Involvement of insulin-degrading enzyme in the clearance of beta-amyloid at the blood-CSF barrier: Consequences of lead exposure

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is characterized by the deposition of beta-amyloid (Aβ) peptides in the brain extracellular matrix, resulting in pathological changes and neurobehavioral deficits. Previous work from this laboratory demonstrated that the choroid plexus (CP) possesses the capacity to remove Aβ from the cerebrospinal fluid (CSF), and exposure to lead (Pb) compromises this function. Since metalloendopeptidase insulin-degrading enzyme (IDE), has been implicated in the metabolism of Aβ, we sought to investigate whether accumulation of Aβ following Pb exposure was due to the effect of Pb on IDE.</p> <p>Methods</p> <p>Rats were injected with a single dose of Pb acetate or an equivalent concentration of Na-acetate; CP tissues were processed to detect the location of IDE by immunohistochemistry. For <it>in vitro </it>studies, choroidal epithelial Z310 cells were treated with Pb for 24 h in the presence or absence of a known IDE inhibitor, N-ethylmaleimide (NEM) to assess IDE enzymatic activity and subsequent metabolic clearance of Aβ. Additionally, the expression of IDE mRNA and protein were determined using real time PCR and western blots respectively.</p> <p>Results</p> <p>Immunohistochemistry and confocal imaging revealed the presence of IDE towards the apical surface of the CP tissue with no visible alteration in either its intensity or location following Pb exposure. There was no significant difference in the expressions of either IDE mRNA or protein following Pb exposure compared to controls either in CP tissues or in Z310 cells. However, our findings revealed a significant decrease in the IDE activity following Pb exposure; this inhibition was similar to that seen in the cells treated with NEM alone. Interestingly, treatment with Pb or NEM alone significantly increased the levels of intracellular Aβ, and a greater accumulation of Aβ was seen when the cells were exposed to a combination of both.</p> <p>Conclusion</p> <p>These data suggest that Pb exposure inhibits IDE activity but does not affect its expression in the CP. This, in turn, leads to a disrupted metabolism of Aβ resulting in its accumulation at the blood-CSF barrier.</p

PAPR: Proximity Attention Point Rendering

Learning accurate and parsimonious point cloud representations of scene surfaces from scratch remains a challenge in 3D representation learning. Existing point-based methods often suffer from the vanishing gradient problem or require a large number of points to accurately model scene geometry and texture. To address these limitations, we propose Proximity Attention Point Rendering (PAPR), a novel method that consists of a point-based scene representation and a differentiable renderer. Our scene representation uses a point cloud where each point is characterized by its spatial position, foreground score, and view-independent feature vector. The renderer selects the relevant points for each ray and produces accurate colours using their associated features. PAPR effectively learns point cloud positions to represent the correct scene geometry, even when the initialization drastically differs from the target geometry. Notably, our method captures fine texture details while using only a parsimonious set of points. We also demonstrate four practical applications of our method: geometry editing, object manipulation, texture transfer, and exposure control. More results and code are available on our project website at https://zvict.github.io/papr/

Fine Tuning the Pore Surface in Zirconium Metal−Organic Frameworks for Selective Ethane/Ethylene Separation

Ethylene is an important chemical feedstock for production of polymers and high-value organic chemicals, and yet its conventional purification process is plagued with high consumption of energy. Metal−organic frameworks (MOFs) provide a suitable adsorption platform for selective ethane/ ethylene separation thanks to their structural diversity, tunable pore characteristics, designable pore sizes, and high pore volumes. Although there are empirical design rules like avoiding open metal sites and creating nonpolar pore surfaces for development of adsorptive MOFs, it is still challenging to design robust MOFs that can realize direct ethane-selective separation. Herein, we systematically designed and synthesized three Zr-MOFs based on the assembly of angular ligands and 12-connected Zr6 clusters that feature the pcu network structure. By changing the size and flexibility of the substituent on the angular ligand, we were able to prevent interpenetration and identified NPF-802, which exhibits good C2H6/C2H4 separation performance that is attributed to the bulky and inert tert-butyl groups of its carbazole ligand. This work provides insights for design of ligands of MOFs with suitable pore environments to address important and challenging gas separations

Driving mechanism for farmers' participation in improving farmland ecosystem: Evidence from China

peer reviewe

Disrupted Balance of Long- and Short-Range Functional Connectivity Density in Type 2 Diabetes Mellitus: A Resting-State fMRI Study

