Aptasensor based on gold nanostructure-decorated 2D Cu metal-organic framework nanosheets for highly sensitive and specific electrochemical lipopolysaccharide detection.

Detecting lipopolysaccharide (LPS) using electrochemical methods is significant because of their exceptional sensitivity, simplicity, and user-friendliness. Two-dimensional metal-organic framework (2D-MOF) that merges the benefits of MOF and 2D nanostructure has exhibited remarkable performance in constructing electrochemical sensors, notably surpassing traditional 3D-MOFs. In this study, Cu[tetrakis(4-carboxylphenyl)porphyrin] (Cu-TCPP) and Cu(tetrahydroxyquinone) (Cu-THQ) 2D nanosheets were synthesized and applied on a glassy carbon electrode (GCE). The 2D-MOF nanosheets, which serve as supporting layers, exhibit improved electron transfer and electronic conductivity characteristics. Subsequently, the modified electrode was subjected to electrodeposition with Au nanostructures, resulting in the formation of Au/Cu-TCPP/GCE and Au/Cu-THQ/GCE. Notably, the Au/Cu-THQ/GCE demonstrated superior electrochemical activity because of the 2D morphology, redox ligand, dense Cu sites, and improved deposition of flower-like Au nanostructure based on Cu-THQ. The electron transfer specific surface area was increased by the improved deposition of Au nanostructures, which facilitates enriched binding of LPS aptamer and significantly improved the detection performance of Apt/Au/Cu-THQ/GCE electrochemical aptasensor. The limit of detection for LPS reached 0.15 fg/mL with a linear range of 1 fg/mL - 100 pg/mL. The proposed aptasensor demonstrated the ability to detect LPS in serum samples with satisfactory accuracy, indicating significant potential for clinical diagnosis.

Highly Sensitive Fluorescence Detection of Global 5-Hydroxymethylcytosine from Nanogram Input with Strongly Emitting Copper Nanotags.

Quantitative analysis of 5-hydroxymethylcytosine (5hmC) has remarkable clinical significance to early cancer diagnosis; however, it is limited by the requirement in current assays for large amounts of starting material and expensive instruments requring expertise. Herein, we present a highly sensitive fluorescence method, termed hmC-TACN, for global 5hmC quantification from several nanogram inputs based on terminal deoxynucleotide transferase (TdT)-assisted formation of fluorescent copper (Cu) nanotags. In this method, 5hmC is labeled with click tags by T4 phage ß-glucosyltransferase (ß-GT) and cross-linked with a random DNA primer via click chemistry. TdT initiates the template-free extension along the primer at the modified 5hmC site and then generates a long polythymine (T) tail, which can template the production of strongly emitting Cu nanoparticles (CuNPs). Consequently, an intensely fluorescent tag containing numerous CuNPs can be labeled onto the 5hmC site, providing the sensitive quantification of 5hmC with a limit of detection (LOD) as low as 0.021% of total nucleotides (S/N = 3). With only a 5 ng input (∼1000 cells) of genomic DNA, global 5hmC levels were accurately determined in mouse tissues, human cell lines (including normal and cancer cells of breast, lung, and liver), and urines of a bladder cancer patient and healthy control. Moreover, as few as 100 cells can also be distinguished between normal and cancer cells. The hmC-TACN method has great promise of being cost effective and easily mastered, with low-input clinical utility, and even for the microzone analysis of tumor models.

Pearl Necklacelike Strategy Enables Quantification of Global 5-Hydroxymethylcytosine and 5-Formylcytosine by Inductively Coupled Plasma-Atomic Emission Spectrometry.

