Drying of bio-colloidal sessile droplets: Advances, applications, and perspectives

Drying of biologically-relevant sessile droplets, including passive systems such as DNA, proteins, plasma, and blood, as well as active microbial systems comprising bacterial and algal dispersions, has garnered considerable attention over the last decades. Distinct morphological patterns emerge when bio-colloids undergo evaporative drying, with significant potential in a wide range of biomedical applications, spanning bio-sensing, medical diagnostics, drug delivery, and antimicrobial resistance. Consequently, the prospects of novel and thrifty bio-medical toolkits based on drying bio-colloids have driven tremendous progress in the science of morphological patterns and advanced quantitative image-based analysis. This review presents a comprehensive overview of bio-colloidal droplets drying on solid substrates, focusing on the experimental progress during the last ten years. We provide a summary of the physical and material properties of relevant bio-colloids and link their native composition (constituent particles, solvent, and concentrations) to the patterns emerging due to drying. We specifically examined the drying patterns generated by passive bio-colloids (e.g., DNA, globular, fibrous, composite proteins, plasma, serum, blood, urine, tears, and saliva). This article highlights how the emerging morphological patterns are influenced by the nature of the biological entities and the solvent, micro- and global environmental conditions (temperature and relative humidity), and substrate attributes like wettability. Crucially, correlations between emergent patterns and the initial droplet compositions enable the detection of potential clinical abnormalities when compared with the patterns of drying droplets of healthy control samples, offering a blueprint for the diagnosis of the type and stage of a specific disease (or disorder). Recent experimental investigations of pattern formation in the bio-mimetic and salivary drying droplets in the context of COVID-19 are also presented. We further summarized the role of biologically active agents in the drying process, including bacteria, algae, spermatozoa, and nematodes, and discussed the coupling between self-propulsion and hydrodynamics during the drying process. We wrap up the review by highlighting the role of cross-scale in situ experimental techniques for quantifying sub-micron to micro-scale features and the critical role of cross-disciplinary approaches (e.g., experimental and image processing techniques with machine learning algorithms) to quantify and predict the drying-induced features. We conclude the review with a perspective on the next generation of research and applications based on drying droplets, ultimately enabling innovative solutions and quantitative tools to investigate this exciting interface of physics, biology, data sciences, and machine learning.

Effect of temperature on evaporation dynamics of sheep's blood droplets and topographic analysis of induced patterns

To characterize various induced phenomena and the blood of healthy sheep using several parameters, the evaporation dynamics of 72 drops of sheep blood evaporated at several temperatures: 23, 37, 60, and 90 °C on glass hydrophilic substrates were studied. This allows the prediction of the sheep blood pattern, knowing the surface temperature and vice versa. To determine the variation in the Marangoni number between the center and the triple line, an infrared thermography method was used to measure the temperature variation along the surface of the drop. Simultaneously, a high-performance camera was used to measure the variation in the height of the drop during the evaporation using a superior algorithm software for image analysis, drop shape analyzer, under controlled conditions (Humidity = 40%, T_atm = 23 °C). The study of the evaporation dynamics and pattern formation shows the effect of temperature on the flow circulation inside the drop, resulting in the final deposit. The results showed two categories corresponding to two different evaporation phenomena induced by the thermal Marangoni effect. Furthermore, to transform the induced pattern of sheep blood evaporation into a 3D image, a topographic study was performed using a highly accurate, fast, and flexible optical 3D measurement system. The topographic parameters were subsequently extracted from these 3D images. The statistical study showed a good correlation between the topographic parameters and the surface temperature, and a significant difference between each temperature group for each parameter.

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns

The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the stains left behind by their drying droplets. To analyze the complex stain patterns, deep-learning neuronal networks are challenged with polarized light microscopy images derived from the drying droplet deposits of a range of amyloid beta (1-42) (Aβ₄₂ ) peptides. These peptides differ in a single amino acid residue and represent hereditary mutants of Alzheimer's disease. Stain patterns are not only reproducible but also result in comprehensive stratification of eight amyloid beta (Aβ) variants with predictive accuracies above 99%. Similarly, peptide stains of a range of distinct Aβ₄₂ peptide conformations are identified with accuracies above 99%. The results suggest that a method as simple as drying a droplet of a peptide solution onto a solid surface may serve as an indicator of minute, yet structurally meaningful differences in peptides' primary and secondary structures. Scalable and accurate detection schemes for stratification of conformational and structural protein alterations are critically needed to unravel pathological signatures in many human diseases such as Alzheimer's and Parkinson's disease.

