Omega-6支撑身体，Omega-3支撑大脑：均衡摄入对儿童大脑发育的影响（网络首发、推荐阅读）

人体大脑和身体的发育，需要从食物中摄取均衡的营养物质。人类大脑是区分人类和其他动物的特征。食物中的必需脂肪酸是机体组织结构和功能的必要组成部分。Omega-6（O6）亚油酸（LA6）是皮肤组织的组成成分，且是炎症、血栓形成、免疫和其他信号分子的前体；Omega-3（O3）α-亚麻酸（ALA3），特别是其长链代谢产物——二十二碳六烯酸（DHA3），是大脑、视网膜和部分神经组织中的关键组分。从富含LA6脂肪酸（缺乏O3脂肪酸）的植物籽中提取出的廉价而优质油脂，是20世纪的西方国家食品工业生产的主要脂肪来源。在代谢通路中，高浓度的LA6脂肪酸可拮抗O3脂肪酸代谢，造成O3脂肪酸不足，因此，在给怀孕动物的饲料中，只提供富含LA6但缺乏O3脂肪酸的油脂作为唯一的脂肪来源，会导致幼崽大脑发育不良。过去20~30年的研究表明，低含量LA6且含DHA3的油脂可改善大脑的功能。近年来的研究较多集中在营养因素对大脑发育的影响，最新研究数据表明，脂肪酸平衡对营养不良儿童的大脑发育尤为重要。世界卫生组织（WHO）越来越重视大脑的营养健康，通过其下属的食品法典委员会，建议用于治疗严重急性营养不良儿童的即食治疗食品中，使用含有均衡脂肪酸组成/构成的脂肪。同样，脂肪酸均衡对老年人可能也很重要。目前，业界已经有了调整油脂成分的方法，以确保脂肪酸均衡，从而维持人体整个生命周期的大脑健康。     

Red-shift and improved afterglow of Sr3Al2-xBxO5Cl2:Eu2+, Dy3+ phosphors via a cation substitution strategy

Sr₃Al_2-xB_xO₅Cl₂:Eu²⁺, Dy³⁺ (x = 0, 0.2, 0.4) long persistent phosphors were prepared via solid-state process. The pristine Sr₃Al₂O₅Cl₂:Eu²⁺, Dy³⁺ phosphor exhibits orange/red broad band emission around 609 nm, which can be attributed to the electric radiation transitions 4f⁶5 d¹→4f⁷ of Eu²⁺. Upon the same excitation, the B³⁺-doped Sr₃Al_2-xB_xO₅Cl₂:Eu²⁺, Dy³⁺ phosphors display red-shift from 609 nm to 625 nm with increasing B³⁺ concentrations. The XRD patterns show that Al³⁺ can be replaced by B³⁺ in the host lattice at the tetrahedral site, which causes lattice contraction and crystal field enhancement, and thereafter achieves the red-shift on the emission spectrum. The XPS investigation provides direct evidence of the dominant 2-valent europium in the phosphor, which can be ascribed for the broad band emission of the prepared phosphors. The afterglow of all phosphors show standard double exponential decay behavior, and the afterglow of Sr₃Al₂O₅Cl₂:Eu²⁺, Dy³⁺is rather weak, while the sample co-doped with B³⁺shows longer and stronger afterglow, as confirmed after the curve simulation. The analysis of thermally stimulated luminescence showed that, when B³⁺ is introduced, a much deeper trap is created, and the density of the electron trap is also significantly increased. As a result, B³⁺ ions caused redshift and enhanced afterglow for the Sr₃Al_2-xB_xO₅Cl₂:Eu²⁺, Dy³⁺ phosphor.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

3S技术应用现状与发展趋势

3S技术出现至今,已在诸多领域成功运用并产生了巨大的价值。文章简单介绍了3S三大组成部分:GIS、RS、GNSS的基本概念,分析了3S技术目前在农业、生态环境监测、土地资源管理以及智慧城市方面的应用现状以及对其在该方面未来的发展趋势进行展望。最后对目前3S在应用中遇到的一些问题进行了探讨,给未来3S技术的发展提供一些参考。     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

径向不耦合装药爆破效果的数值研究

为了研究径向不耦合条件下爆破效果的影响因素,利用AUTODYN-2D对比不耦合系数、不耦合介质、炸药种类对爆破效果的影响规律。结果表明,与耦合装药相比,径向不耦合装药条件下炮孔压力明显降低。对比水介质和空气介质下的爆破效果可知,水介质不耦合条件下,炸药爆炸能量的传递效率更高。炮孔压力与炸药种类密切相关,TNT产生的炮孔压力最大,但作用时间较短,而ANFO和乳化炸药的作用时间较长。     

2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.     

Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

建筑用钎焊合金的热腐蚀行为研究

研究了建筑用钎焊合金BCo46、DZ468和BNi-2在热腐蚀条件下的腐蚀行为。结果表明,在热腐蚀条件下,合金BCo46的抗腐蚀能力强于合金DZ468和BNi-2。3种合金在热腐蚀环境中都出现了硫化物析出和氧化薄膜溶解现象。