生物医学工程学杂志最新文献

The simultaneous objectives of destroying tumor cells while protecting normal pelvic organs present a dual clinical and technical challenge within the realm of pelvic tumor radiotherapy. This article reviews the latest literatures, focusing on technological innovations in key aspects of radiotherapy such as positioning, planning, and delivery. These include positioning fixation techniques, organ-at-risk avoidance irradiation, non-coplanar irradiation techniques, as well as organ displacement protection and image-guided adaptive techniques. It summarizes and discusses the research progress made in the protection of critical organs during pelvic tumor radiotherapy. The paper emphasizes technological advancements in the protection of critical organs throughout the processes of radiotherapy positioning, planning, and implementation, aiming to provide references for further research on the protection of critical organs in the external irradiation treatment of pelvic tumors.

The deep learning-based automatic detection of epilepsy electroencephalogram (EEG), which can avoid the artificial influence, has attracted much attention, and its effectiveness mainly depends on the deep neural network model. In this paper, an attention-based multi-scale residual network (AMSRN) was proposed in consideration of the multiscale, spatio-temporal characteristics of epilepsy EEG and the information flow among channels, and it was combined with multiscale principal component analysis (MSPCA) to realize the automatic epilepsy detection. Firstly, MSPCA was used for noise reduction and feature enhancement of original epilepsy EEG. Then, we designed the structure and parameters of AMSRN. Among them, the attention module (AM), multiscale convolutional module (MCM), spatio-temporal feature extraction module (STFEM) and classification module (CM) were applied successively to signal reexpression with attention weighted mechanism as well as extraction, fusion and classification for multiscale and spatio-temporal features. Based on the Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) public dataset, the AMSRN model achieved good results in sensitivity (98.56%), F1 score (98.35%), accuracy (98.41%) and precision (98.43%). The results show that AMSRN can make good use of brain network information flow caused by seizures to enhance the difference among channels, and effectively capture the multiscale and spatio-temporal features of EEG to improve the performance of epilepsy detection.

Targeting p21-activated kinase 1 (PAK1) is a novel strategy for pancreatic cancer treatment. Compound Kushen injection contains many anti-pancreatic cancer components, but the specific targets are unknown. In this study, 14α-hydroxymatrine, an active component of Kushen injection, was found to possess high binding free energy with the allosteric site of PAK1 by molecular docking based virtual screening. Molecular dynamics simulations suggested that 14α-hydroxymatrine caused the α1 and α2 helices of the allosteric site of PAK1 to extend outward to form a deep allosteric regulatory pocket. Meanwhile, 14α-hydroxymatrine induced the β-folding region at the adenosine triphosphate (ATP)-binding pocket of PAK1 to close inward, resulting in the ATP-binding pocket in a "semi-closed" state which caused the inactivation of PAK1. After removal of 14α-hydroxymatrine, PAK1 showed a tendency to change from the inactive conformation to the active conformation. We supposed that 14α-hydroxymatrine of compound Kushen injection might be a reversible allosteric inhibitor of PAK1. This study used modern technologies and methods to study the active components of traditional Chinese medicine, which laid a foundation for the development and utilization of natural products and the search for new treatments for pancreatic cancer.

Emotion recognition refers to the process of determining and identifying an individual's current emotional state by analyzing various signals such as voice, facial expressions, and physiological indicators etc. Using electroencephalogram (EEG) signals and virtual reality (VR) technology for emotion recognition research helps to better understand human emotional changes, enabling applications in areas such as psychological therapy, education, and training to enhance people's quality of life. However, there is a lack of comprehensive review literature summarizing the combined researches of EEG signals and VR environments for emotion recognition. Therefore, this paper summarizes and synthesizes relevant research from the past five years. Firstly, it introduces the relevant theories of VR and EEG signal emotion recognition. Secondly, it focuses on the analysis of emotion induction, feature extraction, and classification methods in emotion recognition using EEG signals within VR environments. The article concludes by summarizing the research's application directions and providing an outlook on future development trends, aiming to serve as a reference for researchers in related fields.

Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm ³. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.

Previous studies have shown that growth arrest, dedifferentiation, and loss of original function occur in cells after multiple generations of culture, which are attributed to the lack of stress stimulation. To investigate the effects of multi-modal biomimetic stress (MMBS) on the biological function of human bladder smooth muscle cells (HBSMCs), a MMBS culture system was established to simulate the stress environment suffered by the bladder, and HBSMCs were loaded with different biomimetic stress for 24 h. Then, cell growth, proliferation and functional differentiation were detected. The results showed that MMBS promoted the growth and proliferation of HBSMCs, and 80 cm H ₂O pressure with 4% stretch stress were the most effective in promoting the growth and proliferation of HBSMCs and the expression level of α-smooth muscle actin and smooth muscle protein 22-α. These results suggest that the MMBS culture system will be beneficial in regulating the growth and functional differentiation of HBSMCs in the construction of tissue engineered bladder.

