Neelesh A. Patankar

BACKGROUND: Intrabolus pressure (IBP) reflects the pressure within the esophageal lumen during bolus transit and serves as a physiologic marker of outflow resistance at the esophagogastric junction (EGJ). The lack of a standardized or validated method to measure IBP is a critical limitation for interpreting high resolution manometry (HRM) and identification of clinically relevant EGJ outflow obstruction (EGJOO). METHODS: Three distinct cohorts, "Controls", Normal motility", and "conclusive EGJOO" were selected from a prospectively enrolled cohort of adult patients. All patients had at least undergone HRM with impedance (HRIM), and functional lumen impedance probe (FLIP) testing. 4D HRM analysis was performed blinded to clinical characteristics. 4D HRM IBP results were assessed on a per-swallow and also on a per-patient level. Receiver operating curve (ROCs) to assess each metrics prediction of conclusive EGJOO vs. not EGJOO (normal motility and controls) were utilized for the per-swallow analysis. KEY RESULTS: 33 controls, 35 normal motility, and 15 conclusive EGJOO patients were included. Swallow level analysis was conducted on 156 swallows, 165 swallows, and 61 swallows from each group, respectively. Per-swallow analysis demonstrated differences between conclusive EGJOO, normal motility, and controls for all ten IBP measures (P-values < 0.001), with greater IBP measures in conclusive EGJOO than in normal motility and controls. The 1 s max IBP had the greatest AUROC. CONCLUSIONS & INFERENCES: Standardized measurement of IBP using an optimized method (1-s max IBP) within the 4D-HRM framework with impedance-confirmed bolus tracking and phase-specific measures represents a physiologically grounded and clinically meaningful advance in HRIM interpretation.

Large animal models, while valuable, are expensive, time-consuming, and limited to discrete interventional or terminal timepoints, while existing benchtop models do not offer an accurate representation of the esophageal environment. Moreover, current pre-clinical models cannot effectively simulate swallowing dysfunction (dysphagia), restricting progress in understanding motility disorders like achalasia and hindering evidence-based dietary recommendations. In response, we present RoboGullet, a biomimetic soft-robotic model with independent localized longitudinal and circumferential muscle actuation, enabling, for the first time, simulation of both normal and diseased esophageal motility. We further enhance realism with a biohybrid variant, RoboGullet + , incorporating porcine esophageal mucosa/submucosa. We demonstrate this platform's versatility through three key applications: assessing stent migration, simulating achalasia I-III within clinical diagnostic criteria, and analyzing bolus swallowing. Our findings reveal that: (1) stent migration increases over fivefold when incorporating longitudinal muscle movement versus isolated circumferential; (2) using a viscous non-Newtonian bolus improves high-resolution manometry diagnostic sensitivity of Achalasia III through increasing the Distal Latency diagnostic metric by 20.83%; and (3) stirring Greek-style yoghurt (common non-Newtonian dietary recommendation) significantly improves bolus transit versus unstirred for Achalasia Types I-II patients. This establishes RoboGullet+ as a powerful translational tool, advancing our understanding of esophageal motility and its therapeutic interventions.

Background: Retrograde urethrogram (RUG) remains the gold standard for diagnosing urethral stricture disease, however no widely available diagnostic modality currently quantifies stricture characteristics using cross-sectional area or tissue compliance. We hypothesized that pressure-derived metrics could improve diagnostic accuracy and guide treatment. We aimed to develop an in vitro latex urethra model to simulate “healthy” and “strictured” states and directly measure luminal pressure as an initial step toward compliance assessment. Methods: Ten 20-cm latex tubes were studied; five contained 1.5-cm simulated strictures. All tubes were clamped at both ends to prevent leakage. Strictures were created by clamping across an 8Fr bougie at the midpoint, while healthy models were left unclamped at the 8Fr bougie location. Tubes were pressurized for 10 s to simulate RUG conditions. Pressure was measured using a 7Fr air-charged dual-sensor urodynamic catheter positioned such that the midpoint stricture was located 2 cm distal to the first pressure sensor. Saline was infused at 20 mL/min through the catheter port positioned proximal to the stricture, and maximum pressure (Pmax, cmH2O) was selectively recorded only from the first proximal sensor to reflect upstream resistance generated by the narrowing. Time to maximum pressure (Tmax, seconds) was also measured. Compliance was calculated (ΔV/ΔP). Comparisons were performed using an unpaired Student’s t-test. Results: Ten pressure–time curves were generated. Mean (Standard Deviation) Pmax was significantly higher in strictured models compared to healthy controls (160.8 [9.4] vs. 29.8 [16.4] cmH2O, p < 0.001). Tmax was similar between groups (9.2 [1.1] vs. 9.8 [0.4] s, p = 0.289). Compliance was lower in strictured (0.019 [0.003] cm³/cmH2O) vs. healthy tubes (0.150 [0.107] cm³/cmH2O, p = 0.025). Conclusions: This proof-of-concept model demonstrates that pressure profiling can distinguish healthy from strictured urethras and supports compliance as a novel diagnostic metric.

