Lie-Group Theoretic Approach to Shape-Sensing Using FBG-Sensorized Needles Including Double-Layer Tissue and S-Shape Insertions.

Flexible bevel-tipped needles are often used for needle insertion in minimally-invasive surgical techniques due to their ability to be steered in cluttered environments. Shapesensing enables physicians to determine the location of needles intra-operatively without requiring radiation of the patient, enabling accurate needle placement. In this paper, we validate a theoretical method for flexible needle shape-sensing that allows for complex curvatures, extending upon a previous sensor-based model. This model combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod to determine and predict the 3D needle shape during insertion. We evaluate the model's shape sensing capabilities in C- and S-shape insertions in single-layer isotropic tissue, and C-shape insertions in two-layer isotropic tissue. Experiments on a four-active area, FBG-sensorized needle were performed in varying tissue stiffnesses and insertion scenarios under stereo vision to provide the 3D ground truth needle shape. The results validate a viable 3D needle shape-sensing model accounting for complex curvatures in flexible needles with mean needle shape sensing root-mean-square errors of 0.160 ± 0.055 mm over 650 needle insertions.

Continuous body 3-D reconstruction of limbless animals.

Limbless animals such as snakes, limbless lizards, worms, eels and lampreys move their slender, long bodies in three dimensions to traverse diverse environments. Accurately quantifying their continuous body's 3-D shape and motion is important for understanding body-environment interactions in complex terrain, but this is difficult to achieve (especially for local orientation and rotation). Here, we describe an interpolation method to quantify continuous body 3-D position and orientation. We simplify the body as an elastic rod and apply a backbone optimization method to interpolate continuous body shape between end constraints imposed by tracked markers. Despite over-simplifying the biomechanics, our method achieves a higher interpolation accuracy (∼50% error) in both 3-D position and orientation compared with the widely used cubic B-spline interpolation method. Beyond snakes traversing large obstacles as demonstrated, our method applies to other long, slender, limbless animals and continuum robots. We provide codes and demo files for easy application of our method.

Spectrum of susceptibility to air quality and weather in individual children with atopic dermatitis.

BACKGROUND: Exposure to air pollution aggravates symptoms of atopic dermatitis (AD) in children in the population studies. Variability in individual patient's response from individual susceptibility is needed to be explored. OBJECTIVE: This study aimed to investigate spectrum of individual variability in the associations between AD symptoms and air quality. METHODS: We enrolled 89 children aged 0-6 years with AD (22 890 person-days). Daily manifestation of symptoms was recorded for an average of 257 days (range 100-499). Both an individual analysis using logistic regression models and an overall analysis using a generalized estimating equation were performed. RESULTS: The odds ratios of an individual ranged 0.24-8.11 for particulate matter <10 µm in diameter (PM10 ), 0.09-101.92 for nitrogen oxide (NO2 ), 0.03-44.00 for ozone (O3 ), 0.11-58.30 for sulfur dioxide (SO2 ), 0.00-15.83 for carbon monoxide (CO), 0.00-39 446.94 for temperature, and 0.03-5.18 for relative humidity, demonstrating a wide individual variability. In the overall analysis, PM10 , NO2 , SO2 , and CO had a significantly positive association, whereas temperature and relative humidity were negatively associated with AD symptoms. Air pollution was responsible for aggravation of symptoms from 24.7% (O3 ) to 39.3% (SO2 ) of AD children. Overall, 71.9% of the AD children responded to at least one or more air pollution and weather variable. CONCLUSION: Responses of AD children to air pollution and weather variable were considerably variable among individuals. An individualized model would be useful to forecast and manage AD symptoms in patients.

A simple insertion technique to reduce the bending of thinbevel-point needles.

Objective: Needle insertion is a common component of most diagnostic and therapeutic interventions. Needles with asymmetrically sharpened points such as the bevel point are ubiquitous. Their insertion path is typically curved due to the rudder effect at the point. However, the common planned path is straight, leading to targeting errors. We present a simple technique that may substantially reduce these errors. The method was inspired by practical experience, conceived mathematically, and refined experimentally. Methods: Targeting errors are reduced by flipping the bevel on the opposite side (rotating the needle 180° about its axis), at a certain depth during insertion. The ratio of the flip depth to the full depth of insertion is defined as the flip depth ratio (FDR). Based on a model, FDR is constant 0.3. Results: Experimentally, the ratio depends on the needle diameter, 0.35 for 20Ga and 0.45 for 18Ga needles. Thinner needles should be flipped a little shallower, but never less than 0.3. Conclusion: Practically, a physician may expect to reduce ∼80% of needle deflection errors by simply flipping the needle. The technique may be used by hand or with guidance devices.

