Progress in biomedical engineering (Bristol, England)最新文献

Chemical cues have been extensively explored in tissue engineering (TE). However, biophysical cues, such as electrical stimulation (ES) have recently gained attention for their capacity to enhance stem cell (SC) viability, proliferation, and differentiation. This scoping review focused on the impact of space and methods of ES parameters, including voltage, electric field (EF), current, frequency, and duration, when SCs are seeded on scaffolds for TE applications. The review's PICOT question was: 'What is the optimal parameter space of external ES on SCs seeded on a scaffold in anin vitrocell culture?' Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews guidelines, publications were systematically searched and selected from PubMed, Web of Science, and Scopus databases up to April-2025. The predefined inclusion criteria required that publications: employed ES, involved the use of SCs, included seeding SCs on a scaffold, and were conducted in anin vitroexperimental setting.65 publications covering ES and SCs have been incorporated, acknowledging the interdisciplinary challenges in this research domain. This scoping review synthesises the ES literature, highlights challenges, and proposes optimal parameters for SCs in TEs. Our findings highlight the importance of integrating conductive scaffolds with ES. Specifically, results indicate that moderate EF intensities i.e. (<200 V m^-1) protocols under direct coupling stimulation enhance key physiological processes in SCs. These results introduce the therapeutic potential of integrating ES with TE, particularly in neural regeneration, cardiac repair, and wound healing. Achieving that relies on optimising ES parameters to effectively translatein vitrofindings into clinically viable regenerative therapies and contribute to the development of more effective ES strategies and lay the groundwork for future translational research in TE and regenerative medicine.

Artificial intelligence-based radiogenomics has emerged as a promising approach for precision medicine in lung cancer. By integrating medical imaging, genomics, and clinical data, radiogenomics enables non-invasive prediction of key oncogenic driver mutations, exploration of associations between imaging features and gene expression, and development of prognostic models in lung cancer management. Machine learning and deep learning techniques have been applied to predict the mutation status of genes such as epidermal growth factor receptor and Kirsten rat sarcoma viral oncogene homolog, which are crucial for personalized treatment strategies. Radiogenomic studies have identified significant correlations between radiomic features and gene clusters, providing insights into tumor heterogeneity and biological pathways. Moreover, radiogenomics has shown potential in predicting treatment responses, recurrence, and overall survival in lung cancer patients. However, challenges remain in standardization, comprehensive validation, model interpretability, ethnic diversity, and the construction of multi-omics databases. With the advancement of artificial intelligence and the expansion of multimodal databases, future research should focus on solving these challenges to improve the clinical value and generalizability of radiogenomic models, thus playing a greater role in personalized medicine for cancer.

Peripheral arterial disease (PAD) is a common circulatory condition that leads to reduced blood flow to the limbs, often resulting in limb ischemia which can severely impact a patient's quality of life and increase the risk of amputation. Early diagnosis and timely intervention are critical in managing PAD-associated limb ischemia. This review provides a comprehensive overview of the latest diagnostic and therapeutic approaches for PAD and limb ischemia. We explored both non-invasive and invasive diagnostic techniques including ankle-brachial index, duplex ultrasonography, magnetic resonance angiography, computed tomography angiography and emerging technologies like molecular imaging and near-infrared spectroscopy. Therapeutic strategies discussed include pharmacological treatments such as antiplatelet agents and statins, endovascular interventions like angioplasty and stenting as well as advanced options such as gene and stem cell therapies. Emerging treatments including non-thermal plasma and extracellular vesicle therapy are also highlighted for their regenerative potential. We have also addressed the challenges of current approaches, including diagnostic limitations, barriers to new therapies and cost considerations aimed at improving outcomes for PAD patients.

