High-Abundance Protein-Guided Hybrid Spectral Library for Data-Independent Acquisition Metaproteomics.

Metaproteomics offers a direct avenue to identify microbial proteins in microbiota, enabling the compositional and functional characterization of microbiota. Due to the complexity and heterogeneity of microbial communities, in-depth and accurate metaproteomics faces tremendous limitations. One challenge in metaproteomics is the construction of a suitable protein sequence database to interpret the highly complex metaproteomic data, especially in the absence of metagenomic sequencing data. Herein, we present a high-abundance protein-guided hybrid spectral library strategy for in-depth data independent acquisition (DIA) metaproteomic analysis (HAPs-hyblibDIA). A dedicated high-abundance protein database of gut microbial species is constructed and used to mine the taxonomic information on microbiota samples. Then, a sample-specific protein sequence database is built based on the taxonomic information using Uniprot protein sequence for subsequent analysis of the DIA data using hybrid spectral library-based DIA analysis. We evaluated the accuracy and sensitivity of the method using synthetic microbial community samples and human gut microbiome samples. It was demonstrated that the strategy can successfully identify taxonomic compositions of microbiota samples and that the peptides identified by HAPs-hyblibDIA overlapped greatly with the peptides identified using a metagenomic sequencing-derived database. At the peptide and species level, our results can serve as a complement to the results obtained using a metagenomic sequencing-derived database. Furthermore, we validated the applicability of the HAPs-hyblibDIA strategy in a cohort of human gut microbiota samples of colorectal cancer patients and controls, highlighting its usability in biomedical research.

Nontarget Discovery of Per- and Polyfluoroalkyl Sulfonyl Halides in Soils by Integration of Derivatization and Specific Fragment-Based Liquid Chromatography-High Resolution Mass Spectrometry Screening.

Though long recognized as synthetic precursors to other poly- and perfluoroalkyl substances (PFASs), most poly- and perfluoroalkyl sulfonyl halides (PASXs) cannot be directly measured and have generally received minimal attention. Inspired by the redox reaction between sulfonyl halide groups and p-toluenethiol in organic chemistry, we developed a novel nontarget analysis strategy for PASXs by intergrating derivatization and specific fragment-based liquid chromatography-high resolution mass spectrometry screening for m/z 82.961 [SO2F-] and m/z 95.934 [S2O2-]. By using this strategy, we discovered 11 PASXs, namely, perfluoroalkyl sulfonyl fluorides (5), polyfluoroalkyl sulfonyl fluorides (2), unsaturated perfluoroalkyl sulfonyl fluoride (1), and perfluoroalkyl sulfonyl chlorides (3) in soil samples collected from an abandoned fluorochemical manufacturing park. These average ∑PASXs concentrations were 1120 µg kg-1 (range: 9.7-9860 µg kg-1), which were very likely to be the key intermediates and undesired byproducts of electrochemical fluorination processes. Spatial variation in the mass ratio of ∑PASXs to ∑PFSAs (range: 0.7-795%) also indicates their different transportation pathways. More importantly, the decline of PASXs and increase of perfluoroalkyl sulfonates (when compared to a prior study at this site) suggest the continued hydrolysis of PASXs and the relatively fast environmental transformation rates in the abandoned fluorochemical park soils. Overall, these findings demonstrated the utility of a novel nontarget analysis strategy, which may change most PASXs from inferred precursors to measured intermediates and further could be adapted for structures, distribution, and transformation studies of PFASXs in other matrices.

Natural Disinfection-like Process Unveiled in Soil Microenvironments by Enzyme-Catalyzed Chlorination.

