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Papillary thyroid carcinoma (PTC) is generally considered a highly indolent endocrine malignancy, often accompanied by cervical lymph node metastasis and rarely involving distant metastases. We present a rare case of a 37-year-old woman with PTC, who exhibited regional lymph node metastasis, right breast metastasis, and probable right psoas major and multiple bone metastases. Initial symptoms included hoarseness, and subsequent examination revealed a secondary malignant tumor in the right breast, originating from the thyroid gland. This case highlights an unusual pattern of multiple systemic metastasis in PTC, particularly the rare occurrence of breast metastasis. [ABSTRACT FROM AUTHOR]

In recent years, potential new therapeutic options have been yielded for the immunotherapy of invasive cancers. The most important breakthrough in breast cancer research today is to understand the immune features and profiles of triple negative breast cancer and then design novel immune-modulatory targeted therapy. The major findings are the use of immune checkpoint inhibitors, which have obtained good curative effect in neoadjuvant treatment for early stage triple negative breast cancer and salvage treatment for metastatic triple negative breast cancer. This paper summarizes the advances of immunotherapy and its application in triple negative breast cancer with emphasis on immune checkpoint inhibitor and its combination with chemotherapy, radiotherapy and targeted therapy.

In this paper, derived from the proportional–derivative control and robust control, a novel practical robust control method based on a dynamic feedforward model is established by taking six-axis motion cooperative industrial robots as the research object. The nonlinear friction, parameter uncertainty, and external disturbance are taken into consideration while establishing the dynamic model of the cooperative industrial robot. The method includes a proportional–derivative control and a robust control. Lyapunov theory is used to analyze the proposed controller, and it is shown that this method can guarantee uniformly bounded and uniformly final bounded systems. Simulation and experiment results show that the proposed controller is better than proportional–integral–derivative control and mode-based proportional–derivative control in stability tracking performance and robustness. In addition, the CSPACE platform for rapid controller prototyping may reduce the arduous programming effort and offer a lot of ease for the trials. [ABSTRACT FROM AUTHOR]

As industrial development and population growth continue, water pollution has become increasingly severe, particularly in rapidly industrializing regions like the area surrounding the Yopurga landfill. Ensuring water resource safety and environmental protection necessitates effective water quality monitoring and assessment. This paper explores the application of advanced machine learning technologies and the Water Quality Index (WQI) model as a comprehensive method for accurately assessing groundwater quality near the Yopurga landfill. The methodology involves selecting water quality indicators based on available data and the hydrochemical characteristics of the study area, comparing the performance of Decision Trees, Random Forest, and Xgboost algorithms in predicting water quality, and identifying the optimal algorithm to determine indicator weights. Indicators are scored using appropriate sub-index (SI) functions, and six different aggregation functions are compared to find the most suitable one. The study reveals that the Xgboost model surpasses Decision Trees and Random Forest models in water quality prediction. The top three indicator weights identified are pH, Manganese (Mn), and Nickel (Ni). The SWM model, with a 0% overestimation eclipsing rate and a 34% underestimation eclipsing rate, is chosen as the most appropriate WQI model for evaluating groundwater quality at the Yopurga landfill. According to the WQI results from the SWM aggregation function, the overall water quality in the area ranges from moderately polluted to slightly polluted. These assessment results provide a scientific basis for regional water environment protection. [ABSTRACT FROM AUTHOR]

Objective To analyse breast cancer incidence and mortality based on the data of Hubei cancer registries in 2012. Methods According to the breast cancer data collected from seven Hubei cancer registries, descriptive analysis included Hubei breast cancer incidence, distribution and mortality in 2012 stratified by areas, gender, age and cancer site. Results A total of 1830 cases of newly diagnosed breast cancers were reported in seven Hubei registries, including 1809(98.85%) female patients, accounting for 16.75% of female cancers; 443 cases breast cancer deaths, including 433(97.74%) cases of female breast cancer deaths, accounting for 8.31% of female cancer deaths. The crude incidence of female breast cancer was 44.81 per 10 million, among which, urban areas was 62.53 per 10 million and rural areas was 27.46 per 10 million; mortality was 10.73 per 10 million, among which, urban areas was 14.57 per 10 million and rural areas was 6.96 per million. Breast cancer incidence was the highest among female cancers, and the breast cancer mortality ranked as the fifth among female cancers. Female breast cancer incidence was bimodal distribution of 60-64 and 75-79 year-old groups; mortality increased within 0-59 years old and decreased slowly after 59 years old, then rapidly rose after 74 years old. Conclusion There is a significant difference of the breast cancer incidence and mortality between the annual Hubei Province's data and annual national data, providing a reliable basis according to which the government and the relational department could formulate prevention and control strategies and planning.