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There has been an increasing, and welcome, Open Hardware trend towards science teams building and sharing their designs for new instruments. These devices, often built upon low-cost microprocessors and micro-controllers, can be readily connected to enable complex, automated, and smart experiments. When designed to use open communication web standards, devices from different laboratories and manufacturers can be controlled using a single protocol, and even communicate with each other. However, science labs still have a majority of old, perfectly functional, equipment which tends to use older, and sometimes proprietary, standards for communications. In order to encourage the continued and integrated use of this equipment in modern automated experiments, we develop and demonstrate LabThings Retro. This allows us to retrofit old instruments to use modern web-of-things standards, which we demonstrate with closed-loop feedback involving an optical microscope, digital imaging and fluid pumping., Comment: Supplementary material - video demonstration available at https://zenodo.org/doi/10.5281/zenodo.10123735

Making user interaction with laboratory equipment more convenient and intuitive should promote experimental work and help researchers to complete their tasks efficiently. The most common form of interaction in current instrumentation is either direct tactile, with buttons and knobs, or interfaced through a computer, using a mouse and keyboard. Scripting is another function typical of smart and automated laboratory equipment, yet users are currently required to learn bespoke programming languages and libraries for individual pieces of equipment. In this paper, we present two open-source, novel and intuitive ways of interacting with and scripting laboratory equipment. We choose the OpenFlexure family of microscopes as our exemplar, due to their open-source nature and smart control system. Firstly, we demonstrate 'OpenFlexure Voice Control' to enable users to control the microscope hands-free. Secondly, we present 'OpenFlexure Blockly' which uses the Blockly Visual Programming Language to enable users to easily create scripts for the microscope, using a drag and drop web interface. We explain the design choices when developing these tools, and discuss more typical use cases and more general applications.

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS)., Comment: 18 pages, 13 figures

Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection given the current audio sample, but do not monitor disease progression in COVID-19. Limited exploration has been put forward to continuously monitor COVID-19 progression, especially recovery, through longitudinal audio data. Tracking disease progression characteristics could lead to more timely treatment. The primary objective of this study is to explore the potential of longitudinal audio samples over time for COVID-19 progression prediction and, especially, recovery trend prediction using sequential deep learning techniques. Crowdsourced respiratory audio data, including breathing, cough, and voice samples, from 212 individuals over 5-385 days were analyzed. We developed a deep learning-enabled tracking tool using gated recurrent units (GRUs) to detect COVID-19 progression by exploring the audio dynamics of the individuals' historical audio biomarkers. The investigation comprised 2 parts: (1) COVID-19 detection in terms of positive and negative (healthy) tests, and (2) longitudinal disease progression prediction over time in terms of probability of positive tests. The strong performance for COVID-19 detection, yielding an AUROC of 0.79, a sensitivity of 0.75, and a specificity of 0.71 supported the effectiveness of the approach compared to methods that do not leverage longitudinal dynamics. We further examined the predicted disease progression trajectory, displaying high consistency with test results with a correlation of 0.75 in the test cohort and 0.86 in a subset of the test cohort who reported recovery. Our findings suggest that monitoring COVID-19 evolution via longitudinal audio data has potential in the tracking of individuals' disease progression and recovery., Comment: Updated title. Revised format according to journal requirements

Microscopes are vital pieces of equipment in much of biological research and medical diagnostics. However, access to a microscope can represent a bottleneck in research, especially in lower-income countries. `Smart' computer controlled motorized microscopes, which can perform automated routines or acquire images in a range of modalities are even more expensive and inaccessible. Developing low-cost, open-source, smart microscopes enables more researchers to conceive and execute optimized or more complex experiments. Here we present the OpenFlexure Delta Stage, a 3D-printed microscope designed for researchers. Powered by the OpenFlexure software stack, it is capable of performing automated experiments. The design files and assembly instructions are freely available under an open licence. Its intuitive and modular design -- along with detailed documentation -- allows researchers to implement a variety of imaging modes with ease. The versatility of this microscope is demonstrated by imaging biological and non-biological samples (red blood cells with Plasmodium parasites and colloidal particles in brightfield, epi-fluorescence, darkfield, Rheinberg and differential phase contrast. We present the design strategy and choice of tools to develop devices accessible to researchers from lower-income countries, as well as the advantages of an open-source project in this context. This microscope, having been open-source since its conception, has already been built and tested by researchers around the world, promoting a community of expertise and an environment of reproducibility in science.

