A machine learning approach to predict in vivo skin growth.

Since their invention, tissue expanders, which are designed to trigger additional skin growth, have revolutionised many reconstructive surgeries. Currently, however, the sole quantitative method to assess skin growth requires skin excision. Thus, in the context of patient outcomes, a machine learning method which uses non-invasive measurements to predict in vivo skin growth and other skin properties, holds significant value. In this study, the finite element method was used to simulate a typical skin expansion protocol and to perform various simulated wave propagation experiments during the first few days of expansion on 1,000 individual virtual subjects. An artificial neural network trained on this dataset was shown to be capable of predicting the future skin growth at 7 days (avg. R2 = 0.9353) as well as the subject-specific shear modulus (R2 = 0.9801), growth rate (R2 = 0.8649), and natural pre-stretch (R2 = 0.9783) with a very high degree of accuracy. The method presented here has implications for the real-time prediction of patient-specific skin expansion outcomes and could facilitate the development of patient-specific protocols.

Insights into the mechanics of solid conical microneedle array insertion into skin using the finite element method.

In order to develop optimum microneedle designs, researchers must first develop robust, repeatable and adaptable test methods which are representative of in vivo conditions. However, there is a lack of experimental tools which can accurately comparatively interrogate functional microneedle penetration of tissue. In this study, we seek to develop a state of the art finite element model of microneedle insertion into and penetration of human skin. The developed model employs a 3D hyperelastic, anisotropic pre-stressed multi-layered material which more accurately reflects in vivo skin conditions, while the microneedle is modeled as an array, which can capture the influence of adjacent microneedles on the overall response. Using the developed finite element model, we highlight the importance of accurate computational modeling which can decipher the mechanics of microneedle insertion, including the influence of its position within an array and how it correlates well with experimental observations. In particular, we have concluded that, for our model microneedle array, increasing skin pretension from 0 to 10% strain reduces the penetration force by 13%, ultimate local deformation about the microneedle by 22% and the ultimate penetration efficiency by 15%. We have also concluded that the presence of a base plate limits the penetration efficiency by up to 24%, while the penetration efficiency across a 5 × 1 microneedle array may vary by 27%. This model elucidates, for the first time, the combined effects of skin tension and needle geometry on accurately predicting microneedle penetration efficiency. STATEMENT OF SIGNIFICANCE: Microneedles arrays (MNAs) are medical devices with microscale protrusions, typically designed to penetrate the outermost layer of the skin, that upon optimisation, could lead to disruptive minimally-invasive disease management. However, the mechanics of MNA insertion are complex, due in part to a 'bed of nails' effect, and difficult to elucidate experimentally. Therefore, comparisons between designs, functional assessment of production batches and ultimately the likelihood of clinical translation are challenging to predict. Here, we have develop the most sophisticated in silico model of MNA insertion into pre-tensioned human skin to predict the extent of MNA penetration and therefore the likelihood of successful therapeutic delivery. Researchers can customise this model to predict the penetration efficiency of any MNA design.

Ranking and Rating Bicycle Helmet Safety Performance in Oblique Impacts Using Eight Different Brain Injury Models.

Bicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall's tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.

Equestrian Helmet Standards: Do They Represent Real-World Accident Conditions?

The use of helmets in equestrian sports has reduced the occurrence of traumatic brain injuries although, despite improvements to helmets, concussion remains a common injury. Currently, equestrian helmets are designed to pass certification standards involving a linear drop test to a rigid surface, while most concussions in equestrian sports result from oblique impacts to a compliant surface. The purpose of this study was to: (1) Compare the head kinematics and brain tissue response of the current equestrian helmet standard (EN1) and proposed standard EN13087-11 (EN2) to those associated with reconstructions of real-world equestrian concussion accidents. (2) Design a test protocol that would reflect the real-world conditions associated with concussion in equestrian sports. (3) To assess the protective capacity of an equestrian helmet using the flat turf and 45° turf proposed test protocols. Results for reconstructions of real-world concussions were obtained from a previous study (Clark et al. in J. Sci. Med. Sport 23:222-236, 2020). Using one jockey helmet model, impact tests were conducted according to the EN1 and EN2 protocols. Additionally, helmeted and unhelmeted tests were conducted at 5.9 and 6.0 m/s on to flat turf and 45° turf anvils for front, front-boss and rear-boss impact locations. The results demonstrated EN1 and EN2 both had higher magnitude accelerations and shorter duration impacts than reconstructed real-world concussive impacts. Impacts to turf anvils, on the other hand, produced similar head kinematics compared to the reconstructed real-world concussive impacts. Additionally, this study demonstrated that helmeted impacts significantly decreased rotational kinematics and brain tissue response below what is associated with unhelmeted impacts for oblique falls. However, the head kinematics and brain tissue response associated with these helmeted falls were consistent with concussion, suggesting that scope exists to improve the capacity of equestrian helmets to protect against concussion.

