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Intercalation compounds are commonly‐used electrodes for commercialized lithium ion batteries (LIBs), while suffering from the sluggish interfacial processes at subzero temperature. Herein, nanoscale Nb2O5 has been investigated as a viable cathode for rechargeable batteries operated at the temperature of as low as −75 °C. Benefitting from the surface‐controlled charge storage process, the intrinsic intercalation pseudocapacitance of Nb2O5 broke the rate limitation at low temperature. Particularly, the battery exhibited outstanding rate performance (100 C) at room temperature and delivered high a reversible charge/discharge with a high capacity of 121 mAh g−1 at −75 °C. Furthermore, a capacity retention of 50 % and a long life for 100 cycles without capacity fading were achieved with a rate of 0.5 C at such low temperature. Based on the outstanding electrochemical performance from −75 °C to +25 °C, it can be envisaged that materials with intercalation pseudocapacitive behavior could be served as good candidate for energy storage systems under extreme conditions. [ABSTRACT FROM AUTHOR]

The field of bioinspired iontronics, bridging electronic devices and ionic systems, has multiple biological applications. Carbon-based ultracapacitive devices hold promise for controlling bioactive ions via electric double layers due to their high-surface-area and biocompatible porous carbon electrodes. However, the interplay between complex bioactive ions and porous carbons remains unclear due to the variety of structures of bioactive ions present in biological systems. Herein, we investigate the adsorption behavior of a series of bioactive ammonium-based cations with varying alkyl chain lengths in nanoporous carbons. We find that strong physisorption results from the synergistic hydrophobic interaction and electrostatic attraction between porous carbons (with a negative zeta potential) and bioactive cations. Bioactive cations with varying alkyl chain lengths can be irreversibly physically adsorbed and confined within nanoporous carbons resulting in anion enrichment and depletion during electric polarization. This situation, in turn, results in a characteristic memristive behavior in all-carbon capacitive ionic memristor devices. Our findings highlight the relationship between the resistance state of the memristor and ion adsorption mechanisms in all-carbon capacitive devices, which hold potential for future transmitter delivery, biointerfacing, and neuromorphic devices., (© 2024 Wiley‐VCH GmbH.)

DNA nanotechnology plays a crucial role in precise cancer medicine. Currently, molecular logic circuits are applied to detect tumor-specific biomarkers and control the release of therapeutic drugs. However, these systems lack self-learning capabilities for intelligent diagnostics in biological samples, and their data processing capabilities are limited. Here, a molecular learning vector quantization neural network (LVQNN) model based on DNA strand displacement (DSD) technology for breast tumor diagnosis is developed. Compared to previous work, the molecular LVQNN boasts powerful computing abilities, handling high-dimensional data for intelligent cancer diagnosis. To verify the feasibility and versatility of the network, two distinct typical datasets are selected: one from a single source with cell morphology data from 569 cases, and a more extensive one spanning different populations and ages, with miRNA gene expression data from 1881 cases. By using the molecular LVQNN, diagnostic experiments are conducted on 50 and 120 public individuals from these two datasets, respectively, achieving accuracy rates of 94% and 97.5%. This study demonstrates that the LVQNN model exhibits significant advantages in breast cancer diagnosis and enhances diagnostic accuracy while introducing new approaches for intelligent cancer diagnosis, anticipated to bring significant breakthroughs and application prospects to precise cancer medicine., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background: The risk factors of cardiovascular disease (CVD) in end-stage renal disease (ESRD) with hemodialysis remain not fully understood. In this study, we developed and validated a clinical-longitudinal model for predicting CVD in patients with hemodialysis, and employed Mendelian randomization to evaluate the causal 6study included 468 hemodialysis patients, and biochemical parameters were evaluated every three months. A generalized linear mixed (GLM) predictive model was applied to longitudinal clinical data. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the performance of the model. Kaplan-Meier curves were applied to verify the effect of selected risk factors on the probability of CVD. Genome-wide association study (GWAS) data for CVD ( n  = 218,792,101,866 cases), end-stage renal disease (ESRD, n  = 16,405, 326 cases), diabetes ( n  = 202,046, 9,889 cases), creatinine ( n  = 7,810), and uric acid (UA, n  = 109,029) were obtained from the large-open GWAS project. The inverse-variance weighted MR was used as the main analysis to estimate the causal associations, and several sensitivity analyses were performed to assess pleiotropy and exclude variants with potential pleiotropic effects., Results: The AUCs of the GLM model was 0.93 (with accuracy rates of 93.9% and 93.1% for the training set and validation set, sensitivity of 0.95 and 0.94, specificity of 0.87 and 0.86). The final clinical-longitudinal model consisted of 5 risk factors, including age, diabetes, ipth, creatinine, and UA. Furthermore, the predicted CVD response also allowed for significant ( p  < 0.05) discrimination between the Kaplan-Meier curves of each age, diabetes, ipth, and creatinine subclassification. MR analysis indicated that diabetes had a causal role in risk of CVD ( β  =   0.088, p  < 0.0001) and ESRD ( β  =   0.26, p =  0.007). In turn, ESRD was found to have a causal role in risk of diabetes ( β  =   0.027, p  = 0.013). Additionally, creatinine exhibited a causal role in the risk of ESRD ( β  =   4.42, p  = 0.01)., Conclusions: The results showed that old age, diabetes, and low level of ipth, creatinine, and UA were important risk factors for CVD in hemodialysis patients, and diabetes played an important bridging role in the link between ESRD and CVD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Tian, Xu, Wang, Zhu, Huang, Liu, Li and Li.)

