Conspectus Magnetic nanomaterials (MNMs) have attracted significant interest in the past few decades because of their unique properties such as superparamagnetism, which results from the influence of ...thermal energy on a ferromagnetic nanoparticle. In the superparamagnetic size regime, the moments of nanoparticles fluctuate as a result of thermal energy. To understand the fundamental behavior of superparamagnetism and develop relevant potential applications, various preparation routes have been explored to produce MNMs with desired properties and structures. However, some challenges remain for the preparation of well-defined magnetic nanostructures, including exchange-coupled nanomagnets, which are considered as the next generation of advanced magnets. In such a case, effective synthetic methods are required to achieve control over the chemical composition, size, and structure of MNMs. For instance, liquid-phase chemical syntheses, a set of emerging approaches to prepare various magnetic nanostructures, facilitate precise control over the nucleation and specific growth processes of nanomaterials with diverse structures. Among them, the high-temperature organic-phase method is an indispensable one in which the microstructures and physical/chemical properties of MNMs can be tuned by controlling the reaction conditions such as precursor, surfactant, or solvent amounts, reaction temperature or time, reaction atmosphere, etc. In this Account, we present an overview of our progress on the chemical synthesis of various MNMs, including monocomponent nanostructures (e.g., metals, metal alloys, metal oxides/carbides) and multicomponent nanostructures (heterostructures and exchange-coupled nanomagnets). We emphasize the high-temperature organic-phase synthetic method, on which we have been focused over the past decade. Notably, multicomponent nanostructures, obtained by growing or incorporating different functional components together, not only retain the functionalities of each single component but also possess synergic properties that emerge from interfacial coupling, with improved magnetic, optical, or catalytic features. Herein, potential applications of MNMs are covered in three representative areas: biomedicine, catalysis, and environmental purification. Regarding biomedicine, MNMs can detect or target biological entities after being modified with specific biomolecules, and they can be applied to magnetic resonance imaging, imaging-guided drug delivery, and photothermal therapy. Apart from their magnetic features, the catalytic performance of some MNMs resulting from their highly specific chemical components and surface structure will be briefly introduced, highlighting its impact in the methanol oxidation reaction, the oxygen reduction reaction, the oxygen and hydrogen evolution reactions, and the Fischer–Tropsch synthesis. Finally, environmental purification, primarily for water remediation, will be highlighted with two main aspects: the effective capture of bacteria and the removal of adverse ions in wastewater. We hope that this Account will clarify the progress on the controllable preparation of MNMs with specific compositions, sizes, and structures and generate broad interest in the realms of biomedicine and catalysis as well as in environmental issues and other potential applications.
This study was performed to investigate the anti-diabetic effect of citrus pectin in type 2 diabetic rats and its potential mechanism of action. The results showed that fasting blood glucose levels ...were significantly decreased after 4 weeks of citrus pectin administration. Citrus pectin improved glucose tolerance, hepatic glycogen content and blood lipid levels (TG, TC, LDL-c and HDL-c) in diabetic rats. Citrus pectin also significantly reduced insulin resistance, which played an important role in the resulting anti-diabetic effect. Moreover, after the pectin treatment, phosphorylated Akt expression was upregulated and GSK3β expression was downregulated, indicating that the potential anti-diabetic mechanism of citrus pectin might occur through regulation of the PI3K/Akt signaling pathway. Together, these results suggested that citrus pectin could ameliorate type 2 diabetes and potentially be used as an adjuvant treatment.
Developing efficient and economical noble-metal free catalysts for oxygen reduction reaction (ORR) is one of the essential factors for the industrialization of fuel cells. Recent studies on ...transition metal ORR catalysts have become the priority to practical low-temperature fuel cells. Herein, we proposed a novel in situ design, Fe2N nanoparticles (NPs) in an N doped porous carbon matrix (Fe2N@NPC) derived from metal organic frameworks (MOFs) as high-performance ORR catalysts. The decorated Fe2N NPs increase the amount of Fe-N/C bonding as catalytic site. Meanwhile, the coated NPC facilitates the mass transport of the reaction and improves the conductivity simultaneously. The catalyst exhibits an onset potential of -0.038 V, a half-wave potential of -0.175 V in 0.1 M KOH, and superior stabilities and methanol tolerance performances to commercial Pt/C catalysts. More importantly, the proposed in situ 'two-step' annealing route provides potential possibilities for producing other non-precious metal catalysts for ORR.
