Nanodiamond-Assisted High-Performance Sodium-Ion Batteries with Weakly Solvated Ether Electrolyte at -40 °C.

Realizing high performances of sodium-ion batteries (SIBs) working at low temperatures is a pressing need for the commercial applications of SIBs. In this work, nanodiamonds (NDs) are introduced in diglyme electrolytes (ND-Diglyme) to significantly improve the low-temperature performances of SIBs. The corresponding SIB achieves an initial reversible specific capacity of 324 mA h g-1 at -40 °C (slightly decreased from 357 mA h g-1 at 25 °C) and shows a capacity retention ratio of ≈82% after 100 cycles at 0.1 A g-1. Moreover, it shows a capacity as high as 40 mA h g-1 at 1 A g-1, nearly five times the date of the pure Diglyme electrolyte. Experimentally reveals that introducing NDs is helpful in inhibiting dendrite growth and improving the cyclic stability of anode at LT, because the ND with strong adsorption to sodium ions can not only assist in forming an effective solid electrolyte interface rich with NaF and Na2CO3 but also effectively reduce the activation energy (decreased from 426.68 to 370.51 meV) during the charge transfer processes. Hence, the proposed ND-assisted weakly ether electrolyte in this study presents a viable electrolyte additive solution to fulfill the rising low-temperature demands of SIBs.

Weakly-supervised Depth Estimation and Image Deblurring via Dual-Pixel Sensors.

Dual-pixel (DP) imaging sensors are getting more popularly adopted by modern cameras. A DP camera captures a pair of images in a single snapshot by splitting each pixel in half. Several previous studies show how to recover depth information by treating the DP pair as an approximate stereo pair. However, dual-pixel disparity occurs only in image regions with defocus blur which is unlike classic stereo disparity. Heavy defocus blur in DP pairs affects the performance of depth estimation approaches based on matching. Therefore, we treat the blur removal and the depth estimation as a joint problem. We investigate the formation of the DP pair, which links the blur and depth information, rather than blindly removing the blur effect. We propose a mathematical DP model that can improve depth estimation by the blur. This exploration motivated us to propose our previous work, an end-to-end DDDNet (DP-based Depth and Deblur Network), which jointly estimates depth and restores the image in a supervised fashion. However, collecting the ground-truth (GT) depth map for the DP pair is challenging and limits the depth estimation potential of the DP sensor. Therefore, we propose an extension of the DDDNet, called WDDNet (Weakly-supervised Depth and Deblur Network), which includes an efficient reblur solver that does not require GT depth maps for training. To achieve this, we convert all-in-focus images into supervisory signals for unsupervised depth estimation in our WDDNet. We jointly estimate an all-in-focus image and a disparity map, then use a Reblur and Fstack module to regularize the disparity estimation and image restoration. We conducted extensive experiments on synthetic and real data to demonstrate the competitive performance of our method when compared to state-of-the-art (SOTA) supervised approaches. Index Terms-Dual-pixel Sensor, Weakly-supervised, Depth Estimation, Deblur and Reblu.

Alternative splicing and intron retention: Their profiles and roles in cutaneous fibrosis of systemic sclerosis.

BACKGROUND: Alternative splicing (AS) and intron retention (IR) implicated in multiple pathophysiological processes, have rarely been reported in systemic sclerosis (SSc). METHODS: We integrated bulk RNA-seq and 4D label-free mass spectrometry to perform a multi-omics analysis of AS and IR in SSc skin tissue and fibroblasts. RMATS and iREAD were used to identify AS and IR, which were validated by real-time PCR. Spearman correlation and the LASSO method were employed to assess correlations among clinical features, introns, splicing factors (regulators of AS) and proteins. FINDINGS: AS profiles showed distinct alterations in SSc skin tissue, with the most pronounced changes occurring in IR. AS and IR were associated with total modified Rodnan skin score (mRSS) and local skin score. Upon TGF-ß stimulation, fibroblasts exhibited significant alterations in IR profiles, affecting genes related to fibroblast proliferation and collagen fibril organization. A comprehensive integrated analysis of introns, exons, and proteome profiles revealed that IR exerted a negative impact on protein expression, with certain changes being under intronic control. RT-PCR confirmed the presence of intron and exon-derived sequences of CTTN, OGA, MED16 and PHYKPL. Additionally, notable changes were observed in the regulatory network of splicing factors in SSc skin tissues. These factors are also involved in fibrosis pathways and correlated with clinical features. CONCLUSION: Totally, abnormal AS, IR profiles and splicing factors were identified in SSc, altered IRs and splicing factors participated in fibrosis-related pathways. IR exerted a negative impact on protein expression in TGF-ß-stimulated fibroblasts. Clarification of the IR mechanisms will provide new insights into the pathophysiology of SSc.

