Magnetic Resonance Imaging to Evaluate the Recovery Effects of Cerebral Nerve Function in Comprehensive Treatment of Poststroke Depression by Intelligent Algorithm-Based Hyperbaric Oxygen Therapy.

This research was aimed to discuss magnetic resonance imaging (MRI) evaluation of recovery effects of cerebral nerve function in comprehensive treatment of poststroke depression (PSD) by intelligence-based hyperbaric oxygen therapy. Low-rank matrix algorithm was adopted to denoise MRI images of patients with PSD, and mean square error (MSE) and peak signal-to-noise ratio (PSNR) were the evaluation indicators of the results of image denoising. 118 patients were randomly divided into the control group (administered escitalopram oxalate) and the research group (hyperbaric oxygen therapy was implemented based on the treatment in control group). National Institutes of Health Stroke Scale (NIHSS), Hamilton Depression Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), glial fibrillary acidic protein (GFAP), and changes of norepinephrine (NE) level of patients in two groups were compared before and after treatment. The value of MSE of MRI images processed by low-rank matrix algorithm was 92.39, which was higher than that calculated by nonlocal mean (NLM) algorithm (80.54). The PSNR value calculated by low-rank matrix algorithm was 25.35, which was lower than that calculated by NLM algorithm (29.07). In contrast, NIHSS score and HAMD score of the research group after treatment were lower than those of the control group, while PSQI score of the research group was higher than that of the control group. The level of GFAP of the research group was at 852.46 ± 94.47, which was significantly lower than that of the control group, reaching 948.53 ± 98.42. However, the level of NE of the research group was 1478.59 ± 99.85, which was higher than that of the control group (1061.80 ± 98.02). All the comparisons of above indicators had statistical meaning (P < 0.05). The low-rank matrix algorithm can help in clinical diagnosis and treatment to provide more accurate MRI images. In addition, hyperbaric oxygen comprehensive therapy can promote the recovery of neurological function in patients with poststroke depression and significantly improve the depressive state and sleep quality of patients.

Naringin Alleviates H2O2-Inhibited Osteogenic Differentiation of Human Adipose-Derived Stromal Cells via Wnt/ß-Catenin Signaling.

Osteoporosis is an age-related systemic bone disease that places a heavy burden on patients and society. In this study, we aimed to investigate the effects of naringin (NAR) on the osteogenic differentiation of human adipose-derived stromal cells (ADSCs). The results demonstrated that NAR pretreatment effectively abated H2O2-induced cell death and ROS accumulation in ADSCs undergoing osteogenic differentiation (ADSCs-OD). In addition, we also observed that the impaired extracellular matrix mineralization and ALP activity in H2O2-stimulated ADSCs-OD were notably rescued by NAR pretreatment. Moreover, the effects of H2O2 exposure on Wnt/ß-catenin signaling in ADSCs-OD were largely reversed by NAR pretreatment. Collectively, our findings indicated that NAR could protect ADSCs-OD against H2O2-inhibited osteogenic differentiation.

Proteomic and metabolomic analyses reveal the novel targets of spermine for alleviating diabetic cardiomyopathy in type II diabetic mice.

Diabetic cardiomyopathy (DCM) is one of the most serious complications of diabetes. Recent cardiology studies suggest that spermine has a cardioprotective effect. Here, we used proteomic and metabolomic analyses to reveal the underlying research targets in a type II diabetic (T2D) mouse model treated with spermine. Left ventricular tissues from nine mice (Control group, three; T2D group, three; T2D+SP group, three) were excised and analyzed. Quantitative analysis of the global proteome and metabolome was performed using the 4D label-free technique and untargeted metabolomics, respectively, and differentially expressed proteins (DEPs) and metabolites were used to perform bioinformatic analyses. A total of 169 DEPs were identified in T2D/Control group, including 115 upregulated and 54 downregulated proteins. Furthermore, 16 DEPs were identified in T2D+SP/T2D group, where these DEPs were found highly enriched in the cellular, metabolic processes, biological regulation, response to stimulus, and immune system process. The results of association analysis between proteomics and metabolomics showed that SP could affect the production of 51 metabolites by regulating the expression of 16 DEPs in the T2D+SP/T2D group. We also found that PRKG1 was closely related to the expressions of 10 overlapping metabolites between db/db and SP-treated mice. Our findings provide insights into the underlying mechanisms for DCM and suggest the potential applicability of utilizing spermine on protecting against DCM-associated cardiac function deterioration.

Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State.