Previous studies have shown that type 2 diabetes mellitus (T2DM) can accelerate the rate of cognitive decline in patients. As an organ with high energy consumption, the brain network balances between lower energy consumption and higher information transmission efficiency. However, T2DM may modify the proportion of short- and long-range connections to adapt to the inadequate energy supply and to respond to various cognitive tasks under the energy pressure caused by homeostasis alterations in brain glucose metabolism. On the basis of the above theories, this study determined the abnormal functional connections of the brain in 32 T2DM patients compared with 32 healthy control (HC) subjects using long- and short-range functional connectivity density (FCD) analyses with resting-state fMRI data. The cognitive function level in these patients was also evaluated by neuropsychological tests. Moreover, the characteristics of abnormal FCD and their relationships with cognitive impairment were investigated in T2DM patients. Compared with the HC group, T2DM patients exhibited decreased long-range FCD in the left calcarine and left lingual gyrus and increased short-range FCD in the right angular gyrus and medial part of the left superior frontal gyrus (p &lt; 0.05, Gaussian random-field theory corrected). In T2DM patients, the FCD z scores of the medial part of the left superior frontal gyrus were negatively correlated with the time cost in part B of the Trail Making Test (ρ = -0.422, p = 0.018). In addition, the FCD z scores of the right angular gyrus were negatively correlated with the long-term delayed recall scores of the Auditory Verbal Learning Test (ρ = -0.356, p = 0.049) and the forward scores of the Digital Span Test (ρ = -0.373, p = 0.039). T2DM patients exhibited aberrant long-range and short-range FCD patterns, which may suggest brain network reorganization at the expense of losing the integration of long-range FCD to adapt to the deficiency in energy supply. These changes may be associated with cognitive decline in T2DM patients

3D Morphology of Open Clusters in the Solar Neighborhood with Gaia EDR 3. II. Hierarchical Star Formation Revealed by Spatial and Kinematic Substructures

We identify members of 65 open clusters in the solar neighborhood using the machine-learning algorithm StarGO based on Gaia EDR3 data. After adding members of 20 clusters from previous studies we obtain 85 clusters, and study their morphology and kinematics. We classify the substructures outside the tidal radius into four categories: filamentary (f1) and fractal (f2) for clusters 100 Myr. The kinematical substructures of f1-type clusters are elongated; these resemble the disrupted cluster Group X. Kinematic tails are distinct in t-type clusters, especially Pleiades. We identify 29 hierarchical groups in four young regions (Alessi 20, IC 348, LP 2373, LP 2442); 10 among these are new. The hierarchical groups form filament networks. Two regions (Alessi 20, LP 2373) exhibit global orthogonal expansion (stellar motion perpendicular to the filament), which might cause complete dispersal. Infalling-like flows (stellar motion along the filament) are found in UBC 31 and related hierarchical groups in the IC 348 region. Stellar groups in the LP 2442 region (LP 2442 gp 1–5) are spatially well mixed but kinematically coherent. A merging process might be ongoing in the LP 2442 subgroups. For younger systems (≲30 Myr), the mean axis ratio, cluster mass, and half-mass–radius tend to increase with age values. These correlations between structural parameters may imply two dynamical processes occurring in the hierarchical formation scenario in young stellar groups: (1) filament dissolution and (2) subgroup mergers

Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be improved by genomic selection (GS), which has become a practical and effective breeding tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought stress environments in northeast China. Adequate genetic variations were observed for all the target traits, but they were divergent across environments. Similarly, the heritability of the target trait also varied across years and environments, the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) were higher than those in 2020 (0.65, 0.53, 0.33) and cross-2-years (0.32, 0.26, 0.33). In total, three marker datasets, 11,865 SilicoDArT markers obtained from the DArT-seq platform, 7837 SNPs obtained from the DArT-seq platform, and 91,003 SNPs obtained from the GBS platform, were used for GS analysis after quality control. The results of phylogenetic trees showed that broad genetic diversity existed in the NCCP population. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the two-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For the trait with lower heritability, the prediction accuracy can be improved using the dataset filtered by linkage disequilibrium. For the same trait, the prediction accuracies estimated with two DArT marker datasets were consistently higher than that estimated with the GBS SNP dataset under the same genotyping cost. The prediction accuracy was improved by controlling population structure and marker quality, even though the marker density was reduced. The prediction accuracies were improved by more than 30% using the significant-associated SNPs. Due to the complexity of drought tolerance under the natural stress environments, multiple years of data need to be accumulated to improve prediction accuracy by reducing genotype-by-environment interaction. Modeling genotype-by-environment interaction into genomic prediction needs to be further developed for improving drought tolerance in maize. The results obtained from the present study provides valuable pathway for improving drought tolerance in maize using GS

生細胞における皮層アクチンフィラメントの動態と制御機構の解析

京都大学新制・課程博士博士(生命科学)甲第23334号生博第452号新制||生||60(附属図書館)京都大学大学院生命科学研究科統合生命科学専攻(主査)教授 永尾 雅哉, 教授 渡邊 直樹, 教授 安達 泰治学位規則第4条第1項該当Doctor of Philosophy in Life SciencesKyoto UniversityDGA

Dynamical Analysis of an Age-Structured SVEIR Model with Imperfect Vaccine

Based on the spread of COVID-19, in the present paper, an imperfectly vaccinated SVEIR model for latent age is proposed. At first, the equilibrium points and the basic reproduction number of the model are calculated. Then, we discuss the asymptotic smoothness and uniform persistence of the semiflow generated by the solutions of the system and the existence of an attractor. Moreover, LaSalle’s invariance principle and Volterra type Lyapunov functions are used to prove the global asymptotic stability of both the disease-free equilibrium and the endemic equilibrium of the model. The conclusion is that if the basic reproduction number Rρ is less than one, the disease will gradually disappear. However, if the number is greater than one, the disease will become endemic and persist. In addition, numerical simulations are also carried out to verify the result. Finally, suggestions are made on the measures to control the ongoing transmission of COVID-19