Substantial natural chlorination processes are a growing concern in diverse terrestrial ecosystems, occurring through abiotic redox reactions or biological enzymatic reactions. Among these, exoenzymatically mediated chlorination is suggested to be an important pathway for producing organochlorines and converting chloride ions (Cl-) to reactive chlorine species (RCS) in the presence of reactive oxygen species like hydrogen peroxide (H2O2). However, the role of natural enzymatic chlorination in antibacterial activity occurring in soil microenvironments remains unexplored. Here, we conceptualized that heme-containing chloroperoxidase (CPO)-catalyzed chlorination functions as a naturally occurring disinfection process in soils. Combining antimicrobial experiments and microfluidic chip-based fluorescence imaging, we showed that the enzymatic chlorination process exhibited significantly enhanced antibacterial activity against Escherichia coli and Bacillus subtilis compared to H2O2. This enhancement was primarily attributed to in situ-formed RCS. Based on semiquantitative imaging of RCS distribution using a fluorescence probe, the effective distance of this antibacterial effect was estimated to be approximately 2 mm. Ultrahigh-resolution mass spectrometry analysis showed over 97% similarity between chlorine-containing formulas from CPO-catalyzed chlorination and abiotic chlorination (by sodium hypochlorite) of model dissolved organic matter, indicating a natural source of disinfection byproduct analogues. Our findings unveil a novel natural disinfection process in soils mediated by indigenous enzymes, which effectively links chlorine-carbon interactions and reactive species dynamics.

Metabolic and Microbial Profiling of Soil Microbial Community under Per- and Polyfluoroalkyl Substance (PFAS) Stress.

Per- and polyfluoroalkyl substances (PFAS) represent significant stress to organisms and are known to disrupt microbial community structure and function. Nevertheless, a detailed knowledge of the soil microbial community responding to PFAS stress at the metabolism level is required. Here we integrated UPLC-HRMS-based metabolomics data with 16S rRNA and ITS amplicon data across soil samples collected adjacent to a fluoropolymer production facility to directly identify the biochemical intermediates in microbial metabolic pathways and the interactions with microbial community structure under PFAS stress. A strong correlation between metabolite and microbial diversity was observed, which demonstrated significant variations in soil metabolite profiles and microbial community structures along with the sampling locations relative to the facility. Certain key metabolites were identified in the metabolite-PFAS co-occurrence network, functioning on microbial metabolisms including lipid metabolism, amino acid metabolism, and secondary metabolite biosynthesis. These results provide novel insights into the impacts of PFAS contamination on soil metabolomes and microbiomes. We suggest that soil metabolomics is an informative and useful tool that could be applied to reinforce the chemical evidence on the disruption of microbial ecological traits.

Probing Molecular-Level Dynamic Interactions of Dissolved Organic Matter with Iron Oxyhydroxide via a Coupled Microfluidic Reactor and an Online High-Resolution Mass Spectrometry System.

The interactions between dissolved organic matter (DOM) and iron (Fe) oxyhydroxide are crucial in regulating the biogeochemical cycling of nutrients and elements, including the preservation of carbon in soils. The mechanisms of DOM molecular assembly on mineral surfaces have been extensively studied at the mesoscale with equilibrium experiments, yet the molecular-level evolution of the DOM-mineral interface under dynamic interaction conditions is not fully understood. Here, we designed a microfluidic reactor coupled with an online solid phase extraction (SPE)-LC-QTOF MS system to continually monitor the changes in DOM composition during flowing contact with Fe oxyhydroxide at circumneutral pH, which simulates soil minerals interacting with constant DOM input. Time-series UV-visible absorption spectra and mass spectrometry data showed that after aromatic DOM moieties were first preferentially sequestered by the pristine Fe oxyhydroxide surface, the adsorption of nonaromatic DOM molecules with greater hydrophobicity, lower acidity, and lower molecular weights (<400) from new DOM solutions was favored. This is accompanied by a transition from mineral surface chemistry-dominated adsorption to organic-organic interaction-dominated adsorption. These findings provide direct molecular-level evidence to the zonal model of DOM assembly on mineral surfaces by taking the dynamics of interfacial interactions into consideration. This study also shows that coupled microfluidics and online high-resolution mass spectrometry (HRMS) system is a promising experimental platform for probing microscale environmental carbon dynamics by integrating in situ reactions, sample pretreatment, and automatic analysis.