The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke. 208 patients with severe stroke who all received MRI examination were recruited as the research objects. According to cerebral small vascular disease (CSVD) score, the patients were divided into CSVD 0∼4 groups. The patients who completed the three-month follow-up were classified into cognitive impairment group (124 cases) and the noncognitive impairment group (84 cases) according to the cut-off point of the Montreal cognitive assessment (MOCA) scale score of 26. A novel image segmentation algorithm was proposed based on U-shaped fully CNN (U-Net) and conditional random field, which was compared with the fully CNN (FCN) algorithm and U-Net algorithm, and was applied to the MRI segmentation training of patients with severe stroke. It was found that the average symmetric surface distance (ASSD) (3.13 ± 1.35), Hoffman distance (HD) (28.71 ± 9.05), Dice coefficient (0.78 ± 1.35), accuracy (0.74 ± 0.11), and sensitivity (0.85 ± 0.13) of the proposed algorithm were superior to those of FCN algorithm and U-Net algorithm. There were significant differences in the MOCA scores among the five groups of patients from CSVD 0 to CSVD 4 in the three time periods (0, 1, and 3 months) (P < 0.05). Differences in cerebral microhemorrhage (CMB), perivascular space (PVS), and number of cavities, Fazekas, and total CSVD scores between the two groups were significant (P < 0.05). Multivariate regression found that the number of PVS, white matter hyperintensity (WMH) Fazekas, and total CSVD score were independent factors of cognitive impairment. In short, MRI images based on deep learning image segmentation algorithm had good application value for clinical diagnosis and treatment of stroke and can effectively improve the detection effect of brain domain characteristics and psychological state of patients after stroke.

MicroRNA-365-3p inhibits bone marrow mesenchymal stem cell differentiation into islet-like cell clusters via targeting Pax6 and inhibiting the MEK/ERK pathway.

BACKGROUND: Diabetes has severe impacts on the health of patients. The differentiation of mesenchymal stem cells (MSCs) into islet-like cell clusters (ICCs) is an effective protocol for the treatment of diabetes. microRNAs (miRs) regulate multiple cellular processes including cell differentiation. This study sought to identify the mechanism of miR-365-3p in the differentiation of bone marrow MSCs (bMSCs) into ICCs. METHODS: Initially, the differentiation of bMSCs into ICCs was induced. Then, the miR-365-3p expression pattern in the bMSCs and ICCs was detected. Next, the miR-365-3p expression pattern was silenced in bMSCs to assess the effect on differentiation efficiency and measure the expressions of ICC marker genes during the differentiation of bMSCs into ICCs. The miR-365-3p downstream target genes were predicted and verified. Paired box protein 6 (Pax6) was downregulated in bMSCs with silenced miR-365-3p to evaluate the differentiation of bMSCs into ICCs. Furthermore, the Pax6 downstream pathway was evaluated. RESULTS: The differentiation of bMSCs into ICCs was successfully induced. The miR-365-3p expression in bMSCs was higher than that in ICCs. miR-365-3p downregulation in bMSCs facilitated the differentiation of bMSCs into ICCs, as evidenced by elevated releases of insulin and C-peptide in ICCs and elevated expressions of ICC marker genes. Our findings denoted that miR-365-3p targeted Pax6. Inhibition of Pax6 expression annulled the promotion of miR-365-3p downregulation on the differentiation of bMSCs into ICCs. Increased phosphorylation levels of MEK and ERK were identified in ICCs after downregulation of miR-365-3p however they were decreased after downregulation of Pax6. CONCLUSIONS: This study supported that miR-365-3p inhibited the differentiation of bMSCs into ICCs via targeting Pax6 and inhibiting the MEK/ERK pathway.

Arsenic trioxide inhibits breast cancer cell growth via microRNA-328/hERG pathway in MCF-7 cells.

Arsenic trioxide (As2O3) has been widely used in the treatment of acute promyelocytic leukemia and has been observed to exhibit therapeutic effects in various types of solid tumor. In a previous study by this group, it was shown that As2O3 induces the apoptosis of MCF-7 breast cancer cells through inhibition of the human ether-à-go-go-related gene (hERG) channel. The present study was designed to further investigate the effect of As2O3 on breast cancer cells and to examine the mechanism underlying the regulation of hERG expression. The present study confirmed that As2O3 inhibited tumor growth in vivo, following MCF-7 cell implantation into nude mice. Using computational prediction , it was identified that microRNA (miR)-328 had a binding site in the 3'-untranslated region of hERG mRNA. A luciferase activity assay demonstrated that hERG is a target gene of miR-328. Further investigation using western blot analysis and reverse transcription-quantitative polymerase chain reaction revealed that As2O3 downregulated hERG expression via upregulation of miR-328 expression in MCF-7 cells. In conclusion, As2O3 was observed to inhibit breast cancer cell growth, at least in part, through the miR-328/hERG pathway.