Cerebral small vessel disease burden is associated with poststroke depressive symptoms: A 15-month prospective study

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients with acute ischemic stroke were followed over a 15-month period after the index stroke. A score of _7 on the 15-item Geriatric Depression Scale was defined as clinically significant PDS. Scores of the four SVD markers ascertained on magnetic resonance imaging were summed up to represent total SVD burden. The association between SVD burden and PDS was assessed with generalized estimating equation models. Results: The study sample had a mean age of 67.0 _ 10.2 years and mild-moderate stroke [National Institutes of Health Stroke Scale score: 3, interquartile, 1–5]. PDS were found in 18.3%, 11.6%, and 12.3% of the sample at 3, 9, and 15 months after stroke, respectively. After adjusting for demographic characteristics, vascular risk factors, social support, stroke severity, physical and cognitive functions, and size and locations of stroke, the SVD burden was associated with an increased risk of PDS [odds ratio = 1.30; 95% confidence interval = 1.07–1.58; p = 0.010]. Other significant predictors of PDS were time of assessment, female sex, smoking, number of acute infarcts, functional independence, and social support. Conclusion: SVD burden was associated with PDS examined over a 15-month follow-up in patients with mild to moderate acute ischemic stroke

Sharp Generalized Seiffert Mean Bounds for Toader Mean

For p∈[0,1], the generalized Seiffert mean of two positive numbers a and b is defined by Sp(a,b)=p(a-b)/arctan[2p(a-b)/(a+b)],  00 with a≠b, and give new bounds for the complete elliptic integrals of the second kind. Here, T(a,b)=(2/π)∫0π/2a2cos⁡2θ+b2sin⁡2θdθ denotes the Toader mean of two positive numbers a and b

Shifts of Hydrogen Metabolism From Methanogenesis to Propionate Production in Response to Replacement of Forage Fiber With Non-forage Fiber Sources in Diets in vitro

The rumen microbial complex adaptive mechanism invalidates various methane (CH4) mitigation strategies. Shifting the hydrogen flow toward alternative electron acceptors, such as propionate, was considered to be a meaningful mitigation strategy. A completely randomized design was applied in in vitro incubation to investigate the effects of replacing forage fiber with non-forage fiber sources (NFFS) in diets on methanogenesis, hydrogen metabolism, propionate production and the methanogenic and bacterial community. There are two treatments in the current study, CON (a basic total mixed ration) and TRT (a modified total mixed ration). The dietary treatments were achieved by partly replacing forage fiber with NFFS (wheat bran and soybean hull) to decrease forage neutral detergent fiber (fNDF) content from 24.0 to 15.8%, with the composition and inclusion rate of other dietary ingredients remaining the same in total mixed rations. The concentrations of CH4, hydrogen (H2) and volatile fatty acids were determined using a gas chromatograph. The archaeal and bacterial 16S rRNA genes were sequenced by Miseq high-throughput sequencing and used to reveal the relative abundance of methanogenic and bacterial communities. The results revealed that the concentration of propionate was significantly increased, while the concentration of acetate and the acetate to propionate ratio were not affected by treatments. Compared with CON, the production of H2 increased by 8.45% and the production of CH4 decreased by 14.06%. The relative abundance of Methanomassiliicoccus was significantly increased, but the relative abundance of Methanobrevibacter tended to decrease in TRT group. At the bacterial phylum level, the TRT group significantly decreased the relative abundance of Firmicutes and tended to increase the relative abundance of Bacteroidetes. The replacement of forage fiber with NFFS in diets can affect methanogenesis by shifting the hydrogen flow toward propionate, and part is directed to H2in vitro. The shift was achieved by a substitution of Firmicutes by Bacteroidetes, another substitution of Methanobrevibacter by Methanomassiliicoccus. Theoretical predictions of displacements of H2 metabolism from methanogenesis to propionate production was supported by the dietary intervention in vitro

Association of cerebral small vessel disease burden and health-related quality of life after acute ischemic stroke

