Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows.

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocity measurements in pial perivascular spaces (PVSs) or low-resolution measurements from brain-wide imaging. Additionally, volume flow rate, pressure, and shear stress variation in PVSs are essentially impossible to measure in vivo. Here, we show that artificial intelligence velocimetry (AIV) can integrate sparse velocity measurements with physics-informed neural networks to quantify CSF flow in PVSs. With AIV, we infer three-dimensional (3D), high-resolution velocity, pressure, and shear stress. Validation comes from training with 70% of PTV measurements and demonstrating close agreement with the remaining 30%. A sensitivity analysis on the AIV inputs shows that the uncertainty in AIV inferred quantities due to uncertainties in the PVS boundary locations inherent to in vivo imaging is less than 30%, and the uncertainty from the neural net initialization is less than 1%. In PVSs of N = 4 wild-type mice we find mean flow speed 16.33 ± 11.09 µm/s, volume flow rate 2.22 ± 1.983 × 103 µm3/s, axial pressure gradient ( - 2.75 ± 2.01)×10-4 Pa/µm (-2.07 ± 1.51 mmHg/m), and wall shear stress (3.00 ± 1.45)×10-3 Pa (all mean ± SE). Pressure gradients, flow rates, and resistances agree with prior predictions. AIV infers in vivo PVS flows in remarkable detail, which will improve fluid dynamic models and potentially clarify how CSF flow changes with aging, Alzheimer's disease, and small vessel disease.

Rheology of debris flow materials is controlled by the distance from jamming.

Debris flows are dense and fast-moving complex suspensions of soil and water that threaten lives and infrastructure. Assessing the hazard potential of debris flows requires predicting yield and flow behavior. Reported measurements of rheology for debris flow slurries are highly variable and sometimes contradictory due to heterogeneity in particle composition and volume fraction ([Formula: see text]) and also inconsistent measurement methods. Here we examine the composition and flow behavior of source materials that formed the postwildfire debris flows in Montecito, CA, in 2018, for a wide range of [Formula: see text] that encapsulates debris flow formation by overland flow. We find that shear viscosity and yield stress are controlled by the distance from jamming, [Formula: see text], where the jamming fraction [Formula: see text] is a material parameter that depends on grain size polydispersity and friction. By rescaling shear and viscous stresses to account for these effects, the data collapse onto a simple nondimensional flow curve indicative of a Bingham plastic (viscoplastic) fluid. Given the highly nonlinear dependence of rheology on [Formula: see text], our findings suggest that determining the jamming fraction for natural materials will significantly improve flow models for geophysical suspensions such as hyperconcentrated flows and debris flows.

Tracking colloidal silica particles to evaluate their dispersion and interactions in concentrated suspensions under shear force applications.

This study aimed to characterize interactions within colloidal silica particles in their concentrated suspensions, using rheo-confocal measurements and imaging, followed by image analysis. We studied the effect of shear rate (0-500 s-1) and solution pH (6, 10) on the dispersion degree of colloidal silica particles via the determination and comparison of interparticle distances and their modeling. Images corresponding to different shear rates were analyzed to identify the coordinates of the particles. These coordinates were further analyzed to calculate the distance among the particles and then their surface-to-surface distance normalized by the particle diameter (H/D). It was found that the population of the particles per unit area of the image and H/D varied with increasing shear rate. The comparison between experimentally measured and theoretically calculated H/D identified that for some particles, the former was shorter than the latter, indicating the unexpected attractions among them against the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. Then, the modification of previously reported equations for H/D was suggested and confirmed its validity. Assuming pair potential interaction and hydrodynamic interaction were the main non-DLVO interactions, their magnitudes were calculated and confirmed the significance of pH and shear application strength on particle dispersion/coagulation.

Ergodic speckle contrast optical coherence tomography velocimetry of rapid blood flow.

Visualizing a 3D blood flow velocity field through noninvasive imaging is crucial for analyzing hemodynamic mechanisms in areas prone to disorders. However, traditional correlation-based optical coherence tomography (OCT) velocimetry techniques have a maximum measurable flow velocity depending on the A-line rate. We presented the ergodic speckle contrast OCT (ESCOCT) to break the bottleneck in measuring the rapid blood flow velocity. It achieved a measurement of blood flow velocity ranging from 9.5 to 280 mm/s using a 100 kHz swept-source (SS) OCT based on 100 A-repeats scanning mode. Addressing the non-ergodic problem of temporal OCT signals by integrating more consecutive A-scans, ESCOCT can enable the estimation for lower velocity flows by increasing A-repeats. ESCOCT provided a wide dynamic range with no upper limit on measuring blood flow velocity with an adequate signal-to-noise ratio and improved the sensitivity and accuracy of the hemodynamic assessment.

