Advancements in hydrogel design for articular cartilage regeneration: A comprehensive review.

This review paper explores the cutting-edge advancements in hydrogel design for articular cartilage regeneration (CR). Articular cartilage (AC) defects are a common occurrence worldwide that can lead to joint breakdown at a later stage of the disease, necessitating immediate intervention to prevent progressive degeneration of cartilage. Decades of research into the biomedical applications of hydrogels have revealed their tremendous potential, particularly in soft tissue engineering, including CR. Hydrogels are highly tunable and can be designed to meet the key criteria needed for a template in CR. This paper aims to identify those criteria, including the hydrogel components, mechanical properties, biodegradability, structural design, and integration capability with the adjacent native tissue and delves into the benefits that CR can obtain through appropriate design. Stratified-structural hydrogels that emulate the native cartilage structure, as well as the impact of environmental stimuli on the regeneration outcome, have also been discussed. By examining recent advances and emerging techniques, this paper offers valuable insights into developing effective hydrogel-based therapies for AC repair.

Molded Round Window Niche Implant as a Dexamethasone Delivery System in a Cochlear Implant-Trauma Animal Model.

BACKGROUND: Preserving residual hearing after cochlear implant (CI) surgery remains a crucial challenge. The application of dexamethasone (DEX) has been proven to positively affect residual hearing. To deliver DEX in a localized and controlled way, a round window niche implant (RNI), allowing drug diffusion via the round window membrane into the cochlea, may be used. To prove this concept, an RNI for guinea pigs as a CI-trauma model was manufactured by molding and tested for its drug release in vitro and biological effects in vivo. METHODS: The RNIs were molded using silicone containing 10% DEX. Release was analyzed over time using high-performance liquid chromatography (HPLC). Fourteen adult guinea pigs were randomly assigned to two groups (CI or CI + RNI group). All animals received a unilateral CI electrode insertion trauma followed by CI insertion. The CI + RNI group was additionally implanted with an RNI containing 10% DEX. Animals were followed up for 4 weeks. Acoustically evoked auditory brainstem response and impedance measurement, micro-computed tomography (µCT) imaging, and histology were performed for evaluation. RESULTS: DEX was released for more than 250 days in vitro, with an initial burst followed by a slower release over time. Comparing the hearing threshold shift (from day 0 to day 28) of the CI and CI + RNI groups, significant differences were observed at 32 and 40 kHz. The impedance shift at basal contacts was lower in the CI + RNI group than in the CI group. Moreover, the fibrosis in the lower basal turn was reduced in the CI + RNI group in contrast to the CI group. CONCLUSIONS: The RNI containing 10% DEX has anti-inflammatory potential concerning fibrosis inhibition and has beneficial effects on hearing preservation at high frequencies.

Machine Learning Classification of Self-Organized Surface Structures in Ultrashort-Pulse Laser Processing Based on Light Microscopic Images.

In ultrashort-pulsed laser processing, surface modification is subject to complex laser and scanning parameter studies. In addition, quality assurance systems for monitoring surface modification are still lacking. Automated laser processing routines featuring machine learning (ML) can help overcome these limitations, but they are largely absent in the literature and still lack practical applications. This paper presents a new methodology for machine learning classification of self-organized surface structures based on light microscopic images. For this purpose, three application-relevant types of self-organized surface structures are fabricated using a 300 fs laser system on hot working tool steel and stainless-steel substrates. Optical images of the hot working tool steel substrates were used to learn a classification algorithm based on the open-source tool Teachable Machine from Google. The trained classification algorithm achieved very high accuracy in distinguishing the surface types for the hot working steel substrate learned on, as well as for surface structures on the stainless-steel substrate. In addition, the algorithm also achieved very high accuracy in classifying the images of a specific structure class captured at different optical magnifications. Thus, the methodology proposed represents a simple and robust automated classification of surface structures that can be used as a basis for further development of quality assurance systems, automated process parameter recommendation, and inline laser parameter control.

Different Scenarios of Autonomous Operation of an Environmental Sensor Node Using a Piezoelectric-Vibration-Based Energy Harvester.

This paper delves into the application of vibration-based energy harvesting to power environmental sensor nodes, a critical component of modern data collection systems. These sensor nodes play a crucial role in structural health monitoring, providing essential data on external conditions that can affect the health and performance of structures. We investigate the feasibility and efficiency of utilizing piezoelectric vibration energy harvesters to sustainably power environmental wireless sensor nodes on the one hand. On the other hand, we exploit different approaches to minimize the sensor node's power consumption and maximize its efficiency. The investigations consider various sensor node platforms and assess their performance under different voltage levels and broadcast frequencies. The findings reveal that optimized harvester designs enable real-time data broadcasting with short intervals, ranging from 1 to 3 s, expanding the horizons of environmental monitoring, and show that in case the system includes a battery as a backup plan, the battery's lifetime can be extended up to 9 times. This work underscores the potential of vibration energy harvesting as a viable solution for powering sensor nodes, enhancing their autonomy, and reducing maintenance costs in remote and challenging environments. It opens doors to broader applications of sustainable energy sources in environmental monitoring and data collection systems.