Ozone-Assisted Cu-Based Catalysts for the Efficient Electro-Reforming Glycerol to Formic Acid.

Glycerol electrooxidation reaction (GOR) to produce value-added chemicals, such as formic acid, could make more efficient use of abundant glycerol and meet future demand for formic acid as a fuel for direct or indirect formic acid fuel cells. Non-noble metal Cu-based catalysts have great potential in electro-reforming glycerol to formic acid. However, the high activity, selectivity and stability of Cu based catalysts in GOR cannot be achieved simultaneously. Here, we used ozone-assisted electrocatalyst to convert glycerol to formic acid under alkaline conditions, the onset potential was reduced by 60 mV, the Faraday efficiency (FE) reached 95%. The catalyst has excellent stability within 300 h at the current density of 10 mA cm-2. The electron spin resonance proved that ozone produced superoxide anion during the GOR. In situ Raman spectroscopy, electrochemical studies showed that glycerol can be activated with ozone in GOR, and the C-C bond can be broken to reduce the polymerization of glycerol on the catalyst surface, so as to produce more formic acid at a lower voltage. Moreover, the removal of dissolved O3 from water can be up to 100% after 30 minutes of GOR reaction at a solubility of 50 mg L-1 as measured by UV-VIS spectrophotometry.

Integration of miRNA expression analysis of purified leukocytes and whole blood reveals blood-borne candidate biomarkers for lung cancer.

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.

scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data.

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate rare cell types and achieve accurate identification. We benchmark scCAD on 25 real-world scRNA-seq datasets, demonstrating its superior performance compared to 10 state-of-the-art methods. In-depth case studies across diverse datasets, including mouse airway, brain, intestine, human pancreas, immunology data, and clear cell renal cell carcinoma, showcase scCAD's efficiency in identifying rare cell types in complex biological scenarios. Furthermore, scCAD can correct the annotation of rare cell types and identify immune cell subtypes associated with disease, thereby offering valuable insights into disease progression.

LTM-NeRF: Embedding 3D Local Tone Mapping in HDR Neural Radiance Field.

Recent advances in Neural Radiance Fields (NeRF) have provided a new geometric primitive for novel view synthesis. High Dynamic Range NeRF (HDR NeRF) can render novel views with a higher dynamic range. However, effectively displaying the scene contents of HDR NeRF on diverse devices with limited dynamic range poses a significant challenge. To address this, we present LTM-NeRF, a method designed to recover HDR NeRF and support 3D local tone mapping. LTM-NeRF allows for the synthesis of HDR views, tone-mapped views, and LDR views under different exposure settings, using only the multi-view multi-exposure LDR inputs for supervision. Specifically, we propose a differentiable Camera Response Function (CRF) module for HDR NeRF reconstruction, globally mapping the scene's HDR radiance to LDR pixels. Moreover, we introduce a Neural Exposure Field (NeEF) to represent the spatially varying exposure time of an HDR NeRF to achieve 3D local tone mapping, for compatibility with various displays. Comprehensive experiments demonstrate that our method can not only synthesize HDR views and exposure-varying LDR views accurately but also render locally tone-mapped views naturally. For video results, please view our supplemental materials or visit the project page at: https://xhuangcv.github.io/LTM-NeRF/.

Electronic and magnetic properties of Au-doped diamond surfaces by first-principles calculation.

The electronic and magnetic properties of the Au-doped diamond surface are investigated by first-principles calculation. After Au-doping, diamond shows surface p-type conductivity with an areal electron density of 6.34 × 1013 cm-2. Unlike the non-magnetic feature of intrinsic diamond, magnetism is induced for diamond (100), (110) and (111) surfaces as well as at different terminations (H, F, N and O). The magnetism originates from the s-p hybridization between the Au-6s state and the C-2p state, and the spin charge density and magnetic moments of Au-doped diamond originate mainly from the Au atoms and their surrounding C atoms. Further studies show that the magnetic properties still maintain under different doping concentrations (0.125-0.5 monolayer). Therefore, this study would provide great potential applications of diamond in novel magnetic semiconductors and transistors.

A dual-functional electrolyte additive displaying hydrogen bond fusion enables highly reversible aqueous zinc ion batteries.

