Functional Inactivation of Drosophila GCK Orthologs Causes Genomic Instability and Oxidative Stress in a Fly Model of MODY-2

Maturity-onset diabetes of the young (MODY) type 2 is caused by heterozygous inactivating mutations in the gene encoding glucokinase (GCK), a pivotal enzyme for glucose homeostasis. In the pancreas GCK regulates insulin secretion, while in the liver it promotes glucose utilization and storage. We showed that silencing the Drosophila GCK orthologs Hex-A and Hex-C results in a MODY-2-like hyperglycemia. Targeted knock-down revealed that Hex-A is expressed in insulin producing cells (IPCs) whereas Hex-C is specifically expressed in the fat body. We showed that Hex-A is essential for insulin secretion and it is required for Hex-C expression. Reduced levels of either Hex-A or Hex-C resulted in chromosome aberrations (CABs), together with an increased production of advanced glycation end-products (AGEs) and reactive oxygen species (ROS). This result suggests that CABs, in GCK depleted cells, are likely due to hyperglycemia, which produces oxidative stress through AGE metabolism. In agreement with this hypothesis, treating GCK-depleted larvae with the antioxidant vitamin B6 rescued CABs, whereas the treatment with a B6 inhibitor enhanced genomic instability. Although MODY-2 rarely produces complications, our data revealed the possibility that MODY-2 impacts genome integrity.     

Epitaxial Growth of 2D Materials on High-Index Substrate Surfaces

Recently, the successful synthesis of wafer-scale single-crystal graphene, hexagonal boron nitride (hBN), and MoS₂ on transition metal surfaces with step edges boosted the research interests in synthesizing wafer-scale 2D single crystals on high-index substrate surfaces. Here, using hBN growth on high-index Cu surfaces as an example, a systematic theoretical study to understand the epitaxial growth of 2D materials on various high-index surfaces is performed. It is revealed that hBN orientation on a high-index surface is highly dependent on the alignment of the step edges of the surface as well as the surface roughness. On an ideal high-index surface, well-aligned hBN islands can be easily achieved, whereas curved step edges on a rough surface can lead to the alignment of hBN along with different directions. This study shows that high-index surfaces with a large step density are robust for templating the epitaxial growth of 2D single crystals due to their large tolerance for surface roughness and provides a general guideline for the epitaxial growth of various 2D single crystals.     

Determinants of the intention to use non-medical insertable digital devices: The case of Chile and Colombia

In the past, thinking of carrying electronic devices inside our bodies was only posed by non-real scenarios. The emergence of insertable devices has changed this. Since this technology is still in its initial development stages, few studies have investigated factors that influence its acceptance. This paper analyzes the predictors of the intention to use non-medical insertable devices in two Latin American contexts. We used partial least squares structural equation modeling to examine whether six constructs predicted intention to use insertable devices. A questionnaire was administered to undergraduate students located in Colombia and Chile (n = 672). We also examined whether these predictors influenced intention differently for both of them. Four common constructs significantly and positively influenced both Chilean and Colombian respondents to use insertable devices (hedonic motivation, habit, performance expectancy, and social influence). Also, the habit has a complementary mediating effect on the relationship between social influence and behavioral intention. By contrast, effort expectations were a positive and significant predictor, but only among Chilean respondents. Findings suggest that when technologies are emerging, well-known predictors of intention (e.g., performance and effort expectations) are less influential than predictors related to self-efficacy (e.g., habit and hedonic motivation). The use of insertable devices has a significant impact on society. Thus, a better understanding of what motivates their use has implications for both academia and industry.     

Estimates of daily oxygen consumption,carbon dioxide and methane emissions,and heat production for beef and dairy cattle using spot gas sampling