Objective: Cerebral small vessel disease (SVD) is associated with increased mortality, disability and cognitive decline, depression in stroke survivors. This study examined the association between SVD burden, defined by a combination of SVD markers, and health-related quality of life (HRQoL) in acute ischemic stroke. Methods: Patients admitted with acute ischemic stroke of any etiology were prospectively screened between January 2010 to December 2014 and enrolled in the study if they met study entry criteria. HRQoL was evaluated with the 12-item Stroke Specific Quality of Life (SSQoL) at 3 months after the onset of acute ischemic stroke. SVD was ascertained by the presence of any of the SVD markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds (CMB) and enlarged perivascular spaces (EPVS) in the basal ganglia or their combinations on brain magnetic resonance imaging (MRI). The presence of each individual marker scored 1 point and was summed up to generate an ordinal “SVD score” (0–4) capturing total SVD burden. Linear regression was used to determine the associations between SVD burden and HRQoL. Results: Of the743 acute ischemic stroke patients that formed he study sample (mean age: 66.3 ± 10.6 years; 41.7% women), 49.3%, 22.5%, 16.0%, 9.2% and 3.1% had SVD scores of 0, 1, 2, 3 and 4, respectively. After adjusting for demographic, clinical and imaging variables, the SVD score was independently associated with lower overall score of SSQoL (B = − 1.39, SE = 0.56, p = 0.01), and its domains of mobility (B = − 0.41, SE = 0.10, p \u3c 0.001) and vision (B = − 0.12, SE = 0.06, p = 0.03). Acute infract volume (B = − 1.44, SE = 0.54, p = 0.01), functional independence (B = 5.69, SE = 0.34, p \u3c 0.001) and anxious (B = − 1.13, SE = 0.23, p \u3c 0.001) and depressive symptoms (B = − 3.41, SE = 0.22, p \u3c 0.001) were also the significant predictors of the overall score of SSQoL. Conclusion: The brain’s SVD burden predicts lower HRQoL, predominantly in domains of mobility and vision at 3 months after acute ischemic stroke. The evaluation of SVD burden could facilitate developing individual treatment strategies

Oxidative Stress Activates SIRT2 to Deacetylate and Stimulate Phosphoglycerate Mutase

Glycolytic enzyme phosphoglycerate mutase (PGAM) plays an important role in coordinating energy production with generation of reducing power and the biosynthesis of nucleotide precursors and amino acids. Inhibition of PGAM by small RNAi or small molecule attenuates cell proliferation and tumor growth. PGAM activity is commonly upregulated in tumor cells, but how PGAM activity is regulated in vivo remains poorly understood. Here we report that PGAM is acetylated at lysine 100 (K100), an active site residue that is invariably conserved from bacteria, to yeast, plant, and mammals. K100 acetylation is detected in fly, mouse, and human cells and in multiple tissues and decreases PGAM2 activity. The cytosolic protein deacetylase sirtuin 2 (SIRT2) deacetylates and activates PGAM2. Increased levels of reactive oxygen species stimulate PGAM2 deacetylation and activity by promoting its interaction with SIRT2. Substitution of endogenous PGAM2 with an acetylation mimetic mutant K100Q reduces cellular NADPH production and inhibits cell proliferation and tumor growth. These results reveal a mechanism of PGAM2 regulation and NADPH homeostasis in response to oxidative stress that impacts cell proliferation and tumor growth

Acetylation Targets the M2 Isoform of Pyruvate Kinase for Degradation through Chaperone-Mediated Autophagy and Promotes Tumor Growth

Most tumor cells take up more glucose than normal cells but metabolize glucose via glycolysis even in the presence of normal levels of oxygen, a phenomenon known as the Warburg effect. Tumor cells commonly express the embryonic M2 isoform of pyruvate kinase (PKM2) that may contribute to the metabolism shift from oxidative phosphorylation to aerobic glycolysis and tumorigenesis. Here we show that PKM2 is acetylated on lysine 305 and that this acetylation is stimulated by high glucose concentration. PKM2 K305 acetylation decreases PKM2 enzyme activity and promotes its lysosomal-dependent degradation via chaperone-mediated autophagy (CMA). Acetylation increases PKM2 interaction with HSC70, a chaperone for CMA, and association with lysosomes. Ectopic expression of an acetylation mimetic K305Q mutant accumulates glycolytic intermediates and promotes cell proliferation and tumor growth. These results reveal an acetylation regulation of pyruvate kinase and the link between lysine acetylation and CMA

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities