ACS Publications最新文献

Approaches for evaluating excited state wave functions and energies using diffusion Monte Carlo (DMC) with guiding functions (guided DMC) are discussed. For this work, the guiding functions are functions of a subset of the 3N - 6 coordinates that are needed to describe the structure of the molecule of interest. The DMC wave functions are used to evaluate intensities using two approaches. In the trial wave function approach, the product of the molecular wave function for one of the states involved in the transition and the guiding function for the second state is used to evaluate the matrix elements of the dipole moment. In the descendant weighting approach, descendant weights are used to evaluate the value of the wave function for one of the states involved in the transition at the geometries sampled by the DMC wave function for the second state. The descendant weighting approximation is shown to be more accurate as well as computationally more expensive compared to approximations that are based on various forms of the trial wave function approach. Strategies are explored, which combine results of different forms of the trial wave function approximation to minimize the errors in this approach. The trial wave function and descendant weighting approaches are applied to a study of a harmonic oscillator, where the sensitivity of the calculated energies and intensities to the quality of the trial wave function is explored. The two approaches are also applied to calculations of frequencies and intensities of transitions in water, H₃O₂^-, a four-dimensional (4D) model based on H₃O₂^- and H₅O₂⁺. We also show how comparisons of the results obtained using several forms of the trial wave function approach allow us to explore how couplings among vibrational motions are reflected in the intensities.

Sickle cell disease and β-Thalassemia are two of the most prevalent hemoglobinopathies worldwide. Both occur due to genetic mutations within the HBB gene and are characterized by red blood cell dysfunction, anemia, and end-organ injury. The spleen and liver are the primary organs where erythrophagocytosis, engulfing the red blood cells, occurs in these diseases. Understanding metabolism and protein composition within these tissues can therefore inform the extent of hemolysis and disease progression. We utilized a multiomics approach to highlight metabolomic and proteomic differences in the spleen and liver. The Berkley sickle cell disease (Berk-SS), heterozygous B1/B2 globin gene deletion (Hbb^Th3/+) a known β-Thalassemia model, and wildtype (WT, C57/Bl6) murine models were evaluated in this report. This analysis showed Berk-SS and Hbb^Th3/+ shared distinct antioxidant and immunosuppressive splenic phenotypes compared to WT mice with divergence in purine metabolism, gluconeogenesis, and glycolysis. In contrast, Berk-SS mice have a distinct liver pro-inflammatory phenotype not shared by Hbb^Th3/+ or WT mice. Together, these data emphasize that metabolic and proteomic reprogramming of the spleen and livers in Berk-SS and Hbb^Th3/+mice may be relevant to the individual disease processes.

Current diagnostic methods for JIA lack specificity, often failing to distinguish it from other childhood diseases of similar clinical presentations. The present study is a comparative cross-sectional study that identified potential biomarkers using label-free mass spectrometry and bioinformatics. Two differentially expressed proteins (DEPs), Myosin light chain 12b (Myl12b) and Mannose-binding lectin serine protease 1 (MASP1), showed increased expression in JIA patients. Receiver operating characteristic (ROC) analysis revealed strong predictive power (AUC: Myl12b = 0.757, MASP1 = 0.855), validated in a separate cohort via Western blot and ELISA. These findings suggest Myl12b and MASP1 as promising biomarkers for JIA diagnosis and treatment. Data: ProteomeXchange (PXD058863).

A novel strategy for C-P bond formation has been developed. The reaction employed aromatic carboxylic acids as the source of aromatic groups to couple with three types of P(O)-H₍₂₎ compounds without the need to isolate intermediates, thereby achieving a one-pot construction of carbon-phosphorus bonds. The protocol demonstrated excellent applicability and functional group tolerance, enabling the production of Ar-P(O)R₂ and Ar₂-PPh with moderate to excellent yields.

Photoenols, formed through photoinduced intramolecular H atom abstraction in o-alkyl-substituted arylketones, typically have limited utility as reactive intermediates owing to fast reversion to the starting material. Herein, we introduced an azido group on the o-alkyl substituent to render the photoreaction irreversible. Irradiation of 2-azidomethylbenzophenone (1) in methanol yielded 2-(hydroxy(phenyl)methyl)benzonitrile (2). Laser flash photolysis of 1 revealed the formation of biradical ³Br1 followed by intersystem crossing to photoenols Z-3 (τ ∼ 3.3 μs) and E-3 (τ > 45 μs), both of which reverted to 1. Alternatively, ³Br1 could lose N₂ to form ³Br2 (not detected), which decays to 2. In cryogenic argon matrices, irradiation of 1 yielded nitrene ³1N and 2 but no photoenols, likely because Z-3 regenerated 1. Both ESR spectroscopy and absorption analysis in methyltetrahydrofuran (80 K) confirmed ³1N formation. Upon prolonged irradiation, the absorbance of ³1N decreased, whereas that of 3 remained unchanged and that of 2 increased. Thus, T_K of 1 is proposed to form ³Br1 via H atom abstraction, with subsequent intersystem crossing to 3 competing with the loss of N₂ to generate ³Br2. DFT calculations revealed a small energy gap (∼2 kcal/mol) between the triplet and singlet configurations of Br2, supporting a mechanism in which ³Br2 intersystem crosses to yield 2.

