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Antibiotics that use novel mechanisms are needed to combat antimicrobial resistance1–3. Teixobactin4 represents a new class of antibiotics with a unique chemical scaffold and lack of detectable resistance. Teixobactin targets lipid II, a precursor of peptidoglycan5. Here we unravel the mechanism of teixobactin at the atomic level using a combination of solid-state NMR, microscopy, in vivo assays and molecular dynamics simulations. The unique enduracididine C-terminal headgroup of teixobactin specifically binds to the pyrophosphate-sugar moiety of lipid II, whereas the N terminus coordinates the pyrophosphate of another lipid II molecule. This configuration favours the formation of a β-sheet of teixobactins bound to the target, creating a supramolecular fibrillar structure. Specific binding to the conserved pyrophosphate-sugar moiety accounts for the lack of resistance to teixobactin4. The supramolecular structure compromises membrane integrity. Atomic force microscopy and molecular dynamics simulations show that the supramolecular structure displaces phospholipids, thinning the membrane. The long hydrophobic tails of lipid II concentrated within the supramolecular structure apparently contribute to membrane disruption. Teixobactin hijacks lipid II to help destroy the membrane. Known membrane-acting antibiotics also damage human cells, producing undesirable side effects. Teixobactin damages only membranes that contain lipid II, which is absent in eukaryotes, elegantly resolving the toxicity problem. The two-pronged action against cell wall synthesis and cytoplasmic membrane produces a highly effective compound targeting the bacterial cell envelope. Structural knowledge of the mechanism of teixobactin will enable the rational design of improved drug candidates.

INTRODUCTION: It remains unclear whether functional brain networks are consistently altered in individuals with subjective cognitive decline (SCD) of diverse ethnic and cultural backgrounds and whether the network alterations are associated with an amyloid burden.METHODS: Cross-sectional resting-state functional magnetic resonance imaging connectivity (FC) and amyloid-positron emission tomography (PET) data from the Chinese Sino Longitudinal Study on Cognitive Decline and German DZNE Longitudinal Cognitive Impairment and Dementia cohorts were analyzed.RESULTS: Limbic FC, particularly hippocampal connectivity with right insula, was consistently higher in SCD than in controls, and correlated with SCD-plus features. Smaller SCD subcohorts with PET showed inconsistent amyloid positivity rates and FC-amyloid associations across cohorts.DISCUSSION: Our results suggest an early adaptation of the limbic network in SCD, which may reflect increased awareness of cognitive decline, irrespective of amyloid pathology. Different amyloid positivity rates may indicate a heterogeneous underlying etiology in Eastern and Western SCD cohorts when applying current research criteria. Future studies should identify culture-specific features to enrich preclinical Alzheimer's disease in non-Western populations.HIGHLIGHTS: Common limbic hyperconnectivity across Chinese and German subjective cognitive decline (SCD) cohorts was observed. Limbic hyperconnectivity may reflect awareness of cognition, irrespective of amyloid load. Further cross-cultural harmonization of SCD regarding Alzheimer's disease pathology is required.

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Regression-based blind image quality assessment (IQA) models are susceptible to biased training samples, leading to a biased estimation of model parameters. To mitigate this issue, we propose a regression-free framework for image quality evaluation, which is founded upon retrieving similar instances by incorporating semantic and distortion features. The motivation behind this approach is rooted in the observation that the human visual system (HVS) has analogous visual responses to semantically similar image contents degraded by the same distortion. The proposed framework comprises two classification-based modules: semantic-based classification (SC) module and distortion-based classification (DC) module. Given a test image and an IQA database, the SC module retrieves multiple pristine images based on semantic similarity. The DC module then retrieves instances based on distortion similarity from the distorted images that correspond to each retrieved pristine image. Finally, the predicted quality score is derived by aggregating the subjective quality scores of multiple retrieved instances. Experimental results on four benchmark databases validate that the proposed model can remarkably outperform the state-of-the-art regression-based models., Comment: 11 pages, 7 figures, 50 conferences

Additional file 1: Table S1. Immune responses against ancestral virus, BA.1 and BA.5of prime-booster groups by gender. Table S2. Immune responses against ancestralvirus, BA.1 and BA.5 of prime-booster groups by Body Mass Index group.

Objective To construct a mouse model of skin-dominant chronic graft-versus-host disease (cGVHD). Methods BALB/c mice were irradiated with lethal dose and then received a mixture of bone marrow and spleen cells transplantation from B10.D2 donor mice. Then the clinical manifestations, pathological features of the mice and cell subsets of targeted organs were observed to evaluate the establishment of model. Results The clinical manifestations of the model mice mainly involved skin depilation, sclerosis, dandruff, scab, as well as arched back and joint stiffness due to skin shrinkage and sclerosis. The clinicopathological scores were increased with the progression of cGVHD, while the model mice showed no obvious manifestations of intestinal cGVHD. Moreover, increase of collagen deposition and decrease or even disappearance of hair follicles was observed on the histopathologic sections of skin, while other targeted organs showed no major alterations. T cell subsets analysis indicated that Th1 cells, CD4+IL-13+T cells and Tc1 cells were closely related to the disease progression. Conclusion The skin-dominant cGVHD mouse model is successfully established, with skin damage and fibrosis as main pathological changes.