Melanin, a widespread natural biopigment, has attracted growing attention owing to its multifunctional properties and potential in novel biomaterials. This review addresses the classification, biological sources, and extraction methodology of natural melanin from animals, plants, fungi, and bacteria, focusing on its physicochemical properties and bioactivities in therapeutic and diagnostic applications. Melanin's broadband ultraviolet and near-infrared absorbance, strong antioxidant and anti-inflammatory activities, and photothermal conversion efficiency allow its incorporation in photothermal therapy, radioprotection, and wound healing platforms. Moreover, melanin's antimicrobial and antiviral activities that inhibit a diverse array of pathogens indicate its usefulness in surface disinfection and infection prevention. Current advancements in melanin-containing nanoformulations, hydrogels, and microneedle patches highlight their versatility in drug delivery, molecular imaging, and tissue regeneration. Importantly, eco-friendly extraction and utilization of natural melanin advance environmentally friendly approaches in the field of biomedical technology. This review highlights natural melanin's promise as a safe, biocompatible, and multifunctional agent, supporting its use in biomedical applications that address current healthcare challenges.

Skeletal muscles play a pivotal role in facilitating and stabilizing joint movement, retaining body posture, maintaining temperature, and enabling storage and release of nutrients. While most skeletal muscle injuries are benign and can heal via simple home remedial measures, serious muscle injuries due to excessive tension/torsional forces and volumetric muscle loss (VML) caused by trauma or infection often require surgical intervention. Functional free muscle transfer (FFMT) by harvesting healthy muscle tissue and grafting into the damaged site (i.e. autografts) is the current clinical gold standard; however, FFMT is associated with a myriad of limitations including donor site morbidity, infection, and suboptimal tissue regeneration. Skeletal muscle tissue engineering (SMTE) has made giant strides as a promising alternative option for treating VML injuries by developing viable tissue scaffolds that mimic the organized microarchitecture of native tissue, guide myoblast/myotube alignment, and promote skeletal muscle tissue regeneration. In this review, new advancements in the methodology and fabrication of 3D printed/bioprinted scaffolds for skeletal muscle repair and regeneration are discussed. Further, recent studies that employ novel 4D biofabrication approaches using external stimuli (i.e. magnetic field, electric field, temperature, humidity) to guide time-based shape shifting of printed scaffolds towards achieving tissue-mimicking cellular organization and function are highlighted. Finally, current challenges and future perspectives are presented for further development and clinical translation of 4D printed scaffolds for SMTE applications.

Transcatheter aortic valve implantation (TAVI)-related post-operative complications remain significant clinical challenges, and current in-silico simulations fall short in predicting them accurately, limiting their clinical applicability. This scoping review evaluates the state of the art in TAVI computational modeling, identifying methodological gaps and proposing directions for refinement to enhance translational impact. Following PRISMA-ScR guidelines, 40 studies were included, with data extracted and summarized by evaluated outcomes. A quality assessment was performed using a 14-item rubric. Most studies focused on predicting paravalvular leak (65%) and conduction disturbances (20%). This review reveals substantial heterogeneity in modeling approaches, with limited standardization and varying degrees of validation. To improve clinical relevance, future efforts should prioritize model standardization, rigorous validation following ASME V&V guidelines, increased automation, and improved interpretability for clinical users. By ensuring robustness, efficiency, and clinical accessibility, in-silico models could transform TAVI outcome prediction and support personalized treatment planning, ultimately enhancing care standards in structural heart interventions.

In situcartilage engineering aims to repair damaged cartilage within the body by using biomaterials such as hydrogels, often loaded with regenerative cells to support tissue formation at the injury site. Hydrogels are promising candidates forin situcartilage repair due to their biocompatibility and tunable properties. Two major strategies have been explored to enhance their performance: mechanical reinforcement, through the incorporation of secondary structures to improve mechanical behavior and structural integrity; and growth factor delivery, to stimulate cell proliferation, differentiation, and extracellular matrix synthesis. This review first analyzes mechanical reinforcement and growth factor delivery separate, discussing their advantages, limitations, and gaps in the context ofin situapplications. It then highlights the emerging opportunity to combine these strategies within composite, cell-laden hydrogels, and critically examines the current studies, alongside the additional challenges in clinical translation that arises. Finally, future directions are proposed to guide the design and testing of composite hydrogels for more effective and translatablein situcartilage repair therapies.