Despite progress in ortho C-H functionalization of aromatic rings directed by guiding groups, achieving highly selective hydroxylation in simple systems without the need for additional ligand assistance remains a significant challenge. Here, we report the direct hydroxylation of the ortho C-H bond of aromatic rings directed by quinoline under Cu(II) catalysis. Based on experimental analysis and DFT calculations, the main reason for the high selectivity of the quinoline-directed hydroxylation reaction is that the match between the new substrate and the method leads to an increased range of oxygen source incorporation. Isotope experiments and DFT calculations provide support for the origin of the oxygen source in the hydroxylation process and the rationale behind its observed distribution. Additionally, the introduction of various nucleophiles enabled the cyanation, nitration, and halogenation of ortho C-H bonds in the aryl group.

The utilization of organophosphate pesticides (OPs) has escalated in response to the growing global food demand driven by a rapidly increasing population and the environmental disruptions caused by climate change. While acute exposure leads to cholinergic poisoning, chronic OP exposure has been linked to organ dysfunction, inflammation, and carcinogenesis. Serum samples from healthy individuals (n = 11), patients with acute OP exposure (n = 12), and those with chronic OP exposure (n = 31) were analyzed to discern the differentially expressed pathways after acute and chronic OP exposure. Differential expression analysis identified 132 proteins altered in chronic exposure vs control, 86 in acute exposure vs control, and 124 in chronic vs acute exposure. Pathway analysis revealed increased blood coagulation and reduced LXR/RXR activation and DCHR24 signaling in both acute and chronic exposures. Elevated levels of pro-inflammatory proteins, such as S100A8, VWF, and GPIBA, were observed, particularly in chronic exposure, highlighting significant inflammatory effects of OP exposure. These findings provide insights into the pathological mechanisms underlying chronic OP exposure and its contribution to inflammation and long-term health risks.

Estimating the false discovery rate (FDR) is one of the key steps in ensuring appropriate error control in the analysis of shotgun proteomics data. Traditional estimation methods typically rely on decoy sequence databases or spectral libraries, which may not always provide satisfactory results due to limitations of decoy construction methods. This study introduces the query mix-max (QMM) method, a decoy-free alternative for FDR estimation in proteomics. The QMM framework builds upon the existing mix-max procedure but replaces decoy matches with entrapment queries to estimate the number of false positive discoveries. Through simulations and real data set analyses, the QMM method was demonstrated to provide reasonably accurate FDR estimation across various scenarios, particularly when smaller sample-to-entrapment spectra ratios were achieved. The QMM method tends to be conservatively biased, particularly at higher FDR values, which can ensure stringent FDR control. While flexible, the protocol's effectiveness may vary depending on the evolutionary distance between the sample and entrapment organisms. It also requires a sufficient number of entrapment queries to provide stable FDR estimates, especially for low FDR values. Despite these limitations, the QMM method is a promising alternative as one of the first query-based FDR estimation approaches in shotgun proteomics.

Meningioma, the most prevalent brain tumor, poses significant challenges due to its unclear transition from low-grade to aggressive forms, with limited knowledge about grade-specific markers. We have utilized vibrational spectroscopic techniques such as ATR-FTIR and Raman spectroscopy, alongside LC-MS/MS-based mass spectrometry to understand the systemic cues and evaluate them for clinical practice. The acquired Raman and ATR-FTIR spectra of 46 meningioma patients (27 low-grade and 19 high-grade) and 8 healthy individuals revealed 98.15% and 83.33% accuracy based on PC-LDA. The grade classification revealed an accuracy of around 70%, implying the presence of subtypes and transition phases. The observed alterations corresponded to lipids, nucleic acids, and proteins. Further, the LC-MS/MS-based study identified different derivatives of cholines, indoles, lipids, sphingosine, tryptophan, and their respective metabolic pathways as contributors in tumorigenesis and progression. Further, PRM-based targeted validation and feature selection was carried out on 43 meningioma patients and 17 healthy controls. Glycochenodeoxycholic acid, indole-3-acetic acid, trans-3-indoleacrylic acid, glycodeoxycholic acid, 5α-dihydrotestosteroneglucornide, and glycocholic acid segregated meningioma samples with an accuracy of around 90% while features like indole-3-acetic acid, stercobilin, sphingosine-1-phosphate, deoxycholic acid, and citric acid could classify grades with around 70% accuracy. These findings suggest that further validation across larger cohorts could enhance its usage in clinical settings.

The variation in venom between and within snake species has significant implications for snakebite treatment. This highlights the critical importance of studying venom composition and its variations, not only for medical purposes but also from an evolutionary perspective. This study explores analytics for characterizing venom variability, focusing on venom toxin accurate masses, and emphasizes how the complexity of studying snake venom variability can be addressed by using liquid chromatography mass spectrometry (LC-MS) analysis with bioinformatics tools. This was demonstrated by investigating LC-MS data obtained from the venoms of 15 true cobras (Naja spp.), 5 mambas (Dendroaspis spp.) and 28 vipers (Crotalus and Bothrops spp.; total of 20 Elapidae and 28 Viperidae venoms), with newly developed bioinformatics tools. The measured LC-MS data was processed in an automated fashion and sorted based on the monoisotopic accurate masses of all toxins found, their peak intensities, and their retention times in LC. The data was then investigated using bioinformatic tools, before the toxin data available in open-source databases was used to predict the class of a toxin by means of its mass. This study highlights the importance of studying venom variability, which is performed by our combinatorial approach of intact-toxin analysis and toxin grouping by accurate mass.