PaperNet: A Dataset and Benchmark for Fine-Grained Paper Classification

Document classification is an important area in Natural Language Processing (NLP). Because a huge amount of scientific papers have been published at an accelerating rate, it is beneficial to carry out intelligent paper classifications, especially fine-grained classification for researchers. However, a public scientific paper dataset for fine-grained classification is still lacking, so the existing document classification methods have not been put to the test. To fill this vacancy, we designed and collected the PaperNet-Dataset that consists of multi-modal data (texts and figures). PaperNet 1.0 version contains hierarchical categories of papers in the fields of computer vision (CV) and NLP, 2 coarse-grained and 20 fine-grained (7 in CV and 13 in NLP). We ran current mainstream models on the PaperNet-Dataset, along with a multi-modal method that we propose. Interestingly, none of these methods reaches an accuracy of 80% in fine-grained classification, showing plenty of room for improvement. We hope that PaperNet-Dataset will inspire more work in this challenging area

A Versatile PDA(DOX) Nanoplatform for Chemo-Photothermal Synergistic Therapy against Breast Cancer and Attenuated Doxorubicin-Induced Cardiotoxicity

Abstract Photothermal therapy (PTT) is a highly clinical application promising cancer treatment strategy with safe, convenient surgical procedures and excellent therapeutic efficacy on superficial tumors. However, a single PTT is difficult to eliminate tumor cells completely, and tumor recurrence and metastasis are prone to occur in the later stage. Chemo-photothermal synergistic therapy can conquer the shortcomings by further killing residual tumor cells after PTT through systemic chemotherapy. Nevertheless, chemotherapy drugs' extreme toxicity is also a problematic issue to be solved, such as anthracycline-induced cardiotoxicity. Herein, we selected polydopamine nanoparticles (PDA) as the carrier of the chemotherapeutic drug doxorubicin (DOX) to construct a versatile PDA(DOX) nanoplatform for chemo-photothermal synergistic therapy against breast cancer and simultaneously attenuated DOX-induced cardiotoxicity (DIC). The excellent photothermal properties of PDA were used to achieve the thermal ablation of tumors. DOX carried out chemotherapy to kill residual and occult distant tumors. Furthermore, the PDA(DOX) nanoparticles significantly alleviate DIC, which benefits from PDA's excellent antioxidant enzyme activity. The experimental data of the chemotherapy groups showed that the results of the PDA(DOX) group were much better than the DOX group. This study not only effectively inhibits cancer but tactfully attenuates DIC, bringing a new perspective into synergistic therapy against breast cancer. Graphical Abstrac