Effect of Fe and Zn co-doping on LiCoPO4 cathode materials for High-Voltage Lithium-Ion batteries.

Lithium cobalt phosphate (LiCoPO4) has great potential to be developed as a cathode material for lithium-ion batteries (LIBs) due to its structural stability and higher voltage platform with a high theoretical energy density. However, the relatively low diffusion of lithium ions still needs to be improved. In this work, Fe and Zn co-doped LiCoPO4: LiCo0.9-xFe0.1ZnxPO4/C is utilized to enhance the battery performance of LiCoPO4. The electrochemical properties of LiCo0.85Fe0.1Zn0.05PO4/C demonstrated an initial capacity of 118 mAh/g, with 93.4 % capacity retention at 1C after 100 cycles, and a good capacity of 87 mAh/g remained under a high current density of 10C. In addition, the diffusion rate of Li ions was investigated, proving the improvement of the materials with doping. The impedance results also showed a smaller resistance of the doped materials. Furthermore, operando X-ray diffraction displayed a good reversibility of the structural transformation, corresponding to cycling stability. This work provided studies of both the electrochemical properties and structural transformation of Fe and Zn co-doped LiCoPO4, which showed that 10 % Fe and 5 % Zn co-doping enhanced the electrochemical performance of LiCoPO4 as a cathode material in LIBs.

Text2Face: Text-based Face Generation with Geometry and Appearance Control.

Recent years have witnessed the emergence of various techniques proposed for text-based human face generation and manipulation. Such methods, targeting bridging the semantic gap between text and visual contents, provide users with a deft hand to turn ideas into visuals via text interface and enable more diversified multimedia applications. However, due to the flexibility of linguistic expressiveness, the mapping from sentences to desired facial images is clearly many-to-many, causing ambiguities during text-to-face generation. To alleviate these ambiguities, we introduce a local-to-global framework with two graph neural networks (one for geometry and the other for appearance) embedded to model the inter-dependency among facial parts. This is based upon our key observation that the geometry and appearance attributes among different facial components are not mutually independent, i.e., the combinations of part-level facial features are not arbitrary and thus do not conform to a uniform distribution. By learning from the dataset distribution and enabling recommendations given partial descriptions of human faces, these networks are highly suitable for our text-to-face task. Our method is capable of generating high-quality attribute-conditioned facial images from text. Extensive experiments have confirmed the superiority and usability of our method over the prior art.

How Modulator Binding at the Amyloidß-γ-Secretase Interface Enhances Substrate Binding and Attenuates Membrane Distortion.

Inhibition of γ-secretase, an intramembrane protease, to reduce secretion of Amyloid-ß (Aß) peptides has been considered for treating Alzheimer's disease. However, γ-secretase inhibitors suffer from severe side effects. As an alternative, γ-secretase modulators (GSM) reduce the generation of toxic peptides by enhancing the cleavage processivity without diminishing the enzyme activity. Starting from a known γ-secretase structure without substrate but in complex with an E2012 GSM, we generated a structural model that included a bound Aß43 peptide and studied interactions among enzyme, substrate, GSM, and lipids. Our result suggests that E2012 binding at the enzyme-substrate-membrane interface attenuates the membrane distortion by shielding the substrate-membrane interaction. The model predicts that the E2012 modulation is charge-dependent and explains the preserved hydrogen acceptor and the aromatic ring observed in many imidazole-based GSM. Predicted effects of γ-secretase mutations on E2012 modulation were confirmed experimentally. We anticipate that the study will facilitate the future development of effective GSMs.

APP substrate ectodomain defines amyloid-ß peptide length by restraining γ-secretase processivity and facilitating product release.

Sequential proteolysis of the amyloid precursor protein (APP) by γ-secretases generates amyloid-ß (Aß) peptides and defines the proportion of short-to-long Aß peptides, which is tightly connected to Alzheimer's disease (AD) pathogenesis. Here, we study the mechanism that controls substrate processing by γ-secretases and Aß peptide length. We found that polar interactions established by the APPC99 ectodomain (ECD), involving but not limited to its juxtamembrane region, restrain both the extent and degree of γ-secretases processive cleavage by destabilizing enzyme-substrate interactions. We show that increasing hydrophobicity, via mutation or ligand binding, at APPC99 -ECD attenuates substrate-driven product release and rescues the effects of Alzheimer's disease-associated pathogenic γ-secretase and APP variants on Aß length. In addition, our study reveals that APPC99 -ECD facilitates the paradoxical production of longer Aßs caused by some γ-secretase inhibitors, which act as high-affinity competitors of the substrate. These findings assign a pivotal role to the substrate ECD in the sequential proteolysis by γ-secretases and suggest it as a sweet spot for the potential design of APP-targeting compounds selectively promoting its processing by these enzymes.