In recent years, aqueous zinc-ion batteries (AZIBs) have attracted significant attention in energy storage due to their notable advantages, including high safety, low cost, high capacity, and environmental friendliness. However, side reactions like hydrogen evolution and zinc (Zn) dendrites can significantly impact their Coulombic efficiency (CE) and lifespan. Effectively addressing these issues has become a focus of research in this field. In our study, dimethyl sulfoxide (DMSO) and nanodiamonds (NDs) were used to optimize the electrolyte of AZIBs. Benefiting from the hydrogen bond fusion of DMSO and NDs, which regulates the Zn deposition behavior, effectively inhibiting the growth of Zn dendrites, hydrogen evolution, and corrosion. The Zn | |Zn symmetric cells using NDs-DMSO-ZS demonstrate exceptional cycling stability for over 1500 h at 1 mA cm-2, while the Zn//Cu asymmetric cells achieve up to 99.8% CE at 2 mA cm-2. This study not only shows the application prospects of electrolyte optimization in enhancing AZIBs performance, but also provides a reference for the advancement of electrolyte technology in advanced AZIBs technology.

Nitrogen-Doped CoP-Co2P-Supported Ru with Interconnected Channels through a Microwave Quasi-Solid Approach for Hydrogen Evolution Reaction over a Wide pH Range.

Transition-metal phosphides (TMPs) have attracted extensive attention in energy-related fields, especially for electrocatalytic hydrogen evolution reaction (HER). However, it is imperative to develop a facile and time-consuming approach to prepare metal phosphides with satisfactory catalytic performance. Herein, nitrogen-doped CoP-Co2P decorated with Ru (Ru/N-CoP-Co2P) is synthesized (Ru/N-CoP-Co2P) through a hydrothermal route and following an ultrafast and simple microwave avenue within 20 s. The achieved Ru/N-CoP-Co2P possesses an interconnected porous morphology to expose abundant active sites and accelerate the mass transport. Moreover, N doping and Ru-supported decorated Ru/N-CoP-Co2P also play a key role in promoting the electrocatalytic activity. Therefore, the as-designed Ru/N-CoP-Co2P presents good catalytic performance for the HER in a wide pH range. Ru/N-CoP-Co2P merely needs overpotentials of 63, 100, and 65 mV to obtain 10 mA cm-2 in acidic, alkaline, and seawater electrolytes. This research provides a novel and efficient strategy for the synthesis of TMPs with highly efficient catalytic activity.

Deep Non-rigid Structure-from-Motion: A Sequence-to-Sequence Translation Perspective.

Directly regressing the non-rigid shape and camera pose from the individual 2D frame is ill-suited to the Non-Rigid Structure-from-Motion (NRSfM) problem. This frame-by-frame 3D reconstruction pipeline overlooks the inherent spatial-temporal nature of NRSfM, i.e., reconstructing the 3D sequence from the input 2D sequence. In this paper, we propose to solve deep sparse NRSfM from a sequence-to-sequence translation perspective, where the input 2D keypoints sequence is taken as a whole to reconstruct the corresponding 3D keypoints sequence in a self-supervised manner. First, we apply a shape-motion predictor on the input sequence to obtain an initial sequence of shapes and corresponding motions. Then, we propose the Context Layer, which enables the deep learning framework to effectively impose overall constraints on sequences based on the structural characteristics of non-rigid sequences. The Context Layer constructs modules for imposing the self-expressiveness regularity on non-rigid sequences with multi-head attention (MHA) as the core, together with the use of temporal encoding, both of which act simultaneously to constitute constraints on non-rigid sequences in the deep framework. Experimental results across different datasets such as Human3.6M, CMU Mocap, and InterHand prove the superiority of our framework. The code will be made publicly available.

Ultrafast Quasi-Solid-State Microwave Construction of Spongy Cobalt-Molybdenum Phosphide for Hydrogen Production Over Wide pH Range.

The developed strategies for synthesizing metal phosphides are usually cumbersome and pollute the environment. In this work, an ultrafast (30 s) quasi-solid-state microwave approach is developed to construct cobalt-molybdenum phosphide decorated with Ru (Ru/CoxP-MoP) featured porous morphology with interconnected channels. The specific nanostructure favors mass transport, such as electrolyte bubbles transfer and exposing rich active sites. Moreover, the coupling effects between metallic elements, especially the decorated Ru, also act as a pivotal role on enhancing the electrocatalytic performance. Benefiting from the effects of composition and specific nanostructure, the prepared Ru/CoxP-MoP exhibits efficient HER performance with a current density of 10 mA cm-2 achieved in 1 m KOH, 0.5 m H2SO4, seawater containing 1 m KOH and 1 m PBS, with overpotentials of 52, 59, 55, 90 mV, and coupling with good stability. This work opens a novel and fast avenue to design metal-phosphide-based nanomaterials in energy-conversion and storage fields.