Simulating the mechanical stimulation of cells on a porous hydrogel scaffold using an FSI model to predict cell differentiation.

3D-structured hydrogel scaffolds are frequently used in tissue engineering applications as they can provide a supportive and biocompatible environment for the growth and regeneration of new tissue. Hydrogel scaffolds seeded with human mesenchymal stem cells (MSCs) can be mechanically stimulated in bioreactors to promote the formation of cartilage or bone tissue. Although in vitro and in vivo experiments are necessary to understand the biological response of cells and tissues to mechanical stimulation, in silico methods are cost-effective and powerful approaches that can support these experimental investigations. In this study, we simulated the fluid-structure interaction (FSI) to predict cell differentiation on the entire surface of a 3D-structured hydrogel scaffold seeded with cells due to dynamic compressive load stimulation. The computational FSI model made it possible to simultaneously investigate the influence of both mechanical deformation and flow of the culture medium on the cells on the scaffold surface during stimulation. The transient one-way FSI model thus opens up significantly more possibilities for predicting cell differentiation in mechanically stimulated scaffolds than previous static microscale computational approaches used in mechanobiology. In a first parameter study, the impact of the amplitude of a sinusoidal compression ranging from 1% to 10% on the phenotype of cells seeded on a porous hydrogel scaffold was analyzed. The simulation results show that the number of cells differentiating into bone tissue gradually decreases with increasing compression amplitude, while differentiation into cartilage cells initially multiplied with increasing compression amplitude in the range of 2% up to 7% and then decreased. Fibrous cell differentiation was predicted from a compression of 5% and increased moderately up to a compression of 10%. At high compression amplitudes of 9% and 10%, negligible areas on the scaffold surface experienced high stimuli where no cell differentiation could occur. In summary, this study shows that simulation of the FSI system is a versatile approach in computational mechanobiology that can be used to study the effects of, for example, different scaffold designs and stimulation parameters on cell differentiation in mechanically stimulated 3D-structured scaffolds.

A Printing Strategy for Embedding Conductor Paths into FFF Printed Parts.

A novel approach to manufacture components with integrated conductor paths involves embedding and sintering an isotropic conductive adhesive (ICA) during fused filament fabrication (FFF). However, the molten plastic is deposited directly onto the adhesive path which causes an inhomogeneous displacement of the uncured ICA. This paper presents a 3D printing strategy to achieve a homogeneous cross-section of the conductor path. The approach involves embedding the ICA into a printed groove and sealing it with a wide extruded plastic strand. Three parameter studies are conducted to obtain a consistent cavity for uniform formation of the ICA path. Specimens made of polylactic acid (PLA) with embedded ICA paths are printed and evaluated. The optimal parameters include a groove printed with a layer height of 0.1 mm, depth of 0.4 mm, and sealed with a PLA strand of 700 µm diameter. This resulted in a conductor path with a homogeneous cross-section, measuring 660 µm ± 22 µm in width (relative standard deviation: 3.3%) and a cross-sectional area of 0.108 mm2 ± 0.008 mm2 (relative standard deviation 7.2%). This is the first study to demonstrate the successful implementation of a printing strategy for embedding conductive traces with a homogeneous cross-sectional area in FFF 3D printing.

3D printing of piezoelectric and bioactive barium titanate-bioactive glass scaffolds for bone tissue engineering.

Bone healing is a complex process orchestrated by various factors, such as mechanical, chemical and electrical cues. Creating synthetic biomaterials that combine several of these factors leading to tailored and controlled tissue regeneration, is the goal of scientists worldwide. Among those factors is piezoelectricity which creates a physiological electrical microenvironment that plays an important role in stimulating bone cells and fostering bone regeneration. However, only a limited number of studies have addressed the potential of combining piezoelectric biomaterials with state-of-the-art fabrication methods to fabricate tailored scaffolds for bone tissue engineering. Here, we present an approach that takes advantage of modern additive manufacturing techniques to create macroporous biomaterial scaffolds based on a piezoelectric and bioactive ceramic-crystallised glass composite. Using binder jetting, scaffolds made of barium titanate and 45S5 bioactive glass are fabricated and extensively characterised with respect to their physical and functional properties. The 3D-printed ceramic-crystallised glass composite scaffolds show both suitable mechanical strength and bioactive behaviour, as represented by the accumulation of bone-like calcium phosphate on the surface. Piezoelectric scaffolds that mimic or even surpass bone with piezoelectric constants ranging from 1 to 21 pC/N are achieved, depending on the composition of the composite. Using MC3T3-E1 osteoblast precursor cells, the scaffolds show high cytocompatibility coupled with cell attachment and proliferation, rendering the barium titanate/45S5 ceramic-crystallised glass composites promising candidates for bone tissue engineering.

