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

Emergence of Novel Patterns in Dried Droplets of Combinations of Low Potencies of Plant Extracts and Salts Compared to Single Substances: A Pilot Study

BACKGROUND

 Patterns in dried droplets have previously facilitated the characterization of homeopathic preparations of different substances at low potency levels. The objective of the present study was to examine combinations of plant extracts and salts in 2x and 3x potency (nominal dilution of 10-2 and 10-3) and to determine which influence the plant and salt components have on the patterns of these mixtures.

METHODS

 We used the droplet evaporation method (DEM) to test seven plant extracts, five salt solutions and their 1:1 combinations, either in 2x or 3x potency levels. Drops of each sample were evaporated and the resulting patterns were photographed with a dark-field microscope at 25-fold and 100-fold magnification. The images were analyzed mainly visually for their characteristics; a supporting quantitative analysis was performed by means of the computer program ImageJ for several textural features.

RESULTS

 Patterns of 2x potencies showed more and richer structures than those of 3x potencies. At both tested potency levels, patterns of plant-salt potency combinations exhibited structures that were different from those of single potencies.

CONCLUSION

 Combining homeopathic potencies led to the emergence of novel patterns differing from those formed by the single components. There were noticeable differences in the extent to which specific salts appeared to retain their characteristic patterns in relation to the plant potency with which they were combined. This pilot study has identified promising potential for the further investigation of homeopathic preparations in low dilution ranges by means of DEM, with the aim to understand better the diverse pattern-forming processes that take place in combined compared with single potency droplets. Such endeavor would help to address the current lack of fundamental research on potency combinations.

A low-cost picowatt calorimeter using a flexible printed circuit board

Calorimetry is crucial in biology, chemistry, physics, and pharmaceutical research, enabling the detection of heat changes at nanowatt and picowatt levels. However, traditional calorimetry systems are often limited by high costs and complex fabrication processes. Here, we reduce the cost and fabrication complexity of microcalorimeters by utilizing widely available flexible printed circuit manufacturing processes. This device achieves temperature and power resolutions of ≈ 6 μK and ≈ 654 pW in vacuum. Its feasibility is validated across a wide range of measurements, including salt crystallization, protein crystallization, and cellular metabolism. Our concept enhances the accessibility of microcalorimeters for high-resolution thermal analysis, which is challenging for conventional calorimeters.

Age-related features of the pattern of oral fluid patients with non-alcoholic fatty liver disease

INTRODUCTION

In recent years, non-invasive screening methods for diagnosing various human conditions, including those corresponding to biological age, have attracted great interest, one of the sources for non-invasive research of which is oral fluid.

Vortex-like vs. turbulent mixing of a Viscum album preparation affects crystalline structures formed in dried droplets

Various types of motion introduced into a solution can affect, among other factors, the alignment and positioning of molecules, the agglomeration of large molecules, oxidation processes, and the production of microparticles and microbubbles. We employed turbulent mixing vs. laminar flow induced by a vortex vs. diffusion-based mixing during the production of Viscum album Quercus L. 10-3 following the guidelines for manufacturing homeopathic preparations. The differently mixed preparation variants were analyzed using the droplet evaporation method. The crystalline structures formed in dried droplets were photographed and analyzed using computer-supported image analysis and deep learning. Computer-supported evaluation and deep learning revealed that the patterns of the variant succussed under turbulence are characterized by lower complexity, whereas those obtained from the vortex-mixed variant are characterized by greater complexity compared to the diffusion-based mixed control variant. The droplet evaporation method could provide a relatively inexpensive means of testing the effects of liquid flow and serve as an alternative to currently used methods.