Validating the performance of organ dysfunction scores in children with infection: A cohort study.

PURPOSE: We aimed to validate the performance of six available scoring models for predicting hospital mortality in children with suspected or confirmed infections. METHODS: This single-center retrospective cohort study included pediatric patients admitted to the PICU for infection. The primary outcome was hospital mortality. The six scores included the age-adapted pSOFA score, SIRS score, PELOD2 score, Sepsis-2 score, qSOFA score, and PMODS. RESULTS: Of the 5,356 children admitted to the PICU, 9.1% (488) died, and 25.1% (1,342) had basic disease with a mortality rate of 12.7% (171); 65.3% (3,499) of the patients were younger than 2 years, and 59.4% (3,183) were male. The discrimination abilities of the pSOFA and PELOD2 scores were superior to those of the other models. The calibration curves of the pSOFA and PELOD2 scores were consistent between the predictions and observations. Elevated lactate levels were a risk factor for mortality. CONCLUSION: The pSOFA and PELOD2 scores had superior predictive performance for mortality. Given the relative unavailability of items and clinical operability, the pSOFA score should be recommended as an optimal tool for acute organ dysfunction in pediatric sepsis patients. Elevated lactate levels are related to a greater risk of death from infection in children in the PICU.

Oxygen-Terminated Polycrystalline Boron-Doped Diamond Superhydrophobic Surface with Excellent Mechanical and Thermal Stabilities.

Superhydrophobic surfaces are of great interest because of their remarkable properties. Due to its maximal hardness and chemical inertness, diamond film has great potential in fabricating robust superhydrophobic surfaces. In the present study, an oxygen-terminated polycrystalline boron-doped diamond (O-PBDD) superhydrophobic surface with micro/nano-hierarchical porous structures is developed. The preparation method is very simple, requiring only sputtering and dewetting procedures. The former involves sputtering gold and copper particles onto the hydrogen-terminated polycrystalline boron-doped diamond (H-PBDD) to form gold/copper films, whereas the latter involves placing the samples in an atmospheric tube furnace to form hierarchical pores. By controlling the etching parameters, the wettability of the O-PBDD surface can be adjusted from hydrophilic to superhydrophobic, which is significantly different to the normal hydrophilicity feature of O-termination diamonds. The water contact angle of the obtained O-PBDD surface can reach 165 ± 5°, which is higher than the superhydrophobic diamond surfaces that are reported in the literature. In addition, the O-PBDD surface exhibits excellent durability; it can maintain satisfactory superhydrophobicity even after high-pressure, high-temperature, and sandpaper friction tests. This work provides a new research direction for fabricating robust superhydrophobic materials with diamond film.

Synergistic Effect of Doxorubicin and Blue Light Irradiation on the Antitumor Treatment of HepG2 Cells in Liver Cancer.

Doxorubicin (DOX) has been an effective antitumor agent for human liver cancer cells; however, an overdose might lead to major side effects appearing in clinical applications. In this work, we present a strategy of combining DOX and blue light (BL) irradiation for the antitumor treatment of HepG2 cells (one typical human liver cancer cell line). It is demonstrated that synergetic DOX and BL can significantly reduce cell proliferation and increase the apoptotic rate of HepG2 cells in comparison to individual DOX treatment. The additional BL irradiation is further helpful for enhancing the inhibition of cell migration and invasion. Analyses of reactive oxygen species (ROS) level and Western blotting reveal that the strategy results in more ROS accumulation, mitochondrial damage, and the upregulation of proapoptotic protein (Bcl-2) and downregulation of antiapoptotic protein (Bax). In addition to the improved therapeutic effect, the non-contact BL irradiation is greatly helpful for reducing the dosage of DOX, and subsequently reduces the side effects caused by the DOX drug. These findings offer a novel perspective for the therapeutic approach toward liver cancer with high efficiency and reduced side effects.

Spatial Steerability of GANs via Self-Supervision from Discriminator.

