Reliable Method for Fabricating Tissue‐Mimicking Materials With Designated Relative Permittivity and Conductivity at 128 MHz

Artificial materials that can simultaneously mimic the relative permittivity and conductivity of various human tissues are usually used in medical applications. However, the method of precisely designing these materials with designated values of both relative permittivity and conductivity at 3 T MRI resonance frequency is lacking. In this study, a reliable method is established to determine the compositions of artificial dielectric materials with designated relative permittivity and conductivity at 128 MHz. Sixty dielectric materials were produced using oil, sodium chloride, gelatin, and deionized water as the main raw materials. The dielectric properties of these dielectric materials were measured using the open‐ended coaxial line method at 128 MHz. Nonlinear least‐squares Marquardt–Levenberg algorithm was used to obtain the formula, establishing the relationship between the compositions of the dielectric materials and their dielectric properties at 128 MHz. The dielectric properties of the blood, gall bladder, muscle, skin, lung, and bone at 128 MHz were selected to verify the reliability of the obtained formula. For the obtained formula, the coefficient of determination and the expanded uncertainties with a coverage factor of k = 2 were 0.991% and 4.9% for relative permittivity and 0.992% and 6.4% for conductivity. For the obtained artificial materials measured using the open‐ended coaxial line method, the maximal difference of relative permittivity and conductivity were 1.0 and 0.02 S/m, respectively, with respect to the designated values. In conclusion, the compositions of tissue‐mimicking material can be quickly determined after the establishment of the formulas with the expanded uncertainties of less than 10%. Bioelectromagnetics. 2021;42:86–94. © 2020 Bioelectromagnetics Society.     

The Short‐Term Effect of Occupational Levels of 50 Hz Electromagnetic Field on Human Heart Rate Variability

Previous studies have indicated that there is no consensus on the effects of extremely low‐frequency electromagnetic (ELF‐EMF) exposure on the cardiovascular system. This study aimed to explore the short‐term effect of ELF‐EMF exposure on heart rate (HR) and HR variability (HRV). The sample consisted of 34 healthy males aged 18–27 years. The participants were randomly assigned to the EMF (n = 17) or the Sham group (n = 17). We employed a double‐blind repeated‐measures design consisting of three 5 min experimental periods. The chest region of each individual in the EMF group was exposed to 50 Hz, 28 μT, linear polarized, continuous EMF during the EMF exposure period. HR and HRV data were recorded continuously by using a photoplethysmography sensor. Within‐subject statistical analysis indicated a significant HR deceleration in both the EMF and Sham groups. However, the standard deviation of the NN intervals (SDNN), root mean square of successive differences (RMSSD), low‐frequency (LF), and high‐frequency (HF) powers increased only in the EMF group and remained stable in the Sham group. We also compared the same HRV indices measured during the EMF and Sham periods between the two experimental groups. The between‐subject analysis results demonstrated significantly higher SDNN, RMSSD, LF, and HF values in the EMF group than in the Sham group. The LF/HF ratio did not change significantly within and between groups. On the basis of these results, we concluded that short‐term exposure of the chest region to ELF‐EMF could potentially enhance parasympathetic predominance during the resting condition. Bioelectromagnetics. 2021;42:60–75. © 2020 Bioelectromagnetics Society.     

Membrane dynamics of γ‐secretase with the anterior pharynx‐defective 1B subunit

The four‐subunit protease complex γ‐secretase cleaves many single‐pass transmembrane (TM) substrates, including Notch and β‐amyloid precursor protein to generate amyloid‐β (Aβ), central to Alzheimer's disease. Two of the subunits anterior pharynx‐defective 1 (APH‐1) and presenilin (PS) exist in two homologous forms APH1‐A and APH1‐B, and PS1 and PS2. The consequences of these variations are poorly understood and could affect Aβ production and γ‐secretase medicine. Here, we developed the first complete structural model of the APH‐1B subunit using the published cryo‐electron microscopy (cryo‐EM) structures of APH1‐A (Protein Data Bank: 5FN2, 5A63, and 6IYC). We then performed all‐atom molecular dynamics simulations at 303 K in a realistic bilayer system to understand both APH‐1B alone and in γ‐secretase without and with substrate C83‐bound. We show that APH‐1B adopts a 7TM topology with a water channel topology similar to APH‐1A. We demonstrate direct transport of water through this channel, mainly via Glu84, Arg87, His170, and His196. The apo and holo states closely resemble the experimental cryo‐EM structures with APH‐1A, however with subtle differences: The substrate‐bound APH‐1B γ‐secretase was quite stable, but some TM helices of PS1 and APH‐1B rearranged in the membrane consistent with the disorder seen in the cryo‐EM data. This produces different accessibility of water molecules for the catalytic aspartates of PS1, critical for Aβ production. In particular, we find that the typical distance between the catalytic aspartates of PS1 and the C83 cleavage sites are shorter in APH‐1B, that is, it represents a more closed state, due to interactions with the C‐terminal fragment of PS1. Our structural‐dynamic model of APH‐1B alone and in γ‐secretase suggests generally similar topology but some notable differences in water accessibility which may be relevant to the protein's existence in two forms and their specific function and location.     

Ring‐opening of azetidiniums by nucleophiles. Synthesis of polysubstituted linear amines

This microreview focuses on the nucleophilic ring‐opening of azetidiniums presenting various substitution patterns at C2, C3, and C4. In most cases, the nucleophilic ring‐opening occurred in a stereoselective and regioselective fashion producing functionalized linear amines. Experimental selectivities associated with Density Functional Theory (DFT) calculations have allowed a better understanding of the parameters governing the regioselectivities.     

Revisiting the phosphotyrosine binding pocket of Fyn SH2 domain led to the identification of novel SH2 superbinders.

Protein engineering through directed evolution is an effective way to obtain proteins with novel functions with the potential applications as tools for diagnosis or therapeutics. Many natural proteins have undergone directed evolution in vitro in the test tubes in the laboratories worldwide, resulting in the numerous protein variants with novel or enhanced functions. we constructed here an SH2 variant library by randomizing 8 variable residues in its phosphotyrosine (pTyr) binding pocket. Selection of this library by a pTyr peptide led to the identification of SH2 variants with enhanced affinities measured by EC50. Fluorescent polarization was then applied to quantify the binding affinities of the newly identified SH2 variants. As a result, three SH2 variants, named V3, V13 and V24, have comparable binding affinities with the previously identified SH2 triple‐mutant superbinder. Biolayer Interferometry assay was employed to disclose the kinetics of the binding of these SH2 superbinders to the phosphotyrosine peptide. The results indicated that all the SH2 superbinders have two‐orders increase of the dissociation rate when binding the pTyr peptide while there was no significant change in their associate rates. Intriguingly, though binding the pTyr peptide with comparable affinity with other SH2 superbinders, the V3 does not bind to the sTyr peptide. However, variant V13 and V24 have cross‐reactivity with both pTyr and sTyr peptides. The newly identified superbinders could be utilized as tools for the identification of pTyr‐containing proteins from tissues under different physiological or pathophysiological conditions and may have the potential in the therapeutics.     

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression‐based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression‐like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.