Patterns from dried drops as a characterisation and healthcare diagnosis technique, potential and challenges: A review

When particulate-laden droplets evaporate, they leave behind complex patterns on the substrate depending on their composition and the dynamics of their evaporation. Over the past two decades, there has been an increased interest in interpreting these patterns due to their numerous applications in biomedicine, forensics, food quality analysis and inkjet printing. The objective of this review is to investigate the use of patterns from dried drops as a characterisation and diagnosis technique. The patterns left behind by dried drops of various complex fluids are categorised. The potential applications of these patterns are presented, focussing primarily on healthcare, where the future impact could be greatest. A discussion on the limitations which must be overcome and prospective works that may be carried out to allow for widespread implementation of this technique is presented in conclusion.

Diagnostic tests based on pattern formation in drying body fluids - A mapping review

There are numerous diagnostic tests based on pattern formation in desiccating body fluids, where the pattern or some of its characteristics constitute the diagnostic test outcome. However, partially due to the development in different time periods, and partially due to publications in languages different from English, most of these diagnostic tests exist as separate approaches and have never been grouped, systematized, nor compared with each other. In the present mapping review, we performed a wide literature search with the aim to collect all diagnostic tests based on pattern formation in desiccating body fluids. Furthermore, we grouped the identified diagnostic tests according to their experimental protocols, type of body fluids investigated, and target conditions, and propose so for the first time a classification of different diagnostic tests based on pattern formation in desiccating body fluids. The literature search revealed 1603 publications, out of which 141 were included into the review. Following three main classification criteria (way of deposition of the fluid for desiccation, addition of reagents, and spatial restrictions during evaporation), we identified six different methods; following a further classification concerning the analyzed body fluid we identified 30 different diagnostic tests based on pattern formation in evaporating body fluids. Amongst these tests are well-known procedures such as ferning tests (tear ferning for the assessment of tear film quality, saliva and cervical mucus ferning for the detection of the fertile period, and amniotic fluid ferning for the diagnosis of fetal membrane rupture), whereas other tests are less well-established. In the latter group, the most frequently investigated body fluids were serum, saliva, and blood; the most frequently addressed target conditions were cancer, inflammation, and benign tumors. We recommend conducting further systematic reviews and meta-analyses concerning groups of methods addressing the same target condition.

Temperature and Concentration Dependence of Human Whole Blood and Protein Drying Droplets

The drying of bio-colloidal droplets can be used in many medical and forensic applications. The whole human blood is the most complex bio-colloid system, whereas bovine serum albumin (BSA) is the simplest. This paper focuses on the drying characteristics and the final morphology of these two bio-colloids. The experiments were conducted by varying their initial concentrations, and the solutions were dried under various controlled substrate temperatures using optical and scanning electron microscopy. The droplet parameters (the contact angle, the fluid front, and the first-order image statistics) reveal the drying process's unique features. Interestingly, both BSA and blood drying droplets' contact angle measurements show evidence of a concentration-driven transition as the behavior changes from non-monotonic to monotonic decrease. This result indicates that this transition behavior is not limited to multi-component bio-colloid (blood) only, but may be a phenomenon of a bio-colloidal solution containing a large number of interacting components. The high dilution of blood behaves like the BSA solution. The ring-like deposition, the crack morphology, and the microstructures suggest that the components have enough time to segregate and deposit onto the substrate under ambient conditions. However, there is insufficient time for evaporative-driven segregation to occur at elevated temperatures, as expected.

