The energy band structure analysis and 2 µm Q-switched laser application of layered rhenium diselenide.

Layered rhenium diselenide (ReSe2) has triggered strong interest because of its outstanding optical and electrical properties. In this paper, we prepared a high-quality multilayer ReSe2 saturable absorber with a liquid-phase exfoliation method and characterized its saturable absorption properties around 2 µm. During the Q-switching regime, a maximum average output power of 1.7 W was obtained. A shortest pulse width of 925.8 ns was measured and the corresponding single pulse energy and peak power were 17.6 µJ and 19.0 W, respectively. The results indicate that layered ReSe2 is a promising alternative as a nonlinear optical modulator near the 2 µm region.

Aspidin PB, a novel natural anti-fibrotic compound, inhibited fibrogenesis in TGF-ß1-stimulated keloid fibroblasts via PI-3K/Akt and Smad signaling pathways.

Keloid is an overgrowth of scar tissue that develops around a wound. The mechanisms of keloid formation and development still remain unknown, and no effective treatment is available. Searching for active natural resources may develop better prevention and treatment approaches for keloids. Aspidin PB is a natural resource with lower toxicity. We explored its effect on the regulation of TGF-ß1-induced expression of type I collagen, CTGF, and α-SMA in keloid fibroblasts (KFs). Western blotting was used to detect the expression levels of type I collagen, CTGF, α-SMA, PI-3K/Akt and Smad-dependent and Smad-independent signaling pathway. The effect of aspidin PB on cell viability in human keloid fibroblasts was measured by MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide). The percentage of the apoptotic cells was studied by flow cytometry. Based on our results, we revealed that aspidin PB inhibited the production of type I collagen, CTGF, and α-SMA in TGF-ß1-induced KFs by blocking PI-3K/Akt signaling pathway. The TGF-ß1-mediated phosphorylated levels of Smad2/3 were inhibited by aspidin PB pretreatment. Conclusively, our study suggests that aspidin PB has an inhibitory effect on fibrogenesis in TGF-ß1-induced KFs. Our findings imply that aspidin PB has a therapeutic potential to intervene and prevent keloids and other fibrotic diseases.

Knowledge-based virtual screening of HLA-A*0201-restricted CD8+ T-cell epitope peptides from herpes simplex virus genome.

A novel knowledge-based method is developed to virtually screen potential HLA-A*0201 binders from large-scale peptide candidates. This method utilizes the information from both the crystal structures and experimental affinities of various peptides bound with HLA-A*0201 to construct a single-position mutation free energy profile for accurately characterizing HLA-A*0201-peptide interaction and for effectively predicting the binding affinities of peptides to HLA-A*0201. We employ this method to analyze physicochemical properties and structural implication underlying the specific recognition and association between the HLA-A*0201 and a large panel of peptide segments generated from the herpes simplex virus type 1 (HSV-1) genome, and to evaluate the binding potencies of these peptide candidates to HLA-A*0201. As a result, 288 out of 38,020 candidates are predicted as the potential high-affinity binders of HLA-A*0201, from which three most promising peptides are picked out for further development of potent vaccines against HSV-1. In addition, we also demonstrate that this newly proposed method can successfully identify 8 known binders and 3 known nonbinders from the glycoproteins D and K of HSV-1.

Stepwise identification of HLA-A*0201-restricted CD8+ T-cell epitope peptides from herpes simplex virus type 1 genome boosted by a StepRank scheme.

Identification of immunodominant epitopes is the first step in the rational design of peptide vaccines aimed at T-cell immunity. To date, however, it is yet a great challenge for accurately predicting the potent epitope peptides from a pool of large-scale candidates with an efficient manner. In this study, a method that we named StepRank has been developed for the reliable and rapid prediction of binding capabilities/affinities between proteins and genome-wide peptides. In this procedure, instead of single strategy used in most traditional epitope identification algorithms, four steps with different purposes and thus different computational demands are employed in turn to screen the large-scale peptide candidates that are normally generated from, for example, pathogenic genome. The steps 1 and 2 aim at qualitative exclusion of typical nonbinders by using empirical rule and linear statistical approach, while the steps 3 and 4 focus on quantitative examination and prediction of the interaction energy profile and binding affinity of peptide to target protein via quantitative structure-activity relationship (QSAR) and structure-based free energy analysis. We exemplify this method through its application to binding predictions of the peptide segments derived from the 76 known open-reading frames (ORFs) of herpes simplex virus type 1 (HSV-1) genome with or without affinity to human major histocompatibility complex class I (MHC I) molecule HLA-A*0201, and find that the predictive results are well compatible with the classical anchor residue theory and perfectly match for the extended motif pattern of MHC I-binding peptides. The putative epitopes are further confirmed by comparisons with 11 experimentally measured HLA-A*0201-restrcited peptides from the HSV-1 glycoproteins D and K. We expect that this well-designed scheme can be applied in the computational screening of other viral genomes as well.