Searching for working refrigerant materials is the key element in the design of magnetic cooling devices. Herein, we report on the thermodynamic and magnetocaloric parameters of an X 1 phase ...oxyorthosilicate, Gd2SiO5, by field-dependent static magnetization and specific heat measurements. An overall correlation strength of |J|S 2 ≈ 3.4 K is derived via the mean-field estimate, with antiferromagnetic correlations between the ferromagnetically coupled Gd–Gd layers. The magnetic entropy change −ΔS m is quite impressive, reaches 0.40 J K–1 cm–3 (58.5 J K–1 kg–1) at T = 2.7 K, with the largest adiabatic temperature change T ad = 23.2 K for a field change of 8.9 T. At T = 20 K, the lattice entropy S L is small enough compared to the magnetic entropy S m, S m/S L = 21.3, which warrants its potential in 2 −20 K cryocoolers with both the Stirling and Carnot cycles. Though with relatively large exchange interactions, the layered A-type spin arrangement ultimately enhances the magnetocaloric coupling, raising the possibilities of designing magnetic refrigerants with a high ratio of cooling capacity to volume.
Air pollution is a leading cause of human diseases. Accurate air quality predictions are critical to human health. However, it is difficult to extract spatiotemporal features among complex ...spatiotemporal dependencies effectively. Most existing methods focus on constructing multiple spatial dependencies and ignore the systematic analysis of spatial dependencies. We found that besides spatial proximity stations, functional similarity stations, and temporal pattern similarity stations, the shared spatial dependencies also exist in the complete spatial dependencies. In this paper, we propose a novel deep learning model, the spatiotemporal adaptive attention graph convolution model, for city-level air quality prediction, in which the prediction of future short-term series of PM2.5 readings is preferred. Specifically, we encode multiple spatiotemporal dependencies and construct complete spatiotemporal interactions between stations using station-level attention. Among them, we design a Bi-level sharing strategy to extract shared inter-station relationship features between certain stations efficiently. Then we extract multiple spatiotemporal features with multiple decoders, which it is extracted from the complete spatial dependencies between stations. Finally, we fuse multiple spatiotemporal features with a gating mechanism for multi-step predictions. Our model achieves state-of-the-art experimental results in several real-world datasets.
Searching for working refrigerant materials is the key element in the design of magnetic cooling devices. Herein, we report on the thermodynamic and magnetocaloric parameters of an
phase ...oxyorthosilicate, Gd
SiO
, by field-dependent static magnetization and specific heat measurements. An overall correlation strength of |
|
≈ 3.4 K is derived via the mean-field estimate, with antiferromagnetic correlations between the ferromagnetically coupled Gd-Gd layers. The magnetic entropy change -Δ
is quite impressive, reaches 0.40 J K
cm
(58.5 J K
kg
) at
= 2.7 K, with the largest adiabatic temperature change
= 23.2 K for a field change of 8.9 T. At
= 20 K, the lattice entropy
is small enough compared to the magnetic entropy
,
/
= 21.3, which warrants its potential in 2 -20 K cryocoolers with both the Stirling and Carnot cycles. Though with relatively large exchange interactions, the layered A-type spin arrangement ultimately enhances the magnetocaloric coupling, raising the possibilities of designing magnetic refrigerants with a high ratio of cooling capacity to volume.
Mastering the pattern of food loss caused by droughts and floods aids in planning the layout of agricultural production, determining the scale of drought and flood control projects, and reducing food ...loss. The Standardized Precipitation Evapotranspiration Index is calculated using monthly meteorological data from 1984 to 2020 in Shandong Province of China and is used to identify the province’s drought and flood characteristics. Then, food losses due to droughts and floods are estimated separately from disaster loss data. Finally, the relationship between drought/flood-related factors and food losses is quantified using methods such as the Pearson correlation coefficient and linear regression. The results show that: 1) there is a trend of aridity in Shandong Province, and the drought characteristic variables are increasing yearly while flood duration and severity are decreasing. 2) The food losses caused by droughts in Shandong Province are more than those caused by floods, and the area where droughts and floods occur frequently is located in Linyi City. 3) The impact of precipitation on food loss due to drought/flood is significant, followed by potential evapotranspiration and temperature. 4) The relationship between drought and flood conditions and food losses can be precisely quantified. The accumulated drought duration of one month led to 1.939 × 10
4
t of grain loss, and an increase in cumulative flood duration of one month resulted in 1.134 × 10
4
t of grain loss. If the cumulative drought severity and average drought peak increased by one unit, food loss due to drought will increase by 1.562 × 10
4
t and 1.511 × 10
6
t, respectively. If the cumulative flood severity and average flood peak increase by one unit, food loss will increase by 8.470 × 10
3
t and 1.034 × 10
6
t, respectively.
