The fluorescence-based optical imaging in the second near-infrared region (NIR-II, 1,000-1,700 nm) has broad applications in the biomedical field, but it is still difficult to find new NIR-II fluorescence materials in the two dimension. As a crucial characteristic of the electronic structure, the band structure determines the fundamental properties of two-dimensional materials, such as their optical excitations and electronic transportation. Therefore, we calculated the electronic structures and optical properties of different crystalline phases (1T phase and 2H phase) of pure monolayer MoS2 films and found that the 1T phase has better absorption and thus better fluorescence in the NIR-II window. However, its poor stability makes the 1T-phase MoS2 less useful in vivo bioimaging. By introducing vacancy defects and doping with foreign atoms, we successfully tuned the bandgap of the monolayer 2H-MoS2 and activated it in the NIR-II. Our results show that by engineering the vacancy defects, the bandgap of the 2H phase can be tailored to around 1 eV, and there are three candidates of vacancy structures that exhibit strong absorption in the NIR-II.Nanocomposites combining magnetic and plasmonic properties are very attractive within the field of surface-enhanced Raman scattering (SERS) spectroscopy. Avexitide Applications presented so far take advantage of not only the cooperation of both components but also synergy (enhanced properties), leading to multi-approach analysis. While many methods were proposed to synthesize such plasmonic-magnetic nanoparticles, the issue of their collective magnetic behavior, inducing irreversible self-aggregation, has not been addressed yet. Thus, here we present a simple and fast method to overcome this problem, employing 2-mercaptoethanesulfonate (MES) ions as both a SERS tag and primer molecules in the silica-coating process of the previously fabricated Fe3O4/Ag nanocomposite. The use of MES favored the formation of silica-coated nanomaterial comprised of well-dispersed small clusters of Fe3O4/Ag nanoparticles. Furthermore, adsorbed MES molecules provided a reliable SERS response, which was successfully detected after magnetic assembly of the Fe3O4/Ag@MES@SiO2 on the surface of the banknote. Improved chemical stability after coating with a silica layer was also found when the nanocomposite was exposed to suspension of yeast cells. This work reports on the application of 2-mercaptoethanesulfonate not only providing a photostable SERS signal due to a non-aromatic Raman reporter but also acting as a silica-coating primer and a factor responsible for a substantial reduction of the self-aggregation of the plasmonic-magnetic nanocomposite. Additionally, here obtained Fe3O4/Ag@MES@SiO2 SERS nanotags showed the potential as security labels for the authentication purposes, retaining its original SERS performance after deposition on the banknote.The development of accurate and efficient potential energy functions for the molecular dynamics simulation of metalloproteins has long been a great challenge for the theoretical chemistry community. An artificial neural network provides the possibility to develop potential energy functions with both the efficiency of the classical force fields and the accuracy of the quantum chemical methods. In this work, neural network potentials were automatically constructed by using the ESOINN-DP method for typical zinc proteins. For the four most common zinc coordination modes in proteins, the potential energy, atomic forces, and atomic charges predicted by neural network models show great agreement with quantum mechanics calculations and the neural network potential can maintain the coordination geometry correctly. In addition, MD simulation and energy optimization with the neural network potential can be readily used for structural refinement. The neural network potential is not limited by the function form and complex parameterization process, and important quantum effects such as polarization and charge transfer can be accurately considered. The algorithm proposed in this work can also be directly applied to proteins containing other metal ions.Rapid rise of antimicrobial resistance against conventional antimicrobials, resurgence of multidrug resistant microbes and the slowdown in the development of new classes of antimicrobials, necessitates the urgent development of alternate classes of therapeutic molecules. Antimicrobial peptides (AMPs) are small proteins present in different lifeforms in nature that provide defense against microbial infections. They have been effective components of the host defense system for a very long time. The fact that the development of resistance by the microbes against the AMPs is relatively slower or delayed compared to that against the conventional antibiotics, makes them prospective alternative therapeutics of the future. Several thousands of AMPs have been isolated from various natural sources like microorganisms, plants, insects, crustaceans, animals, humans, etc. to date. However, only a few of them have been translated commercially to the market so far. This is because of some inherent drawbacks of the naturallye commercially viable therapeutics of the future. This review entails the journey of the AMPs from their natural sources to the laboratory.Fe/Ti-oxides-modified-carbon nanotubes CNTs nanocomposites were prepared and tested toward Co removal from solution under different operational conditions. The final performance of the nanocomposites for Co was highly dependent on the type and loaded amount of the oxides. The nanocomposites were characterized by standard methods and the results evidenced that the presence of CNTs hampers the growth of Fe3O4 and TiO2 particles and forming smaller nano-particles leading to better Co removal from solution. Analysis of isotherms at different temperatures indicated that Co retention was two-fold increased upon adding Ti-oxides up to 90.2%. All isotherms were fairly presented using Langmuir-Freundlich isotherm and most surfaces have high heterogeneity particularly after deposition of oxides. The combined influence of the factors was investigated by running a multivariate analysis. An empirical equation was generated by principal component analysis (PCA) for predicting Co retention assuming different relationships and the binary-interaction behavior between factors was the most dominant Co retention (mg/g) = 5.