Annals of Biomedical Engineering最新文献

Reduced-size CRISPR systems have become a possible remedy to the delivery and size constraints of the traditional SpCas9 (~ 1368 Å). Recently described small nucleases, including Cas12f (400-700 Å) or CasX (~ 980 Å), along with designed mini-Cas9 versions, can efficiently be used in vivo to edit cells as well as to perform point-of-care diagnostics because of their lower molecular weight and less complex structures. This review will sum up progress in compact Cas protein engineering, guide RNA optimization, and delivery vector miniaturization, and point to their influence in therapeutic gene editing and portable diagnostic platforms. We additionally cover the contemporary issues of interest, such as off-target activity, delivery barriers and regulatory requirements, and future opportunities provided through AI-assisted protein design and synthetic biology. The miniaturized CRISPR technology is bound to substantially transform the translational arena of gene editing and world diagnostics.

Self-powered intracardiac implant devices show great promise for future clinical applications due to their extended operational lifespan and the potential to reduce the need for high-risk repeat surgeries. This study investigates the feasibility of harvesting energy from cardiac motion through in vivo testing of intracardiac devices. Comprehensive three-dimensional translational and rotational cardiac motions are captured in a porcine model using a miniaturized 9-degree-of-freedom motion sensor implanted at six strategic epicardial sites. Kinematic criteria are developed to evaluate the energy harvesting potential of each implant site based on the available kinetic energy, acceleration, and jerk factors. The recorded heart motion signals are analyzed and applied to a conceptual energy harvester proposed to identify the optimal implant site. The results reveal that the left ventricular apex emerges as a preferable site for energy harvesting, particularly at moderate heart rates. These findings offer valuable insights into optimizing self-powered intracardiac implants, reducing dependency on battery replacements, and enhancing long-term patient safety.

In the rapidly evolving landscape of medicine, hyperbaric oxygen therapy (HBOT) has emerged as a clinically recognized treatment involving the inhalation of pure oxygen in a pressurized chamber. Despite its proven applications, further research is needed to understand and simulate the physical processes governing HBOT. This paper presents a novel modeling technique and an automated pressurized chamber specifically designed for laboratory studies to better analyze oxygenated air circulation in hyperbaric environments. The proposed model integrates hydraulic principles and geometric constraints to replicate real-world HBOT dynamics. It incorporates dimensionless equations, including Reynolds, Froude, and Archimedes principles, to account for fluid motion, energy dissipation, and pressure field behavior. Geometric conditions involve initial and boundary parameters such as velocity, temperature, pressure, concentration, and mass density. For realistic simulation, both physical and geometric similarity conditions must be satisfied. To enhance the generalizability of results, the Ruark transformation is employed to introduce dimensionless coordinates, allowing findings to extend to related scenarios.The proposed laboratory model demonstrates the ability to accurately simulate complex oxygenation and flow dynamics in pressurized environments. The automated chamber ensures precise control and experimental reproducibility. The model effectively reproduces velocity fields and pressure distributions across varied geometric and dynamic configurations.By combining hydraulic theory with geometric modeling, this study provides a robust framework for exploring HBOT mechanisms in a controlled setting. The approach not only advances theoretical understanding but also lays the groundwork for future experimental and clinical investigations in hyperbaric therapy and similar therapeutic environments.

Purpose: Fenestrated EndoVascular Aneurysm Repair (fEVAR) has been demonstrated to be an excellent treatment for complex abdominal aortic aneurysms. In addition to the aortic endograft, bridging stent-grafts (SG) are deployed within the renal arteries, resulting in rare but serious renal complications. This study aims to assess renal artery hemodynamic changes post-fEVAR, including the effect of respiration-induced renal deformation.

Methods: Pre-fEVAR models were segmented from CT scans (patients involved in clinical trial NCT04724863), while post-fEVAR models were created from structural simulations that included respiratory-induced deformation. Computational Fluid Dynamics (CFD) simulations applied inflow velocity waveforms at the supraceliac aorta and Windkessel boundary conditions at the outlets. A dynamic mesh was implemented to reproduce renal deformation during breathing, and inspiration and expiration static configurations were analyzed.