Wearable Potentiometric Chloride Sweat Sensor: The Critical Role of the Salt Bridge.

The components of sweat provide an array of potential biomarkers for health and disease. Sweat chloride is of interest as a biomarker for cystic fibrosis, electrolyte metabolism disorders, electrolyte balance, and electrolyte loss during exercise. Developing wearable sensors for biomarkers in sweat is a major technological challenge. Potentiometric sensors provide a relatively simple technology for on-body sweat chloride measurement, however, equilibration between reference and test solutions has limited the time over which accurate measurements can be made. Here, we report on a wearable potentiometric chloride sweat sensor. We performed parametric studies to show how the salt bridge geometry determines equilibration between the reference and test solutions. From these results, we show a sweat chloride sensor can be designed to provide accurate measurements over extended times. We then performed on-body tests on healthy subjects while exercising to establish the feasibility of using this technology as a wearable device.

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Flexible needle insertion procedures are common in minimally-invasive surgeries for diagnosing and treating prostate cancer. Bevel-tip needles provide physicians the capability to steer the needle during long insertions to avoid vital anatomical structures in the patient and reduce post-operative patient discomfort. To provide needle placement feedback to the physician, sensors are embedded into needles for determining the real-time 3D shape of the needle during operation without needing to visualize the needle intra-operatively. Through expansive research in fiber optics, a plethora of bio-compatible, MRI-compatible, optical shape-sensors have been developed to provide real-time shape feedback, such as single-core and multicore fiber Bragg gratings. In this paper, we directly compare single-core fiber-based and multicore fiber-based needle shape-sensing through similarly constructed, four-active area sensorized bevel-tip needles inserted into phantom and ex-vivo tissue on the same experimental platform. In this work, we found that for shape-sensing in phantom tissue, the two needles performed identically with a p-value of 0.164 > 0.05, but in ex-vivo real tissue, the single-core fiber sensorized needle significantly outperformed the multicore fiber configuration with a p-value of 0.0005 < 0.05. This paper also presents the experimental platform and method for directly comparing these optical shape sensors for the needle shape-sensing task, as well as provides direction, insight and required considerations for future work in constructively optimizing sensorized needles.

Optical Fiber -Based Needle Shape Sensing: Three-channel Single Core vs. Multicore Approaches.

Bevel-tip needles are commonly utilized in percutaneous medical interventions where a curved insertion trajectory is required. To avoid deviation from the intended trajectory, needle shape sensing and tip localization is crucial in providing the operator with feedback. There is an abundance of previous work that investigate the medical application of fiber Bragg grating (FBG) sensors, but most works select only one specific type of fiber among the many available sensor options to integrate into their hardware designs. In this work, we compare two different types of FBG sensors under identical conditions and application, namely, acting as the sensor for needle insertion shape reconstruction. We built a three-channel single core needle and a seven-channel multicore fiber (MCF) needle and discuss the pros and cons of both constructions for shape sensing experiments into constant curvature jigs. The overall needle tip error is 1.23 mm for the single core needle and 2.08 mm for the multicore needle.

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Flexible needle insertion procedures are common for minimally-invasive surgeries for diagnosing and treating prostate cancer. Bevel-tip needles provide physicians the capability to steer the needle during long insertions to avoid vital anatomical structures in the patient and reduce post-operative patient discomfort. To provide needle placement feedback to the physician, sensors are embedded into needles for determining the real-time 3D shape of the needle during operation without needing to visualize the needle intra-operatively. Through expansive research in fiber optics, a plethora of bio-compatible, MRI-compatible, optical shape-sensors have been developed to provide real-time shape feedback, such as single-core and multicore fiber Bragg gratings. In this paper, we directly compare single-core fiber-based and multicore fiber-based needle shape-sensing through identically constructed, four-active area sensorized bevel-tip needles inserted into phantom and ex-vivo tissue on the same experimental platform. In this work, we found that for shape-sensing in phantom tissue, the two needles performed identically with a p-value of 0.164 > 0.05, but in ex-vivo real tissue, the single-core fiber sensorized needle significantly outperformed the multicore fiber configuration with a p-value of 0.0005 < 0.05. This paper also presents the experimental platform and method for directly comparing these optical shape sensors for the needle shape-sensing task, as well as provides direction, insight and required considerations for future work in constructively optimizing sensorized needles.

