Bioengineering最新文献

Mesenchymal stem cells (MSCs) hold immense therapeutic potential due to their regenerative and immunomodulatory properties. However, to utilize this potential, it is crucial to optimize their in vitro cultivation conditions. Three-dimensional (3D) culture methods using cell-laden hydrogels aim to mimic the physiological microenvironment in vitro, thus preserving MSC biological functionalities. Cellulosic hydrogels are particularly promising due to their biocompatibility, sustainability, and tunability in terms of chemical, morphological, and mechanical properties. This study investigated the impact of (1) two physical crosslinking scenarios for hydrogels derived from anionic cellulose nanofibers (to-CNF) used to encapsulate adipose-derived MSCs (adMSCs) and (2) physiological culture conditions on the in vitro proliferation, differentiation, and extracellular vesicle (EV) production of these adMSCs. The results revealed that additional Ca²⁺-mediated crosslinking, intended to complement the self-assembly and gelation of aqueous to-CNF in the adMSC cultivation medium, adversely affected both the mechanical properties of the hydrogel spheres and the growth of the encapsulated cells. However, cultivation under dynamic and hypoxic conditions significantly improved the proliferation and differentiation of the encapsulated adMSCs. Furthermore, it was demonstrated that the adMSCs in the CNF hydrogel spheres exhibited potential for scalable EV production with potent immunosuppressive capacities in a bioreactor system. These findings underscore the importance of physiological culture conditions and the suitability of cellulosic materials for enhancing the therapeutic potential of MSCs. Overall, this study provides valuable insights for optimizing the in vitro cultivation of MSCs for various applications, including tissue engineering, drug testing, and EV-based therapies.

Early diagnosis and treatment of surgical wound infection can be challenging. This is especially relevant in the management of periprosthetic joint infection: early detection is key to success and reducing morbidity, mortality and resource use. 'Smart' dressings have been developed to detect parameters suggestive of infection. This scoping review investigates the current status of the field, limited to devices tested in animal models and/or humans, with a focus on their application to arthroplasty. The literature was searched using MEDLINE/PubMed and Embase databases from 2000 to 2023. Original articles assessing external sensing methods for the detection of wound infection in animal models or human participants were included. Sixteen articles were eligible. The results were broadly divided by sensing method: colorimetric, electrochemical and fluorescence/photothermal responses. Six of the devices detected more than one parameter (multimodal), while the rest were unimodal. The most common parameters examined were temperature and pH. Most 'smart' dressings focused on diagnosing infection in chronic wounds, and none were tested in humans with wound infections. There is limited late-stage research into using dressing sensors to diagnose wound infection in post-surgical patients. Future research should explore this to enable inpatient and remote outpatient monitoring of post-operative wounds to detect wound infection.

This paper presents a real-time wearable system designed to assist Parkinson's disease patients experiencing freezing of gait episodes. The system utilizes advanced machine learning models, including convolutional and recurrent neural networks, enhanced with past sample data preprocessing to achieve high accuracy, efficiency, and robustness. By continuously monitoring gait patterns, the system provides timely interventions, improving mobility and reducing the impact of freezing episodes. This paper explores the implementation of a CNN+RNN+PS machine learning model on a microcontroller-based device. The device operates at a real-time processing rate of 40 Hz and is deployed in practical settings to provide 'on demand' vibratory stimulation to patients. This paper examines the system's ability to operate with minimal latency, achieving an average detection delay of just 261 milliseconds and a freezing of gait detection accuracy of 95.1%. While patients received on-demand stimulation, the system's effectiveness was assessed by decreasing the average duration of freezing of gait episodes by 45%. These preliminarily results underscore the potential of personalized, real-time feedback systems in enhancing the quality of life and rehabilitation outcomes for patients with movement disorders.

