A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.

The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affect treatment decision and patient prognosis. Thus, it is crucial to make a preliminary judgement on whether the tumor is benign or malignant with hematoxylin and eosin-stained images. A deep learning-based system, Soft Tissue Tumor Box (STT-BOX), is presented herein, with only hematoxylin and eosin images for malignant STT identification from benign STTs with histopathologic similarity.

RBF network-based adaptive sliding mode control strategy for the tendon-sheath driven joint of a prosthetic hand.

Background: The complex in-hand manipulation puts forward higher requirements for the dexterity and joint control accuracy of the prosthetic hand. The tendon-sheath drive has important application potential in the fields of prosthetic hand to obtain higher dexterity. However, the existing control methods of tendon-sheath driven joint are mainly open-loop compensation based on friction model, which makes it difficult to achieve high-precision joint control.

Basal Nanosuit of Graphite for High-Energy Hybrid Li Batteries.

Lithium (Li) metal anode has attracted tremendous attention for its highest capacity (3860 mAh g). Herein, we report that the formation of dead Li can be effectively suppressed through Li plating on porous lithiated graphite lamina (PLGL). A lithiophilic carbon layer was decorated on the lithiophobic basal plane of porous graphite lamina (PGL) with an industry-scalable slurry-coating strategy.

A Simple Method for the Complete Performance Recovery of Degraded Ni-rich LiNiCoMnO Cathode via Surface Reconstruction.

The highly active surfaces of Ni-rich cathodes usually result in rapid surface degradation, which is manifested by poor cycle and rate capabilities. In this work, we propose a simple method to restore those degraded surfaces after storage. More importantly, the mechanism of surface degradation and recovery are investigated thoroughly.

The correlation of PTPN4 expression with prognosis in breast cancer.

Precision medicine, applying knowledge of breast cancer's molecular subtypes, has improved the disease's prognosis. However, recurrence and chemoresistance are critical issues for breast cancer patients. PTPN4, a new potential therapeutic target, has not been studied sufficiently in breast cancer, and the potential role of PTPN4 in the prognosis of breast cancer patients is still unknown.