RESUMO
Germanium is a promising material for mid-infrared (MIR) integrated photonics due to its CMOS compatibility and wide transparency window covering the fingerprint spectral region (2-15 µm). However, due to the limited quality and structural configurations of conventional germanium-based integration platforms, the realization of high-Q on-chip germanium resonators in the MIR spectral range remains challenging to date. Here we experimentally demonstrate an air-cladding MIR germanium microring resonator with, to the best of our knowledge, the highest loaded Q-factor of â¼57,000 across all germanium-based integration platforms to date. A propagation loss of 5.4 dB/cm and a high extinction ratio of 22 dB approaching the critical coupling condition are experimentally realized. These are enabled by our smart-cut methods for developing high-quality germanium-on-insulator wafers and by implementing our suspended-membrane structure. Our high-Q germanium microring resonator is a promising step towards a number of on-chip applications in the MIR spectral range.
RESUMO
Long-non-coding RNAs (lncRNAs) are defined as RNA sequences which are >200 nt with no coding capacity. These lncRNAs participate in various biological mechanisms, and are widely abundant in a diversity of species. There is well-documented evidence that lncRNAs can interact with genomic DNAs by forming triple helices (triplexes). Previously, several computational methods have been designed based on the Hoogsteen base-pair rule to find theoretical RNA-DNA:DNA triplexes. While powerful, these methods suffer from a high false-positive rate between the predicted triplexes and the biological experiments. To address this issue, we first collected the experimental data of genomic RNA-DNA triplexes from antisense oligonucleotide (ASO)-mediated capture assays and used Triplexator, the most widely used tool for lncRNA-DNA interaction, to reveal the intrinsic information on true triplex binding potential. Based on the analysis, we proposed six computational attributes as filters to improve the in-silico triplex prediction by removing most false positives. Further, we have built a new database, TRIPBASE, as the first comprehensive collection of genome-wide triplex predictions of human lncRNAs. In TRIPBASE, the user interface allows scientists to apply customized filtering criteria to access the potential triplexes of human lncRNAs in the cis-regulatory regions of the human genome. TRIPBASE can be accessed at https://tripbase.iis.sinica.edu.tw/.