Esophageal motility arises from the continuous coupling between enteric neural activity and the organ's mechanical response, yet the structure of this coupling remains poorly understood. Esophageal motility disorders represent mechanical dysfunctions that originate from abnormalities in neural control, underscoring the need to understand how neural and mechanical processes interact to produce coordinated motion. We present an empirically guided neuromechanical model of the esophagus, comprising unidirectionally coupled relaxation oscillators activated by intrinsic enteric nervous system mechanoreceptors sensitive to wall distension. The model reveals complex behaviors emerging from interactions among its components, predicting various clinically observed normal and abnormal esophageal responses to distension. Specifically, repetitive antegrade contractions (RACs) are shown to arise from the coupled neuromechanical dynamics in response to sustained volumetric distension. Normal RACs are shown to have a robust balance between excitatory and inhibitory neural activities and mechanical input through these intrinsic distension-sensitive mechanoreceptors. When this balance is affected, contraction patterns resembling motility disorders emerge. For example, clinically observed repetitive retrograde contractions emerge due to hypersensitive mechanoreceptors in the esophageal wall. Such neuromechanical insights may ultimately guide the development of targeted pharmacological interventions.

Treatment strategies for COPD and asthmatic patients is a critical issue faced by pulmonologists across the world. The article by Li et al. sheds light on how deeper insights into pathogenesis and phenotyping of COPD may be obtained using a combination of single-photon emission computed tomography (SPECT) and quantitative computed tomography (qCT)-derived biomarkers. These insights can be utilised to develop new avenues for evaluating COPD progression and devising appropriate therapeutic responses. A different interventional approach was adopted by Abu Shaphe et al. They investigated how treadmill exercise responses, guided by the 6-minute walk test, vary among individuals with differing COPD severity. Their findings suggest that personalising treadmill exercise protocols according to COPD severity levels and walk test results can reveal important functional limitations and help tailor rehabilitation strategies for improved outcomes in COPD management. The study by Zhong et al. show that Fe2O3 nanoparticles -when used in optimal concentration -can potentially disrupt the microstructure of airway mucosal fluid significantly lowering the viscoelastic nature of the mucosal fluid and facilitating easier mucus clearance from airways. Tests using mucus from asthmatic patients confirm these findings suggesting that Fe2O3 nanoparticles could act as expectorants, potentially outperforming conventional mucolytics by virtue of their biocompatibility and availability.Pulmonary drug delivery presents a plausible route for achieving efficient systemic drug delivery [West, 2012]. However, despite the clinical relevance, its efficiency remains suboptimal owing to significant deposition of inhaled aerosolised drug dose in the upper respiratory tract (Bessler et al., 2024). Compensation through larger doses is often prescribed although undesirable side effects or even systemic exposure is possible [De Boer et al., 2017]. Various novel strategies are, thus, being investigated for overcoming this drawback [Dua et al., 2020;Chakravarty et al., 2022;Kole et al., 2023]. Bessler et al. reports on a relatively less investigated strategy -leveraging the inherent electrostatic charge present on inhaled aerosols. Their study -using an in vitro airway-on-chip platform mimicking small bronchial geometries -reveal that electrostatic forces substantially alter deposition patterns in constricted airways: for submicron particles, there is enhanced proximal airway deposition due to electrostatic-diffusive effects, while larger particles show extended deposition footprints beyond what gravity alone would allow. These results suggest electrostatic attraction could be strategically used to improve the targeting of inhaled therapeutics in obstructive lung diseases like asthma and COPD.The pulmonary drug delivery systems also warrant personalisation for achieving desired therapeutic efficacy due to inter-patient variability in lung morphology. Direct quantification of such variability is, however, not possible beyond the 7 th lung generation owing to technological limitations, despite recent advances in imaging and diagnostic techniques. The article by Karthiga Devi et al. discusses a novel non-invasive method to estimate morphology of the distal lung by measuring radio-aerosol deposition patterns in healthy individuals utilizing gamma scintigraphy. The results demonstrate that aerosol deposition, particularly in the distal airways, serves as a sensitive marker of morphological variability, suggesting this approach could be developed into a walk-in lab test to personalize diagnosis and optimize pulmonary drug delivery.A different aspect of personalised respiratory care is highlighted in Vijay Anand