LC-NeRF: Local Controllable Face Generation in Neural Radiance Field.

3D face generation has achieved high visual quality and 3D consistency thanks to the development of neural radiance fields (NeRF). However, these methods model the whole face as a neural radiance field, which limits the controllability of the local regions. In other words, previous methods struggle to independently control local regions, such as the mouth, nose, and hair. To improve local controllability in NeRF-based face generation, we propose LC-NeRF, which is composed of a Local Region Generators Module (LRGM) and a Spatial-Aware Fusion Module (SAFM), allowing for geometry and texture control of local facial regions. The LRGM models different facial regions as independent neural radiance fields and the SAFM is responsible for merging multiple independent neural radiance fields into a complete representation. Finally, LC-NeRF enables the modification of the latent code associated with each individual generator, thereby allowing precise control over the corresponding local region. Qualitative and quantitative evaluations show that our method provides better local controllability than state-of-the-art 3D-aware face generation methods. A perception study reveals that our method outperforms existing state-of-the-art methods in terms of image quality, face consistency, and editing effects. Furthermore, our method exhibits favorable performance in downstream tasks, including real image editing and text-driven facial image editing.

Enzyme-substrate hybrid ß-sheet controls geometry and water access to the γ-secretase active site.

γ-Secretase is an aspartyl intramembrane protease that cleaves the amyloid precursor protein (APP) involved in Alzheimer's disease pathology and other transmembrane proteins. Substrate-bound structures reveal a stable hybrid ß-sheet immediately following the substrate scissile bond consisting of ß1 and ß2 from the enzyme and ß3 from the substrate. Molecular dynamics simulations and enhanced sampling simulations demonstrate that the hybrid ß-sheet stability is strongly correlated with the formation of a stable cleavage-compatible active geometry and it also controls water access to the active site. The hybrid ß-sheet is only stable for substrates with 3 or more C-terminal residues beyond the scissile bond. The simulation model allowed us to predict the effect of Pro and Phe mutations that weaken the formation of the hybrid ß-sheet which were confirmed by experimental testing. Our study provides a direct explanation why γ-secretase preferentially cleaves APP in steps of 3 residues and how the hybrid ß-sheet facilitates γ-secretase proteolysis.

A Chemical Proteomic Strategy Reveals Inhibitors of Lipoate Salvage in Bacteria and Parasites.

The development of novel anti-infectives requires unprecedented strategies targeting pathways which are solely present in pathogens but absent in humans. Following this principle, we developed inhibitors of lipoic acid (LA) salvage, a crucial pathway for the survival of LA auxotrophic bacteria and parasites but non-essential in human cells. An LA-based probe was selectively transferred onto substrate proteins via lipoate protein ligase (LPL) in intact cells, and their binding sites were determined by mass spectrometry. Probe labeling served as a proxy of LPL activity, enabling in situ screenings for cell-permeable LPL inhibitors. Profiling a focused compound library revealed two substrate analogs (LAMe and C3) as inhibitors, which were further validated by binding studies and co-crystallography. Importantly, LAMe exhibited low toxicity in human cells and achieved killing of Plasmodium falciparum in erythrocytes with an EC50 value of 15 µM, making it the most effective LPL inhibitor reported to date.

What Makes a Good Protein-Protein Interaction Stabilizer: Analysis and Application of the Dual-Binding Mechanism.

Protein-protein interactions (PPIs) are essential for biological processes including immune reactions and diseases. Inhibition of PPIs by drug-like compounds is a common basis for therapeutic approaches. In many cases the flat interface of PP complexes prevents discovery of specific compound binding to cavities on one partner and PPI inhibition. However, frequently new pockets are formed at the PP interface that allow accommodation of stabilizers which is often as desirable as inhibition but a much less explored alternative strategy. Herein, we employ molecular dynamics simulations and pocket detection to investigate 18 known stabilizers and associated PP complexes. For most cases, we find that a dual-binding mechanism, a similar stabilizer interaction strength with each protein partner, is an important prerequisite for effective stabilization. A few stabilizers follow an allosteric mechanism by stabilizing the protein bound structure and/or increase the PPI indirectly. On 226 protein-protein complexes, we find in >75% of the cases interface cavities suitable for binding of drug-like compounds. We propose a computational compound identification workflow that exploits new PP interface cavities and optimizes the dual-binding mechanism and apply it to 5 PP complexes. Our study demonstrates a great potential for in silico PPI stabilizers discovery with a wide range of therapeutic applications.

