Mechanism of Exact Transition between Cationic and Anionic Redox Activities in Cathode Material Li2FeSiO4.

The discovery of anion redox activity is promising for boosting the capacity of lithium ion battery (LIB) cathodes. However, fundamental understanding of the mechanisms that trigger the anionic redox is still lacking. Here, using hybrid density functional study combined with experimental soft X-ray absorption spectroscopy (sXAS) measurements, we unambiguously proved that Li(2- x)FeSiO4 performs sequent cationic and anionic redox activity through delithiation. Specifically, Fe2+ is oxidized to Fe3+ during the first Li ion extraction per formula unit (f.u.), while the second Li ion extraction triggered the oxygen redox exclusively. Cationic and anionic redox result in electron and hole polaron states, respectively, explaining the poor conductivity of Li(2- x)FeSiO4 noted by previous experiments. In contrast, other cathode materials in this family exhibit diversity of the redox process. Li2MnSiO4 shows double cationic redox (Mn2+-Mn4+) during the whole delithiation, while Li2CoSiO4 shows simultaneous cationic and anionic redox. The present finding not only provides new insights into the oxygen redox activity in polyanionic compounds for rechargeable batteries but also sheds light on the future design of high-capacity rechargeable batteries

Efficacy of intravenous amphotericin B-polybutylcyanoacrylate nanoparticles against cryptococcal meningitis in mice

Amphotericin B deoxycholate (AmB), a classic antifungal drug, remains the initial treatment of choice for deep fungal infections, but it is not appropriate for treatment of cryptococcal meningitis due to its inability to pass through the blood–brain barrier (BBB). We examined the efficacy of amphotericin B-polybutylcyanoacrylate nanoparticles (AmB-PBCA-NPs) modified with polysorbate 80 that had a mean particle diameter less than 100 nanometers (69.0 ± 28.6 nm). AmB-PBCA-NPs were detected in the brain 30 minutes after systemic administration into BALB/c mice and had a higher concentration than systemically administered AmB liposome (AmB-L, P < 0.05); AmB was not detected in the brain. Following infection for 24 hours and then 7 days of treatment, the survival rate of mice in the AmB-PBCA-NP group (80%) was significantly higher than that of the AmB (0%) or AmB-L (60%) treatment groups. Fungal load was also lower when assessed by colony-forming unit counts obtained after plating infected brain tissue (P < 0.05). Our study indicates that AmB-PBCA-NPs with polysorbate 80 coating have the capacity to transport AmB across the BBB and is an efficient treatment against cryptococcal meningitis in a mouse model

RGD-conjugated gold nanorods induce radiosensitization in melanoma cancer cells by downregulating αvβ3 expression

Background: Melanoma is known to be radioresistant and traditional treatments have been intractable. Therefore, novel approaches are required to improve the therapeutic efficacy of melanoma treatment. In our study, gold nanorods conjugated with Arg-Gly-Asp peptides (RGD-GNRs) were used as a sensitizer to enhance the response of melanoma cells to 6 mV radiation. Methods and materials: A375 melanoma cells were treated by gold nanorods or RGD-GNRs with or without irradiation. The antiproliferative impact of the treatments was measured by MTT assay. Radiosensitizing effects were determined by colony formation assay. Apoptosis and cell cycle data were measured by flow cytometry. Integrin alpha(v)beta(3) expression was also investigated by flow cytometry. Results: Addition of RGD-GNRs enhanced the radiosensitivity of A375 cells with a dose-modifying factor of 1.35, and enhanced radiation-induced apoptosis. DNA flow cytometric analysis indicated that RGD-GNRs plus irradiation induced significant G2/M phase arrest in A375 cells. Both spontaneous and radiation-induced expressions of integrin alpha(v)beta(3) were downregulated by RGD-GNRs. Conclusion: Our study indicated that RGD-GNRs could sensitize melanoma A375 cells to irradiation. It was hypothesized that this was mainly through downregulation of radiation-induced alpha(v)beta(3), in addition to induction of a higher proportion of cells within the G2/M phase. The combination of RGD-GNRs and radiation needs further investigation.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000302718200001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Nanoscience &amp; NanotechnologyPharmacology &amp; PharmacySCI(E)22ARTICLE915-924

Super-resolution hyper-spectral imaging for the direct visualization of local bandgap heterogeneity

