In-Situ Formation of Holmium Oxide in Pores of Mesoporous Carbon Nanoparticles as Substrates for Neutron-Activatable Radiotherapeutics.

Radionuclide therapy with nano-sized carriers is a very promising approach to treat various types of cancer. The preparation of radioactive nanocarriers can be achieved with minimum handling using a neutron-activation approach. However, the nanocarrier material must possess certain characteristics such as low density, heat-resistance, high metal adsorption, easy surface modification and low toxicity in order to be useful. Mesoporous Carbon Nanoparticles (MCNs) in which holmium oxide is formed in their pores by a wet-impregnation process are investigated as a suitable material for this application. Holmium (165Ho) has a natural abundance of 100% and possesses a large cross-section for capturing thermal neutrons. After irradiation of Ho-containing MCNs in a neutron flux, 166Ho, which emits therapeutic high energy beta particles as well as diagnostic low energy gamma photons that can be imaged externally, is produced. The wet impregnation process (16 w/w% Ho loading) is shown to completely prevent the leaching of radioactive holmium from the MCNs without compromising their structural integrity. In vitro studies showed that the MCNs containing non-radioactive holmium do not exhibit toxicity and the same formulation with radioactive holmium (166Ho) demonstrated a tumoricidal effect. Post-irradiation PEGylation of the MCN surfaces endows dispersibility and biocompatibility.

[Effects of nitrogen fertilizer application rate on nitrogen use efficiency and grain yield and quality of different rice varieties]. / æ°®è‚¥æ°´å¹³å¯¹ä¸åŒåŸºå› åž‹æ°´ç¨»æ°®ç´ åˆ©ç”¨çŽ‡ã€äº§é‡å’Œå“è´¨çš„å½±å“.

To provide scientific basis for reasonable application of nitrogen and create varieties with high N use-efficiency, an experiment was carried out to study the effects of nitrogen fertilizer application rate on grain yield, N use rate and quality of different rice varieties. Four different genotypic rice varieties, Nipponbare, N70, N178 and OM052 were used as tested material and three levels of nitrogen application rate (0, 120, 270 kg·hm-2) were conducted. Urea as nitrogen source was applied as basal (70%) and panicle (30%) fertilizer. The results showed that nitrogen fertilizer could raise yield mainly because of the increased effective panicles and filled grains per panicle. When the N application rate was 120 and 270 kg·hm-2, OM052 had the largest grain yield among four varieties, being 41.1% and 76.8% higher, respectively compared with control. Difference in grain yield among four varieties was due to the difference of nitrogen use efficiency. Under 120 and 270 kg·hm-2 nitrogen levels, Nipponbare had the lowest grain yield and N agronomic efficiency (NAE, 40.90 g·g-1 and 18.56 g·g-1), which was a variety with low N use-efficiency. On the contrary, OM052 had the highest grain yield and NAE (145.9 g·g-1 and 81.24 g·g-1), was a variety with high N use-efficiency. N fertilizer application increased the amylose content and protein content, lengthened gel consistency, reduced chalky kernel, chalkiness, and alkali digestion value. With the increase of N fertilizer application, hot paste viscosity, peak viscosity, consistence viscosity and breakdown viscosity were decreased gradually, and setback viscosity was increased. Correlation analysis showed that the yield and yield components had more significant correlations with appearance quality, cooking and eating quality under low N level. This study confirmed that OM052 was a double high variety with extremely high N agronomic efficiency and yield. Reasonable application of nitrogen fertilizer could significantly increase effective panicles and filled grains per panicle, improve rice quality, and ensure high yield and superior quality simultaneously.

Robust determination of surface relaxivity from nuclear magnetic resonance DT(2) measurements.

Nuclear magnetic resonance (NMR) is a powerful tool to probe into geological materials such as hydrocarbon reservoir rocks and groundwater aquifers. It is unique in its ability to obtain in situ the fluid type and the pore size distributions (PSD). The T1 and T2 relaxation times are closely related to the pore geometry through the parameter called surface relaxivity. This parameter is critical for converting the relaxation time distribution into the PSD and so is key to accurately predicting permeability. The conventional way to determine the surface relaxivity ρ2 had required independent laboratory measurements of the pore size. Recently Zielinski et al. proposed a restricted diffusion model to extract the surface relaxivity from the NMR diffusion-T2 relaxation (DT2) measurement. Although this method significantly improved the ability to directly extract surface relaxivity from a pure NMR measurement, there are inconsistencies with their model and it relies on a number of preset parameters. Here we propose an improved signal model to incorporate a scalable LT and extend their method to extract the surface relaxivity based on analyzing multiple DT2 maps with varied diffusion observation time. With multiple diffusion observation times, the apparent diffusion coefficient correctly describes the restricted diffusion behavior in samples with wide PSDs, and the new method does not require predetermined parameters, such as the bulk diffusion coefficient and tortuosity. Laboratory experiments on glass beads packs with the beads diameter ranging from 50 µm to 500 µm are used to validate the new method. The extracted diffusion parameters are consistent with their known values and the determined surface relaxivity ρ2 agrees with the expected value within ±7%. This method is further successfully applied on a Berea sandstone core and yields surface relaxivity ρ2 consistent with the literature.

Dehydration of Ions in Voltage-Gated Carbon Nanopores Observed by in Situ NMR.

Ion transport through nanochannels is of fundamental importance in voltage-gated protein ion channels and energy storage devices. Direct microscopic observations are critical for understanding the intricacy of ionic processes in nanoconfinement. Here we report an in situ nuclear magnetic resonance study of ion hydration in voltage-gated carbon nanopores. Nucleus-independent chemical shift was employed to monitor the ionic processes of NaF aqueous electrolyte in nanopores of carbon supercapacitors. The state of ion hydration was revealed by the chemical shift, which is sensitive to the hydration number. A large energy barrier was observed for ions to enter nanopores smaller than the hydrated ion size. Increasing the gating voltage above 0.4 V overcomes this barrier and brings F(-) into the nanopores without dehydration. Partial dehydration of F(-) occurs only at gating voltage above 0.7 V. No dehydration was observed for Na(+) cations, in agreement with their strong ion hydration.

Electroneutrality breakdown and specific ion effects in nanoconfined aqueous electrolytes observed by NMR.

Ion distribution in aqueous electrolytes near the interface plays a critical role in electrochemical, biological and colloidal systems, and is expected to be particularly significant inside nanoconfined regions. Electroneutrality of the total charge inside nanoconfined regions is commonly assumed a priori in solving ion distribution of aqueous electrolytes nanoconfined by uncharged hydrophobic surfaces with no direct experimental validation. Here, we use a quantitative nuclear magnetic resonance approach to investigate the properties of aqueous electrolytes nanoconfined in graphitic-like nanoporous carbon. Substantial electroneutrality breakdown in nanoconfined regions and very asymmetric responses of cations and anions to the charging of nanoconfining surfaces are observed. The electroneutrality breakdown is shown to depend strongly on the propensity of anions towards the water-carbon interface and such ion-specific response follows, generally, the anion ranking of the Hofmeister series. The experimental observations are further supported by numerical evaluation using the generalized Poisson-Boltzmann equation.