Synthesis, In Vitro, In Vivo and In Silico Antidiabetic Bioassays of 4-Niztro(thio)phenoxyisobutyric Acids Acting as Unexpected PPARγ Modulators: An In Combo Study

Four isobutyric acids (two nitro and two acetamido derivatives) were prepared in two steps and characterized using spectral analysis. The mRNA concentrations of PPARγ and GLUT-4 (two proteins documented as key diabetes targets) were increased by 3T3-L1 adipocytes treated with compounds 1–4, but an absence of in vitro expression of PPARα was observed. Docking and molecular dynamics studies revealed the plausible interaction between the synthesized compounds and PPARγ. In vivo studies established that compounds 1–4 have antihyperglycemic modes of action associated with insulin sensitization. Nitrocompound 2 was the most promising of the series, being orally active, and one of multiple modes of action could be selective PPARγ modulation due to its extra anchoring with Gln-286. In conclusion, we demonstrated that nitrocompound 2 showed strong in vitro and in vivo effects and can be considered as an experimental antidiabetic candidate.

qEEG Analysis in the Diagnosis of Alzheimers Disease; a Comparison of Functional Connectivity and Spectral Analysis

Alzheimers disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients brains are in a phase-locked state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimers detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.

Trends, periodicities and ENSO relationship of New Zealand rainfall

The rainfall series for six homogeneous regions of New Zealand for 1901-1996 were not well intercorrelated (maximum correlation +0.6). Rainfalls were almost equally spread in all months. Trends (total changes over about 90 years) were ~0, +11, +2, -6, +1, +8 (±~4)% for the six regions. For seasonal rainfall, large trends were -19% for DJF and +16% for MAM of region 1. Spectral analysis showed peaks in QBO (Quasi-biennial oscillations, 2-3 years) range and near 3, 4-5, 6-9, 10-11 years and higher periodicities. ENSO relationships were not clear-cut. In individual El Niño events, only the very strong events of 1972-73, 1982-83 and 1997-98 were associated with widespread droughts in New Zealand, while the 1940-41 El Niño event was associated with excess rainfall. During the durations of all other El Niño events, New Zealand rainfalls were excess or deficit for a few months, followed by deficit or excess for the next few months (oscillatory nature), similar in all regions in some events, dissimilar in others, with no preference for any season. During La Niña (anti-El Niño) events also, oscillations were observed.

Identification of Vehicle System Dynamics from the Aspect of Interaction between the Steering and the Suspension Systems

Steering and suspension systems of a motor vehicle have very important mutual connections that have direct influence on a vehicle’s steerability, stability, comfort and life expectancy. These mechanical and functional couplings cause an intensive interaction between the two mentioned vehicle systems on a geometrical, kinematical and dynamical level. This article presents a study on nonparametric identification of dynamic interaction between the steering and the suspension system of a passenger vehicle. A specific methodology for experimental research in on-road conditions was designed that was in line with the research objectives and the applied measuring system. Experimental data were acquired for a curvilinear drive, with different constant driving speeds and on different roads. A multiple input/multiple output model for identification of the vehicle dynamics system from the aspect of interaction between the steering and the suspension system was developed. The analysis of experimental data was realized with the selection of a corresponding identification model, decoupling of model inputs and conditioned spectral analysis. The results of the conditioned spectral analysis of experimentally obtained data records indicate the level of interaction between the observed input and output parameters of the steering and the suspension systems to be in the frequency range below 30 Hz.