Explore the vast range of titles available.

Phylogenetic analysis has entered the genomics (multilocus) era. For less experienced researchers, conquering the large number of software programs required for a multilocus‐based phylogenetic reconstruction can be somewhat daunting and time‐consuming. PhyloSuite, a software with a user‐friendly GUI, was designed to make this process more accessible by integrating multiple software programs needed for multilocus and single‐gene phylogenies and further streamlining the whole process. In this protocol, we aim to explain how to conduct each step of the phylogenetic pipeline and tree‐based analyses in PhyloSuite. We also present a new version of PhyloSuite (v1.2.3), wherein we fixed some bugs, made some optimizations, and introduced some new functions, including a number of tree‐based analyses, such as signal‐to‐noise calculation, saturation analysis, spurious species identification, and etc. The step‐by‐step protocol includes background information (i.e., what the step does), reasons (i.e., why do the step), and operations (i.e., how to do it). This protocol will help researchers quick‐start their way through the multilocus phylogenetic analysis, especially those interested in conducting organelle‐based analyses. A new release of PhyloSuite, capable of conducting tree‐based analyses. Detailed guidelines for each step of phylogenetic and tree‐based analyses, following the “What? Why? and How?” structure. This protocol will help beginners learn how to conduct multilocus phylogenetic analyses and help experienced scientists improve their efficiency. Highlights A new release of PhyloSuite, capable of conducting tree‐based analyses. Detailed guidelines for each step of phylogenetic and tree‐based analyses, following the “What, Why, and How” structure. This protocol will help beginners learn how to conduct multilocus phylogenetic analyses and help experienced scientists improve their efficiency.

Background Within the class Enoplea, the earliest-branching lineages in the phylum Nematoda, the relatively highly conserved ancestral mitochondrial architecture of Trichinellida is in stark contrast to the rapidly evolving architecture of Dorylaimida and Mermithida. To better understand the evolution of mitogenomic architecture in this lineage, we sequenced the mitogenome of a fish parasite Pseudocapillaria tomentosa (Trichinellida: Capillariidae) and compared it to all available enoplean mitogenomes. Results P. tomentosa exhibited highly reduced noncoding regions (the largest was 98 bp), and a unique base composition among the Enoplea. We attributed the latter to the inverted GC skew (0.08) in comparison to the ancestral skew in Trichinellidae (-0.43 to -0.37). Capillariidae, Trichuridae and Longidoridae (Dorylaimida) generally exhibited low negative or low positive skews (-0.1 to 0.1), whereas Mermithidae exhibited fully inverted low skews (0 to 0.05). This is indicative of inversions in the strand replication order or otherwise disrupted replication mechanism in the lineages with reduced/inverted skews. Among the Trichinellida, Trichinellidae and Trichuridae have almost perfectly conserved architecture, whereas Capillariidae exhibit multiple rearrangements of tRNA genes. In contrast, Mermithidae (Mermithida) and Longidoridae (Dorylaimida) exhibit almost no similarity to the ancestral architecture. Conclusions Longidoridae exhibited more rearranged mitogenomic architecture than the hypervariable Mermithidae. Similar to the Chromadorea, the evolution of mitochondrial architecture in enoplean nematodes exhibits a strong discontinuity: lineages possessing a mostly conserved architecture over tens of millions of years are interspersed with lineages exhibiting architectural hypervariability. As Longidoridae also have some of the smallest metazoan mitochondrial genomes, they contradict the prediction that compact mitogenomes should be structurally stable. Lineages exhibiting inverted skews appear to represent the intermediate phase between the Trichinellidae (ancestral) and fully derived skews in Chromadorean mitogenomes (GC skews = 0.18 to 0.64). Multiple lines of evidence (CAT-GTR analysis in our study, a majority of previous mitogenomic results, and skew disruption scenarios) support the Dorylaimia split into two sister-clades: Dorylaimida + Mermithida and Trichinellida. However, skew inversions produce strong base composition biases, which can hamper phylogenetic and other evolutionary studies, so enoplean mitogenomes have to be used with utmost care in evolutionary studies.