Thermal-tagging photoacoustic remote sensing flowmetry.

Ultrasound coupling is one of the critical challenges for traditional photoacoustic (or optoacoustic) microscopy (PAM) techniques transferred to the clinical examination of chronic wounds and open tissues. A promising alternative potential solution for breaking the limitation of ultrasound coupling in PAM is photoacoustic remote sensing (PARS), which implements all-optical non-interferometric photoacoustic measurements. Functional imaging of PARS microscopy was demonstrated from the aspects of histopathology and oxygen metabolism, while its performance in hemodynamic quantification remains unexplored. In this Letter, we present an all-optical thermal-tagging flowmetry approach for PARS microscopy and demonstrate it with comprehensive mathematical modeling and ex vivo and in vivo experimental validations. Experimental results demonstrated that the detectable range of the blood flow rate was from 0 to 12 mm/s with a high accuracy (measurement error:±1.2%) at 10-kHz laser pulse repetition rate. The proposed all-optical thermal-tagging flowmetry offers an effective alternative approach for PARS microscopy realizing non-contact dye-free hemodynamic imaging.

Pinching dynamics, extensional rheology, and stringiness of saliva substitutes.

Saliva substitutes are human-made formulations extensively used in medicine, food, and pharmaceutical research to emulate human saliva's biochemical, tribological, and rheological properties. Even though extensional flows involving saliva are commonly encountered in situations such as swallowing, coughing, sneezing, licking, drooling, gleeking, and blowing spit bubbles, rheological evaluations of saliva and its substitutes in most studies rely on measured values of shear viscosity. Natural saliva possesses stringiness or spinnbarkeit, governed by extensional rheology response, which cannot be evaluated or anticipated from the knowledge of shear rheology response. In this contribution, we comprehensively examine the rheology of twelve commercially available saliva substitutes using torsional rheometry for rate-dependent shear viscosity and dripping-onto-substrate (DoS) protocols for extensional rheology characterization. Even though most formulations are marketed as having suitable rheology, only three displayed measurable viscoelasticity and strain-hardening. Still, these too, failed to emulate the viscosity reduction with the shear rate observed for saliva or match perceived stringiness. Finally, we explore the challenges in creating saliva-like formulations for dysphagia patients and opportunities for using DoS rheometry for diagnostics and designing biomimetic fluids.

Yield stress Measurement of municipal sludge: A comprehensive evaluation of testing methods and concentration effects using a rotational rheometer.

Accurate prediction and measurement of yield stress are crucial for optimizing sludge treatment and disposal. However, the differences and applicability of various methods for measuring yield stress are subjects of ongoing debate. Meanwhile, literature on measuring sludge yield stress is limited to low solid concentrations (TS <10%), understanding and studying the yield stress of medium to high solid concentration sludge is crucial due to increasingly stringent standards for sludge treatment and disposal. So, this study employed a rotational rheometer to measure sludge yield stress across a wide range of TS (4-50%) using steady shear, dynamic oscillatory shear, and transient shear. The study derived significant conclusions by comparing and summarizing the applicability and limitations of each testing method: Dynamic oscillatory shear methods, including G'-σ curve method, γ-σ curve method, and G**γc method can measure sludge yield stress ranging from 4% to 40% TS, while other methods are restricted to low or limited solid concentrations; The G' = G″ method, utilizing the intersection of G' and G″ curves, consistently yields the highest value for yield stress when 4%≤ TS ≤ 12%; The rotational rheometer cannot measure sludge yield stress when the solid concentration exceeds 40% TS; The relationship between sludge yield stress and solid concentration is stronger as a power-law for TS ≤ 25%, transitioning to linear for higher concentrations (28%≤ TS <40%). This study systematically explores the applicability and limitations of various measurement methods for characterizing sludge yield stress across a wide range of solid concentrations, providing valuable guidance for scientific measurement and highlighting challenging research issues.

Microrheology reveals microscale viscosity gradients in planktonic systems.