Risk of myocardial infarction, heart failure, and cerebrovascular disease with the use of valsartan, losartan, irbesartan, and telmisartan in patients.

There is a lack of studies comparing the risk of cardio-cerebrovascular disease between angiotensin receptor blockers (ARBs) of different half-lives. We aimed to compare the risks of myocardial infarction (MI), heart failure (HF), and cerebrovascular disease with the use of valsartan, losartan, irbesartan, and telmisartan with different half-lives in a national claim-based retrospective cohort of patients aged ≥ 40 years with hypertension. To establish a cohort exposed to valsartan, losartan, irbesartan, or telmisartan, we performed propensity score (PS) matching and used an as-treated approach to evaluate exposure. The Cox regression model was employed to calculate hazard ratios, which were based on the incidence rate for each newly occurring event of MI, heart failure, or cerebrovascular disease. These hazard ratios were calculated to compare the risk of MI, heart failure, and cerebrovascular disease associated with valsartan, losartan, and irbesartan in comparison to telmisartan. A PS-matched cohort of 148,229 patients was established for each of valsartan, losartan, irbesartan, or telmisartan. The matched cohort analysis showed that the adjusted hazard ratio (aHRs, 95% confidence interval) for MI was higher for valsartan use (1.39, 1.33-1.45) and losartan use (1.10, 1.05-1.15) but lower for irbesartan use (0.90, 0.86-0.94) compared with the reference (telmisartan). The aHRs for HF were not different among these ARBs (angiotensin receptor blockers). The aHR for cerebrovascular disease was lower for valsartan use (0.85, 0.83-0.87) and losartan use (0.80, 0.78-0.82) but higher for irbesartan use (1.11, 1.09-1.13) compared with the reference. We found differences in the risk of MI and cerebrovascular disease with the use of different ARBs compared to telmisartan use. Valsartan, and losartan with a short half-life, which showed a higher risk of MI, had a lower risk of cerebrovascular disease. Conversely, irbesartan with a long half-life, which showed a lower risk of MI, had a higher risk of cerebrovascular disease.

A mechanochemical model of actin filaments.

In eukaryotic cells, actin filaments are involved in important processes such as motility, division, cell shape regulation, contractility, and mechanosensation. Actin filaments are polymerized chains of monomers, which themselves undergo a range of chemical events such as ATP hydrolysis, polymerization, and depolymerization. When forces are applied to F-actin, in addition to filament mechanical deformations, the applied force must also influence chemical events in the filament. We develop an intermediate-scale model of actin filaments that combines actin chemistry with filament-level deformations. The model is able to compute mechanical responses of F-actin during bending and stretching. The model also describes the interplay between ATP hydrolysis and filament deformations, including possible force-induced chemical state changes of actin monomers in the filament. The model can also be used to model the action of several actin-associated proteins, and for large-scale simulation of F-actin networks. All together, our model shows that mechanics and chemistry must be considered together to understand cytoskeletal dynamics in living cells.

Mathematical modeling of the impact of actin and keratin filaments on keratinocyte cell spreading.

Keratin intermediate filaments (IFs) form cross-linked arrays to fulfill their structural support function in epithelial cells and tissues subjected to external stress. How the cross-linking of keratin IFs impacts the morphology and differentiation of keratinocytes in the epidermis and related surface epithelia remains an open question. Experimental measurements have established that keratinocyte spreading area is inversely correlated to the extent of keratin IF bundling in two-dimensional culture. In an effort to quantitatively explain this relationship, we developed a mathematical model in which isotropic cell spreading is considered as a first approximation. Relevant physical properties such as actin protrusion, adhesion events, and the corresponding response of lamellum formation at the cell periphery are included in this model. Through optimization with experimental data that relate time-dependent changes in keratinocyte surface area during spreading, our simulation results confirm the notion that the organization and mechanical properties of cross-linked keratin filaments affect cell spreading; in addition, our results provide details of the kinetics of this effect. These in silico findings provide further support for the notion that differentiation-related changes in the density and intracellular organization of keratin IFs affect tissue architecture in epidermis and related stratified epithelia.

