Current Medical Science最新文献

Objective: This study aimed to investigate the protective effects of berberine (BBR) on pancreatic β-cells and explore its underlying molecular mechanisms via a proteomics-based approach.

Methods: Using db/db mice as a diabetes model, BBR was administered at doses of 100 mg/kg and 200 mg/kg for 8 weeks. The protective effects were assessed through fasting blood glucose (FBG), oral glucose tolerance test (OGTT), insulin tolerance test (ITT), pancreatic histopathological analysis, and TUNEL staining. Proteomic analysis employing the data-independent acquisition (DIA) method identified differentially expressed proteins (DEPs), whereas Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to identify potential pathways. Molecular docking, surface plasmon resonance (SPR), and immunohistochemistry (IHC) were performed to validate key target proteins.

Results: BBR significantly reduced blood glucose levels, improved insulin resistance, enhanced insulin secretion, and reversed pathological changes in pancreatic tissue, thereby alleviating β-cell damage. Proteomic analysis identified 171 DEPs, implicating the AGE/RAGE signaling pathway as a key mechanism through which BBR exerts its protective effects. The results of molecular docking, SPR and IHC confirmed that BBR markedly inhibited the activation of the AGE/RAGE pathway.

Conclusions: These findings suggest that BBR alleviates pancreatic β-cell damage, potentially through regulation of the AGE/RAGE pathway, providing insights into its therapeutic potential for diabetes management.

Objective: Emerging evidence implicates neuroinflammation in the pathogenesis of major depressive disorder (MDD), yet the role of memory B cells remains unclear. In this study, we conducted a bidirectional two-sample Mendelian randomization (MR) study and Bayesian colocalization analyses to investigate the causal relationships between memory B-cell traits and MDD risk.

Methods: MDD summary data were gathered from a meta-analysis of genome-wide association studies (GWASs), whereas memory B-cell genetic variations were sourced from GWASs on immune phenotypes. MR analysis utilized the inverse variance weighted (IVW), MR-Egger, and weighted median methods. Moreover, various sensitivity analyses, including Cochran's Q test, MR Pleiotropy Residual Sum and Outlier (MR-PRESSO), MR-Egger intercept test and Leave-one-out (LOO) analysis, were performed to confirm MR result stability. Bayesian colocalization analyses were also conducted to identify genetic loci shared between memory B cells and MDD.

Results: Our results indicated that genetically predicted increased CD27 protein expression on memory B cells causally elevated MDD risk (ORs: 1.025-1.063, P_FDR < 0.05). Conversely, MDD did not causally affect memory B-cell traits. Additionally, the colocalization analysis revealed no shared genetic variants, suggesting distinct biological pathways.

Conclusions: These findings highlight CD27 as a potential novel biomarker and therapeutic target in MDD, warranting further clinical validation in the future.

Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with metabolic dysregulation. This study aimed to investigate the role of homogentisic acid (HGA), a tyrosine metabolite, in AD pathogenesis and explore its potential as a noninvasive diagnostic biomarker.

Methods: Human saliva samples from AD patients and controls were analyzed. In vivo experiments were conducted using APP/PS1 (Aβ-driven) and P301S (tauopathy-focused) mouse models, which received exogenous HGA via gavage. Key techniques included behavioral tests (Morris water maze, novel object recognition, fear conditioning), Western blot, immunofluorescence, real-time PCR, and mass spectrometry to assess cognitive function, blood-brain barrier (BBB) integrity, Aβ aggregation, synaptic protein expression, and HGA metabolism. In vitro experiments were performed on HT22, SY5Y cells, and primary brain microvascular endothelial cells (BMECs) to verify HGA's direct effects.

