Comparative proteomic and clinicopathological analysis of breast adenoid cystic carcinoma and basal-like triple-negative breast cancer

BackgroundAdenoid cystic carcinoma (ACC) is a rare type of triple-negative breast cancer that has an indolent clinical behavior. Given the substantial overlapping morphological, immunohistochemical, and molecular features with other basal-like triple-negative breast cancer (BL-TNBC), accurate diagnosis of ACC is crucial for effective clinical treatment. The integrative analysis of the proteome and clinicopathological characteristics may help to distinguish these two neoplasms and provide a deep understanding on biological behaviors and potential target therapy of ACC.MethodsWe applied mass spectrometry-based quantitative proteomics to analyze the protein expression in paired tumor and adjacent normal breast tissue of five ACC and five BL-TNBC. Bioinformatic analyses and the clinicopathological characteristics, including histological features, immunohistochemistry, and FISH results, were also collected to get comprehensive information.ResultsA total of 307 differentially expressed proteins (DEPs) were identified between ACC and BL-TNBC. Clustering analysis of DEPs clearly separated ACC from BL-TNBC. GSEA found downregulation of the immune response of ACC compared with BL-TNBC, which is consistent with the negative PD-L1 expression of ACC. Vesicle-mediated transport was also inhibited, while ECM organization was enriched in ACC. The top upregulated proteins in DEPs were ITGB4, VCAN, and DPT. Moreover, in comparison with normal breast tissue, ACC showed elevated ribosome biogenesis and RNA splicing activity.ConclusionThis study provides evidence that ACC presents a substantially different proteomic profile compared with BL-TNBC and promotes our understanding on the molecular mechanisms and biological processes of ACC, which might be useful for differential diagnosis and anticancer strategy

Recent results on heavy-ion induced reactions of interest for neutrinoless double beta decay at INFN-LNS

Abstract. The possibility to use a special class of heavy-ion induced direct reactions, such as double charge exchange reactions, is discussed in view of their application to extract information that may be helpful to determinate the nuclear matrix elements entering in the expression of neutrinoless double beta decay halflife. The methodology of the experimental campaign presently running at INFN - Laboratori Nazionali del Sud is reported and the experimental challenges characterizing such activity are describe

Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based) model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to be addressed. In this study, a new energy demand forecasting framework is presented at first. On the basis of historical annual data of electricity usage over the period of 1985–2015, the coefficients of linear and quadratic forms of the AI-based model are optimized by combining an adaptive genetic algorithm and a cointegration analysis shown as an example. Prediction results of the proposed model indicate that the annual growth rate of electricity demand in China will slow down. However, China will continue to demand about 13 trillion kilowatt hours in 2030 because of population growth, economic growth, and urbanization. In addition, the model has greater accuracy and reliability compared with other single optimization methods

Trade-off and synergy analysis among ecosystem services in a karst watershed

The underground river watersheds in karst areas are undergoing the degradation of ecosystem functions, thus hindering the development of benefits to humans. Taking the Nandong underground river watershed (NURW) as a test case in southern China, this study evaluated net primary productivity (NPP), water yield (WY), and soil retention (SR) and the relationships between the three factors from 2000 to 2018. The results showed that (1) NPP exhibited a continuously rising trend from 2000 to 2018, and the WY and SR also increased in general; (2) land use was an important influencing factor for ecosystem services, and the synergy between the two improved since 2006; (3) the ecosystem synergy was poor in the NURW, and the conflicts among ecosystem services were especially severe in areas with a high incidence of rocky desertification. This study will provide a reference for regional governments by clarifying the possible future state of the ecosystem

The Impact of Foreign and Indigenous Innovations on the Energy Intensity of China’s Industries

China’s industrial sectors have an approximate consumption amounting to 70% of the aggregate power of the entire country. Investigating the driving forces of the decline in the energy intensity is essential for accelerating China’s conversion into a low-carbon economy. Nowadays, there has been no agreement as yet when it comes to the impacts of China’s industrial sectors on energy intensity. The current research work studies the impacts of key driving forces, in particular foreign as well as indigenous innovations, on China’s industrial energy intensity in 34 industrial sectors between 2000 and 2010. Linear and nonlinear analysis methodologies are put to use. The linear empirical findings show that indigenous innovation primarily contributes to driving down the industrial energy intensity across the sampling duration. The foreign innovations, which take the shape of FDI as well as imports, are seen as benefiting the decline in industrial energy intensity; on the other hand, exports ramp up the industrial energy intensity. An additional investigation, on the basis of the panel threshold framework, indicates that the impact of foreign innovations by means of openness as well as industrial energy intensity has an association with the technological absorptive potential. The empirical evidence puts forward some pivotal inferences for policymakers with regard to China’s declining industrial energy intensity—for instance, exploitation of the maximum benefit associated with the technology spillovers; in addition, it is important to take into consideration the attributes and scenarios that impact industrial energy intensity

The preoperative platelet–lymphocyte ratio neutrophil–lymphocyte ratio: which is better as a prognostic factor in oral squamous cell carcinoma?

Objective: Recent studies have shown that the presence of systemic inflammation and platelet status correlate with poor survival in various cancers. The aim of this study was to evaluate the prognostic value of the preoperative platelet–lymphocyte ratio (PLR) and the neutrophil–lymphocyte ratio (NLR) in patients with oral squamous cell carcinoma (OSCC) undergoing surgery. Methods: In this study, 306 patients with OSCC who had surgery were enrolled. The optimal cutoff value of PLR and NLR was determined by receiver operating characteristic (ROC) curve analysis. The prognostic significance of both markers was determined by uni- and multivariate analysis. Results: The results showed that high NLR and PLR were classified using a cutoff value of 2.7 and 135, respectively, based on ROC curve analysis. Only PLR was associated with decreased disease-free survival [hazard ratio (HR) = 2.237; 95% confidence interval (CI): 1.401–3.571; p = 0.001] and overall survival [HR = 2.022; 95% CI: 1.266–3.228; p = 0.003] by both uni- and multivariate analysis. Conclusion: The preoperative PLR is superior to NLR as an independent indicator in predicting disease-free survival and overall survival in patients who undergo oral cancer resection for OSCC

bayesianmixedmodelsanddivergencetimeestimationofchinesecavefishescyprinidaesinocyclocheilus

The genus Sinocyclocheilus is distributed in Yun-Gui Plateau and its surrounding region only, within more than 10 cave species showing different degrees of degeneration of eyes and pigmentation with wonderful adaptations. To present, published morphological and molecular phylogenetic hypotheses of Sinocyclocheilus from prior works are very different and the relationships within the genus are still far from clear. We obtained the sequences of cytochrome b (cyt b) and NADH dehydrogenase subunit 4 (ND4) of 34 species within Sinocyclocheilus, which represent the most dense taxon sampling to date. We performed Bayesian mixed models analyses with this data set. Under this phylogenetic framework, we estimated the divergence times of recovered clades using different methods under relaxed molecular clock. Our phyloegentic results supported the monophyly of Sinocyclocheilus and showed that this genus could be subdivided into 6 major clades. In addition, an earlier finding demonstrating the polyphyletic of cave species and the most basal position of S. jii was corroborated. Relaxed divergence-time estimation suggested that Sinocyclocheilus originated at the late Miocene, about 11 million years ago (Ma), which is older than what have been assumed