新型杂合四芳烯光控分子开关的设计合成与性能测试

围绕分子开关及聚集诱导发光的科研热点领域进行本科教学实验设计,将光致变色二芳烯巧妙嵌合于具有聚集诱导发光性能的四芳烯体系中,制备得到兼具变色和发光功能的新型杂合四芳烯光控荧光分子开关,科教融合,将科研前沿引入到本科实验教学。从物质的制备、分离提纯、结构表征和性能测试等方面进行了综合实验探索。本实验分子设计简练新颖,内容丰富,现象明显,在综合运用和巩固本科学习的基本理论和基本操作的基础上,激发学生的科研兴趣,培养团结协作和突破创新的科学精神。

Dietary sodium acetate and sodium butyrate improve high-carbohydrate diet utilization by regulating gut microbiota, liver lipid metabolism, oxidative stress, and inflammation in largemouth bass(Micropterus salmoides)

Background Adequate level of carbohydrates in aquafeeds help to conserve protein and reduce cost. However, studies have indicated that high-carbohydrate(HC) diet disrupt the homeostasis of the gut–liver axis in largemouth bass, resulting in decreased intestinal acetate and butyrate level.Method Herein, we had concepted a set of feeding experiment to assess the effects of dietary sodium acetate(SA) and sodium butyrate(SB) on liver health and the intestinal microbiota in largemouth bass fed an HC diet. The experimental design comprised 5 isonitrogenous and isolipidic diets, including LC(9% starch), HC(18% starch), HCSA(18% starch;2 g/kg SA), HCSB(18% starch;2 g/kg SB), and HCSASB(18% starch;1 g/kg SA + 1 g/kg SB). Juvenile largemouth bass with an initial body weight of 7.00 ± 0.20 g were fed on these diets for 56 d.Results We found that dietary SA and SB reduced hepatic triglyceride accumulation by activating autophagy(ATG101, LC3B and TFEB), promoting lipolysis(CPT1α, HSL and AMPKα), and inhibiting adipogenesis(FAS, ACCA, SCD1 and PPARγ). In addition, SA and SB decreased oxidative stress in the liver(CAT, GPX1α and SOD1) by activating the Keap1-Nrf2 pathway. Meanwhile, SA and SB alleviated HC-induced inflammation by downregulating the expression of pro-inflammatory factors(IL-1β, COX2 and Hepcidin1) through the NF-κB pathway. Importantly, SA and SB increased the abundance of bacteria that produced acetic acid and butyrate(Clostridium_sensu_stricto_1). Combined with the KEGG analysis, the results showed that SA and SB enriched carbohydrate metabolism and amino acid metabolism pathways, thereby improving the utilization of carbohydrates. Pearson correlation analysis indicated that growth performance was closely related to hepatic lipid deposition, autophagy, antioxidant capacity, inflammation, and intestinal microbial composition.Conclusions In conclusion, dietary SA and SB can reduce hepatic lipid deposition;and alleviate oxidative stress and inflammation in largemouth bass fed on HC diet. These beneficial effects may be due to the altered composition of the gut microbiota caused by SA and SB. The improvement effects of SB were stronger than those associated with SA.

磷化钴封装在磷富集的三维多孔碳及其双功能氧电催化性能研究

能源和环境问题是制约人类延续和发展的首要问题,高效便宜的能源存储和转换装置吸引着广泛注意。基于便携式,功率密度高,无污染等,可充放电锌-空气电池(ZAB)被大量研究。然而,阴极的氧还原(ORR)和氧析出反应(OER)缓慢的动力学限制了ZAB的实际应用。开发电催化高效,便宜,高稳定性的双功能电催化剂至关重要,而其中将过渡金属和碳基材料复合是明智的决定。磷化钴(Co_(2)P)化合物已经广泛研究用作高效的OER催化剂,但是对于催化剂的ORR活性很少研究。在此,本论文通过简单热处理钴盐和植酸掺杂的k-卡拉胶复合物制备出磷化钴封装在磷掺杂的多孔碳(Co_(2)P-PCA-800)纳米催化剂。该催化剂具有3D分级多孔结构,表现出具有与商用Pt/C相当的半波电位(E_(1/2)) 0.84 V,从而满足了可充放电锌-空电池需求。同时,我们还制备了磷掺杂的多孔碳(PCA)和钴掺杂的多空碳(Co-CA),对比了结构形貌对性能的影响。结果表明,具有完整的多孔结构,在每个位点的阻抗更一致,从而会有更多的有效活性位点。高效的ORR和OER活性主要归功于3D蜂窝分层多孔结构和正电荷磷化钴(Co_(2)P)纳米颗粒的协同作用。此外,蜂窝状3D孔结构不仅利于传质和加快电子传输也保护了磷化钴,让其更稳定。最后,我们组装了可充放电锌-空气电池用Co_(2)P-PCA-800作空气阴极催化剂。相比贵金属,该催化剂组装的ZAB具有接近的充放电性能和能量密度以及更高的比容量和更好的稳定性。这项工作也为解决能源和环境问题提供了新思路。

