Our previous study found that suppression of TRPM7 reduced neuronal death in adult rat ischemic brain injury. It was reported that carvacrol blocked TRPM7 and attenuated brain injury in an adult rat MCAO model. The effects of carvacrol on neonatal stroke remain unknown. This study investigated the effects of carvacrol on neuronal injury and behavioral impairment after hypoxia-ischemia in neonatal mice and the potential signaling pathway underlying these effects. Carvacrol inhibited TRPM7 current in HEK293 cells over-expressing TRPM7 and TRPM7-like current in hippocampal neurons in a dose-dependent manner. Carvacrol (>200 μM) reduced OGD-induced neuronal injury in cortical neurons. 24 hours after HI, TRPM7 protein level in the ipsilateral hemisphere was significantly higher than in the contralateral hemisphere. Carvacrol (30 and 50 mg/kg) pre-treatment reduced brain infarct volume 24 hours after HI in a dose-dependent manner. Carvacrol pre-treatment also improved neurobehavioral outcomes. Furthermore, animals pre-treated with carvacrol had fewer TUNEL-positive cells in the brain compared to vehicle-treated animals 3 days after HI. Carvacrol pre-treatment also increased Bcl-2/Bax and p-Akt/t-Akt protein ratios and decreased cleaved caspase-3 protein expression 24 hours after HI. Carvacrol pre-treatment protects against neonatal hypoxic-ischemic brain injury by reducing brain infarct volume, promoting pro-survival signaling and inhibiting pro-apoptotic signaling, as well as improving behavioral outcomes. The neuroprotective effect may be mediated by the inhibition of TRPM7 channel function. Carvacrol is a potential drug development target for the treatment of neonatal stroke.

Type 2 diabetes mellitus (T2DM) affects the formation of carotid atherosclerotic plaques (CAPs) and patients are prone to plaque instability. It is crucial to clarify transcriptomics profiles and identify biomarkers related to the progression of T2DM complicated by CAPs. Ten human CAP samples were obtained, and whole transcriptome sequencing (RNA-seq) was performed. Samples were divided into two groups: diabetes mellitus (DM) versus non-DM groups and unstable versus stable groups. The Limma package in R was used to identify lncRNAs, circRNAs, and mRNAs. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) network creation, and module generation were performed for differentially expressed mRNAs. Cytoscape was used to create a transcription factor (TF)-mRNA regulatory network, lncRNA/circRNA-mRNA co-expression network, and a competitive endogenous RNA (ceRNA) network. The GSE118481 dataset and RT-qPCR were used to verify potential mRNAs.The regulatory network was constructed based on the verified core genes and the relationships were extracted from the above network. In total, 180 differentially expressed lncRNAs, 343 circRNAs, and 1092 mRNAs were identified in the DM versus non-DM group; 240 differentially expressed lncRNAs, 390 circRNAs, and 677 mRNAs were identified in the unstable versus stable group. Five circRNAs, 14 lncRNAs, and 171 mRNAs that were common among all four groups changed in the same direction. GO/KEGG functional enrichment analysis showed that 171 mRNAs were mainly related to biological processes, such as immune responses, inflammatory responses, and cell adhesion. Five circRNAs, 14 lncRNAs, 46 miRNAs, and 54 mRNAs in the ceRNA network formed a regulatory relationship. C22orf34—hsa-miR-6785-5p—RAB37, hsacirc_013887—hsa-miR-6785-5p/hsa-miR-4763-5p/hsa-miR-30b-3p—RAB37, MIR4435-1HG—hsa-miR-30b-3p—RAB37, and GAS5—hsa-miR-30b-3p—RAB37 may be potential RNA regulatory pathways. Seven upregulated mRNAs were verified using the GSE118481 dataset and RT-qPCR. The regulatory network included seven mRNAs, five circRNAs, six lncRNAs, and 14 TFs. We propose five circRNAs (hsacirc_028744, hsacirc_037219, hsacirc_006308, hsacirc_013887, and hsacirc_045622), six lncRNAs (EPB41L4A-AS1, LINC00969, GAS5, MIR4435-1HG, MIR503HG, and SNHG16), and seven mRNAs (RAB37, CCR7, CD3D, TRAT1, VWF, ICAM2, and TMEM244) as potential biomarkers related to the progression of T2DM complicated with CAP. The constructed ceRNA network has important implications for potential RNA regulatory pathways.

Neonatal hypoxic-ischemic encephalopathy causes neurodegeneration and brain injury, leading to sensorimotor dysfunction. Xyloketal B is a novel marine compound isolated from a mangrove fungus Xylaria species (no. 2508) with unique antioxidant effects. In this study, we investigated the effects and mechanism of xyloketal B on oxygen-glucose deprivation-induced neuronal cell death in mouse primary cortical culture and on hypoxic-ischemic brain injury in neonatal mice in vivo. We found that xyloketal B reduced anoxia-induced neuronal cell death in vitro, as well as infarct volume in neonatal hypoxic-ischemic brain injury model in vivo. Furthermore, xyloketal B improved functional behavioral recovery of the animals following hypoxic-ischemic insult. In addition, xyloketal B significantly decreased calcium entry, reduced the number of TUNEL-positive cells, reduced the levels of cleaved caspase-3 and Bax proteins, and increased the level of Bcl-2 protein after the hypoxic-ischemic injury. Our findings indicate that xyloketal B is effective in models of hypoxia-ischemia and thus has potential as a treatment for hypoxic-ischemic brain injury.

The continually increasing number of patients with type 2 diabetes is a worldwide health problem, and the incidence of microvascular complications is closely related to type 2 diabetes. Structural brain abnormalities are considered an important pathway through which type 2 diabetes causes brain diseases. In fact, there is considerable evidence that type 2 diabetes is associated with an increased risk of structural brain abnormalities such as lacunar infarcts (LIs), white matter hyperintensities (WMHs), and brain atrophy. WMHs are a common cerebral small-vessel disease in elderly adults, and it is characterized histologically by demyelination, loss of oligodendrocytes, and vacuolization as a result of small-vessel ischemia in the white matter. An increasing number of studies have found that diabetes is closely related to WMHs. However, the exact mechanism by which type 2 diabetes causes WMHs is not fully understood. This article reviews the mechanisms of type 2 diabetes-related WMHs to better understand the disease and provide help for better clinical treatment.

Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis-acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques.