Distinct MRI characteristics of spinal cord diffuse midline glioma, H3 K27-altered in comparison to spinal cord glioma without H3 K27-alteration and demyelination disorder.

BACKGROUND: An applicable magnetic resonance imaging (MRI) biomarker for diffuse midline glioma (DMG), H3 K27-altered of the spinal cord is important for non-invasive diagnosis. PURPOSE: To evaluate the efficacy of conventional MRI (cMRI) in distinguishing between DMGs, H3 K27-altered, gliomas without H3 K27-alteration, and demyelinating lesions in the spinal cord. MATERIAL AND METHODS: Between January 2017 and February 2023, patients with pathology-confirmed spinal cord gliomas (including ependymomas) with definite H3 K27 status and demyelinating diseases diagnosed by recognized criteria were recruited as the training set for this retrospective study. Morphologic parameter assessment was performed by two neuroradiologists on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted imaging. Variables with high inter- and intra-observer agreement were included in univariable correlation analysis and multivariable logistic regression. The performance of the final model was verified by internal and external testing sets. RESULTS: The training cohort included 21 patients with DMGs (13 men; mean age = 34.57 ± 13.489 years), 21 with wild-type gliomas (10 men; mean age = 46.76 ± 17.017 years), and 20 with demyelinating diseases (5 men; mean age = 49.50 ± 18.872 years). A significant difference was observed in MRI features, including cyst(s), hemorrhage, pial thickening with enhancement, and the maximum anteroposterior diameter of the spinal cord. The prediction model, integrating age, age2, and morphological characteristics, demonstrated good performance in the internal and external testing cohort (accuracy: 0.810 and 0.800, specificity: 0.810 and 0.720, sensitivity: 0.872 and 0.849, respectively). CONCLUSION: Based on cMRI, we developed a model with good performance for differentiating among DMGs, H3 K27-altered, wild-type glioma, and demyelinating lesions in the spinal cord.

Mechanism of dexmedetomidine protection against cisplatin induced acute kidney injury in rats.

OBJECTIVE: This study explored the molecular mechanisms by which dexmedetomidine (Dex) alleviates cisplatin (CP)-induced acute kidney injury (AKI) in rats. METHODS: CP-induced AKI models were established, and Dex was intraperitoneally injected at different concentrations into rats in the model groups. Subsequently, rats were assigned to the control, CP, CP + Dex 10 µg/kg, and CP + Dex 25 µg/kg groups. After weighing the kidneys of the rats, the kidney arterial resistive index was calculated, and CP-induced AKI was evaluated. In addition, four serum biochemical indices were measured: histopathological damage in rat kidneys was detected; levels of inflammatory factors, interleukin (IL)-1ß, IL-18, IL-6, and tumor necrosis factor alpha, in kidney tissue homogenate of rats were assessed through enzyme-linked immunosorbent assay (ELISA); and levels of NLRP-3, caspase-1, cleaved caspase-1, gasdermin D (GSDMD), and GSDMD-N in kidney tissues of rats were determined via western blotting. RESULTS: Dex treatment reduced nephromegaly and serum clinical marker upregulation caused by CP-induced AKI. In addition, hematoxylin and eosin staining revealed that Dex treatment relieved CP-induced kidney tissue injury in AKI rats. ELISA analyses demonstrated that Dex treatment reduced the upregulated levels of proinflammatory cytokines in the kidney tissue of AKI rats induced by CP, thereby alleviating kidney tissue injury. Western blotting indicated that Dex alleviated CP-induced AKI by inhibiting pyroptosis mediated by NLRP-3 and caspase-1. CONCLUSION: Dex protected rats from CP-induced AKI, and the mechanism may be related to NLRP-3/Caspase-1-mediated pyroptosis.

Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms.

Background: In the face of continued growth in the elderly population, the need to understand and combat age-related cardiac decline becomes even more urgent, requiring us to uncover new pathological and cardioprotective pathways. Methods: We obtained the aging-related genes of heart failure through WGCNA and CellAge database. We elucidated the biological functions and signaling pathways involved in heart failure and aging through GO and KEGG enrichment analysis. We used three machine learning algorithms: LASSO, RF and SVM-RFE to further screen the aging-related genes of heart failure, and fitted and verified them through a variety of machine learning algorithms. We searched for drugs to treat age-related heart failure through the DSigDB database. Finally, We use CIBERSORT to complete immune infiltration analysis of aging samples. Results: We obtained 57 up-regulated and 195 down-regulated aging-related genes in heart failure through WGCNA and CellAge databases. GO and KEGG enrichment analysis showed that aging-related genes are mainly involved in mechanisms such as Cellular senescence and Cell cycle. We further screened aging-related genes through machine learning and obtained 14 key genes. We verified the results on the test set and 2 external validation sets using 15 machine learning algorithm models and 207 combinations, and the highest accuracy was 0.911. Through screening of the DSigDB database, we believe that rimonabant and lovastatin have the potential to delay aging and protect the heart. The results of immune infiltration analysis showed that there were significant differences between Macrophages M2 and T cells CD8 in aging myocardium. Conclusion: We identified aging signature genes and potential therapeutic drugs for heart failure through bioinformatics and multiple machine learning algorithms, providing new ideas for studying the mechanism and treatment of age-related cardiac decline.

TLF: Triple learning framework for intracranial aneurysms segmentation from unreliable labeled CTA scans.

Intracranial aneurysm (IA) is a prevalent disease that poses a significant threat to human health. The use of computed tomography angiography (CTA) as a diagnostic tool for IAs remains time-consuming and challenging. Deep neural networks (DNNs) have made significant advancements in the field of medical image segmentation. Nevertheless, training large-scale DNNs demands substantial quantities of high-quality labeled data, making the annotation of numerous brain CTA scans a challenging endeavor. To address these challenges and effectively develop a robust IAs segmentation model from a large amount of unlabeled training data, we propose a triple learning framework (TLF). The framework primarily consists of three learning paradigms: pseudo-supervised learning, contrastive learning, and confident learning. This paper introduces an enhanced mean teacher model and voxel-selective strategy to conduct pseudo-supervised learning on unreliable labeled training data. Concurrently, we construct the positive and negative training pairs within the high-level semantic feature space to improve the overall learning efficiency of the TLF through contrastive learning. In addition, a multi-scale confident learning is proposed to correct unreliable labels, which enables the acquisition of broader local structural information instead of relying on individual voxels. To evaluate the effectiveness of our method, we conducted extensive experiments on a self-built database of hundreds of cases of brain CTA scans with IAs. Experimental results demonstrate that our method can effectively learn a robust CTA scan-based IAs segmentation model using unreliable labeled data, outperforming state-of-the-art methods in terms of segmentation accuracy. Codes are released at https://github.com/XueShuangqian/TLF.

Construction of test strips for lung cancer detection based on aptamers.

Lung cancer is the most common malignancy worldwide. Early diagnosis helps to reduce mortality and improve survival. Aptamers are widely used in cancer screening because of their high specificity, good stability and low cost. In this study, using the specific aptamer of lung cancer serum, the sandwich method colloidal gold test strip was prepared by isothermal amplification technique and the principle of nucleic acid hybridisation for the early diagnosis of lung cancer. The results showed that the test strip was positive in 8 patients with lung cancer, which was consistent with the actual cases. The test strip can accurately identify lung cancer patients. The concentration range of nucleic acid detection is 1 × 10-4 - 7 × 10-4 mol/L, and the detection limit is 0.67 mM. The test strip detection method has low cost and simple operation, and provides a reference for the development of home portable tumor early detection.

The Role of Endothelial Cell Mitophagy in Age-Related Cardiovascular Diseases.

Aging is a major risk factor for cardiovascular diseases (CVD), and mitochondrial autophagy impairment is considered a significant physiological change associated with aging. Endothelial cells play a crucial role in maintaining vascular homeostasis and function, participating in various physiological processes such as regulating vascular tone, coagulation, angiogenesis, and inflammatory responses. As aging progresses, mitochondrial autophagy impairment in endothelial cells worsens, leading to the development of numerous cardiovascular diseases. Therefore, regulating mitochondrial autophagy in endothelial cells is vital for preventing and treating age-related cardiovascular diseases. However, there is currently a lack of systematic reviews in this area. To address this gap, we have written this review to provide new research and therapeutic strategies for managing aging and age-related cardiovascular diseases.

Exploring the mechanism of diabetic cardiomyopathy treated with Qigui Qiangxin mixture based on UPLC-Q/TOF-MS, network pharmacology and experimental validation.

