The efficacy of nano-mediated drug delivery has been impeded by multiple biological barriers such as the mononuclear phagocyte system (MPS), as well as vascular and interstitial barriers. To overcome ...the abovementioned obstacles, we report a nano-pathogenoid (NPN) system that can in situ hitchhike circulating neutrophils and supplement photothermal therapy (PTT). Cloaked with bacteria-secreted outer membrane vesicles inheriting pathogen-associated molecular patterns of native bacteria, NPNs are effectively recognized and internalized by neutrophils. The neutrophils migrate towards inflamed tumors, extravasate across the blood vessels, and penetrate through the tumors. Then NPNs are rapidly released from neutrophils in response to inflammatory stimuli and subsequently taken up by tumor cells to exert anticancer effects. Strikingly, due to the excellent targeting efficacy, cisplatin-loaded NPNs combined with PTT completely eradicate tumors in all treated mice. Such a nano-platform represents an efficient and generalizable strategy towards in situ cell hitchhiking as well as enhanced tumor targeted delivery.
Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of ...computational methods have been developed to predict peptide-protein interactions. However, most of the existing prediction approaches heavily depend on high-resolution structure data. Here, we present a deep learning framework for multi-level peptide-protein interaction prediction, called CAMP, including binary peptide-protein interaction prediction and corresponding peptide binding residue identification. Comprehensive evaluation demonstrated that CAMP can successfully capture the binary interactions between peptides and proteins and identify the binding residues along the peptides involved in the interactions. In addition, CAMP outperformed other state-of-the-art methods on binary peptide-protein interaction prediction. CAMP can serve as a useful tool in peptide-protein interaction prediction and identification of important binding residues in the peptides, which can thus facilitate the peptide drug discovery process.
Computational approaches for understanding compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, a number of deep-learning-based methods have been proposed to ...predict binding affinities and attempt to capture local interaction sites in compounds and proteins through neural attentions (i.e., neural network architectures that enable the interpretation of feature importance). Here, we compiled a benchmark dataset containing the inter-molecular non-covalent interactions for more than 10,000 compound-protein pairs and systematically evaluated the interpretability of neural attentions in existing models. We also developed a multi-objective neural network, called MONN, to predict both non-covalent interactions and binding affinities between compounds and proteins. Comprehensive evaluation demonstrated that MONN can successfully predict the non-covalent interactions between compounds and proteins that cannot be effectively captured by neural attentions in previous prediction methods. Moreover, MONN outperforms other state-of-the-art methods in predicting binding affinities. Source code for MONN is freely available for download at https://github.com/lishuya17/MONN.
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•MONN models compound-protein interactions from structure-free information•MONN predicts both inter-molecular non-covalent interactions and binding affinities•MONN outperforms other methods, on large datasets with or without atomic structures•Predictions of MONN can be validated by known chemical rules
Identifying compound-protein interactions is one of the essential challenges in drug discovery. We developed MONN, a multi-objective neural network, which not only accurately predicts the binding affinities but also successfully captures the non-covalent interactions between compounds and proteins. MONN can prove to be a useful tool in exploring compound-protein interactions.
The development of thin film nanocomposite (TFN) reverse osmosis (RO) membranes has promoted the membrane technology for desalination. Novel nanocomposites are urgently being explored to develop ...superior performance TFN RO membranes. Graphene oxide quantum dots (GOQD) is considered to be an ideal nanofiller for improving membrane permeability due to its rich hydrophilic groups, uniform dispersion and small nanosheet shape. As a silver ion (Ag+) compound, silver phosphate (AP) possesses higher bactericidal effect than silver particle in membrane application. Accordingly, we synthesized the multifunctional nanocomposite of AP loaded GOQD by a facile electrostatically driven method. Subsequently, GOQD/AP was embedded into the dense polyamide (PA) layer via interfacial polymerization reaction. The GOQD/AP incorporated TFN membrane possessed a high flux of 39.6 L·m−2·h−1 at 16 bar, which was 1.5-fold higher than that of the pristine TFC membrane. Meanwhile, the salt rejection was maintained at 98.4%. Noteworthy, the TFN-GOQD/AP membrane exhibited strong bactericidal property against E. coli with a sterilization rate of 99.9% and good stability as well as excellent antifouling performance during RO process. This work provides a feasible strategy to prepare high permselective and anti-bacterial TFN RO membranes for desalination and wastewater reclamation.
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•GOQD/AP nanocomposite is successfully synthesized through a facile electrostatically driven method.•GOQD/AP is doped into the dense polyamide layer via interfacial polymerization reaction.•GOQD/AP significantly enhances the membrane surface hydrophilicity.•TFN-GOQD/AP50 membrane achieves dual-functions of excellent permeability and outstanding antibacterial property.•The TFN membrane shows considerable stability and prominent antifouling capacity.