5-Hydroxymethylcytosine (5hmC) and 5-formylcytosine (5fC) are key intermediates of active DNA demethylation, for which the global detection methods are still restricted by high cost and long operation time. Here, we demonstrate a pearl necklacelike strategy to accurately quantify global 5hmC and 5fC in genomic DNA. In this method, the metal-organic framework (MOF), [Cu3(BTC)2] (denoted as HKUST-1, H3BTC = 1,3,5-benzenetricarboxylic acid), with a diameter of ∼30 nm that contains ∼15 000 copper ions (Cu2+) as the "super label" was in situ grown in the carboxylated 5hmC and 5fC loci of genomic DNA via the coordination between Cu2+ and the carboxyl group. After the acid digestion of MOF, the concentration of Cu2+, which has a quantitative relationship with the 5hmC/5fC content, was measured by inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The metal element enrichment during MOF growth has amplified the signal by 4 orders of magnitude, realizing sensitive and accurate quantification of global 5hmC and 5fC in different tissues with a detection limit of 0.031% and 0.019‰ in DNA, respectively. The bisulfite- and mass spectrometry-free strategy is easily performed in almost all research and medical laboratories and would provide potential capability to quantify other candidate modifications in nucleotides.

PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model.

BACKGROUND: In systems biology, it is of great interest to identify previously unreported associations between genes. Recently, biomedical literature has been considered as a valuable resource for this purpose. While classical clustering algorithms have popularly been used to investigate associations among genes, they are not tuned for the literature mining data and are also based on strong assumptions, which are often violated in this type of data. For example, these approaches often assume homogeneity and independence among observations. However, these assumptions are often violated due to both redundancies in functional descriptions and biological functions shared among genes. Latent block models can be alternatives in this case but they also often show suboptimal performances, especially when signals are weak. In addition, they do not allow to utilize valuable prior biological knowledge, such as those available in existing databases. RESULTS: In order to address these limitations, here we propose PALMER, a constrained latent block model that allows to identify indirect relationships among genes based on the biomedical literature mining data. By automatically associating relevant Gene Ontology terms, PALMER facilitates biological interpretation of novel findings without laborious downstream analyses. PALMER also allows researchers to utilize prior biological knowledge about known gene-pathway relationships to guide identification of gene-gene associations. We evaluated PALMER with simulation studies and applications to studies of pathway-modulating genes relevant to cancer signaling pathways, while utilizing biological pathway annotations available in the KEGG database as prior knowledge. CONCLUSIONS: We showed that PALMER outperforms traditional latent block models and it provides reliable identification of novel gene-gene associations by utilizing prior biological knowledge, especially when signals are weak in the biomedical literature mining dataset. We believe that PALMER and its relevant user-friendly software will be powerful tools that can be used to improve existing pathway annotations and identify novel pathway-modulating genes.

[Analysis of imagery motor effective networks based on dynamic partial directed coherence].

The research on brain functional mechanism and cognitive status based on brain network has the vital significance. According to a time-frequency method, partial directed coherence (PDC), for measuring directional interactions over time and frequency from scalp-recorded electroencephalogram (EEG) signals, this paper proposed dynamic PDC (dPDC) method to model the brain network for motor imagery. The parameters attributes (out-degree, in-degree, clustering coefficient and eccentricity) of effective network for 9 subjects were calculated based on dataset from BCI competitions IV in 2008, and then the interaction between different locations for the network character and significance of motor imagery was analyzed. The clustering coefficients for both groups were higher than those of the random network and the path length was close to that of random network. These experimental results show that the effective network has a small world property. The analysis of the network parameter attributes for the left and right hands verified that there was a significant difference on ROI2 ( P = 0.007) and ROI3 ( P = 0.002) regions for out-degree. The information flows of effective network based dPDC algorithm among different brain regions illustrated the active regions for motor imagery mainly located in fronto-central regions (ROI2 and ROI3) and parieto-occipital regions (ROI5 and ROI6). Therefore, the effective network based dPDC algorithm can be effective to reflect the change of imagery motor, and can be used as a practical index to research neural mechanisms.

Comprehensive Evaluation of Cultivated Land Quality at County Scale: A Case Study of Shengzhou, Zhejiang Province, China.