The process of making blood smears is common in both research and clinical settings, for investigating the health of blood cells and the presence of blood-borne parasites. It is very often carried out manually. We focus here on smears for malaria diagnosis and research which are frequently analyzed by optical microscopy and require a high quality. Automating the smear preparation promises to increase throughput and to improve the quality and consistency of the smears. We present here two devices (manual and motorized) designed to aid in the making of blood smears. These are fully documented, open-source hardware, and an important principle was to make them easily fabricated locally anywhere. Designs and assembly instructions are freely available under an open license. We also describe an image analysis pipeline for characterizing the quality of smears, and use it to optimize the settings and tunable parameters in the two devices. The devices perform as well as expert human operators, while not requiring a trained operator and offering potential advantages in reproducibility and standardization across facilities.

Researchers have been battling with the question of how we can identify Coronavirus disease (COVID-19) cases efficiently, affordably and at scale. Recent work has shown how audio based approaches, which collect respiratory audio data (cough, breathing and voice) can be used for testing, however there is a lack of exploration of how biases and methodological decisions impact these tools' performance in practice. In this paper, we explore the realistic performance of audio-based digital testing of COVID-19. To investigate this, we collected a large crowdsourced respiratory audio dataset through a mobile app, alongside recent COVID-19 test result and symptoms intended as a ground truth. Within the collected dataset, we selected 5,240 samples from 2,478 participants and split them into different participant-independent sets for model development and validation. Among these, we controlled for potential confounding factors (such as demographics and language). The unbiased model takes features extracted from breathing, coughs, and voice signals as predictors and yields an AUC-ROC of 0.71 (95\% CI: 0.65$-$0.77). We further explore different unbalanced distributions to show how biases and participant splits affect performance. Finally, we discuss how the realistic model presented could be integrated in clinical practice to realize continuous, ubiquitous, sustainable and affordable testing at population scale.

Physics can be seen as a conceptual approach to scientific problems, a method for discovery, but teaching this aspect of our discipline can be a challenge. We report on a first-time remote teaching experience for a computational physics third-year physics laboratory class taught in the first part of the 2020 COVID-19 pandemic (March-May 2020). To convey a ``physics of data" approach to data analysis and data-driven physical modeling we used interdisciplinary data sources, with an openended ``COVID-19 data challenge" project as the core of the course. COVID-19 epidemiological data provided an ideal setting for motivating the students to deal with complex problems, where there is no unique or preconceived solution. Our results indicate that such problems yield qualitatively different improvements compared to close-ended projects, as well as point to critical aspects in using these problems as a teaching strategy. By breaking the students' expectations of unidirectionality, remote teaching provided unexpected opportunities to promote active work and active learning., Comment: revised in the text and references following 1st round of peer review

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation SubChallenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the 'usual' COMPARE and BoAW features as well as deep unsupervised representation learning using the AuDeep toolkit, and deep feature extraction from pre-trained CNNs using the Deep Spectrum toolkit; in addition, we add deep end-to-end sequential modelling, and partially linguistic analysis., Comment: 5 pages

The development of fast and accurate screening tools, which could facilitate testing and prevent more costly clinical tests, is key to the current pandemic of COVID-19. In this context, some initial work shows promise in detecting diagnostic signals of COVID-19 from audio sounds. In this paper, we propose a voice-based framework to automatically detect individuals who have tested positive for COVID-19. We evaluate the performance of the proposed framework on a subset of data crowdsourced from our app, containing 828 samples from 343 participants. By combining voice signals and reported symptoms, an AUC of $0.79$ has been attained, with a sensitivity of $0.68$ and a specificity of $0.82$. We hope that this study opens the door to rapid, low-cost, and convenient pre-screening tools to automatically detect the disease., Comment: 5 pages, 3 figures, 2 tables, Accepted for publication at ICASSP 2021

A growing body of work on the dynamics of eukaryotic flagella has noted that their oscillation frequencies are sufficiently high that the viscous penetration depth of unsteady Stokes flow is comparable to the scales over which flagella synchronize. Incorporating these effects into theories of synchronization requires an understanding of the global unsteady flows around oscillating bodies. Yet, there has been no precise experimental test on the microscale of the most basic aspects of such unsteady Stokes flow: the orbits of passive tracers and the position-dependent phase lag between the oscillating response of the fluid at a distant point and that of the driving particle. Here, we report the first such direct Lagrangian measurement of this unsteady flow. The method uses an array of $30$ submicron tracer particles positioned by a time-shared optical trap at a range of distances and angular positions with respect to a larger, central particle, which is then driven by an oscillating optical trap at frequencies up to $400$ Hz. In this microscale regime, the tracer dynamics is considerably simplified by the smallness of both inertial effects on particle motion and finite-frequency corrections to the Stokes drag law. The tracers are found to display elliptical Lissajous figures whose orientation and geometry are in agreement with a low-frequency expansion of the underlying dynamics, and the experimental phase shift between motion parallel and orthogonal to the oscillation axis exhibits a predicted scaling form in distance and angle. Possible implications of these results for synchronization dynamics are discussed., Comment: 13 pages, 7 figures