Objective To determine the prophylactic effect of human umbilical cord mesenchymal stem cells (HUCMSCs) on murine acute graft-versus-host disease (aGVHD) and preliminarily explore its mechanism. Methods In order to establish a mouse model of aGVHD, the male BALB/c mice were transplanted with bone marrow cells and spleen lymphocytes from male C57BL/6 mice after receiving 7.5 Gy total body irradiation (TBI) on the day of allogeneic hematopoietic stem cell transplantation (allo-HSCT). The mice were divided into BM group and aGVHD group, receiving 500 μL cell suspension containing 5×106 bone marrow cells or 5×106 bone marrow cells and 5×106 spleen cells, respectively, by tail vein. Their survival rate, clinical score and loss of body weight were assessed, chimerism was detected by flow cytometry, and pathological changes of target organs (lung, liver, colon, small intestine) were detected by HE staining. The HUCMSCs at passage 4 were collected and transplanted into aGVHD+MSCs group of BALB/c mice. The mice were then divided into aGVHD group (model group), aGVHD+MSCs group (5×106 bone marrow cells and 5×106 spleen cells and 5×105 HUCMSCs). Besides, the serum concentration of IFN-γ and TNF-α were detected by ELISA, and the infiltration and apoptosis of lymphocytes were detected by flow cytometry. Results Compared with the BM group, the aGVHD group showed a decreased survival rate, higher clinical score, and much obvious body weight loss (P < 0.05) and severer pathological injuries (P < 0.05). The mice achieved complete chimerism after transplantation. The aGVHD+MSCs group showed increased survival rate, lower clinical score and slighter pathological injuries (P < 0.05), the serum concentrations of IFN-γ and TNF-α were decreased (P < 0.05), and the apoptosis of CD4+ T cells in target organs was increased while the count was decreased (P < 0.05). Conclusion HUCMSCs infusion effectively prevent the development of murine aGVHD after allo-HSCT through mediating the apoptosis of lymphocytes to decrease their infiltration in target organs and regulating the secretion of inflammatory factors.

BACKGROUND The high cost of controlled-release urea (CRU) has prompted this study to explore whether the amount of CRU can be reduced by adding biostimulants while maintaining or increasing rice yield. A 2 year field experiment was conducted with CRU at three levels (60%, 80%, and 100% of the recommended nitrogen (N) fertilizer) and a novel biostimulant Paecilomyces variotii extract (ZNC), to investigate their synergistic effects on yield, nitrogen use efficiency (NUE), and net profitability of rice. RESULTS Controlled-release urea achieved a significantly higher gain yield and NUE than conventional urea with the same N level, which could be attributed to its N supply. Even if the N level of CRU was reduced by 40%, both rice yield and net profit were still significantly higher than for the full amount of urea. Paecilomyces variotii extract sprayed on the surface of CRU at a dose of only 87.5 mL ha-1 exhibited ultra-high effectiveness by increasing the panicles, the N accumulation, and the rice yield. Controlled-release urea enriched by ZNC achieved significantly higher gain yield than CRU alone, increasing the yield by 9.2% and 8.7%, respectively, in 2 years under the full recommended N rate. The combination of 80% CRU and ZNC showed no significant difference in rice yield from treatment with 100% CRU, indicating that the rate of CRU could be reduced by ZNC. The application of ZNC further increased NUE, N partial factor productivity, and net profit. CONCLUSION The CRU and ZNC combination provided a feasible approach for reducing N input while maintaining rice yield and agricultural sustainability. © 2021 Society of Chemical Industry.

In this study, the potential regulatory effects of fulvic acid extracted from paper mill effluent (PFA) in apple replant disease (ARD) were investigated through a comprehensive experimental evaluation of the effects of PFA on soil properties, growth inhibition of apple replant pathogens, and growth of replanted Malus hupehensis Rehd. seedlings. PFA with a relatively lower molecular weight was mainly composed of carbohydrates, lignin derivatives, and polysaccharides and was rich in functional groups such as carboxyl and phenolic hydroxyl groups. Treatment with PFA dosages ranging from 2 to 3 g/pot significantly increased available phosphorus (P) in soil by 47.5 to 57.5% when compared with the control without PFA, indicating that PFA had a positive effect in activating P. In addition, PFA stimulated the growth of replanted seedlings by promoting root elongation, enhancing leaf photosynthesis, and increasing the activity of root antioxidant enzymes including superoxide dismutase, peroxidase, and catalase. However, no convincing evidence was found that application of different dosages of PFA had remarkable effects on soil pH, inorganic nitrogen, available potassium, organic matter, and the numbers of bacteria and fungi. Notably, PFA had no effect on the copy number of the main pathogenic fungi causing ARD, including Fusarium oxysporum, Fusarium solani, Fusarium proliferatum, and Fusarium moniliforme. Overall, PFA can alleviate ARD to a certain extent mainly through its effects on improving the resilience of replanted young seedlings rather than by affecting soil microorganisms or providing nutrients.

Antimicrobial peptides (AMPs) commonly target bacterial membranes and show broad-spectrum activity against microorganisms. In this research we used three AMPs (nisin, epilancin 15×, [R4L10]-teixobactin) and tested their membrane effects towards three strains (Staphylococcus simulans, Micrococcus flavus, Bacillus megaterium) in relation with their antibacterial activity. We describe fluorescence and luminescence-based assays to measure effects on membrane potential, intracellular pH, membrane permeabilization and intracellular ATP levels. The results show that our control peptide, nisin, performed mostly as expected in view of its targeted pore-forming activity, with fast killing kinetics that coincided with severe membrane permeabilization in all three strains. However, the mechanisms of action of both Epilancin 15× as well as [R4L10]-teixobactin appeared to depend strongly on the bacterium tested. In certain specific combinations of assay, peptide and bacterium, deviations from the general picture were observed. This was even the case for nisin, indicating the importance of using multiple assays and bacteria for mode of action studies to be able to draw proper conclusions on the mode of action of AMPs.

N-Acetylglucosamine (GlcNAc) is an essential monosaccharide required in almost all organisms. Fluorescent labeling of the peptidoglycan (PG) on N-acetylglucosamine has been poorly explored. Here, we report on the labeling of the PG with a bioorthogonal handle on the GlcNAc. We developed a facile one-step synthesis of uridine diphosphate N-azidoacetylglucosamine (UDP-GlcNAz) using the glycosyltransferase OleD, followed by in vitro incorporation of GlcNAz into the peptidoglycan precursor Lipid II and fluorescent labeling of the azido group via click chemistry. In a PG synthesis assay, fluorescent GlcNAz-labeled Lipid II was incorporated into peptidoglycan by the DD-transpeptidase activity of bifunctional class A penicillin-binding proteins. We further demonstrate the incorporation of GlcNAz into the PG layer of OleD-expressed bacteria by feeding with 2-chloro-4-nitrophenyl GlcNAz (GlcNAz-CNP). Hence, our labeling method using the heterologous expression of OleD is useful to study PG synthesis and possibly other biological processes involving GlcNAc metabolism in vivo.