Microbial activity in planktonic systems creates a dynamic and heterogeneous microscale seascape that harbors a diverse community of microorganisms and ecological interactions of global significance. In recent decades great effort has been put into understanding this complex system, particularly focusing on the role of chemical patchiness, while overlooking a physical parameter that governs microbial life and is affected by biological activity: viscosity. Here we reveal spatial heterogeneity of viscosity in planktonic systems by using microrheological techniques that allow measurement of viscosity at length scales relevant to microorganisms. We show the viscous nature and the spatial extent of the phycosphere, the region surrounding phytoplankton. In ∼45% of the phytoplankton cells analyzed we detected increases in viscosity that extended up to 30 µm away from the cell with up to 40 times the viscosity of seawater. We also show how these gradients of viscosity can be amplified around a lysing phytoplankton cell as its viscous contents leak away. Finally, we report conservative estimates of viscosity inside marine aggregates, hotspots of microbial activity, more than an order of magnitude higher than in seawater. Since the diffusivities of dissolved molecules, particles, and microorganisms are inversely related to viscosity, microheterogeneity in viscosity alters the microscale distribution of microorganisms and their resources, with pervasive implications for the functioning of the planktonic ecosystem. Increasing viscosities impacts ecological interactions and processes, such as nutrient uptake, chemotaxis, and particle encounter, that occur at the microscale but influence carbon and nutrient cycles at a global scale.

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease.

Understanding the mechanics of blood flow is necessary for developing insights into mechanisms of physiology and vascular diseases in microcirculation. Given the limitations of technologies available for assessing in vivo flow fields, in vitro methods based on traditional microfluidic platforms have been developed to mimic physiological conditions. However, existing methods lack the capability to provide accurate assessment of these flow fields, particularly in vessels with complex geometries. Conventional approaches to quantify flow fields rely either on analyzing only visual images or on enforcing underlying physics without considering visualization data, which could compromise accuracy of predictions. Here, we present artificial-intelligence velocimetry (AIV) to quantify velocity and stress fields of blood flow by integrating the imaging data with underlying physics using physics-informed neural networks. We demonstrate the capability of AIV by quantifying hemodynamics in microchannels designed to mimic saccular-shaped microaneurysms (microaneurysm-on-a-chip, or MAOAC), which signify common manifestations of diabetic retinopathy, a leading cause of vision loss from blood-vessel damage in the retina in diabetic patients. We show that AIV can, without any a priori knowledge of the inlet and outlet boundary conditions, infer the two-dimensional (2D) flow fields from a sequence of 2D images of blood flow in MAOAC, but also can infer three-dimensional (3D) flow fields using only 2D images, thanks to the encoded physics laws. AIV provides a unique paradigm that seamlessly integrates images, experimental data, and underlying physics using neural networks to automatically analyze experimental data and infer key hemodynamic indicators that assess vascular injury.

Adaptive river flow measurement method based on spatiotemporal image velocimetry and optical flow.

This paper proposes an adaptive river discharge measurement method based on spatiotemporal image velocimetry (STIV) and optical flow to solve the problem of blurred texture features and limited measurement accuracy under complex natural environmental conditions. Optical flow tracking generates spatiotemporal images by following the flow mainstream direction of rivers with both regular and irregular natural banks. A texture similarity function filtering method effectively enhances spatiotemporal texture features. The proposed method is applied to a natural river, with measurement results from a propeller-type current meter used as truth values. It is evaluated and compared with three other methods regarding measurement accuracy, error, and other evaluation indices. The results demonstrate that the method significantly improves spatiotemporal image quality. Its estimation outcomes perform better across all evaluation metrics, enhancing the adaptability and accuracy of the flow measurement method.

Potential of Powder Rheology for Detecting Unforeseen Cross-Contamination of Foreign Active Pharmaceutical Ingredients.

Unexpected cross-contamination by foreign components during the manufacturing and quality control of pharmaceutical products poses a serious threat to the stable supply of drugs and the safety of customers. In Japan, in 2020, a mix-up containing a sleeping drug went undetected by liquid chromatography during the final quality test because the test focused only on the main active pharmaceutical ingredient (API) and known impurities. In this study, we assessed the ability of a powder rheometer to analyze powder characteristics in detail to determine whether it can detect the influence of foreign APIs on powder flow. Aspirin, which was used as the host API, was combined with the guest APIs (acetaminophen from two manufacturers and albumin tannate) and subsequently subjected to shear and stability tests. The influence of known lubricants (magnesium stearate and leucine) on powder flow was also evaluated for standardized comparison. Using microscopic morphological analysis, the surface of the powder was observed to confirm physical interactions between the host and guest APIs. In most cases, the guest APIs were statistically detected due to characteristics such as their powder diameter, pre-milling, and cohesion properties. Furthermore, we evaluated the flowability of a formulation incorporating guest APIs for direct compression method along with additives such as microcrystalline cellulose, potato starch, and lactose. Even in the presence of several additives, the influence of the added guest APIs was successfully detected. In conclusion, powder rheometry is a promising method for ensuring stable product quality and reducing the risk of unforeseen cross-contamination by foreign APIs.

Mixed-Micelle in Situ Gel as a Candidate for Oral Inflammatory Ulcerative Diseases.

