The solid electrolyte interface (SEI) significantly affects alkaline metal ion battery performance in terms of reversible capacity, Coulombic efficiency, and cycling stability. However, intrinsic ...properties of SEI layer in potassium ion batteries (KIBs), including structures, components, formation mechanism, and corresponding K+ storage behavior, are poorly understood. Here, we focus on the effect of electrolyte on SEI formation and K+ storage behavior in self-supported nitrogen-doped graphite foams (NGFs). Two types of organic electrolytes, KPF6 and KN(SO2F)2 (KFSI) salt in EC/DEC solution, were carefully selected and compared in detail to reveal the effect of SEI on the K+ ion storage mechanism. The experimental results, including in situ electrochemical evaluations and depth-profiling XPS analysis, demonstrate that the salts of KFSI result in a more uniform, stable, and thinner SEI layer compared with the SEI induced by KPF6. Particularly, the KFSI-induced SEI is rich in stable and uniformly distributed inorganic species and polycarbonates, whereas the KPF6-induced SEI is mainly composed of instable alkyl carbonates. This could be attributed to the larger FSI– size over PF6 – and lower LUMO levels than solvents according to theoretical calculations, which effectively prevent SEI from co-intercalation damage, thus leading to high stability of the as-obtained SEI layer. In general, the above-mentioned features could ensure high reversibility and good cycling stability of the self-supported NGFs electrode in KFSI-based electrolyte.
Manganese cobaltite (MnCo2O4) is a promising electrode material because of its attractive redox chemistry and excellent charge storage capability. Our previous work demonstrated that the ...octahedrally-coordinated Mn are prone to react with the hydroxyl ions in alkaline electrolyte upon electrochemical cycling and separates on the surface of spinel to reconstruct into δ-MnO2 nanosheets irreversibly, thus results in a change of the reaction mechanism with K+ ion intercalation. However, the low capacity has greatly limited its practical application. Herein, we found that the tetrahedrally-coordinated Co2+ ions were leached when MnCo2O4 was equilibrated in 1 mol L−1 HCl solution, leading to the formation of layered CoOOH on MnCo2O4 surface which is originated from the covalency competition induced selective breakage of the CoT–O bond in CoT–O–CoO and subsequent rearrangement of free CoO6 octahedra. The as-formed CoOOH is stable upon cycling in alkaline electrolyte, exhibits conversion reaction mechanism with facile proton diffusion and is free of massive structural evolution, thus enables utilization of the bulk electrode material and realizes enhanced specific capacity as well as facilitated charge transfer and ion diffusion. In general, our work not only offers a feasible approach to deliberate modification of MnCo2O4's surface structure, but also provides an in-depth understanding of its charge storage mechanism, which enables rational design of the spinel oxides with promising charge storage properties.
Covalency competition induced selective bond breakage, cobalt leaching and surface reconstruction of spinel-type MnCo2O4 to CoOOH nanosheets leading to enhanced charge storage capability. Display omitted
•Covalency competition induced selective bond breakage and surface reconstruction from MnCo2O4 to CoOOH.•Enhanced charge storage capability has been achieved via facilitated charge transfer and ion diffusion in CoOOH.•In-situ Raman/EIS and ex-situ XANES revealed in-depth understanding of structure evolution and charge storage mechanism.
Gastric cancer is the fifth most common type of human cancer and the third leading cause of cancer-related death. The purpose of this study is to investigate the immune infiltration signatures of ...gastric cancer and their relation to prognosis. We identified two distinct subtypes of gastric cancer (C1/C2) characterized by different immune infiltration signatures. C1 is featured by immune resting, epithelial-mesenchymal transition, and angiogenesis pathways, while C2 is featured by enrichment of the MYC target, oxidative phosphorylation, and E2F target pathways. The C2 subtype has a better prognosis than the C1 subtype (HR = 0.61, 95% CI: 0.44-0.85; log-rank test,
= 0.0029). The association of C1/C2 with prognosis remained statistically significant (HR = 0.62, 95% CI: 0.44-0.87;
= 0.006) after controlling for age, gender, and stage. The prognosis prediction of C1/C2 was verified in four independent cohorts (including an internal cohort). In summary, our study is helpful for better understanding of the association between immune infiltration and the prognosis of gastric cancer.
Bronze phase titanium dioxide (TiO2(B)) could be a promising high-power anode for lithium ion battery. However, TiO2(B) is a metastable material, so the as-synthesized samples are inevitably ...accompanied by the existence of anatase phases. It has been found that the TiO2(B)'s purity is positively correlated with its electrochemical performance. Herein, we have established an accurate quantification of the TiO2(B)/anatase ratio, by figuring out the function between the purity of TiO2(B) phase in the high purity range and its Raman spectra features in combination of the calibration by the synchrotron radiation X-ray diffraction (XRD). Compared with the time-consuming electrochemical method, the rapid, sensitive and non-destructive features of Raman spectroscopy have made it a promising candidate for determining the purity of TiO2(B). Further, the correlations developed in this work should be instructive in synthesizing pure TiO2(B) and furthermore optimizing its electrochemical charge storage properties.
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•The purity of TiO2(B) affects its electrochemical performance in battery as a promising anode material.•Synchrotron XRD calibrated function obtained by Raman enables accurate, ease and rapid determination of TiO2(B)’s purity.•Our electrochemical method enables more reliable determination of TiO2(B)’s purity compared with Thomas Beuvier's approach.
