Electrochemical energy storage devices with a high energy density are an important technology in modern society, especially for electric vehicles. The most effective approach to improve the energy ...density of batteries is to search for high‐capacity electrode materials. According to the concept of energy quality, a high‐voltage battery delivers a highly useful energy, thus providing a new insight to improve energy density. Based on this concept, a novel and successful strategy to increase the energy density and energy quality by increasing the discharge voltage of cathode materials and preserving high capacity is proposed. The proposal is realized in high‐capacity Li‐rich cathode materials. The average discharge voltage is increased from 3.5 to 3.8 V by increasing the nickel content and applying a simple after‐treatment, and the specific energy is improved from 912 to 1033 Wh kg−1. The current work provides an insightful universal principle for developing, designing, and screening electrode materials for high energy density and energy quality.
Li‐ion batteries with high energy quality require a high capacity coupled with high operating voltage. This requires the electrode materials to not only have a high specific capacity but also a high discharge voltage for cathode materials and low charge voltage for anode materials.
Objectives
This study was conducted in order to establish and validate a radiomics model for predicting lymph node (LN) metastasis of intrahepatic cholangiocarcinoma (IHC) and to determine its ...prognostic value.
Methods
For this retrospective study, a radiomics model was developed in a primary cohort of 103 IHC patients who underwent curative-intent resection and lymphadenectomy. Radiomics features were extracted from arterial phase computed tomography (CT) scans. A radiomics signature was built based on highly reproducible features using the least absolute shrinkage and selection operator (LASSO) method. Multivariate logistic regression analysis was adopted to establish a radiomics model incorporating radiomics signature and other independent predictors. Model performance was determined by its discrimination, calibration, and clinical usefulness. The model was internally validated in 52 consecutive patients.
Results
The radiomics signature comprised eight LN-status–related features and showed significant association with LN metastasis in both cohorts (
p
< 0.001). A radiomics nomogram that incorporates radiomics signature and CA 19-9 level showed good calibration and discrimination in the primary cohort (AUC 0.8462) and validation cohort (AUC 0.8921). Promisingly, the radiomics nomogram yielded an AUC of 0.9224 in the CT-reported LN-negative subgroup. Decision curve analysis confirmed the clinical utility of this nomogram. High risk for metastasis portended significantly lower overall and recurrence-free survival than low risk for metastasis (both
p
< 0.001). The radiomics nomogram was an independent preoperative predictor of overall and recurrence-free survival.
Conclusions
Our radiomics model provided a robust diagnostic tool for prediction of LN metastasis, especially in CT-reported LN-negative IHC patients, that may facilitate clinical decision-making.
Key Points
• The radiomics nomogram showed good performance for prediction of LN metastasis in IHC patients, particularly in the CT-reported LN-negative subgroup.
• Prognosis of high-risk patients remains dismal after curative-intent resection.
• The radiomics model may facilitate clinical decision-making and define patient subsets benefiting most from surgery.
COVID‐19 pneumonia started in December 2019 and caused large casualties and huge economic losses. In this study, we intended to develop a computer‐aided diagnosis system based on artificial ...intelligence to automatically identify the COVID‐19 in chest computed tomography images. We utilized transfer learning to obtain the image‐level representation (ILR) based on the backbone deep convolutional neural network. Then, a novel neighboring aware representation (NAR) was proposed to exploit the neighboring relationships between the ILR vectors. To obtain the neighboring information in the feature space of the ILRs, an ILR graph was generated based on the k‐nearest neighbors algorithm, in which the ILRs were linked with their k‐nearest neighboring ILRs. Afterward, the NARs were computed by the fusion of the ILRs and the graph. On the basis of this representation, a novel end‐to‐end COVID‐19 classification architecture called neighboring aware graph neural network (NAGNN) was proposed. The private and public data sets were used for evaluation in the experiments. Results revealed that our NAGNN outperformed all the 10 state‐of‐the‐art methods in terms of generalization ability. Therefore, the proposed NAGNN is effective in detecting COVID‐19, which can be used in clinical diagnosis.