Toward FBG-Sensorized Needle Shape Prediction in Tissue Insertions.

Complex needle shape prediction remains an issue for planning of surgical interventions of flexible needles. In this paper, we validate a theoretical method for flexible needle shape prediction allowing for non-uniform curvatures, extending upon a previous sensor-based model which combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod to determine and predict the 3D needle shape during insertion. We evaluate the model's effectiveness in single-layer isotropic tissue for shape sensing and shape prediction capabilities. Experiments on a four-active area, FBG-sensorized needle were performed in varying single-layer isotropic tissues under stereo vision to provide 3D ground truth of the needle shape. The results validate a viable 3D needle shape prediction model accounting for non-uniform curvatures in flexible needles with mean needle shape sensing and prediction root-mean-square errors of 0.479 mm and 0.892 mm, respectively.

Toward FBG-Sensorized Needle Shape Detection in Real Tissue Insertions.

The determination of flexible needle shape during insertion is critical for planning and validation in minimally invasive surgical percutaneous procedures. In this paper, we validate a needle shape-sensing method using fiber Bragg grating (FBG) sensors over sequential needle insertion lengths in gel phantom and real tissue. Experiments on a four-active area, FBG-sensorized needle were performed in both isotropic simulated tissue and inhomogeneous animal tissue with computed tomography (CT) as the ground truth of the needle shape. The results show that the needle shape obtained from the FBG sensors has an overall consistent accuracy in real tissue in comparison to the phantom gel. The results validate a viable 3D needle shape-sensing model and reconstruction method over various insertion depths in comparison to the needle shapes determined from CT in both gel phantom and real tissue.

Towards Automatic Robotic Calibration System for Flexible Needles with FBG Sensors.

There has been much research exploring the use of fiber Bragg grating (FBG)-sensorized needles in the prostate biopsy procedure, but all FBG needles used in the research need to be calibrated, which is time consuming and prone to human errors. In this work, a semi-automatic robotic system was developed to perform FBG needle calibration. Compared to manual calibration results, the robotic system is able to calibrate FBG needles with the similar level of accuracy as achieved by an experienced manual operator, thus reducing the time cost during the needle calibration process.

Modeling the self-organization property of keratin intermediate filaments.

Keratin intermediate filaments (IFs) fulfill an important function of structural support in epithelial cells. The necessary mechanical attributes require that IFs be organized into a crosslinked network and accordingly, keratin IFs are typically organized into large bundles in surface epithelia. For IFs comprised of keratins 5 and 14 (K5, K14), found in basal keratinocytes of epidermis, bundling can be self-driven through interactions between K14's carboxy-terminal tail domain and two regions in the central α-helical rod domain of K5. Here, we exploit theoretical principles and computational modeling to investigate how such cis-acting determinants best promote IF crosslinking. We develop a simple model where keratin IFs are treated as rigid rods to apply Brownian dynamics simulation. Our findings suggest that long-range interactions between IFs are required to initiate the formation of bundlelike configurations, while tail domain-mediated binding events act to stabilize them. Our model explains the differences observed in the mechanical properties of wild-type versus disease-causing, defective IF networks. This effort extends the notion that the structural support function of keratin IFs necessitates a combination of intrinsic and extrinsic determinants, and makes specific predictions about the mechanisms involved in the formation of crosslinked keratin networks in vivo.

Trajectory Generation of FBG-Sensorized Needles for Insertions into Multi-Layer Tissue.

Several models incorporate needle shape prediction, however prediction in multi-layer tissue for complex needle shape remains an issue. In this work, we present a method for trajectory generation of flexible needles that allows for complex curvatures, extending upon a previous sensor-based model. This model combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod for shape-sensing. We evaluate the method's effectiveness in single- and double-layer isotropic tissue prediction. The results illustrate a valid trajectory generation method accounting for complex curvatures in flexible needles.

Lateral Oscillation and Body Compliance Help Snakes and Snake Robots Stably Traverse Large, Smooth Obstacles.