This study sought to identify a reference tissue-based quantification approach for improving the statistical power in detecting changes in brain glucose metabolism, amyloid, and tau deposition in Alzheimer's disease studies. A total of 794, 906, and 903 scans were included for 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir, respectively. Positron emission tomography (PET) and T1-weighted images of participants were collected from the Alzheimer's disease Neuroimaging Initiative database, followed by partial volume correction. The standardized uptake value ratios (SUVRs) calculated from the cerebellum gray matter, centrum semiovale, and pons were evaluated at both region of interest (ROI) and voxelwise levels. The statistical power of reference tissues in detecting longitudinal SUVR changes was assessed via paired t-test. In cross-sectional analysis, the impact of reference tissue-based SUVR differences between cognitively normal and cognitively impaired groups was evaluated by effect sizes Cohen's d and two sample t-test adjusted by age, sex, and education levels. The average ROI t values of pons were 86.62 and 38.40% higher than that of centrum semiovale and cerebellum gray matter in detecting glucose metabolism decreases, while the centrum semiovale reference tissue-based SUVR provided higher t values for the detection of amyloid and tau deposition increases. The three reference tissues generated comparable d images for 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir and comparable t maps for 18 F-florbetapir and 18 F-flortaucipir, but pons-based t map showed superior performance in 18 F-FDG. In conclusion, the tracer-specific reference tissue improved the detection of 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir PET SUVR changes, which helps the early diagnosis, monitoring of disease progression, and therapeutic response in Alzheimer's disease., (© 2022 United Imaging Healthcare. Human Brain Mapping published by Wiley Periodicals LLC.)

Aberrant expression of long non-coding RNAs (lncRNAs) has been reported in multiple cancers. However, the underlying mechanisms mediated by super-enhancers remain elusive. Here we sought to define the role of a novel lncRNA termed lncRNA-DAW in tumorigenesis. Our results revealed that lncRNA-DAW was driven by a liver-specific super-enhancer and transcriptionally activated by HNF4G, leading to frequent elevation in hepatocellular carcinoma (HCC) specimens. Ectopic expression of lncRNA-DAW promoted both in vivo and in vitro tumor growth. By using RNA sequencing, Wnt2 was screened out as a downstream effector of lncRNA-DAW. We next found that lncRNA-DAW physically interacted with EZH2, a negative regulator of Wnt2. This interplay subsequently potentiated CDK1-EZH2 interaction, leading to the phosphorylation and ubiquitination of EZH2. The lncRNA-DAW-mediated EZH2 degradation facilitated the de-repression of Wnt2 transcription, which eventually activated the Wnt/β-catenin pathway. Furthermore, we verified that Wnt2 potentiated in vitro and in vivo cancer cell growth by activating the Wnt/β-catenin pathway. Finally, Wnt2 amplification was confirmed as a common event in liver cancer, and the expression of lncRNA-DAW was positively correlated with Wnt2 in HCC specimens. Collectively, we are the first to identify lncRNA-DAW as a novel candidate oncogene in liver cancer, and this lncRNA may serve as a novel clinical diagnosis biomarker for liver cancer., Competing Interests: The authors declare no competing interests., (© 2021.)

