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Nan-Nan Du, Jia-Mei Feng, Shi-Jun Shao, Hua Wan, Xue-Qing Wu Breast Department, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200021, People’s Republic of ChinaCorrespondence: Xue-Qing Wu; Hua Wan, Breast Department, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200021, People’s Republic of China, Tel +86 13817792022 ; +86 13611666266, Email snow_zi@hotmail.com; drwanhua@163.comBackground: Granulomatous lobular mastitis (GLM) is a chronic inflammatory breast disease, and abscess formation is a common complication of GLM. The process of abscess formation is accompanied by changes in multiple inflammatory markers. The present study aimed to construct a diagnosis model for the early of GLM abscess formation based on multiple inflammatory parameters.Methods: Based on the presence or absence of abscess formation on breast magnetic resonance imaging (MRI), 126 patients with GLM were categorised into an abscess group (85 patients) and a non-abscess group (41 patients). Demographic characteristics and the related laboratory results for the 9 inflammatory markers were collected. Logistics univariate analysis and collinearity test were used for selecting independent variables. A regression model to predict abscess formation was constructed using Logistics multivariate analysis.Results: The univariate and multivariate analysis showed that the N, ESR, IL-4, IL-10 and INF-α were independent diagnostic factors of abscess formation in GLM (P< 0. 05). The nomogram was drawn on the basis of the logistics regression model. The area under the curve (AUC) of the model was 0.890, which was significantly better than that of a single indicator and the sensitivity and specificity of the model were high (81.2% and 85.40%, respectively). These results predicted by the model were highly consistent with the actual diagnostic results. The results of this calibration curve indicated that the

Machine Translation has made impressive progress in recent years offering close to human-level performance on many languages, but studies have primarily focused on high-resource languages with broad online presence and resources. With the help of growing Large Language Models, more and more low-resource languages achieve better results through the presence of other languages. However, studies have shown that not all low-resource languages can benefit from multilingual systems, especially those with insufficient training and evaluation data. In this paper, we revisit state-of-the-art Neural Machine Translation techniques to develop automatic translation systems between German and Bavarian. We investigate conditions of low-resource languages such as data scarcity and parameter sensitivity and focus on refined solutions that combat low-resource difficulties and creative solutions such as harnessing language similarity. Our experiment entails applying Back-translation and Transfer Learning to automatically generate more training data and achieve higher translation performance. We demonstrate noisiness in the data and present our approach to carry out text preprocessing extensively. Evaluation was conducted using combined metrics: BLEU, chrF and TER. Statistical significance results with Bonferroni correction show surprisingly high baseline systems, and that Back-translation leads to significant improvement. Furthermore, we present a qualitative analysis of translation errors and system limitations., Comment: Preprint accepted at the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages (SIGUL 2024)

Guomin Gu,1 Bo Yu,2 Hua Wan,2 Suqiong Lu,1 Xiaodan Zhu,1 Yan Zhao,1 Yujing Fuxi,1 Chunling Liu1 1Department of Pulmonary Medicine, Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830011, People’s Republic of China; 2Department of Medicine, Beijing USCI Medical Laboratory, Beijing, 100195, People’s Republic of ChinaCorrespondence: Chunling Liu, Department of Pulmonary Medicine, Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Urumqi, Xinjiang, 830011, People’s Republic of China, +Tel/Fax +86-991-7819352, Email Liudeyouxiang66@sina.comPurpose: Non-small cell lung cancer (NSCLC) is a malignant tumor with high mortality. The Kirsten rat sarcoma vial oncogene (KRAS) gene can affect patient prognosis. In this study, we aim to explore the impact of KRAS mutation status on the clinical prognosis of NSCLC immunotherapy.Patients and Methods: Collected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 220 patients with stage III–IV NSCLC were included the study. All patients are on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we analysis of the effect of KRAS mutation on the treatment outcome of NSCLC.Results: In this study, the main mutant subtypes of KRAS were G12C, G12D, and G12V. In the KRAS mutation group, the highest mutation frequency other than KRAS was TP53, followed by STK11 and KMT2C. We found that among patients received immunotherapy, KRAS-mutant patients were more sensitive to immunotherapy, with an objective response rate (ORR) of 65% and a disease control rate (DCR) of 80%. Survival analysis found that patients with KRAS mutation had better prognosis with immunotherapy than the non-KRAS mutation patients by comparing the overall survival (OS) (median OS: 18.1 months vs 12.2 months, p=0.0032) and progression-free survival (PFS) (media PFS: 7.9 months vs 3.6 months, p=0.01). We found tha

