BioMedical Engineering OnLine最新文献

Background: Neurological disorders, including Parkinson's and Alzheimer's disease, impose a significant burden on individuals and healthcare systems. Effective treatment is often hindered by the restrictive nature of the blood-brain barrier (BBB), limiting drug access to the central nervous system (CNS).

Aim: The purpose of this review is to provide an overview of existing methods to deliver therapeutics to the CNS across the BBB with an emphasis on drug delivery systems that utilize nanotechnology.

Method/source: We performed a thorough review of the published literature on recently emerging trends in pharmacology and nanomedicine that have attempted to deliver drugs to the CNS by addressing the challenge of delivering therapeutics across the BBB.

Result/finding: Nanoparticles and nanocarriers have shown promise for crossing the blood-brain barrier (BBB), improving drug bioavailability in the brain, and facilitating targeted delivery. Several systems applying nanomaterials, including polymeric nanoparticles, liposomes, solid-lipid nanoparticles, and quantum dots, have successfully advanced through preclinical or early clinical studies. However, demonstrated evidence of the implementation and uptake of nanoparticles in specific antitumor and neurotherapeutic indications have several significant challenges, primarily due to safety, biocompatibility, and scalability.

Conclusion: The combination of traditional pharmacology and nanotechnology provides valuable opportunities for drug delivery to the CNS. Gains in the design of nanocarrier systems have great potential for addressing the limits of BBBs and for improving therapeutic outcomes in neurological disease, but more research is necessary for the development of translational clinical studies.

Objective: Using three-dimensional reconstruction techniques to facilitate precision surgery of parapharyngeal interstitial tumours with transoral endoscopic assistance.

Methods: We reported three cases in this article including a hemangioma in the left parapharyngeal space, a nerve sheath tumour in the right parapharyngeal space and a pleomorphic adenoma in the left parapharyngeal space. Three-dimensional (3D) visualisation technology facilitated the creation of a digital three-dimensional model of the patient's tumour and the surrounding structures. This model enabled intuitive visualisation of the tumour's anatomical characteristics and anatomical relationship with surrounding tissues. Consequently, general anaesthesia was administered with the assistance of transoral endoscopy, and the surgical incision was strategically located in the lateral palatoglossal arch and the pharyngo-palatine muscular space.

Results: The postoperative pathological diagnosis was as follows: left parapharyngeal hemangioma, right parapharyngeal complex nerve sheath tumour and left parapharyngeal pleomorphic adenoma. Following the administration of oral endoscopy-assisted surgical treatment, the patient exhibited a marked alleviation of related symptoms. No complications were observed.

Discussion: The integration of medical imaging with contemporary software for three-dimensional reconstruction facilitates the delivery of precise and minimally invasive treatment, ensuring enhanced safety and efficacy. Transoral endoscopic-assisted parapharyngeal space tumour resection is a surgical procedure that offers several advantages, including minimal trauma, rapid recovery and a low complication rate. It is considered a highly effective method for treating benign tumours in the parapharyngeal space.

Implications for practice: The combination of medical imaging and three-dimensional technology can better evaluate the preoperative location of complex tumors,avoid the risk of intraoperative damage to important structures. And it can also be used in medical teaching.

Background: Internet Gaming Disorder (IGD) has become an important emerging research topic with the popularization of Internet technology, but until now, few studies have investigated the dynamic relationship between persistent tolerance symptoms and physiological feedback. From a biomedical signal processing perspective, this gap in research development is due to the difficulty of identifying and examining the relationship between tiny, rapid fluctuations in non-linear, non-stationary physiological signals with limited time-resolved processing techniques. In this study, we propose to use high time-resolved complementary ensemble empirical pattern decomposition and normalized direct quadrature algorithm to explore the interactions between psychological characteristics and peripheral autonomic activity of individuals with IGD during a one-minute play session using the technique of instantaneous pulse rate variability (iPRV).

Results: 26 healthy students and 20 individuals with IGD were recruited to participate in two levels of online games (G1 and G2). The IGD group reported having a fear of missing out and striving for high game standards, both reflecting the inadequacy component of tolerance symptoms. The inadequacy component was significantly positively correlated with IGD risks (r = 0.657). The IGD group also perceived G2 as significantly more challenging than G1. During the G1 stage, emotional intensity was significantly positively correlated with the time component of tolerance (r = 0.293). At the sixth minute of the G1 stage, normalized very high-frequency (r =  - 0.330) and normalized low-frequency (nLF) bands iPRV (r = 0.329) were significantly negatively and positively correlated with the IGD risk, respectively. This nLF band was significantly positively correlated with the inadequacy component (r = 0.313).

Conclusion: These results suggest that tolerance-related motivational components may trigger heightened emotional intensity and peripheral autonomic activation in individuals with IGD. This study provides novel insights into short-term psychophysiological dynamics underlying IGD, contributing to a deeper understanding of its persistent addictive behavior.

