10 research outputs found

    Synthesis, Optical and Electrical Properties of ZnFe2O4 Nanocomposites

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    ZnFe2O4 nanocomposites have been prepared by a simple co‐precipitation method. The prepared samples were characterized by Scanning Electron Microscopy (SEM), Powder X‐ray Diffraction (XRD), Energy Disperse X‐ray Analysis (EDX), Transmission electron microscopy (TEM) and UV‐visible absorption spectral techniques. Conductivity measurements show a transition from ferrimagnetism to paramagnetism. The enhancement in fluorescence spectra shows that there is an electronic transition to an exciting level. In UV‐Vis spectra, the peak observed at 647nm indicates ZnFe2O4 nanocomposites are a photoactive compound. The above results suggest that these nanomateria

    Minimal Hepatic Encephalopathy in Patients with Alcohol Related and Non-alcoholic Steatohepatitis Related Cirrhosis by Psychometric Hepatic Cephalopathy Score and Critical Flicker Frequency

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    Background: alcohol may have additional neurotoxic ill-effects in patients with alcohol related cirrhosis apart from hepatic encephalopathy. We aimed to evaluate minimal hepatic encephalopathy (MHE) with Psychometric Hepatic Encephalopathy (PHES) score and Critical Flicker Frequency (CFF) in alcohol (ALD) and non-alcoholic steatohepatitis related (NASH) related cirrhosis. Methods: 398 patients were screened between March 2016 and December 2018; of which 71 patients were included in ALD group and 69 in NASH group. All included patients underwent psychometric tests which included number connection test A and B (NCT-A and NCT-B), serial dot test (SDT), digit symbol test (DST), line tracing test (LTT) and CFF. MHE was diagnosed when their PHES was <-4. Results: the prevalence of MHE was significantly higher in ALD group compared to NASH (69.01% vs 40.58%; P=0.007). The performance of individual psychometric tests was significantly poorer in ALD (P<0.05). Overall sensitivity and specificity of CFF was 76.62% (95%CI 65.59 – 85.52) and 46.03% (95%CI 33.39 – 59.06) respectively. Mean CFF was significantly lower in ALD than NASH (37.07 (SD 2.37) vs 39.05 (SD 2.40), P=0.001); also in presence of MHE (36.95 (SD 2.04) vs 37.96 (SD 1.87), P=0.033) and absence of MHE (37.34 (SD 3.01) vs 39.79 (SD 2.46), P=0.001). Conclusion: MHE is significantly more common in patients with ALD cirrhosis than NASH counterparts. Overall CFF values are less in alcohol related cirrhosis than NASH related cirrhosis, even in presence or absence of MHE. We recommend additional caution in managing MHE in ALD cirrhosis

    Additional file 1 of Neuroinflammatory transcriptional programs induced in rhesus pre-frontal cortex white matter during acute SHIV infection

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    Additional file 1: Fig. S1. Ranked genes by median normalized read counts in units of Log2 counts per million (Log2CPM) in the subcortical white matter of the pre-frontal cortex (PFCw), and gray matter of the superior temporal sulcus (STS), caudate nucleus (CN), and hippocampus (HP) of uninfected animals. Dotted lines indicate location of marker genes associated with neurons (MAP2), astrocytes (GFAP), microglia (P2RY12), and oligodendrocytes (MOG) within ranked distribution. Fig. S2. T-stochastic neighborhood embedding analysis (t-SNE) of gene expression profiles from the pre-frontal cortex white matter (black), superior temporal sulcus (blue), caudate nucleus (red), and hippocampus (green) of uninfected animals. Outlier sample [Animal 43661 pre-frontal cortex white matter] is included. Symbols represent individual animals. Circles indicate 95% confidence intervals. Fig. S3. Regional eigengene expression and corresponding top fifteen most significantly enriched (p < 0.01 by Fisher’s exact test) biological processes GO terms within region specific modules (PFCw-specific [MEmagenta, MEmidnightblue], STS-specific [MEtan], CN-specific [MEpurple, MEred], HP-specific [MEsalmon]) determined by weighted gene co-expression network analysis from uninfected animals. *p < 0.05 by linear mixed effects model (region effect). Boxplots represent quartiles. Fig. S4. Normalized read counts of genes encoding for chemokines in the STS (blue), PFCw (black), CN (red), and HP (green) of uninfected animals. Expression levels are displayed in normalized read counts in units of Log2 counts per million (Log2CPM). Brackets indicate structural chemokine classes. Fig. S5. Log2 Fold change of genes regulating inflammatory processes and synaptic functions between SHIV infected and uninfected animals in all brain regions (gray), STS (blue), and PFCw (red). Dotted line indicates a fold change of 1. Fig. S6. T-stochastic neighborhood embedding (t-SNE) analysis of gene expression profiles from SHIV infected and uninfected animals. (Left) t-SNE plot indicates clustering of gene expression profiles by region and SHIV infection status (SHIV infected [pink], uninfected [black]) with removal of outlier sample [Animal 43661 Pre-frontal cortex white matter]. (Right) t-SNE plot shows all samples including the outlier with data points indicating regions (pre-frontal cortex white matter (P), superior temporal sulcus [S], caudate nucleus [C], hippocampus [H]) and infection status (color) and individual animals (symbols). Circles indicate 95% confidence intervals. Fig. S7 Expression levels of genes (expressed as normalized read counts in units of Log2 Counts per million [CPM]) related to synaptic functions, endoplasmic reticulum stress, and ATP synthase subunits in the PFCw of SHIV infected (red) and uninfected (gray) animals. Violin plots indicate quartiles. P values determined by linear mixed effects model. Table S1 Animal/Sample Data. Animal information—Animal ID, Sex, Age, SHIV infection status, and medical cull rationale. Sample Information—Sample ID, Sample Code, Tissue identity, Tissue weight (mg), purified RNA absorbance ratios (A260/A280 and A260/A230), and sample RNA yield. Table S3. Reagents used for flow cytometric analysis
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