Background Gyrodactylus is a lineage of monogenean flatworm ectoparasites exhibiting many features that make them a suitable model to study the host-parasite coevolutionary dynamics. Previous coevolutionary studies of this lineage mainly relied on low-power datasets (a small number of samples and a single molecular marker) and (now) outdated algorithms. Methods To investigate the coevolutionary relationship of gyrodactylids and their fish hosts in high resolution, we used complete mitogenomes (including two newly sequenced Gyrodactylus species), a large number of species in the single-gene dataset, and four different coevolutionary algorithms. Results The overall coevolutionary fit between the parasites and hosts was consistently significant. Multiple indicators confirmed that gyrodactylids are generally highly host-specific parasites, but several species could parasitize either multiple (more than 5) or phylogenetically distant fish hosts. The molecular dating results indicated that gyrodactylids tend to evolve towards high host specificity. Speciation by host switch was identified as a more important speciation mode than co-speciation. Assuming that the ancestral host belonged to Cypriniformes, we inferred four major host switch events to non-Cypriniformes hosts (mostly Salmoniformes), all of which occurred deep in the evolutionary history. Despite their relative rarity, these events had strong macroevolutionary consequences for gyrodactylid diversity. For example, in our dataset, 57.28% of all studied gyrodactylids parasitized only non-Cypriniformes hosts, which implies that the evolutionary history of more than half of all included lineages could be traced back to these major host switch events. The geographical co-occurrence of fishes and gyrodactylids determined the host use by these gyrodactylids, and geography accounted for most of the phylogenetic signal in host use. Conclusions Our findings suggest that the coevolution of Gyrodactylus flatworms and their hosts is largely driven by geography, phylogeny, and host switches. Graphical Abstract

The host‐parasite arms race involves complex molecular crosstalk mediated by protein–protein interactions (PPIs). Bioinformatic analyses can be used to predict both host‐parasite PPIs and potential drug targets in parasite genomes, but high‐quality genomic data remain scarce for parasitic monogenean flatworms. Herein, an experimental lineage of Gyrodactylus kobayashii (Monopisthocotylea: Gyrodactylidae) is set up on goldfish hosts and used to conduct phased genome assembly using long‐range PacBio HiFi and Hi‐C technologies. In silico analyses of genomes of three Gyrodactylus species identified innexins as the most promising novel drug candidate genes. Drug screening and experimental verification singled out Imatinib as the most promising drug targeting innexins, with a high efficiency against G. kobayashii (100% mortality at 25 µM within 6 h in vitro) and low toxicity to the host. Prediction of PPIs in three Gyrodactylus‐host pairs revealed proteins associated with cAMP‐dependent signaling as key candidates, including the host's PRKACB and the parasite's PRKAR2A, RAP1A, ULK2, and Catenin Beta‐2. Two interacting G proteins are also identified: GNAO1 and GNB5. As the first high‐quality phased chromosome‐level genomic assembly for “monogeneans” and the first identification of PPIs in a fish‐parasite system, this study significantly advances the understanding of host‐parasite interactions at the genomic level. Genomic data offer a powerful tool for studying the molecular interactions between parasites and their hosts, but they remain scarce for parasitic monogenean flatworms. This study presents the first high‐quality phased genome assembly for monogeneans (Gyrodactylus kobayashii), and uses it to predict key interacting proteins between monogenean parasite ‐ fish host pairs, and identify novel drug targets.

New types of antimicrobial systems are urgently needed owing to the emergence of pathogenic microbial strains that gain resistance to antibiotics commonly used in daily life and medical care. In this study we developed for the first time a broad-spectrum and robust antimicrobial thin film coating based on large-area chemical vapor deposition （CVD）-grown graphene-wrapped silver nanowires （AgNWs）. The antimicrobial graphene/AgNW hybrid coating can be applied on commerdal flexible transparent ethylene vinyl acetate/polyethylene terephthalate （EVA/PET） plastic films by a full roll-to-roll process. The graphene/AgNW hybrid coating showed broad-spectrum antimicrobial activity against Gram-negative （Escherichia coli） and Gram-positive bacteria （Staphylococcus aureus）, and fungi （Candida albicans）. This effect was attributed to a weaker microbial attachment to the ultra-smooth graphene film and the sterilization capacity of Ag＋, which is sustainably released from the AgNWs and presumably enhanced by the electrochemical corrosion of AgNWs. Moreover, the robust antimicrobial activity of the graphene/AgNW coating was reinforced by AgNW encapsulation by graphene. Furthermore, the antimicrobial efficiency could be enhanced to -100% by water electrolysis by using the conductive graphene/AgNW coating as a cathode. We developed a transparent and flexible antimicrobial cover made of graphene/AgNW/EVA/PET and an antimicrobial denture coated by graphene/ AgNW, to show the potential applications of the antimicrobial materials.

