of the complicated dynamical processes that take place on plasma membranes. These processes are often so complicated that purely temporal models cannot always adequately capture the dynamics. On the other hand, spatial models can have large computational overheads. In this article, we review some of these issues with respect to chemistry, membrane microdomains and anomalous diffusion and discuss how to select appropriate modelling and simulation paradigms based on some or all the following aspects: discrete, continuous, stochastic, delayed and complex spatial processes.

Protein Linear Molecular Motor-Powered Nanodevices

Myosin–actin and kinesin–microtubule linear protein motor systems and their application in hybrid nanodevices are reviewed. Research during the past several decades has provided a wealth of understanding about the fundamentals of protein motors that continues to be pursued. It has also laid the foundations for a new branch of investigation that considers the application of these motors as key functional elements in laboratory-on-a-chip and other micro/nanodevices. Current models of myosin and kinesin motors are introduced and the effects of motility assay parameters, including temperature, toxicity, and in particular, surface effects on motor protein operation, are discussed. These parameters set the boundaries for gliding and bead motility assays. The review describes recent developments in assay motility confinement and unidirectional control, using micro- and nano-fabricated structures, surface patterning, microfluidic flow, electromagnetic fields, and self-assembled actin filament/microtubule tracks. Current protein motor assays are primitive devices, and the developments in governing control can lead to promising applications such as sensing, nano-mechanical drivers, and biocomputation.