Bacteroides-derived isovaleric acid enhances mucosal immunity by facilitating intestinal IgA response in broilers

Background:The interaction between nutrition and immunity plays a vital role in nutrient digestion,absorption,and metabolism during poultry production.Recent studies showed that the gut microbiota contributes to the development of intestinal mucosal immunity.However,the mechanisms by which gut microbes regulate this process remain unclear.Methods:We compared the intestinal mucosal immunity and gut microbiota of Arbor Acre broilers AA(lower mucosal immunity)and Chinese native Wuliang Mountain Black-bone chickens(WLMB)(higher mucosal immunity)using 16S rDNA sequencing,transcriptomic analysis,and immunoglobulin A(IgA)antibody repertoire sequencing.We then combined 16S rDNA sequencing with transcriptomics to identify the key microbes and found that they were positively correlated with IgA production.Next,we transplanted candidate microbes into 1-day-old broiler to explore their role in intestinal mucosal immunity.Finally,we verified the function of candidate microbial metabolites in regulating the immune function of macrophages and the intestinal-epithelial cells(IECs)using in vitro experiments.Results:WLMB performs stronger mucosal immunity than AA,including higher IgA levels,more diverse IgA antibody repertoire,and higher bacterial affinity.Bacteroides was identified as the key microbes related to the intestinal IgA response.Bacteroides transplantation could increase IgA concentration in the duodenal contents by enhancing the expression of IgA,polymeric immunoglobin receptor(PIgR),B cell-activating factor of the TNF family(BAFF),and activation-induced cytidine deaminase(AID)in the duodenum.Additionally,Bacteroides-derived isovaleric acid promoted M2 macrophage polarization of macrophage via mTOR/PPAR-γ/STAT3 signaling pathways and regulated the immunologic function of IECs to produce cytokines,including interleukin(IL)-10,IL-4,BAFF,and transforming growth factor-beta(TGF-β),thus promoting IgA production in B cells by facilitating AID expression.Conclusion:Our study revealed that Bacteroides modulate the intestinal IgA response and maintain gut health in broilers.Bacteroides may be a promising alternative as an immunomodulatory microbial agent for developing nextgeneration probiotics for broiler production.

Serverless distributed learning for smart grid analytics

The digitization,informatization,and intelligentization of physical systems require strong support from big data analysis.However,due to restrictions on data security and privacy and concerns about the cost of big data collection,transmission,and storage,it is difficult to do data aggregation in real-world power systems,which directly retards the effective implementation of smart grid analytics.Federated learning,an advanced distributed learning method proposed by Google,seems a promising solution to the above issues.Nevertheless,it relies on a server node to complete model aggregation and the framework is limited to scenarios where data are independent and identically distributed.Thus,we here propose a serverless distributed learning platform based on blockchain to solve the above two issues.In the proposed platform,the task of machine learning is performed according to smart contracts,and encrypted models are aggregated via a mechanism of knowledge distillation.Through this proposed method,a server node is no longer required and the learning ability is no longer limited to independent and identically distributed scenarios.Experiments on a public electrical grid dataset will verify the effectiveness of the proposed approach.

The Spin Transition and Susceptibility of NMR Samples in a Time Dependent Longitudinal Field

To construct pulsed high magnet, with rapid adjustments to large changes in the field strength, it is a mandatory acces-sory to development a special NMR probes to provide a precise real-time map of the magnetic field. In order to do so, it is necessary to understand the variations of the spin transition and susceptibility of NMR samples in a time dependent longitudinal field. This work analyzes the effect on the spin transition by a time dependent longitudinal field. For a 1/2 spin system, we have derived a simple formula for the prediction of the probabilities of occupation of the 1/2 and ?1/2 states in a non-static field. We also calculate the magnetic susceptibility of the water and give an analysis of the effect on the magnetic susceptibility in a time dependent longitudinal field and RF frequency.

