Biomolecules & biomedicine最新文献

The Diabetic Foot Ulcer (DFU) is a severe complication that affects approximately 33% of diabetes patients globally, often leading to limb amputation if not detected early. This study introduces an automated approach for identifying and classifying DFU using transfer learning. DFU is typically categorized into ischemic and infection states, which are challenging to distinguish visually. We evaluate the effectiveness of pre-trained Deep Convolutional Neural Network (DCNN) models for autonomous DFU detection. Seven models are compared: EfficientNetB0, DenseNet121, ResNet101, VGG16, MobileNetV2, InceptionV3, and InceptionResNetV2. Additionally, we propose E-DFu-Net, a novel model derived from existing architectures, designed to mitigate overfitting. Experimental results demonstrate that E-DFu-Net achieves remarkable performance, with 97% accuracy in ischemia classification and 92% in infection classification. This advancement enhances current methodologies and aids practitioners in effectively detecting DFU cases.

Heart valve diseases are a prevalent cardiovascular pathology worldwide, affecting nearly 2.5% of the population. Degenerative aortic stenosis is the most common form of heart valve disease. The treatment options include surgical or transcatheter procedures. There are two main categories of valve prostheses available: mechanical heart valves constructed from synthetic materials and bioprosthetic heart valves made from natural biomaterials. The choice of valve type depends on various factors, including the underlying medical condition, suitability for anticoagulation, valve durability, and the patient's age and preferences. Mechanical heart valves have the advantage of long-term durability. However, patients receiving mechanical implants are subjected to lifelong anticoagulation therapy with an increased risk of thromboembolism and bleeding. Natural biomaterials do not require long-term anticoagulation. However, they experience degenerative changes leading to structural valve deterioration that may require reoperation. The purpose of this article is to review the role of natural biological materials used for aortic valve replacement or repair, assess their biomedical and clinical advantages and limitations, and analyze the direction and perspectives of future development.

Cerebral aneurysms (CA) are critical conditions often associated with oxidative stress in vascular endothelial cells (VECs). The enzyme lactate dehydrogenase A (LDHA) plays a crucial role in glycolysis and lactate metabolism, processes implicated in the pathogenesis of aneurysms. Understanding these molecular mechanisms can inform the development of novel therapeutic targets. This study investigated the role of lactate metabolism and lactate-related genes, particularly LDHA and vascular endothelial growth factor A (VEGFA) genes, in VECs during oxidative stress. Using the GSE26969 dataset, we identified differential expression of lactate-related genes and performed functional enrichment analysis, revealing significant associations with glycolysis and lactate metabolic pathways. To induce oxidative stress, VECs were treated with H2O2, and the expression of LDHA and VEGFA was analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting (WB) assays. Under oxygen-glucose deprivation/reperfusion (OGD/R) conditions, the effects of LDHA overexpression and VEGFA knockdown on cell viability and apoptosis were evaluated. Immunoprecipitation combined with western blotting was used to detect the lactylation status of LDHA following OGD/R stimulation and treatment with lactic acid (LA) and 2-deoxyglucose (2-DG). Our results indicated that oxidative stress modulates LDHA expression, glucose uptake, and lactate production, suggesting a metabolic shift towards glycolysis. LDHA overexpression improved cell survival and reduced apoptosis, while VEGFA knockdown had the opposite effect. Additionally, 2-DG treatment reduced LDHA lactylation and apoptosis. Our findings demonstrated that LDHA plays a critical role in the oxidative stress response of VECs, highlighting the potential therapeutic value of targeting glycolysis in CA. This study contributes to the understanding of metabolic adaptations in vascular pathologies and suggests new avenues for therapeutic intervention in CA management.