The current treatment for oral inflammatory ulcerative diseases has limitations. In situ forming hydrogels have shown great potential to deliver therapeutic substances for drug delivery to the buccal cavity. This study aimed to prepare and characterize lipid- and surfactant-based mixed micelle in situ gel (MIG) and evaluate whether it can offer more favorable properties than the in situ gel for effective treatment of the disease. Dexamethasone was incorporated into the MIGs particles, based on Poloxamer 407 and chitosan. The lower gelation time at 37 ℃ was considered a criterion to select superior formulations among the different lipid- and surfactant-based candidates. Further characterization was performed to evaluate the opted formulations regarding morphology, physical stability, rheology, texture, and release profile. All formulations were thermoresponsive and had a shorter gelation time as the temperature increased. Dexamethasone was released in a highly controlled manner, and morphological evaluation revealed that the mixed micelle in situ gels had spherical nanoparticles. Thixotropic behavior was observed in all MIGs, indicating a prolonged retention time of the formulation after oral administration. This study has shown that among different MIGs, the one with oleic acid is a more promising candidate than the in situ gel and other MIGs for drug delivery to the buccal cavity.

Aggregation controlled by condensate rheology.

Biomolecular condensates in living cells can exhibit a complex rheology, including viscoelastic and glassy behavior. This rheological behavior of condensates was suggested to regulate polymerization of cytoskeletal filaments and aggregation of amyloid fibrils. Here, we theoretically investigate how the rheological properties of condensates can control the formation of linear aggregates. To this end, we propose a kinetic theory for linear aggregation in coexisting phases, which accounts for the aggregate size distribution and the exchange of aggregates between inside and outside of condensates. The rheology of condensates is accounted in our model via aggregate mobilities that depend on aggregate size. We show that condensate rheology determines whether aggregates of all sizes or dominantly small aggregates are exchanged between condensate inside and outside on the timescale of aggregation. As a result, the ratio of aggregate numbers inside to outside of condensates differs significantly. Strikingly, we also find that weak variations in the rheological properties of condensates can lead to a switch-like change of the number of aggregates. These results suggest a possible physical mechanism for how living cells could control linear aggregation in a switch-like fashion through variations in condensate rheology.

Vortex-assisted electroosmotic mixing of Carreau fluid in a microchannel.

Pertaining to the mixing of the non-Newtonian Carreau fluid under electrokinetic actuation inside a plane microchannel, we propose a new design of micromixer that involves inserting a two-part cylinder bearing zeta potential of the same sign but different magnitude in the upstream and downstream directions. We numerically solve the transport equations to predict the underlying mixing characteristics. We demonstrate that a substantial momentum difference between the microchannel's plane wall and cylinder leads to the development of a vortex in the flow pathway, which in turn, enhances mixing substantially. As shown, for a fluid having a highly shear-thinning nature, the vortex-assisted convection mixing strength increases with diffusivity of the candidate fluids. Moreover, it is shown that for the higher shear-thinning nature of the candidate fluid, an increase in cylinder radius enhances mixing efficiency and flow rate simultaneously, resulting in a "quick and efficient" mixing condition. Additionally, the fluid rheology significantly alters the kinetics of shear-induced binary aggregation. Our findings show that the shear-induced aggregation characteristic time sharply increases with increasing shear-thinning behavior of the fluid.

Characterising the mechanical properties of soft solids through acoustics and rheology, exemplified by anhydrous milk fat.

Foods vary in their elastic properties over a wide range of behaviours. In the case of mastication, textures vary from hard solid through brittle (chocolate bar) and crispy/crunchy (biscuits) to viscous and extensional flow (syrup) and finally very low viscosity fluid (water). Here we deploy an elastic description of soft solids which embraces all these behaviours to quantify the elastic behaviour of food, in particular through the use of sound. We illustrate the use of this mathematical description in the quantitative characterisation of the elastic and flow properties of food through orthodox measurement techniques and novel ultrasound methods. Measurement is complicated by human sensory capabilities that span the entire range from solid to fluid to gas in an integrated manner, during the appreciation of food. We use acoustic and rheological measurement techniques for the determination of the mechanical properties of soft solids, comparing oscillatory rheometry with acoustic parameters as exemplified by acoustic and oscillatory rheometry measurements in crystallising anhydrous milk fat (AMF). We conclude that acoustic and rheological measurements complement each other with acoustic techniques offering the possibility of inline, in process determination of mechanical and flow properties such as viscosity, rigidity, compressibility and bulk modulus.

Energy spectrum analysis on a red blood cell model.