Comparative pharmacokinetic study of nine bioactive components in osteoarthritis rat plasma using ultra-performance liquid chromatography-tandem mass spectrometry after single and combined oral administration of Epimedii Folium and Chuanxiong Rhizoma extracts.

The herb pair Epimedii Folium-Chuanxiong Rhizoma (EF-CR), derived from the classical traditional Chinese medicine 'Xian Ling Pi San', has a distinctive compatibility therapeutic profile and is clinically safe and effective. This study aimed to investigate and compare the pharmacokinetic characteristics of nine analytes in osteoarthritis (OA) rat plasma after the oral administration of EF, CR or a combination of these two herbs. We developed an ultra-performance liquid chromatography method coupled with quadrupole linear ion-trap mass spectrometry to simultaneously quantify and assess the pharmacokinetics of icariin, epimedin A, epimedin B, epimedin C, icariside I, icariside II, ferulic acid, ligustilide and senkyunolide A of the EF-CR pair in the plasma of osteoarthritic rats. The pharmacokinetic parameters showed that the absorption of multiple components was significantly enhanced and residence time was prolonged in the EF-CR group (P < 0.05) compared to the single-herb group. These parameters revealed that the combination of EF and CR exhibited synergistic effects of the nine bioactive components, suggesting the potential application of the EF-CR combination for the treatment of OA.

UPLC-Q-TOF/MS-Based Metabolomics Approach Reveals Osthole Intervention in Breast Cancer 4T1 Cells.

Osthole (OST) is a simple coumarin derivative with pharmacological effects in many types of cancer cells. However, its role and its mechanism of action in breast cancer 4T1 cells remain unclear. In this study, we explored the effects and potential mechanisms of action of OST in 4T1 cells. The MTT, PI, and Annexin V-FITC/PI methods were used to evaluate the effects of OST-treated and untreated 4T1 cells on viability, cell cycle, and apoptosis, respectively. UPLC-Q-TOF/MS combined with multivariate data analysis was used to screen potential biomarkers relevant to the therapeutic mechanisms of OST. Additionally, mTOR, SREBP1, and FASN protein levels were detected using western blotting in OST-treated and untreated 4T1 cells. OST inhibited 4T1 cell proliferation, blocked the cells from remaining in S-phase, and induced apoptosis. In 4T1 cells, OST mainly affected the phospholipid biosynthesis, methyl histidine metabolism, pyrimidine metabolism, and ß-oxidation of very long chain fatty acid pathways, suggesting that metabolic changes related to lipid metabolism-mediated signaling systems were the most influential pathways, possibly via inhibition of mTOR/SREBP1/FASN signaling. Our findings reveal biomarkers with potential therapeutic effects in breast cancer and provide insight into the therapeutic and metabolic mechanisms of OST in 4T1 cells.

N-doped CoAl oxides from hydrotalcites with enhanced oxygen vacancies for excellent low-temperature propane oxidation.

A series of nitrogen-doped CoAlO (N-CoAlO) were constructed by a hydrothermal route combined with a controllable NH3 treatment strategy. The effects of NH3 treatment on the physico-chemical properties and oxidation activities of N-CoAlO catalysts were investigated. In comparison to CoAlO, a smallest content decrease in surface Co3+ (serving as active sites) while a largest increased amount of surface Co2+ (contributing to oxygen species) are obtained over N-CoAlO/4h among the N-CoAlO catalysts. Meanwhile, a maximum N doping is found over N-CoAlO/4h. As a result, N-CoAlO/4h (under NH3 treatment at 400°C for 4 hr) with rich oxygen vacancies shows optimal catalytic activity, with a T90 (the temperature required to reach a 90% conversion of propane) at 266°C. The more oxygen vacancies are caused by the co-operative effects of N doping and suitable reduction of Co3+ for N-CoAlO/4h, leading to an enhanced oxygen mobility, which in turn promotes C3H8 total oxidation activity dominated by Langmuir-Hinshelwood mechanism. Moreover, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs) analysis shows that N doping facilities the decomposition of intermediate species (propylene and formate) into CO2 over the catalyst surface of N-CoAlO/4h more easily. Our reported design in this work will provide a promising way to develop abundant oxygen vacancies of Co-based catalysts derived from hydrotalcites by a simple NH3 treatment.