Keyframe Control of Music-driven 3D Dance Generation.

For 3D animators, choreography with artificial intelligence has attracted more attention recently. However, most existing deep learning methods mainly rely on music for dance generation and lack sufficient control over generated dance motions. To address this issue, we introduce the idea of keyframe interpolation for music-driven dance generation and present a novel transition generation technique for choreography. Specifically, this technique synthesizes visually diverse and plausible dance motions by using normalizing flows to learn the probability distribution of dance motions conditioned on a piece of music and a sparse set of key poses. Thus, the generated dance motions respect both the input musical beats and the key poses. To achieve a robust transition of varying lengths between the key poses, we introduce a time embedding at each timestep as an additional condition. Extensive experiments show that our model generates more realistic, diverse, and beat-matching dance motions than the compared state-of-the-art methods, both qualitatively and quantitatively. Our experimental results demonstrate the superiority of the keyframe-based control for improving the diversity of the generated dance motions.

Identity-Aware and Shape-Aware Propagation of Face Editing in Videos.

The development of deep generative models has inspired various facial image editing methods, but many of them are difficult to be directly applied to video editing due to various challenges ranging from imposing 3D constraints, preserving identity consistency, ensuring temporal coherence, etc. To address these challenges, we propose a new framework operating on the StyleGAN2 latent space for identity-aware and shape-aware edit propagation on face videos. In order to reduce the difficulties of maintaining the identity, keeping the original 3D motion, and avoiding shape distortions, we disentangle the StyleGAN2 latent vectors of human face video frames to decouple the appearance, shape, expression, and motion from identity. An edit encoding module is used to map a sequence of image frames to continuous latent codes with 3D parametric control and is trained in a self-supervised manner with identity loss and triple shape losses. Our model supports propagation of edits in various forms: I. direct appearance editing on a specific keyframe, II. implicit editing of face shape via a given reference image, and III. existing latent-based semantic edits. Experiments show that our method works well for various forms of videos in the wild and outperforms an animation-based approach and the recent deep generative techniques.

Reference-Based Deep Line Art Video Colorization.

Coloring line art images based on the colors of reference images is a crucial stage in animation production, which is time-consuming and tedious. This paper proposes a deep architecture to automatically color line art videos with the same color style as the given reference images. Our framework consists of a color transform network and a temporal refinement network based on 3U-net. The color transform network takes the target line art images as well as the line art and color images of the reference images as input and generates corresponding target color images. To cope with the large differences between each target line art image and the reference color images, we propose a distance attention layer that utilizes non-local similarity matching to determine the region correspondences between the target image and the reference images and transforms the local color information from the references to the target. To ensure global color style consistency, we further incorporate Adaptive Instance Normalization (AdaIN) with the transformation parameters obtained from a multiple-layer AdaIN that describes the global color style of the references extracted by an embedder network. The temporal refinement network learns spatiotemporal features through 3D convolutions to ensure the temporal color consistency of the results. Our model can achieve even better coloring results by fine-tuning the parameters with only a small number of samples when dealing with an animation of a new style. To evaluate our method, we build a line art coloring dataset. Experiments show that our method achieves the best performance on line art video coloring compared to the current state-of-the-art methods.

DrawingInStyles: Portrait Image Generation and Editing With Spatially Conditioned StyleGAN.

The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques. The recently proposed StyleGAN architectures achieve state-of-the-art generation ability but the original StyleGAN is not friendly for sketch-based creation due to its unconditional generation nature. To address this issue, we propose a direct conditioning strategy to better preserve the spatial information under the StyleGAN framework. Specifically, we introduce Spatially Conditioned StyleGAN (SC-StyleGAN for short), which explicitly injects spatial constraints to the original StyleGAN generation process. We explore two input modalities, sketches and semantic maps, which together allow users to express desired generation results more precisely and easily. Based on SC-StyleGAN, we present DrawingInStyles, a novel drawing interface for non-professional users to easily produce high-quality, photo-realistic face images with precise control, either from scratch or editing existing ones. Qualitative and quantitative evaluations show the superior generation ability of our method to existing and alternative solutions. The usability and expressiveness of our system are confirmed by a user study.