A multitude of studies have been conducted on graph drawing, but many existing methods only focus on optimizing a single aesthetic aspect of graph layouts. There are a few existing methods that attempt to develop a flexible solution for optimizing different aesthetic aspects measured by different aesthetic criteria. Furthermore, thanks to the significant advance in deep learning techniques, several deep learning-based layout methods were proposed recently, which have demonstrated the advantages of the deep learning approaches for graph drawing. However, none of these existing methods can be directly applied to optimizing non-differentiable criteria without special accommodation. In this work, we propose a novel Generative Adversarial Network (GAN) based deep learning framework for graph drawing, called SmartGD, which can optimize any quantitative aesthetic goals even though they are non-differentiable. In the cases where the aesthetic goal is too abstract to be described mathematically, SmartGD can draw graphs in a similar style as a collection of good layout examples, which might be selected by humans based on the abstract aesthetic goal. To demonstrate the effectiveness and efficiency of SmartGD, we conduct experiments on minimizing stress, minimizing edge crossing, maximizing crossing angle, and a combination of multiple aesthetics. Compared with several popular graph drawing algorithms, the experimental results show that SmartGD achieves good performance both quantitatively and qualitatively.

Senescence in plants is induced by endogenous physiological changes and exogenous stresses. In this study, we isolated two alleles of a novel rice (Oryza sativa) mutant, yellow and premature dwarf 1 (ypd1). The ypd1 mutants exhibited a yellow and dwarf phenotype from germination, and premature senescence starting at tillering. Moreover, the ypd1 mutants were sensitive to high light, which accelerated cell death and senescence. Consistent with their yellow phenotype, the ypd1 mutants had abnormal chloroplasts and lower levels of photosynthetic pigments. TUNEL assays together with histochemical staining demonstrated that ypd1 mutants showed cell death and that they accumulated reactive oxygen species. The ypd1 mutants also showed increased expression of genes associated with senescence. Map-based cloning revealed a G→A substitution in exon 6 (ypd1-1) and exon 13 (ypd1-2) of LOC_Os06g13050 that affected splicing and caused premature termination of the encoded protein. YPD1 was found to be preferentially expressed in the leaf and it encodes a LRR-like1 protein. Complementation, overexpression, and targeted deletion confirmed that the mutations in YPD1 caused the ypd1 phenotype. YPD1 was localized on the chloroplast membrane. Our results thus demonstrate that the novel rice LRR-like1 protein YPD1 affects chloroplast development and leaf senescence.

De novo protein structure prediction can be treated as a conformational space optimization problem under the guidance of an energy function. However, it is a challenge of how to design an accurate energy function which ensures low-energy conformations close to native structures. Fortunately, recent studies have shown that the accuracy of de novo protein structure prediction can be significantly improved by integrating the residue-residue distance information. In this paper, a two-stage distance feature-based optimization algorithm (TDFO) for de novo protein structure prediction is proposed within the framework of evolutionary algorithm. In TDFO, a similarity model is first designed by using feature information which is extracted from distance profiles by bisecting K-means algorithm. The similarity model-based selection strategy is then developed to guide conformation search, and thus improve the quality of the predicted models. Moreover, global and local mutation strategies are designed, and a state estimation strategy is also proposed to strike a trade-off between the exploration and exploitation of the search space. Experimental results of 35 benchmark proteins show that the proposed TDFO can improve prediction accuracy for a large portion of test proteins.

Ferredoxins (Fds) play a crucial role in photosynthesis by regulating the distribution of electrons to downstream enzymes. Multiple Fd genes have been annotated in the Oryza sativa L. (rice) genome; however, their specific functions are not well understood. Here, we report the functional characterization of rice Fd1. Sequence alignment, phylogenetic analysis of seven rice Fd proteins and quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis showed that rice Fd1 is a primary leaf-type Fd. Electron transfer assays involving NADP+ and cytochrome c indicated that Fd1 can donate electrons from photosystem I (PSI) to ferredoxin-NADP+ reductase. Loss-of-function fd1 mutants showed chlorosis and seedling lethality at the three-leaf stage. The deficiency of Fd1 impaired photosynthetic electron transport, which affected carbon assimilation. Exogenous glucose treatment partially restored the mutant phenotype, suggesting that Fd1 plays an important role in photosynthetic electron transport in rice. In addition, the transcript levels of Fd-dependent genes were affected in fd1 mutants, and the trend was similar to that observed in fdc2 plants. Together, these results suggest that OsFd1 is the primary Fd in photosynthetic electron transport and carbon assimilation in rice.

Background With the aim of addressing the difficulty in identifying temperatures in virtual chemistry experiments, we propose a temperature-sensing simulation method of virtual chemistry experiments. Methods We construct a virtual chemistry experiment temperature simulation platform, based on which a wearable temperature generation device is developed. The typical middle school virtual experiments of concentrated sulfuric acid dilution and ammonium nitrate dissolution are conducted to verify the actual effect of the device. Results The platform is capable to indicate near real-world experimental situations. The performance of the device not only meets the temperature sensing characteristics of human skin, but also matches the temperature change of virtual chemistry experiments in real-time. Conclusions It is demonstrated that this temperature-sensing simulation method can represent exothermic or endothermic chemistry experiments, which is beneficial for students to gain understanding of the principles of thermal energy transformation in chemical reactions, thus avoiding the danger that may be posed in the course of traditional teaching of chemistry experiments effectively. Although this methoddoes not have a convenient enough operation for users, the immersion of virtual chemical experiments can be enhanced.