Results: Salivary HGA levels were higher in AD patients than in controls, correlating with BBB impairment. Exogenous HGA significantly exacerbated cognitive deficits, BBB leakage, Aβ deposition, and loss of synaptic proteins (PSD93, synaptophysin) in mice, with effects more pronounced in the APP/PS1 than in the P301S model. In vitro, HGA exerted dose-dependent neurotoxicity, promoted Aβ aggregation, and downregulated tight junction proteins (claudin-5, occludin, ZO-1) in BMECs. Mechanistically, AD patients showed reduced expression of HGA-metabolizing enzymes (homogentisate 1,2-dioxygenase, maleylacetoacetate isomerase) and downstream metabolites, indicating impaired HGA catabolism. These findings confirm HGA promotes AD progression via two mutually reinforcing pathways: (1) accelerating Aβ aggregation and synaptic dysfunction; (2) disrupting BBB integrity through downregulating tight junction proteins.

Conclusion: This study identifies salivary HGA as a potential noninvasive biomarker and highlights targeting HGA metabolism or BBB protection as promising strategies for early AD intervention.

The electrical activity of the human heart, recorded via an electrocardiogram (ECG), is characterized by distinct waveforms such as the P wave, QRS complex, and T wave. By analyzing the duration, morphology, and intervals between these waveforms, various cardiac disorders can be identified. This study aims to develop a deep learning-based approach for the accurate classification of congenital heart disease (CHD) using ECG data. We employed convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to analyze ECG signals, leveraging their ability to detect multiple features in time-series data. A deep learning model was developed and trained using features such as estimated peak locations, inter-peak intervals, and other ECG parameters. To address class imbalance, we applied the synthetic minority oversampling technique (SMOTE), which generates synthetic samples to balance each class. The analysis was conducted using the MIT-BIH Arrhythmia Database, enabling CHD classification based on ECG patterns. The proposed method improved classification accuracy by effectively balancing the dataset with SMOTE. Compared to conventional methods, the deep learning algorithms demonstrated robust performance in analyzing ECG data and detecting disease-related patterns, achieving superior results. This study highlights the potential of CNNs and RNNs for classifying CHD from ECG signals. By mitigating data imbalance with SMOTE, the approach enhances both accuracy and reliability. Future work will focus on validating the model with additional datasets and addressing real-world challenges such as noise handling and external validation.

Objective: Previous studies have yielded contradictory conclusions on the relationship between intermittent exotropia (IXT) and the magnitude of myopia, especially in children. The aim of this study was to determine the clinical characteristics of IXT in children with myopia and myopic anisometropia.

Methods: We retrospectively evaluated the clinical data of patients (4-15 years of age) with convergence insufficiency (CI)-IXT and basic IXT who underwent surgery between 2022 and 2023. All patients underwent cycloplegia before the examinations and surgery. The degree of strabismus was measured when the patient viewed from the center of the glasses. Ocular dominance was routinely tested in children with IXT via the "hole-in-card test" after best-corrected visual acuity was obtained. Children were subsequently grouped into 2 groups (anisometropia and nonanisometropia) according to the difference in binocular spherical equivalent (SE) values (≥ 1.0 diopters [D]).

Results: A total of 197 patients were included in the study. The preoperative deviation at near was significantly lower in the basic IXT group than in the CI-IXT group, whereas the distance exodeviation was significantly greater in the basic IXT group than in the CI-IXT group (P < 0.05). Patients with anisometropia were older than those without anisometropia (P < 0.001). The dominant eyes had significantly less myopia than the nondominant eyes did in the CI-IXT and anisometropia groups (P = 0.049 and P = 0.003, respectively). High myopia was more prevalent in middle school students with IXT (16.67%) than in preschool students (4.55%) and primary schoolchildren (3.18%). The percentage of individuals with anisometropia (≥ 3.0 D) varied in the low (1.68%), moderate (8.7%), and high myopia groups (22.22%). Binomial logistic regression analysis revealed that age and SE of the dominant eye were independent factors related to anisometropia in children with IXT (P < 0.001 and P < 0.001, respectively).

Conclusion: Patients with IXT, especially those with anisometropia and CI-IXT, were shown to have less myopia in the dominant eye. Age and SE of the dominant eye were found to be independent factors related to anisometropia in children with IXT.