Amorphous Boron Dispersed in LaCoO3 with Large Oxygen Vacancies for Efficient Catalytic Propane Oxidation.

Unsatisfactory oxygen mobility is a considerable barrier to the development of perovskites for low-temperature volatile organic compounds (VOCs) oxidation. This work introduced small amounts of dispersed non-metal boron into the LaCoO3 crystal through an easy sol-gel method to create more oxygen defects, which are conducive to the catalytic performance of propane (C3 H8 ) oxidation. It reveals that moderate addition of boron successfully induces a high distortion of the LaCoO3 crystal, decreases the perovskite particle size, and produces a large proportion of bulk Co2+ species corresponding to abundant oxygen vacancies. Additionally, surface Co3+ species, as the acid sites, which are active for cleaving the C-H bonds of C3 H8 molecules, are enriched. As a result, the LCB-7 (molar ratio of Co/B=0.93:0.07) displays the best C3 H8 oxidation activity. Simultaneously, the above catalyst exhibits superior thermal stability against CO2 and H2 O, lasting 200 h. This work provides a new strategy for modifying the catalytic VOCs oxidation performance of perovskites by the regulation of amorphous boron dispersion.

Sensitive detection of caspase-3 enzymatic activities and inhibitor screening by mass spectrometry with dual maleimide labelling quantitation.

There is a great need to develop sensitive and specific methods for quantitative analysis of caspase-3 activities in cell apoptosis. Herein, we report a new method for sensitive detection of caspase-3 enzyme activities and inhibitor screening based on dual maleimide (DuMal) labeling quantitation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Evaluation of caspase-3 activities is performed using MS analysis of the enzymatic product of the peptide probe, which fuses a caspase-3 cleavable peptide segment (DEVD) and a quantifiable "ID tag" (a peptide segment of FRGLRGFKC labeled by maleimide). The DuMal labeling technique features non-isotopic tagging, rapid reactions, and reproducible quantitation. We have achieved quantitative analysis of the enzyme activities with a limit of detection (LOD) and limit of quantitation (LOQ) of caspase-3 down to 0.11 nM and 0.29 nM respectively and a proof-of-concept demonstration of its inhibitor screening. Our method has further been tested for caspase-3 activities in a Parkinson's disease cellular model, suggesting a useful tool for protease activity research.

Dual Maleimide Tagging for Relative and Absolute Quantitation of Cysteine-Containing Peptides by MALDI-TOF MS.

A dual maleimide (DuMal) tagging method has been developed for both relative and absolute quantitation of cysteine-containing peptides (CCPs) in combination with MALDI-TOF mass spectrometry. A pair of maleimides with minimal differences in their chemical structures, N-methylmaleimide and Nethylmaleimide, have been chosen to allow for the rapid (≈minutes) tagging of CCPs in the Michael addition reaction with high efficiency. It has been validated that the DuMal tagging technique is sensitive and reliable in the quantitative analysis of CCPs. Absolute quantitation of CCPs can be achieved with a detection limit as low as 7.3 nm. Relative quantitation of CCPs can be performed in various sample mixtures with consistent results (coefficient of variation <5 %). The DuMal tagging technique provides a sensitive and accurate approach for the quantitation of biomolecules containing thiol reactive sites; thus it is promising for protein detection, disease diagnosis, and biomarker discovery associated with post-translational modifications of cysteines.

