Explore the vast range of titles available.

A comprehensive set of real-world environmental laboratory experiments This complete summary of laboratory work presents a richly detailed set of classroom-tested experiments along with background information, safety and hazard notes, a list of chemicals and solutions needed, data collection sheets, and blank pages for compiling results and findings. This useful resource also: * Focuses on environmental, i.e., \"dirty\" samples * Stresses critical concepts like analysis techniques and documentation * Includes water, air, and sediment experiments * Includes an interactive software package for pollutant fate and transport modeling exercises * Functions as a student portfolio of documentation abilities * Offers instructors actual samples of student work for troubleshooting, notes on each procedure, and procedures for solutions preparation.

In natural-product drug discovery, finding new compounds is the main task, and thus fast dereplication of known compounds is essential. This is usually performed by manual liquid chromatography-ultraviolet (LC-UV) or visible light-mass spectroscopy (Vis-MS) interpretation of detected peaks, often assisted by automated identification of previously identified compounds. We used a 15 min high-performance liquid chromatography–diode array detection (UHPLC–DAD)–high-resolution MS method (electrospray ionization (ESI) + or ESI − ), followed by 10–60 s of automated data analysis for up to 3000 relevant elemental compositions. By overlaying automatically generated extracted-ion chromatograms from detected compounds on the base peak chromatogram, all major potentially novel peaks could be visualized. Peaks corresponding to compounds available as reference standards, previously identified compounds, and major contaminants from solvents, media, filters etc. were labeled to differentiate these from compounds only identified by elemental composition. This enabled fast manual evaluation of both known peaks and potential novel-compound peaks, by manual verification of: the adduct pattern, UV–Vis, retention time compared with log D, co-identified biosynthetic related compounds, and elution order. System performance, including adduct patterns, in-source fragmentation, and ion-cooler bias, was investigated on reference standards, and the overall method was used on extracts of Aspergillus carbonarius and Penicillium melanoconidium , revealing new nitrogen-containing biomarkers for both species.

Liquid chromatography–high resolution mass spectrometry (LC-HRMS) is a well-established technique for nontarget screening of contaminants in complex environmental samples. Automatic peak detection is essential, but its performance has only rarely been assessed and optimized so far. With the aim to fill this gap, we used pristine water extracts spiked with 78 contaminants as a test case to evaluate and optimize chromatogram and spectral data processing. To assess whether data acquisition strategies have a significant impact on peak detection, three values of MS cycle time (CT) of an LTQ Orbitrap instrument were tested. Furthermore, the key parameter settings of the data processing software MZmine 2 were optimized to detect the maximum number of target peaks from the samples by the design of experiments (DoE) approach and compared to a manual evaluation. The results indicate that short CT significantly improves the quality of automatic peak detection, which means that full scan acquisition without additional MS 2 experiments is suggested for nontarget screening. MZmine 2 detected 75–100 % of the peaks compared to manual peak detection at an intensity level of 10 5 in a validation dataset on both spiked and real water samples under optimal parameter settings. Finally, we provide an optimization workflow of MZmine 2 for LC-HRMS data processing that is applicable for environmental samples for nontarget screening. The results also show that the DoE approach is useful and effort-saving for optimizing data processing parameters. Graphical Abstract ᅟ

Rice cultivation is one of the most significant human-created sources of methane gas. How to accurately measure the methane concentration produced by rice cultivation has become a major problem. The price of the automatic gas sampler used as a national standard for methane detection (HJ 38-2017) is higher than that of gas chromatography, which greatly increases the difficulty of methane detection in the laboratory. This study established a novel methane detection method based on manual injection and split pattern by changing the parameters of the national standard method without adding any additional automatic gas samplers. The standard curve and correlation coefficient obtained from the parallel determination of methane standard gas were y = 2.4192x + 0.1294 and 0.9998, respectively. Relative standard deviation (RSD, <2.82%), recycle rate (99.67–102.02%), limit of detection (LOD, 0.0567 ppm) and limit of quantification (LOQ, 0.189 ppm) of this manual injection method are satisfying, demonstrating that a gas chromatography-flame ionization detector (GC-FID), based on manual injection at a split ratio (SR) of 5:1, could be an effective and accurate method for methane detection. Methane gases produced by three kinds of low-methane rice treated with oxantel pamoate acid, fumaric acid and alcohol, were also collected and detected using the proposed manual injection approach Good peak shapes were obtained, indicating that this approach could also be used for quantification of methane concentration.

