Frontiers in Bioengineering and Biotechnology最新文献

Purpose: Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.

Methods: A sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features.

Results: The predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution.

Conclusion: The pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.

The balance of mitochondrial fission and fusion plays an important role in maintaining the stability of cellular homeostasis. Abnormal mitochondrial fission and fragmentation have been shown to be associated with oxidative stress, which causes a variety of human diseases from neurodegeneration disease to cancer. Therefore, the induction of mitochondrial aggregation and fusion may provide an alternative approach to alleviate these conditions. Here, an optogenetic-based mitochondrial aggregation system (Opto-MitoA) developed, which is based on the CRY2clust/CIBN light-sensitive module. Upon blue light illumination, CRY2clust relocates from the cytosol to mitochondria where it induces mitochondrial aggregation by CRY2clust homo-oligomerization and CRY2clust-CIBN hetero-dimerization. Our functional experiments demonstrate that Opto-MitoA-induced mitochondrial aggregation potently alleviates niclosamide-caused cell dysfunction in ATP production. This study establishes a novel optogenetic-based strategy to regulate mitochondrial dynamics in cells, which may provide a potential therapy for treating mitochondrial-related diseases.

Traumatic brain injury (TBI) represents a significant global public health issue, with effective management posing numerous challenges. The pathophysiology of TBI is typically categorized into two phases: primary and secondary injuries. Secondary injury involves pathophysiological mechanisms such as blood-brain barrier (BBB) disruption, mitochondrial dysfunction, oxidative stress, and inflammatory responses. Current pharmacological strategies often encounter obstacles in treating TBI effectively, primarily due to challenges in BBB penetration, inadequate target site accumulation, and off-target toxicity. Versatile hydrogels and nanoparticles offer potential solutions to these limitations. This review discusses recent progress in utilizing hydrogels and nanoparticles for TBI treatment over the past 5 years, highlighting their relevance to the underlying injury pathophysiology. Hydrogels and nanoparticles demonstrate substantial promise in addressing secondary brain injury, providing a broad spectrum of future therapeutic opportunities.

The bladder is a dynamic organ located in the lower urinary tract, responsible for complex and important physiological activities in the human body, including collecting and storing urine. Severe diseases or bladder injuries often lead to tissue destruction and loss of normal function, requiring surgical intervention and reconstruction. The rapid development of innovative biomaterials has brought revolutionary opportunities for modern urology to overcome the limitations of tissue transplantation. This article first summarized the latest research progress in the processing approaches and functionalization of acellular matrix, hydrogels, nanomaterials, and porous scaffolds in repairing and reconstructing the physiological structure and dynamic function of damaged bladder. Then, we discussed emerging strategies for bladder regeneration and functional recovery, such as cell therapy, organoids, etc. Finally, we outlined the important issues and future development prospects of biomaterials in bladder regeneration to inspire future research directions. By reviewing these innovative biomaterials and technologies, we hope to provide appropriate insights to achieve the ultimate goal of designing and manufacturing artificial bladder substitutes with ideal performance in all aspects.

Introduction: Parkinson's Disease is the second most common neurodegenerative disease in the world. It affects mainly people over 65 and the incidence increases with age. It is characterized by motor and non-motor symptoms and several clinical manifestations. The most evident symptom that affects all patients with Parkinson's Disease is the impairment of motor control, including bradykinesia, tremor, joint rigidity, and postural instability. In the literature, it has been evaluated with muscle synergies, a well-known method for evaluating motor control at the muscular level. However, few studies are available and there is still a major gap to fill to exploit the potential of the method for assessing motor control in Parkinson's Disease, both in the understanding of physiopathology and clinical practice.

Methods: In the light of understanding and fostering future developments for the field, in this review we initially screened 212 papers on Scopus and Web of Science and selected 15 of them to summarize the main features of investigations that employed muscle synergies to analyze patients with Parkinson's Disease. We detailed the features of the screened papers by reporting the clinical findings, a detailed report of EMG processing choices and synergy-based results.

