Texture Analysis of Dried Droplets for the Quality Control of Medicines

Dried blood drops on vertical surfaces

The analysis of structures in dried droplets has made it possible to detect the presence and conformational state of macromolecules in relevant biofluids. Therefore, the implementation of novel drying strategies for pattern formation could facilitate the identification of biomarkers for the diagnosis of pathologies. We present an experimental study of patterns formed by evaporating water-diluted blood droplets on a vertical surface. Three significant morphological features were observed in vertical droplet deposits: (1) The highest concentration of non-volatile molecules is consistently deposited in the lower part of the droplet, regardless of erythrocyte concentration. (2) The central region of deposits decreases rapidly with hematocrit; (3) At high erythrocyte concentrations (36-40% HCT), a broad coating of blood serum is produced in the upper part of the deposit. These findings are supported by the radial intensity profile, the relative thickness of the crown, the aspect ratio of the deformation, the relative area of the central region, and the Entropy of the Gray Level Co-occurrence Matrix Entropy (GLCM). Moreover, we explore the pattern formation during the drying of vertical blood drops. We found that hematocrit concentration has a significant impact on droplet drying dynamics. Finally, we conducted a proof-of-concept test to investigate the impact of vertical droplet evaporation on blood droplets with varying lipid concentrations. The results revealed that it is possible to differentiate between deposits with normal, slightly elevated, and moderately elevated lipid levels using only the naked eye.

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.

Deep learning applied to analyze patterns from evaporated droplets of Viscum album extracts

This paper introduces a deep learning based methodology for analyzing the self-assembled, fractal-like structures formed in evaporated droplets. To this end, an extensive image database of such structures of the plant extract Viscum album Quercus\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^{-3}$$\end{document}10-3 was used, prepared by three different mixing procedures (turbulent, laminar, and diffusion based). The proposed pattern analysis approach is based on two stages: (1) automatic selection of patches that exhibit rich texture along the database; and (2) clustering of patches in accordance with prevalent texture by means of a Dense Convolutional Neural Network. The fractality of the patterns in each cluster is verified through Local Connected Fractal Dimension histograms. Experiments with Gray-Level Co-Occurrence matrices are performed to determine the benefit of the proposed approach in comparison with well established image analysis techniques. For the investigated plant extract, significant differences were found between the production modalities; whereas the patterns obtained by laminar flow showed the highest fractal structure, the patterns obtained by the application of turbulent mixture exhibited the lowest fractality. Our approach is the first to analyze, at the pure image level, the clustering properties of regions of interest within a database of evaporated droplets. This allows a greater description and differentiation of the patterns formed through different mixing procedures.

Evaporation Patterns of Dextran-Poly(Ethylene Glycol) Droplets with Changes in Wettability and Compatibility

The dextran−PEG system is one of the most famous systems exhibiting phase separation. Various phase behaviors, including the evaporation process of the dextran−PEG system, have been studied in order to understand the physicochemical mechanism of intracellular phase separation and the effect of condensation on the origin of life. However, there have been few studies in dilute regime. In this study, we focused on such regimes and analyzed the pattern formation by evaporation. The specificity of this regime is the slow onset of phase separation due to low initial concentration, and the separated phases can have contrasting wettability to the substrate as evaporation progresses. When the polymer concentration is rather low (<5 wt%), the dextran−PEG droplets form a phase-separated pattern, consisting of PEG at the center and dextran ring of multiple strings pulling from the ring. This pattern formation is explained from the difference in wettability and compatibility between dextran and PEG upon condensation. At the initial dilute stage, the dextran-rich phase with higher wettability accumulates at the contact line of the droplet to form a ring pattern, and then forms multiple domains due to density fluctuation. The less wettable PEG phase recedes and pulls the dextran domains, causing them to deform into strings. Further condensation leads to phase separation, and the condensed PEG with improved wettability stops receding and prevents a formed circular pattern. These findings suggest that evaporation patterns of polymer blend droplets can be manipulated through changes in wettability and compatibility between polymers due to condensation, thus providing the basis to explore origins of life that are unique to the process of condensate formation from dilute systems.

Patterns in Dried Droplets to Detect Unfolded BSA

The morphological analysis of patterns in dried droplets has allowed the generation of efficient techniques for the detection of molecules of medical interest. However, the effectiveness of this method to reveal the coexistence of macromolecules of the same species, but different conformational states, is still unknown. To address this problem, we present an experimental study on pattern formation in dried droplets of bovine serum albumin (BSA), in folded and unfolded conformational states, in saline solution (NaCl). Folded proteins produce a well-defined coffee ring and crystal patterns all over the dry droplet. Depending on the NaCl concentration, the crystals can be small, large, elongated, entangled, or dense. Optical microscopy reveals that the relative concentration of unfolded proteins determines the morphological characteristics of deposits. At a low relative concentration of unfolded proteins (above 2%), small amorphous aggregates emerge in the deposits, while at high concentrations (above 16%), the "eye-like pattern", a large aggregate surrounded by a uniform coating, is produced. The radial intensity profile, the mean pixel intensity, and the entropy make it possible to characterize the patterns in dried droplets. We prove that it is possible to achieve 100% accuracy in identifying 4% of unfolded BSA contained in a protein solution.