Generative models make huge progress to the photorealistic image synthesis in recent years. To enable human to steer the image generation process and customize the output, many works explore the interpretable dimensions of the latent space in GANs. Existing methods edit the attributes of the output image such as orientation or color scheme by varying the latent code along certain directions. However, these methods usually require additional human annotations for each pretrained model, and they mostly focus on editing global attributes. In this work, we propose a self-supervised approach to improve the spatial steerability of GANs without searching for steerable directions in the latent space or requiring extra annotations. Specifically, we design randomly sampled Gaussian heatmaps to be encoded into the intermediate layers of generative models as spatial inductive bias. Along with training the GAN model from scratch, these heatmaps are being aligned with the emerging attention of the GAN's discriminator in a self-supervised learning manner. During inference, users can interact with the spatial heatmaps in an intuitive manner, enabling them to edit the output image by adjusting the scene layout, moving, or removing objects. Moreover, we incorporate DragGAN into our framework, which facilitates fine-grained manipulation within a reasonable time and supports a coarse-to-fine editing process. Extensive experiments show that the proposed method not only enables spatial editing over human faces, animal faces, outdoor scenes, and complicated multi-object indoor scenes but also brings improvement in synthesis quality. Code, models, and demo video are available at https://genforce.github.io/SpatialGAN/.

Realized Record Capacity and Rate Performance of Dual-Carbon Batteries Constructed by Introducing Superhard Nanodiamonds.

Dual-ion batteries (DIBs) are becoming an important technology for energy storage. To overcome the disadvantages of traditional electrodes and electrolytes, here we assemble a dual-carbon DIB with nanodiamond (ND)-modified crimped graphene (DCG) and electrolyte. The DCG anode and cathode realize high capacities of 1121 mA h g-1 and 149 mA h g-1, respectively, at 0.1 A g-1. The corresponding DCG//DCG full cells present a high capacity of 143 mA h g-1 at 1 A g-1 after 3300 cycles, which is superior to most reported results. Achieving these record performances is strongly dependent on the formed DCG electrodes with expanded interlayer spacing and abundant active sites, and NDs dispersed in DCG and electrolytes are very helpful for enhancing the storage of both cations and anions, effectively suppressing the irreversible decomposition of electrolytes. This work breaks through the bottleneck of graphitic-based DIBs, paving the way for realizing high-performance DIBs applied in industry.

Defective Diamane: A Superior Sensor for Toxic Gases Capture and Detection with Excellent Selectivity, Sensitivity, and Reversibility at Room Temperature.

The toxic gases emitted from industrial production have caused significant damage to the environment and human health, necessitating efficient gas sensors for their detection and removal. In this work, first-principles calculations are employed to investigate the potential application of diamanes for high-performance toxic gas sensors. The results show that nine gas molecules (CO, CO2, NO, NO2, NH3, SO2, N2, O2, and H2O) are physisorbed on pristine diamane by weak van der Waals interactions. After introducing H/F defects, diamane can effectively capture specific toxic gases (CO, NO, NO2, and SO2) in the presence of interfering gases (N2, O2, and H2O), suggesting excellent selectivity and anti-interference ability. Orbital hybridization and significant charge redistribution between gas molecules and defective diamane dominate the enhanced adsorbate-substrate interactions. More importantly, the high sensitivity and good reversibility of defective diamane for detecting CO, NO, and SO2 molecules enable its reuse as a superior resistance-type gas sensor. Our calculations provide valuable insights into the potential of defective diamane for detecting toxic gases and shed light on the practical application of novel carbon-based materials in the gas-sensing field.

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks.

MOTIVATION: Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited. RESULTS: Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes. AVAILABILITY AND IMPLEMENTATION: DISHyper is freely available for download at https://github.com/genemine/DISHyper.

Charge Redistribution of Lattice-Mismatched Co─Cu3P Boosting pH-Universal Water/Seawater Hydrogen Evolution.

Practical applications of the hydrogen evolution reaction (HER) rely on the development of highly efficient, stable, and low-cost catalysts. Tuning the electronic structure, morphology, and architecture of catalysts is an important way to realize efficient and stable HER electrocatalysts. Herein, Co-doped Cu3P-based sugar-gourd structures (Co─Cu3P/CF) are prepared on copper foam as active electrocatalysts for hydrogen evolution. This hierarchical structure facilitates fast mass transport during electrocatalysis. Notably, the introduction of Co not only induces a charge redistribution but also leads to lattice-mismatch on the atomic scale, which creates defects and performs as additional active sites. Therefore, Co─Cu3P/CF requires an overpotential of only 81, 111, 185, and 230 mV to reach currents of 50, 100, 500, and 1000 mA cm-2 in alkaline media and remains stable after 10 000 CV cycles in a row and up to 110 h i-t stability tests. In addition, it also shows excellent HER performance in water/seawater electrolytes of different pH values. Experimental and DFT show that the introduction of Co modulates the electronic and energy level structures of the catalyst, optimizes the adsorption and desorption behavior of the intermediate, reduces the water dissociation energy barrier during the reaction, accelerates the Volmer step reaction, and thus improves the HER performance.