The existing evaluation system of cultivated land quality mainly considers the natural quality and utilisation conditions, but without sufficient emphasis on ecological environment, which can't meet the requirements of the trinity pattern protection policy. This study, using GIS spatial analysis and multifactor comprehensive evaluation method, constructed a comprehensive evaluation index system, and applied it in Shengzhou. The results show that: (1) under the comprehensive evaluation system, the quality of cultivated land was classified into five levels and revealed normal distribution with the third level cultivated land area as the peak, successive reduction to the two poles, and the overall quality was good relatively; (2) A close relationship was observed between the quality grade of cultivated land and the landform, the valley plain with highest cultivated land quality was the main grain-producing areas. However, the cultivated land in mountainous areas was poor relatively, and vulnerable to geological disasters; (3) The quality grade of cultivated land was related to economical activities directly. The high-quality cultivated land resources made these towns the main grain-producing areas with many agricultural industries distribution. This study provided a new assessment approach that can support cultivated land grading, quality improvement, and sustainable usage, as well as providing a reference for related research and application.

Influence of Structural Isomerism on the Photophysical Properties of a Series of Donor-Acceptor 1-Naphthalenecarbonitrile Derivatives Possessing Amine Substituents.

In an effort to probe the influence of structural isomerism on the excited-state properties of a naphthalene-based donor-acceptor (D-A) system, four 1-naphthalenecarbonitrile compounds with amine substituents in the 2-, 3-, and 4-positions were synthesized and their photophysical properties were examined. Specifically, the molecules 2-dimethylamino-1-naphthalenecarbonitrile (2DA), 2-(1-piperidinyl)-1-naphthalenecarbonitrile (2P), 3-dimethylamino-1-naphthalenecarbonitrile (3DA), and 4-(1-piperidinyl)-1-naphthalenecarbonitrile (4P) were studied. The substitution position of the amine donor has a significant impact on both the ground-state absorption and excited-state properties of the complexes in toluene solution. The energy, band shape, and extinction coefficient of the ground-state absorption spectra are highly dependent on the substitution position of the amine donor. All of the derivatives exhibit fluorescence at room temperature. The fluorescence observed from 2DA, 2P, and 3DA demonstrates a vibronic structure with all three molecules possessing Stokes shifts on the order of 40 nm, whereas the fluorescence observed from 4P is broad and has a Stokes shift 2 times greater than the other derivatives. The fluorescence lifetimes, fluorescence quantum yields, and intersystem crossing quantum yields vary greatly with the substitution position of the amine donor. 2DA and 2P display intermediate fluorescence lifetimes (2.7 ns) and fluorescence quantum yields (0.20) while possessing the greatest intersystem quantum yield (0.80). 3DA has a much greater fluorescence lifetime (16.9 ns) and fluorescence quantum yield (0.82) at the expense of the intersystem crossing quantum yield (0.12). 4P has the shortest lifetime (0.53 ns), with the lowest fluorescence and intersystem crossing quantum yields (<0.05). The singlet-triplet energy gaps are nearly identical for 2DA, 2P, and 3DA with values on the order of 0.70 eV. This singlet-triplet gap is larger in 4P, with a calculated value of 0.94 eV. The triplet-triplet absorption spectra of 2DA, 2P, and 3DA are similar. Broad peaks in the UV and visible regions with maxima around 330 and 500 nm characterize all three spectra. The triplet excited-state extinction coefficient values for 3DA were found to be 1.5 times larger than those in 2DA and 2P. The triplet-triplet absorption spectrum of 4P is markedly different from the triplet-triplet absorption spectra of the other derivatives. The spectrum is broad, with the four local maxima observed at 374, 445, 624, and 774 nm. All four molecules display delayed fluorescence and laser-power-dependent triplet excited-state decay kinetics, indicating the involvement of triplet-triplet annihilation in the deactivation of the triplet excited states. Both the intrinsic triplet lifetimes and triplet-triplet annihilation rate constants were determined. These values are similar for all of the derivatives with triplet lifetimes on the order of 100 µs and diffusion-controlled rates of triplet-triplet annihilation.