Accurate segmentation of thyroid nodules in ultrasound images is crucial for the diagnosis of thyroid cancer and preoperative planning. However, the segmentation of thyroid nodules is challenging due to their irregular shape, blurred boundary, and uneven echo texture. To address these challenges, a novel Mamba- and ResNet-based dual-branch network (MRDB) is proposed. Specifically, the visual state space block (VSSB) from Mamba and ResNet-34 are utilized to construct a dual encoder for extracting global semantics and local details, and establishing multi-dimensional feature connections. Meanwhile, an upsampling-convolution strategy is employed in the left decoder focusing on image size and detail reconstruction. A convolution-upsampling strategy is used in the right decoder to emphasize gradual feature refinement and recovery. To facilitate the interaction between local details and global context within the encoder and decoder, cross-skip connection is introduced. Additionally, a novel hybrid loss function is proposed to improve the boundary segmentation performance of thyroid nodules. Experimental results show that MRDB outperforms the state-of-the-art approaches with DSC of 90.02% and 80.6% on two public thyroid nodule datasets, TN3K and TNUI-2021, respectively. Furthermore, experiments on a third external dataset, DDTI, demonstrate that our method improves the DSC by 10.8% compared to baseline and exhibits good generalization to clinical small-scale thyroid nodule datasets. The proposed MRDB can effectively improve thyroid nodule segmentation accuracy and has great potential for clinical applications.

Microbially influenced corrosion represents a critical challenge to the integrity and durability of carbon steel infrastructure, particularly in environments conducive to biofilm formation by nitrate-reducing bacteria (NRB). This study investigated the impact of NRB biofilms on biocorrosion processes within oil/water recovery operations in Algerian pipelines. A comprehensive suite of experimental and analytical techniques, including microbial analysis, gravimetric methods, and surface characterization, were employed to elucidate the mechanisms of microbially influenced corrosion (MIC). Weight loss measurements revealed that carbon steel samples exposed to injection water exhibited a corrosion rate of 0.0125 mm/year, significantly higher than the 0.0042 mm/year observed in crude oil environments. The microbial analysis demonstrated that injection water harbored an average of (4.4 ± 0.56) × 10⁶ cells/cm² for sessile cells and (3.1 ± 0.25) × 10⁵ CFU/mL for planktonic cells, in stark contrast to crude oil, which contained only (2.4 ± 0.34) × 10³ cells/cm² for sessile cells and (4.5 ± 0.12) × 10² CFU/mL for planktonic cells, thereby highlighting the predominant role of injection water in facilitating biofilm formation. Contact angle measurements of injection water on carbon showed 45° ± 2°, compared to 85° ± 4° for crude oil, suggesting an increased hydrophilicity associated with enhanced biofilm adhesion. Scanning electron microscopy further confirmed the presence of thick biofilm clusters and corrosion pits on carbon steel exposed to injection water, while minimal biofilm and corrosion were observed in the crude oil samples.

Nocturnal sympathetic overdrive is an early indicator of cardiovascular (CV) disease, emphasizing the importance of reliable remote patient monitoring (RPM) for autonomic function during sleep. To be effective, RPM systems must be accurate, non-intrusive, and cost-effective. This review evaluates non-invasive technologies, metrics, and algorithms for tracking nocturnal autonomic nervous system (ANS) activity, assessing their CV relevance and feasibility for integration into RPM systems. A systematic search identified 18 relevant studies from an initial pool of 169 publications, with data extracted on study design, population characteristics, technology types, and CV implications. Modalities reviewed include electrodes (e.g., electroencephalography (EEG), electrocardiography (ECG), polysomnography (PSG)), optical sensors (e.g., photoplethysmography (PPG), peripheral arterial tone (PAT)), ballistocardiography (BCG), cameras, radars, and accelerometers. Heart rate variability (HRV) and blood pressure (BP) emerged as the most promising metrics for RPM, offering a comprehensive view of ANS function and vascular health during sleep. While electrodes provide precise HRV data, they remain intrusive, whereas optical sensors such as PPG demonstrate potential for multimodal monitoring, including HRV, SpO2, and estimates of arterial stiffness and BP. Non-intrusive methods like BCG and cameras are promising for heart and respiratory rate estimation, but less suitable for continuous HRV monitoring. In conclusion, HRV and BP are the most viable metrics for RPM, with PPG-based systems offering significant promise for non-intrusive, continuous monitoring of multiple modalities. Further research is needed to enhance accuracy, feasibility, and validation against direct measures of autonomic function, such as microneurography.