Applying interlayers is the main strategy to address the large area specific resistance (ASR) of Li/garnet interface. However, studies on eliminating the Li 2 CO 3 and LiOH interfacial lithiophobic contaminants are still insufficient. Here, thermal-decomposition vapor deposition (TVD) of a carbon modification layer on Li 6.75 La 3 Zr 1.75 Ta 0.25 O 12 (LLZTO) provides a contaminant-free surface. Owing to the protection of the carbon layer, the air stability of LLZTO is also improved. Moreover, owing to the amorphous structure of the low graphitized carbon (LGC), instant lithiation is achieved, and the ASR of the Li/LLZTO interface is reduced to 9 Ω cm 2 . Lithium volatilization and Zr 4+ reduction are also controllable during TVD. Compared with its high graphitized carbon counterpart (HGC), the LGC-modified Li/LLZTO interface displays a higher critical current density of 1.2 mA cm -2 , as well as moderate Li plating and stripping, which provides enhanced polarization voltage stability., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Lithium metal is an ideal anode for high-energy rechargeable batteries at low temperature, yet hindered by the electrochemical instability with the electrolyte. Concentrated electrolytes can improve the oxidative/reductive stability, but encounter high viscosity. Herein, a co-solvent formulation was designed to resolve the dilemma. By adding electrochemically "inert" dichloromethane (DCM) as a diluent in concentrated ethyl acetate (EA)-based electrolyte, the co-solvent electrolyte demonstrated a high ionic conductivity (0.6 mS cm -1 ), low viscosity (0.35 Pa s), and wide range of potential window (0-4.85 V) at -70 °C. Spectral characterizations and simulations show these unique properties are associated with the co-solvation structure, in which high-concentration clusters of salt in the EA solvent were surrounded by mobile DCM diluent. Overall, this novel electrolyte enabled rechargeable metallic Li battery with high energy (178 Wh kg -1 ) and power (2877 W kg -1 ) at -70 °C., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Porous carbon and nanocarbons have been extensively applied as anode materials for high-energy density lithium-ion batteries (LIBs). However, as another representative nanocarbon, fullerenes, such as C 60 , have been scarcely utilized in LIBs because of their poor electrochemical reversibility. Herein, we designed a novel C 60 -embedded nitrogen-doped microporous carbon material (denoted as C 60 @N-MPC), which was derived from a zeolitic imidazolate framework-8 (ZIF-8) precursor, demonstrating its promising application as a superior anode material for LIB. We first embedded C 60 in situ into a ZIF-8 matrix via a facile solid-state mechanochemical route, which acted as a precursor and was transformed to C 60 @N-MPC after carbonization. The C 60 @N-MPC was applied as a novel anode for LIBs, showing an improved reversible specific capacity of ≈1351 mA h g -1 at 0.1 A g -1 and a better rate capacity (≈1077 mA h g -1 at 1 A g -1 after 400 cycles) relative to those based on the unmodified N-MPC anode. The role of C 60 in the superior lithium storage performance of C 60 @N-MPC was elucidated, revealing that C 60 functioned as a pore expander for N-MPC with 3-20 nm mesopores (versus sub-1 nm micropores for the unmodified N-MPC), which facilitated the rapid diffusion of the organic electrolyte.

Background: Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods., New Method: In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization., Results: We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD., Comparison With Existing Method(s): To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis., Conclusions: The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field., (Copyright © 2017 Elsevier B.V. All rights reserved.)