et al. They presented a mechanistic compartmental model designed to investigate how airway secretion accumulation and its removal affect respiratory dynamics in ICU patients on mechanical ventilation. The study identifies characteristic changes in ventilator waveforms due to secretion buildup-such as reduced inspiratory flow and longer exhalation-and introduces a model-informed secretion index for continuous bedside monitoring. These findings can be utilised to improve personalized respiratory care and secretion management for mechanically ventilated patients.Another key contribution to this research topic (Chakravarty et al.) discusses the development of a versatile physics-based, 1D reduced-order computational model encompassing varied and complex bio-physical phenomena involving airflow, gas exchange, particle/aerosol transport and deposition, mucus transport and pathogen infection progression within the human airways. The model has been utilised for identifying routes of improving drug delivery to the acinar region of the lung (Chakravarty et al., 2022). A different application of this model (Chakravarty et al., 2023) led to the hypothesis of re-aerosolisation of nasopharyngeal mucosa (RNM) as a plausible route of COVID-19 infection spread to the acinar region of the lung (Morawska et al., 2022), while reinforcing the utility of vaccination in preventing fatal infections.The hypothesis of RNM is being investigated through computations and experiments by various groups [Pairetti et al., 2021;Anzai et al., 2022;Kant et al. 2023;Saha et al., 2024;Li et al., 2025]. One such group (Ilegbusi et al.) studied the formation and transport of mucus droplets during cough across CTderived upper airway geometries. Increases in mucus thickness and viscosity-characteristic of respiratory diseases-is observed to substantially affect the number and size of exhaled droplets, with thicker mucus yielding more and larger droplets, while more viscous mucus results in fewer but larger droplets. Similar findings were reported by Saha et al. (2024). A more generic case of the same mechanism involving inhaled lower airway transmission of pathogen-laden microdroplets fragmented from the upper airway mucosa has been recently explored in a different study (Basu, 2025), through full-scale computational simulation of the intra-airway inhalation physics within CT-based anatomical domains. The simulated patterns of advective transport were validated against reduced-order analytical estimates (tracking the impact of dominant vortex cores in the laryngotracheal space on downwind bronchial transport) and published experimental results (Miguel, 2017). The mechanism has been hypothesized (Basu, 2025;Chakravarty et al., 2023) as a key factor for brisk onset of secondary deep lung infections, following the emergence of symptoms in the upper respiratory tract. These findings show that the distribution of exhaled cough droplets can act as a sensitive, non-invasive biomarker for classifying pulmonary diseases, underlining the diagnostic potential of droplet dynamics and mucosal properties in respiratory health assessment.To summarise, the article collection on the research topic highlights the potential of airway biomechanics to be used for defining clinically-relevant metrics called physiomarkers and develop diagnostic tools. For example, the reduced-order model (Chakravarty et al.) introduces several dimensionless parameters for defining lung physiology which can be used to construct a virtual disease landscape (VDL) --essentially a mapping of different disease groups and normal function in a hyperspace of dimensionless parameters controlling lung function. These parameters defining the VDL can help obtain mechanistic insights into pathologies and hence used as physiomarkers for disease classification and diagnosis. The VDL -coupled machine learning techniques -could be developed into a powerful diagnostic tool for disease trajectory prediction, optimize therapeutic interventions, and ultimately improve patient outcomes.

The need to understand how infection spreads to the deep lung was acutely realized during the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. The challenge of modeling virus laden aerosol transport and deposition in the airways, coupled with mucus clearance, and infection kinetics, became evident. This perspective provides a consolidated view of coupled one-dimensional physics-based mathematical models to probe multifaceted aspects of lung physiology. Successes of 1D trumpet models in providing mechanistic insights into lung function and optimalities are reviewed while identifying limitations and future directions. Key non-dimensional numbers defining lung function are reported. The need to quantitatively map various pathologies on a physics-based parameter space of non-dimensional numbers (a virtual disease landscape) is noted with an eye on translating modeling to clinical practice. This could aid in disease diagnosis, get mechanistic insights into pathologies, and determine patient specific treatment plan. 1D modeling could, thus, be an important tool in developing novel measurement and analysis platforms that could be deployed at point-of-care.