Our greater understanding of the importance of N -linked glycosylation in biological systems has spawned the field of glycomics and development of analytical tools to address the many challenges regarding our ability to characterize and quantify this complex and important modification as it relates to biological function. One of the unmet needs of the field remains a systematic method for characterization of glycans in new biological systems. This study presents a novel workflow for identification of glycans using Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy developed in our lab. This consists of monoisotopic mass extraction followed by peak pair identification of tagged glycans from a theoretical library using an in-house program. Identification and relative quantification could then be performed using the freely available bioinformatics tool Skyline. These studies were performed in the biological context of studying the N- linked glycome of differentiating xylem of the poplar tree, a widely studied model woody plant, particularly with respect to understanding lignin biosynthesis during wood formation. Through our workflow, we were able to identify 502 glycosylated proteins including 12 monolignol enzymes and 1 peroxidase (PO) through deamidation glycosite analysis. Finally, our novel semi-automated workflow allowed for rapid identification of 27 glycans by intact mass and by NAT/SIL peak pairing from a library containing 1573 potential glycans, eliminating the need for extensive manual analysis. Implementing Skyline for relative glycan quantification allowed for improved accuracy and precision of quantitative measurements over current processing tools which we attribute to superior algorithms correction for baseline variation and MS1 peak filtering. Graphical abstract Workflow for FANGS-INLIGHT glycosite profiling of plant xylem and monolignol proteins followed by INLIGHT tagging with semi-automated identification of glycans by light-heavy peak pairs. Finally, manual validation and relative quantification was performed in Skyline

To minimize chemical waste and protect the environment, our team has used green analysis with natural reagents. In this work, we designed a natural-reagent assay kit for iron determination and implemented it in chemistry education in Thailand. The iron assay method was adapted from Thai local wisdom of testing water quality using guava leaves. The guava leaf powder served as a natural reagent in the assay. The kit included equipment, standard and buffer solutions and a manual. A smart device with a built-in camera was used as a detector. Educators in six universities in Thailand implemented the kit in laboratories with modifications depending on their learning outcomes. The kit implementation was evaluated using a survey with questions in four aspects: usability, learning achievement, green chemistry and portability. The high average scores for all questions (> 4.00 of 5.00 points), with the average overall score of 4.53 ± 0.60, indicated satisfaction regarding in all aspects. Using a locally available bio-resource as a natural reagent for green analysis in chemistry education supported sustainable education in Thailand, in terms of quality education (SDG 4) and reduced inequalities (SDG 10) and environmental sustainability (SDG 6—Clean water and sanitation, 12—Responsible consumption and production and 14—Life be-low water).

A novel method of large volume of water samples directly introduced in dispersive liquid–liquid microextraction was developed, which is based on ultrasound/manual shaking-synergy-assisted emulsification and self-generating carbon dioxide gas (CO 2 ) breaking down the emulsion for the determination of 15 triazole fungicides by gas chromatography-tandem mass spectrometry. This technique makes low-density extraction solvent toluene (180 μL) dissolve in 200 mL of samples containing 0.05 mol L −1 of HCl and 5 % of NaCl (w/v) to form a well emulsion by synergy of ultrasound and manual shaking, and injects NaHCO 3 solution (1.0 mol L −1 ) to generate CO 2 achieving phase separation with the assistance of ultrasound. The entire process is accomplished within 8 min. The injection of NaHCO 3 to generate CO 2 achieves phase separation that breaks through the centrifugation limited large volume aqueous samples. In addition, the device could be easily cleaned, and this kind of vessel could be reconfigured for any volume of samples. Under optimal conditions, the low limits of detection ranging from 0.7 to 51.7 ng L −1 , wide linearity, and enrichment factors obtained were in the range 924–3669 for different triazole fungicides. Southern end of the Beijing-Hangzhou Grand Canal water (Hangzhou, China) was used to verify the applicability of the developed method. Graphical Abstract Flow chart of ultrasound/manual shaking-synergy-assisted emulsification and self-generating carbon dioxide gas breaking down the emulsion

