Graph-Based Method for Calibration of High-Resolution Mass Spectra of Natural Organic Matter

Inaccuracies in ion detection and signal processing can undermine confidence in the molecular formula assignment of high-resolution mass spectrometry, which relies on precise matching of the mass-to-charge ratio (m/z). This study proposes a novel graph-based spectra calibration method, MSCMcalib, which implements coordinate transformation and pattern detection. MSCMcalib maps uncalibrated m/z data onto a modified 2D mass defect plot, facilitating the automatic calibration of detected lines, i.e., the calibration of uncalibrated peaks aligned with these lines. The “propagation” method is subsequently employed to accurately and automatically calibrate 605 m/z values across multiple lines, encompassing 98% of the m/z range. The calibrated m/z values divide the m/z range of the spectrum into multiple subintervals, with each subinterval undergoing a process of “scaling” calibration. The utilization of narrower partitions effectively mitigates divergence issues at both ends that arise from the polynomial fitting of errors against m/z. The effectiveness of MSCMcalib is validated through the calibration of SRFA data with m/z error ranges spanning from −10 to −6 ppm, resulting in an additional assignment of 11%–30% more molecular formulas compared to the quadratic fitting calibration

Graph-Based Method for Calibration of High-Resolution Mass Spectra of Natural Organic Matter

Inaccuracies in ion detection and signal processing can undermine confidence in the molecular formula assignment of high-resolution mass spectrometry, which relies on precise matching of the mass-to-charge ratio (m/z). This study proposes a novel graph-based spectra calibration method, MSCMcalib, which implements coordinate transformation and pattern detection. MSCMcalib maps uncalibrated m/z data onto a modified 2D mass defect plot, facilitating the automatic calibration of detected lines, i.e., the calibration of uncalibrated peaks aligned with these lines. The “propagation” method is subsequently employed to accurately and automatically calibrate 605 m/z values across multiple lines, encompassing 98% of the m/z range. The calibrated m/z values divide the m/z range of the spectrum into multiple subintervals, with each subinterval undergoing a process of “scaling” calibration. The utilization of narrower partitions effectively mitigates divergence issues at both ends that arise from the polynomial fitting of errors against m/z. The effectiveness of MSCMcalib is validated through the calibration of SRFA data with m/z error ranges spanning from −10 to −6 ppm, resulting in an additional assignment of 11%–30% more molecular formulas compared to the quadratic fitting calibration

Control of the Redox Activity of Quantum Dots through Introduction of Fluoroalkanethiolates into Their Ligand Shells

Increasing the fraction of 1<i>H</i>,1<i>H</i>,2<i>H</i>,2<i>H</i>-perfluorodecanethiol (PFDT) in the mixed-PFDT/oleate ligand shell of a PbS quantum dot (QD) dramatically reduces the permeability of the ligand shell to alkyl-substituted benzoquinones (s-BQs), as measured by a decrease in the efficiency of collisional photoinduced electron transfer. Replacing only 21% of the oleates on the QD surface with PFDT reduces the yield of photo-oxidation by tetramethyl BQ by 68%. Experiments with s-BQ quenchers of two different sizes reveal that the degree of protection provided by the PFDT-doped monolayer, relative to a decanethiolate (DT)-doped monolayer at similar coverage, is due to both size exclusion (PFDT is larger and more rigid than DT), and the oleophobicity of PFDT. This work demonstrates the usefulness of fluorinated ligands in designing molecule-selective and potentially corrosion-inhibiting surface coatings for QDs for applications as robust emitters or high fidelity sensing platforms

Reversible Modulation of the Electrostatic Potential of a Colloidal Quantum Dot through the Protonation Equilibrium of Its Ligands

This Letter describes the reversible modulation of the electrostatic potential at the interface between a colloidal PbS quantum dot (QD) and solvent, through the protonation equilibrium of the QD’s histamine-derivatized dihydrolipoic acid (DHLA) ligand shell. The electrostatic potential is sensitively monitored by the yield of photoinduced electron transfer from the QD to a charged electron acceptor, 9,10-anthraquinone-2-sulfonate (AQ). The permeability of the DHLA coating to the AQ progressively increases as the average degree of protonation of the ligand shell increases from 0 to 92%, as quantified by ¹H NMR, upon successive additions of <i>p</i>-toluenesulfonic acid; this increase results in a decrease in the photoluminescence (PL) intensity of the QDs by a factor of 6.7. The increase in permeability is attributable to favorable electrostatic interactions between the ligands and AQ. This work suggests the potential of the combination of near-IR-emitting QDs and molecular quenchers as robust local H⁺ sensors