Xiaoqi Wang1 ,* Wenxing Mao2 ,* Zhi Wang3 ,* Xinrui Li,1 Yaokun Xiong,4 Hongjin Lu,1 Xiuzhen Wang,1 Haoyuan Yin,1 Xiang Cao,1 Hongliang Xin1 1Department of Pharmaceutics and Key Laboratory of Cardiovascular & Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing 211166, People’s Republic of China; 2Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, People’s Republic of China; 3Department of Pharmacy, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China; 4School of Pharmacy, Jiangxi University of Traditional Chinese Medicine, Nanchang 330004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hongliang Xin Fax +86 25 86868467; +86 25 86868477Email xhl@njmu.edu.cnPurpose: Currently, the treatment of brain metastases from non-small cell lung cancer (NSCLC) is rather difficult in the clinic. A combination of small molecule-targeted drug and chemo-drug is a promising therapeutic strategy for the treatment of NSCLC brain metastases. But the efficacy of this combination therapy is not satisfactory due to the blood–brain barrier (BBB). Therefore, it is urgent to develop a drug delivery system to enhance the synergistic therapeutic effects of small molecule–targeted drug and chemo-drug for the treatment of NSCLC brain metastases.Methods: T7 peptide installed and osimertinib (AZD9291) loaded intracellular glutathione (GSH) responsive doxorubicin prodrug self-assembly nanocarriers (T7-DSNPs/9291) have been developed as a targeted co-delivery system to enhance the combined therapeutic effect on brain metastases from NSCLC. In vitro cell experiments, including intracellular uptake assay, in vitro BBB transportation, and MTT assay were used to demonstrate the efficacy of T7-DSNPs/9291 in NSCLC brain metastasis in vitro. Real-time fluorescence imaging analysis, magnetic resonance imaging analysis, and Kaplan–Meier survival curves were used to study the effect of T7-DSNPs/9291 on an animal model in vivo.Results: T7-DSNPs/9291 could significantly enhance BBB penetration of AZD9291 and doxorubicin via transferrin receptor-mediated transcytosis. Moreover, T7-DSNPs/9291 showed significant anti-NSCLC brain metastasis effect and prolonged median survival of an intracranial NSCLC brain metastasis animal model.Conclusion: T7-DSNPs/9291 is a potential drug delivery system for the combined therapy of brain metastasis from NSCLC.Keywords: drug delivery, brain metastasis, AZD9291, redox-responsive, brain targeted delivery system

A novel biostimulant, Paecilomyces variotii extracts (ZNC), with the ability to promote N absorption in the plant at a very low level has been proved in the lab experiment, but its chemical composition and practical effect in the field remain unclear. In this work, we determined the molecular composition of ZNC. Then, a three-year field experiment was conducted to investigate the synergistic effects of controlled-release urea (CRU) without ZNC or with ZNC at three doses (87.5, 175, and 262.5 mL ha-1) on the yield, nitrogen use efficiency (NUE), and net returns of rice. Results indicated that ZNC contained more carbohydrates, amino acids, alkyl structures, and less aromatic structures with a molecular weight between 140 and 2507 Da. Rice yield was 6.9-21.0% higher with CRU than with conventional urea. Combining CRU with ZNC at a dose of 87.5 mL ha-1 performed the best and significantly increased rice yields by 8.7-12.1%, NUE by 15.0-20.2%, and average net returns by 10.9-15.4% during three rice-growing seasons compared to the application of CRU only, which is attributed to the positively increasing panicles and N uptake of rice. With the increased dose of ZNC, the yield of rice showed a decreasing trend, but the yield was still higher/not significant than the CFF treatment without ZNC. Therefore, the planting patterns with the combination of CRU and biostimulant are an efficient way to increase the rice grain yield and net returns.

We assume that the state of a number of nodes in a network could be investigated if necessary, and study what configuration of those nodes could facilitate a better solution for the diffusion-source-localization (DSL) problem. In particular, we formulate a candidate set which contains the diffusion source for sure, and propose the method, Percolation-based Evolutionary Framework (PrEF), to minimize such set. Hence one could further conduct more intensive investigation on only a few nodes to target the source. To achieve that, we first demonstrate that there are some similarities between the DSL problem and the network immunization problem. We find that the minimization of the candidate set is equivalent to the minimization of the order parameter if we view the observer set as the removal node set. Hence, PrEF is developed based on the network percolation and evolutionary algorithm. The effectiveness of the proposed method is validated on both model and empirical networks in regard to varied circumstances. Our results show that the developed approach could achieve a much smaller candidate set compared to the state of the art in almost all cases. Meanwhile, our approach is also more stable, i.e., it has similar performance irrespective of varied infection probabilities, diffusion models, and outbreak ranges. More importantly, our approach might provide a new framework to tackle the DSL problem in extreme large networks.

Recently, Graph Neural Networks (GNNs) have significantly advanced the performance of machine learning tasks on graphs. However, this technological breakthrough makes people wonder: how does a GNN make such decisions, and can we trust its prediction with high confidence? When it comes to some critical fields, such as biomedicine, where making wrong decisions can have severe consequences, it is crucial to interpret the inner working mechanisms of GNNs before applying them. In this paper, we propose a model-agnostic model-level explanation method for different GNNs that follow the message passing scheme, GNNInterpreter, to explain the high-level decision-making process of the GNN model. More specifically, GNNInterpreter learns a probabilistic generative graph distribution that produces the most discriminative graph pattern the GNN tries to detect when making a certain prediction by optimizing a novel objective function specifically designed for the model-level explanation for GNNs. Compared to existing works, GNNInterpreter is more flexible and computationally efficient in generating explanation graphs with different types of node and edge features, without introducing another blackbox or requiring manually specified domain-specific rules. In addition, the experimental studies conducted on four different datasets demonstrate that the explanation graphs generated by GNNInterpreter match the desired graph pattern if the model is ideal; otherwise, potential model pitfalls can be revealed by the explanation.