Proposed injury thresholds for concussion in equestrian sports.

OBJECTIVES: Equestrian helmets are designed to pass certification standards based on linear drop tests onto rigid steel surfaces. However, concussions in equestrian sports occur most commonly when a rider is thrown off a horse and obliquely impacts a compliant surface such as turf or sand. This paper seeks to elucidate the mechanics of such impacts and thereby propose corresponding thresholds for the occurrence of concussion that can improve equestrian helmet standards and designs. DESIGN: The present study examined the biomechanics of real-world equestrian accidents and developed thresholds for the occurrence of concussive injury. METHODS: Twenty-five concussive and 25 non-concussive falls in equestrian sports were reconstructed using a combination of video analysis, computational and physical reconstruction methods. These represented male and female accidents from horse racing and the cross-country phase of eventing. RESULTS: The resulting thresholds for concussion [59g, 2700rad/s2, 28rad/s, 0.24 (MPS), 6.6kPa and 0.27 (CSMD10) for 50% risk] were consistent with those reported in the literature and represent a unique combination of head kinematic thresholds compared to other sports. Current equestrian helmet standards commonly use a threshold of 250g and a linear drop to a steel anvil resulting in less than 15ms impacts. This investigation found that concussive equestrian accidents occurred from oblique impacts to turf or sand with lower magnitude and longer duration impacts (<130g and >20ms). This suggests that current equestrian helmet standards may not adequately represent real-world concussive impact conditions and, consequently, there is an urgent need to assess the protective capacity of equestrian helmets under real-world conditions.

Hydrolytically degradable hyperbranched PEG-polyester adhesive with low swelling and robust mechanical properties.

Photocrosslinkable and water soluble hyperbranched PEG-polyester polymers (HPEGDA) have been developed as robust degradable adhesives. The HPEGDA polymers have been synthesized from controlled homopolymerization of poly(ethylene glycol) diacrylate (PEGDA700 ) via in situ deactivation enhanced atom transfer radical polymerization (DE-ATRP). By introducing a high initiator-to-monomer ratio, the obtained HPEGDA polymer is composed of extremely short carbon-carbon backbones interconnected together by the long PEG chains as well as pendent photocrosslinkable acrylate moieties. Due to the extremely short C-C backbone, the long PEG chains can therefore be seen as the main chain, thus, HPEGDA polymers behave more like polyester which is a category of polymers that contain the ester functional group in their main chain. Photo-cured HPEGDA can be readily adhered to tissue forming a patch with robust mechanical and adhesive strengths. The degradation profile by hydrolysis of polyester blocks as well as a significantly low swelling ratio of HPEGDA gels in an aqueous environment allow them to have great potential for sealing and repair of internal tissue. Furthermore, HPEGDA gels appear to have minor significant cytotoxicity in vitro. These unique properties indicate that the reported HPEGDA polymers are well poised for the development of adhesive tissue engineering matrixes, wound dressings, and sealants.

On-demand and negative-thermo-swelling tissue adhesive based on highly branched ambivalent PEG-catechol copolymers.

A series of well-designed highly branched PEG-catechol based thermo-responsive copolymers were synthesized via a one-pot RAFT polymerization. A varying degree of photocrosslinkable (meth)acrylate moieties were incorporated within the 3D structure to allow on-demand photocuring (strong cohesion, unlike conventional PEG adhesives). At the same time, multitudes of free catechol groups inspired from adhesive proteins of marine mussels were also introduced in the hyperbranched structure, giving rise to adherence to skin and cardiac tissue. The resulting ambivalent PEG-catechol based copolymers were systematically studied to investigate the effects of polymer composition on tissue bioadhesive and swelling properties, comparing acrylates to methacrylates and PEG to 2-hydroxyethyl acrylamide (HEAA). It was proved that DOPA played a major role in the adhesion performance as it significantly enhanced the adhesion performances on varied substrates. The highly branched PEG-catechol copolymers demonstrate the great potential in the design of novel surgical glues, sealants or drug delivery vectors.

A combined experimental and numerical study of stab-penetration forces.

The magnitude of force used in a stabbing incident can be difficult to quantify, although the estimate given by forensic pathologists is often seen as 'critical' evidence in medico-legal situations. The main objective of this study is to develop a quantitative measure of the force associated with a knife stabbing biological tissue, using a combined experimental and numerical technique. A series of stab-penetration tests were performed to quantify the force required for a blade to penetrate skin at various speeds and using different 'sharp' instruments. A computational model of blade penetration was developed using ABAQUS/EXPLICIT, a non-linear finite element analysis (FEA) commercial package. This model, which incorporated element deletion along with a suitable failure criterion, is capable of systematically quantifying the effect of the many variables affecting a stab event. This quantitative data could, in time, lead to the development of a predictive model that could help indicate the level of force used in a particular stabbing incident.