[Microbial metaproteomics--From sample processing to data acquisition and analysis].

Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics.

BACKGROUND: Microbiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis. RESULTS: Herein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample. CONCLUSIONS: Overall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples. Video Abstract.

Advection-Dispersion Behavior for Simulation of H-3 and Pu-238 Transport in Undisturbed Argillaceous Shale of a Near-Surface Repository.

In this study, a column experiment was employed to evaluate the nuclide migration behavior in the surrounding rock medium of a near-surface disposal site in China and to investigate the advection-dispersion behavior of tritium (H-3) and plutonium-238 (Pu-238) in highly weathered argillaceous shale. A reasonable numerical model was selected to fit the experimental breakthrough curves (BTCs) and to obtain the relevant migration parameters. The results show the following: (1) the internal structure of the highly weathered argillaceous shale exhibited heterogeneity, and the nuclide migration BTC showed characteristics of a "curve peak moving forward" and a "tail curve trailing"; (2) compared with other models, the stream tube mode could better fit the BTCs and obtain the average dispersion coefficient , average distribution coefficient , and other parameters; (3) compared to the results of the batch experiment, the distribution coefficient Kd obtained from the column experiment was smaller than that obtained from the batch experiment, which is speculated to be due to the influence of contact time and the contact area between the nuclide and the medium.

Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota.

Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.

Effects of Lycium Barbarum Polysaccharides on the Metabolism of Dendritic Cells: An In Vitro Study.

Targeting dendritic cells (DCs) metabolism-related pathways and in-situ activation of DCs have become a new trend in DC-based immunotherapy. Studies have shown that Lycium barbarum polysaccharide can promote DCs function. This study is aimed at exploring the mechanism of LBP affecting DCs function from the perspective of metabolomics. MTT method was used to detect the activity of DC2.4 cells. ELISA kit method was used to detect the contents of IL-6, IL-12, and TNF-α in the supernatant of cells. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to detect general changes in DC2.4 cell metabolism. And then multidistance covariates and bioinformatics, partial least squares-discriminant analysis (PLS-DA) were used to analyze differential metabolites. Finally, metabolic pathway analysis was performed by MetaboAnalyst v5.0. The results showed that LBP had no significant inhibitory effect on the activity of DC2.4 cells at the experimental dose of 50-200 µg/ml. LBP (100 µg/ml) could significantly stimulate DC2.4 cells to secrete IL-6, TNF-α, and IL-12. Moreover, 20 differential metabolites could be identified, including betaine, hypoxanthine, L-carnitine, 5'-methylthioadenosine, orotic acid, sphingomyelin, and L-glutamine. These metabolites were involved 28 metabolic pathways and the top 5 metabolic pathways were aspartate metabolism, pyrimidine metabolism, phenylacetate metabolism, methionine metabolism, and fatty acid metabolism. These results suggest that the effect of LBP on DCs function is related to the regulation of cell metabolism.

High-throughput glycolytic inhibitor discovery targeting glioblastoma by graphite dots-assisted LDI mass spectrometry.

Malignant tumors will become vulnerable if their uncontrolled biosynthesis and energy consumption engaged in metabolic reprogramming can be cut off. Here, we report finding a glycolytic inhibitor targeting glioblastoma with graphite dots-assisted laser desorption/ionization mass spectrometry as an integrated drug screening and pharmacokinetic platform (GLMSD). We have performed high-throughput virtual screening to narrow an initial library of 240,000 compounds down to the docking of 40 compounds and identified five previously unknown chemical scaffolds as promising hexokinase-2 inhibitors. The best inhibitor (Compd 27) can regulate the reprogrammed metabolic pathway in U87 glioma cells (median inhibitory concentration ~ 11.3 µM) for tumor suppression. Highly effective therapy against glioblastoma has been demonstrated in both subcutaneous and orthotopic brain tumors by synergizing Compd 27 and temozolomide. Our glycolytic inhibitor discovery can inspire personalized medicine targeting reprogrammed metabolisms of malignant tumors. GLMSD enables large, high-quality data for next-generation artificial intelligence-aided drug development.