Objective: This study aimed to systematically evaluate the application of the Cavitron Ultrasonic Surgical Aspirator (CUSA) system in epilepsy surgery and summarize associated surgical experiences.

Methods: In this retrospective analysis, 70 patients with refractory epilepsy underwent CUSA-assisted resection, while 20 controls underwent conventional surgical resection. Patients were categorized according to surgical scenarios for CUSA application, including lesion-related epilepsy resections, mesial temporal lobe procedures, neocortical resections within eloquent areas, and cases requiring preservation of critical vascular structures. Detailed operative metrics were analyzed for each category. Comparative assessments between the CUSA and conventional groups included surgical efficiency, complication rates, and postoperative seizure outcomes on the basis of the modified Engel classification.

Results: CUSA was used for the following procedures: resection of epileptic lesions (n = 26), mesial temporal structures (n = 32), the epileptogenic neocortex (n = 28), and the rolandic cortex (n = 17). Additionally, it was utilized in 6 cases requiring vascular protection during insular resection and in 18 cases involving preservation of cortical dangerous veins. Although the overall surgical efficiency was comparable between the CUSA and conventional groups (68.0 ± 18.2 vs. 61.1 ± 14.7 min, P = 0.180), the CUSA group demonstrated superior efficiency in resecting low-grade tumors (58.6 ± 14.9 vs. 68.1 ± 11.2 min, P = 0.034). Furthermore, the CUSA group presented significantly fewer permanent complications (5.7% vs. 10%, P < 0.0001) and a higher rate of Engel Class I outcomes (82.9% vs. 70.0%, P = 0.278).

Conclusions: The CUSA system represents a suitable and promising surgical tool for resective epilepsy surgery, potentially serving as a valuable option for epilepsy surgeons. Further studies are warranted to validate these findings.

Objective: Patients with chronic kidney disease (CKD) without atherosclerotic cardiovascular disease (ASCVD) have high mortality rates. Guidelines indicate that statin therapy can reduce mortality in CKD patients with ASCVD; however, its benefits for CKD patients without ASCVD remain unclear. This study examined the survival benefits of statin therapy in CKD patients without ASCVD in American and Chinese cohorts.

Methods: A total of 4369 patients diagnosed with CKD without concurrent ASCVD were included from the American Medical Information Mart for Intensive Care (MIMIC)-IV database (n = 1786) and the Chinese Multicenter Registry Cohort for Cardiorenal Improvement II (CIN-II, n = 2583). Participants were grouped by statin use (treated and untreated). The two groups were compared for key indicators, including: (1) statin use rate; (2) 4-year all-cause mortality; (3) 4-year cardiovascular mortality (assessed in the CIN-II cohort). Statistical analyses included Kaplan-Meier survival curves (with log-rank test for group differences) and Cox proportional hazard models (adjusted for confounders) to estimate the association between statin use and mortality.

Results: In the MIMIC-IV cohort, 37.6% of CKD patients received statins, with a 4-year all-cause mortality of 36.3%. After adjustment, statin therapy was associated with lower all-cause mortality (adjusted hazard ratio [aHR]: 0.61; 95% confidence interval [CI]: 0.51-0.72; P < 0.001). In the CIN-II cohort, 33.9% of patients received statins; the 4-year all-cause and cardiovascular mortalities were 10.5% and 5.3%, respectively. Adjusted analyses demonstrated that statin therapy reduced both all-cause mortality (aHR: 0.74; 95% CI: 0.56-0.99; P = 0.037) and cardiovascular mortality (aHR: 0.64; 95% CI: 0.42-0.97; P = 0.031).

Conclusion: Approximately two-thirds of CKD patients without ASCVD in both the American (MIMIC-IV) and Chinese (CIN-II) cohorts did not receive statins. However, statin therapy reduced 4-year all-cause mortality by 26% and 39% in the American and Chinese cohorts, respectively. These findings highlight a clear survival benefit of statin therapy and warrant future randomized controlled trials.