The esophagus, the tube-like organ responsible for transporting food from the pharynx to the stomach, operates as a highly mechanical structure, exhibiting complex contraction and distension patterns triggered by neurological impulses. Despite the critical role of mechanics in its function and the need for high-fidelity models of esophageal transport, mechanical characterization studies of human esophagus remain relatively scarce. In addition to the paucity of studies in human specimens, the available results are often scattered in terms of methodology and scope, making it difficult to compare findings across studies and thereby limiting their use in computational models. In this work, we present a detailed passive-mechanical and structural characterization of the esophageal muscular layers, excised from short esophageal segments obtained from live patients with varied clinical presentations. Specifically, we conducted uniaxial and planar biaxial extension tests on the smooth muscle layers, complemented by pre- and post-testing structural characterization via histological imaging. Unlike existing studies, our experimental results on passive behavior are discussed in the context of physiological relevance (e.g., physiological stretches, and activity-inhibiting pathologies), providing valuable insights that guide the subsequent modeling of the esophagus' mechanical response. As such, this work provides new insights into the passive properties of the fresh human esophagus, expands the existing database of mechanical parameters for computational modeling, and lays the foundation for future studies on active mechanical properties. STATEMENT OF SIGNIFICANCE: Understanding the mechanical properties of the esophagus is crucial for developing accurate models of its function and suitable replacements. This study provides insights into the passive mechanical behavior of fresh human esophageal tissue, enhancing our understanding of how it responds to stretching under physiological conditions. By characterizing the properties of different esophageal layers, obtained from esophagectomy specimens with various presentations, and considering their relevance to both normal and abnormal functioning, this work addresses the gap in ex-vivo human esophagus studies. The findings emphasize the importance of contextually analyzing experimental results within physiological parameters and suggest avenues for future research to further refine our understanding of esophageal mechanics, paving the way for improved diagnostic and therapeutic approaches in managing esophageal disorders.

Some biological systems exhibit both direct and retrograde propagating signal waves despite unidirectional coupling. To explain this phenomenon, we study a chain of unidirectionally coupled Wilson-Cowan oscillators. Surprisingly, we find that changes in the homogeneous global input to the chain suffice to reverse the wave propagation direction. To obtain insights, we analyze the frequencies and bifurcations of the limit cycle solutions of the chain as a function of the global input. Specifically, we determine that the directionality of wave propagation is controlled by differences in the intrinsic frequencies of oscillators caused by the differential proximity of the oscillators to a homoclinic bifurcation.

BACKGROUND: The functional lumen imaging probe (FLIP) has proven to be a versatile device for diagnosing esophageal motility disorders and estimating esophageal wall compliance, but there is a lack of viable software for quantitative assessment of FLIP measurements. METHODS: A Python-based web framework was developed for a unified assessment of FLIP measurements including clinical metrics such as esophagogastric junction (EGJ) distensibility index (DI), maximum EGJ opening diameter, mechanics-based metrics for estimating strength, and effectiveness of contractions, such as contraction power and displaced volume, and machine learning-based clustering and predictive algorithms such as the virtual disease landscape (VDL) and EGJ obstruction probability. The clinical and VDL probability metrics were then validated using FLIP data from 121 subjects constituting different categories of EGJ opening which were diagnosed by expert clinicians. RESULTS: The clinical metrics estimated by the framework matched the manual diagnosis of the clinicians. Misclassifications were minimal and were mostly between neighboring groups, that is, normal and borderline normal or borderline normal and borderline reduced EGJ opening. Similar results were also obtained for the VDL probability metrics. The misclassifications were further analyzed by clinicians and approved. CONCLUSION: The FLIP web framework was developed and validated to reliably estimate various clinical, mechanical, and machine learning-based metrics for diagnosing esophageal motility disorders.