Despite its effectiveness in treating diabetic cardiomyopathy (DCM), Qigui Qiangxin Mixture (QGQXM) remains unclear in terms of its active ingredients and specific mechanism of action. The purpose of this study was to explore the active ingredients and mechanism of action of QGQXM in the treatment of DCM through the comprehensive strategy of serum pharmacology, network pharmacology and combined with experimental validation. The active ingredients of QGQXM were analyzed using Ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-Q/TOF-MS). Network pharmacology was utilized to elucidate the mechanism of action of QGQXM for the treatment of DCM. Finally, in vivo validation was performed by intraperitoneal injection of STZ combined with high-fat feeding-induced DCM rat model. A total of 25 active compounds were identified in the drug-containing serum of rats, corresponding to 121 DCM-associated targets. GAPDH, TNF, AKT1, PPARG, EGFR, CASP3, and HIF1 were considered as the core therapeutic targets. Enrichment analysis showed that QGQXM mainly treats DCM by regulating PI3K-AKT, MAPK, mTOR, Insulin, Insulin resistance, and Apoptosis signaling pathways. Animal experiments showed that QGQXM improved cardiac function, attenuated the degree of cardiomyocyte injury and fibrosis, and inhibited apoptosis in DCM rats. Meanwhile, QGQXM also activated the PI3K/AKT signaling pathway, up-regulated Bcl-2, and down-regulated Caspase9, which may be an intrinsic mechanism for its anti-apoptotic effect. This study preliminarily elucidated the mechanism of QGQXM in the treatment of DCM and provided candidate compounds for the development of new drugs for DCM.

Association of Serum Uric Acid with Non-Valvular Atrial Fibrillation: A Retrospective Study in China.

Purpose: The association between serum uric acid (SUA) and atrial fibrillation (AF) has been widely focused on and studied in recent years. However, the exact association between SUA and AF is unclear, and the effect of gender on the association between SUA levels and AF has been controversial. This study aimed to investigate the association between SUA levels and non-valvular AF (NVAF) and the potential effect of gender on it. Patients and Methods: A total of 866 NVAF patients (463 males, age 69.44 ± 8.07 years) and 646 sex-matched control patients in sinus rhythm, with no history of arrhythmia were included in this study. t-test, ANOVA, and chi-square test were used for baseline data analysis. The receiver operating characteristic curve, logistic regression and Pearson correlation analysis were used for correlation analysis. Results: Compared to controls, NVAF patients exhibited higher SUA (P<0.001). After adjusting for confounders of NVAF, SUA remained significantly associated with NVAF, regardless of gender (OR= 1.31, 95% CI 1.18-1.43, P<0.001). SUA demonstrated higher predictability and sensitivity in predicting the occurrence of female NVAF compared to male (area under the curve was 0.68 (95% CI 0.64-0.72, P<0.001), sensitivity 87.3%), with the optimal cut-off point identified as 5.72 mg/dL. Furthermore, SUA levels correlated with APOA1, Scr and NT-proBNP in NVAF patients. SUA levels varied significantly among NVAF subtypes. Conclusion: High SUA levels were independently associated with NVAF, regardless of gender. SUA exhibited higher predictability and sensitivity in predicting the occurrence of NVAF in females compared to males. High SUA levels may affect other NVAF-related factors and participate in the pathophysiological process of NVAF.

Identifying potential ferroptosis key genes for diagnosis and treatment of postmenopausal osteoporosis through competitive endogenous RNA network analysis.

