The PKR/P38/RIPK1 Signaling Pathway as a Therapeutic Target in Alzheimer’s Disease

Neuropathological lesions in Alzheimer’s disease (AD) include amyloid plaques formed by the accumulation of amyloid peptides, neurofibrillary tangles made of hyperphosphorylated tau protein, synaptic and neuronal degenerations, and neuroinflammation. The cause of AD is unknown, but according to the amyloid hypothesis, amyloid oligomers could lead to the activation of kinases such as eukaryotic translation initiation factor 2-alpha kinase 2 (PKR), p38, and receptor-interacting serine/threonine-protein kinase 1 (RIPK1), which all belong to the same stress-activated pathway. Many toxic kinase activations have been described in AD patients and in experimental models. A p38 mitogen-activated protein kinase inhibitor was recently tested in clinical trials but with unsuccessful results. The complex PKR/P38/RIPK1 (PKR/dual specificity mitogen-activated protein kinase kinase 6 (MKK6)/P38/MAP kinase-activated protein kinase 2 (MK2)/RIPK1) is highly activated in AD brains and in the brains of AD transgenic animals. To delineate the implication of this pathway in AD, we carried out a search on PubMed including PKR/MKK6/p38/MK2/RIPK1, Alzheimer, and therapeutics. The involvement of this signaling pathway in the genesis of AD lesions, including Aβ accumulations and tau phosphorylation as well as cognitive decline, is demonstrated by the reports described in this review. A future combination strategy with kinase inhibitors should be envisaged to modulate the consequences for neurons and other brain cells linked to the abnormal activation of this pathway.     

An inverse Black–Scholes problem

Optimization and Engineering - In this work, we provide a new Black–Scholes model, where the weak formulation at stake is done in the case of a general class of finite Radon measures. A...     

Applying a normalized ratio scale technique to assess influences of urban expansion on land surface temperature of the semi-arid city of Erbil

The difference between surface and air temperature within a city and its surrounding area is a result of variations in surface cover, thermal capacity, and 3-dimensional geometry. This research has examined and quantified the decreasing daytime land surface temperature (LST) in Erbil, Kurdistan region of Iraq, and the influence of rapid urban expansion on urban heat/cool island effect over a 20 year period. Land-use/land-cover change across this time period is also established using pixel samples. The current study proposes the application of the normalized ratio scale (NRS) to adjust the temperature of images acquired at different dates to the same range. Eleven satellite images acquired by Landsat 4, 5, 7, and 8 during the period 1992–2013 are used to retrieve LST. The results indicate that 55.3 km² of city land cover changed from bare soil to urban; consequently, the mean LST of the new urbanized area decreased by 2.28°C. The normalized difference vegetation index (NDVI) of Sami Abdul-Rahman (S.A.) Park increased from 0.09 ± 0.01 to 0.32 ± 0.11, resulting in a decrease of the mean LST by 7.29°C. This study shows that the NRS method is appropriate for detecting temperature trends from urbanization using remote-sensing data. It also highlights that urban expansion may lead to a decrease in daytime LST in drylands.     

Cokriging-Based Sequential Design Strategies Using Fast Cross-Validation Techniques for Multi-Fidelity Computer Codes

Cokriging-based surrogate models have become popular in recent decades to approximate a computer code output from a few simulations using both coarse and more complex versions of the code. In practical applications, it is common to sequentially add new simulations to obtain more accurate approximations. We propose a method of cokriging-based sequential design, which combines both the error evaluation provided by the cokriging model and the observed errors of a leave-one-out cross-validation procedure. This method is proposed in two versions, the first one selects points one at a time. The second one allows us to parallelize the simulations and to add several design points at a time. The main advantage of the suggested strategies is that at a new design point they choose which code versions should be simulated (i.e., the complex code or one of its fast approximations). A multifidelity application is used to illustrate the efficiency of the proposed approaches. In this example, the accurate code is a two-dimensional finite element model and the less accurate one is a one-dimensional approximation of the system. This article has supplementary material online.     

Analysis of indoor particles and gases and their evolution with natural ventilation

The air composition and reactivity from outdoor and indoor mixing field campaign was conducted to investigate the impacts of natural ventilation (ie, window opening and closing) on indoor air quality. In this study, a thermal desorption aerosol gas chromatograph (TAG) obtained measurements of indoor particle‐ and gas‐phase semi‐ and intermediately volatile organic compounds both inside and outside a single‐family test home. Together with measurements from a suite of instruments, we use TAG data to evaluate changes in indoor particles and gases at three natural ventilation periods. Positive matrix factorization was performed on TAG and adsorbent tube data to explore five distinct chemical and physical processes occurring in the indoor environment. Outdoor‐to‐indoor transport is observed for sulfate, isoprene epoxydiols, polycyclic aromatic hydrocarbons, and heavy alkanes. Dilution of indoor species is observed for volatile, non‐reactive species including methylcyclohexane and decamethylcyclopentasiloxane. Window opening drives enhanced emissions of semi‐ and intermediately volatile species including TXIB, DEET, diethyl phthalate, and carvone from indoor surfaces. Formation via enhanced oxidation was observed for nonanal and 2‐decanone when outdoor oxidants entered the home. Finally, oxidative depletion of gas‐phase terpenes (eg, limonene and α‐pinene) was anticipated but not observed due to limited measurement resolution and dynamically changing conditions.     

Statistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behavior

In this paper, a strategy for multi-objective optimization based upon the behavior of a particle swarm with rotational and linear motion is presented. The strategy for multi-objective optimization is based upon the emulation of the linear and circular movements of a swarm (flock). Thus emerges the physical basis for the cognitive model, which in conjunction with exploration–exploitation results in the proposal of a cognitive algorithm, which is tested through several multi-objective optimization functions. The algorithm proposed is compared with standard particle swarm optimization multi-objective via statistical analysis.     

Policy conflicts in home automation

The nature of home automation is introduced. It is argued that end users should be able to define how the home system reacts to changing circumstances. Policies are employed as user-defined rules for how this should happen. The architecture of the Homer home automation system is briefly overviewed. The Homer policy system and the Homeric policy language it supports are explained. A technique is described for offline conflict analysis among policies (the analogue of the feature interaction problem). A substantial worked example shows how conflict detection is performed on a range of sample home policies.