For decades, the computational multiphase flow community has grappled with mass loss in the level set method. Numerous solutions have been proposed, from fixing the reinitialization step to combining the level set method with other conservative schemes. However, our work reveals a more fundamental culprit: the smooth Heaviside and delta functions inherent to the standard formulation. Even if reinitialization is done exactly, i.e., the zero contour interface remains stationary, the use of smooth functions lead to violation of mass conservation. We propose a novel approach using variational analysis to incorporate a mass conservation constraint. This introduces a Lagrange multiplier that enforces overall mass balance. Notably, as the delta function sharpens, i.e., approaches the Dirac delta limit, the Lagrange multiplier approaches zero. However, the exact Lagrange multiplier method disrupts the signed distance property of the level set function. This motivates us to develop an approximate version of the Lagrange multiplier that preserves both overall mass and signed distance property of the level set function. Our framework even recovers existing mass-conserving level set methods, revealing some inconsistencies in prior analyses. We extend this approach to three-phase flows for fluid-structure interaction (FSI) simulations. We present variational equations in both immersed and non-immersed forms, demonstrating the convergence of the former formulation to the latter when the body delta function sharpens. Rigorous test problems confirm that the FSI dynamics produced by our simple, easy-to-implement immersed formulation with the approximate Lagrange multiplier method are accurate and match state-of-the-art solvers. • Precise reasons for mass loss in the standard level set method are investigated. • A variational analysis is performed to incorporate a mass conservation constraint through the use of Lagrange multipliers for the level set method. • The new framework recovers existing mass-conserving level set methods. • The two-phase variational approach is extended to three phase flows in both immersed and non-immersed forms, enabling multiphase fluid-structure interaction simulations. • Stringent test problems are devised to test the performance of the mass conserving level set method.

This study presents an unprecedented directional transport phenomenon during the coalescence of two droplets on a pre-wetted cylindrical fiber, where the larger droplet is pulled toward the smaller one. The magnitude of this effect often exceeds the gravitational pull, enabling coalescing droplets to climb up a vertical fiber. This occurs primarily because the viscous friction that the droplets experience is negatively correlated with the droplet size. We present a scaling relation and a mass-spring-damper model to explain the phenomenon, which shows good agreement with the experimental results. This research reveals an intriguing aspect of the coalescence dynamics of droplets on a pre-wetted fiber, offering a fresh perspective on the interfacial phenomena in droplet–fiber systems.

Fluid-structure interaction is ubiquitous in nature and occurs at all biological scales. Immersed methods provide mathematical and computational frameworks for modeling fluid-structure systems. These methods, which typically use an Eulerian description of the fluid and a Lagrangian description of the structure, can treat thin immersed boundaries and volumetric bodies, and they can model structures that are flexible or rigid or that move with prescribed deformational kinematics. Immersed formulations do not require body-fitted discretizations and thereby avoid the frequent grid regeneration that can otherwise be required for models involving large deformations and displacements. This article reviews immersed methods for both elastic structures and structures with prescribed kinematics. It considers formulations using integral operators to connect the Eulerian and Lagrangian frames and methods that directly apply jump conditions along fluid-structure interfaces. Benchmark problems demonstrate the effectiveness of these methods, and selected applications at Reynolds numbers up to approximately 20,000 highlight their impact in biological and biomedical modeling and simulation.

BACKGROUND: Esophageal motility disorders can be diagnosed by either high-resolution manometry (HRM) or the functional lumen imaging probe (FLIP) but there is no systematic approach to synergize the measurements of these modalities or to improve the diagnostic metrics that have been developed to analyze them. This work aimed to devise a formal approach to bridge the gap between diagnoses inferred from HRM and FLIP measurements using deep learning and mechanics. METHODS: The "mechanical health" of the esophagus was analyzed in 740 subjects including a spectrum of motility disorder patients and normal subjects. The mechanical health was quantified through a set of parameters including wall stiffness, active relaxation, and contraction pattern. These parameters were used by a variational autoencoder to generate a parameter space called virtual disease landscape (VDL). Finally, probabilities were assigned to each point (subject) on the VDL through linear discriminant analysis (LDA), which in turn was used to compare with FLIP and HRM diagnoses. RESULTS: Subjects clustered into different regions of the VDL with their location relative to each other (and normal) defined by the type and severity of dysfunction. The two major categories that separated best on the VDL were subjects with normal esophagogastric junction (EGJ) opening and those with EGJ obstruction. Both HRM and FLIP diagnoses correlated well within these two groups. CONCLUSION: Mechanics-based parameters effectively estimated esophageal health using FLIP measurements to position subjects in a 3-D VDL that segregated subjects in good alignment with motility diagnoses gleaned from HRM and FLIP studies.

Abstract Endometriosis affects a significant portion of fertile-age women, often leading to infertility and a substantial decline in quality of life. Despite its prevalence, current diagnostic methods are limited, focusing on assessing the presence or absence of endometrial lesion, rather than the origin of the disorder. Thus, resulting in underdiagnosis. A potential mechanics-based metric for diagnosing endometriosis is proposed here by leveraging the retrograde menstruation hypothesis. By examining the interplay between uterine and fallopian tube peristalses, a non-dimensional physiomarker is introduced to signify the onset of retrograde flow. The analysis reveals that increased uterine contractile activity, coupled with decreased fallopian tube contractile activity, correlates with retrograde flow, suggesting a predisposition to endometriosis. This mechanophysiology-based approach offers a promising avenue for origin based diagnosis, with the proposed non-dimensional physiomarker – the endometriosis number – serving as a potential indicator of endometrial cell migration and the onset of endometriosis.