Zhihong Wang,1,&ast; Peng Tang,2,&ast; Surong Hua,1 Junyi Gao,1 Bin Zhang,3 Hua Wan,4 Qixi Wu,4 Jiaxin Zhang,5 Ge Chen1 1Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Department of Breast and Thyroid Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, People’s Republic of China; 3Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 4Research and Development Department, Beijing USCI Medical Laboratory, Beijing, People’s Republic of China; 5Department of Thyroid and Breast Surgery, Affiliated Hospital of Xuzhou Medical University, Xuzhou, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ge ChenDepartment of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuai Fu Yuan Hu Tong, Beijing, 100730, People’s Republic of China, Tel +86 156 1123 3738, Fax +86 156 69152600, Email chenge@pumch.cn; Jiaxin ZhangDepartment of Thyroid and Breast Surgery, Affiliated Hospital of Xuzhou Medical University, No. 99, Huaihai West Road, Xuzhou, 221004, People’s Republic of China, Tel +86 180 5226 8693, Fax +86 180 85802306, Email zhangjiaxin1969@163.comPurpose: To describe the genetic landscape and clinical characteristics of Chinese patients diagnosed with papillary thyroid cancer (PTC) and to determine which high-risk genetic characteristics suggest a likelihood of lymph node metastasis (LNM) and lateral lymph node metastasis (LLNM).Patients and Methods: Data from previously untreated patients with PTC collected between May 2018 and December 2020 from 14 hospitals in China were analyzed retrospectively. High-risk pathologic characteristics were defined as T3/T4, N(+), and N1b(+) stages. All patients were tested for 57 genes by second-generation sequencing. The t-test, chi

Mei-Xiang Yu,1,* Xiao-Qin Ma,1,* Xin Song,2 Yong-Mei Huang,3 Hui-Ting Jiang,1 Jing Wang,1 Wan-Hua Yang1,4 1Department of Pharmacy, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200025, People’s Republic of China; 2South Campus, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 201100, People’s Republic of China; 3Jinshan Hospital, Shanghai Fudan University School of Medicine, Shanghai 201508, People’s Republic of China; 4Department of Pharmacy, Ruijin Hospital North Affiliated to the Shanghai Jiao Tong University Medical School, Shanghai 201801, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wan-Hua Yang Email yangwanhuaxy@163.comBackground: Shenjin Huoxue Mixture (SHM), a classic traditional herb mixture has shown significant clinical efficacy against osteoarthritis (OA). Our previous experimental study has confirmed its anti–inflammatory and analgesic effect on acute soft tissue injury in rats, with the compound of glycyrrhizinate in SHM identified and the content of paeoniflorin in SHM determined by high-performance liquid chromatography (HPLC). However, the components and its pharmacological mechanisms of SHM against OA have not been systematically elucidated yet. Thus this study aimed to predict the key active ingredients and potential pharmacological mechanisms of SHM in the treatment of OA by network pharmacology approach and thin-layer chromatography (TLC) validation.Methods: The active ingredients of SHM and their targets, as well as OA-related targets, were identified from databases. The key active ingredients were defined and ranked by the number of articles retrieved in PubMed using the keyword “(the active ingredients [Title/Abstract]) AND Osteoarthritis[Title/Abstract] ”, and validated partially by TLC. The pharmacological mechanisms of SHM against OA were displayed by GO term and Reactome

Taiwan is a country colonized by various regimes over the past four hundred years. The research first adopted the narrative inquiry-an autobiography on my journey to find my Taiwanese identity and mother tongue loss. Secondly, a phenomenological study on three Taiwanese families was conducted to secure an in-depth complex understanding on the scope and extent of the language loss phenomenon in Taiwan, of the thoughts and feelings about losing mother tongues, of the role of political power, the colonial history and other sociocultural contexts in the language loss phenomenon in Taiwan. Ten features and eleven themes were identified in this study. The political power and colonial history are important factors of mother tongue loss among my three participant families.

With China's rapid economic growth, chemical-related environmental issues have become increasingly prominent, and the environmental management of chemicals has garnered increased attention from the government. This review focuses on the current situation and the application of risk assessment in China's environmental management of industrial chemicals. The related challenges and research needs of the country are also discussed. The Chinese government promulgated regulations for the import and export of toxic chemicals in 1994. Regulations for new chemical substances came into force in 2003, and were revised in 2010 based on the concept of risk management. In order to support the implementation of new regulations, Guidance for Risk Assessment of Chemicals is under development in an attempt to provide the concepts and techniques of risk assessment. With increasing concern and financial support from Chinese government, China is embarking on the fast track of research and development in environmental management of industrial chemicals.