DNA-mediated multivalent interactions between colloidal particles have been extensively applied for their ability to program bulk phase behaviour and dynamic processes. Exploiting the competition between different types of DNA-DNA bonds, here we experimentally demonstrate the selective triggering of colloidal self-assembly in the presence of a functionalised surface, which induces changes in particle-particle interactions. Besides its relevance to the manufacturing of layered materials with controlled thickness, the intrinsic signal-amplification features of the proposed interaction scheme make it valuable for biosensing applications.

Audio signals generated by the human body (e.g., sighs, breathing, heart, digestion, vibration sounds) have routinely been used by clinicians as indicators to diagnose disease or assess disease progression. Until recently, such signals were usually collected through manual auscultation at scheduled visits. Research has now started to use digital technology to gather bodily sounds (e.g., from digital stethoscopes) for cardiovascular or respiratory examination, which could then be used for automatic analysis. Some initial work shows promise in detecting diagnostic signals of COVID-19 from voice and coughs. In this paper we describe our data analysis over a large-scale crowdsourced dataset of respiratory sounds collected to aid diagnosis of COVID-19. We use coughs and breathing to understand how discernible COVID-19 sounds are from those in asthma or healthy controls. Our results show that even a simple binary machine learning classifier is able to classify correctly healthy and COVID-19 sounds. We also show how we distinguish a user who tested positive for COVID-19 and has a cough from a healthy user with a cough, and users who tested positive for COVID-19 and have a cough from users with asthma and a cough. Our models achieve an AUC of above 80% across all tasks. These results are preliminary and only scratch the surface of the potential of this type of data and audio-based machine learning. This work opens the door to further investigation of how automatically analysed respiratory patterns could be used as pre-screening signals to aid COVID-19 diagnosis., Comment: 9 pages, 6 figures, 2 tables, Accepted for publication at KDD'20 (Health Day)

Motile cilia are a striking example of functional cellular organelle, conserved across all the eukaryotic species. Motile cilia allow swimming of cells and small organisms and transport of liquids across epithelial tissues. Whilst the molecular structure is now very well understood, the dynamics of cilia is not well established either at the single cilium level nor at the level of collective beating. Indeed, a full understanding of this requires connecting together behaviour across various lengthscales, from the molecular to the organelle, then at cellular level and up to the tissue scale. Aside from the fundamental interest in this system, understanding beating is important to elucidate aspects of embryonic development and a variety of health conditions from fertility to genetic and infectious diseases of the airways., Comment: a review of 11 pages, Submitted to Biochemical Society Transactions

In low Reynolds number swimming and pumping, differently to everyday experience, a net motion (or flow) can be achieved only if the constructing parts of the swimmer (or pump) follow a non-trivial pattern of motion, in order to break time reciprocity. The case of a driven fan, which spins to create a flow of air, but conversely rotates when turned off and subjected to a strong external flow, is a familiar example of reciprocal connection between physical cause and effect. We explore here in a well controlled low Reynolds number system whether such an exchange of the cause and effect also holds in the low Reynolds number regime. As a case study we investigate the motion of two microspheres which interact hydrodynamically through their surrounding fluid. Each sphere is constrained in a fixed optical trap potential, allowing local fluctuations around an equilibrium position. An external flow is shown to induce non-trivial coupled motion. We find a signature of reciprocity: the nonequilibrium sphere fluctuations mimic the symmetry of the motions that one would impose in order for them to produce a constant flow., Comment: 5 pages, 3 figures

At the heart of the structured architecture and complex dynamics of biological systems are specific and timely interactions operated by biomolecules. In many instances, biomolecular agents are spatially confined to flexible lipid membranes where, among other functions, they control cell adhesion, motility and tissue formation. Besides being central to several biological processes, \emph{multivalent interactions} mediated by reactive linkers confined to deformable substrates underpin the design of synthetic-biological platforms and advanced biomimetic materials. Here we review recent advances on the experimental study and theoretical modelling of a heterogeneous class of biomimetic systems in which synthetic linkers mediate multivalent interactions between fluid and deformable colloidal units, including lipid vesicles and emulsion droplets. Linkers are often prepared from synthetic DNA nanostructures, enabling full programmability of the thermodynamic and kinetic properties of their mutual interactions. The coupling of the statistical effects of multivalent interactions with substrate fluidity and deformability gives rise to a rich emerging phenomenology that, in the context of self-assembled soft materials, has been shown to produce exotic phase behaviour, stimuli-responsiveness, and kinetic programmability of the self-assembly process. Applications to (synthetic) biology will also be reviewed., Comment: 63 pages, review

