Pathologic fracture does not influence prognosis in stage IIB osteosarcoma: a case–control study

OBJECTIVE: This study tested the implication of pathologic fractures on the prognosis in stage IIb osteosarcoma. METHODS: A single center retrospective evaluation of clinical management and oncologic outcome was conducted with 15 pathological fracture patients (M:F = 10:5; age: mean 23.2, range 12–42) and 50 non-fracture patients between April 2002 and December 2010. These stage IIB osteosarcoma patients were matched for age, tumor site (femur, tibia, and humerus), and osteosarcoma subtype (i.e., control patients with osteosarcoma in the same sites as the fracture patients). All osteosarcoma patients with pathological fractures underwent brace or cast immobilization, adjuvant chemotherapy, and limb salvage surgery or amputation. Musculoskeletal Tumor Society (MSTS) functional scores were assessed. The mean follow-up time was 34.7 months (range, 8–47 months). RESULTS: Following limb salvage surgery, no statistical differences were observed in major complications (fracture = 20.0%, control = 12.0%, P = 0.43) or local recurrence complications (fracture = 26.7%, control = 14.0%, P = 0.25). Overall 3-year survival rates of the fracture and control groups (66.7% and 75.3%, respectively) were not statistically different (P = 0.5190). Three-year disease-free survival rates of the fracture and control groups were 53.3% and 66.5%, respectively (P = 0.25). CONCLUSIONS: Pathologic fracture was not a prognostic indicator of recurrence or overall survival in localized osteosarcoma patients. Limb salvage can be achieved by and maintaining adequate surgical margins and applying adjuvant chemotherapy

RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking

In various natural language processing tasks, passage retrieval and passage re-ranking are two key procedures in finding and ranking relevant information. Since both the two procedures contribute to the final performance, it is important to jointly optimize them in order to achieve mutual improvement. In this paper, we propose a novel joint training approach for dense passage retrieval and passage re-ranking. A major contribution is that we introduce the dynamic listwise distillation, where we design a unified listwise training approach for both the retriever and the re-ranker. During the dynamic distillation, the retriever and the re-ranker can be adaptively improved according to each other's relevance information. We also propose a hybrid data augmentation strategy to construct diverse training instances for listwise training approach. Extensive experiments show the effectiveness of our approach on both MSMARCO and Natural Questions datasets. Our code is available at https://github.com/PaddlePaddle/RocketQA.Comment: EMNLP 202

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation

Knowledge-intensive tasks (e.g., open-domain question answering (QA)) require a substantial amount of factual knowledge and often rely on external information for assistance. Recently, large language models (LLMs) (e.g., ChatGPT), have demonstrated impressive prowess in solving a wide range of tasks with world knowledge, including knowledge-intensive tasks. However, it remains unclear how well LLMs are able to perceive their factual knowledge boundaries, particularly how they behave when incorporating retrieval augmentation. In this study, we present an initial analysis of the factual knowledge boundaries of LLMs and how retrieval augmentation affects LLMs on open-domain QA. Specially, we focus on three primary research questions and analyze them by examining QA performance, priori judgement and posteriori judgement of LLMs. We show evidence that LLMs possess unwavering confidence in their capabilities to respond to questions and the accuracy of their responses. Furthermore, retrieval augmentation proves to be an effective approach in enhancing LLMs' awareness of knowledge boundaries, thereby improving their judgemental abilities. Additionally, we also find that LLMs have a propensity to rely on the provided retrieval results when formulating answers, while the quality of these results significantly impacts their reliance. The code to reproduce this work is available at https://github.com/RUCAIBox/LLM-Knowledge-Boundary

