Bioengineering最新文献

Ensemble Learning (EL) has been used for almost ten years to classify heart diseases, but it is still difficult to grasp how the "black boxes", or non-interpretable models, behave inside. Predicting heart disease is crucial to healthcare, since it allows for prompt diagnosis and treatment of the patient's true state. Nonetheless, it is still difficult to forecast illness with any degree of accuracy. In this study, we have suggested a framework for the prediction of heart disease based on Explainable artificial intelligence (XAI)-based hybrid Ensemble Learning (EL) models, such as LightBoost and XGBoost algorithms. The main goals are to build predictive models and apply SHAP (SHapley Additive expPlanations) and LIME (Local Interpretable Model-agnostic Explanations) analysis to improve the interpretability of the models. We carefully construct our systems and test different hybrid ensemble learning algorithms to determine which model is best for heart disease prediction (HDP). The approach promotes interpretability and transparency when examining these widespread health issues. By combining hybrid Ensemble learning models with XAI, the important factors and risk signals that underpin the co-occurrence of heart disease are made visible. The accuracy, precision, and recall of such models were used to evaluate their efficacy. This study highlights how crucial it is for healthcare models to be transparent and recommends the inclusion of XAI to improve interpretability and medical decisionmaking.

Wound healing is a complex and precisely regulated process that encompasses multiple stages, including inflammation, anti-inflammation, and tissue repair. It involves various cells and signaling molecules, with macrophages demonstrating a significant degree of plasticity and playing a crucial regulatory role at different stages. In recent years, the use of biomaterials, which include both natural and synthetic polymers or macromolecules, has proliferated for the purpose of enhancing wound healing. This review summarizes how these diverse biomaterials promote wound healing by modulating macrophage behavior and examines the broader implications of these modulations. Additionally, we discuss the limitations associated with the clinical application of immunomodulatory biomaterials and propose potential solutions. Finally, we look towards future developments in the design of immunomodulatory biomaterials intended to enhance wound healing.

Tendons enable movement through their highly aligned extracellular matrix (ECM), predominantly composed of collagen I. Tendinopathies disrupt the structural integrity of tendons by causing fragmentation of collagen fibers, disorganization of fiber bundles, and an increase in glycosaminoglycans and microvasculature, thereby driving the apparent biomechanical and regenerative capacity in patients. Moreover, the complex cellular communication within the tendon microenvironment ultimately dictates the fate between healthy and diseased tendon, wherein extracellular vesicles (EVs) may facilitate the tendon's fate by transporting biomolecules within the tissue. In this study, we aimed to elucidate how the EV functionality is altered in the context of tendon microenvironments by using polycaprolactone (PCL) electrospun scaffolds mimicking healthy and pathological tendon matrices. Scaffolds were characterized for fiber alignment, mechanical properties, and cellular activity. EVs were isolated and analyzed for concentration, heterogeneity, and protein content. Our results show that our mimicked healthy tendon led to an increase in EV secretion and baseline metabolic activity over the mimicked diseased tendon, where reduced EV secretion and a significant increase in metabolic activity over 5 days were observed. These findings suggest that scaffold mechanics may influence EV functionality, offering insights into tendon homeostasis. Future research should further investigate how EV cargo affects the tendon's microenvironment.

This study used epigenomic methylation differential expression analysis to identify primary biomarkers in patients with amyotrophic lateral sclerosis (ALS). We combined electronic medical record datasets from MIMIC-IV (United States) and NHIRD (Taiwan) to explore ALS comorbidities in depth and discover any comorbidity-related biomarkers. We also applied word2vec to these two clinical diagnostic medical databases to measure similarities between ALS and other similar diseases and evaluated the statistical assessment of the odds ratio to discover significant comorbidities for ALS subjects. Important and representative DNA methylation biomarker candidates could be effectively selected by cross-comparing similar diseases to ALS, comorbidity-related genes, and differentially expressed methylation loci for ALS subjects. The screened epigenomic and comorbidity-related biomarkers were clustered based on their genetic functions. The candidate DNA methylation biomarkers associated with ALS were comprehensively discovered. Gene ontology annotations were then applied to analyze and cluster the candidate biomarkers into three different groups based on gene function annotations. The results showed that a potential testing kit for ALS detection can be composed of SOD3, CACNA1H, and ERBB4 for effective early screening of ALS using blood samples. By developing an effective DNA methylation biomarker screening mechanism, early detection and prophylactic treatment of high-risk ALS patients can be achieved.

Ocular artifacts, including blinks and saccades, pose significant challenges in the analysis of electroencephalographic (EEG) data, often obscuring crucial neural signals. This tutorial provides a comprehensive guide to the most effective methods for correcting these artifacts, with a focus on algorithms designed for both laboratory and real-world settings. We review traditional approaches, such as regression-based techniques and Independent Component Analysis (ICA), alongside more advanced methods like Artifact Subspace Reconstruction (ASR) and deep learning-based algorithms. Through detailed step-by-step instructions and comparative analysis, this tutorial equips researchers with the tools necessary to maintain the integrity of EEG data, ensuring accurate and reliable results in neurophysiological studies. The strategies discussed are particularly relevant for wearable EEG systems and real-time applications, reflecting the growing demand for robust and adaptable solutions in applied neuroscience.