Oxygen vacancy-expedited ion diffusivity in transition-metal oxides for high-performance lithium-ion batteries

Rapid capacity decay and inferior kinetics are the vital issues of anodes in the conversion reaction for lithium-ion batteries.Vacancy engineering can efficiently modulate the intrinsic properties of transition-metal oxide(TMO)-based electrode materials,but the effect of oxygen vacancies on electrode performance remains unclear.Herein,abundant oxygen vacancies are in situ introduced into the lattice of different TMOs(e.g.,Co_(3)O_(4),Fe_(2)O_(3),and NiO)via a facile hydrothermal treatment combined with calcination.Taking Co_(3)O_(4)as a typical example,results prove that the oxygen vacancies in Co_(3)O_(4−x)effectively accelerate charge transfer at the interface and significantly increase electrical conductivity and pseudocapacitance contribution.The Li-ion diffusion coefficient of Co_(3)O_(4−x) is remarkably improved by two orders of magnitude compared with that of Co_(3)O_(4).Theoretical calculations reveal that Co_(3)O_(4−x)has a lower Li-insertion energy barrier and more density of states around the Fermi level than Co_(3)O_(4),which is favorable for ion and electron transport.Therefore,TMOs with rich vacancies exhibit superior cycling performance and enhanced rate capability over their counterparts.This strategy regulating the reaction kinetics would provide inspiration for designing other TMObased electrodes for energy applications.

METTL3-mediated m^(6)A modification of HMGA2 mRNA promotes subretinal fibrosis and epithelial-mesenchymal transition

Subretinal fibrosis is a major cause of the poor visual prognosis for patients with neovascular age-related macular degeneration(nAMD).Myofibroblasts originated from retinal pigment epithelial(RPE)cells through epithelial-mesenchymal transition(EMT)contribute to the fibrosis formation.N^(6)-Methyladenosine(m^(6)A)modification has been implicated in the EMT process and multiple fibrotic diseases.The role of m^(6)A modification in EMT-related subretinal fibrosis has not yet been elucidated.In this study,we found that during subretinal fibrosis in the mouse model of laser-induced choroidal neovascularization,METTL3 was upregulated in RPE cells.Through m^(6)A epitranscriptomic microarray and further verification,high-mobility group AT-hook 2(HMGA2)was identified as thekey downstream target of METTL3,subsequently activating potent EMT-inducing transcription factor SNAIL.Finally,by subretinal injections of adeno-associated virus vectors,we confirmed that METTL3 deficiency in RPE cells could efficiently attenuate subretinal fibrosis in vivo.In conclusion,our present research identified an epigenetic mechanism of METTL3-m^(6)A-HMGA2 in subretinal fibrosis and EMT of RPE cells,providing a novel therapeutic target for subretinal fibrosis secondary to nAMD.

Longitudinal proteomic investigation of cOVID-19 vaccination

Although the development of covID-19 vaccines has been a remarkable success,the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict.In this study,blood samples were collected from 163 participants who next received two doses of an inactivated COvVID-19 vaccine(CoronaVac)at a 28-day interval.Using TMT-based proteomics,we identified 1,715 serum and 7,342 peripheral blood mononuclear cells(PBMCs)proteins.We proposed two sets of potential biomarkers(seven from serum,five from PBMCs)at baseline using machine learning,and predicted the individual seropositivity 57 days after vaccination(AUC=0.87).Based on the four PBMC's potential biomarkers,we predicted the antibody persistence until 180 days after vaccination(AUC=0.79).Our data highlighted characteristic hematological host responses,including altered lymphocyte migration regulation,neutrophil degranulation,and humoral immune response.This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after coVID-19 vaccination,shedding light on immunization mechanisms and individual booster shot planning.

OnionGraph:Hierarchical topology+attribute multivariate network visualization

Hierarchical abstraction is a scalable strategy to deal with large networks.Existing visualization methods have allowed to aggregate the network nodes into hierarchies based on the node attributes or network topology,each of which has its own advantage.Very few previous system has the capability to enjoy the best of both worlds.This paper presents OnionGraph,an integrated framework for the exploratory visual analysis of heterogeneous multivariate networks.OnionGraph allows nodes to be aggregated based on either node attributes,topology,or a hierarchical combination of both.These aggregations can be split,merged and filtered under the focus+context interaction model,or automatically traversed by the information-theoretic navigation method.Node aggregations that contain subsets of nodes are displayed by the onion metaphor,indicating the level and details of the abstraction.We have evaluated the OnionGraph tool in three real-world cases.Performance experiments demonstrate that on a commodity desktop,our method can scale to million-node networks while preserving the interactivity for analysis.