A-770041 reverses paclitaxel and doxorubicin resistance in osteosarcoma cells

Background: Reversing multidrug resistance (MDR) has been an important goal for clinical and investigational oncologists. In the last few decades, significant effort has been made to search for inhibitors to reverse MDR by targeting ATP-binding cassette (ABC) transporters (Pgp, MRP) directly, but these efforts have achieved little clinical success. Protein kinases play important roles in many aspects of tumor cell growth and survival. Combinations of kinase inhibitors and chemotherapeutics have been observed to overcome cancer drug resistance in certain circumstances. Methods: We screened a kinase specific inhibitor compound library in human osteosarcoma MDR cell lines to identify inhibitors that were capable of reversing chemoresistance to doxorubicin and paclitaxel. Results: We identified 18 small molecules that significantly increase chemotherapy drug-induced cell death in human osteosarcoma MDR cell lines U-2OSMR and KHOSR2. We identified A-770041 as one of the most effective MDR reversing agents when combined with doxorubicin or paclitaxel. A-770041 is a potent Src family kinase (Lck and Src) inhibitor. Western blot analysis revealed A-770041 inhibits both Src and Lck activation and expression. Inhibition of Src expression in U-2OSMR and KHOSR2 cell lines using lentiviral shRNA also resulted in increased doxorubicin and paclitaxel drug sensitivity. A-770041 increases the intracellular drug accumulation as demonstrated by calcein AM assay. Conclusions: These results indicate that small molecule inhibitor A-770041 may function to reverse ABCB1/Pgp-mediated chemotherapy drug resistance. Combination of Src family kinase inhibitor with regular chemotherapy drug could be clinically effective in MDR osteosarcoma. Electronic supplementary material The online version of this article (doi:10.1186/1471-2407-14-681) contains supplementary material, which is available to authorized users

Hydrogen atom collisions with a semiconductor efficiently promote electrons to the conduction band

The Born-Oppenheimer approximation is the keystone of modern computational chemistry and there is wide interest in understanding under what conditions it remains valid. Hydrogen atom scattering from insulator, semi-metal and metal surfaces has helped provide such information. The approximation is adequate for insulators and for metals it fails, but not severely. Here we present hydrogen atom scattering from a semiconductor surface: Ge(111)c(2 × 8). Experiments show bimodal energy-loss distributions revealing two channels. Molecular dynamics trajectories within the Born-Oppenheimer approximation reproduce one channel quantitatively. The second channel transfers much more energy and is absent in simulations. It grows with hydrogen atom incidence energy and exhibits an energy-loss onset equal to the Ge surface bandgap. This leads us to conclude that hydrogen atom collisions at the surface of a semiconductor are capable of promoting electrons from the valence to the conduction band with high efficiency. Our current understanding fails to explain these observations. [Abstract copyright: © 2022. The Author(s).

Simultaneous Impact of the Presence of Foreign MNEs on Indigenous Firms’ Exports and Domestic Sales

YesIncorporating the global production network approach and competitor analysis, this paper establishes an analytical framework with two hypotheses for the role of foreign multinational enterprises (FMNEs) in indigenous firms’ exports and domestic sales. First, the presence of FMNEs as a whole is likely to have a negative impact on indigenous firms’ domestic sales but a simultaneous positive impact on their exports in an emerging economy like China. Second, the presence of MNEs from Hong Kong, Macau and Taiwan (HMT MNEs) is more likely to generate this pattern of impact than MNEs from other countries (Other FMNEs). The FDI-led export strategy contributed to the dominance of the scenario described by the first hypothesis in China, while a higher degree of market commonality and resource similarity of HMT MNEs with that of indigenous Chinese firms than Other FMNEs leads to the second hypothesis. These novel hypotheses are tested and supported by a very large and recent firm-level panel dataset from Chinese manufacturing

Mesenchymal stem cells in the osteosarcoma microenvironment: their biological properties, influence on tumor growth, and therapeutic implications

Abstract During tumorigenesis and development, participation of the tumor microenvironment is not negligible. As an important component in the tumor microenvironment, mesenchymal stem cells (MSCs) have been corroborated to mediate proliferation, metastasis, and drug resistance in many cancers, including osteosarcoma. What’s more, because of tumor site tropism, MSCs can be engineered to be loaded with therapeutic agents so that drugs can be precisely delivered to tumor lesions. In this review, we mainly discuss recent advances concerning the functions of MSCs in osteosarcoma and their possible clinical applications in the future

Degree sums and dense spanning trees

<div><p>Finding dense spanning trees (DST) in unweighted graphs is a variation of the well studied minimum spanning tree problem (MST). We utilize established mathematical properties of extremal structures with the minimum sum of distances between vertices to formulate some general conditions on the sum of vertex degrees. We analyze the performance of various combinations of these degree sum conditions in finding dense spanning subtrees and apply our approach to practical examples. After briefly describing our algorithm we also show how it can be used on variations of DST, motivated by variations of MST. Our work provide some insights on the role of various degree sums in forming dense spanning trees and hopefully lay the foundation for finding fast algorithms or heuristics for related problems.</p></div

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