Eukaryotic cilia and flagella are chemo-mechanical oscillators capable of generating long-range coordinated motions known as metachronal waves. Pair synchronization is a fundamental requirement for these collective dynamics, but it is generally not sufficient for collective phase-locking, chiefly due to the effect of long-range interactions. Here we explore experimentally and numerically a minimal model for a ciliated surface; hydrodynamically coupled oscillators rotating above a no-slip plane. Increasing their distance from the wall profoundly effects the global dynamics, due to variations in hydrodynamic interaction range. The array undergoes a transition from a traveling wave to either a steady chevron pattern or one punctuated by periodic phase defects. Within the transition between these regimes the system displays behavior reminiscent of chimera states., Comment: 8 pages, 7 figures

Charged colloidal particles trapped at an air--water interface are well known to form an ordered crystal, stabilized by a long ranged repulsion, the details of this repulsion remain something of a mystery, but all experiments performed to date have confirmed a dipolar-repulsion, at least at dilute concentrations. More complex arrangements are often observed, especially at higher concentration, and these seem to be incompatible with a purely repulsive potential. In addition to electrostatic repulsion, interfacial particles may also interact via deformation of the surface: so-called capillary effects. Pair-wise capillary interactions are well understood, and are known to be too small (for these colloidal particles) to overcome thermal effects. Here we show that collective effects may significantly modify the simple pair-wise interactions and become important at higher density, though we remain well below close packing throughout. In particular, we show that the interaction of many interfacial particles can cause much larger interfacial deformations than do isolated particles, and show that the energy of interaction per particle due to this "collective sinking" grows as the number of interacting particles grows. Though some of the parameters in our simple model are unknown, the scaling behaviour is entirely consistent with experimental data, strongly indicating that estimating interaction energy based solely on pair-wise potentials may be too simplistic for surface particle layers., Comment: 19 pages, 6 figures. In press at Soft Matter

We propose a methodology to measure the mechanical properties of membranes from their fluctuations and apply this to optical microscopy measurements of giant unilamellar vesicles of lipids. We analyze the effect of the projection of thermal shape undulations across the focal depth of the microscope. We derive an analytical expression for the mode spectrum that varies with the focal depth and accounts for the projection of fluctuations onto the equatorial plane. A comparison of our model with existing approaches, that use only the apparent equatorial fluctuations without averaging out of this plane, reveals a significant and systematic reduction in the inferred value of the bending rigidity. Our results are in full agreement with the values measured through X-ray scattering and other micromechanical manipulation techniques, resolving a long standing discrepancy with these other experimental methods., Comment: 5 pages, 3 figures, 1 table

Cilia and flagella in biological systems often show large scale cooperative behaviors such as the synchronization of their beats in "metachronal waves". These are beautiful examples of emergent dynamics in biology, and are essential for life, allowing diverse processes from the motility of eukaryotic microorganisms, to nutrient transport and clearance of pathogens from mammalian airways. How these collective states arise is not fully understood, but it is clear that individual cilia interact mechanically,and that a strong and long ranged component of the coupling is mediated by the viscous fluid. We review here the work by ourselves and others aimed at understanding the behavior of hydrodynamically coupled systems, and particularly a set of results that have been obtained both experimentally and theoretically by studying actively driven colloidal systems. In these controlled scenarios, it is possible to selectively test aspects of the living motile cilia, such as the geometrical arrangement, the effects of the driving profile and the distance to no-slip boundaries. We outline and give examples of how it is possible to link model systems to observations on living systems, which can be made on microorganisms, on cell cultures or on tissue sections. This area of research has clear clinical application in the long term, as severe pathologies are associated with compromised cilia function in humans., Comment: 31 pages, to appear in Annual Review of Condensed Matter Physics

