Identifying compound-protein interaction (CPI) is a crucial task in drug discovery and chemogenomics studies, and proteins without three-dimensional structure account for a large part of potential ...biological targets, which requires developing methods using only protein sequence information to predict CPI. However, sequence-based CPI models may face some specific pitfalls, including using inappropriate datasets, hidden ligand bias and splitting datasets inappropriately, resulting in overestimation of their prediction performance.
To address these issues, we here constructed new datasets specific for CPI prediction, proposed a novel transformer neural network named TransformerCPI, and introduced a more rigorous label reversal experiment to test whether a model learns true interaction features. TransformerCPI achieved much improved performance on the new experiments, and it can be deconvolved to highlight important interacting regions of protein sequences and compound atoms, which may contribute chemical biology studies with useful guidance for further ligand structural optimization.
https://github.com/lifanchen-simm/transformerCPI.
The previous research has suggested that the existence of technology disparities reduces a contribution of environmental technological progress to combat various environmental issues. To handle the ...difficulty, we propose a new framework for assessing technology inequality and technology diffusion barriers. To measure them, we discuss the concept of efficiency Gini coefficient. Then, we combine it with Data Envelopment Analysis (DEA), DEA-DA (Discriminant Analysis) and decomposition methods of inequality measurement. Using the combined approach, we perform group-based and source-based decomposition to identify technology diffusion barriers. Empirically, this study has utilized the approach to evaluate technology inequality in Chinese provinces from 2007 to 2018. The main findings are summarized as follows. First, an overall efficiency Gini coefficient tended to increase over time, implying that technological disparity has increased across Chinese provinces. The disparity reduced the contribution of technological progress in addressing various environmental issues. Second, two factors mainly produced the technology inequality. They were cross-group inequality and within-group efficiency Gini coefficient. These results explained growing disparities across Chinese regions. Finally, a considerable difference existed in the within-group efficiency Gini coefficient.
•This study puts forward the concept of efficiency Gini coefficient.•It proposes a new approach to measure technology inequality.•Our approach is used to evaluate Chinese provinces.•We performed group- and source-based decomposition analysis.•A substantial technology inequality is found among Chinese provinces.
•A novel self-enhanced ECL Ru(II)-complex was firstly synthesized.•Luminophor (NH2-Ru@SiO2) and co-reactant (NGQDs) existed in the same nanoparticle.•An effective monitoring method for ZEN was ...developed by the developed aptasensor.•ZEN produced during the mildew process of corn flour was monitored.•Results exhibited superior determination and potential application in real samples.
Accurate and early diagnosis of mycotoxin is particularly significant to the food and agricultural product safety. In the present work, a sensitive and effective monitoring method for zearalenone (ZEN) was exploited based on a novel self-enhanced electrochemiluminescence (ECL) aptasensor. The self-enhanced lumonophore was compounded by electrostatically combining amine-functionalized Ru(bpy)32+-doped silica nanoparticles (NH2-Ru@SiO2 NPs) and nitrogen doped graphene quantum dots (NGQDs) together. Since the emitter and co-reactant simultaneously existed in the same nanoparticle, shortened electron-transfer distance and decreased energy loss was obtained. Therefore, self-enhanced ECL aptasensor based on the novel complex expressed the widest linear range of 10 fg mL−1–10 ng mL−1 and the lowest detection limit of 1 fg mL−1 for ZEN detection. More importantly, ZEN produced during the mildew process of corn flour was monitored by the developed aptasensor, which exhibited superior determination and potential application in real samples.
To test the function of candidate genes in soybean for resistance to the soybean cyst nematode (SCN), a large collection of EMS-mutants from the SCN-resistant soybean cultivar “Forrest” was developed ...for Targeting Induced Local Lesions IN Genomes (TILLING). Additionally, due to the complexity of the soybean genome, an integrated set of genomic and genetic analysis tools was employed to complement the TILLING approach. The efficiency of this integrated set of tools was tested using a candidate soybean gene for resistance to SCN, encoding a leucine-rich repeat receptor-like kinase (LRR-RLK) that was identified by map-based cloning at the Rhg4 locus. The Rhg4 locus is one of the major quantitative trait loci controlling soybean resistance against SCN race 3 (HG type 0) in cv. Forrest, but the gene(s) sequence for resistance remains to be determined. Using TILLING, a Forrest mutant containing a nonsense mutation in the LRR domain of the candidate resistance protein was identified and confirmed; however, the SCN-resistant phenotype of the mutant was not altered. Haplotyping and EcoTILLING of recombinant inbred lines along with complementation analysis corroborated the TILLING result and ruled out the possibility of functional redundancy by a second copy of the LRR-RLK gene identified in the soybean genome. This study validates the use of TILLING, in combination with an integrated set of genomic tools, as an efficient means of testing candidate genes for SCN resistance in soybean.
