2021-1-28, Schleusener, Johannes, Guo, Shuxia, Darvin, Maxim E., Thiede, Gisela, Chernavskaia, Olga, Knorr, Florian, Lademann, Jürgen, Popp, Jürgen, Bocklitz, Thomas W.

Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.

2020, He, Yongmin, Tang, Pengyi, Hu, Zhili, He, Qiyuan, Zhu, Chao, Wang, Luqing, Zeng, Qingsheng, Golani, Prafful, Gao, Guanhui, Fu, Wei, Huang, Zhiqi, Gao, Caitian, Xia, Juan, Wang, Xingli, Wang, Xuewen, Zhu, Chao, Ramasse, Quentin M., Zhang, Ao, An, Boxing, Zhang, Yongzhe, Martí-Sánchez, Sara, Morante, Joan Ramon, Wang, Liang, Tay, Beng Kang, Yakobson, Boris I., Trampert, Achim, Zhang, Hua, Wu, Minghong, Wang, Qi Jie, Arbiol, Jordi, Liu, Zheng

Atom-thin transition metal dichalcogenides (TMDs) have emerged as fascinating materials and key structures for electrocatalysis. So far, their edges, dopant heteroatoms and defects have been intensively explored as active sites for the hydrogen evolution reaction (HER) to split water. However, grain boundaries (GBs), a key type of defects in TMDs, have been overlooked due to their low density and large structural variations. Here, we demonstrate the synthesis of wafer-size atom-thin TMD films with an ultra-high-density of GBs, up to ~1012 cm−2. We propose a climb and drive 0D/2D interaction to explain the underlying growth mechanism. The electrocatalytic activity of the nanograin film is comprehensively examined by micro-electrochemical measurements, showing an excellent hydrogen-evolution performance (onset potential: −25 mV and Tafel slope: 54 mV dec−1), thus indicating an intrinsically high activation of the TMD GBs.

2021, Strobbia, Pietro, Cupil-Garcia, Vanessa, Crawford, Bridget M., Fales, Andrew M., Pfefer, T. Joshua, Liu, Yang, Maiwald, Martin, Sumpf, Bernd, Vo-Dinh, Tuan

For the majority of cancer patients, surgery is the primary method of treatment. In these cases, accurately removing the entire tumor without harming surrounding tissue is critical; however, due to the lack of intraoperative imaging techniques, surgeons rely on visual and physical inspection to identify tumors. Surface-enhanced Raman scattering (SERS) is emerging as a non-invasive optical alternative for intraoperative tumor identification, with high accuracy and stability. However, Raman detection requires dark rooms to work, which is not consistent with surgical settings. Methods: Herein, we used SERS nanoprobes combined with shifted-excitation Raman difference spectroscopy (SERDS) detection, to accurately detect tumors in xenograft murine model. Results: We demonstrate for the first time the use of SERDS for in vivo tumor detection in a murine model under ambient light conditions. We compare traditional Raman detection with SERDS, showing that our method can improve sensitivity and accuracy for this task. Conclusion: Our results show that this method can be used to improve the accuracy and robustness of in vivo Raman/SERS biomedical application, aiding the process of clinical translation of these technologies. © The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.