Optical hyperspectral imaging based on absorption and scattering of photons at the visible and adjacent frequencies denotes one of the most informative and inclusive characterization methods in material research. Unfortunately, restricted by the diffraction limit of light, it is unable to resolve the nanoscale inhomogeneity in light-matter interactions, which is diagnostic of the local modulation in material structure and properties. Moreover, many nanomaterials have highly anisotropic optical properties that are outstandingly appealing yet hard to characterize through conventional optical methods. Therefore, there has been a pressing demand in the diverse fields including electronics, photonics, physics, and materials science to extend the optical hyperspectral imaging into the nanometer length scale. In this work, we report a super-resolution hyperspectral imaging technique that simultaneously measures optical absorption and scattering spectra with the illumination from a tungsten-halogen lamp. We demonstrated sub-5 nm spatial resolution in both visible and near-infrared wavelengths (415 to 980 nm) for the hyperspectral imaging of strained single-walled carbon nanotubes (SWNT) and reconstructed true-color images to reveal the longitudinal and transverse optical transition-induced light absorption and scattering in the SWNTs. This is the first time transverse optical absorption in SWNTs were clearly observed experimentally. The new technique provides rich near-field spectroscopic information that had made it possible to analyze the spatial modulation of band-structure along a single SWNT induced through strain engineering.Comment: 4 Figure

QTLs and candidate genes analyses for fruit size under domestication and differentiation in melon (Cucumis melo L.) based on high resolution maps

Background: Melon is a very important horticultural crop produced worldwide with high phenotypic diversity. Fruit size is among the most important domestication and differentiation traits in melon. The molecular mechanisms of fruit size in melon are largely unknown. Results: Two high-density genetic maps were constructed by whole-genome resequencing with two F2 segregating populations (WAP and MAP) derived from two crosses (cultivated agrestis × wild agrestis and cultivated melo × cultivated agrestis). We obtained 1,871,671 and 1,976,589 high quality SNPs that show differences between parents in WAP and MAP. A total of 5138 and 5839 recombination events generated 954 bins in WAP and 1027 bins in MAP with the average size of 321.3 Kb and 301.4 Kb respectively. All bins were mapped onto 12 linkage groups in WAP and MAP. The total lengths of two linkage maps were 904.4 cM (WAP) and 874.5 cM (MAP), covering 86.6% and 87.4% of the melon genome. Two loci for fruit size were identified on chromosome 11 in WAP and chromosome 5 in MAP, respectively. An auxin response factor and a YABBY transcription factor were inferred to be the candidate genes for both loci. Conclusion: The high-resolution genetic maps and QTLs analyses for fruit size described here will provide a better understanding the genetic basis of domestication and differentiation, and provide a valuable tool for map-based cloning and molecular marker assisted breeding.info:eu-repo/semantics/publishedVersio

DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning

We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-turn question answering abilities, domain text processing capabilities, mathematical computation skills, and retrieval-enhanced generation capabilities. We build a financial instruction-tuning dataset named DISC-FIN-SFT, including instruction samples of four categories (consulting, NLP tasks, computing and retrieval-augmented generation). Evaluations conducted on multiple benchmarks demonstrate that our model performs better than baseline models in various financial scenarios. Further resources can be found at https://github.com/FudanDISC/DISC-FinLLM.Comment: 18 pages, 13 figures, 7 table

Accommodation capacity evaluation of renewable energy in power systems considering peak and frequency regulation

With the fast growth of renewable energy, the modern power systems are transitioning to the renewable energy dominated energy systems. However, the intrinsic intermittence and volatility of renewable energy also impose considerable challenges on the power system operation. Hence, it is of great significance to accurately evaluate the renewable energy accommodation capacity (REAC) in power system so as to effectively instruct the sustainable development of renewable energy and to alleviate the ongoing operational burdens. This paper proposes a novel evaluation method of REAC in power system comprehensively considering peak and frequency regulation. First, the mechanism and cost of deep peak regulation of thermal power units are deeply analyzed, and then the frequency dynamics response is modeled explicitly and simplified effectively. Next, a synthetic interaction model of “source-network-storage” is developed with diversified generation units, network and energy storage constraints. Furthermore, a multi-objective optimization model is established considering both economic and technical issues, and a REAC evaluation method is developed by integrating an incremental capacity augment approach with the proposed multi-objective model. Finally, the proposed REAC evaluation method is tested on the modified IEEE 39-bus system, and the numerical results verify the effectiveness of the proposed method

Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

Background: Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism. Results: In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse. Conclusions: The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies