Kockgonzales2825

Plasmonic nanostructure-enabled label-free surface-enhanced Raman spectroscopy (SERS) emerges as a rapid nondestructive molecular fingerprint characterization technique for complex biological samples. However, label-free SERS bioanalysis faces challenges in reliability and reproducibility due to SERS signals' high susceptibility to local optical field variations at plasmonic hotspots, which can bias correlations between the measured spectroscopic features and the actual molecular concentration profiles of complex biochemical matrices. Herein, we report that plasmonically enhanced electronic Raman scattering (ERS) signals from metal nanostructures can serve as a SERS calibration internal standard to improve multivariate analysis of living biological systems. Through side-by-side comparisons with noncalibrated SERS datasets, we demonstrate that the ERS-based SERS calibration can enhance supervised learning classification of label-free living cell SERS spectra in (1) subtyping breast cancer cells with different degrees of malignancy and (2) assessing cancer cells' drug responses at different dosages. Notably, the ERS-based SERS calibration has the advantages of excellent photostability under laser excitation, no spectral interference with biomolecule Raman signatures, and no occupation competition with biomolecules at hotspots. Therefore, we envision that the ERS-based SERS calibration can significantly boost the multivariate analysis performance in label-free SERS measurements of living biological systems and other complex biochemical matrices.The development of computationally advantageous methods for the study of large systems is a long-standing research topic in theoretical chemistry. Among these techniques, a prominent place is certainly occupied by the multiscale embedding strategies, from the well-known QM/MM (quantum mechanics/molecular mechanics) methods to the latest and promising fully quantum mechanical approaches. In this Feature Article, we will briefly review the recently proposed QM/ELMO (quantum mechanics/extremely localized molecular orbital) scheme, namely a new multiscale embedding strategy in which the most chemically relevant region of the investigated system is treated at fully quantum chemical level, while the remaining part (namely, the environment) is described by means of transferred extremely localized molecular orbitals that remain frozen throughout the computation. Other than highlighting the theoretical bases, here we will also review the main results obtained through all the currently available variants of the novel mntext of quantum crystallography to perform unprecedented accurate refinements of macromolecular crystal structures.Per and polyfluoroalkyl substances (PFAS) cocontamination with nonaqueous-phase organic liquids (NAPLs) has been observed or suspected at various sites, particularly at fire-training areas at which aqueous film-forming foams (AFFFs) were applied. The objectives of this study are to (1) delineate the relative significance of specific PFAS-NAPL processes on PFAS retention, including partitioning into the bulk NAPL phase and adsorption to the NAPL-water interface; (2) investigate the influence of NAPL properties, saturation, and mass-transfer constraints on PFAS retention; and (3) determine whether PFAS may impact NAPL distribution through mobilization or dissolution. Nimbolide concentration Perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) are used as representative PFAS, and trichloroethene (TCE) and decane are used as representative NAPLs. NAPL-water interfacial adsorption was quantified with NAPL-water interfacial-tension measurements; partitioning into NAPL was quantified with batch experiments, and retardation factors (R) in the absence and presence of residual NAPL were determined with miscible-displacement transport experiments. R values increased in the presence of residual NAPL, with adsorption to the NAPL-water interface accounting for as much as ∼77% of retention and solid-phase adsorption also significantly contributing to retention. Additionally, this study provides the first QSPR analysis focused on NAPL-water interfacial adsorption coefficients, with results consistent with those from previous air-water studies. Lastly, this initial investigation into PFAS impacts on NAPL behavior determined that PFOS/PFOA are unlikely to enhance solubilization or mobilization of NAPL under the conditions present at many AFFF legacy sites.Class B G-protein-coupled receptors (GPCRs) remain an underexploited target for drug development. The calcitonin receptor (CTR) family is particularly challenging, as its receptors are heteromers comprising two distinct components the calcitonin receptor-like receptor (CLR) or calcitonin receptor (CTR) together with one of three accessory proteins known as receptor activity-modifying proteins (RAMPs). CLR/RAMP1 forms a CGRP receptor, CLR/RAMP2 forms an adrenomedullin-1 (AM1) receptor, and CLR/RAMP3 forms an adrenomedullin-2 (AM2) receptor. The CTR/RAMP complexes form three distinct amylin receptors. While the selective blockade of AM2 receptors would be therapeutically valuable, inhibition of AM1 receptors would cause clinically unacceptable increased blood pressure. We report here a systematic study of structure-activity relationships that has led to the development of first-in-class AM2 receptor antagonists. These compounds exhibit therapeutically valuable properties with 1000-fold selectivity over the AM1 receptor. These results highlight the therapeutic potential of AM2 antagonists.We introduce a new software, Efficient Detection of Hydrogen Bonds (EDHB), that systematically detects hydrogen bonds based on the nearest neighbors algorithm. EDHB classifies inter- and intramolecular hydrogen bonds as well as hydrogen bond networks. EDHB outperforms commonly used hydrogen bond detection methods in terms of speed of execution. An important additional feature of EDHB is that information from preceding quantum chemical studies (i.e., natural bond orbital analysis data and second energy derivative information) can be used to determine the electrostatic/covalent character of the hydrogen bonds and to calculate local-mode hydrogen bond force constants as a quantitative measure of their intrinsic strength. We applied EDHB to a diverse set of 163 proteins. We identified hydrogen bond networks forming intramolecular rings of different sizes as a common feature playing an important role for specific secondary structure orientations such as α-helixes and turns. However, these networks do not have a significant influence on the hydrogen bond strength.