The Effectiveness of a Critical Appraisal Skills Workshop 6 Months After Nurses' Participation.

Background The aim of this study was to explore whether nursing staff retained knowledge, self-confidence, and attitudes 6 months after participating in a critical appraisal skills workshop. Method A retrospective matched case-control study was conducted to ascertain the effects of this training on the ability to appraise literature. Results Mean scores on the critical appraisal knowledge test, self-confidence, and attitudes were significantly higher in the case group compared to the control group (p < .001, p < .05, and p = .031, respectively). Conclusion Six months after the workshop, critical appraisal knowledge, self-confidence, and attitudes remained improved among the nursing staff who participated. This indicates that the workshop was effective for learning and can be used for clinical training. [J Contin Educ Nurs. 2022;53(8):372-378.].

Population genetics and genetic variation of Ctenocephalides felis and Pulex irritans in China by analysis of nuclear and mitochondrial genes.

BACKGROUND: Fleas are the most economically significant blood-feeding ectoparasites worldwide. Ctenocephalides felis and Pulex irritans can parasitize various animals closely related to humans and are of high veterinary significance. METHODS: In this study, 82 samples were collected from 7 provinces of China. Through studying the nuclear genes ITS1 and EF-1α and two different mitochondrial genes cox1 and cox2, the population genetics and genetic variation of C. felis and P. irritans in China were further investigated. RESULTS: The intraspecies differences between C. felis and P. irritans ranged from 0 to 3.9%. The interspecific variance in the EF-1α, cox1, and cox2 sequences was 8.2-18.3%, while the ITS1 sequence was 50.1-52.2%. High genetic diversity was observed in both C. felis and P. irritans, and the nucleotide diversity of cox1 was higher than that of cox2. Moderate gene flow was detected in the C. felis and P. irritans populations. Both species possessed many haplotypes, but the haplotype distribution was uneven. Fu's Fs and Tajima's D tests showed that C. felis and P. irritans experienced a bottleneck effect in Guangxi Zhuang Autonomous Region and Henan province. Evolutionary analysis suggested that C. felis may have two geographical lineages in China, while no multiple lineages of P.irritans were found. CONCLUSIONS: Using sequence comparison and the construction of phylogenetic trees, we found a moderate amount of gene flow in the C. felis and P. irritans populations. Both species possessed many haplotypes, but the distribution of haplotypes varied among the provinces. Fu's Fs and Tajima's D tests indicated that both species had experienced a bottleneck effect in Guangxi and Henan provinces. Evolutionary analysis suggested that C. felis may have two geographical lineages in China, while no multiple lineages of P.irritans were found. This study will help better understand fleas' population genetics and evolutionary biology.

Active site geometry stabilization of a presenilin homolog by the lipid bilayer promotes intramembrane proteolysis.

Cleavage of membrane proteins in the lipid bilayer by intramembrane proteases is crucial for health and disease. Although different lipid environments can potently modulate their activity, how this is linked to their structural dynamics is unclear. Here, we show that the carboxy-peptidase-like activity of the archaeal intramembrane protease PSH, a homolog of the Alzheimer's disease-associated presenilin/γ-secretase is impaired in micelles and promoted in a lipid bilayer. Comparative molecular dynamics simulations revealed that important elements for substrate binding such as transmembrane domain 6a of PSH are more labile in micelles and stabilized in the lipid bilayer. Moreover, consistent with an enhanced interaction of PSH with a transition-state analog inhibitor, the bilayer promoted the formation of the enzyme's catalytic active site geometry. Our data indicate that the lipid environment of an intramembrane protease plays a critical role in structural stabilization and active site arrangement of the enzyme-substrate complex thereby promoting intramembrane proteolysis.

