In continuation of the series of perovskite oxides that includes 3d4 cubic BaFeO3 and 4d4 cubic BaRuO3, 5d4 cubic BaOsO3 was synthesized by a solid-state reaction at a pressure of 17 GPa, and its ...crystal structure was investigated by synchrotron powder X-ray diffraction measurements. In addition, its magnetic susceptibility, electrical resistivity, and specific heat were measured over temperatures ranging from 2 to 400 K. The results establish a series of d4 cubic perovskite oxides, which can help in the mapping of the itinerant ferromagnetism that is free from any complication from local lattice distortions for transitions from the 3d orbital to the 5d orbital. Such a perovskite series has never been synthesized at any d configuration to date. Although cubic BaOsO3 did not exhibit long-range ferromagnetic order unlike cubic BaFeO3 and BaRuO3, enhanced feature of paramagnetism was detected with weak temperature dependence. Orthorhombic CaOsO3 and SrOsO3 show similar magnetic behaviors. CaOsO3 is not as conducting as SrOsO3 and BaOsO3, presumably due to impact of tilting of octahedra on the width of the t 2g band. These results elucidate the evolution of the magnetism of perovskite oxides not only in the 5d system but also in group 8 of the periodic table.
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IJS, KILJ, NUK, PNG, UL, UM
For the beneficial utilization of food waste (FW), valorization processes that output high-value products including carbon source alternatives for biological nutrient removal, biochar, or ...refuse-derived fuels (RDF) are reported to be technically and economically beneficial, while the climate change impact of these emerging valorization technologies is unclear and lacks a benchmark for comparison. In this study, the climate change impacts of six diverse valorization scenarios for FW were evaluated through a life cycle assessment and compared with that of incineration and anaerobic digestion (AD). Six valorization scenarios all exhibit better climate change benefits than incineration (−40.8 kgCO2-eq/t), and hydrolysis for the carbon source alternatives production coupled with thermal drying-RDF scenario and thermal drying-RDF scenario achieves the best (−276.8 kgCO2-eq/t) and the second-best (−224.2 kgCO2-eq/t) climate change benefits beyond AD with digestate incineration (−149.1 kgCO2-eq/t). Sensitivity analysis implies that the diverse total solid content of FW, biodrying efficiency, hydrolysis efficiency, dewatering efficiency, and energy efficiency of biomass power plants are key parameters affecting the global warming potential results. This study provided the data basis and insight for estimating the climate change relating to FW valorization decision-making.
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Ionic evolution–induced phase transformation can lead to wide ranges of novel material functionalities with promising applications. Here, using the gating voltage during ionic liquid gating as a ...tuning knob, the brownmillerite SrCoO2.5 is transformed into a series of protonated HxSrCoO2.5 phases with distinct hydrogen contents. The unexpected electron to charge‐neutral doping crossover along with the increase of proton concentration from x = 1 to 2 suggests the formation of exotic charge neutral H–H dimers for higher proton concentration, which is directly visualized at the vacant tetrahedron by scanning transmission electron microscopy and then further supported by first principles calculations. Although the H–H dimers cause no change of the valency of Co2+ ions, they result in clear enhancement of electronic bandgap and suppression of magnetization through lattice expansion. These results not only reveal a hydrogen chemical state beyond anion and cation within the complex oxides, but also suggest an effective pathway to design functional materials through tunable ionic evolution.