Snakes can move through almost any terrain. Similarly, snake robots hold the promise as a versatile platform to traverse complex environments such as earthquake rubble. Unlike snake locomotion on flat surfaces which is inherently stable, when snakes traverse complex terrain by deforming their body out of plane, it becomes challenging to maintain stability. Here, we review our recent progress in understanding how snakes and snake robots traverse large, smooth obstacles such as boulders and felled trees that lack "anchor points" for gripping or bracing. First, we discovered that the generalist variable kingsnake combines lateral oscillation and cantilevering. Regardless of step height and surface friction, the overall gait is preserved. Next, to quantify static stability of the snake, we developed a method to interpolate continuous body in three dimensions (3D) (both position and orientation) between discrete tracked markers. By analyzing the base of support using the interpolated continuous body 3-D kinematics, we discovered that the snake maintained perfect stability during traversal, even on the most challenging low friction, high step. Finally, we applied this gait to a snake robot and systematically tested its performance traversing large steps with variable heights to further understand stability principles. The robot rapidly and stably traversed steps nearly as high as a third of its body length. As step height increased, the robot rolled more frequently to the extent of flipping over, reducing traversal probability. The absence of such failure in the snake with a compliant body inspired us to add body compliance to the robot. With better surface contact, the compliant body robot suffered less roll instability and traversed high steps at higher probability, without sacrificing traversal speed. Our robot traversed large step-like obstacles more rapidly than most previous snake robots, approaching that of the animal. The combination of lateral oscillation and body compliance to form a large, reliable base of support may be useful for snakes and snake robots to traverse diverse 3-D environments with large, smooth obstacles.

Morphology of Caulobacter crescentus and the Mechanical Role of Crescentin.

Bacterial cells exist in a wide variety of shapes. To understand the mechanism of bacterial shape maintenance, we investigate the morphology of Caulobacter crescentus, which is a Gram-negative bacterium that adopts a helical crescent shape. It is known that crescentin, an intermediate filament homolog of C. crescentus, is required for maintaining this asymmetrical cell shape. We employ a continuum model to understand the interaction between the bacterial cell wall and the crescentin bundle. The model allows us to examine different scenarios of attaching crescentin to the cell wall and compute the shape of the bacterium. Results show that if the sole influence of crescentin is mechanical, then the crescentin bundle is unrealistically rigid and must be attached to the cell wall directly. The model suggests that alternative roles for crescentin such as how it influences cell wall growth must be considered.

Continuum modeling of forces in growing viscoelastic cytoskeletal networks.

Mechanical properties of the living cell are important in cell movement, cell division, cancer development and cell signaling. There is considerable interest in measuring local mechanical properties of living materials and the living cytoskeleton using micromechanical techniques. However, living materials are constantly undergoing internal dynamics such as growth and remodeling. A modeling framework that combines mechanical deformations with cytoskeletal growth dynamics is necessary to describe cellular shape changes. The present paper develops a general finite deformation modeling approach that can treat the viscoelastic cytoskeleton. Given the growth dynamics in the cytoskeletal network and the relationship between deformation and stress, the shape of the network is computed in an incremental fashion. The growth dynamics of the cytoskeleton can be modeled as stress dependent. The result is a consistent treatment of overall cell deformation. The framework is applied to a growing 1-d bundle of actin filaments against an elastic cantilever, and a 2-d cell undergoing wave-like protrusion dynamics. In the latter example, mechanical forces on the cell adhesion are examined as a function of the protrusion dynamics.

Symmetrical Parameterization of Rigid Body Transformations for Biomolecular Structures.

Assessing preferred relative rigid body position and orientation is important in the description of biomolecular structures (such as proteins) and their interactions. In this article, we extend and apply the "symmetrical parameterization," which we recently introduced in the kinematics community, to address problems in structural biology. We also review parameterization methods that are widely used in structural biology to describe relative rigid body motions (in particular, orientations) as a basis for comparison. The new symmetrical parameterization is useful in describing the relative biomolecular rigid body motions, where the parameters are symmetrical in the sense that the subunits of a complex biomolecular structure are described in the same way for the corresponding motion and its inverse. The properties of this new parameterization, singularity analysis, and inverse kinematics are also investigated in more detail. Finally, parameterization is applied to real biomolecular structures and a potential application to structure modeling of symmetric macromolecules to show the efficacy of the symmetrical parameterization in the field of computational structural biology.