Cutting proteins into pieces is a crucial process in the cell, allowing several important processes to take place, including cell differentiation (which allows cells to develop into specific types), cell death, protein quality control, or even where in the cell a protein will end up. However, the specialized proteins that carry out this task, known as proteases, can also be involved in the development of disease. For example, in the brain, a protease called γ-secretase cuts up the amyloid-ß protein precursor, producing toxic forms of amyloid-ß peptides that are widely believed to cause Alzheimer's disease. Proteases like γ-secretase carry out their role in the membrane, the layer of fats (also known as lipids) that forms the outer boundary of the cell. The environment in this area of the cell can influence the activity of proteases, but it is poorly understood how this happens. One way to address this question would be to compare the activity of γ-secretase in the lipid environment of the membrane to its activity when it is entirely surrounded by different molecules, such as detergent molecules. Unfortunately, γ-secretase is not active when it is removed from its lipid environment by a detergent, making it difficult to perform this comparison. To overcome this issue, Feilen et al. chose to study PSH, a protease similar to γ-secretase that produces the same amyloid-ß peptides but remains active in detergent. When Feilen et al. mixed PSH with lipid molecules like those found in the membrane and amyloid-ß precursor protein, PSH produced amyloid-ß peptides including those that are thought to cause Alzheimer's. However, when a detergent was substituted for the lipid molecules this led to longer amyloid-ß peptides than usual, indicating that PSH was not able to cut proteins as effectively. The change in environment appeared to reduce PSH's ability to progressively trim small segments from the peptides. Computer modelling of the protease's structure in lipids versus detergent supported the experimental findings: the model predicted that the areas of PSH important for recognizing and cutting other proteins would be more stable in the membrane compared to the detergent. These results indicate that the cell membrane plays a vital role in the stability of the active regions of proteases that are cleaving in this environment. In the future, this could help to better understand how changes to the lipid molecules in the membrane may contribute to the activity of γ-secretase and its role in Alzheimer's disease.

An internal docking site stabilizes substrate binding to γ-secretase: Analysis by molecular dynamics simulations.

Amyloid precursor protein (APP) is cleaved and processed sequentially by γ-secretase yielding amyloid ß (Aß) peptides of different lengths. Longer Aß peptides are associated with the formation of neurotoxic plaques related to Alzheimer's disease. Based on the APP substrate-bound structure of γ-secretase, we investigated the enzyme-substrate interaction using molecular dynamics simulations and generated model structures that represent the sequentially cleaved intermediates during the processing reaction. The simulations indicated an internal docking site providing strong enzyme-substrate packing interaction. In the enzyme-substrate complex, it is located close to the region where the helical conformation of the substrate is interrupted and continues toward the active site in an extended conformation. The internal docking site consists of two non-polar pockets that are preferentially filled by large hydrophobic or aromatic substrate side chains to stabilize binding. Placement of smaller residues such as glycine can trigger a shift in the cleavage pattern during the simulations or results in destabilization of substrate binding. The reduced packing by smaller residues also influences the hydration of the active site and the formation of a catalytically active state. The simulations on processed substrate intermediates and a substrate G33I mutation offer an explanation of the experimentally observed relative increase of short Aß fragment production for this mutation. In addition, studies on a substrate K28A mutation indicate that the internal docking site opposes the tendency of substrate dissociation due to a hydrophobic mismatch at the membrane boundary caused by K28 during processing and substrate movement toward the enzyme active site. The proposed internal docking site could also be useful for the specific design of new γ-secretase modulators.

Molecular Identification and Phylogenetic Analysis of Ascarids in Wild Animals.

Ascarid nematodes are the most common and harmful nematodes parasites in animals. By analyzing genetic variation, this study explores the genetic and phylogenetic relationship among ascarids from 11 different hosts. This study collected ascarid samples from the feces of nine animal species in Changsha Ecological Zoo of Hunan Province and two animal kinds in the College of Veterinary Medicine of Hunan Agricultural University. The mitochondrial gene (pcox1) and ribosomal ITS sequences were amplified, sequenced, and analyzed by PCR to identify the species of the samples. The phylogenetic tree was constructed based on two genes (cox1 and ITS) by the Neighbor-joining method, and the phylogenetic relationship was analyzed. The sequencing results showed that the sequence lengths of pcox1 and ITS genes in the samples were 441 bp and 838-1,177 bp, respectively. The difference rates were 0.00-1.70% in pcox1 gene and 0.00-7.30% in ITS gene. Phylogenetic analysis showed that ascarid worms from the white lion, Northeast tiger, South China tiger and cheetah were identified as Toxascaris leonina. Ascarids from the zebra were identified as Parascaris equorum, while those from chicken and peacocks were identified as Ascaridia galli. Ascarids of wolf and dog origin were Toxocara canis, the snake ascarids belonged to Ophidascaris filaria, and the bear ascarids belonged to Baylisascaris transfuga. There was a significant gap between different kinds of ascarid worms. We found that these two mitochondrial genes pcox1 and ITS showed a common characteristic that the intraspecific differences were significantly smaller than the interspecific differences, confirming that these two genes could be used as interspecific genetic markers for molecular identification of different ascarids origins. The intraspecific variation rate of the ITS gene was higher than that of pcox1, indicating that ITS can also be used in the genetic research of Ascaris species development. This study revealed the genetic evolution and phylogeny of ascarids in wild animals, and our results will help prevent and control ascarids in wild animals.