Results: Post-fEVAR reduction in renal artery flow was detected, together with recirculation regions near the SG protrusions into the aorta. Higher time-averaged wall shear stress was observed in the unstented section of the renal arteries. The comparison between static and dynamic mesh simulations reveals that renal artery motion has negligible effect on the flow. Finally, velocity fields were compared to metrics used clinically to assess renal stenosis, to build a model for the prediction of renal complications in silico.

Conclusion: This study evaluates the impact of renal stenting on flow, accounting for respiratory-induced deformation. It shows a minimal influence on overall hemodynamics, but significant reduction of renal flow post-fEVAR. Future studies should evaluate a patient cohort who experienced renal complications to correlate CFD metrics with post-operative clinical outcomes.

AI is widely recognized as a tool that biomedical scientists, engineers and clinicians can, and should, use. However, what do we mean by a tool? I take the example of convolutional neural networks that learn latent statistical associations from images, but those associations can be used to different ends. I focus on two different uses in the field of medical diagnostics, what I call human-AI "outskilling" and human-AI "newskilling". Outskilling is a prosthetic human-AI activity to outperform human capacities (in Greek: prosthesis, adding) in tasks that experts can nevertheless perform well. I study computer-aided diagnostics (CADx) to detect polyps as an example of AI outskilling, which carries the risk of deskilling without a proven gain in meaningful outcomes. I term the second use "newskilling," a human-AI activity that brings forth something new (in Greek: poiesis) by using latent statistical associations to discover variables that human inference cannot detect. I study the example of AI deriving clinically relevant variables from retinal fundus images to derive "retinal age gaps" as an example of human-AI newskilling. There are two major conclusions based on this distinction: the design of AI uses, and the discernment of how and when to use them.

Purpose: Growth and remodeling of the cardiac outflow tract (OFT) are poorly understood but associated with serious congenital heart defects (CHD). While only a minority of CHDs have identifiable genetic causes, the functional roles of mechanical forces in OFT remodeling are far less characterized. A key barrier has been the lack of longitudinal investigations examining the interplay between dynamic blood flow and wall motion across clinically relevant stages.

Methods: Here, we developed a live high-frequency ultrasound-derived four-dimensional (4D) moving-domain computational fluid dynamics (CFD) simulation approach, enabling longitudinal quantification of OFT hemodynamics and tissue mechanics in the same ex ovo chicken embryos across Hamburger-Hamilton (HH) stage 21 to HH27.

Results: We found that wall shear stress (WSS) increases more than fourfold from HH21 to HH27, which strongly correlates with tissue extension in the distal OFT (R = 0.79, p < 0.05), whereas the proximal OFT experiences 20% larger expansive strains over development and higher hydrostatic stress than the distal OFT (dO) with heartbeats. Additionally, we identified a double-helical flow pattern with a ~ 3 degree flow direction shift in the OFT lumen, possibly contributing to the OFT septation and reflecting a streaming pattern associated with oxygenated and deoxygenated blood paths originated from extra-embryonic venous return and embryonic tissue return, respectively, before physical aorticopulmonary septation forms.

Conclusion: We identified hemodynamic force and tissue mechanics as drivers of local tissue development and important stimuli for OFT remodeling and septation, advancing insights in how mechanical forces contribute to OFT development.

Purpose: Deep vein thrombosis (DVT) poses significant health risks, including potentially fatal pulmonary embolism. Current clinical practice relies heavily on ultrasonography, requiring a skilled specialist. Alternative methods, such as light reflection rheography (LRR) and venous occlusion plethysmography (VOP), are non-invasive and simple; however, studies report limited consistency and standardization. The development of biosignal-based diagnostic tools is constrained by the inherent risks of DVT, including embolization, and challenges in patient recruitment. The ability to simulate DVT-like conditions would aid in developing and testing alternative screening methods. This study aims to present a simulation method of venous hemodynamic alterations resembling deep vein thrombosis using controlled external thigh compression with ultrasonic visualization.

Methods: Data collection with thirty healthy volunteers was conducted in a laboratory using a commercially available system VasoScreen 5000-4000 to record LRR and VOP signals. Vein stenosis at varying levels was induced through controlled external thigh compression under ultrasonic guidance.

