Additional file 2: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Table S2. The quality related genetic background diagnosis of parent lines. (XLSX 14 kb

Additional file 6: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Table S6. The yield and quality traits of RILs in four areas. (XLSX 143 kb

Additional file 3: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Table S3. QTL mapping for Texture properties of the RIL population in 2015. (XLSX 10 kb

Additional file 5: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Table S5. The QTL analysis of amylopectin chain length distribution. (XLSX 9 kb

Additional file 4: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Figure S1. The fine mapping of dep1. (a) The fine mapping of DEP1 using the data of amylopectin chain length distribution. (b) The sequence comparison of annotated genes in block 19,948. (c) The express preference of annotated genes in block 19,948. (d) The image of DEP1 mutant generated by CRISPR/Cas9 gene editing technology, and the taste score of mutant and WT (Sasanishiki). *, significant at 5% level. (XLSX 1871 kb

Additional file 1: of Effects of Genetic Background and Environmental Conditions on Texture Properties in a Recombinant Inbred Population of an Inter-Subspecies Cross

Table S1. The sowing, heading and mature date of RILs in four areas. (XLSX 27 kb

Additional file 1 of A hybrid model for hand-foot-mouth disease prediction based on ARIMA-EEMD-LSTM

Additional file 1

Integrated molecular modeling and dynamics approaches revealed the mechanism of selective inhibition of HDAC6/8

The high structural homology of histone deacetylases 6 and 8 (HDAC6/8) poses a challenge in achieving isoform selectivity and has resulted in adverse side effects due to pan-inhibition in clinical applications. Additionally, the rational design of dual-target inhibitors, centered on HDAC6/8, demands a profound understanding of their selectivity mechanisms. Addressing the urgent need for enhanced specificity in the development of inhibitors targeting specific isoforms, we elucidate the mechanism underpinning the selective inhibition of HDAC6/8 inhibitors through in-silico strategies. The hydrogen bonding interaction with Asp101 and Tyr306 is a key factor that enables compound 12b to selectively inhibit HDAC8. Its favorable spatial orientation places the Cap group of 12b between Tyr306 and Tyr100, resulting in an overall L-shaped conformation. These two factors significantly contribute to the selective inhibitory activity of 12b against HDAC8. The zinc binding group (ZBG) of compound NN-390 forms a hydrogen bond with His610, a key residue of HDAC6, facilitating stable chelation with zinc ions. In addition, the Cap group of NN-390 interacts with Phe620 and Phe680 via van der Waals forces, leading to an overall Y-shaped conformation. The aforementioned factors are the main reasons for the selective inhibition of HDAC6 by NN-390. Furthermore, whether the Cap group is in the para or meta-position will influence the selective inhibition of either HDAC6 or HDAC8. We believe these clues can offer valuable insights for the rational design of selective inhibitors targeting HDAC6/8 and pave the way for rational design of dual-target HDAC6/8-based inhibitors. Communicated by Ramaswamy H. Sarma</p

Additional file 2 of ATP6V1F is a novel prognostic biomarker and potential immunotherapy target for hepatocellular carcinoma

Additional file 2: Table S1. The top ranked and overlapping hub genes according to 11 topological algorithms in the PPI networks

Additional file 1 of ATP6V1F is a novel prognostic biomarker and potential immunotherapy target for hepatocellular carcinoma

Additional file 1: Figure S1. The PPI network of ATP6V1F constructed using the STRING database. Figure S2. TIDE scores in ATP6V1F-low and ATP6V1F-high groups in HCC. Set the top ¼ as high expression group and the bottom ¼ as low expression group. ****P < 0.0001. G1: low expression group, G2: high expression group. Figure S3. Western blot assays verified that ATP6V1F protein expression was successfully knocked down by si-ATP6V1F in Hepg2 and SMMC7721 cells (A). Statistical results of western blot assays (B). ***P < 0.001