Objective: Cardiovascular-kidney-metabolic (CKM) syndrome involves complicated interactions among cardiovascular integrity, metabolic disorders, and chronic kidney disease, significantly impacting global morbidity and mortality. This study aimed to investigate the effect of an inflammatory diet on CKM syndrome progression.

Methods: This study included 10,387 adults aged 20 years and older with complete data on CKM syndrome diagnosis and dietary inflammatory index (DII) scores. The DII score was derived on the basis of a 2-day dietary recall interview, and CKM syndrome stages were categorized according to clinical criteria. Multinomial logistic regression, restricted cubic spline (RCS) model, and mediation analysis were used to assess the associations between food components, DII scores, and CKM syndrome stages.

Results: A higher DII score was significantly associated with advanced CKM syndrome stages, with odds ratios increasing from 1.35 (1.10, 1.65) to 3.76 (2.76, 5.12) as the DII score rose from the 1st quartile to the 4th quartile (all P < 0.05). The RCS model presented a linear relationship between the DII score and the CKM stage. Mediation analysis revealed that biological age acceleration partially mediated the association between DII score and CKM syndrome, accounting for 21.43%-40.00% of the effect.

Conclusions: Inflammatory diets are associated with increased risk and progression of CKM syndrome. Biological age acceleration is a critical mediating factor, highlighting the importance of dietary interventions in managing CKM syndrome and its associated complications. Future research should focus on longitudinal studies to confirm these findings and explore additional mechanisms through which dietary patterns influence CKM syndrome.

Acute myeloid leukemia (AML) is a common and aggressive blood cancer characterized by the abnormal growth of primitive bone marrow cells. Genetic mutations prevent normal differentiation into blood components. Potential causes include environmental factors, radiation, and viral infections. Research on AML is essential for enhancing our understanding of the disease, facilitating the development of effective treatments, and improving early diagnostic methods to ultimately increase patient survival rates and quality of life. This study focused on the T-cell immune response and T-cell immunotherapy in AML. We collected CD8+ T cells, CD4 + T cells, Natural killer T (NKT) cells, and γδ T cells among the T cells and analyzed the roles that they play in AML. Long-term disease control in AML requires a variety of immunotherapies, including T-cell receptor-engineered T cells (TCR-T), chimeric antigen receptor T-cell therapy (CAR-T), and T-cell immune checkpoint inhibitors. We discuss these treatments and try to find better treatments for AML in the future.

Objective: This study aimed to develop a few-shot learning model for lung nodule detection in CT images by leveraging visual open-set object detection.

Methods: The Lung Nodule Analysis 2016 (LUNA16) public dataset was used for validation. It was split into training and testing sets in an 8:2 ratio. Classical You Only Look Once (YOLO) models of three sizes (n, m, x) were trained on the training set. Transfer learning experiments were then conducted using the mainstream open-set object detection models derived from Detection Transformer (DETR) with Improved DeNoising AnchOr Boxes (DINO), i.e., Grounding DINO and Open-Vocabulary DINO (OV-DINO), as well as our proposed few-shot learning model, across a range of different shot sizes. Finally, all trained models were compared on the test set.

Results: After training on LUNA16, the precision, recall, and mean average precision (mAP) of the different-sized YOLO models showed no significant differences, with peak values of 82.8%, 73.1%, and 77.4%, respectively. OV-DINO's recall was significantly higher than YOLO's, but it did not show clear advantages in precision or mAP. Using only one-fifth of the training samples and one-tenth of the training epochs, our proposed model outperformed both YOLO and OV-DINO, achieving improvements of 6.6%, 9.3%, and 6.9% in precision, recall, and mAP, respectively, with final values of 89.4%, 96.2%, and 87.7%.

Conclusion: The proposed few-shot learning model demonstrates stronger scene transfer capabilities, requiring fewer samples and training epochs, and can effectively improve the accuracy of lung nodule detection.