Effect of the grain-growing purpose and farm size on the ability of stable land property rights to encourage farmers to apply organic fertilizers.

The application of organic fertilizer by farmers is an important method for promoting the transition of agricultural production from increasing the yield to improving the quality and safety of agricultural products and realizing the green development of agriculture. The behavior of farmers can have a direct impact on organic fertilizer application, and the active participation of farmers can effectively reduce moral hazards and improve governance efficiency. A consensus appears to have been reached regarding the importance of land property rights stability (LPRS) for farmers' organic fertilizer application (FOFA) in China; however, few studies have focused on the conditions under which LPRS exerts an effect or the extent of the effect. Moreover, the grain-growing purpose and farm size are rarely included as driving factors underlying the impact of LPRS on FOFA; thus, biased estimations are easily formed. This study analyzed the influence mechanism of LPRS on FOFA and its dependent conditions using the 2017 China Rural Household Panel Survey from Zhejiang University and conducted an empirical analysis via a logit model. The results showed that LPRS could enable farmers to apply organic fertilizer, although the degree of its impact will vary due to differences in the grain-growing purpose and farm size. Currently, selling products is not conducive to the application of organic fertilizer and will reduce the positive impact of LPRS on the application of organic fertilizer by farmers, whereas expanding the farm size will enhance the positive impact of LPRS. The government should constantly improve the methods and channels for realizing high-quality and high-priced agricultural products and fully acknowledge the role of market demand in guiding farmers' agricultural production, which will increase their enthusiasm for organic fertilizer application. The government should also improve the contract management system for land transfer to strengthen the ability of farmers to expand their farm size to fully demonstrate the role of large-scale farmers.

GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature.

In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative biomarkers that can be used as diagnostic tools in treating patients. Although biomedical literature is considered a valuable data source for this task, currently only a limited number of webservers are available for mining gene-gene associations from the vast amount of biomedical literature using text mining techniques. Moreover, these webservers often have limited coverage of biomedical literature and also lack efficient and user-friendly tools to interpret and visualize mined relationships among genes. To address these limitations, we developed GAIL (Gene-gene Association Inference based on biomedical Literature), an interactive webserver that infers human gene-gene associations from Gene Ontology (GO) guided biomedical literature mining and provides dynamic visualization of the resulting association networks and various gene set enrichment analysis tools. We evaluate the utility and performance of GAIL with applications to gene signatures associated with systemic lupus erythematosus and breast cancer. Results show that GAIL allows effective interrogation and visualization of gene-gene networks and their subnetworks, which facilitates biological understanding of gene-gene associations. GAIL is available at http://chunglab.io/GAIL/.

Simulation optimization for Bayesian multi-arm multi-stage clinical trial with binary endpoints.

Multi-arm multi-stage designs, in which multiple active treatments are compared to a control and accumulated information from interim data are used to add or remove arms from the trial, may reduce development costs and shorten the drug development timeline. As such, this adaptive update is a natural complement to Bayesian methodology in which the prior clinical belief is sequentially updated using the observed probability of success. Simulation is often required for planning clinical trials to accommodate the complexity of the design and to optimize key design characteristics. This paper addresses two key limiting factors in simulations, namely the computational burden and the time needed to obtain results. We first introduce a generic process for simulating Bayesian multi-arm multi-stage designs with binary endpoints. Then, to address the computational burden and time, we optimize the method for calculating the posterior probability and posterior predictive probability of success.

Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information.

Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because of low reproducibility and instability of identified cancer subgroups and molecular features. In order to address this challenge, we developed Integrative Genomics Robust iDentification of cancer subgroups (InGRiD), a statistical approach that integrates information from biological pathway databases with high-throughput genomic data to improve the robustness for identification and interpretation of molecularly-defined subgroups of cancer patients. We applied InGRiD to the gene expression data of high-grade serous ovarian cancer from The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The results indicate clear benefits of the pathway-level approaches over the gene-level approaches. In addition, using the proposed InGRiD framework, we also investigate and address the issue of gene sharing among pathways, which often occurs in practice, to further facilitate biological interpretation of key molecular features associated with cancer progression. The R package "InGRiD" implementing the proposed approach is currently available in our research group GitHub webpage ( https://dongjunchung.github.io/INGRID/ ).

A calix[4]arene-modified (Pc)Eu(Pc)Eu[T(C4A)PP]-based sensor for highly sensitive and specific host-guest electrochemical recognition.

A calix[4]arene (C4A)-functionalized (phthalocyaninato)(porphyrinato) europium(iii) triple-decker compound (Pc)Eu(Pc)Eu[T(C4A)PP] (1) is firstly designed, synthesized and prepared into well-organized films using a simple solution-processing quasi-Langmuir-Shäfer (QLS) method. The QLS film of 1 on an ITO (film 1/ITO) electrode, serving as a host-guest electrochemical recognition layer, is able to establish specific responses/interactions toward organic molecules with biological and drug interest including dopamine (DA), uric acid (UA), tyrosine (Tyr), tryptophan (Trp) and Acetaminophen (APAP), depending mainly on the matching degree of molecular dimensions between the analytes and the C4A cavity in addition to their chemical nature. More significantly, the film 1/ITO electrode shows a wide linear range of electrochemical detection (from 0.1 to 100 µM) to DA and APAP, with a high sensitivity of 53.0 and 94.3 µA mM-1 and a very low detection limit of 25 and 11 nM for DA and APAP, respectively, representing the best result among the nonenzymatic organic semiconductor-based biosensors. In particular, the film 1/ITO electrode exhibits excellent stability, reproducibility, high selectivity, and anti-interference nature for the detection of both DA and APAP, indicating the great potential of calix[n]arene macrocycle-modified tetrapyrrole rare earth sandwich compounds in the field of ultrasensitive and specific nonenzymatic sensors.

Effects of intramolecular hydrogen bonding and sterically forced non-coplanarity on organic donor/acceptor two-photon-absorbing molecules.

Two photon absorption (2PA) is of great interest across many disciplines and there has been a large effort to increase the two-photon cross section (σ2) via synthetic modification, especially by enhancing intramolecular charge-transfer (ICT). This work takes the previously studied (7-benzothiazol-2-yl-9,9-diethylfluoren-2-yl)diphenylamine (AF240), an asymmetric D-π-A chromophore, and intentionally appends a functional group (-OH, AF240-OH or -OCH3, AF240-OMe) to the 6-position of the fluorenyl π-bridge of the new chromophores. Electrochemical results in both dichloromethane and acetonitrile support stabilization of the highest occupied molecular orbital in the derivatives due to inductive electron donating effects of the hydroxy and methoxy groups. The lowest unoccupied molecular orbital is stabilized via intramolecular hydrogen bonding to the benzothiazole moiety in the case of AF240-OH. As previously observed for AF240, the steady-state emission spectra show significant solvatochromism as they broaden and red shift with increasing solvent polarity. The fluorescence lifetimes and quantum yields show that the non-radiative rate constant is increased for AF240-OH in all solvents, especially in nonpolar media. The results suggest there is forced intramolecular hydrogen bonding to the benzothiazole in nonpolar solvents because the solvent poorly solubilizes the hydroxy group. This increases the non-radiative decay rate constant (knr) via additional vibrational decay pathways. While not as dramatic, the increase in knr in polar solvents supports some deactivation via hydrogen bonding to the solvent. Steric effects are also observed in the methoxy derivative, which inhibits planarization of the benzothiazole with the fluorene, increasing the energy of the excited state. Ultrafast transient absorption spectroscopy in tetrahydrofuran solution supports stabilization of the excited state in a few ps as solvent and structural reorganizations occur. In the case of AF240-OH, no evidence of proton transfer is observed. The decrease in emission energies in the case of AF240-OH support increased ICT driven by higher degree of coplanarity and the quinoidal structure in the excited state. However, a moderate increase in the intrinsic 2PA cross-section is resulted. It is likely because of the two possible and competing solvent-stabilized ICT processes (PICT and TICT) in AF240-OH. Nevertheless, the strategic presence of a hydroxide group capable of intramolecular hydrogen bonding in AF240-OH provides a much broader 2PA sensitivity window than AF240.