3D printed and stimulus responsive drug delivery systems based on synthetic polyelectrolyte hydrogels manufactured via digital light processing.

Hydrogels are three-dimensional hydrophilic polymeric networks absorbing up to and even more than 90 wt% of water. These superabsorbent polymers retain their shape during the swelling process while enlarging their volume and mass. In addition to their swelling behavior, hydrogels can possess other interesting properties, such as biocompatibility, good rheological behavior, or even antimicrobial activity. This versatility qualifies hydrogels for many medical applications, especially drug delivery systems. As recently shown, polyelectrolyte-based hydrogels offer beneficial properties for long-term and stimulus-responsive applications. However, the fabrication of complex structures and shapes can be difficult to achieve with common polymerization methods. This obstacle can be overcome by the use of additive manufacturing. 3D printing technology is gaining more and more attention as a method of producing materials for biomedical applications and medical devices. Photopolymerizing 3D printing methods offer superior resolution and high control of the photopolymerization process, allowing the fabrication of complex and customizable designs while being less wasteful. In this work, novel synthetic hydrogels, consisting of [2-(acryloyloxy) ethyl]trimethylammonium chloride (AETMA) as an electrolyte monomer and poly(ethylene glycol)-diacrylate (PEGDA) as a crosslinker, 3D printed via Digital Light Processing (DLP) using a layer height of 100 µm, are reported. The hydrogels obtained showed a high swelling degree q∞m,t ∼ 12 (24 h in PBS; pH 7; 37 °C) and adjustable mechanical properties with high stretchability (εmax ∼ 300%). Additionally, we embedded the model drug acetylsalicylic acid (ASA) and investigated its stimulus-responsive drug release behaviour in different release media. The stimulus responsiveness of the hydrogels is mirrored in their release behavior and could be exploited in triggered as well as sequential release studies, demonstrating a clear ion exchange behavior. The received 3D-printed drug depots could also be printed in complex hollow geometry, exemplarily demonstrated via an individualized frontal neo-ostium implant prototype. Consequently, a drug-releasing, flexible, and swellable material was obtained, combining the best of both worlds: the properties of hydrogels and the ability to print complex shapes.

Correction: 3D printed and stimulus responsive drug delivery systems based on synthetic polyelectrolyte hydrogels manufactured via digital light processing.

Correction for '3D printed and stimulus responsive drug delivery systems based on synthetic polyelectrolyte hydrogels manufactured via digital light processing' by Sonja Vaupel et al., J. Mater. Chem. B, 2023, DOI: https://doi.org/10.1039/d3tb00285c.

Micro Injection Molding of Drug-Loaded Round Window Niche Implants for an Animal Model Using 3D-Printed Molds.

A novel approach for the long-term medical treatment of the inner ear is the diffusion of drugs through the round window membrane from a patient-individualized, drug-eluting implant, which is inserted in the middle ear. In this study, drug-loaded (10 wt% Dexamethasone) guinea pig round window niche implants (GP-RNIs, ~1.30 mm × 0.95 mm × 0.60 mm) were manufactured with high precision via micro injection molding (µIM, Tmold = 160 °C, crosslinking time of 120 s). Each implant has a handle (~3.00 mm × 1.00 mm × 0.30 mm) that can be used to hold the implant. A medical-grade silicone elastomer was used as implant material. Molds for µIM were 3D printed from a commercially available resin (TG = 84 °C) via a high-resolution DLP process (xy resolution of 32 µm, z resolution of 10 µm, 3D printing time of about 6 h). Drug release, biocompatibility, and bioefficacy of the GP-RNIs were investigated in vitro. GP-RNIs could be successfully produced. The wear of the molds due to thermal stress was observed. However, the molds are suitable for single use in the µIM process. About 10% of the drug load (8.2 ± 0.6 µg) was released after 6 weeks (medium: isotonic saline). The implants showed high biocompatibility over 28 days (lowest cell viability ~80%). Moreover, we found anti-inflammatory effects over 28 days in a TNF-α-reduction test. These results are promising for the development of long-term drug-releasing implants for human inner ear therapy.