A Mechanistic Model for Bacterial Retention and Infiltration on a Leaf Surface during a Sessile Droplet Evaporation

Dynamical Adsorption Behavior Prediction of Dried Tobacco Leaf Heterogeneous Interfaces through Simulation and Image Recognition Techniques

The process of spraying water and flavorings on dry tobacco is an important factor in the industrial environment and product quality. Tobacco as a complex porous fiber material, the interfacial transfer process of water is complex. In this study, machine learning and image recognition techniques were utilized to quickly obtain the structural parameters of the tobacco surface and construct a cellular structure model of the tobacco surface. In situ observation of the droplet impact spreading process was carried out using a high-speed camera to explore the droplet dissipation dynamics on different surfaces. And the competing processes of droplet wetting and evaporation under the influence of surface microstructure were determined by combining experimental studies and finite element simulation calculations. Based on the characteristics of tobacco pore size distribution, the infiltration under gas-liquid two-phase action was transformed into single-phase flow transfer under capillary force, and the continuous droplet infiltration process was simulated. A parallel artificial membrane permeability measurement method of bionic tobacco waxy layer was constructed for the screening of spray dosing copenetrant. This study brings new insights into the wetting of porous fibrous materials and is important for exploring the wetting process and additive development process influenced by the microstructure.

Forced Wetting Properties of Bacteria-Laden Droplets Experiencing Initial Evaporation

Microbial adhesion and spreading on surfaces are crucial aspects in environmental and industrial settings being also the early stage of complex surface-attached microbial communities known as biofilms. In this work, Pseudomonas fluorescens-laden droplets on hydrophilic substrates (glass coupons) are allowed to partially evaporate before running wetting measurements, to study the effect of evaporation on their interfacial behavior during spillover or splashing. Forced wetting is investigated by imposing controlled centrifugal forces, using a novel rotatory device (Kerberos). At a defined evaporation time, results for the critical tangential force required for the inception of sliding are presented. Microbe-laden droplets exhibit different wetting/spreading properties as a function of the imposed evaporation times. It is found that evaporation is slowed down in bacterial droplets with respect to nutrient medium ones. After sufficient drying times, bacteria accumulate at droplet edges, affecting the droplet shape and thus depinning during forced wetting tests. Droplet rear part does not pin during the rotation test, while only the front part advances and spreads along the force direction. Quantitative results obtained from the well-known Furmidge's equation reveal that force for sliding inception increases as evaporation time increases. This study can be of support for control of biofilm contamination and removal and possible design of antimicrobial/antibiofouling surfaces.

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.

Spatiotemporal evaporating droplet dynamics on fomites enhances long term bacterial pathogenesis

Naturally drying bacterial droplets on inanimate surfaces representing fomites are the most consequential mode for transmitting infection through oro-fecal route. We provide a multiscale holistic approach to understand flow dynamics induced bacterial pattern formation on fomites leading to pathogenesis. The most virulent gut pathogen, Salmonella Typhimurium (STM), typically found in contaminated food and water, is used as model system in the current study. Evaporation-induced flow in sessile droplets facilitates the transport of STM, forming spatio-temporally varying bacterial deposition patterns based on droplet medium's nutrient scale. Mechanical and low moisture stress in the drying process reduced bacterial viability but interestingly induced hyper-proliferation of STM in macrophages, thereby augmenting virulence in fomites. In vivo studies of fomites in mice confirm that STM maintains enhanced virulence. This work demonstrates that stressed bacterial deposit morphologies formed over small timescale (minutes) on organic and inorganic surfaces, plays a significant role in enhancing fomite's pathogenesis over hours and days.

Engineering modeling frameworks for microbial food safety at various scales

The landscape of mathematical model-based understanding of microbial food safety is wide and deep, covering interdisciplinary fields of food science, microbiology, physics, and engineering. With rapidly growing interest in such model-based approaches that increasingly include more fundamental mechanisms of microbial processes, there is a need to build a general framework that steers this evolutionary process by synthesizing literature spread over many disciplines. The framework proposed here shows four interconnected, complementary levels of microbial food processes covering sub-cellular scale, microbial population scale, food scale, and human population scale (risk). A continuum of completely mechanistic to completely empirical models, widely-used and emerging, are integrated into the framework; well-known predictive microbiology modeling being a part of this spectrum. The framework emphasizes fundamentals-based approaches that should get enriched over time, such as the basic building blocks of microbial population scale processes (attachment, migration, growth, death/inactivation and communication) and of food processes (e.g., heat and moisture transfer). A spectrum of models are included, for example, microbial population modeling covers traditional predictive microbiology models to individual-based models and cellular automata. The models are shown in sufficient quantitative detail to make obvious their coupling, or their integration over various levels. Guidelines to combine sub-processes over various spatial and time scales into a complete interdisciplinary and multiphysics model (i.e., a system) are provided, covering microbial growth/inactivation/transport and physical processes such as fluid flow and heat transfer. As food safety becomes increasingly predictive at various scales, this synthesis should provide its roadmap. This big picture and framework should be futuristic in driving novel research and educational approaches.