BackgroundThere are concerns that altered thyroid functioning could be the result of ingesting too much fluoride. Community water fluoridation (CWF) is an important source of fluoride exposure. Our objectives were to examine the association between fluoride exposure and (1) diagnosis of a thyroid condition and (2) indicators of thyroid functioning among a national population-based sample of Canadians.MethodsWe analysed data from Cycles 2 and 3 of the Canadian Health Measures Survey (CHMS). Logistic regression was used to assess associations between fluoride from urine and tap water samples and the diagnosis of a thyroid condition. Multinomial logistic regression was used to examine the relationship between fluoride exposure and thyroid-stimulating hormone (TSH) level (low/normal/high). Other available variables permitted additional exploratory analyses among the subset of participants for whom we could discern some fluoride exposure from drinking water and/or dental products.ResultsThere was no evidence of a relationship between fluoride exposure (from urine and tap water) and the diagnosis of a thyroid condition. There was no statistically significant association between fluoride exposure and abnormal (low or high) TSH levels relative to normal TSH levels. Rerunning the models with the sample constrained to the subset of participants for whom we could discern some source(s) of fluoride exposure from drinking water and/or dental products revealed no significant associations.ConclusionThese analyses suggest that, at the population level, fluoride exposure is not associated with impaired thyroid functioning in a time and place where multiple sources of fluoride exposure, including CWF, exist.

Desorption electrospray ionization (DESI) mass spectrometry is an emerging technology for direct therapeutic drug monitoring in dried blood spots (DBS). Current DBS methods require manual application of small molecules as internal standards for absolute drug quantification. With industrial standardization in mind, we superseded the manual addition of standard and built a three-layer setup for robust quantification of salicylic acid directly from DBS. We combined a dioctyl sodium sulfosuccinate weave facilitating sample spreading with a cellulose layer for addition of isotope-labeled salicylic acid as internal standard and a filter paper for analysis of the standard-containing sample by DESI-MS. Using this setup, we developed a quantification method for salicylic acid from whole blood with a validated linear curve range from 10 to 2000 mg/L, a relative standard deviation (RSD%) ≤14 %, and determination coefficients of 0.997. The limit of detection (LOD) was 8 mg/L and the lower limit of quantification (LLOQ) was 10 mg/L. Recovery rates in method verification by LC-MS/MS were 97 to 101 % for blinded samples. Most importantly, a study in healthy volunteers after administration of a single dose of Aspirin provides evidence to suggest that the three-layer setup may enable individual pharmacokinetic and endpoint testing following blood collection by finger pricking by patients at home. Taken together, our data suggests that DBS-based quantification of drugs by DESI-MS on pre-manufactured three-layer cartridges may be a promising approach for future near-patient therapeutic drug monitoring.

This study investigated antimony exposure among employees in industries in Taiwan and evaluated whether their immunologic markers were associated with antimony exposure. We recruited 91 male workers and 42 male office administrators from 2 glass manufacturing plants, 1 antimony trioxide manufacturing plants, and 2 engineering plastic manufacturing plants. Air samples were collected at worksites and administrative offices, and each participant provided specimens of urine, blood, and hair to assay antimony levels. We also determined white blood cells, lymphocyte, and monocyte, IgA, IgE, and IgG in blood specimens. The mean antimony concentration in the air measured at worksites was much higher in the antimony trioxide plant (2.51 ± 0.57 mg/m3) than in plastic plants (0.21 ± 0.06 mg/m3) and glass plants (0.14 ± 0.01 mg/m3). Antimony levels in blood, urine, and hair measured for participants were correlated with worksites and were higher in workers than in administrators. The mean serum IgG, IgA, and IgE levels were lower in workers than in administrators (p < 0.001). Serum IgA and IgE levels in participants were negatively associated with antimony levels in air samples of workplaces, and in blood, urine, and hairs of participants. Serum IgG and IgE of all participants were also negatively associated with antimony levels in their hairs. In conclusion, the antimony exposure is greater for workers employed in the five industrial plants than for administrators. This study suggests serum IgG, IgA, and IgE levels are negatively associated with antimony exposure.