Some unavoidable factors in the process of cold strip shape measurement interfere with the shape meter, so the shape measuring results cannot reflect the true shape of the strip and the measuring precision is low. The influences of the measuring error of the strip edges, the transverse temperature difference of the strip, the deflection of shape detection roller, and the shape of the strip coil on the shape measuring results were analyzed in detail, and the corresponding compensation models were established. The simulation calculation and analysis were carried out on a cold strip mill, and a number of disciplinarian cognitions were obtained.

Insect pest recognition has always been a significant branch of agriculture and ecology. The slight variance among different kinds of insects in appearance makes it hard for human experts to recognize. It is increasingly imperative to finely recognize specific insects by employing machine learning methods. In this study, we proposed a feature fusion network to synthesize feature presentations in different backbone models. Firstly, we employed one CNN-based backbone ResNet, and two attention-based backbones Vision Transformer and Swin Transformer to localize the important regions of insect images with Grad-CAM. During this process, we designed new architectures for these two Transformers to enable Grad-CAM to be applicable in such attention-based models. Then we further proposed an attention-selection mechanism to reconstruct the attention area by delicately integrating the important regions, enabling these partial but key expressions to complement each other. We only need part of the image scope that represents the most crucial decision-making information for insect recognition. We randomly selected 20 species of insects from the IP102 dataset and then adopted all 102 kinds of insects to test the classification performance. Experimental results show that the proposed approach outperforms other advanced CNN-based models. More importantly, our attention-selection mechanism demonstrates good robustness to augmented images.

High‐performance polymers have proliferated in modern society across a variety of industries because of their low density, good chemical stability, and superior mechanical properties. However, while polymers are widely applied, frequent fire disasters induced by their intrinsic flammability have caused massive impacts on human beings, the economy, and the environment. Supramolecular chemistry has recently been intensively researched to provide fire retardancy for polymers via the physical barrier and char‐catalyzing effects of supramolecular aggregates. In parallel, the noncovalent interactions between supramolecular and polymer chains, such as hydrogen bonding, π–π interactions, metal–ligand coordination, and synergistic interactions, can endow the matrix with enhanced mechanical strength. This makes it possible to integrate physical–chemical properties and noncovalent interactions into one supramolecular aggregate‐based high‐performance polymeric system on demand. However, fulfilling these promises needs more research. Here, we provide an overview of the latest research advances of fire‐retardant and high‐strength polymer materials based on supramolecular structures and interactions of aggregates. This work reviews their conceptual design, characterization, modification principles, performances, applications, and mechanisms. Finally, development challenges and perspectives on future research are also discussed. This work provides an overview of fire‐retardant and high‐strength polymer materials based on supramolecular structures and interactions of aggregates, including their conceptual design, characterization, modification principles, performances, applications, mechanisms, challenges, and future perspectives.

Glycolytic enzyme phosphoglycerate mutase 1 (PGAM1) plays a critical role in cancer metabolism by coordinating glycolysis and biosynthesis. A well-validated PGAM1 inhibitor, however, has not been reported for treating pancreatic ductal adenocarcinoma (PDAC), which is one of the deadliest malignancies worldwide. By uncovering the elevated PGAM1 expressions were statistically related to worse prognosis of PDAC in a cohort of 50 patients, we developed a series of allosteric PGAM1 inhibitors by structureguided optimization. The compound KH3 significantly suppressed proliferation of various PDAC cells by down-regulating the levels of glycolysis and mitochondrial respiration in correlation with PGAM1 expression. Similar to PGAM1 depletion, KH3 dramatically hampered the canonic pathways highly involved in cancer metabolism and development. Additionally, we observed the shared expression profiles of several signature pathways at 12 h after treatment in multiple PDAC primary cells of which the matched patient-derived xenograft (PDX) models responded similarly to KH3 in the 2 wk treatment. The better responses to KH3 in PDXs were associated with higher expression of PGAM1 and longer/stronger suppressions of cancer metabolic pathways. Taken together, our findings demonstrate a strategy of targeting cancer metabolism by PGAM1 inhibition in PDAC. Also, this work provided “proof of concept” for the potential application of metabolic treatment in clinical practice.