Objective: Postmenopausal osteoporosis (PMOP) is a common systemic metabolic bone disorder that is owing to the reduced estrogen secretion and imbalance of bone absorption and bone formation in postmenopausal women. Ferroptosis has been identified as a novel modulatory mechanism of osteoporosis. Nevertheless, the particular modulatory mechanism between ferroptosis and PMOP is still unclear. The objective of the current investigation was to detect potential biomarkers connected to ferroptosis in PMOP and discover its probable mechanism through bioinformatics. Methods: We downloaded PMOP-related microarray datasets from the database of Gene Expression Omnibus (GEO) and obtained the differentially expressed genes (DEGs). Utilizing bioinformatics analysis, the DEGs were intersected with the ferroptosis dataset to obtain ferroptosis-connected mRNAs. Enrichment analysis employing KOBAS 3.0 was conducted to comprehend the biological functions and enrichment pathways of the DEGs. The generation of the protein-protein interaction (PPI) network was conducted with the aim of identifying central genes. Lastly, the coexpression and competitive endogenous RNA (ceRNA) networks were built using Cytoscape. With the help of external datasets GSE56815 to verify the reliability of the hub genes by plotting ROC curves. Results: We identified 178 DE microRNAs (miRNAs), 138 DE circular RNAs (circRNAs), and 86 ferroptosis-related mRNAs. Enrichment analysis exhibited that mRNAs were primarily connected with the signaling pathways of PI3K/Akt, metabolism, mTOR, FoxO, HIF-1, AMPK, MAPK, ferroptosis, VEGF, and NOD-like receptors. Generation of the PPI network detected eight hub genes. The circRNA/miR-23b-3p/PTEN axis may relieve PMOP by inhibiting ferroptosis through targeting the pathway of PI3K/Akt signaling, which is a vital modulatory pathway for PMOP progression. Moreover, the ROC curves ultimately indicates that the four hub genes have greater diagnostic importance in PMOP samples in contrast to the normal group samples, which may be possible markers for PMOP diagnosis. Conclusions: Bioinformatics analysis identified four hub genes, namely, PTEN, SIRT1, VEGFA, and KRAS, as potential biomarkers for PMOP diagnosis and management. Moreover, the circRNA/miR-23b-3p/PTEN axis may relieve PMOP by suppressing ferroptosis through targeting the pathway of PI3K/Akt signaling, providing a new avenue to explore the pathogenesis of PMOP.

Targeted delivery of berberine using bionic nanomaterials for Atherosclerosis therapy.

Atherosclerosis (AS) is a prevalent chronic vascular inflammatory disease globally, initiated by injury to vascular endothelial cells (VECs). Macrophages play a pivotal role in disease pathogenesis, involving lipid metabolism and inflammation. The application of nanomaterials has been hindered by their rapid clearance by the immune system. Utilizing macrophage cell membranes can mitigate abnormal immune responses and induce a "homing" effect. Here, M2 macrophage cell membranes (M2) were coated onto berberine polylactic-hydroxylase-polylactide (PLGA) nanoparticles (BBR NPs), employing M2 macrophage immune escape, "homing" ability, and membrane coating nanotechnology, and loaded with mannose (Man) to create bionic nanoparticles (BBR NPs@Man/M2). Subsequently, the physical properties of BBR NPs@Man/M2 were characterized. The biocompatibility and biological function of BBR NPs@Man/M2 were assessed in vitro. Finally, the targeting, therapeutic efficacy, and safety of BBR NPs@M2 were investigated in an AS mouse model. The newly developed BBR NPs@Man/M2 exhibited good biocompatibility. Owing to their M2 coating, the nanoparticles effectively targeted macrophages in vitro, inducing a shift from a pro-inflammatory to an anti-inflammatory state. This transition reduced inflammation in endothelial cells and facilitated the repair of damaged endothelial cells. Moreover, M2-coated nanoparticles efficiently targeted and accumulated in atherosclerotic lesions in vivo. Following four weeks of treatment, BBR NPs@Man/M2 significantly delayed AS progression. Furthermore, BBR NPs@Man/M2 demonstrated a good safety profile after long-term administration. In conclusion, BBR NPs@Man/M2 effectively and safely inhibited AS progression. Biomimetic nanoparticles represent a promising approach for the safe and effective delivery of anti-AS drugs.

Modular Biomimetic Strategy Enables Discovery and SAR Exploration of Oxime Macrocycles as Influenza A Virus (H1N1) Inhibitors.

Although vaccination remains the prevalent prophylactic means for controlling Influenza A virus (IAV) infections, novel structural antivirus small-molecule drugs with new mechanisms of action for treating IAV are highly desirable. Herein, we describe a modular biomimetic strategy to expeditiously achieve a new class of macrocycles featuring oxime, which might target the hemagglutinin (HA)-mediated IAV entry into the host cells. SAR analysis revealed that the size and linker of the macrocycles play an important role in improving potency. Particularly, as a 14-membered macrocyclic oxime, 37 exhibited potent inhibitory activity against IAV H1N1 with an EC50 value of 23 nM and low cytotoxicity, which alleviated cytopathic effects and protected cell survival obviously after H1N1 infection. Furthermore, 37 showed significant synergistic activity with neuraminidase inhibitor oseltamivir in vitro.