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•A self-healing current collector is obtained via combining EGaIn and 3D-Cu foam.•The formed self-healing graphite anode shows a specific capacity of 328 mA h g−1.•The self-healing ...graphite anode shows a retention of 94.2% after scratch damage.•The EGaIn@3D-Cu current collector could enhance cycling stability of electrode.
Traditional lithium-ion batteries are prone to cracks and perforations in extreme environments, which could cause electrochemical performance degradation or even safety problems. Here, based on the alloying reaction of liquid metal, through the adjustment of alloying temperature and reaction time, a uniform and stable dispersion of eutectic gallium indium liquid metal (EGaIn) on the surface and internal structure of the micro-etched 3D-Cu current collector (EGaIn@3D-Cu) is obtained. Furthermore, the graphite anode prepared with the EGaIn@3D-Cu current collector (the self-healing graphite anode) shows an excellent self-healing performance. Namely, the specific capacities of the self-healing graphite anode before and after scratch damage are 327.4 mA h g−1 and 309.6 mA h g−1, respectively, which is significantly better than that of the graphite anode assembled with 2D-Cu foil current collector. Therefore, the EGaIn@3D-Cu current collector prepared by a simple manufacturing process could effectively realizes the self-healing function, prevent the capacity degradation and improve the stability of the battery.
Health providers create Electronic Health Records (EHRs) to describe the conditions and procedures used to treat their patients. Medical notes entered by medical staff in the form of free text are a ...particularly insightful component of EHRs. There is a great interest in applying machine learning tools on medical notes in numerous medical informatics applications. Learning vector representations, or embeddings, of terms in the notes, is an important pre-processing step in such applications. However, learning good embeddings is challenging because medical notes are rich in specialized terminology, and the number of available EHRs in practical applications is often very small.
In this paper, we propose a novel algorithm to learn embeddings of medical terms from a limited set of medical notes. The algorithm, called definition2vec, exploits external information in the form of medical term definitions. It is an extension of a skip-gram algorithm that incorporates textual definitions of medical terms provided by the Unified Medical Language System (UMLS) Metathesaurus.
To evaluate the proposed approach, we used a publicly available Medical Information Mart for Intensive Care (MIMIC-III) EHR data set. We performed quantitative and qualitative experiments to measure the usefulness of the learned embeddings. The experimental results show that definition2vec keeps the semantically similar medical terms together in the embedding vector space even when they are rare or unobserved in the corpus. We also demonstrate that learned vector embeddings are helpful in downstream medical informatics applications.
This paper shows that medical term definitions can be helpful when learning embeddings of rare or previously unseen medical terms from a small corpus of specialized documents such as medical notes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Different gut microbiota is implicated in different diseases, including cancer. However, gut microbiota differences between individuals with clear cell renal cell carcinoma (ccRCC) and healthy ...individuals are unclear. Here, we analyzed gut microbiota composition in 51 ccRCC patients and 40 healthy controls using 16S rRNA sequencing analysis. We observed that
Blautia
,
Streptococcus
,
Ruminococcus_torques_group
,
Romboutsia
, and
Eubacterium_hallii_group
were dominant and positively associated with ccRCC. We isolated and cultured
Streptococcus lutetiensis
to characterize specific gut microbiota that promotes ccRCC and found that it promoted
in vitro
ccRCC proliferation, migration, and invasion
via
the TGF-signaling pathway. Interactions identified between the gut microbiota and ccRCC suggest the gut microbiota could serve as a potential non-invasive tool for predicting ccRCC risk and also function as a cancer therapy target.
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