Ovarian clear cell carcinoma (OCCC) is a subtype of ovarian cancer with a poor prognosis that often shows resistance to chemotherapy. This study retrospectively analyzed 247 patients with OCCC who were admitted to the Cancer Hospital of the Chinese Academy of Medical Sciences (CAMS) between August 2007 and August 2023. Univariate and multivariate Cox regression analyses were used to identify clinicopathological factors associated with OCCC, and a nomogram prediction model was developed to predict OCCC patient survival outcomes. Kaplan‒Meier survival analysis was used to compare survival outcomes among patients with recurrent disease. Compared with systemic therapy, secondary debulking surgery significantly improved the postrecurrence survival (PRS) rate (P = 0.006). Subgroup analysis revealed that the survival benefit was more pronounced in patients with recurrence and satisfactory tumor shrinkage (PPRS = 0.01, PPFS2 = 0.047). The multivariate analysis revealed that positive preoperative ascites, incomplete remission following initial treatment, and undergoing more than six cycles of postoperative chemotherapy were independent prognostic factors affecting overall survival (OS). Additionally, patients with a positive PD-L1 test who received immunotherapy did not experience relapse during the follow-up period. In conclusion, the secondary clearance procedure offers significant benefits for patients with recurrent OCCC, and patients may experience a survival benefit from supplemental immune or targeted therapy at the end of chemotherapy. The development of a personalized treatment plan can help achieve precise treatment, improve prognosis, and enhance patients' quality of life.

Myasthenia gravis (MG) is an acquired autoimmune disease characterized by impaired transmission at the neuromuscular junction, primarily manifesting as fluctuating muscle weakness, fatigability, and partial paralysis. Due to its long disease course, treatment resistance, and frequent relapses, it places a significant burden on patients and their families. In recent years, advances in molecular biology have provided growing evidence that mitochondrial dysfunction impairs muscle function and affects immune cell proliferation and differentiation in patients. Mitochondria, as the cell's energy source, play a critical role in various pathological processes in MG, including oxidative stress, dynamic abnormalities, mitophagy, and mitochondrial metabolism. The role of mitochondrial dysfunction in the pathogenesis of MG has garnered increasing attention. This manuscript primarily explores mitochondrial function and abnormal morphological changes in MG, as well as mitochondrial quality control, metabolic reprogramming, and their potential mechanisms in the pathological changes of the disease. It also reviews the current status of drug therapies aimed at improving mitochondrial function. The goal is to provide novel perspectives and strategies for future mitochondrial-targeted therapies in MG.

The importance of evaluating the nutritional status and immune condition prior to surgery has gained significant attention in predicting the prognosis of cancer patients in recent years. The objective of this study is to establish a risk model for predicting the prognosis of gallbladder carcinoma (GBC) patients. Data from GBC patients who underwent radical resection at West China Hospital of Sichuan University (China) from 2014 to 2021 were retrospectively collected. A novel risk model was created by incorporating the prognostic nutritional index and glucose-to-lymphocyte ratio, and each patient was assigned a risk score. The patients were then divided into low- and high-risk cohorts, and comparisons were made between the two groups in terms of clinicopathological features and prognosis. Propensity score matching was conducted to reduce potential bias. A total of 300 GBC patients receiving radical surgery were identified and included in this study. Patients in the high-risk group were older, had higher levels of serum carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), and cancer antigen 19-9 (CA19-9), were more likely to experience postoperative complications, and had more aggressive tumor characteristics, such as poor differentiation, lymph node metastasis, and advanced tumor stage. They also had lower overall survival (OS) rates (5-year OS rate: 11.2% vs. 37.4%) and disease-free survival (DFS) rates (5-year DFS rate: 5.1% vs. 18.2%). After propensity score matching, the high-risk population still experienced poorer prognosis (5-year OS rate: 12.7% vs 20.5%; 5-year DFS rate: 3.2% vs 8.2%). The risk model combining prognostic nutritional index and glucose-to-lymphocyte ratio can serve as a standalone predictor for the prognosis and assist in optimizing the treatment approach for GBC patients.