Objective: To systematically review and compare the clinical efficacy and impact on fertility function between laparoscopic surgery and methotrexate treatment for tubal pregnancy.

Methods: Five English databases and four Chinese databases were systematically searched from the database establishment to January 31, 2024, and a meta-analysis was conducted using Review Manager 5.3.

Results: Ten articles were included, with a total of 1,034 study patients. The meta-analysis showed that compared with a single intramuscular injection of methotrexate, laparoscopic surgery for tubal pregnancy was associated with a significantly higher tubal patency rate [OR = 2.47, 95% CI 1.72-3.53, P < 0.001]; and a significantly higher spontaneous pregnancy rate [OR = 2.10, 95% CI 1.28-3.46, P = 0.003]; and a shorter time for serum HCG levels to return to normal [MD = -7.10, 95% CI - 7.84-6.36, P < 0.001]. However, there was no statistically significant difference in treatment success rate between the two treatment methods [OR = 1.88, 95% CI 0.53-6.69, P = 0.33], and no statistically significant difference in recurrent EP rate [OR = 1.09, 95% CI 0.41-2.87, P = 0.87].

Conclusion: Compared with a single intramuscular injection of methotrexate, laparoscopic surgery for tubal pregnancy is associated with better fertility function in the future, while the difference in clinical efficacy needs further exploration.

Background: Concomitant epicardial ablation of ventricular tachycardia (VT) remains a clinical challenge in cardiac surgery due to the need for intra-operative mapping. A preoperative patient-tailored epicardial guide could provide an intraoperative 'blueprint' of arrhythmogenic target substrate, thereby facilitating the workflow. Thus far, no 3D printing material or technique has fully met the requirements for this application. This study explores the feasibility of high-consistency rubber (HCR) silicone molding to produce low-cost, customized guides for VT scar ablation.

Methods: An inverted mold was created in Meshmixer using merged LGE-CMR and cardiac CT images of a 61-year-old VT patient, and printed using fused deposition modeling. HCR silicone was milled, sculpted, and trimmed to fit the negative mold. The guide was cured, subjected to autoclaving, and bench-tested on an ex vivo porcine heart model using radiofrequency and cryo-ablation. Various durometers and thicknesses were tested to determine the optimal fit for our application.

Results: Five surgical guides were made using NuSil^™ MED-4072 and MED-4080 silicone (thickness range: 2.0-3.4 mm). Models with 2.1-3.0 mm thickness and 70 Shore A hardness achieved the best balance between flexibility and rigidity for application on a beating heart. The thinnest model (2.0 mm) was too pliable for stable placement. The guides withstood autoclaving and ablation procedures (radiofrequency; cryo-energy) without deformation or compromising structural integrity.

Conclusions: The HCR silicone molding technique allows for the production of flexible, cost-effective epicardial guides for VT ablation, minimizing the need for a full electrophysiology team throughout the entire procedure.

Malignant melanoma remains the most aggressive type of skin cancer, leading to a high rate of associated death over the past decade, often exhibiting resistance to conventional therapies and presenting significant challenges for preclinical testing. In this instance, the complexity of the progression and the interaction within the tumor microenvironment highlight the necessity for advanced models. Traditional 2D cultures and standard 3D systems, such as spheroids and organoids, fail to fully replicate native skin architecture and lack reproducibility, vascularization, and immune integration. Recent advances in 3D bioprinting have enabled the development of melanoma models that more accurately mimic human skin by incorporating multiple cell types, extracellular matrix components, and spatial control. These models support the evaluation of innovative therapies, including nanocarrier-based drug delivery systems and photodynamic therapy (PDT). This review discusses the evolution of in vitro melanoma modeling, highlighting the role of bioprinting technologies and bioink design within this setting, and investigates emerging applications in PDT and drug delivery systems, assessing the advances and current challenges in the context of melanoma.

Background: This study aimed to investigate the risk factors for complications of intra-abdominal infection (IAI) after endoscopic total resection of gastric submucosal tumors (GSMT) and to establish a nomogram prediction model for the occurrence of IAI.

Methods: Clinical data of patients with GSMT who underwent endoscopic full-thickness resection (EFR) from January 2018 to July 2023 were retrospectively analyzed. The patients were divided into IAI and non-IAI groups according to whether IAI occurred during postoperative hospitalization. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analyses were performed on the relevant clinical data of patients in the two groups to screen the independent influencing factors for the occurrence of IAI. The nomogram model was constructed based on the independent influencing factors. Model discrimination was assessed by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The consistency of model predicted risk with actual risk was evaluated using the Hosmer-Lemeshow goodness-of-fit test. The clinical performance of the nomogram model was evaluated using decision curve analysis.