The effect of neutrophil extracellular traps (NETs) on promoting intravascular microthrombi formation and exacerbating the severity of sepsis in patients has gained extensive attention. However, in sepsis, the mechanisms and key signaling molecules mediating NET formation during direct interactions of endothelial cells and neutrophils still need further explored. Herein, we utilized lipoteichoic acid (LTA), a component shared by Gram-positive bacteria, to induce NET extrusion from neutrophils firmly adhered to the glass slides coated with intercellular adhesion molecule-1(ICAM-1). We also used Sytox green to label NET-DNA and Flou-4 AM as the intracellular Ca ²⁺ signaling indicator to observe the NET formation and fluctuation of Ca ²⁺ signaling. Our results illustrated that LTA was able to induce NET release from neutrophils firmly attached to ICAM-1-coated glass slides, and the process was time-dependent. In addition, our study indicated that LTA-induced NET release by neutrophils stably adhered to ICAM-1 depended on Ca ²⁺ signaling but not intracellular reactive oxygen species (ROS). This study reveals NET formation mediated by direct interactions between endothelial ICAM-1 and neutrophils under LTA stimulation and key signaling molecules involved, providing the theoretical basis for medicine development and clinical treatment for related diseases.

Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrence-free survival (RFS) of lung adenocarcinoma patients post-surgery is of paramount importance in tailoring postoperative treatment plans. Addressing the challenging task of accurate RFS prediction using CT images, this paper introduces an innovative approach based on self-supervised pre-training and multi-task learning. We employed a self-supervised learning strategy known as "image transformation to image restoration" to pretrain a 3D-UNet network on publicly available lung CT datasets to extract generic visual features from lung images. Subsequently, we enhanced the network's feature extraction capability through multi-task learning involving segmentation and classification tasks, guiding the network to extract image features relevant to RFS. Additionally, we designed a multi-scale feature aggregation module to comprehensively amalgamate multi-scale image features, and ultimately predicted the RFS risk score for lung adenocarcinoma with the aid of a feed-forward neural network. The predictive performance of the proposed method was assessed by ten-fold cross-validation. The results showed that the consistency index (C-index) of the proposed method for predicting RFS and the area under curve (AUC) for predicting whether recurrence occurs within three years reached 0.691 ± 0.076 and 0.707 ± 0.082, respectively, and the predictive performance was superior to that of existing methods. This study confirms that the proposed method has the potential of RFS prediction in lung adenocarcinoma patients, which is expected to provide a reliable basis for the development of individualized treatment plans.

Temporal interference (TI) as a new neuromodulation technique can be applied to non-invasive deep brain stimulation. In order to verify its effectiveness in the regulation of motor behavior in animals, this paper uses the TI method to focus the envelope electric field to the ventral posterior lateral nucleus (VPL) of the thalamus in the deep brain of mouse to regulate left- and right-turning motor behavior. The focusability of TI in the mouse VPL was analyzed by finite element method, and the focus area and volume were obtained by numerical calculation. A stimulator was used to generate TI current to stimulate the mouse VPL to verify the effectiveness of the TI stimulation method, and the accuracy of the focus location was further determined by c-Fos immunofluorescence experiments. The results showed that the electric field generated by TI stimulation was able to focus on the VPL nuclei when the stimulation current reached 800 μA; the mouse were able to make corresponding left and right turns according to the stimulation position; and the c-Fos positive cell markers in the VPL nuclei increased significantly after stimulation. This study confirms the feasibility of TI in regulating animal motor behavior and provides a non-invasive stimulation method for brain tissue for animal robots.

The freeze-drying is a technology that preserves biological samples in a dry state, which is beneficial for storage, transportation, and cost saving. In this study, the bovine pericardium was treated with a freeze-drying protectant composed of polyethylene glycol (PEG) and trehalose (Tre), and then freeze-dried. The results demonstrated that the mechanical properties of the pericardium treated with PEG + 10% w/v Tre were superior to those of the pericardium fixed with glutaraldehyde (GA). The wet state water content of the rehydrated pericardium, determined using the Karl Fischer method, was (74.81 ± 1.44)%, which was comparable to that of the GA-fixed pericardium. The dry state water content was significantly reduced to (8.64 ± 1.52)%, indicating effective dehydration during the freeze-drying process. Differential scanning calorimetry (DSC) testing revealed that the thermal shrinkage temperature of the pericardium was (84.96 ± 0.49) ℃, higher than that of the GA-fixed pericardium (83.14 ± 0.11) ℃, indicating greater thermal stability. Fourier transform infrared spectroscopy (FTIR) results showed no damage to the protein structure during freeze-drying. Hematoxylin and eosin (HE) staining demonstrated that the freeze-drying process reduced pore formation, prevented ice crystal growth, and resulted in a tighter arrangement of tissue fibers. The frozen-dried bovine pericardium was subjected to tests for cell viability and hemolysis rate. The results revealed a cell proliferation rate of (77.87 ± 0.49)%, corresponding to a toxicity grade of 1. Additionally, the hemolysis rate was (0.17 ± 0.02)%, which is below the standard of 5%. These findings indicated that the frozen-dried bovine pericardium exhibited satisfactory performance in terms of cytotoxicity and hemolysis, thus meeting the relevant standards. In summary, the performance of the bovine pericardium treated with PEG + 10% w/v Tre and subjected to freeze-drying could meet the required standards.