Multidrug resistance (MDR) occurs frequently after long-term chemotherapy, resulting in refractory cancer and tumor recurrence. Therefore, combatting MDR is an important issue. Autophagy, a ...self-degradative system, universally arises during the treatment of sensitive and MDR cancer. Autophagy can be a double-edged sword for MDR tumors: it participates in the development of MDR and protects cancer cells from chemotherapeutics but can also kill MDR cancer cells in which apoptosis pathways are inactive. Autophagy induced by anticancer drugs could also activate apoptosis signaling pathways in MDR cells, facilitating MDR reversal. Therefore, research on the regulation of autophagy to combat MDR is expanding and is becoming increasingly important. We summarize advanced studies of autophagy in MDR tumors, including the variable role of autophagy in MDR cancer cells.
Abstract
Na-ion cathode materials operating at high voltage with a stable cycling behavior are needed to develop future high-energy Na-ion cells. However, the irreversible oxygen redox reaction at ...the high-voltage region in sodium layered cathode materials generates structural instability and poor capacity retention upon cycling. Here, we report a doping strategy by incorporating light-weight boron into the cathode active material lattice to decrease the irreversible oxygen oxidation at high voltages (i.e., >4.0 V vs. Na
+
/Na). The presence of covalent B–O bonds and the negative charges of the oxygen atoms ensures a robust ligand framework for the NaLi
1/9
Ni
2/9
Fe
2/9
Mn
4/9
O
2
cathode material while mitigating the excessive oxidation of oxygen for charge compensation and avoiding irreversible structural changes during cell operation. The B-doped cathode material promotes reversible transition metal redox reaction enabling a room-temperature capacity of 160.5 mAh g
−1
at 25 mA g
−1
and capacity retention of 82.8% after 200 cycles at 250 mA g
−1
. A 71.28 mAh single-coated lab-scale Na-ion pouch cell comprising a pre-sodiated hard carbon-based anode and B-doped cathode material is also reported as proof of concept.
Computer-aided diagnosis system is becoming a more and more important tool in clinical treatment, which can provide a verification of the doctors’ decisions. In this paper, we proposed a novel ...abnormal brain detection method for magnetic resonance image. Firstly, a pre-trained AlexNet was modified with batch normalization layers and trained on our brain images. Then, the last several layers were replaced with an extreme learning machine. A searching method was proposed to find the best number of layers to be replaced. Finally, the extreme learning machine was optimized by chaotic bat algorithm to obtain better classification performance. Experiment results based on 5 × hold-out validation revealed that our method achieved state-of-the-art performance.
Lithium‐rich layered oxides with the capability to realize extraordinary capacity through anodic redox as well as classical cationic redox have spurred extensive attention. However, the ...oxygen‐involving process inevitably leads to instability of the oxygen framework and ultimately lattice oxygen release from the surface, which incurs capacity decline, voltage fading, and poor kinetics. Herein, it is identified that this predicament can be diminished by constructing a spinel Li4Mn5O12 coating, which is inherently stable in the lattice framework to prevent oxygen release of the lithium‐rich layered oxides at the deep delithiated state. The controlled KMnO4 oxidation strategy ensures uniform and integrated encapsulation of Li4Mn5O12 with structural compatibility to the layered core. With this layer suppressing oxygen release, the related phase transformation and catalytic side reaction that preferentially start from the surface are consequently hindered, as evidenced by detailed structural evolution during Li+ extraction/insertion. The heterostructure cathode exhibits highly competitive energy‐storage properties including capacity retention of 83.1% after 300 cycles at 0.2 C, good voltage stability, and favorable kinetics. These results highlight the essentiality of oxygen framework stability and effectiveness of this spinel Li4Mn5O12 coating strategy in stabilizing the surface of lithium‐rich layered oxides against lattice oxygen escaping for designing high‐performance cathode materials for high‐energy‐density lithium‐ion batteries.
A heterostructured spinel Li4Mn5O12 encapulated lithium‐rich layered oxide cathode is designed by the controlled KMnO4 oxidiation strategy. Spinel Li4Mn5O12 is chosen due to its lattice stability against oxygen release as well as a 3D lithium diffusion framework with minimal Jahn–Teller distortion. Such uniform coating can suppress lattice oxygen release, associated phase transformation, and catalytic side reactions, consequently ensuring improved electrochemical performance.