Additional file 1: Table S1. RDKit functions and their descriptions. Table S2. Hyperparameters for NeRD. The adjustment of hyperparameters often has an important impact on the specific data set. Table S3. Hyperparameters for DeepCDR, CDRScan, tCNNS, and GraphDRP. These models are all dual-channel or quasi-dual-channel, so the same method is used to adjust the hyperparameters. Table S4. Hyperparameters for RF. The parameters of the RF framework are few, and the parameter selection is generally to adjust the value of N\_estimators, i.e., the number of decision trees. Table S5. Hyperparameters for SVR. Gamma is the coefficient of kernel functions, only valid for `rbf', `poly', and `sigmod'. The parameter Degree only works for `kernel=poly'. C represents the penalty coefficient of the error term. The larger C is, the greater the degree of penalty for wrongly classified samples. Table S6. Hyperparameters for CNN. What we use here is the one-dimensional convolution function provided by pytorch. Table S7. Hyperparameters for MLP. The number of neurons in each layer is also fine-tuned according to the number of hidden layers. Table S8. Hyperparameters for SRMF. SRMF is a method based on matrix factorization, and its hyperparameters mainly include the dimension of the feature space and the regularization parameters. Table S9. Hyperparameters for VAE+MLP. The number of neurons in each layer is also fine-tuned according to the number of hidden layers. Table S10. Number of data instances corresponds to each data partition in the blind test. Table S11. Dataset comparison. Table S12. Blind test dividing data by similarity. Set1-Set5 are test sets with increasing similarity. Set1 has the lowest similarity and Set5 has the highest similarity. The values are the Pearson correlation coefficients. Table S13. Predicted results for the top 1\% of drug-cell lines. We used the trained NERD model to predict drug cell line pairs without IC50 data in the PRISM database, sorted from small to large according to the predicted IC50 value, and then screened the top 1\% of drug-cell line pairs (altogether 2537 pairs across 383 cancer cell lines and 91 drugs). Table S14. The drug target gene list. Based on the list of drugs obtained from the top 1\% of predicted drug-cell line pairs, we found the target genes for these drugs from the PRISM database.

Additional file 1.

Citrus polymethoxyflavones (PMFs) have attracted great research interest since the recent decade. However, the existed investigations mainly focused on the potential bioactivities of those PMFs, and paid little attention to the in vivo metabolic fates of them. Nevertheless, it was indicated by former research that the bioefficacy generated from parent compounds may contribute by their in vivo metabolites. Therefore, to explore the basic metabolic patterns of PMF compounds could in turn broaden our understanding towards the inherent mechanism of the health-beneficial roles of those PMFs.One nonnegligible pitfall of the former studies regarding the metabolism of citrus PMFs lies in that, only the demethylation reactions happened on B ring and the C-5 positions are evaluated; probably due to the difficulties in achieving A-ring metabolites (except for the 5-demethylated ones) via chemical synthesis, as well as the high numbers of methoxy groups on A ring of the most frequently investigated PMFs, nobiletin and tangeretin. In this way, sinensetin (Sin), another major citrus PMF, was selected in this study to fulfill our goal. With relatively balanced methoxy groups on both A and B rings, Sin can be treated as an excellent model compound to identify all its mono-demethylated metabolites.In the first part of this study, the two B-ring metabolites of Sin were chemically synthesized via a simplified 3-step pathway, and the 5-demethylsinensetin (5-OH Sin) was achieved via a single-step selected acidic reaction. Considering the difficulties in yielding other A-ring metabolites, the [6-D₃] Sin was synthesized as a replacement of 6-demethylsinensetin, and 6-demethylsinensetin was successfully identified in rats’ urine after the in vivo metabolism of [6-D₃] Sin. In addition, via matching parent and daughter ions with that of 5-OH Sin, the 7-demethylsinensetin was also determined by LC-MS/MS detection using MRM mode.Then, the metabolic fates of these analytes were quantitatively evaluated in urine, feces and plasma of rats after one-time oral administration of Sin at 100 mg/(kg.bw) within 48 hours. Results demonstrated that, Sin could be readily absorbed in the small intestine, and was extensively biotransformed to its metabolites in liver and gut. Besides, the 4′-demethylsinensetin, 6-demethylsinensetin and 3′-demethylsinensetin are identified as the three dominant in vivo metabolites of Sin in the three biological samples. Interestingly, only 5-OH Sin showed a synchronously higher content in feces than in urine with Sin. Moreover, the variation trends of the dynamic concentrations of Sin and 5-OH Sin in rats’ plasma also resembled each other closely, which aroused our interest towards this compound.Being the least biotransformed metabolite from Sin in urine and plasma, 5-OH Sin possessed ultra low polarity. Whereas intriguingly, superior bioactivities of the 5-demethylated PMFs to their parent counterparts has been reported by former researches. In order to uncover this mystery from the aspect of metabolism, the in vivo biotransformation of 5-OH Sin was quantitatively discovered in the second part of this study.5,3′-Didemethylsinensetin and 5,4′-didemethylsinensetin, being speculated as the two major metabolites of 5-OH Sin, were chemically synthesized as standards via a modified 4-step synthetic method. Then, pharmacokinetic and excretion studies were conducted on rats after one-time oral gavage of 5-OH Sin. Results showed that 5-OH Sin was mostly detected in feces, indicating its poor absorption in small intestine. In addition, 5,3′-didemethylsinensetin and 5,4′-didemethylsinensetin were identified as the two major metabolites of 5-OH Sin, and the C-3′ position of 5-OH Sin was more facile to be demethylated in the systemic circulation. Moreover, other than demethylation reactions, the methylation metabolism of 5-OH Sin and its metabolites were also observed in this study, suggesting the bidirectional biotransformation between 5-OH Sin and its parent compound, Sin, under in vivo conditions.Based on these findings, the significantly accumulated 5-OH Sin in gut inspired us that, 5-OH Sin may possess better colon-protective effect than Sin. In addition, the metabolic patterns of PMF compounds in experimental animals with colonic inflammation are still lacking exploration. Therefore, in the third part of this study, we evaluated the basic anti-acute colitis effects of Sin and 5-OH Sin in C57BL/6 mice, as well as their long-time metabolic fates before and during colitis after consecutive oral administration. Results indicated that the shortened colon length of mice brought from DSS-induced colitis was significantly restored by 5-OH Sin at 80 mg/(kg.bw), whereas Sin did not exhibit certain alleviating effect. Besides, the demethylation capability of gut microbiota at the C-3′ positions of PMFs declined in both Sin-treated and 5-OH Sin-treated groups after colitis modeling, suggesting the altered gut microbial structure during colonic inflammation. Interestingly, comparing to Sin-treated group, the average ratios of fewer compounds were significantly changed in 5-OH Sin-treated group after DSS treatment, implying that 5-OH Sin could probably reshape gut microbiota composition in mice with acute colitis. Furthermore, the different biotransformation pathways from parent compounds Sin and 5-OH Sin to 5,3′,4′-tridemethylsinensetin were also elucidated in this study, in detail.

