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The topological charge of magnetic solitons gives rise to characteristic Hall-type effects, which allows to recognize the nontrivial topology of the spin textures, such as skyrmions or antiskyrmions. The selective manipulation of topological magnetic textures with different topological charges could substantially enrich potential applications but remains largely elusive. Here, we report an electrical control of net topological charge in a magnetic film hosting both skyrmions and antiskyrmions at finite magnetic field or bimerons and antibimerons at zero field, where their distinct responses to the current-induced torques result in a nonvolatile imbalance between the two oppositely charged topological textures. Both the magnitude and the sign of the resulting topological charge are found to be controllable efficiently by adjusting the orientation of the driving current with and without magnetic field. Our findings open the way to the on-demand manipulation of topological spin textures and provide more opportunities for designing spin-texture-based multifunctional devices. The selective manipulation of topological magnetic textures with different topological charges could substantially enrich applications but remains largely elusive. Here, the authors report on the electrical control of the net topological charge in a magnetic film hosting both skyrmions and antiskyrmions at finite magnetic field or bimerons and antibimerons at zero field. [ABSTRACT FROM AUTHOR]

Objective: Presentation delay of cancer patients prevents the patient from timely diagnosis and treatment leading to poor prognosis. Predicting the risk of presentation delay is crucial to improve the treatment outcomes. This study aimed to develop and validate prediction models of presentation delay risk in gastric cancer patients by using various machine learning models. Methods: 875 cases of gastric cancer patients admitted to a tertiary oncology hospital from July 2023 to June 2024 were used as derivation cohort, 200 cases of gastric cancer patients admitted to other 4 tertiary hospital were used as external validation cohort. After collecting the data, statistical analysis was performed to identify discriminative variables for the prediction of presentation delay and 13 statistically significant variables are selected to develop machine learning models. The derivation cohort was randomly assigned to the training and internal validation set by the ratio of 7:3. Prediction models were developed based on six machine learning algorithms, which are logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosted trees (GBDT), extremely gradient boosting (XGBoost) and muti-layer perceptron (MLP). The discrimination and calibration of each model were assessed based on various metrics including accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-Score and area under curve (AUC), calibration curves and Brier scores. The best model was selected based on comparing of various metrics. Based on the selected best model, the impact of features to the prediction result was analyzed with the permutation feature importance method. Results: The incidence of presentation delay for gastric cancer patients was 39.3%. The developed models achieved performance metrics as AUC (0.893-0.925), accuracy (0.817-0.847), sensitivity (0.857-0.905), specificity (0.783-0.854), PPV (0.728-0.798), NPV (0.897-0.927), F1 score (0.791-0.826) and Brier score (0.107-0.138) in internal validation set, which indicated good discrimination and calibration for the prediction of presentation delay in gastric cancer patients. Among all models, RF based model was selected as the best one as it achieved good discrimination and calibration performance on both of internal and external validation set. Feature ranking results indicated that both of subjective and objective factors have significant impact on the occurrence of presentation delay in gastric cancer patients. Conclusion: This study demonstrated that the RF based model has favorable performance for the prediction of presentation delay in gastric cancer patients. It can help medical staffs to screen out high-risk gastric cancer patients for presentation delay, and to take appropriate and specific interventions to reduce the risk of presentation delay. [ABSTRACT FROM AUTHOR]

CoFe-based catalysts have shown excellent activity for the oxygen evolution reaction (OER), with the oxidation states of the active sites playing a crucial role in determining catalytic performance. However, how to effectively increase the oxidation state of these active sites remains a key challenge. In this work, a facile treatment with NaBH4 solution was employed to modulate the surface state of CoFeOxHy catalysts, inducing an enhanced OER activity. The overpotential at 10 mA cm−2 for the NaBH4-treated CoFe catalyst was reduced to 270 mV, indicating improved OER activity. X-ray diffraction (XRD), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) results reveal that NaBH4 treatment induced a phase reconstruction of the CoFe oxalate framework, a critical step in enhancing its catalytic properties. The strong reducing ability of NaBH4 strengthened the Co-Fe interaction, allowing the retention of low-valence Co species while facilitating the formation of high-valence Fe sites. This dual modulation of Co and Fe oxidation states significantly accelerated charge transfer kinetics, ultimately boosting OER performance. These findings highlight the importance of improving the oxidation states of active sites in CoFe-based catalysts, providing insights for developing efficient catalysts for electrochemical water splitting. [ABSTRACT FROM AUTHOR]

The aircraft smart skin (ASS) with structural health monitoring capabilities is a promising technology. It enables the real-time acquisition of the aircraft's structural health status and service environment, thereby improving the performance of the aircraft and ensuring the safety of its operation, which in turn reduces maintenance costs. In this paper, a miniaturized and ultra-low-power wireless multi-parameter monitoring system (WMPMS) for ASS is developed, which is capable of monitoring multiple parameters of an aircraft, including random impact events, vibration, temperature, humidity, and air pressure. The system adopts an all-digital monitoring method and a low-power operating mechanism, and it is integrated into a low-power hardware design. In addition, considering the airborne resources limitations, an energy self-supply module based on a thermoelectric generator (TEG) is developed to continuously power the system during flight. Based on the above design, the system has a size of only 45 mm × 50 mm × 30 mm and an average power consumption of just 7.59 mW. Through experimental validation, the system has excellent performance in multi-parameter monitoring and operating power consumption, and it can realize the self-supply of energy. [ABSTRACT FROM AUTHOR]

The tumor secretome comprises the totality of protein factors secreted by various cell components within the tumor microenvironment, serving as the primary medium for signal transduction between tumor cells and between tumor cells and stromal cells. The deletion or mutation of the p53 gene leads to alterations in cellular secretion characteristics, contributing to the construction of the tumor microenvironment in a cell non-autonomous manner. This review discusses the critical roles of mutant p53 in regulating the tumor secretome to remodel the tumor microenvironment, drive tumor progression, and influence the plasticity of cancer-associated fibroblasts (CAFs) as well as the dynamics of tumor immunity by focusing on both secreted protein expression and secretion pathways. The aim is to provide new insights for targeted cancer therapies. [ABSTRACT FROM AUTHOR]