Improving SNP prioritization and pleiotropic architecture estimation by incorporating prior knowledge using graph-GPA.

Summary: Integration of genetic studies for multiple phenotypes is a powerful approach to improving the identification of genetic variants associated with complex traits. Although it has been shown that leveraging shared genetic basis among phenotypes, namely pleiotropy, can increase statistical power to identify risk variants, it remains challenging to effectively integrate genome-wide association study (GWAS) datasets for a large number of phenotypes. We previously developed graph-GPA, a Bayesian hierarchical model that integrates multiple GWAS datasets to boost statistical power for the identification of risk variants and to estimate pleiotropic architecture within a unified framework. Here we propose a novel improvement of graph-GPA which incorporates external knowledge about phenotype-phenotype relationship to guide the estimation of genetic correlation and the association mapping. The application of graph-GPA to GWAS datasets for 12 complex diseases with a prior disease graph obtained from a text mining of biomedical literature illustrates its power to improve the identification of risk genetic variants and to facilitate understanding of genetic relationship among complex diseases. Availability and implementation: graph-GPA is implemented as an R package 'GGPA', which is publicly available at http://dongjunchung.github.io/GGPA/. DDNet, a web interface to query diseases of interest and download a prior disease graph obtained from a text mining of biomedical literature, is publicly available at http://www.chunglab.io/ddnet/. Supplementary information: Supplementary data are available at Bioinformatics online.

The asymptotic maximal procedure for subject randomization in clinical trials.

The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to the lack of the Markovian property of the conditional allocation probabilities. In this paper, we propose the asymptotic maximal procedure, which replaces the sequence-length-dependent conditional allocation probabilities with their asymptotic values. The new randomization procedure is compared with the original maximal procedure and few other randomization procedures with the maximum tolerated imbalance via simulations and is found to be a practical choice for future clinical trials.

(Pc)Eu(Pc)Eu[trans-T(COOCH3)2PP]/GO Hybrid Film-Based Nonenzymatic H2O2 Electrochemical Sensor with Excellent Performance.

A facile approach was developed for preparing the multilayer hybrid films of mixed (phthalocyaninato) (porphyrinato) europium(III) triple-decker compound (Pc)Eu(Pc)Eu[trans-T(COOCH3)2PP] (1) and graphene oxide (GO) using the solution-processing QLS method. The combination of the nature of relatively high conductivity and great surface area for GO with the electroactive and semiconductive triple-decker compound in ITO electrode renders the hybrid film excellent sensing property for H2O2, due to the optimized triple-decker molecular packing in the uniform-sized nanoparticles (ca. 70 nm) formed on the GO surface. The amperometric responses are linearly proportional to the concentration of H2O2 in the range of 0.05-1800 µM with a fast response time of 0.03 s µM-1, a low detection limit of 0.017 µM, and good sensitivity of 7.4 µA mM-1. The present work represents the best result of tetrapyrrole-based nonenzymatic electrochemical sensor for H2O2. Nevertheless, the triple-decker/GO/ITO also shows excellent stability, reproducibility, and selectivity, indicating the great potential of electroactive tetrapyrrole rare earth sandwich compounds in combination with GO in the field of nonenzymatic electrochemical sensors.