Computational pathology for gigapixel whole-slide images (WSIs) at slide level is helpful in disease diagnosis and remains challenging. We propose a context-aware approach termed WSI inspection via ...transformer (WIT) for slide-level classification via holistically modeling dependencies among patches on WSI. WIT automatically learns feature representation of WSI by aggregating features of all image patches. We evaluate classification performance of WIT and state-of-the-art baseline method. WIT achieved an accuracy of 82.1% (95% CI, 80.7%–83.3%) in the detection of 32 cancer types on the TCGA dataset, 0.918 (0.910–0.925) in diagnosis of cancer on the CPTAC dataset, and 0.882 (0.87–0.890) in the diagnosis of prostate cancer from needle biopsy slide, outperforming the baseline by 31.6%, 5.4%, and 9.3%, respectively. WIT can pinpoint the WSI regions that are most influential for its decision. WIT represents a new paradigm for computational pathology, facilitating the development of digital pathology tools.
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•WIT aggregates representations of all image patches for slide-level classification•WIT achieves high accuracy in the detection of 32 cancer types and diagnosis of cancer•Saliency maps obtained from WIT are visually interpretable
Oncology; Pathology; Computer science
Texture as a measure of spatial features has been useful as supplementary information to improve image classification in many areas of research fields. This study focuses on assessing the ability of ...different textural vectors and their combinations to aid spectral features in the classification of silicate rocks. Texture images were calculated from Landsat 8 imagery using a fractal dimension method. Different combinations of texture images, fused with all seven spectral bands, were examined using the Jeffries-Matusita (J-M) distance to select the optimal input feature vectors for image classification. Then, a support vector machine (SVM) fusing textural and spectral features was applied for image classification. The results showed that the fused SVM classifier achieved an overall classification accuracy of 83.73%. Compared to the conventional classification method, which is based only on spectral features, the accuracy achieved by the fused SVM classifier is noticeably improved, especially for granite and quartzose rock, which shows an increase of 38.84% and 7.03%, respectively. We conclude that the integration of textural and spectral features is promising for lithological classification when an appropriate method is selected to derive texture images and an effective technique is applied to select the optimal feature vectors for image classification.
Exponential accumulation of single-cell transcriptomes poses great challenge for efficient assimilation. Here, we present an approach entitled generative pretraining from transcriptomes (tGPT) for ...learning feature representation of transcriptomes. tGPT is conceptually simple in that it autoregressive models the ranking of a gene in the context of its preceding neighbors. We developed tGPT with 22.3 million single-cell transcriptomes and used four single-cell datasets to evalutate its performance on single-cell analysis tasks. In addition, we examine its applications on bulk tissues. The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states. The feature patterns of tumor bulk tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis, and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering massive amounts of transcriptome data and it will facilitate the interpretation and clinical translation of single-cell transcriptomes.
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•tGPT models gene rankings via autoregressive language modeling•tGPT works effectively on fundamental single-cell analysis tasks•tGPT captures distinctive features of different cell types•tGPT learns expression signatures linked to genomic and clinical features
Automation in bioinformatics; Data processing in systems biology; Transcriptomics
The effect of continuous DC longitudinal magnetic field heat treatment on soft magnetic properties of Fe78Si9B13 amorphous cores was studied. The results showed that comparing with the amorphous ...cores without magnetic field heat treatment, the permeability increases and the coercivity decreases after the longitudinal magnetic field heat treatment. At the same time, the rectangular ratio Br/Bm of the amorphous cores increases from 0.58 to 0.94, and the rectangular hysteresis loop is obtained, the loss value of Ps the amorphous cores is significantly reduced at low frequency, while it is almost the same at the high frequency. At f=50Hz and Bm=1.3T, the loss value of Ps is 0.278W/kg in the heat treatment without magnetic field, and the loss value of Ps was 0.153W/kg in the longitudinal magnetic field heat treatment, which was 44.9% lower than that of heat treatment without magnetic field. The effect of structural relaxation on magnetic properties of the magnetic cores in longitudinal magnetic heat treatment is not significant, and the magnetic properties exhibit good stability.
We developed Miscell, a self-supervised learning approach with deep neural network as latent feature encoder for mining information from single-cell transcriptomes. We demonstrated the capability of ...Miscell with canonical single-cell analysis tasks including delineation of single-cell clusters and identification of cluster-specific marker genes. We evaluated Miscell along with three state-of-the-art methods on three heterogeneous datasets. Miscell achieved at least comparable or better performance than the other methods by significant margin on a variety of clustering metrics such as adjusted rand index, normalized mutual information, and V-measure score. Miscell can identify cell-type specific markers by quantifying the influence of genes on cell clusters via deep learning approach.
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•We presented a deep learning approach Miscell to dissecting single-cell transcriptomes•Miscell achieved high performance on canonical single-cell analysis tasks•Miscell can transfer knowledge learned from single-cell transcriptomes to bulk tumors
Biological sciences; Neural networks; Transcriptomics
Supercapacitor with ultrahigh energy density (e.g., comparable with those of rechargeable batteries) and long cycling ability (>50000 cycles) is attractive for the next-generation energy storage ...devices. The energy density of carbonaceous material electrodes can be effectively improved by combining with certain metal oxides/hydroxides, but many at the expenses of power density and long-time cycling stability. To achieve an optimized overall electrochemical performance, rationally designed electrode structures with proper control in metal oxide/carbon are highly desirable. Here we have successfully realized an ultrahigh-energy and long-life supercapacitor anode by developing a hierarchical graphite foam–carbon nanotube framework and coating the surface with a thin layer of iron oxide (GF–CNT@Fe2O3). The full cell of anode based on this structure gives rise to a high energy of ∼74.7 Wh/kg at a power of ∼1400 W/kg, and ∼95.4% of the capacitance can be retained after 50000 cycles of charge–discharge. These performance features are superior among those reported for metal oxide based supercapacitors, making it a promising candidate for the next generation of high-performance electrochemical energy storage.
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