For decades, the computational multiphase flow community has grappled with mass loss in the level set method. Numerous solutions have been proposed, from fixing the reinitialization step to combining the level set method with other conservative schemes. However, our work reveals a more fundamental culprit: the smooth Heaviside and delta functions inherent to the standard formulation. Even if reinitialization is done exactly, i.e., the zero contour interface remains stationary, the use of smooth functions lead to violation of mass conservation. We propose a novel approach using variational analysis to incorporate a mass conservation constraint. This introduces a Lagrange multiplier that enforces overall mass balance. Notably, as the delta function sharpens, i.e., approaches the Dirac delta limit, the Lagrange multiplier approaches zero. However, the exact Lagrange multiplier method disrupts the signed distance property of the level set function. This motivates us to develop an approximate version of the Lagrange multiplier that preserves both overall mass and signed distance property of the level set function. Our framework even recovers existing mass-conserving level set methods, revealing some inconsistencies in prior analyses. We extend this approach to three-phase flows for fluid-structure interaction (FSI) simulations. We present variational equations in both immersed and non-immersed forms, demonstrating the convergence of the former formulation to the latter when the body delta function sharpens. Rigorous test problems confirm that the FSI dynamics produced by our simple, easy-to-implement immersed formulation with the approximate Lagrange multiplier method are accurate and match state-of-the-art solvers.

The need to understand how infection spreads to the deep lung was acutely realized during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic. The challenge of modeling virus laden aerosol transport and deposition in the airways, coupled with mucus clearance, and infection kinetics, became evident. This perspective provides a consolidated view of coupled one-dimensional physics-based mathematical models to probe multifaceted aspects of lung physiology. Successes of 1D trumpet models in providing mechanistic insights into lung function and optimalities are reviewed while identifying limitations and future directions. Key non-dimensional numbers defining lung function are reported. The need to quantitatively map various pathologies on a physics-based parameter space of non-dimensional numbers (a virtual disease landscape) is noted with an eye on translating modeling to clinical practice. This could aid in disease diagnosis, get mechanistic insights into pathologies, and determine patient specific treatment plan. 1D modeling could be an important tool in developing novel measurement and analysis platforms that could be deployed at point-of-care.

An understanding how neurological disorders lead to mechanical dysfunction of the esophagus requires knowledge of the neural circuit of the enteric nervous system. Historically, this has been elusive. Here, we present an empirically guided neural circuit for the esophagus. It has a chain of unidirectionally coupled relaxation oscillators, receiving excitatory signals from stretch receptors along the esophagus. The resulting neuromechanical model reveals complex patterns and behaviors that emerge from interacting components in the system. A wide variety of clinically observed normal and abnormal esophageal responses to distension are successfully predicted. Specifically, repetitive antegrade contractions (RACs) are conclusively shown to emerge from the coupled neuromechanical dynamics in response to sustained volumetric distension. Normal RACs are shown to have a robust balance between excitatory and inhibitory neuronal populations, and the mechanical input through stretch receptors. When this balance is affected, contraction patterns akin to motility disorders are observed. For example, clinically observed repetitive retrograde contractions emerge due to a hyper stretch sensitive wall. Such neuromechanical insights could be crucial to eventually develop targeted pharmacological interventions.

Certain biological systems exhibit both direct and retrograde propagating wave signals, despite unidirectional neural coupling. However, there is no model to explain this. Therefore, the underlying physics of reversing the signal's direction for one-way coupling remains unclear. Here, we resolve this issue using a Wilson-Cowan oscillators network. By analyzing the limit cycle period of various coupling configurations, we determine that intrinsic frequency differences among oscillators control wave directionality.