Steric hindrance inhibits excited-state relaxation and lowers the extent of intramolecular charge transfer in two-photon absorbing dyes.

The two-photon absorbing dye AF240 [1, (7-benzothiazol-2-yl-9,9-diethylfluoren-2-yl)diphenylamine] is modified by adding bulky alkyl groups to the diphenylamino moiety. Three new compounds are synthesized which have ethyl groups in both ortho positions of each phenyl ring (2), t-butyl groups in one ortho position of each phenyl ring (3), and t-butyl groups in the para position of each phenyl ring (4). The dyes are examined in several aprotic solvents with varying polarity to observe the effects of the sterically hindering bulky groups on the ground and excited-state photophysical properties. While the ground state shows minimal solvent dependence, there is significant dependence on the fluorescence quantum yield and lifetime, as well as the excited-state energy levels. This effect is caused by the formation of an intramolecular charge-transfer (ICT) state, which is observed in the solvents more polar than n-hexane and supported by TD-DFT calculations. Electronic effects of ortho or para alkyl substitution should be similar, yet drastic differences are observed. A red shift in the fluorescence maximum is observed in 4 relative to 1, yet a blue shift occurs in 2 and 3 because the substituents at the sterically sensitive ortho-positions inhibit excited-state geometric relaxation and result in less ICT character than 1. Coupled with theoretical calculations, the data support a planar ICT (PICT) excited state where the diphenylamino nitrogen in an sp(2)-like geometry is integral with the plane containing the fluorene and benzothiazole moieties. Ultrafast transient absorption experiments show that ICT occurs rapidly (<150 fs) followed by geometric and solvent relaxation in ∼ 1-4 ps to form the PICT or solvent-stabilized ICT (SSICT) state. This relaxation is not observed in non-polar n-hexane because the solvent dependent ICT state energy lies higher than the locally-excited (LE) state. Finally, formation of a triplet state (T1) is only efficiently observed in n-hexane for all four dyes.

An integrative bioinformatics framework for genome-scale multiple level network reconstruction of rice.

Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs), protein-protein interactions (PPIs) and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs) approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Graphene surface-enabled lithium ion-exchanging cells: next-generation high-power energy storage devices.

Herein reported is a fundamentally new strategy for the design of high-power and high energy-density devices. This approach is based on the exchange of lithium ions between the surfaces (not the bulk) of two nanostructured electrodes, completely obviating the need for lithium intercalation or deintercalation. In both electrodes, massive graphene surfaces in direct contact with liquid electrolyte are capable of rapidly and reversibly capturing lithium ions through surface adsorption and/or surface redox reaction. These devices, based on unoptimized materials and configuration, are already capable of storing an energy density of 160 Wh/kg(cell), which is 30 times higher than that (5 Wh/kg(cell)) of conventional symmetric supercapacitors and comparable to that of Li-ion batteries. They are also capable of delivering a power density of 100 kW/kg(cell), which is 10 times higher than that (10 kW/kg(cell)) of supercapacitors and 100 times higher than that (1 kW/kg(cell)) of Li-ion batteries.

Graphene-based supercapacitor with an ultrahigh energy density.

A supercapacitor with graphene-based electrodes was found to exhibit a specific energy density of 85.6 Wh/kg at room temperature and 136 Wh/kg at 80 °C (all based on the total electrode weight), measured at a current density of 1 A/g. These energy density values are comparable to that of the Ni metal hydride battery, but the supercapacitor can be charged or discharged in seconds or minutes. The key to success was the ability to make full utilization of the highest intrinsic surface capacitance and specific surface area of single-layer graphene by preparing curved graphene sheets that will not restack face-to-face. The curved morphology enables the formation of mesopores accessible to and wettable by environmentally benign ionic liquids capable of operating at a voltage >4 V.