An ionic liquid gating strategy is proposed, and then a series of HxSrCoO2.5 phases with distinct hydrogen contents is discovered. The unexpected electron to charge‐neutral doping crossover suggests the formation of exotic H–H dimers for higher hydrogen concentration, which is directly visualized at the vacant tetrahedron of the lattice by scanning transmission electron microscopy and supported by theoretical calculations.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Urban forest diversity is the cornerstone of providing ecosystem services and improving urban environment. However, the spatial pattern of urban forest (UF) diversity and its driving mechanisms are ...still not well understood. In our study, using 330 UF sample plots and the corresponding plot-based standard deviation values of remote sensing parameters with different spatial resolutions, we developed prediction models for the spatial pattern of UF diversity, and the driving factors of UF diversity were further explored in our study. Our findings indicated that the 3-m spatial resolution of remote sensing was optimal for predicting UF diversity. Both excessively high and excessively low resolutions can increase misclassification errors. In addition, among the three prediction models, the boosted regression trees (BRT) model exhibited greater robustness than the support vector machine (SVM) and random forest (RF) models for predicting UF diversity. UF species were abundant, with 112 tree species in Changchun City. Spatially, the UF diversity showed a significant gradient decreasing trend from suburban areas (outer rings) to downtown areas. We also observed higher diversity in the older communities with high housing prices, supporting the “legacy effect and luxury effect”. Additionally, our research revealed that socioeconomic factors, landscape cover, and patterns collectively explained 41.25% of the UF diversity variation, wherein socioeconomic factors contributed the most variation (17.33%). We further found that UF diversity does not increase more with increasing house prices when the house prices are higher than ¥ 12,000/m2. The higher patch density reduced UF diversity, while a higher UF landscape shape index (LSI) promoted diversity. The LSI threshold, which significantly impacted UF diversity, was about 12. Our research showed that high-resolution remote sensing offers a rapid, cost-effective approach to acquire UF diversity patterns, which could enhance urban forest diversity and contribute to sustainable urban development.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Prunus armeniaca Lam. is the dominant species in the wild fruit forest in the Tianshan Mountains and has important values of ecology and resource. The altitude of wild fruit forest is closely linked ...to its distribution and growth. To clarify the changes of flowering phenological period and floral organs of P. armeniaca in different altitudes, the P. armeniaca forest in Tuergenxinghuagou, Xinyuan County, Xinjiang was selected as the research region from March to April 2021. In the mountainous area of 1000-1500 m with concentrated distribution of P. armeniaca, the sample plots were set up at the altitude gradient of I-V grade from low to high. We monitored the environmental conditions, and investigated the flowering phenological period and floral organ development characteristics of P. armeniaca population. The results showed that:（1） the flowering phenological period of P. armeniaca population lasted about 32 d, and the longest difference of each altitude gradient was 2 d. There was no significant difference in flowering phenological period between the grade I and grade Ⅱ, and there were significant differences between other altitude gradients. The last flowering grade V was 9 d later than the earliest flowering grade I, but the flowering phenological period of the P. armeniaca population was 4 d. The altitude was significantly positively correlated with the flowering phenological period, while temperature was significantly negatively correlated with flowering phenological period;（2） The sepalled length and width, ovary height and width of P. armeniaca were the largest at grade II; corolla diameter, petal longitudinal diameter and transverse diameter were the largest in grade I, while the anther length and width were the largest in grade IV; the style length was the largest in grade V. Altitude was significantly negatively correlated with the external organs and pistils of flowers, and positively correlated with the stamens. Light intensity was significantly negatively correlated with the external organs and pistils of flowers;（3） Climatic factors for the flowering period of P. armeniaca, with significant differences between grade IV, grade V and grade I. Altitude gradient and humidity, light intensity showed significantly positive correlation, altitude gradient and temperature showed significantly negative correlation. The flowering phenological period of P. armeniaca population in Xinjiang lasted about 32 d. As altitude rises, light intensity increases, temperature decreases and humidity increases in P. armeniaca woodlands. The flowering phenological period of P. armeniaca was delayed, and the flowering period increases in duration, with each 100m rise delaying flowering by about 1.8 d; the development of stamens gradually increased, and the development of external organs of pistils and flowers gradually decreased, which was the adaptability of P. armeniaca to altitude changes. The results can provide a theoretical basis for the study on the adaptability of P. armeniaca population distribution.