The solid lubricant MoS
2
demonstrates excellent lubricating properties, but it spontaneously oxidizes and absorbs moisture in air, and thus results in poor wear resistance and short wear-life. In ...this study, the additive g-C
3
N
4
(CN) was successfully combined with MoS
2
via hydrothermal synthesis as a solid lubricant for the first time. Meanwhile, a low friction coefficient (COF, μ = 0.031) and ultra-long wear-life of CN/MoS
2
compared to pure MoS
2
in air were demonstrated. The functional groups and good crystallinity of the lubricant material were characterized via Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD). The formed valence states in CN/MoS
2
were analyzed via X-ray photoelectron spectroscopy (XPS). The characterized results of the scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM) show the morphology and interior crystal phase structure of CN/MoS
2
. From the cross-section analysis, the presence of iron oxide nanoparticles lubricating film is synergistic with CN/MoS
2
film during the friction process, resulting in its ultra-long wear-life. In particular, the friction mechanism of interlayer sliding friction combined with energy storage friction was analyzed and proposed.
Hunting for chemicals with favorable pharmacological, toxicological, and pharmacokinetic properties remains a formidable challenge for drug discovery. Deep learning provides us with powerful tools to ...build predictive models that are appropriate for the rising amounts of data, but the gap between what these neural networks learn and what human beings can comprehend is growing. Moreover, this gap may induce distrust and restrict deep learning applications in practice. Here, we introduce a new graph neural network architecture called Attentive FP for molecular representation that uses a graph attention mechanism to learn from relevant drug discovery data sets. We demonstrate that Attentive FP achieves state-of-the-art predictive performances on a variety of data sets and that what it learns is interpretable. The feature visualization for Attentive FP suggests that it automatically learns nonlocal intramolecular interactions from specified tasks, which can help us gain chemical insights directly from data beyond human perception.
Simulations of mixed‐phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed‐Phase Arctic Cloud Experiment (M‐PACE) are ...performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed‐phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of the boundary layer mixed‐phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid‐scale features in Arctic frontal clouds but does not help improve the simulation of the single‐layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener‐Bergeron‐Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. This paper shows that the Wegener‐Bergeron‐Findeisen process is important for these models to correctly simulate the observed features of mixed‐phase clouds.
This study aimed to explore the process of posttraumatic growth of injured patients after a motor vehicle accident in China. Semi-structured interviews were conducted with six patients. Transcripts ...were analyzed using interpretative phenomenological analysis. Four main super-ordinate themes emerged: construction of meaning; perception of self; perception of connection; and perception of life philosophy. These themes describe growth and emotional distress which may well coexist. Posttraumatic growth can be seen as one outcome of a process of struggling with traumatic injuries. Some strategies for facilitating posttraumatic growth are discussed. Health-care providers may help the recovery of injured patients by facilitating posttraumatic growth.
Accurate and early diagnosis of mycotoxin is particularly significant to the food and agricultural product safety. In the present work, a sensitive and effective monitoring method for zearalenone ...(ZEN) was exploited based on a novel self-enhanced electrochemiluminescence (ECL) aptasensor. The self-enhanced lumonophore was compounded by electrostatically combining amine-functionalized Ru(bpy)
-doped silica nanoparticles (NH
-Ru@SiO
NPs) and nitrogen doped graphene quantum dots (NGQDs) together. Since the emitter and co-reactant simultaneously existed in the same nanoparticle, shortened electron-transfer distance and decreased energy loss was obtained. Therefore, self-enhanced ECL aptasensor based on the novel complex expressed the widest linear range of 10 fg mL
-10 ng mL
and the lowest detection limit of 1 fg mL
for ZEN detection. More importantly, ZEN produced during the mildew process of corn flour was monitored by the developed aptasensor, which exhibited superior determination and potential application in real samples.
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•The epoxy polymers named EPCN and EPCN4-CF composites based on dynamic imine bonds were successfully prepared.•The EPCN-4 epoxy polymer with dynamic imine bonds exhibited excellent ...self-healing and reprocessable properties.•Both EPCN-4 epoxy polymer and EPCN4-CF composites combined excellent degradability in mild acidic conditions.•The surface morphology and chemical structure of the recycled CFs from EPCN4-CF were not changed.
Traditional epoxy thermosets have been extensively used in many fields, including the field of carbon fiber composite materials, which is favored by a large number of researchers. But they usually cannot be recycled under mild conditions. To make matters worse, the material loses its usefulness once it is damaged. Self-healing and degradable thermosetting resins with dynamic covalent bonds offer a potential solution to this conflict. In this paper, a series of epoxy polymers named EPCN based on dynamic imine bonds were easily prepared by a one-pot method using inexpensive industrial materials terephthalaldehyde and common bisphenol A diglycidyl ether as raw materials, which were cured by D230. The results show that the materials exhibit certain self-healing, reprocessability and thermadapt shape memory properties due to the dynamic properties of the imine bonds. Moreover, EPCN epoxy polymers can be degraded due to the hydrolysis of dynamic imine bonds, and their degradation exhibit temperature and acidity dependence. More importantly, the recyclable carbon fiber reinforced polymer composites prepared with EPCN-4 as the resin matrix can be completely degraded under weak acid conditions, leading to the ready and non-destructive recycling of its carbon fiber composite. We envision this reprocessable and degradable carbon fiber-reinforced composite material with cheap raw materials, simple process, and suitable for mass production will make it a potential candidate for sustainable structural material applications.
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