Circular RNA hsa_circ_0000690 as a potential biomarker for diagnosis and prognosis of intracranial aneurysm: Closely relating to the volume of hemorrhage

Abstract Purpose This study aimed to explore circular RNA (circRNA) hsa_circ_0000690 as a potential biomarker for diagnosis and prognosis of intracranial aneurysm (IA) and its relationship with clinical factors and complications of IA. Material/methods 216 IA patients admitted to the neurosurgery department of our hospital from January 2019 to December 2020 were selected as the experimental group, and 186 healthy volunteers were selected as the control group. The expression of hsa_circ_0000690 in peripheral blood was detected by quantitative real‐time PCR, and its diagnostic value was assessed by receiver operating characteristic curve. Relationship between hsa_circ_0000690 and clinical factors of IA was assessed by chi‐square test. Nonparametric test was used in univariate analysis, and regression analysis was used in multivariate analysis. Multivariate Cox proportional hazards regression analysis was used to analyze the survival time. Results CircRNA hsa_circ_0000690 of IA patients was relatively lower than that in the control group (p < .001). The AUC of hsa_circ_0000690 was 0.752, the specificity was 0.780, and sensitivity was 0.620, with diagnostic threshold of 0.0449. In addition, hsa_circ_0000690 expression was correlated with Glasgow Coma Scale, the volume of subarachnoid hemorrhage, modified Fisher scale, Hunt–Hess levels and surgical type. For hydrocephalus and delayed cerebral ischemia, hsa_circ_0000690 was significant in univariate analysis, but nonsignificant in multivariate analysis. For prognosis, hsa_circ_0000690 was significantly associated with modified Rankin Scales after surgery for 3 months, but not associated with survival time. Conclusions The expression of hsa_circ_0000690 can act as a diagnostic marker for IA and predict the prognosis of 3 months after operation and is closely related to the volume of hemorrhage

Swimming Characteristics of Bioinspired Helical Microswimmers Based on Soft Lotus-Root Fibers

Various kinds of helical swimmers inspired by E. coli bacteria have been developed continually in many types of researches, but most of them are proposed by the rigid bodies. For the targeted drug delivery, the rigid body may hurt soft tissues of the working region with organs. Due to this problem, the biomedical applications of helical swimmers may be restricted. However, the helical microswimmers with the soft and deformable body are appropriate and highly adaptive in a confined environment. Thus, this paper presents a lotus-root-based helical microswimmer, which is fabricated by the fibers of lotus-root coated with magnetic nanoparticles to active under the magnetic fields. The helical microstructures are derived from the intrinsic biological structures of the fibers of the lotus-root. This paper aims to study the swimming characteristic of lotus-root-based microswimmers with deformable helical bodies. In the initial step under the uniform magnetic actuation, the helical microswimmers are bent lightly due to the heterogeneous distribution of the internal stress, and then they undergo a swimming motion which is a spindle-like rotation locomotion. Our experiments report that the microswimmers with soft bodies can locomote faster than those with rigid bodies. Moreover, we also find that the curvature of the shape decreases as a function of actuating field frequency which is related to the deformability of lotus-root fibers

VAM-Net: Vegetation-Attentive deep network for Multi-modal fusion of visible-light and vegetation-sensitive images

Multi-modal fusion of remote sensing images poses challenges because of the intricate imaging mechanisms and variations in radiation across different modalities. Specifically, the fusion of visible-light and vegetation-sensitive images encounters similar difficulties. Traditional methods have seldom considered the varied imaging mechanisms and radiation difference between modalities, resulting in discrepancies in the correspond features. To address the issue, we propose the VAM-Net (Vegetation-Attentive Multi-modal deep Network) combining a radiometric correction mechanism and a lightweight multi-modal adaptive feature selection method for fusing multi-modal images. First, the vegetation index (VDVI) is integrated into visible-light images to mitigate the radiometric differences between visible-light images and vegetation-sensitive images (e.g., infrared and red edge images). Then, a two-branch network incorporating attention mechanisms is designed to independently capture the texture features and select similar features cross two different modalities of images. Last, a new loss function is presented to ensure the learned features are suitable for multi-modal fusion. The VAM-Net is evaluated by visible-light and vegetation-sensitive images in three different areas, and the experimental results show that VAM-Net attains an average precision of 67.02%, and recall of 35.49%, and an average RMSE of 2.191px, demonstrating the accuracy and robustness of VAM-Net in multi-modal image fusion

Methylglyoxal Impairs Insulin Secretion of Pancreatic β-Cells through Increased Production of ROS and Mitochondrial Dysfunction Mediated by Upregulation of UCP2 and MAPKs

Methylglyoxal (MG) is a highly reactive glucose metabolic intermediate and a major precursor of advanced glycation end products. MG level is elevated in hyperglycemic disorders such as diabetes mellitus. Substantial evidence has shown that MG is involved in the pathogenesis of diabetes and diabetic complications. We investigated the impact of MG on insulin secretion by MIN6 and INS-1 cells and the potential mechanisms of this effect. Our study demonstrates that MG impaired insulin secretion by MIN6 or ISN-1 cells in a dose-dependent manner. It increased reactive oxygen species (ROS) production and apoptosis rate in MIN6 or ISN-1 cells and inhibited mitochondrial membrane potential (MMP) and ATP production. Furthermore, the expression of UCP2, JNK, and P38 as well as the phosphorylation JNK and P38 was increased by MG. These effects of MG were attenuated by MG scavenger N-acetyl cysteine. Collectively, these data indicate that MG impairs insulin secretion of pancreatic β-cells through increasing ROS production. High levels of ROS can damage β-cells directly via JNK/P38 upregulation and through activation of UCP2 resulting in reduced MMP and ATP production, leading to β-cell dysfunction and impairment of insulin production

Gold with +4 and +6 Oxidation States in AuF₄ and AuF₆

An important goal in chemistry is to prepare compounds with unusual oxidation states showing exciting properties. For gold (Au), the relativistic expansion of its 5d orbitals makes it form high oxidation state compounds. Thus far, the highest oxidation state of Au known is +5. Here, we propose high pressure as a controllable method for preparing +4 and +6 oxidation states in Au via its reaction with fluorine. First-principles swarm-intelligence structure search identifies two hitherto unknown stoichiometric compounds, AuF₄ and AuF₆, exhibiting typical molecular crystal character. The high-pressure phase diagram of Au fluorides is rather different from Cu or Ag fluorides, which is indicated by stable chemical compositions and the pressures needed for the synthesis of these compounds. This difference can be associated with the stronger relativistic effects in Au relative to Cu or Ag. Our work represents a significant step forward in a more complete understanding of the oxidation states of Au