Suchergebnisse

Jiannan Liu,1,2 Feiyan Ma,3 Bing Sun,2 Yang Cong,2 Liang Xuan,2 Qian Wang,2 Shikai Wu2 1Academy of Military Medical Sciences, Beijing 100039, People's Republic of China; 2Department of Radiation Oncology, The Fifth Medical Center of Chinese PLA General Hospital (Former 307th Hospital of the PLA), Beijing 100071, People's Republic of China; 3Baoding No.1 Central Hospital Affiliated with Chengde Medical College, Baoding City, Hebei Province 071000, People's Republic of ChinaCorrespondence: Shikai WuDepartment of Radiation Oncology, The Fifth Medical Center of Chinese PLA General Hospital (Former 307th Hospital of the PLA), No. 8 East Road, Fengtai District, Beijing 100071, People's Republic of ChinaTel/Fax +86 10 66947621Email Skywu4923@sina.comPurpose: Various reports found a relationship between lymphocyte-related blood parameters (LRBP), including absolute lymphocyte counts (ALC), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) and prognosis of breast cancer. Most of the studies focused on LRBP pre-treatment. Seldom have studies focused on LRBP during radiotherapy. We intended to perform a retrospective cohort study on the prognostic value of LRBP at the time point of lowest ALC during radiotherapy for breast cancer.Patients and methods: A total of 158 female patients were included in radiotherapy group because of the strict limitation standards of complete routine blood test results at pre-treatment and pre-operation, and at least once a week during radiotherapy. Besides 221 patients, including the 158 patients of radiotherapy group, were adopted in pre-treatment group and pre-operation group.Results: ALC and PLR at the time point of lowest ALC during radiotherapy are prognostic predictors of breast cancer, and lower ALC and higher PLR are independent significant predictors of poor DFS. Besides, lower ALC, higher NLR and higher PLR at both pre-treatment and pre-operation were found to be independent variables for predicting poor DFS.Conclusion: LRBP at pre-treatment, pre-operation, and during radiotherapy may serve as predictors of outcomes of breast cancer.Keywords: breast cancer, radiotherapy, disease-free survival, lymphocyte-related blood parameters, lowest absolute lymphocyte counts

Public communication about science faces novel challenges, including the increasing complexity of research areas and the erosion of traditional journalistic infrastructures. Although scientists have traditionally been reluctant to engage in public communication at the expense of focusing on academic productivity, our survey of highly cited U.S. nano-scientists, paired with data on their social media use, shows that public communication, such as interactions with reporters and being mentioned on Twitter, can contribute to a scholar's scientific impact. Most importantly, being mentioned on Twitter amplifies the effect of interactions with journalists and other non-scientists on the scholar's scientific impact.

This study explores differences in volume of coverage and thematic content between US print news and online media coverage for an emerging technology – nanotechnology. We found that while American print news media and Google News coverage of this emerging technology has peaked and started to decline, Google Blog Search coverage of nanotechnology is still growing. Additionally, our data show discrepancies in thematic content of online and print news coverage. Specifically, online users are more likely to encounter environmentally themed content relating to nanotechnology than are users of American print newspapers. Differences in the amount of coverage of nanotechnology in print news and online media as well as thematic content suggest that public discourse on related issues will be shaped, in part, by media consumers' preferred information platform.

Chao Liu,1,2 Bing Sun,2 Bin Xu,1 Xiangying Meng,2 Lan Li,1 Yang Cong,2 Jiannan Liu,2 Qian Wang,2 Liang Xuan,2 Qibin Song,1 Shikai Wu2 1Cancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China; 2Department of Radiation Oncology, Affiliated Hospital of Academy of Military Medical Sciences, Beijing, People's Republic of China Introduction: Programmed cell death protein 1 (PD-1), an immune checkpoint molecule, has recently been recognized as a predictive and prognostic biomarker in several malignant tumors, but its diagnostic value remains largely unknown. We aimed to investigate the differential diagnostic efficiency of PD-1 and other immune molecules and propose a panel of immune molecules combined with cancer antigen 15-3 (CA15-3) to distinguish breast cancer (BC) from benign breast disease (BBD).Patients and methods: Ninety-one eligible BC patients and 31 BBD patients were enrolled. Pretreatment peripheral blood was collected and tested for mRNA expression of PD-1, cytotoxic T lymphocyte antigen 4, forkhead box P3, transforming growth factor beta, interleukin-10 (IL-10), IL-2 receptor alpha (IL-2Rα), and cluster of differentiation 28 by quantitative reverse transcription PCR.Results: The diagnostic areas under curve (AUCs) of PD-1, IL-2Rα, and IL-10 for BC–BBD discrimination were 0.764, 0.758, and 0.743, respectively. The diagnostic efficiencies of these three parameters in distinguishing early-stage or advanced BC from BBD were consistent with a role in BC–BBD discrimination. A panel of PD-1 + IL-10 + IL-2Rα + CA15-3 showed the highest AUC (0.862), with a sensitivity of 0.933 and a specificity of 0.724, for BC–BBD discrimination. In addition, for early-stage BC discrimination, this panel also had the highest AUC (0.811), with a sensitivity of 0.933 and a specificity of 0.614, while for advanced BC discrimination, a panel of PD-1 + IL-10 + CA15-3 exhibited the highest AUC (0.896), with a sensitivity of 0.933 and a specificity of 0.783.Conclusion: These data indicate that the panel containing PD-1, IL-2Rα, IL-10, and CA15-3 can effectively discriminate BC from BBD with a high efficiency. After further confirmation, it could be used to complement conventional imaging modalities, especially in discriminating early-stage BC from BBD. Keywords: breast cancer, immune checkpoint, PD-1, CTLA-4, IL-2Rα, diagnosis, biomarker