Assessment of bacterial viability by laser desorption ionization mass spectrometry for antimicrobial susceptibility testing.

Bacterial infection poses a serious threat to human health worldwide. Rapid antimicrobial susceptibility testing (AST) is essential for the clinical treatment of bacterial infection patients. However, the traditional AST relies on bacteria culture, which is time-consuming and limits the analysis to culturable species. Herein, we present a laser desorption ionization (LDI) mass spectrometry-based method for rapid bacterial viability assessment and AST by tracing the redox of resazurin (RS) by viable bacteria. RS as well as its reduction product, fluorescent resorufin (RF), can be directly detected by LDI-MS in the absence of matrix. The intensity ratio between RF and RS can be used to assess the viability of bacteria in specimens. We have demonstrated the high efficiency of the method using different bacterial species, including K. pneumoniae, S. aureus, E. coli, and P. aeruginosa, and various antibiotic drugs, such as ciprofloxacin, ampicillin, tetracycline, oxytetracycline, ciprofloxacin and levofloxacin. Compared to traditional methods based on optical absorption, the current method is faster and more sensitive. Furthermore, we applied the method to bacterial viability detection and AST using human body fluid samples, i.e. serum and urine, demonstrating that it can screen rapidly appropriate antibiotic drugs for timely clinical treatment of infectious diseases. With the advantages of simplicity in methodology as well as sensitivity and speed in analysis, the current method holds the potential of clinical usages.

Titanium-Enriched Slag Prepared by Atmospheric Hydrochloric Acid Leaching of Mechanically Activated Vanadium Titanomagnetite Concentrates.

The titanium-enriched slag was obtained via atmospheric hydrochloric acid leaching of mechanically activated vanadium titanomagnetite concentrates (VTMCs). Under the influence of mechanical activation, specific physicochemical changes were observed via X-ray diffractometry, scanning electron microscopy, and granulometric laser diffraction analysis. Experimental findings revealed that the mechanical activation of VTMCs resulted in a decrease in the median volume particle diameter (d50) and an increase in the specific surface area (SA) with an increased milling time. The results of the leaching experiment revealed that the mechanical activation treatment favors the extraction of iron (Fe) and titanium dioxide (TiO2) from the VTMCs. The Fe and TiO2 extractions from the mechanically activated sample after 10 h compared with the unactivated sample were increased by 12.82% and 4.73%, respectively. The presence of the ilmenite phase in the titanium-enriched slag was confirmed by X-ray diffractometry and EDS patterns, and the content of the TiO2 in the enriched slag can get as high as 43.75%.

An Improved Speciation Method Combining IC with ICPOES and Its Application to Iodide and Iodate Diffusion Behavior in Compacted Bentonite Clay.

An accurate and effective method combining ion chromatography (IC) and inductively coupled plasma optical emission spectrometry (ICP-OES) was applied in this work to qualitatively and quantitatively analyze individual and co-existing iodide (I-) and iodate (IO3-) at various concentrations. More specifically, a very strong linear relationship for the peak area for the co-existing I- and IO3- ions was reached, and a high resolution value between two peaks was observed, which proves the effectiveness of our combined IC-ICP-OES method at analyzing iodine species. We observed lower accessible porosity for the diffusion of both I- and IO3- in samples of bentonite clay using IC-ICP-OES detection methods, where the effective diffusion coefficient varied based on the anion exclusion effect and the size of the diffusing molecules. In fact, the distribution coefficients (Kd) of both I- and IO3- were close to 0, which indicates that there was no adsorption on bentonite clay. This finding can be explained by the fact that no change in speciation took place during the diffusion of I- and IO3- ions in bentonite clay. Our IC-ICP-OES method can be used to estimate the diffusion coefficients of various iodine species in natural environments.