Chronobiology of Viscum album L.: a time series of daily metabolomic fingerprints spanning 27 years

Introduction: European mistletoe (Viscum album L.) has been gaining increasing interest in the field of oncology as a clinically relevant adjunctive treatment in many forms of cancer. In the field of phytopharmacology, harvesting time is pivotal. In the last century, a form of metabolomic fingerprinting based on pattern formation was proposed as a way to determine optimal harvesting times to ensure high quality of mistletoe as raw material for pharmaceutical use. In order to further evaluate the information obtained with this metabolomic fingerprinting method, we analysed a large time series of previously undigitised daily mistletoe chromatograms dating back to the 1950s. Methods: These chromatograms were scanned and evaluated using computerized image analysis, resulting in 12 descriptors for each individual chromatogram. We performed a statistical analysis of the data obtained, investigating statistical distributions, cross-correlations and time self-correlations. Results: The analysed dataset spanning about 27 years, contains 19,037 evaluable chromatograms in daily resolution. Based on the distribution and cross-correlation analyses, the 12 descriptors could be clustered into six independent groups describing different aspects of the chromatograms. One descriptor was found to mirror the annual rhythm being well correlated with temperature and a phase shift of 10 days. The time self-correlation analysis showed that most other descriptors had a characteristic self-correlation of ∼50 days, which points to further infradian rhythms (i.e., more than 24 h). Discussion: To our knowledge, this dataset is the largest of its type. The combination of this form of metabolomic fingerprinting with the proposed computer analysis seems to be a promising tool to characterise biological variations of mistletoe. Additional research is underway to further analyse the different rhythms present in this dataset.

Self-assembled Patterns Formed in Evaporating Droplets to Analyze Bi-component Homeopathic Preparations in the Low Dilution Range

BACKGROUND

Homeopathic complex remedies, composed of several homeopathic medicines in the low potency range, are frequently used in the treatment of a number of common disorders. At the same time, they represent an almost unexplored area of research. Are complex remedies just additive mixtures of the components, or are there interactions between the latter leading to new properties of the complex?

METHODS

In the present study, we analyzed as an example the simple bi-component complex, Luffa 4x - Mercurius bijodatus 9x, by means of patterns from evaporated droplets and tested what influences the complex's single compounds have upon the patterns and if there are any interactions. For this purpose, we compared in a series of five experiments patterns from evaporated droplets of the complex, Luffa 4x - Mercurius bijodatus 9x, and three comparison samples in which one or both of the complex's compounds were replaced by potentized solute. The patterns were photographed and evaluated for their gray-level distribution and texture using the software ImageJ. The experimental set-up's stability was tested by means of systematic control experiments.

RESULTS

We found that Mercurius bijodatus 9x significantly influenced the patterns of Luffa 4x, increasing their homogeneity; at the same time, the patterns of Mercurius bijodatus 9x combined with solvent were more heterogeneous than those obtained from a control consisting of two pure solvents.

CONCLUSION

In this phenomenological assay, the complex Luffa 4x - Mercurius bijodatus 9x does not correspond to a simple addition of the components. The exact nature of the underlying interaction needs to be elucidated in further investigations.

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.

Pattern of an Evaporated Colloidal Droplet on a Porous Membrane Dictated by Competitive Processes of Flow and Absorption

Understanding the deposition pattern formed by an evaporated colloidal drop is of fundamental and technological interest. Such an evaporative process is important in various applications starting from inkjet printing to disease diagnosis. In this work, it is shown that the deposit pattern on a porous membrane can be tuned by varying the colloidal viscosity and membrane pore size. We have used small-angle X-ray scattering (SAXS) in scanning mode for profiling of deposit morphology and also for estimation of the interparticle correlation. It is demonstrated that low viscosity and small pore size favor a centrally dipped pattern owing to the coffee ring effect, which can be modified to a contrasting centrally peaked pattern by increasing the viscosity and pore size. To comprehend the experimental observations, a computer model has been developed using a continuity equation that well corroborates the experimental observations on the final deposited pattern and also provides the time evolution of the pattern. The work provides a way to tune the pattern of colloidal stain on a porous substrate by controlling flow and absorption.