The high-pressure angle-dispersive X-ray diffraction experiments on the iron-based superconductor Nd(O0.88F0.12)FeAs were performed up to 32.7 GPa at room temperature. An isostructural phase ...transition starts at ∼10 GPa. When pressure is higher than 13.5 GPa, Nd(O0.88F0.12)FeAs completely transforms to a high-pressure phase, which remains the same tetragonal structure with a larger a-axis and smaller c-axis than those of the low-pressure phase. The ambient conditions isothermal bulk moduli B 0 are derived as 102(2) and 245(9) GPa for the low-pressure phase and high-pressure phase, respectively. The structure analysis based on the Rietveld refinement methods shows the difference of pressure dependence of the Fe−As and Nd−(O, F) bonding distances, as well as As−Fe−As and Nd−(O, F)−Nd angles between the low-pressure phase and high-pressure phase.
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N-myc downstream-regulated gene 2 (NDRG2), a novel tumour suppressor and cell stress-related gene, is involved in many cell metabolic processes, such as hormone, ion and fluid metabolism. We ...investigated whether NDRG2 is involved in any glucose-dependent energy metabolism, as well as the nature of its correlation with breast carcinoma.
The correlations between NDRG2 expression and glucose transporter 1 (GLUT1) expression in clinical breast carcinoma tissues were analysed. The effects of NDRG2 on glucose uptake were assessed in breast cancer cells and xenograft tumours. The consequences of NDRG2-induced regulation of GLUT1 at the transcription and translation levels and the interaction between NDRG2 and GLUT1 were examined.
Data derived from clinical breast carcinoma specimens revealed that (1) patients with high NDRG2 expression had better disease-free survival and overall survival than those with low NDRG2 expression and (2) NDRG2 expression was negatively correlated with GLUT1 expression in these breast carcinoma tissues. NDRG2 inhibited glucose uptake by promoting GLUT1 protein degradation without affecting GLUT1 transcription in both breast cancer cells and xenograft tumours. In addition, NDRG2 protein interacted and partly colocalised with GLUT1 protein in cell cytoplasm areas.
The results of our study support the notion that NDRG2 plays an important role in tumour glucose metabolism, in which GLUT1 is a likely candidate contributor to glucose uptake suppression and tumour growth. Targeting the actions of NDRG2 in cell glucose-dependent energy delivery may provide an attractive strategy for therapeutic intervention in human breast carcinoma.
The global prevalence of diabetes is steadily increasing, with a high percentage of patients unaware of their disease status. Screening for diabetes is of great significance in preventive medicine ...and may benefit from deep learning technology. In traditional Chinese medicine, specific features on the ocular surface have been explored as diagnostic indicators for systemic diseases. Here we explore the feasibility of using features from the entire ocular surface to construct deep learning models for risk assessment and detection of type 2 diabetes (T2DM). We performed an observational, multicenter study using ophthalmic images of the ocular surface to develop a deep convolutional network, OcularSurfaceNet. The deep learning system was trained and validated with a multicenter dataset of 416580 images from 67151 participants and tested independently using an additional 91422 images from 12544 participants, and can be used to identify individuals at high risk of T2DM with areas under the receiver operating characteristic curve (AUROC) of 0.89–0.92 and T2DM with AUROC of 0.70–0.82. Our study demonstrated a qualitative relationship between ocular surface images and T2DM risk level, which provided new insights for the potential utility of ocular surface images in T2DM screening. Overall, our findings suggest that the deep learning framework using ocular surface images can serve as an opportunistic screening toolkit for noninvasive and low-cost large-scale screening of the general population in risk assessment and early identification of T2DM patients.
Highlights
Phenotypes of ocular surface can be used for accurate, non-invasive, affordable T2DM risk assessment.
Ocular surface phenotypes associated with T2DM risk preliminarily elucidated by the neural network OcularSurfaceNet.
It has potential for generalized high-impact application in T2DM screening for large-scale population.
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