Results: A total of 240 GSMT patients who underwent EFR procedures were finally included in this study, including 14 patients (5.83%) in the IAI group and 226 patients in the non-IAI group. Univariate, LASSO, and multivariate logistic regression analyses showed that age (OR = 1.208, 95% CI: 1.012-1.442), preoperative CAR (OR = 1.259, 95% CI: 1.106-1.433), and surgical time (OR = 1.099, 95% CI: 1.037-1.165) were independent risk factors for IAI following EFR (p < 0.05). A Nomogram model was established based on the above factors. The Hosmer-Lemeshow test value of this model was 3.256 (p = 0.741). The AUC value of the predictive model was 0.968 (95% CI: 0.915-1.000), with a C-index of 0.968 (95% CI: 0.915-1.000), revealing that the nomogram model had good accuracy and discrimination. Decision curve analysis (DCA) supported that the nomogram model provided the highest net benefit when the risk threshold ranged from 0.1 to 1.0.

Conclusions: Age, preoperative CAR level, and surgical time were independent influences on the occurrence of IAI in GSMT patients undergoing EFR surgery. A nomogram model based on these factors had a high predictive efficacy and may provide a guiding intervention for the prevention of postoperative IAI in GSMT patients.

Objective: To explore the predictive value of circulating lymphocyte subpopulation characteristics for the prognosis of stage III-IV non-small cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKI).

Methods: Seventy-two cases of stage III-IV NSCLC patients treated with EGFR-TKI were retrospectively selected as study subjects. The therapeutic effects of the patients were classified into three categories: complete remission (CR) or partial remission (PR) was classified as the remission group; Stable disease (SD) was classified as the stable disease group. Progression disease (PD) is classified as the progression disease group. The clinical data (general information and circulating lymphocyte subpopulation count) of the patients with different treatment effects were compared. The patients were followed up for 5 years, and factors influencing the progression-free survival (PFS) and overall survival (OS) were screened using the COX regression model. Receiver Operating Characteristic (ROC) was plotted to get the optimal stage value of circulating lymphocytes. Changes in PFS and OS of the patients were compared using the KM survival curve.

Results: Analysis of circulating lymphocyte subsets showed that the counts of CD4 + CD45RA + CD62L + T cells in the three groups of patients presented a gradient distribution of remission group > stable disease group > progression disease group. The count of CD19 + B cells in the progression disease group (148.79 ± 39.62) was higher than that in the remission group (118.34 ± 36.71). CD4 + CD45RA + CD62L + T cells were an independent influencing factor of PFS in patients (P < 0.05). ROC curve analysis confirmed that the area under the curve (AUC) of CD4 + CD45RA + CD62L + T cell count for predicting the prognosis of NSCLC patients was 0.840 (95% CI) with a cut-off value of 126.47 and a Youden index of 0.570. The PFS of patients in the high-level group of CD4 + CD45RA + CD62L + T cells was significantly higher than that in the low-level group (P < 0.05).

Conclusion: Circulating lymphocyte subsets were associated with the therapeutic effect of stage III-IV NSCLC patients treated with EGFR-TKI and can be used as a prognostic indicator of PFS in patients treated with EGFR-TKI, but a comprehensive assessment should be made in combination with clinical factors (such as stage and TKI generation).

Objectives: This study aimed to develop and validate a CT radiomics-based explainable machine learning model for precise diagnosing of malignancy and benignity specifically in endometrial cancer (EC) patients.

Methods: A total of 83 EC patients from two centers, including 46 with malignant and 37 with benign conditions, were included, with data split into a training set (n = 59) and a testing set (n = 24). The regions of interest (ROIs) were manually segmented from pre-surgical CT scans, and 1132 radiomic features were extracted from the pre-surgical CT scans using Pyradiomics. Six explainable machine learning (ML) modeling algorithms were implemented, respectively, for determining the optimal radiomics pipeline. The diagnostic performance of the radiomic model was evaluated by using sensitivity, specificity, accuracy, precision, F1 score, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). To enhance clinical understanding and usability, we separately implemented SHAP analysis and feature mapping visualization and evaluated the calibration curve and decision curve.

Results: By comparing six modeling strategies, the Random Forest model emerged as the optimal choice for diagnosing EC, with a training AUROC of 1.00 and a testing AUROC of 0.96. SHAP identified the most important radiomic features, revealing that all selected features were significantly associated with EC (p < 0.05). Radiomics feature maps also provide a feasible assessment tool for clinical applications. Decision curve analysis (DCA) indicated a higher net benefit for our model compared to the "All" and "None" strategies, suggesting its clinical utility in identifying high-risk cases and reducing unnecessary interventions.

Conclusion: CT radiomics-based explainable ML model achieved high diagnostic performance, which could be used as an intelligent auxiliary tool for the diagnosis of endometrial cancer.