As one of the most promising cathodes for rechargeable sodium‐ion batteries (SIBs), O3‐type layered transition metal oxides commonly suffer from inevitably complicated phase transitions and sluggish ...kinetics. Here, a NaLi0.05Ni0.3Mn0.5Cu0.1Mg0.05O2 cathode material with the exposed {010} active facets by multiple‐layer oriented stacking nanosheets is presented. Owing to reasonable geometrical structure design and chemical substitution, the electrode delivers outstanding rate performance (71.8 mAh g−1 and 16.9 kW kg−1 at 50C), remarkable cycling stability (91.9% capacity retention after 600 cycles at 5C), and excellent compatibility with hard carbon anode. Based on the combined analyses of cyclic voltammograms, ex situ X‐ray absorption spectroscopy, and operando X‐ray diffraction, the reaction mechanisms behind the superior electrochemical performance are clearly articulated. Surprisingly, Ni2+/Ni3+ and Cu2+/Cu3+ redox couples are simultaneously involved in the charge compensation with a highly reversible O3–P3 phase transition during charge/discharge process and the Na+ storage is governed by a capacitive mechanism via quantitative kinetics analysis. This optimal bifunctional regulation strategy may offer new insights into the rational design of high‐performance cathode materials for SIBs.
An O3‐type NaLi0.05Ni0.3Mn0.5Cu0.1Mg0.05O2 cathode material with exposed {010} active facets by multiple‐layer oriented stacking nanosheets is successfully constructed via reasonable structure design and chemical substitution. An optimal bifunctional regulation is demonstrated to be an efficient strategy to restrain the unfavorable multiphase transformation and greatly improve Na+ transport kinetics resulting in excellent performance for sodium‐ion batteries.
Recently, sensors that can imitate human skin have received extensive attention. Capacitive sensors have a simple structure, low loss, no temperature drift, and other excellent properties, and can be ...applied in the fields of robotics, human–machine interactions, medical care, and health monitoring. Polymer matrices are commonly employed in flexible capacitive sensors because of their high flexibility. However, their volume is almost unchanged when pressure is applied, and they are inherently viscoelastic. These shortcomings severely lead to high hysteresis and limit the improvement in sensitivity. Therefore, considerable efforts have been applied to improve the sensing performance by designing different microstructures of materials. Herein, two types of sensors based on the applied forces are discussed, including pressure sensors and strain sensors. Currently, five types of microstructures are commonly used in pressure sensors, while four are used in strain sensors. The advantages, disadvantages, and practical values of the different structures are systematically elaborated. Finally, future perspectives of microstructures for capacitive sensors are discussed, with the aim of providing a guide for designing advanced flexible and stretchable capacitive sensors via ingenious human‐made microstructures.
The advantages, disadvantages, and practical applications of several popular microstructures that are widely employed in capacitive sensors are summarized. A microstructured dielectric layer or electrode can improve sensor sensitivity, reduce hysteresis, and endow the rigid electronic device with excellent elastic stretchability, which is an essential part of next‐generation wearable devices and soft robots.
In radiomics studies, researchers usually need to develop a supervised machine learning model to map image features onto the clinical conclusion. A classical machine learning pipeline consists of ...several steps, including normalization, feature selection, and classification. It is often tedious to find an optimal pipeline with appropriate combinations. We designed an open-source software package named FeAture Explorer (FAE). It was programmed with Python and used NumPy, pandas, and scikit-learning modules. FAE can be used to extract image features, preprocess the feature matrix, develop different models automatically, and evaluate them with common clinical statistics. FAE features a user-friendly graphical user interface that can be used by radiologists and researchers to build many different pipelines, and to compare their results visually. To prove the effectiveness of FAE, we developed a candidate model to classify the clinical-significant prostate cancer (CS PCa) and non-CS PCa using the PROSTATEx dataset. We used FAE to try out different combinations of feature selectors and classifiers, compare the area under the receiver operating characteristic curve of different models on the validation dataset, and evaluate the model using independent test data. The final model with the analysis of variance as the feature selector and linear discriminate analysis as the classifier was selected and evaluated conveniently by FAE. The area under the receiver operating characteristic curve on the training, validation, and test dataset achieved results of 0.838, 0.814, and 0.824, respectively. FAE allows researchers to build radiomics models and evaluate them using an independent testing dataset. It also provides easy model comparison and result visualization. We believe FAE can be a convenient tool for radiomics studies and other medical studies involving supervised machine learning.
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