A simulation study was conducted to examine accuracy of estimating daily O₂ consumption, CO₂ and CH₄ emissions, and heat production (HP) using a spot sampling technique and to determine optimal spot sampling frequency (FQ). Data were obtained from 3 experiments where daily O₂ consumption, emissions of CO₂ and CH₄, and HP were measured using indirect calorimetry (respiration chamber or headbox system). Experiment 1 used 8 beef heifers (ad libitum feeding; gaseous exchanges measured every 30 min over 3 d in respiration chambers); Experiment 2 used 56 lactating Holstein-Friesian cows (restricted feeding; gaseous exchanges measured every 12 min over 3 d in respiration chambers); Experiment 3 used 12 lactating Jersey cows (ad libitum feeding; gaseous exchanges measured every hour for 1 d using headbox style chambers). Within experiment, averages of all measurements (FQALL) and averages of measurements selected at time points with 12, 8, 6, or 4 spot sampling FQ (i.e., sampling every 2, 3, 4, and 6 h in a 24-h cycle, respectively; FQ12, FQ8, FQ6, and FQ4, respectively) were compared. Within study a mixed model was used to compare gaseous exchanges and HP among FQALL, FQ12, FQ8, FQ6, and FQ4, and an interaction of dietary treatment by FQ was examined. A regression model was used to evaluate accuracy of spot sampling within study [i.e., FQALL (observed) vs. FQ12, FQ8, FQ6, or FQ4 (estimated)]. No interaction of diet by FQ was observed for any variables except for CH₄ production in experiment 1. No FQ effect was observed for gaseous exchanges and HP except in experiment 2 where CO₂ production was less (5,411 vs. 5,563 L/d) for FQ4 compared with FQALL, FQ12, and FQ8. A regression analysis between FQALL and each FQ within study showed that slopes and intercepts became farther from 1 and 0, respectively, for almost all variables as FQ decreased. Most variables for FQ12 and FQ8 had root mean square prediction error (RMSPE) less than 10% of the mean and concordance correlation coefficient (CCC) greater than 0.80, and RMSPE increased and CCC decreased as FQ decreased. When a regression analysis was conducted with combined data from the 3 experiments (mixed model with study as a random effect), results agreed with those from the analysis for the individual studies. Prediction errors increased and CCC decreased as FQ decreased. Generally, all the estimates from FQ12, FQ8, FQ6, and FQ4 had RMSPE less than 10% of the means and CCC greater than 0.90 except for FQ6 and FQ4 for O₂ consumption and CH₄ production. In conclusion, the spot sampling simulation with 3 indirect calorimetry experiments indicated that FQ of at least 8 samples (every 3 h in a 24-h cycle) was required to estimate daily O₂ consumption, CO₂ and CH₄ production, and HP and to detect changes in those in response to dietary treatments. This sampling FQ may be considered when using techniques that measure spot gas exchanges such as the GreenFeed and face mask systems.     

Effect of nickel concentration on biohydrogen production: Organic solid waste vs. glucose

In recent years, alternative renewable energy generation sources have been investigated, highlighting the dark fermentation process due to it’s potential to obtain hydrogen-rich gas, which can be used as an energy source. Different trace metals intervene in this biological process. Nickel is one of the most important because it is a component of the [Ni–Fe] hydrogenase enzyme that catalyzes the oxidation of H₂ in numerous bacteria. The aim of this study was to evaluate the effect of nickel on biohydrogen production from organic solid waste (OSW). The experimental setup was carried out in batch tests using OSW as the substrate, glucose as a reference compound and the valuation of Ni²⁺ doses on the operation in a Sequencing Batch Reactor. The results of the batch tests showed that when using glucose as a substrate, 2 mg Ni²⁺/g VS_inoculum generated the highest hydrogen production (774 ± 7.3 mL H₂/L/d) and highest yield (55.8 ± 3.4 mL H₂/g of glucose), which was 34.4% higher than the control. Testing of different concentrations of nickel using OSW as a carbon source showed that the highest production was obtained without Ni²⁺ addition since the nickel concentration in the residue was 0.17 ± 0.06 mgNi/gVS; consequently, hydrogen production was not affected by the lack of Ni. The addition of 0.5 mg Ni²⁺/g VS_inoculum decreased acetate and butyrate production and increased caproate production.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Hydrogen production by supercritical water gasification of lignin over CuO–ZnO catalyst synthesized with different methods

In this study, lignin was gasified in supercritical water with catalysis of CuO–ZnO synthesized by deposition precipitation, co-precipitation and sol-gel methods. Sol-gel synthesized CuO–ZnO showed the highest catalytic performance, and the gasification efficiency was increased by 37.92% with it. The XRD, SEM-EDS and N₂ adsorption/desorption analysis showed that the priority of the sol-gel catalyst was the smallest crystallite size, largest specific surface area and high dispersion. For sol-gel synthesized CuO–ZnO, the increase of CuO/ZnO ratio improved the gasification efficiency but reduced H₂ selectivity. And the catalytic activity was reduced with the calcination temperature above 600 °C due to enlarged crystallites and reduced pores. During sol-gel preparation, both the addition of ethanol and PEG in the solvent reduced the agglomeration and improved the catalytic activity. With CuO–ZnO prepared with 1 g PEG + water as the solvent, the highest H₂ yield of 6.86 mol/kg was obtained, which was over 1.5 times of that without catalyst.     

Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process

Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.     

Graphitic-C3N4/ZnCr-layered double hydroxide 2D/2D nanosheet heterojunction: Mesoporous photocatalyst for advanced oxidation of azo dyes with in situ produced H2O2

In this study the constructional modification of Graphitic carbon nitride nanosheet (GCN-ns) has been made with the aid of ZnCr layered double hydroxide (ZC-LDH) in a unique 2D-2D structure to enhance its visible light absorption. Optical and morphological study presents successful incorporation of ZC-LDH on the surface of GCN-ns. Through adjusting of GCN-ns by ZC-LDH lower recombination rate of e^?/h⁺ pairs, longer lifetimes and an increase in contamination reduction was brought out. The binary nanocomposite was employed to effectively degrade Rhodamine B under UV/vis light irradiation. The improvement in photocatalytic abilities was proven to be related to in situ self-production of H₂O₂ on GCN-ns/ZC-LDH surface by Xe light irradiation which in return accounts for additional hydroxide radical generation. Radical quenching experiments specified the main active species involved while the consequent step-scheme (S-scheme) charge transfer mechanism was proposed.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.