Data_Sheet_1_Rice straw increases microbial nitrogen fixation, bacterial and nifH genes abundance with the change of land use types.docx

Soil microorganisms play an important role in soil ecosystems as the main decomposers of carbon and nitrogen. They have an indispensable impact on soil health, and any alterations in the levels of organic carbon and inorganic nitrogen can significantly affect soil chemical properties and microbial community composition. Previous studies have focused on the effects of carbon and nitrogen addition on a single type of soil, but the response of soil microorganisms to varying carbon and nitrogen inputs under different land soil use types have been relatively understudied, leaving a gap in our understanding of the key influencing factors. To address this gap, we conducted a study in the tropical regions of Hainan province, focusing on four distinct land use types: natural forest soil (NS), healthy banana soil (HS), diseased banana garden soil (DS), and paddy soil (PS). Within each of these environments, we implemented five treatments: CK, RS (rice straw), RSN (rice straw and NH4NO3), RR (rice root), and RRN (rice root and NH4NO3). Our aim was to investigate how soil bacteria response to changes in carbon and nitrogen inputs, and to assess their potential for biological nitrogen fixation. The results showed that the addition of rice straw increased the absorption and utilization of nitrate nitrogen by microorganisms. The addition of rice roots (RR) did not increase the absorption capacity of inorganic nitrogen by microorganisms, but increased the content of poorly soluble organic carbon. Most importantly, the addition of rice straw increased microbial respiration and the utilization efficiency of N2 by microorganisms, and the further addition of ammonium nitrate increased microbial respiration intensity. With the change of soil type, the rice straw increases microbial nitrogen fixation, bacterial and nifH genes abundance. Meanwhile, microbial respiration intensity is an important factor influencing the differences in the structure of bacterial communities. The addition of inorganic nitrogen resulted in ammonium nitrogen accumulation, reduced microbial richness and diversity, consequently diminishing the soil microorganisms to resist the environment. Therefore, we believe that with the change of soil types, corresponding soil nutrient retention strategies should be devised and incorporated while reducing the application of ammonium nitrogen, thus ensuring healthy soil development.</p

Bactericidal Dendritic Polycation Cloaked with Stealth Material via Lipase-Sensitive Intersegment Acquires Neutral Surface Charge without Losing Membrane-Disruptive Activity

Net cationicity of membrane-disruptive antimicrobials is necessary for their activity but may elicit immune attack when administered intravenously. By cloaking a dendritic polycation (G2) with poly­(caprolactone-<i>b</i>-ethylene glycol) (PCL-<i>b</i>-PEG), we obtain a nanoparticle antimicrobial, G2-<i>g</i>-(PCL-<i>b</i>-PEG), which exhibits neutral surface charge but kills >99.9% of inoculated bacterial cells at ≤8 μg/mL. The observed activity may be attributed PCL’s responsive degradation by bacterial lipase and the consequent exposure of the membrane-disruptive, bactericidal G2 core. Moreover, G2-<i>g</i>-(PCL-<i>b</i>-PEG) exhibits good colloidal stability in the presence of serum and insignificant hemolytic toxicity even at ≥2048 μg/mL. suggesting good blood compatibility required for intravenous administration

Mechanisms of Defect Passivation by Fluorinated Alkylthiolates on PbS Quantum Dots

Defects in the organic ligand layers on the surfaces of colloidal quantum dots (QDs) provide pathways for corrosive molecules to penetrate to the QD core. This paper describes the decrease in the permeability of the ligand shells of colloidal near-infrared-emitting PbS QDs to the molecular photo-oxidant, duroquinone (Me₄BQ), upon substituting a small fraction of their oleate ligands with either 1-dodecanethiolate (DDT) or progressively fluorinated DDT analogues (with between 1 and 10 fluorinated carbons), as measured by the yield of collisionally gated photoinduced electron transfer from the QD to Me₄BQ. The permeabilities of mixed-monolayer ligand shells of oleate and 8–16% (by surface area) DDT are 35–41% lower than those of the pure oleate monolayers. Increasing the number of fluorinated carbons in the thiolate ligands from 0 to 10 results in an additional 40–66% decrease in the permeability of the ligand shell; as few as 0.05% of collisions between the largest QDs and Me₄BQ result in electron transfer. The thiolate exchange, and fluorination of the thiolate ligands, more effectively protect the largest QDs than the smallest QDs, primarily due to the size-dependence of the types of defects in the native oleate monolayers

