Early breast cancer screening using iron/iron oxide-based nanoplatforms with sub-femtomolar limits of detection

Citation: Udukala, D. N., Wang, H. W., Wendel, S. O., Malalasekera, A. P., Samarakoon, T. N., Yapa, A. S., . . . Bossmann, S. H. (2016). Early breast cancer screening using iron/iron oxide-based nanoplatforms with sub-femtomolar limits of detection. Beilstein Journal of Nanotechnology, 7, 364-373. doi:10.3762/bjnano.7.33Additional Authors: Ortega, R.;Toledo, Y.;Bossmann, L.;Robinson, C.;Janik, K. E.;Koper, O. B.;Motamedi, M.;Zhu, G. H.Proteases, including matrix metalloproteinases (MMPs), tissue serine proteases, and cathepsins (CTS) exhibit numerous functions in tumor biology. Solid tumors are characterized by changes in protease expression levels by tumor and surrounding tissue. Therefore, monitoring protease levels in tissue samples and liquid biopsies is a vital strategy for early cancer detection. Water-dispersable Fe/Fe3O4-core/shell based nanoplatforms for protease detection are capable of detecting protease activity down to sub-femtomolar limits of detection. They feature one dye (tetrakis(carboxyphenyl) porphyrin (TCPP)) that is tethered to the central nanoparticle by means of a protease-cleavable consensus sequence and a second dye (Cy 5.5) that is directly linked. Based on the protease activities of urokinase plasminogen activator (uPA), MMPs 1, 2, 3, 7, 9, and 13, as well as CTS B and L, human breast cancer can be detected at stage I by means of a simple serum test. By monitoring CTS B and L stage 0 detection may be achieved. This initial study, comprised of 46 breast cancer patients and 20 apparently healthy human subjects, demonstrates the feasibility of protease-activity-based liquid biopsies for early cancer diagnosis

Multi-technical approach for the characterization of polychrome decorative surfaces at Spanish Mission Churches in Nueva Vizcaya (Chihuahua, Mexico)

An interdisciplinary and multi-institutional group of science and art conservation specialists has provided new insight into the painting materials used in the polychrome walls and wooden ceilings in four seventeenth century Spanish colonial churches of Nueva Vizcaya (Chihuahua, Mexico). A multi-analytical study of the decorative surfaces was performed in situ using spectroscopic approaches (XRF, FORS), False Colour Infrared Reflectography–IRFC, as well as micro sampling (ATR-FTIR, LM, GC/MS). A survey of natural resources and study (ATR-FTIR, LM) was carried out to elucidate the natural occurrence of a select number of materials in the surrounding areas of the churches. The present paper presents a multi-analytical study and characterization of green, red-orange and black colour pigments and binders selected from the decorative surfaces. The aim of this study is to highlight relationships between local materials and those from the original polychrome ceilings, in order to understand the material and technological influences that converged in the Spanish colonial architecture of northern Mexico

PaLM 2 Technical Report

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more efficient inference compared to PaLM. This improved efficiency enables broader deployment while also allowing the model to respond faster, for a more natural pace of interaction. PaLM 2 demonstrates robust reasoning capabilities exemplified by large improvements over PaLM on BIG-Bench and other reasoning tasks. PaLM 2 exhibits stable performance on a suite of responsible AI evaluations, and enables inference-time control over toxicity without additional overhead or impact on other capabilities. Overall, PaLM 2 achieves state-of-the-art performance across a diverse set of tasks and capabilities. When discussing the PaLM 2 family, it is important to distinguish between pre-trained models (of various sizes), fine-tuned variants of these models, and the user-facing products that use these models. In particular, user-facing products typically include additional pre- and post-processing steps. Additionally, the underlying models may evolve over time. Therefore, one should not expect the performance of user-facing products to exactly match the results reported in this report