Uncovering Atomic‐Scale Stability and Reactivity in Engineered Zinc Oxide Electrocatalysts for Controllable Syngas Production

In this study, scalable, flame spray synthesis is utilized to develop defective ZnO nanomaterials for the concurrent generation of H₂ and CO during electrochemical CO₂ reduction reactions (CO₂RR). The designed ZnO achieves an H₂/CO ratio of ≈1 with a large current density (j) of 40 mA cm^?2 during long‐term continuous reaction at a cell voltage of 2.6 V. Through in situ atomic pair distribution function analysis, the remarkable stability of these ZnO structures is explored, addressing the knowledge gap in understanding the dynamics of oxide catalysts during CO₂RR. Through optimization of synthesis conditions, ZnO facets are modulated which are shown to affect reaction selectivity, in agreement with theoretical calculations. These findings and insights on synthetic manipulation of active sites in defective metal‐oxides can be used as guidelines to develop active catalysts for syngas production for renewable power‐to‐X to generate a range of fuels and chemicals.     

Complications of nonionizing radiofrequency on divided attention

Exposure to electromagnetic fields is considered as a potential hazard for biological systems. The objective of our investigation is the study of probable consequences of radiofrequency electromagnetic fields from Wi-Fi router devices on the short-term memory, and attention's levels. A population consisting of 312 female college students (14 to 17 years old) was elected by cluster random sampling. Teenagers were divided into two groups of control group (Wi-Fi nonusers; n = 138), and experiment group (Wi-Fi users; n = 174). Both groups have been examined using short-term memory tests; selective attention, and also divided attention tests. According to the results, there was no significant difference between using Wi-Fi router devices on levels of selective attentions and short-term memory of the sample students with the control group. However, analyses revealed that there is a significant correlation between the use of Wi-Fi routers and declining levels of divided attentions. Our investigation has demonstrated the adverse consequences of 2.4-2.48 GHz radiofrequency electromagnetic fields of Wi-Fi router devices on divided attention levels of female university students that should be mentioned as a technological risk factor and taken into account by healthcare organizations.     

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients

OBJECTIVES

This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.

METHODS

Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.

RESULTS

CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.

CONCLUSIONS

DSC-MRI is highly repeatable in high-grade glioma patients.     

Molecular and morphological evaluation of transgenic Persian walnut plants harboring Fld gene under osmotic stress condition

Molecular Biology Reports - Soil drought stress is a limiting factor of productivity in walnut (Juglans regia L). Ferredoxin (Fd) level decreases under adverse environmental stress. Functional...     

A deletion containing a CTCF-element in intron 8 of the Bbs7 gene is partially responsible for juvenile obesity in the Berlin Fat Mouse

Mammalian Genome - The Berlin Fat Mouse Inbred (BFMI) line is a model for juvenile obesity. Previous studies on crosses between BFMI and C57Bl/6N (B6N) have identified a recessive defect causing...     

The architecture of gene regulatory variation across multiple human tissues: the MuTHER study

While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis--MCTA) permits immediate replication of eQTLs using co-twins (93%-98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%-20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.     

Next-generation sequencing to generate interactome datasets

Next-generation sequencing has not been applied to protein-protein interactome network mapping so far because the association between the members of each interacting pair would not be maintained in en masse sequencing. We describe a massively parallel interactome-mapping pipeline, Stitch-seq, that combines PCR stitching with next-generation sequencing and used it to generate a new human interactome dataset. Stitch-seq is applicable to various interaction assays and should help expand interactome network mapping.     

Predicting final extent of ischemic infarction using artificial neural network analysis of multi-parametric MRI in patients with stroke

In hemispheric ischemic stroke, the final size of the ischemic lesion is the most important correlate of clinical functional outcome. Using a set of acute-phase MR images (Diffusion-weighted - DWI, T₁-weighted – T1WI, T₂-weighted-T2WI, and proton density weighted - PDWI) for inputs, and the chronic T2WI at 3 months as an outcome measure, an Artificial Neural Network (ANN) was trained to predict the 3-month outcome in the form of a voxel-by-voxel forecast of the chronic T2WI. The ANN was trained and tested using 12 subjects (with 83 slices and 140218 voxels) using a leave-one-out cross-validation method with calculation of the Area Under the Receiver Operator Characteristic Curve (AUROC) for training, testing and optimization of the ANN. After training and optimization, the ANN produced maps of predicted outcome that were well correlated (r = 0.80, p<0.0001) with the T2WI at 3 months for all 12 patients. This result implies that the trained ANN can provide an estimate of 3-month ischemic lesion on T2WI in a stable and accurate manner (AUROC = 0.89).