Surgical meshes play a significant role in the treatment of various medical conditions, such as hernias, pelvic floor issues, guided bone regeneration, and wound healing. To date, commercial surgical meshes are typically made of non-absorbable synthetic polymers, notably polypropylene and polytetrafluoroethylene, which are associated with postoperative complications, such as infections. Biological meshes, based on native tissues, have been employed to overcome such complications, though mechanical strength has been a main disadvantage. The right balance in mechanical and biological performances has been achieved by the advent of bioresorbable meshes. Despite improvements, recurrence of clinical complications associated with surgical meshes raises significant concerns regarding the technical adequacy of current materials and designs, pointing to a crucial need for further development. To this end, current research focuses on the design of meshes capable of biomimicking native tissue and facilitating the healing process without post-operative complications. Researchers are actively investigating advanced bioresorbable materials, both synthetic and natural biopolymers, while also exploring the performance of therapeutic agents, surface modification methods and advanced manufacturing technologies such as 4D printing. This review seeks to evaluate emerging biomaterials and technologies for enhancing the performance and clinical applicability of the next-generation of surgical meshes. STATEMENT OF SIGNIFICANCE: In the ever-transforming landscape of regenerative medicine, the embracement of engineered bioabsorbable surgical meshes stands as a key borderline in addressing persistent challenges and complications associated with existing treatments. The urgency to move beyond conventional non-absorbable meshes, fraught with post-surgery complications, emphasises the necessity of using advanced biomaterials for engineered tissue regeneration. This review critically examines the growing field of absorbable surgical meshes, considering their potential to transform clinical practice. By strategically marrying mechanical strength with bioresorbable characteristics, these innovative meshes hold the promise of mitigating complications and improving patient outcomes across diverse medical applications. As we navigate the complexities of current medicine, this exploration of engineered absorbable meshes emerges as a light of hope, offering an overall perspective on biomaterials, technologies, and strategies adopted to redefine the future of surgical meshes.

Different additive manufacturing technologies have proven effective and useful in remote medicine and emergency or disaster situations. The coronavirus disease 2019 (COVID-19) disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus, has had a huge impact on our society, including in relation to the continuous supply of personal protective equipment (PPE). The aim of the study is to give a detailed overview of 3D-printed PPE devices and provide practical information regarding the manufacturing and further design process, as well as describing the potential risks of using them. Open-source models of a half-face mask, safety goggles, and a face-protecting shield are evaluated, considering production time, material usage, and cost. Estimations have been performed with fused filament fabrication (FFF) and selective laser sintering (SLS) technology, highlighting the material characteristics of polylactic acid (PLA), polyamide, and a two-compound silicone. Spectrophotometry measurements of transparent PMMA samples were performed to determine their functionality as goggles or face mask parts. All the tests were carried out before and after the tetra-acetyl-ethylene-diamine (TAED)-based disinfection process. The results show that the disinfection has no significant effect on the mechanical and structural stability of the used polymers; therefore, 3D-printed PPE is reusable. For each device, recommendations and possible means of development are explained. The files of the modified models are provided. SLS and FFF additive manufacturing technology can be useful tools in PPE development and small-series production, but open-source models must be used with special care.

Additive manufacturing technologies are dynamically developing, strongly affecting almost all fields of industry and medicine. The appearance of electrically conductive polymers has had a great impact on the prototyping process of different electrical components in the case of upper limb prosthetic development. The widely used FFF 3D printing technology mainly uses PLA (polylactic acid) and ABS (acrylonitrile butadiene styrene) based composites, and despite their presence in the field, a detailed, critical characterization and comparison of them has not been performed yet. Our aim was to characterize two PLA and ABS based carbon composites in terms of electrical and mechanical behavior, and extend the observations with a structural and signal transfer analysis. The measurements were carried out by changing the different printing parameters, including layer resolution, printing orientation and infill density. To determine the mechanical properties, static and dynamic tests were conducted. The electrical characterization was done by measuring the resistance and signal transfer characteristics. Scanning electron microscopy was used for the structural analysis. The results proved that the printing parameters had a significant effect on the mechanical and electrical characteristics of both materials. As a major novelty, it was concluded that the ABS carbon composite has more favorable behavior in the case of additive manufacturing of electrical components of upper limb prosthetics, and they can be used as moving, rotating parts as well.

Utilizing additive manufacturing and gamified virtual simulation in the design of neuroprosthetics to improve pediatric outcomes Albert Manero

Additive manufacturing technologies give many new application possibilities in our everyday life. Biomedical applications benefit a lot from 3D printing. In medical applications, several devices can be easily produced or prototyped with FFF/FDM technologies, but we must minimize the contamination risk. New materials regularly appear on the market, recently specified as antibacterial, resulting from compounded silver nanoparticles. Because scientifically accurate and practical information is not available, this way, we lack information regarding mechanical and thermal stability of the printed products. In addition, these parameters are essential in the setting and optimizing the 3D printers. In our recent study, we aimed to analyze PLA, PLA-HDT as well as PLA-Ag nanocomposite in the form of additive manufacturing filament, with DTA/TG. The results showed that these composites, based on their thermal characteristics, can be suitable for 3D print biomedical devices such as orthoses, casts, medical models and also surgical guides; therefore, their further examination should be important, regarding mechanical characteristics and their possible antibacterial effect.

Simulators are widely used in medical education, but objective and automatic assessment is not feasible with low-fidelity simulators, which can be solved with artificial intelligence (AI) and virtual reality (VR) solutions. The effectiveness of a custom-made VR simulator and an AI-based evaluator of a laparoscopic peg transfer exercise was investigated. Sixty medical students were involved in a single-blinded randomised controlled study to compare the VR simulator with the traditional box trainer. A total of 240 peg transfer exercises from the Fundamentals of Laparoscopic Surgery programme were analysed. The experts and AI-based software used the same criteria for evaluation. The algorithm detected pitfalls and measured exercise duration. Skill improvement showed no significant difference between the VR and control groups. The AI-based evaluator exhibited 95% agreement with the manual assessment. The average difference between the exercise durations measured by the two evaluation methods was 2.61 s. The duration of the algorithmic assessment was 59.47 s faster than the manual assessment. The VR simulator was an effective alternative practice compared with the training box simulator. The AI-based evaluation produced similar results compared with the manual assessment, and it could significantly reduce the evaluation time. AI and VR could improve the effectiveness of basic laparoscopic training.