Numerical simulation of moving immersed solid bodies in fluids is now practiced routinely following pioneering work of Peskin and co-workers on immersed boundary method (IBM), Glowinski and co-workers on fictitious domain method (FDM), and others on related methods. A variety of variants of IBM and FDM approaches have been published, most of which rely on using a background mesh for the fluid equations and tracking the solid body using Lagrangian points. The key idea that is common to these methods is to assume that the entire fluid-solid domain is a fluid and then to constrain the fluid within the solid domain to move in accordance with the solid governing equations. The immersed solid body can be rigid or deforming. Thus, in all these methods the fluid domain is extended into the solid domain. In this review, we provide a mathemarical perspective of various immersed methods by recasting the governing equations in an extended domain form for the fluid. The solid equations are used to impose appropriate constraints on the fluid that is extended into the solid domain. This leads to extended domain constrained fluid-solid governing equations that provide a unified framework for various immersed body techniques. The unified constrained governing equations in the strong form are independent of the temporal or spatial discretization schemes. We show that particular choices of time stepping and spatial discretization lead to different techniques reported in literature ranging from freely moving rigid to elastic self-propelling bodies. These techniques have wide ranging applications including aquatic locomotion, underwater vehicles, car aerodynamics, and organ physiology (e.g. cardiac flow, esophageal transport, respiratory flows), wave energy convertors, among others. We conclude with comments on outstanding challenges and future directions.

Functional luminal imaging probe (FLIP) is used to measure cross-sectional area (CSA) and pressure at sphincters. It consists of a catheter surrounded by a fluid filled cylindrical bag, closed on both ends. Plotting the pressure-CSA hysteresis of a sphincter during a contraction cycle, which is available through FLIP testing, offers information on its functionality, and can provide diagnostic insights. However, limited work has been done to explain the mechanics of these pressure-CSA loops. This work presents a consolidated picture of pressure-CSA loops of different sphincters. Clinical data reveal that although sphincters have a similar purpose (controlling the flow of liquids and solids by opening and closing), two different pressure-CSA loop patterns emerge: negative slope loop (NSL) and positive slope loop (PSL). We show that the loop type is the result of an interplay between (or lack thereof) two mechanical modes: (i) neurogenic mediated relaxation of the sphincter muscle or pulling applied by external forces, and (ii) muscle contraction proximal to the sphincter which causes mechanical distention. We conclude that sphincters which only function through mechanism (i) exhibition NSL whereas sphincters which open as a result of both (i) and (ii) display a PSL. This work provides a fundamental mechanical understanding of human sphincters. This can be used to identify normal and abnormal phenotypes for the different sphincters and help in creating physiomarkers based on work calculation.

Rupture of aortic aneurysms is by far the most fatal heart disease, with a mortality rate exceeding 80%. There are no reliable clinical protocols to predict growth, dissection, and rupture because the fundamental physics driving aneurysm progression is unknown. Here, via in-vitro experiments, we show that a blood-wall, fluttering instability manifests in synthetic arteries under pulsatile forcing. We establish a phase space to prove that the transition from stable flow to unstable aortic flutter is accurately predicted by a flutter instability parameter derived from first principles. Time resolved strain maps of the evolving system reveal the dynamical characteristics of aortic flutter that drive aneurysm progression. We show that low level instability can trigger permanent aortic growth, even in the absence of material remodeling. Sufficiently large flutter beyond a secondary threshold localizes strain in the walls to the length scale clinically observed in aortic dissection. Lastly, significant physical flutter beyond a tertiary threshold can ultimately induce aneurysm rupture via failure modes reported from necropsy. Resolving the fundamental physics of aneurysm progression directly leads to clinical protocols that forecast growth as well as intercept dissection and rupture by pinpointing their physical origin.

Rupture of aortic aneurysms is by far the most fatal heart disease, with a mortality rate exceeding 80%. There are no reliable clinical protocols to predict growth, dissection, and rupture because the fundamental physics driving aneurysm progression is unknown. Here, via in-vitro experiments, we show that a blood-wall, fluttering instability manifests in synthetic arteries under pulsatile forcing. We establish a phase space to prove that the transition from stable flow to unstable aortic flutter is accurately predicted by a flutter instability parameter derived from first principles. Time resolved strain maps of the evolving system reveal the dynamical characteristics of aortic flutter that drive aneurysm progression. We show that low level instability can trigger permanent aortic growth, even in the absence of material remodeling. Sufficiently large flutter beyond a secondary threshold localizes strain in the walls to the length scale clinically observed in aortic dissection. Lastly, significant physical flutter beyond a tertiary threshold can ultimately induce aneurysm rupture via failure modes reported from necropsy. Resolving the fundamental physics of aneurysm progression directly leads to clinical protocols that forecast growth as well as intercept dissection and rupture by pinpointing their physical origin.

