Roles of Fragile X Mental Retardation Protein in Dopaminergic Stimulation-induced Synapse-associated Protein Synthesis and Subsequent α-Amino-3-hydroxyl-5-methyl-4-isoxazole-4-propionate (AMPA) Receptor Internalization

Fragile X syndrome, the most common form of inherited mental retardation, is caused by the absence of the RNA-binding protein fragile X mental retardation protein (FMRP). FMRP regulates local protein synthesis in dendritic spines. Dopamine (DA) is involved in the modulation of synaptic plasticity. Activation of DA receptors can regulate higher brain functions in a protein synthesis-dependent manner. Our recent study has shown that FMRP acts as a key messenger for DA modulation in forebrain neurons. Here, we demonstrate that FMRP is critical for DA D1 receptor-mediated synthesis of synapse-associated protein 90/PSD-95-associated protein 3 (SAPAP3) in the prefrontal cortex (PFC). DA D1 receptor stimulation induced dynamic changes of FMRP phosphorylation. The changes in FMRP phosphorylation temporally correspond with the expression of SAPAP3 after D1 receptor stimulation. Protein phosphatase 2A, ribosomal protein S6 kinase, and mammalian target of rapamycin are the key signaling molecules for FMRP linking DA D1 receptors to SAPAP3. Knockdown of SAPAP3 did not affect surface expression of α-amino-3-hydroxyl-5-methyl-4-isoxazole-4-propionate (AMPA) GluR1 receptors induced by D1 receptor activation but impaired their subsequent internalization in cultured PFC neurons; the subsequent internalization of GluR1 was also impaired in Fmr1 knock-out PFC neurons, suggesting that FMRP may be involved in subsequent internalization of GluR1 through regulating the abundance of SAPAP3 after DA D1 receptor stimulation. Our study thus provides further insights into FMRP involvement in DA modulation and may help to reveal the molecular mechanisms underlying impaired learning and memory in fragile X syndrome.     

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province,China

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D²H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D²H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well.     

Triptolide Inhibited Cytotoxicity of Differentiated PC12 Cells Induced by Amyloid-Beta25–35 via the Autophagy Pathway

Evidence shows that an abnormal deposition of amyloid beta-peptide_25–35 (Aβ_25–35) was the primary cause of the pathogenesis of Alzheimer’s disease (AD). And the elimination of Aβ_25–35 is considered an important target for the treatment of AD. Triptolide (TP), isolated from Tripterygium wilfordii Hook.f. (TWHF), has been shown to possess a broad spectrum of biological profiles, including neurotrophic and neuroprotective effects. In our study investigating the effect and potential mechanism of triptolide on cytotoxicity of differentiated rat pheochromocytoma cell line (the PC12 cell line is often used as a neuronal developmental model) induced by Amyloid-Beta_25–35 (Aβ_25–35), we used 3-(4, 5-dimethylthiazol-2-yl)-2, 5- diphenyltetrazolium bromide (MTT) assay, flow cytometry, Western blot, and acridine orange staining to detect whether triptolide could inhibit Aβ_25–35–induced cell apoptosis. We focused on the potential role of the autophagy pathway in Aβ_25–35-treated differentiated PC12 cells. Our experiments show that cell viability is significantly decreased, and the apoptosis increased in Aβ_25–35-treated differentiated PC12 cells. Meanwhile, Aβ_25–35 treatment increased the expression of microtubule-associated protein light chain 3 II (LC3 II), which indicates an activation of autophagy. However, triptolide could protect differentiated PC12 cells against Aβ_25–35-induced cytotoxicity and attenuate Aβ_25–35-induced differentiated PC12 cell apoptosis. Triptolide could also suppress the level of autophagy. In order to assess the effect of autophagy on the protective effects of triptolide in differentiated PC12 cells treated with Aβ_25–35, we used 3-Methyladenine (3-MA, an autophagy inhibitor) and rapamycin (an autophagy activator). MTT assay showed that 3-MA elevated cell viability compared with the Aβ_25–35-treated group and rapamycin inhibits the protection of triptolide. These results suggest that triptolide will repair the neurological damage in AD caused by deposition of Aβ_25–35 via the autophagy pathway, all of which may provide an exciting view of the potential application of triptolide or TWHF as a future research for AD.     

Prevalence of Post-Stroke Cognitive Impairment in China: A Community-Based,Cross-Sectional Study

International hospital-based studies have indicated a high risk of cognitive impairment after stroke, evidence from community-based studies in China is scarce. To determine the prevalence of post-stroke cognitive impairment (PSCI) and its subtypes in stroke survivors residing in selected rural and urban Chinese communities, we conducted a community-based, cross-sectional study in 599 patients accounting for 48% of all stroke survivors registered in the 4 communities, who had suffered confirmed strokes and had undergone cognitive assessments via the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Hachinski Ischemia Scale (HIS). Detection of PSCI was based on scores in these neuropsychological scales. Factors potentially impacting on occurrence of PSCI were explored by comparing demographic characteristics, stroke features, and cardiovascular risk factors between patients with and without PSCI. The overall prevalence of PSCI was 80.97% (95%CI: 77.82%-84.11%), while that of non-dementia PSCI (PSCI-ND) and post-stroke vascular dementia (PSD) was 48.91% (95%CI: 44.91%-52.92%) and 32.05% (95%CI: 28.32%-35.79%), respectively. Prior stroke and complications during the acute phase were independent risk factors for PSCI. The risk of recurrent stroke survivors having PSCI was 2.7 times higher than for first-episode survivors, and it was 3 times higher for those with complications during the acute phase than for those without. The higher prevalence of PSCI in this study compared with previous Chinese studies was possibly due to the combined effects of including rural stroke survivors, a longer period from stroke onset, and different assessment methods. There is an urgent need to recognize and prevent PSCI in stroke patients, especially those with recurrent stroke and complications during the acute phase.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Estimating Mean First Passage Time of Biased Random Walks with Short Relaxation Time on Complex Networks

Biased random walk has been studied extensively over the past decade especially in the transport and communication networks communities. The mean first passage time (MFPT) of a biased random walk is an important performance indicator in those domains. While the fundamental matrix approach gives precise solution to MFPT, the computation is expensive and the solution lacks interpretability. Other approaches based on the Mean Field Theory relate MFPT to the node degree alone. However, nodes with the same degree may have very different local weight distribution, which may result in vastly different MFPT. We derive an approximate bound to the MFPT of biased random walk with short relaxation time on complex network where the biases are controlled by arbitrarily assigned node weights. We show that the MFPT of a node in this general case is closely related to not only its node degree, but also its local weight distribution. The MFPTs obtained from computer simulations also agree with the new theoretical analysis. Our result enables fast estimation of MFPT, which is useful especially to differentiate between nodes that have very different local node weight distribution even though they share the same node degrees.     

Preparation of capacitor’s electrode from sunflower seed shell

Series of nanoporous carbons are prepared from sunflower seed shell (SSS) by two different strategies and used as electrode material for electrochemical double-layer capacitor (EDLC). The surface area and pore-structure of the nanoporous carbons are characterized intensively using N₂ adsorption technique. The results show that the pore-structure of the carbons is closely related to activation temperature and dosage of KOH. Electrochemical measurements show that the carbons made by impregnation-activation process have better capacitive behavior and higher capacitance retention ratio at high drain current than the carbons made by carbonization-activation process, which is due to that there are abundant macroscopic pores and less interior micropore surface in the texture of the former. More importantly, the capacitive performances of these carbons are much better than ordered mesoporous carbons and commercial wood-based active carbon, thus highlighting the success of preparing high performance electrode material for EDLC from SSS.