Air pollution during the COVID-19 epidemic in Beijing and its surrounding regions has received substantial attention. We collected observational data, including air pollutant concentrations and meteorological parameters, during January and February from 2018 to 2021. A statistical and a numerical model were applied to identify the formation of air pollution and the impact of emission reduction on air quality. Relative humidity, wind speed, SO

Overuse of chemical fertilizers in the intensive greenhouse tomato cultivation system has limited the increase of plant production. Nowadays, seaweed extract has been gradually applied in agriculture as an effective way to achieve a higher yield of crops, but its effects on tomato cultivation have not been fully explored. In this study, a greenhouse experiment was conducted in Shandong province of China with a novel seaweed extract (SES) originated from Sargassum horneri, to investigate the effects of different doses of SES (0, 30, 60, and 90 kg hm–2) on yields, quality, ripening time, and net returns of tomato. The results indicated that the application of SES significantly increased tomato yield by 4.6–6.9% compared to the control, which is attributed to the improved photosynthetic capacity of tomato leaves. The yields of tomato increased first and then decreased with increasing dosage of SES, and SES applied at the dose of 60 kg hm–2 achieved the highest tomato yield. Compared to the control, SES at 60 and 90 kg hm–2 significantly increased the hardness of tomato by 10.2 and 19.8%, respectively, and this can help to reduce losses during transportation and storage. Moreover, SES shortened the ripening time of tomato, and the coincidence between tomato harvest and sale price peak achieved a high net return.

Fine-grained sedimentary formations occupy about two-thirds of the entire sedimentary sequences in nature. They have recently received great attention owing to the boom of shale oil and gas exploration. Unlike their coarse counterparts, detailed depositional features of fine-grained sedimentary rocks are quite difficult to recognize directly by visual inspection at core or hand specimen scales. A chemo-sedimentary facies analysis (CSFA) procedure has been developed by incorporating high-resolution (down to 30 μm) 2D elemental maps of rock slabs obtained by in situ XRF scanning with high-resolution optical images. The method enables one to unambiguously differentiate rock compositions and fine sedimentary structures and to generate core-scale chemo-sedimentary facies images. The 2D chemo-sedimentary facies map contains major elements with atomic numbers greater than 12, and some trace elements including Ba, V, Cr, Ni, Cu, Zn, Rb, Sr, Y, Zr, Nb, Mo, Th and U at individual pixels. The CSFA procedure was applied to study the Lucaogou Formation, a key shale oil producing interval in the Jimusaer Sag, Junggar Basin, NW China to illustrate three key advantages of CSFA in studying fine-grained sedimentary formations: (1) recognizing invisible sedimentary structures, (2) determining sediment provenances, (3) identifying subtle paleo environmental changes. The Lucaogou Formation has been characterized in unprecedented fine details with sedimentary heterogeneities at centimeter-millimeter scales. Seven chemo-sedimentary facies were delineated in the Lucaogou Formation. Among them, Facies CS-1 was deposited under a relatively deep, fresh to brackish water with strong energy and moist climate; Facies CS-2 was deposited under relatively shallow, brackish water with weak energy arid climate; Facies CS-6 was deposited under relatively shallow, brackish water, arid climate with intermittent hydrodynamic enhancement; Facies CS-7 was deposited in semi-deep, fresh water with strong energy and moist climate. Facies CS-1 and CS-7 have relatively high porosities. The dolomitic fragments in Facies CS-6 was originally deposited in Facies SC-2, but has higher porosities than that of Facies CS-2. Facies CS-6 and Facies CS-7 commonly occur together. The interval with well-developed. Facies CS-1, Facies CS-6 and Facies CS-7 are identified to be the most favorable exploration intervals in the Lucaogou Formation.

The middle Permian Lucaogou Formation (P2l) in the Jimusaer Sag of the southeastern Junggar Basin, NW China hosts China’s first commercial tight (shale) oil production. Two tight-oil sweet spot intervals have been identified within the P2l formation. Coupled chemostratigraphic and sedimentary facies analysis reveals that the sweet spot intervals were deposited in deep–shallow saline lacustrine to nearshore environments under an overall dry climate setting. The sweet spot intervals in the P2l formation comprises several chemostratigraphically and lithologically distinct units deposited under the influence of subtle climatic and environmental changes that have previously not been recognized. A total of 11 depositional units have been identified within the two sweet spot intervals based on an Integrated Prediction Error Filter Analysis (INFEFA) of Gamma Ray logs and environmental parameters derived from chemostratigraphic data. The tight oil reservoir sweet spot intervals were found to be controlled by the spatial and temporal distribution of total organic carbon (TOC) and reservoir properties (e.g., porosity and permeability) and source-reservoir coupling. Two potential tight oil exploration plays are recognized, including those depositional units with porous reservoir beds interbedded with high-TOC source beds (a self-generation play), and those units with porous reservoir beds adjacent to high-TOC source beds (a near-source play).

Diabetic retinopathy(DR) is the main cause of blindness in diabetic patients. However, DR can easily delay the occurrence of blindness through the diagnosis of the fundus. In view of the reality, it is difficult to collect a large amount of diabetic retina data in clinical practice. This paper proposes a few-shot learning model of a deep residual network based on Earth Mover's Distance algorithm to assist in diagnosing DR. We build training and validation classification tasks for few-shot learning based on 39 categories of 1000 sample data, train deep residual networks, and obtain experience maximization pre-training models. Based on the weights of the pre-trained model, the Earth Mover's Distance algorithm calculates the distance between the images, obtains the similarity between the images, and changes the model's parameters to improve the accuracy of the training model. Finally, the experimental construction of the small sample classification task of the test set to optimize the model further, and finally, an accuracy of 93.5667% on the 3way10shot task of the diabetic retina test set. For the experimental code and results, please refer to: https://github.com/panliangrui/few-shot-learning-funds., The article has been significantly revised