BACKGROUND AND AIMS: The distal contractile integral (DCI) quantifies the contractile vigor of primary peristalsis on high-resolution manometry (HRM), whereas no such metric exists for secondary peristalsis on functional lumen imaging probe (FLIP) panometry. This study aimed to evaluate novel FLIP metrics of contraction power and displaced volume in asymptomatic controls and a patient cohort. METHODS: Thirty-five asymptomatic controls and adult patients (with normal esophagogastric junction outflow/opening and without spasm) who completed HRM and FLIP panometry were included. The patient group also completed timed barium esophagram (TBE). Contraction power (estimate of esophageal work over time) and displaced volume (estimate of contraction-associated fluid flow) were computed from FLIP. HRM was analyzed per Chicago Classification v4.0. KEY RESULTS: In controls, median (5th-95th percentile) contraction power was 27 mW (10-44) and displaced volume was 43 mL (17-66). 95 patients were included: 72% with normal motility on HRM, 17% with ineffective esophageal motility (IEM), and 12% with absent contractility. Among patients, DCI was significantly correlated with both contraction power (rho = 0.499) and displaced volume (rho = 0.342); p values < 0.001. Both contraction power and displaced volume were greater in patients with normal motility versus IEM or absent contractility, complete versus incomplete bolus transit, and normal versus abnormal retention on TBE; p values < 0.02. CONCLUSIONS: FLIP panometry metrics of contraction power and displaced volume appeared to effectively quantify peristaltic vigor. These novel metrics may enhance evaluation of esophageal motility with FLIP panometry and provide a reliable surrogate to DCI on HRM.

We present a novel analysis of 4D flow MRI in the thoracic aorta that identifies fluid structure instabilities, which are elevated in a cohort of 117 suspected-aortopathy patients as compared to 100 healthy subjects, and which are predictive of later complications shown in a follow-up analysis for 72 patients in the cohort.

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique that generates image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the esophagus has only been demonstrated in few feasibility studies and is relatively unexplored. In this work, we present a computational framework called mechanics-informed MRI (MRI-MECH) that enhances that capability, thereby increasing the applicability of dynamic MRI for diagnosing esophageal disorders. Pineapple juice was used as the swallowed contrast material for the dynamic MRI, and the MRI image sequence was used as input to the MRI-MECH. The MRI-MECH modeled the esophagus as a flexible one-dimensional tube, and the elastic tube walls followed a linear tube law. Flow through the esophagus was governed by one-dimensional mass and momentum conservation equations. These equations were solved using a physics-informed neural network. The physics-informed neural network minimized the difference between the measurements from the MRI and model predictions and ensured that the physics of the fluid flow problem was always followed. MRI-MECH calculated the fluid velocity and pressure during esophageal transit and estimated the mechanical health of the esophagus by calculating wall stiffness and active relaxation. Additionally, MRI-MECH predicted missing information about the lower esophageal sphincter during the emptying process, demonstrating its applicability to scenarios with missing data or poor image resolution. In addition to potentially improving clinical decisions based on quantitative estimates of the mechanical health of the esophagus, MRI-MECH can also be adapted for application to other medical imaging modalities to enhance their functionality.

Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung-which may cause a severe infection-is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5-7 days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.

Introduction: Plotting the pressure-cross-sectional area (P-CSA) hysteresis loops within the esophagus during a contraction cycle can provide mechanistic insights into esophageal motor function. Pressure and cross-sectional area during secondary peristalsis can be obtained from the functional lumen imaging probe (FLIP). The pressure-cross-sectional area plots at a location within the esophageal body (but away from the sphincter) reveal a horizontal loop shape. The horizontal loop shape has phases that appear similar to those in cardiovascular analyses, whichinclude isometric and isotonic contractions followed by isometric and isotonic relaxations. The aim of this study is to explain the various phases of the pressurecross-sectional area hysteresis loops within the esophageal body. Materials and Methods: We simulate flow inside a FLIP device placed inside the esophagus lumen. We focus on three scenarios: long functional lumen imaging probe bag placed insidethe esophagus but not passing through the lower esophageal sphincter, long functional lumen imaging probe bag that crosses the lower esophageal sphincter, and a short functional lumen imaging probe bag placed in the esophagus body that does not pass through the lower esophageal sphincter. Results and Discussion: Horizontal P-CSA area loop pattern is robust and is reproduced in all three cases with only small differences. The results indicate that the horizontal loop pattern is primarily a product of mechanical conditions rather than any inherently different function of the muscle itself. Thus, the distinct phases of the loop can be explained solely based on mechanics.

Gas vesicles (GVs) are protein shells that perform superbly as ultrasound contrast agents due to their tunable collapse pressure. Here, the roles of condensation and shell buckling in triggering and controlling final GV collapse are examined.