Molecular-level exploration of properties of dissolved organic matter in natural and engineered water systems: A critical review of FTICR-MS application

Dissolved organic matter (DOM) contains complex molecular compounds that dominate its heterogeneous dynamics and behaviors in aquatic environments. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with ultra-high resolution has proven to be effective in characterizing aquatic DOM. However, a systematic summary of molecular-level compositions and behaviors of DOM in natural and engineered water systems remains insufficient. This study provides a critical review of DOM characterization by FTICR-MS, with emphasis on composition diversity, chemical properties, transformation, and dynamics in the natural and engineered water systems. First, FTICR-MS strategies for DOM characterization are introduced on data interpretation and collaborative analysis of complementary datasets (e.g. spectroscopic data). Second, DOM characteristics, including spatiotemporal distribution, photochemical activity, microbial modification, and interface adsorption in natural water environments were comprehensively summarized based on current FTICR-MS findings. Third, DOM molecular changes caused by different engineered treatment methods were reviewed to highlight the molecular variation, reaction, and transformation by focusing on the FTICR-MS results. Finally, we summarized current limitations, biases, and future directions of FTICR-MS, and future extended studies of natural/engineered-derived DOM behavior. This FTICR-MS application review provides favorable strategies for understanding the molecular chemistry and behaviors of aquatic DOM.</p

Noncovalent Control of the Electrostatic Potential of Quantum Dots through the Formation of Interfacial Ion Pairs

This paper describes the role of tetraalkylammonium counterions [NR₄⁺, R = −CH₃, −CH₂CH₃, −(CH₂)₂CH₃, or −(CH₂)₃CH₃] in gating the electrostatic potential at the interface between the 6-mercaptohexanoate (MHA) ligand shell of a PbS quantum dot (QD) and water. The permeability of this ligand shell to a negatively charged anthraquinone derivative (AQ), measured from the yield of electron transfer (eT) from the QD core to AQ, increases as the steric bulk of NR₄⁺ increases (for a given concentration of NR₄⁺). This result indicates that bulkier counterions screen repulsive interactions at the ligand/solvent interface more effectively than smaller counterions. Free energy scaling analysis and molecular dynamics simulations suggest that ion pairing between the ligand shell of the QD and NR₄⁺ results from a combination of electrostatic and van der Waals components, and that the van der Waals interaction promotes ion pairing with longer-chain counterions and more effective screening. This work provides molecular-level details that dictate a nanoparticle’s electrostatic potential and demonstrates the sensitivity of the yield of photoinduced charge transfer between a QD and a molecular probe to even low-affinity binding events at the QD/solvent interface

Unraveling the Linkages between Molecular Abundance and Stable Carbon Isotope Ratio in Dissolved Organic Matter Using Machine Learning

Dissolved organic matter (DOM) is a complex mixture of molecules that constitutes one of the largest reservoirs of organic matter on Earth. While stable carbon isotope values (δ13C) provide valuable insights into DOM transformations from land to ocean, it remains unclear how individual molecules respond to changes in DOM properties such as δ13C. To address this, we employed Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to characterize the molecular composition of DOM in 510 samples from the China Coastal Environments, with 320 samples having δ13C measurements. Utilizing a machine learning model based on 5199 molecular formulas, we predicted δ13C values with a mean absolute error (MAE) of 0.30‰ on the training data set, surpassing traditional linear regression methods (MAE 0.85‰). Our findings suggest that degradation processes, microbial activities, and primary production regulate DOM from rivers to the ocean continuum. Additionally, the machine learning model accurately predicted δ13C values in samples without known δ13C values and in other published data sets, reflecting the δ13C trend along the land to ocean continuum. This study demonstrates the potential of machine learning to capture the complex relationships between DOM composition and bulk parameters, particularly with larger learning data sets and increasing molecular research in the future