It is important to understand the dynamics of red blood cells (RBCs) in blood flow. This requires the formulation of coarse-grained RBC models that reproduce the hydrodynamic properties of blood accurately. One of the models that successfully reproduces the rheology and morphology of blood has been proposed by Fedosov et al. [Comput. Methods Appl. Mech. Eng. 199, 1937-1948 (2010)]. The proposed RBC model contains several parameters whose values are determined by either various experiments or physical requirements. In this study, we developed a new method of determining parameter values precisely from the fluctuations of the RBC membrane. Specifically, we studied the relationship between the spectra of the fluctuations and model parameters. Characteristic peaks were observed in the spectra, whose peak frequencies were dependent on the parameter values. In addition, we investigated the spectra of the radius of gyration. We identified the peaks originating from the spring potential and the volume-conserving potential appearing in the spectra. These results lead to the precise experimental determination of the parameters used in the RBC model.

Probabilistic reanalysis of storm surge extremes in Europe.

Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all of the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960-2013.

Rheological Issues on Oropharyngeal Dysphagia.

There is an increasing proof of the relevance of rheology on the design of fluids for the diagnosis and management of dysphagia. In this sense, different authors have reported clinical evidence that support the conclusion that an increase in bolus viscosity reduces the risks of airway penetration during swallowing. However, this clinical evidence has not been associated yet to the definition of objective viscosity levels that may help to predict a safe swallowing process. In addition, more recent reports highlight the potential contribution of bolus extensional viscosity, as elongational flows also develops during the swallowing process. Based on this background, the aim of this review paper is to introduce the lecturer (experts in Dysphagia) into the relevance of Rheology for the diagnosis and management of oropharyngeal dysphagia (OD). In this sense, this paper starts with the definition of some basic concepts on Rheology, complemented by a more extended vision on the concepts of shear viscosity and elongational viscosity. This is followed by a short overview of shear and elongational rheometrical techniques relevant for the characterization of dysphagia-oriented fluids, and, finally, an in-depth analysis of the current knowledge concerning the role of shear and elongational viscosities in the diagnosis and management of OD (shear and elongational behaviors of different categories of dysphagia-oriented products and contrast fluids for dysphagia assessment, as well as the relevance of saliva influence on bolus rheological behavior during the swallowing process).

Effect of konjac oligo-glucomannan on emulsifying properties of myofibrillar protein.

BACKGROUND: The high viscosity of konjac glumannan (KGM) limits its application in meat processing. In this work, the effects of konjac oligo-glucomannan (KOG), as a derivative of KGM, on the emulsifying properties of myofibrillar protein (MP) and the related mechanism were investigated. RESULTS: It was found that the addition of KOG had no significant effect on the secondary structure of MP, but altered the tertiary conformation of MP, resulting in exposure of tyrosine residues to polar microenvironments and decreased intrinsic fluorescence intensity. In addition, the addition of KOG increased the emulsifying activity of MP, resulting in decreased particle size and improved physical stability of the emulsion. The emulsifying activity of MP reached the maximum value when 1.0 wt% KOG was added. Moreover, the interfacial tension and interfacially adsorbed protein content of MP/KOG emulsions decreased with the increase in KOG concentration. CONCLUSION: These findings demonstrated that KOG mainly interacted with MP and changed the amphipathy of the KOG-MP at the oil-water interface, forming a stable interface film to improve the emulsifying properties of MP. © 2023 Society of Chemical Industry.

Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer.

Biofluids such as synovial fluid, blood plasma, and saliva contain several proteins which impart non-Newtonian properties to the biofluids. The concentration of such protein macromolecules in biofluids is regarded as an important biomarker for the diagnosis of several health conditions, including cardiovascular disorders, joint quality, and Alzheimer's. Existing technologies for the measurements of macromolecules in biofluids are limited; they require a long turnaround time, or require complex protocols, thus calling for alternative, more suitable, methodologies aimed at such measurements. According to the well-established relations for polymer solutions, the concentration of macromolecules in solutions can also be derived via measurement of rheological properties such as shear-viscosity and the longest relaxation time. We here introduce a microfluidic rheometer for rapid simultaneous measurement of shear viscosity and longest relaxation time of non-Newtonian solutions at different temperatures. At variance with previous technologies, our microfluidic rheometer provides a very short turnaround time of around 2 min or less thanks to the implementation of a machine-learning algorithm. We validated our platform on several aqueous solutions of poly(ethylene oxide). We also performed measurements on hyaluronic acid solutions in the clinical range for joint grade assessment. We observed monotonic behavior with the concentration for both rheological properties, thus speculating on their use as potential rheo-markers, i.e., rheological biomarkers, across several disease states.