Results: The experimental simulation showed statistically significant but small changes in LRR parameters across different stenosis levels. In comparison, VOP results showed greater differences across stenosis levels, with 70% and 100% performing the best. In these cases, 47% and 70% of the measurements, respectively, were below the normal reference limit, with a notably increased outflow time constant, compared to the baseline measurements, where it remained low despite varying venous capacity.

Conclusion: Presented hemodynamic alterations demonstrated to be a feasible option for simulating DVT-like conditions via controlled external pressure on the thigh.

Purpose: There is a lack of predictive biomechanical models and publicly accessible empirical data that quantitatively explore the effect of damping magnitude on the peak knee flexion angle during the swing phase.

Methods: A three-step framework estimates a recommended damping coefficient range required to achieve able-bodied peak knee flexion during swing. A recommended damping range (0.29- $0.56\times {10}^{-2}[-]$ ) was estimated using experimental able-bodied gait data and adjusted based on expected walking speed and shorter duration of swing flexion common in transfemoral prosthetic gait. The resulting damping range was experimentally investigated with five transfemoral amputees. Knee kinematic data were collected from each person for five different damping coefficients that spanned a broad range of values, including the recommended range predicted by the framework.

Results: The experimental study showed that the framework calculates an efficient starting damping value that promotes target able-bodied peak knee flexion. The damping coefficient values within the predicted recommended range resulted in able-bodied peak knee flexion (56 ± 3°) in the prosthetic leg for three out of the five participants. Increasing damping decreased the peak knee flexion, with the no-damping condition resulting in hyperflexion.

Conclusion: This framework could allow prosthetic knee designers to develop devices with near-optimal damping, which may increase efficiency for clinical tuning, especially in low- and middle-income countries, where controlled knee flexion is the desired outcome.

Purpose: Snare-type tools are widely used for polyp tissue resection in cold snare polypectomy. Due to the characteristics of snare-type tools, which fracture the inner tissue first and the surface later, high friction in the contact area may hinder the extension of cracks to the surface, resulting in a lower-quality cut and an increased risk of bleeding. This study is to investigate the mechanism of tissue surface fracture and give guidance on the optimization of tools and techniques.

Methods: This paper proposes a three-phase energy model to explain the mechanism of soft tissue surface fracture. The energy changes in these three phases are characterized by experiments and finite element simulations. The factors affecting the cutting ability of the tool and the surface fracture state are further explored through single-factor experiments.

Results: The results show the effectiveness and consistency of cutting fracture toughness and section root-mean-square (RMS) height as indexes for evaluating the cutting ability and surface fracture state of snare-type tools. High cutting speeds can increase cutting fracture toughness and reduce the RMS height, and surface lubrication reduces the RMS height, but wire diameter has no significant influence on them.

Conclusion: This study introduces a novel energy-based model for clearing the understanding of surface fracture mechanisms for the field of soft tissue cutting and provides guides for the optimization of snare-type tools and surgery technologies.

Purpose: The ocular lens capsule is a biomechanically specialized basement membrane essential for lens function, yet its regional micromechanical properties remain incompletely characterized.

Methods: We employed atomic force microscopy (AFM)-based force spectroscopy to map the stiffness of young porcine anterior and posterior lens capsule samples under physiologically hydrated conditions. A refined dissection protocol was used to preserve native curvature and hydration, with the anterior and posterior regions isolated via selective capsular puncture. Force-indentation measurements were performed using calibrated silicon cantilevers and analyzed with the Johnson-Kendall-Roberts (JKR) model to extract local Young's modulus.

Results: Results from over 12,000 force curves revealed that the anterior capsule exhibited significantly higher stiffness (mean 67.9 kPa, standard deviation 40.1 kPa) than the posterior (mean 54.1 kPa, standard deviation 25.2 kPa; p < 0.0001), with a wider range of stiffness values. AFM topography confirmed comparable surface morphology, ruling out roughness as a confounding factor.

Conclusion: These findings highlight the functional specialization of the lens capsule and the utility of AFM for high-resolution biomechanical characterization. These measurement techniques will be applied to human lens capsules to elucidate age-related changes in capsule properties pertaining to presbyopia, inform surgical strategies, lens capsule modeling, and the design of accommodative intraocular lenses.