Lipo-tridecapeptides, a class of bacterial non-ribosomally produced peptides, show strong antimicrobial activity against Gram-positive pathogens, including antibiotic-resistant Staphylococcus aureus and Enterococcus spp. However, many of these lipo-tridecapeptides have shown high hemolytic activity and cytotoxicity, which has limited their potential to be developed into antibiotics. Recently, we reported a novel antimicrobial lipo-tridecapeptide, brevibacillin 2V, which showed no hemolytic activity against human red blood cells at a high concentration of 128 mg/L, opposite to other brevibacillins and lipo-tridecapeptides. In addition, brevibacillin 2V showed much lower cytotoxicity than the other members of the brevibacillin family. In this study, we set out to elucidate the antimicrobial mode of action of brevibacillin 2V. The results show that brevibacillin 2V acts as bactericidal antimicrobial agent against S. aureus (MRSA). Further studies show that brevibacillin 2V exerts its bactericidal activity by binding to the bacterial cell wall synthesis precursor Lipid II and permeabilizing the bacterial membrane. Combined solid-state NMR, circular dichroism, and isothermal titration calorimetry assays indicate that brevibacillin 2V binds to the GlcNAc-MurNAc moiety and/or the pentapeptide of Lipid II. This study provides an insight into the antimicrobial mode of action of brevibacillin 2V. As brevibacillin 2V is a novel and promising antibiotic candidate with low hemolytic activity and cytotoxicity, the here-elucidated mode of action will help further studies to develop it as an alternative antimicrobial agent.

Bacterial non-ribosomally produced peptides (NRPs) form a rich source of antibiotics, including more than 20 of these antibiotics that are used in the clinic, such as penicillin G, colistin, vancomycin, and chloramphenicol. Here we report the identification, purification, and characterization of a novel NRP, i.e., brevibacillin 2V (lipo-tridecapeptide), from Brevibacillus laterosporus DSM 25. Brevibacillin 2V has a strong antimicrobial activity against Gram-positive bacterial pathogens (minimum inhibitory concentration = 2 mg/L), including difficult-to-treat antibiotic-resistant Enterococcus faecium, Enterococcus faecalis, and Staphylococcus aureus. Notably, brevibacillin 2V has a much lower hemolytic activity (HC50 > 128 mg/L) and cytotoxicity (CC50 = 45.49 ± 0.24 mg/L) to eukaryotic cells than previously reported NRPs of the lipo-tridecapeptide family, including other brevibacillins, which makes it a promising candidate for antibiotic development. In addition, our results demonstrate that brevibacillins display a synergistic action with established antibiotics against Gram-negative bacterial pathogens. Probably due to the presence of non-canonical amino acids and D-amino acids, brevibacillin 2V showed good stability in human plasma. Thus, we identified and characterized a novel and promising antimicrobial candidate (brevibacillin 2V) with low hemolytic activity and cytotoxicity, which can be used either on its own or as a template for further total synthesis and modification.

Hypertension is a critical risk factor of cardiovascular diseases. A new concept of microbiota-gut-brain axis has been established recently, mediating the bidirectional communication between the gut and its microbiome and the brain. Alterations in bidirectional interactions are believed to be involved in the blood pressure regulation. Neuroinflammation and increased sympathetic outflow act as the descending innervation signals from the brain. Increased sympathetic activation plays a recognized role in the genesis of hypertension. The present evidence demonstrates that gut dysbiosis is associated with central nervous system neuroinflammation. However, how the gut influences the brain remains unclear. We reviewed the roles of neuroinflammation and gut microbiota and their interactions in the pathogenesis of hypertension and described the ascending signaling mechanisms behind the microbiota-gut-brain axis in detail. Additionally, the innovative prohypertensive mechanisms of dietary salt through the microbiota-gut-brain axis are summarized. The bidirectional communication mechanisms were proposed for the first time that the descending signals from the brain and the ascending connections from the gut form a vicious circle of hypertension progression, acting as a premise for hypertension therapy.

Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git

The microscopic pore structure of unconventional petroleum reservoirs, such as shale gas、 tight oil、tight gas, and so on, namely the size, geometry, distribution, and interconnected relations of the pores and throats of a shale rock, directly affects their porosity, storage, and permeability. Studies related to the microscopic pore structure of shale are considered to be attractive to evaluate the shale resource and to elucidate their distribution law; additionally, studies aim to improve the productivity and recovery ratio of both oil and gas. Therefore, methods that can be used to accurately characterize the microscopic pore structure of shale have received considerable attention. In this study, we combine electrochemical deposition and scanning electrode microscopy to characterize the microscopic pore structure of shale. Therefore, we could directly observe the three-dimensional microstructure of shale that are smaller than 50 nm with a large observing area. Additionally, the surface areas of the connected pores and throats of the shale are calculated.

In this paper, we investigate the physical layer security over the Alternate Rician Shadowed fading channel, which is a novel channel model for body-centric wireless links and land mobile satellite. We derive exact closed-form expressions for the average secrecy capacity (ASC), secrecy outage probability (SOP), and probability of non-zero secrecy capacity (PNZ) for two cases: (i) m is a positive real number and (ii) m is a positive integer number, where m describes the level of fluctuation of the line-of-sight component. In the first case, SOP is derived in terms of the Meijer's G-function, while ASC and PNZ are derived in terms of the multivariate Fox's H-function. In the second case, ASC is derived in terms of the Meijer's G-function, while SOP and PNZ are derived in terms of elementary functions. In addition, we derive the asymptotic ASC, SOP and PNZ expressions which all match well the exact ones at high values of signal-to-noise ratio, respectively. The capacity slope of asymptotic ASC and the secrecy diversity order of asymptotic SOP have been derived for providing more physical insights. Finally, the accuracy of our derived expressions is validated by Monte-Carlo simulations.

The aim of this Master’s thesis was to study the dynamic behaviour of a special type ofpedestrian timber bridge with a single diagonal arch - a design proposal made in a previousstudent project. The bridge is intended to be built as a gateway to the Alfred Nobel’s Björkbornin the municipality of Karlskoga. The original plan for this thesis was to build and test adownscaled model in order to verify theoretical investigations. The laboratory testing washowever not possible to be performed, therefore the study was conducted only by means ofanalytical and numerical tools. Both a downscaled model and a full-scale bridge model wereanalysed and compared in order to find proper scale parameters. Different studies wereperformed on the models by means of the finite element method in order to investigate theinfluence of relevant parameters on dynamic behaviour of the bridge. A scale factor wasdetermined which allows for the translation of results from the downscaled model to the fullscale model. Results showed that the dynamic behaviour of this type of bridge is rathercomplicated, and the original design needs to be somewhat modified to meet the comfortcriterion for pedestrians. An increase of the width of the arch, a proper arrangement of thecables, and adoption of longitudinal steel beams under the deck were found to be efficientmethods to improve the dynamic performance of the bridge. Future work should includeexperiments on a downscaled model to validate these theoretical solutions.

High light and high temperature (HLHT) stress induces the production of damaging reactive oxygen species (ROS) in many plants. Recently, we described a HLHT-sensitive rice (Oryza sativa) mutant, local lesions (ls1), that exhibits local lesions under HLHT, due to DNA damage and excess ROS accumulation. Here, we determined that an HLHT treatment induced the local lesion phenotype in ls1 within 6 h. Corroborating this result, we found that transient HLHT treatment influenced the expression of many genes in the ls1 mutant, while affecting the growth and development of young leaves.

A novel interpretable end-to-end learning scheme for language identification is proposed. It is in line with the classical GMM i-vector methods both theoretically and practically. In the end-to-end pipeline, a general encoding layer is employed on top of the front-end CNN, so that it can encode the variable-length input sequence into an utterance level vector automatically. After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline. We further introduce a general encoding layer, illustrating the reason why they might be appropriate for language identification. We elaborate on several typical encoding layers, including a temporal average pooling layer, a recurrent encoding layer and a novel learnable dictionary encoding layer. We conducted experiment on NIST LRE07 closed-set task, and the results show that our proposed end-to-end systems achieve state-of-the-art performance., ICASSP 2018 conference paper

Objective To investigate the role and action mechanism of Ganshuang granules in the protection against CCl4-induced chronic liver injury in mice via autophagy, and to provide a basis for its clinical application. Methods We established a chronic liver injury model in mice by intraperitoneal injection of CCl4, and a cell model of liver damage in cell line HL-7702 induced by CCl4 in vitro. The animals were divided into three groups, Ganshuang granule intervention group, normal control group, and CCl4 group without receiving Ganshuang granules. In addition, we exposed the cells to 3-methyladenine (3-MA), an autophagy inhibitor, and observed the effects of Ganshuang granules on cell apoptosis. Liver tissue injury was evaluated by HE staining; serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were determined by biochemical assays. Autophagy was assessed by immunofluorescence staining and Western blotting. Liver apoptosis was analyzed by flow cytometry and Annexin V/PI double staining. Comparisons between groups were performed using analysis of variance. Results HE staining showed that liver tissue injury was significantly milder in the Ganshuang granule intervention group than in the CCl4 group. Serum ALT and AST levels were significantly differences between Ganshuang granule intervention group, normal control group, and CCl4 group (F=15.76、13.35，P＜0.05). Both in vivo and in vitro tests showed that autophagy increased significantly in cells treated with Ganshuang granules than in cells exposed to CCl4 alone, while apoptosis was significantly reduced in the former. The administration of 3-MA weakened the protective effect of Ganshuang granules and increased apoptosis. Flow cytometry showed that apoptosises were significiantly differences between five groups (F=25.637,P＜0.01). Conclusion Ganshuang granules have protective effects against chronic liver injury by inhibiting apoptosis, possibly through enhanced autophagy.

Following North America, shale gas has been proved to be a success in China, considering the commercial exploitation of shale gas in Sichuan province in China, and a continuous increase in the past few years and a good momentum in the next few years. This mainly attributes to the horizontal drilling and multistage hydraulic fracturing technologies and huge capital investment. However, we need to face that even using these advanced technologies, a sharp decrease of the production during the development still exists in all shale gas wells, due to the tightness of the shale matrix and the pressure drop in the fracture network. According to the successful experience of enhanced coalbed methane recovery all over the world, CO2 injection shows a promising future in EGR (enhanced gas recovery) process for shale reservoirs. In the meanwhile, CO2 can be simultaneously sealed underground to reduce pollution. Therefore, in order to guide the engineering process, it is of great importance to reveal the CO2 and CH4 absorption behaviors at microscopic scale,but the corresponding mechanism is as yet unclear. This is because the competitive adsorption process of CO2 and CH4 underground can be affected by a lot of parameters, such as pore size, temperature, pressure, CO2 concentration, etc., and laboratory experiment is usually difficult to carry out, due to limited laboratory temperature and pressure conditions, and difficulty in separating porous OM from shale, etc. In this paper, we employ molecular simulation of CO2-CH4 competitive adsorption behavior in organic matter (OM) nano pores. Using Longmaxi shale as sample, OM pore structure was first characterized using FIB-SEM and scanning ion microscope, and pore-size distribution was studied using N2 adsorption. Then a simplified pillar-layer model was used to study CH4 adsorption behavior and competitive adsorption effect between CO2 and CH4, using grand canonical Monte Carlo (GCMC) method. Results indicate that nanopores with good connectivity widely exist in OM, offering important storage space for absorbed shale gas. The amount of adsorbed CH4 can increase with lower temperature and increased pressure, and overpressure will significantly increase the amount of CH4 adsorbed underground; CO2 shows high competitive adsorption ability; CO2/CH4 selectivity coefficient decreases dramatically with increasing temperature or pressure, or both, and it corresponds to deeper burial depth. CO2 EGR during shale gas exploration will be more efficient, if it is conducted after the pressure drops to a certain degree.

Recent morphological and molecular evidence has challenged classical interpretations of eubrachyuran phylogeny and evolution. Complete mitochondrial genomes of two species of potamid freshwater crabs, Sinopotamon yaanense and Sinopotamon yangtsekiense were obtained using next-generation sequencing. The results revealed a novel gene order with translocations of a five-gene block and a tRNA gene in comparison to available brachyuran mitochondrial genomes. DNA sequence comparisons position the Potamidae, a primary freshwater crab family, outside of the clade for the traditional heterotreme families, and closer to the clade that includes the thoracotreme families of grapsoid and ocypodoid crabs. Mitogenomic comparisons using rapid next-generation sequencing and a much wider taxonomic sample are required for a high-resolution examination of the phylogenetic relationships within the Eubrachyura.