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Biodegradable semicrystalline polymers have attracted great interest in fundamental research as well as in technology. Biodegradability, biocompatibility with organisms, and some ...other specific characteristics are the most essential properties for this kind of material. How those properties vary in actual application, like their biodegradation rate and the degree of compatibility with corresponding cells or tissues, depends significantly on its crystalline structure. Considering biodegradable polymers are frequently employed in the form of thin film, crystallization of biodegradable polymers in thin film has attracted considerable attention during the past decades. The purpose of this feature article is to provide context as to how the crystallization of thin biodegradable polymer films can be controlled. The crystallization of polymer thin film on two kinds of substrates is summarized: (1) Crystallization on substrate without unique interaction and (2) crystallization on substrate with favored crystallographic interaction. We hope that this article will afford useful information for thin biodegradable polymer processing in different application fields.
The water ecology of salt marshes plays a crucial role in climate regulation, industrial production, and flood control. Due to a poor understanding of water ecology and the extensive mining of salt ...resources, concerns are mounting about declining groundwater levels, shrinking salt marshes, and other problems associated with the simple yet extremely fragile water ecosystem of salt marshes in arid salt lake areas. This study assessed the ecological status of water resources in the downstream salt marsh area of West Taijinar Lake in the Qaidam Basin, China (2010-2018). Using data from a field investigation, the water ecosystem was divided into an ecological pressure subsystem, an environmental quality subsystem, and a socio-economic subsystem according to an analytic hierarchy process. Each subsystem was quantitatively assessed using the ecological footprint model, the single-factor index, and available data for the salt marsh area. The results showed that water resources were always in a surplus state during the study period, whose development and utilization had a safe status. Surface water had low plankton diversity with no evidence of eutrophication, but its Cl- and SO42- concentrations were too high for direct industrial water uses. Groundwater quality was classified into class V because of high salt concentrations, which could be considered for industrial use given the demand of industrial production. The socio-economic efficiency of water resources was high, as distinguished by decreased water consumption per 10,000 yuan GDP and excellent flood resistance. In conclusion, the ecological status of water resources was deemed good in the study area and this could help sustain regional development. However, since the water ecology in this area is mainly controlled by annual precipitation, it would be challenging to deal with the uneven distribution of precipitation and flood events and to make full use of them for groundwater recharge. This study provides insight into the impact of salt lake resource exploration on water ecology, and the results can be useful for the rational utilization of water resources in salt marshes in other arid areas.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Single-cell technologies enable the dynamic analyses of cell fate mapping. However, capturing the gene regulatory relationships and identifying the driver factors that control cell fate decisions are ...still challenging. We present CEFCON, a network-based framework that first uses a graph neural network with attention mechanism to infer a cell-lineage-specific gene regulatory network (GRN) from single-cell RNA-sequencing data, and then models cell fate dynamics through network control theory to identify driver regulators and the associated gene modules, revealing their critical biological processes related to cell states. Extensive benchmarking tests consistently demonstrated the superiority of CEFCON in GRN construction, driver regulator identification, and gene module identification over baseline methods. When applied to the mouse hematopoietic stem cell differentiation data, CEFCON successfully identified driver regulators for three developmental lineages, which offered useful insights into their differentiation from a network control perspective. Overall, CEFCON provides a valuable tool for studying the underlying mechanisms of cell fate decisions from single-cell RNA-seq data.
As a green synthetic approach, visible light-driven photosynthesis is highly desirable in arylation of inert alkyl halides, as they are important precursors in the total synthesis of natural products ...and pharmaceuticals. However, the high bond dissociation energy of aryl halides is typically out of the range of a single visible-light photon. Here, we propose an essential initiation and subsequent electron-transfer step process for visible light-driven aryl halide reduction, and identify the key pyrrole radical anion intermediate, that acts as the strong reduction species. We propose a photoinduced disproportionation (PDP) approach without the addition of any photocatalysts or additives to afford radical anions of pyrrole derivatives, which have enough reduction power to transfer an electron to aryl halide, giving rise to the corresponding aryl radical to afford the desired C-H arylated heterocyclic product. Once generated, the heterocyclic product can undergo the same photoinduced disproportionation (PDP) process to activate aryl halides, thereby promoting the reaction rate. This unprecedented initiation step, which was carried out in the absence of photocatalysts and additives under ambient conditions, can also be used for coupling a wide range of (hetero)aryl halides and pyrrole derivatives, as well as the synthesis of drug intermediates and biorelevant compounds.
We developed a facile photoinduced disproportionation approach to generate radical anions of pyrrole derivatives for the reduction of aryl halides, as well as the formation of desired heterocyclic product without the addition of any photocatalysts.
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the ...genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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