Kinesiology, as an interdisciplinary field, emphasizes the study of human physical activity, with a particular focus on biomechanics and sports science [...].

This study aimed to evaluate the osteogenic potential of mesenchymal stromal cell (MSC) spheroids combined with the basic fibroblast growth factor (bFGF) in a mouse femur fracture model. To begin, MSC spheroids were generated, and the expression of key trophic factors (bFGF Bmp2, and Vegfa) was assessed using quantitative PCR (qPCR). A binding assay confirmed the interaction between the bFGF and the spheroids' extracellular matrix. The spheroid cultures significantly upregulated bFGF, Bmp2, and Vegfa expression compared to the monolayers (p < 0.001), and the binding assay demonstrated effective bFGF binding to the MSC spheroids. Following these in vitro assessments, the mice were divided into five groups for the in vivo study: (1) no treatment (control), (2) spheroids alone, (3) bFGF alone, (4) bFGF-loaded spheroids (bFGF-spheroids), and (5) non-viable (frozen) bFGF-loaded spheroids (bFGF-dSpheroids). Bone formation was analyzed by a micro-CT, measuring the bone volume (BV) and bone mineral content (BMC) of the mice four weeks post-fracture. A high dose of the bFGF (10 µg) significantly promoted bone formation regardless of the presence of spheroids, as evidenced by the increases in BV (bFGF, p = 0.010; bFGF-spheroids, p = 0.006; bFGF-dSpheroids, p = 0.032) and BMC (bFGF, p = 0.023; bFGF-spheroids, p = 0.004; bFGF-dSpheroids, p = 0.014), compared to the controls. In contrast, a low dose of the bFGF (1 µg) combined with the MSC spheroids significantly increased BV and BMC compared to the control (BV, p = 0.012; BMC, p = 0.015), bFGF alone (BV, p = 0.012; BMC, p = 0.008), and spheroid (BV, p < 0.001; BMC, p < 0.001) groups. A low dose of the bFGF alone did not significantly promote bone formation (p > 0.05). The non-viable (frozen) spheroids loaded with a low dose of the bFGF resulted in a higher BV and BMC compared to the spheroids alone (BV, p = 0.003; BMC, p = 0.017), though the effect was less pronounced than in the viable spheroids. These findings demonstrate the synergistic effect of the bFGF and MSC spheroids on bone regeneration. The increased expression of the BMP-2 and VEGF observed in the initial experiments, coupled with the enhanced bone formation in vivo, highlight the therapeutic potential of this combination. Future studies will aim to elucidate the underlying molecular mechanisms and assess the long-term outcomes for bone repair strategies.

Lower back pain (LBP) is one of the most prevalent health losses in adults worldwide. Historically, heat has been successfully used for treating pain and relieving tight muscles. Given the effective contact with the occupant's back and proximity to the heat source, coupled with increasing commute times, automotive seats offer an opportunity to intervene. Fifteen adults (nine female) who experienced acute, subacute, and chronic lower back pain were recruited to examine the effectiveness of heat delivered to the lower back in providing temporary pain relief. Participants sat in a car seat for 38 min on two days, which included a 5-min baseline followed by a 33-min intervention; control, or localized. For the control condition, participants sat for 33 min without any thermal devices on, while the localized condition heated and maintained the seat surface temperature of the lower seat back area to ~45 °C. Over the 33-min control condition, the back skin temperature increased by ~1-2 °C and did not impact the subjective LBP. Heating the lower back for 33 min to ~39 °C reduced the subjective LBP by 10%. We demonstrated that lower back pain can be alleviated from an automotive seat providing heat to the lower back within normal commute times in those with lower back pain.