In 2023, the 8th IFSO analysis reported 480 970 metabolic bariatric procedures worldwide, as an action against obesity, a pandemic affecting more than a billion people. Despite the well-documented risks associated with obesity and the potential health benefits after bariatric surgery (BS), many eligible patients avoid it, raising concerns about whether this is due to a lack of awareness or limitations in existing techniques. Indeed, this discrepancy prompts inquiries into how this trend can be reversed. Is this a lack of proper information to the eligible patients, or is it a conscious choice linked to the limitations of existing technology? This aspect highlights the urgent need for more patient-focused, advanced methodologies that enhance both surgical outcomes and accessibility. Bioengineering offers an innovative approach by personalising BS, encouraging patients to pursue a tailored care pathway. In the era of digital twins, artificial intelligence and virtual surgical planning, bioengineers could support both surgeons and patients, predicting individual success rates, with greater control over surgical outcomes. Some examples are reported in the scientific literature, offering additional information, such as the optimal reduction of stomach volume by varying the tube size in laparoscopic sleeve gastrectomy or adjusting the suture pattern in endoscopic sleeve gastroplasty. Computational models can also predict the mechanical stress and strain on the gastric wall, which is crucial for targeting the brain regions associated with satiety and thus facilitating the weight loss process. Moreover, emerging personalised virtual models are demonstrating significant potential to revolutionise BS, leading to more realistic and precise surgical planning. Therefore, how could these virtual approaches impact the evolution of BS? Which could be the next improvements provided by computational bioengineering in this field? This perspective underscores the importance of adopting and advancing computational bioengineering to address current limitations and enhance the global impact of BS.

Progress in prosthetics development have greatly improved everyday life of people with lower limb amputations. However, efficiently operating a prosthetic device requires a complex learning process, as users need to familiarize with the biomechanics of prosthetic-assisted gait. Both mental and physical workloads play a role in this process, with significant implications for prosthetic use and acceptance. In this perspective review, we explore the intricate relationships between these elements in lower limb prosthetic users and foster the discussion about the possible correlation between various metrics and their use in the fields of biomechanics, cognitive and physical fatigue. First, we describe all compensatory movements that may be performed during prosthetic-assisted gait. We then examine the two loads: mental workload (MWL) and physical load, which are both reflected in the metabolic cost required for prosthetic use. From this analysis, we envision that prosthetic gait could be regulated by different factors, namely, biomechanics, MWL and metabolism. The main goal of this perspective is to foster discussion across these three domains, defining all types of 'loads' imposed on the patient using objective and cross related descriptors. We argue that such descriptors should be analyzed through specific approaches and protocols in order to be quantified in absolute manner. Being able to univocally describe the single inference of these macro areas to bionic limbs use, could lead to new paradigms in the patient's rehabilitation process and in the design of future robotic prostheses.

Immersion in cold water alters physiological (including cardiovascular) state via complex interplay between external stressors (namely, hydrostatic pressure of ambient water and heat loss due to cold) and compensatory mechanisms in the body (namely, humoral and autonomic nervous system control). Prolonged immersion in cold water leads to life-threatening physiological states including death. In addition, rewarming can benefit or harm a casualty depending on the casualty's physiological state and compensatory reserve. However, technology for assessing the survivability of a casualty impacted by cold water immersion does not exist. Toward the overarching goal of fostering the development of next-generation triage and treatment guidance technology for resuscitation after cold water immersion, the goal of this paper is to help establish a comprehensive understanding of cardiovascular responses to cold water immersion and rewarming as well as relevant physiological measurement technologies which may enable status assessment in future implementations. We review literature on the influence of water immersion, exposure to cold, and rewarming on cardiovascular physiology. We summarize the existing findings into a comprehensive mechanistic understanding of typical cardiovascular responses to cold water immersion and rewarming through time. Then, we review literature on the physiological measurement and physiological signal analytics technologies applicable to cold water immersion settings. We conclude the paper with a perspective on outstanding challenges and opportunities pertaining to physiological sensing and analytics to enable autonomous assessment and treatment guidance for resuscitation after cold water immersion.