Stress-induced hyperglycemia (SIH) is common in patients with traumatic brain injury (TBI) and has been suggested to influence mortality rates. This meta-analysis aims to evaluate the impact of SIH on mortality in TBI patients without preexisting diabetes mellitus (DM). A comprehensive search was performed in Medline, Web of Science, Embase, Wanfang, and China National Knowledge Infrastructure (CNKI) databases up to May 15, 2024, to retrieve relevant studies. Observational studies reporting the incidence of all-cause mortality among TBI patients without preexisting DM, comparing those with and without SIH, were included. The association between SIH and all-cause mortality was analyzed using risk ratios (RR) and 95% confidence intervals (CI) with a random-effects model. Twelve cohort studies comprising 15 datasets with 16,387 TBI patients were included. The pooled analysis showed that SIH was associated with a higher risk of all-cause mortality (RR: 2.00, 95% CI: 1.72-2.33, P < 0.001), with mild heterogeneity (I² = 25%). Sensitivity analysis confirmed the robustness of these findings. Subgroup analyses indicated no significant differences based on study design, patient age, gender proportion, SIH definition, or follow-up duration. However, the association was slightly weaker but still significant in studies using multivariate analyses (RR: 1.76) compared to univariate analyses (RR: 2.69). In conclusion, SIH was associated with a higher risk of all-cause mortality in TBI patients without preexisting DM. Further research should explore the underlying mechanisms and optimal management strategies for SIH in this population.

Neuromodulation is being utilized across a variety of medical subspecialties to treat both painful and non-painful medical conditions. However, publications on neuromodulation topics infrequently occur in journals targeting generalists and medical specialties outside of pain medicine and neurosurgery. This study reviewed implantable neuromodulation devices, their respective Food and Drug Administration-approved indications for use, as well as off-label usage, and the associated potential risks and benefits for each device. PubMed and Medline databases were queried for systematic reviews with or without meta-analyses and randomized controlled trials of implantable neuromodulation devices. The literature review resulted in 106 studies eligible for inclusion, and 67 were included in the final review. In conclusion, as the clinical volume of neuromodulation continues to grow, supporting and educating medical professionals who care for patients that receive implanted neuromodulation devices is paramount. It is likely the use of neuromodulation will continue to expand across all medical subspecialties, and as such, every clinician should have a baseline understanding of this treatment.

The triglyceride-glucose index (TyGI) is a novel indicator of insulin resistance, which has been associated with an increased risk of cardiovascular diseases. The aim of this meta-analysis was to determine the association between TyGI and the prognosis of patients with heart failure (HF). Cohort studies relevant to the aim of the meta-analysis were retrieved by searching electronic databases, including PubMed, Web of Science, and Embase. A random-effects model was used to combine the data, incorporating the influence of between-study heterogeneity. Twelve studies involving 20,639 patients with HF were included. Pooled results showed that compared to patients with the lowest category of TyGI at baseline, those with the highest TyGI index were associated with a higher risk of all-cause mortality during follow-up (relative risk [RR] 1.71, 95% confidence interval [CI] 1.46 - 2.00; P < 0.001; I² = 55%). Sensitivity analyses limited to studies after adjustment for confounding factors showed similar results (RR 1.89, 95% CI 1.67 - 2.21; P < 0.001; I² = 13%). Subsequent meta-analyses also showed that a high TyGI at baseline was related to the incidence of cardiovascular death (RR 1.87, 95% CI 1.42 - 2.47; P < 0.001; I² = 57%), HF rehospitalization (RR 1.33, 95% CI 1.04 - 1.69; P < 0.02; I² = 46%), and major adverse cardiovascular events (RR 1.69, 95% CI 1.39 - 2.06; P < 0.001; I² = 17%) during follow-up. In conclusion, a high TyGI may be associated with a poor clinical prognosis for patients with HF.

Cardiovascular diseases (CVDs) are a major challenge in global health. Despite significant advances in treatment and management, the incidence and mortality rates of CVDs have been rising in recent years, particularly in the United States. With continuous advancements in medical technology, perioperative transesophageal echocardiography (TEE) has become a key technology in cardiac surgery, enhancing surgical success rates and patient safety. The application of TEE spans preoperative planning, intraoperative monitoring, and postoperative evaluation, especially in complex procedures such as mitral valve repair and aortic valve replacement, where it plays an indispensable role. Simultaneously, the introduction of artificial intelligence (AI) brings new prospects for TEE image analysis and diagnostic support, significantly improving diagnostic accuracy and real-time decision-making capabilities. However, the application of TEE technology faces challenges such as high costs, uneven technological diffusion, and the high skill requirements for medical personnel. Therefore, establishing standardized training protocols and strengthening multidisciplinary collaboration are crucial. This paper reviews the application of TEE in cardiac surgery and its path toward educational and practical standardization from a global perspective, emphasizing its importance in improving the postoperative quality of life for patients and exploring future directions in technological innovation and educational optimization.