Results: We found that synergistic control is in general altered in patients with Parkinson's Disease, but it can improve if patients are subjected to pharmacological and rehabilitation therapies. Moreover, a further understanding of synergistic control in Parkinson's patients is needed.

Discussion: We discuss the future developments in the field with a detailed assessment of the topic on the view of physicians, including the most promising lines of research for clinical practice and from the perspective of engineers, for methodological application of synergistic approaches.

[This corrects the article DOI: 10.3389/fbioe.2024.1518452.].

Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.

Methods: This study aims to develop a highly accurate and lightweight model for automatically predicting and classifying KOA through knee X-ray imaging. We propose a deep learning model named OA-MEN, which integrates a hybrid model combining ResNet and MobileNet feature extraction with multi-scale feature fusion. This approach ensures enhanced extraction of semantic information without losing the advantages of large feature maps provided by high image resolution in lower layers of the network. This effectively expands the model's receptive field and strengthens its understanding capability. Additionally, we conducted unseen-data tests and compared our model with widely used baseline models to highlight its superiority over conventional approaches.

Results: The OA-MEN model demonstrated exceptional performance in tests. In the unseen-data test, our model achieved an average accuracy (ACC) of 84.88% and an Area Under the Curve (AUC) of 89.11%, marking improvements over the best-performing baseline models. These results showcase its improved capability in predicting KOA from X-ray images, making it a promising tool for assisting radiologists in diagnosis and treatment selection in clinical settings.

Conclusion: Leveraging deep learning for osteoarthritis classification guarantees heightened efficiency and accuracy. The future goal is to seamlessly integrate deep learning and advanced computational techniques with the expertise of medical professionals.

An emerging strategy in cancer therapy involves inducing reactive oxygen species (ROS), specifically within tumors using nanozymes. However, existing nanozymes suffer from limitations such as low reactivity, poor biocompatibility, and limited targeting capabilities, hindering their therapeutic efficacy. In response, the PdRu@PEI bimetallic nanoalloys were constructed with well-catalytic activities and effective separation of charges, which can catalyze hydrogen peroxide (H₂O₂) to toxic hydroxyl radical (·OH) under near-infrared laser stimulation. Through facilitating electron transfer and enhancing active sites, the enhanced peroxidase-like (POD-like) enzymatic activity and glutathione (GSH) depletion abilities of nanozymes are boosted through a simple co-reduction process, leading to promising anti-tumor activity. The electron transfer between Pd and Ru of PdRu@PEI nanoalloys contributes to POD-like activity. Then, by oxidizing endogenous overexpressed GSH, enzymatic cycling prevents GSH from consuming ROS. Furthermore, the surface plasmon resonance effect of near-infrared laser on bimetallic nanoalloys ensures its photothermal performance and its local heating, further promoting POD-like activity. The integrated multi-modal therapeutic approach of PdRu@PEI has demonstrated significant anti-cancer effects in vivo studies. The nanozymes exhibit high catalytic efficiency and excellent biocompatibility, offering valuable insights for the development of nano-catalysts/enzymes for biomedical applications.

Salmonella enterica is a foodborne pathogen commonly found in agricultural facilities; its prevalence, as well as increasing levels of disinfectant- and antibiotic-resistance, has significant costs for agriculture as well as human health. In an effort to identify potential new inhibitors of S. enterica on abiotic surfaces, we developed a biomolecule screen of nutrient-type compounds because nutrients would have lower toxicity in animal facilities and bacterial nutrient utilization pathways might prove less susceptible to the development of bacterial resistance. After screening 285 nutrient-type compounds, we identified ten that significantly inhibited the ability of S. enterica to colonize a plastic surface. After conducting a dose-response curve, salicylic acid was selected for further testing due to its low minimal inhibitory concentration (62.5 μM) as well as a low total inhibitory concentration (250 μM). Salicylic acid was also able to inhibit surface colonization of a wide range of bacterial pathogens, suggesting that our biomolecule screen might have broader application beyond S. enterica. Finally, we determined that salicylic acid was also able to inhibit S. enterica colonization of an organic surface on eggshells. Together, these results suggest that nutrient-type biomolecules may provide an avenue for preventing resistant bacteria from contaminating surfaces.