The gelation kinetics of silica nanoparticles is a central process in physical chemistry, yet it is not fully understood. Gelation times are measured to increase by over 4 orders of magnitude, simply changing the monovalent salt species from CsCl to LiCl. This striking effect has no microscopic explanation within current paradigms. The trend is consistent with the Hofmeister series, pointing to short-ranged solvation effects not included in the standard colloidal (DLVO) interaction potential. By implementing a simple form for short-range repulsion within a model that relates the gelation timescale to the colloidal interaction forces, we are able to explain the many orders of magnitude difference in the gelation times at fixed salt concentration. The model allows us to estimate the magnitude of the non-DLVO hydration forces, which dominate the interparticle interactions on the length scale of the hydrated ion diameter. This opens the possibility of finely tuning the gelation time scale of nanoparticles by just adjusting the background electrolyte species

We investigate experimentally the relationship between local structure and dynamical arrest in a quasi-2d colloidal model system which approximates hard discs. We introduce polydispersity to the system to suppress crystallisation. Upon compression, the increase in structural relaxation time is accompanied by the emergence of local hexagonal symmetry. Examining the dynamical heterogeneity of the system, we identify three types of motion : "zero-dimensional" corresponding to beta-relaxation, "one-dimensional" or stringlike motion and "two-dimensional" motion. The dynamic heterogeneity is correlated with the local order, that is to say locally hexagonal regions are more likely to be dynamically slow. However we find that lengthscales corresponding to dynamic heterogeneity and local structure do not appear to scale together approaching the glass transition., Comment: 13 papes, to appear in J. Phys.: Condens. Matter

The mean size of exponentially dividing E. coli cells cultured in different nutrient conditions is known to depend on the mean growth rate only. However, the joint fluctuations relating cell size, doubling time and individual growth rate are only starting to be characterized. Recent studies in bacteria (i) revealed the near constancy of the size extension in a single cell cycle (adder mechanism), and (ii) reported a universal trend where the spread in both size and doubling times is a linear function of the population means of these variables. Here, we combine experiments and theory and use scaling concepts to elucidate the constraints posed by the second observation on the division control mechanism and on the joint fluctuations of sizes and doubling times. We found that scaling relations based on the means both collapse size and doubling-time distributions across different conditions, and explain how the shape of their joint fluctuations deviates from the means. Our data on these joint fluctuations highlight the importance of cell individuality: single cells do not follow the dependence observed for the means between size and either growth rate or inverse doubling time. Our calculations show that these results emerge from a broad class of division control mechanisms (including the adder mechanism as a particular case) requiring a certain scaling form of the so-called "division hazard rate function", which defines the probability rate of dividing as a function of measurable parameters. This gives a rationale for the universal body-size distributions observed in microbial ecosystems across many microbial species, presumably dividing with multiple mechanisms. Additionally, our experiments show a crossover between fast and slow growth in the relation between individual-cell growth rate and division time, which can be understood in terms of different regimes of genome replication control., Comment: 39 pages, 7 main figures, 17 supplementary figures

Short DNA linkers are increasingly being exploited for driving specific self-assembly of Brownian objects. DNA-functionalised colloids can assemble into ordered or amorphous materials with tailored morphology. Recently, the same approach has been applied to compliant units, including emulsion droplets and lipid vesicles. The liquid structure of these substrates introduces new degrees of freedom: the tethers can diffuse and rearrange, radically changing the physics of the interactions. Unlike droplets, vesicles are extremely deformable and DNA-mediated adhesion causes significant shape adjustments. We investigate experimentally the thermal response of pairs and networks of DNA-tethered liposomes and observe two intriguing and possibly useful collective properties: negative thermal expansion and tuneable porosity of the liposome networks. A model providing a thorough understanding of this unexpected phenomenon is developed, explaining the emergent properties out of the interplay between the temperature-dependent deformability of the vesicles and the DNA-mediated adhesive forces.

Mechanical forces are obviously important in the assembly of three-dimensional multicellular structures, but their detailed role is often unclear. We have used growing microcolonies of the bacterium \emph{Escherichia coli} to investigate the role of mechanical forces in the transition from two-dimensional growth (on the interface between a hard surface and a soft agarose pad) to three-dimensional growth (invasion of the agarose). We measure the position within the colony where the invasion transition happens, the cell density within the colony, and the colony size at the transition as functions of the concentration of the agarose. We use a phenomenological theory, combined with individual-based computer simulations, to show how mechanical forces acting between the bacterial cells, and between the bacteria and the surrounding matrix, lead to the complex phenomena observed in our experiments - in particular a non-trivial dependence of the colony size at the transition on the agarose concentration. Matching these approaches leads to a prediction for how the friction coefficient between the bacteria and the agarose should vary with agarose concentration. Our experimental conditions mimic numerous clinical and environmental scenarios in which bacteria invade soft matrices, as well as shedding more general light on the transition between two- and three-dimensional growth in multicellular assemblies.