Molecular Characterization and Phylogenetic Analysis of Spirometra Tapeworms from Snakes in Hunan Province.

Sparganosis is a neglected zoonotic parasitic disease that poses huge threats to humans worldwide. Snakes play an important role in sparganosis transmission because they are the most common second intermediate hosts for Spirometra parasites. However, the population genetics of Spirometra isolates from snakes is currently not well studied in China. The present study was performed to explore the molecular characteristics and phylogenetic analysis of Spirometra tapeworms from different species of snakes in Hunan Province. This study obtained 49 Spirometra isolates from 15 geographical areas in Hunan Province, Central China. Subsequently, the 18S and 28S ribosomal DNA (rDNA) fragments were amplified from the isolated parasites, and their sequences were analyzed to assess their genetic diversity. Phylogenetic analyses were performed using the maximum likelihood algorithm. The results showed that sequence variations among these isolates were 0-2.3% and 0-0.1% for 18S and 28S rDNA, respectively. The phylogenetic analysis showed that all Spirometra isolates from Hunan Province were clustered into the same branch with Spirometra erinaceieuropaei isolated from other areas (China, Vietnam, Australia). Moreover, the phylogenetic trees revealed that Spirometra is closely related to Adenocephalus, Pyramicocephalus, Ligula, Dibothriocephalus, Schistocephalus, and Diphyllobothrium. The Spirometra isolates of different hosts/regions in Hunan Province are not host segregated or geographically isolated, and support for the taxonomic status of Spirometra tapeworms in China has been added. These results provide reference values for future accurate identification and taxonomic status of Spirometra tapeworms in China.

Active Colorization for Cartoon Line Drawings.

In the animation industry, the colorization of raw sketch images is a vitally important but very time-consuming task. This article focuses on providing a novel solution that semiautomatically colorizes a set of images using a single colorized reference image. Our method is able to provide coherent colors for regions that have similar semantics to those in the reference image. An active-learning-based framework is used to match local regions, followed by mixed-integer quadratic programming (MIQP) which considers the spatial contexts to further refine the matching results. We efficiently utilize user interactions to achieve high accuracy in the final colorized images. Experiments show that our method outperforms the current state-of-the-art deep learning based colorization method in terms of color coherency with the reference image. The region matching framework could potentially be applied to other applications, such as color transfer.

Advanced Current Collectors with Carbon Nanofoams for Electrochemically Stable Lithium-Sulfur Cells.

An inexpensive sulfur cathode with the highest possible charge storage capacity is attractive for the design of lithium-ion batteries with a high energy density and low cost. To promote existing lithium-sulfur battery technologies in the current energy storage market, it is critical to increase the electrochemical stability of the conversion-type sulfur cathode. Here, we present the adoption of a carbon nanofoam as an advanced current collector for the lithium-sulfur battery cathode. The carbon nanofoam has a conductive and tortuous network, which improves the conductivity of the sulfur cathode and reduces the loss of active material. The carbon nanofoam cathode thus enables the development of a high-loading sulfur cathode (4.8 mg cm-2) with a high discharge capacity that approaches 500 mA·h g-1 at the C/10 rate and an excellent cycle stability that achieves 90% capacity retention over 100 cycles. After adopting such an optimal cathode configuration, we superficially coat the carbon nanofoam with graphene and molybdenum disulfide (MoS2) to amplify the fast charge transfer and strong polysulfide-trapping capabilities, respectively. The highest charge storage capacity realized by the graphene-coated carbon nanofoam is 672 mA·h g-1 at the C/10 rate. The MoS2-coated carbon nanofoam features high electrochemical utilization attaining the high discharge capacity of 633 mA·h g-1 at the C/10 rate and stable cyclability featuring a capacity retention approaching 90%.