The clinical manifestations of ischemic cardiomyopathy (ICM) bear resemblance to dilated cardiomyopathy (DCM), yet their treatments and prognoses are quite different. Early differentiation between these conditions yields positive outcomes, but the gold standard (coronary angiography) is invasive. The potential use of ECG signals based on variational mode decomposition (VMD) as an alternative remains underexplored. An ECG dataset containing 87 subjects (44 DCM, 43 ICM) is pre-processed for denoising and heartbeat division. Firstly, the ECG signal is processed by empirical mode decomposition (EMD) and VMD. And then, five modes are determined by correlation analysis. Secondly, bispectral analysis is conducted on these modes, extracting corresponding bispectral and nonlinear features. Finally, the features are processed using five machine learning classification models, and a comparative assessment of their classification efficacy is facilitated. The results show that the technique proposed provides a better categorization for DCM and ICM using ECG signals compared to previous approaches, with a highest classification accuracy of 98.30%. Moreover, VMD consistently outperforms EMD under diverse conditions such as different modes, leads, and classifiers. The superiority of VMD on ECG analysis is verified.

Ocular surface disease (OSD) is a frequent disabling challenge among patients with glaucoma who use benzalkonium chloride (BAK)-containing topical glaucoma medications for prolonged periods. In this comprehensive review, we evaluated the prevalence of OSD and its management, focusing on both current and future alternatives. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were used to assess a) the impact of active ingredients and preservatives on the ocular surface and b) the efficacy of preservative-free (PF) alternatives and adjunctive therapies. BAK-containing glaucoma medications were found to significantly contribute to OSD by increasing corneal staining, reducing tear film stability, and elevating ocular surface disease index (OSDI) scores. Transitioning to PF formulations or those with less cytotoxic preservatives, such as Polyquad^® and SofZia^®, demonstrated a marked improvement in OSD symptoms. In particular, the use of adjunct cyclosporine A, through its anti-inflammatory and enhanced tear film stability actions, was shown to be very beneficial to the ocular surface. Therefore, the most effective management of OSD is multi-factorial, consisting of switching to PF or less cytotoxic medications, adjunct use of cyclosporine A, and early incorporation of glaucoma surgical treatments such as laser trabeculoplasty, trabeculectomy, glaucoma drainage devices, or minimally invasive glaucoma surgery (MIGS).

Unmet needs in the treatment of chronic otitis media and Eustachian tube dysfunction (ETD) triggered the development of stents for the Eustachian tube (ET). In this study, for the first time, stents were placed in an artificially blocked ET to evaluate stent function. Eight adult female sheep were injected with stabilized hyaluronic acid (HA) on both sides to induce ETD. Subsequently, a tapered nitinol ET stent was inserted on one side, and animals were examined bilaterally by endoscopy, tympanometry, cone beam computed tomography, and final histology. Seven of the stents were placed in the desired cartilaginous portion of the ET. At the end of the study, one stented side appeared slightly open; all other ET orifices were closed. Tympanometry revealed re-ventilation of the middle ear in four out of seven correctly stented animals within 3 to 6 weeks after stent insertion. The major amount of HA was found at the pharyngeal orifice of the ET anterior to the stent. Thus, the stent position did not completely align with the HA position. While a functional analysis will require refinement of the experimental setup, this study provides first promising results for stent insertion in a sheep model of ETD.

Background: Brain biopsy is required for the accurate specification and further diagnosis of intracranial findings. The conventional stereotactic frames are used clinically for biopsies and offer the highest possible precision. Unfortunately, they come with some insurmountable technical and logistical limitations. The aim of the present work is to determine the clinical precision in the needle biopsy of the human brain using a new patient-specific stereotactic navigation device based on 3D printing.

Methods: MRI data sets of human cadaver heads were used to plan 32 intracranial virtual biopsy targets located in different brain regions. Based on these data, 16 individualized stereotactic frames were 3D-printed. After the intraoperative application of the stereotactic device to the cadaver's head, the actual needle position was verified by postoperative CT.

Results: Thirty-two brain areas were successfully biopsied. The target point accuracy was 1.05 ± 0.63 mm, which represents the difference between the planned and real target points. The largest target point deviation was in the coronal plane at 0.60 mm; the smallest was in the transverse plane (0.45 mm).

Conclusions: Three-dimensional-printed, personalized stereotactic frames or platforms are an alternative to the commonly used frame-based and frameless stereotactic systems. They are particularly advantageous in terms of accuracy, reduced medical imaging, and significantly simplified intraoperative handling.

In reconstructive surgery following partial mandibulectomy, the biomechanical integrity of the fibula free flap applied to the remaining mandibular region directly influences the prognosis of the surgery. The purpose of this study is to evaluate the biomechanical integrity of two fixation materials [titanium (Ti) and hydroxyapatite/poly-L-lactide (HA-PLLA)]. In this study, we simulated the mechanical properties of miniplate and screw fixations in two different systems by finite element analysis. A three-dimensional mandibular model was constructed and a fibula free flap and reconstruction surface were designed. The anterior and posterior end of the free flap was positioned with two miniplates and two additional miniplates were applied to the angled area of the fibula. The masticatory loading was applied considering seven principal muscles. The peak von Mises stress (PVMS) distribution, size of fixation deformation, principal stresses on bones, and gap opening size were measured to evaluate the material properties of the fixation. In the evaluation of properties, superior results were observed with both fixation methods immediately after surgery. However, after the formation of callus between bone segments at 2 months, the performance of Ti fixation decreased over time and the differences between the two fixations became minimal by 6 months after surgery. The result of the study implies the positive clinical potential of the HA-PLLA fixation system applied in fibula free flap reconstruction.