Concentration-driven phase transition and self-assembly in drying droplets of diluting whole blood

Multi-colloidal systems exhibit a variety of structural and functional complexity owing to their ability to interact amongst different components into self-assembled structures. This paper presents experimental confirmations that reveal an interesting sharp phase transition during the drying state and in the dried film as a function of diluting concentrations ranging from 100% (undiluted whole blood) to 12.5% (diluted concentrations). An additional complementary contact angle measurement exhibits a monotonic decrease with a peak as a function of drying. This peak is related to a change in visco-elasticity that decreases with dilution, and disappears at the dilution concentration for the observed phase transition equivalent to 62% (v/v). This unique behavior is clearly commensurate with the optical image statistics and morphological analysis; and it is driven by the decrease in the interactions between various components within this bio-colloid. The implications of these phenomenal systems may address many open-ended questions of complex hierarchical structures.

Self-Assembly of Nanoparticles from Evaporating Sessile Droplets: Fresh Look into the Role of Particle/Substrate Interaction

We studied the dependence of solid deposit shape obtained by free drying of sessile drops on particle concentration and Derjaguin-Landau-Verwey-Overbeek (DLVO) particle/substrate interaction. In contrast to previous contributions using pH as a control parameter of interactions, we investigated an unprecedentedly wide range of concentrations and particle/substrate DLVO forces by modifying the nature of the substrate and particles as well as their size and surface chemistry, whereas long-distance repulsive interactions between particles were maintained for most of the drying time. Our main result is that the different shapes of deposits obtained by modifying the particle concentration are the same in the different regimes of concentration regardless of particle/substrate interaction in the studied range of DLVO forces and particle concentrations. The second result is that, contrary to expectations, the dominant morphology of dry patterns at low particle concentration always shows a dotlike pattern for all the studied systems.

Drop Drying on the Sensor: One More Way for Comparative Analysis of Liquid Media

It is known that the processes of self-organization of the components of drying a liquid drop on a solid substrate are well reproduced under the same external conditions and are determined only by the composition and dispersion of the liquid. If the drop dries on the surface of the sensor device, these processes can be recorded and used as a passport characteristic of the liquid. The first half of the article is devoted to the description of the principles of the method and the proof of the validity of our assumptions. The second half of the article is devoted to the development of a user-friendly version of the device, where the change in the real and imaginary parts of the electrical impedance of the resonator was used as an informative parameter. The measure of the closeness of the relative positions of the hodographs of the compared samples on the complex plane is used as a criterion for the similarity-/-difference of various liquids. The design of a new sensor device and the results of its tests for distinguishing between different brands of alcoholic beverages and reconstituted milk of different concentrations are presented.

Interfacial energy driven distinctive pattern formation during the drying of blood droplets

HYPOTHESIS

Dried blood droplet morphology may potentially serve as an alternative biomarker for several patho-physiological conditions. The deviant properties of the red blood cells and the abnormal composition of diseased samples are hypothesized to manifest through unique cell-cell and cell-substrate interactions leading to different morphological patterns. Identifying distinctive morphological trait from a large sample size and proposing confirmatory explanations are necessary to establish the signatory pattern as a potential biomarker to differentiate healthy and diseased samples.

EXPERIMENTS

Comprehensive experimental investigation was undertaken to identify the signatory dried blood droplet patterns. The corresponding image based analysis was in turn used to differentiate the blood samples with a specific haematological disorder "Thalassaemia" from healthy ones. Relevant theoretical analysis explored the role of cell-surface and cell-cell interactions pertinent to the formation of the distinct dried patterns.

FINDINGS

The differences observed in the dried blood patterns, specifically the radial crack lengths, were found to eventuate from the differences in the overall interaction energies of the system. A first-generation theoretical analysis, with the mean field approximation, also confirmed similar outcome and justified the role of the different physico-chemical properties of red blood cells in diseased samples resulting in shorter radial cracks.

Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets

One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid surface. The analysis of dried patterns from blood droplets has recently gained a lot of attention, experimentally and theoretically, due to its potential application in diagnostic medicine and forensic science. This paper presents evidence that images of dried blood droplets have a signature revealing the exhaustion level of the person, and discloses an entirely novel approach to studying human dried blood droplet patterns. We took blood samples from 30 healthy young male volunteers before and after exhaustive exercise, which is well known to cause large changes to blood chemistry. We objectively and quantitatively analysed 1800 images of dried blood droplets, developing sophisticated image processing analysis routines and optimising a multivariate statistical machine learning algorithm. We looked for statistically relevant correlations between the patterns in the dried blood droplets and exercise-induced changes in blood chemistry. An analysis of the various measured physiological parameters was also investigated. We found that when our machine learning algorithm, which optimises a statistical model combining Principal Component Analysis (PCA) as an unsupervised learning method and Linear Discriminant Analysis (LDA) as a supervised learning method, is applied on the logarithmic power spectrum of the images, it can provide up to 95% prediction accuracy, in discriminating the physiological conditions, i.e., before or after physical exercise. This correlation is strongest when all ten images taken per volunteer per condition are averaged, rather than treated individually. Having demonstrated proof-of-principle, this method can be applied to identify diseases.

Microfluidic system for screening disease based on physical properties of blood

Introduction: A key feature of the 'One Health' concept pertains to the design of novel point of care systems for largescale screening of health of the population residing in resource-limited areas of low- and middle-income countries with a view to obtaining data at a community level as a rationale to achieve better public health outcomes. The physical properties of blood are different for different samples. Our study involved the development of an innovative system architecture based upon the physical properties of blood using automated classifiers to enable large-scale screening of the health of the population living in resource-limited settings. Methods: The proposed system consisted of a simple, robust and low-cost sensor with capabilities to sense and measure even the minute changes in the physical properties of blood samples. In this system, the viscosity of blood was derived from a power-law model coupled with the Rabinowitsch-Mooney correction for non-Newtonian shear rates developed in a steady laminar Poiseuille flow. Surface tension was measured by solving the Young-Laplace equation for pendant drop shape hanging on a vertical needle. An anticipated outcome of this study would be the development of a novel automated classifier based upon the rheological attributes of blood. This automated classifier would have potential application in evaluating the health status of a population at regional and global levels. Results: The proposed system was used to measure the physical properties of various samples like normal, tuberculous and anemic blood samples. The results showed that the physical properties of these samples were different as compared to normal blood samples. The major advantage of this system was low-cost, as well as its simplicity and portability. Conclusion: In this work, we proposed making a case for the validation of a low-cost version of a microfluidic system capable of scanning large populations for a variety of diseases as per the WHO mandate of "One Health".

Blood drop patterns: Formation and applications

The drying of a drop of blood or plasma on a solid substrate leads to the formation of interesting and complex patterns. Inter- and intra-cellular and macromolecular interactions in the drying plasma or blood drop are responsible for the final morphologies of the dried patterns. Changes in these cellular and macromolecular components in blood caused by diseases have been suspected to cause changes in the dried drop patterns of plasma and whole blood, which could be used as simple diagnostic tools to identify the health of humans and livestock. However, complex physicochemical driving forces involved in the pattern formation are not fully understood. This review focuses on the scientific development in microscopic observations and pattern interpretation of dried plasma and whole blood samples, as well as the diagnostic applications of pattern analysis. Dried drop patterns of plasma consist of intricate visible cracks in the outer region and fine structures in the central region, which are mainly influenced by the presence and concentration of inorganic salts and proteins during drying. The shrinkage of macromolecular gel and its adhesion to the substrate surface have been thought to be responsible for the formation of the cracks. Dried drop patterns of whole blood have three characteristic zones; their formation as functions of drying time has been reported in the literature. Some research works have applied engineering treatment to the evaporation process of whole blood samples. The sensitivities of the resultant patterns to the relative humidity of the environment, the wettability of the substrates, and the size of the drop have been reported. These research works shed light on the mechanisms of spreading, evaporation, gelation, and crack formation of the blood drops on solid substrates, as well as on the potential applications of dried drop patterns of plasma and whole blood in diagnosis.

Pattern formation of drying lyotropic liquid crystalline droplet

We present a study of pattern formation in drying sessile droplets of aqueous solutions of cetyltrimethylammonium bromide (CTAB)–water system using polarising optical microscopy (POM) and computer simulation.