Examination of primary aromatic amines content in polylactic acid straws and migration into food simulants using SERS with LC-MS.

Polylactic acid (PLA) straws hold eco-friendly potential; however, residual diisocyanates used to enhance the mechanical strength can generate carcinogenic primary aromatic amines (PAAs), posing health risks. Herein, we present a rapid, comprehensive strategy to detecting PAAs in 18 brands of food-grade PLA straws and assessing their migration into diverse food simulants. Surface-enhanced Raman spectroscopy was conducted to rapidly screen straws for PAAs. Subsequently, qualitative determination of migrating PAAs into various food simulants (4 % acetic acid, 10 % ethanol, 50 % ethanol) occurred at 70 °C for 2 h using liquid chromatography-mass spectrometry. Three PAAs including 4,4'-methylenedianiline, 2,4'-methylenedianiline, and 2,4-diaminotoluene were detected in all straws. Specifically, 2,4-diaminotoluene in 50 % ethanol exceeded specific migration limit of 2 µg/kg, raising safety concerns. Notably, PAAs migration to 10 % and 50 % ethanol surpassed that to 4 % acetic acid within a short 2-hour period. Moreover, PLA straws underwent varying degrees of shape changes before and after migration. Straws with poly(butylene succinate) resisted deformation compared to those without, indicating enhanced heat resistance, while poly(butyleneadipate-co-terephthalate) improved hydrolysis resistance. Importantly, swelling study unveiled swelling effect wasn't the primary factor contributing to the increased PAAs migration in ethanol food simulant, as there was no significant disparity in swelling degrees across different food simulants. FT-IR and DSC analysis revealed higher PAAs content in 50 % ethanol were due to highly concentrated polar ethanol disrupting hydrogen bonds and van der Waal forces holding PLA molecules together. Overall, minimizing contact between PLA straws and alcoholic foods is crucial to avoid potential safety risks posed by PAAs.

Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens.

Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limited focus. Nevertheless, recent studies explored the predictive performance of MALDI-TOF MS for detecting AMR in clinical pathogens when machine learning techniques are applied. This chapter describes a routine MALDI-TOF MS workflow for the rapid screening of AMR in foodborne pathogens, with Campylobacter spp. as a study model.

Identifying Putative Biomarkers of Foodborne Pathogens Using a Metabolomic Approach.

Metabolomics is the study of low molecular weight biochemical molecules (typically <1500 Da) in a defined biological organism or system. In case of food systems, the term "food metabolomics" is often used. Food metabolomics has been widely explored and applied in various fields including food analysis, food intake, food traceability, and food safety. Food safety applications focusing on the identification of pathogen-specific biomarkers have been promising. This chapter describes a nontargeted metabolite profiling workflow using gas chromatography coupled with mass spectrometry (GC-MS) for characterizing three globally important foodborne pathogens, Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella enterica, from selective enrichment liquid culture media. The workflow involves a detailed description of food spiking experiments followed by procedures for the extraction of polar metabolites from media, the analysis of the extracts using GC-MS, and finally chemometric data analysis using univariate and multivariate statistical tools to identify potential pathogen-specific biomarkers.

Investigation of Protein Lysine Acetylation in Antiviral Innate Immunity.

Protein lysine acetylation involved in the antiviral innate immunity contributes to the regulation of antiviral inflammation responses, including type 1 interferon production and interferon-stimulated gene expression. Thus, investigation of acetylated antiviral proteins is vital for the complete understanding of inflammatory responses to viral infections. Immunoprecipitation (IP) assay with anti-targeted-protein antibody or with acetyl-lysine affinity beads followed by immunoblot provides a classical way to determine the potential modified protein in the antiviral innate pathways, whereas mass spectrometry can be utilized to identify the accurate acetylation lysine residues or explore the acetyl-proteomics. We demonstrate here comprehensive methods of protein lysine acetylation determination in virus-infected macrophages and embryonic fibroblast cells or proteins-overexpressed HEK 293 T cells in the context of antiviral innate immunity.

Development and Validation of a Proximity Labeling Fusion Protein Construct to Identify the Protein-Protein Interactions of Transcription Factors.

Dynamic interactions between transcription factors govern changes in gene expression that mediate changes in cell state accompanying injury response and regeneration. Transcription factors frequently function as obligate dimers whose activity is often modulated by post-translational modifications. These critical and often transient interactions are not easily detected by traditional methods to investigate protein-protein interactions. This chapter discusses the design and validation of a fusion protein involving a transcription factor tethered to a proximity labeling ligase, APEX2. In this technique, proteins are biotinylated within a small radius of the transcription factor of interest, regardless of time of interaction. Here we discuss the validations required to ensure proper functioning of the transcription factor proximity labeling tool and the sample preparation of biotinylated proteins for mass spectrometry analysis of putative protein interactors.

Direct analysis in real time mass spectrometry (DART-MS/MS) for rapid urine opioid detection in a clinical setting.

BACKGROUND AND AIMS: Current laboratory methods for opioid detection involve an initial screening with immunoassays which offers efficient but non-specific results and a subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) confirmation which offers accurate results but requires extensive sample preparation and turnaround time. Direct Analysis in Real Time (DART) tandem mass spectrometry is evaluated as an alternative approach for accurate opioid detection with efficient sample preparation and turnaround time. MATERIALS AND METHODS: DART-MS/MS was optimized by testing the method with varying temperatures, operation modes, extraction methods, hydrolysis times, and vortex times. The method was evaluated for 12 opioids by testing the analytical measurement range, percent carryover, precision studies, stability, and method-to-method comparison with LC-MS/MS. RESULTS: DART-MS/MS shows high sensitivity and specificity for the detection of 6-acetylmorphine, codeine, hydromorphone, oxymorphone, hydrocodone, naloxone, buprenorphine, norfentanyl, and fentanyl in urine samples. However, its performance was suboptimal for norbuprenorphine, morphine and oxycodone. CONCLUSION: In this proof-of-concept study, DART-MS/MS is evaluated for its rapid quantitative definitive testing of opioids drugs in urine. Further research is needed to expand its application to other areas of drug testing.

A dopant-assisted iodide-adduct chemical ionization time-of-flight mass spectrometer based on VUV lamp photoionization for atmospheric low-molecular-weight organic acids analysis.

Formic and acetic acids are the most abundant gaseous organic acids and play the key role in the atmospheric chemistry. In iodine-adduct chemical ionization mass spectrometry (CIMS), the low utilization efficiency of methyl iodide and humidity interference are two major issues of the vacuum ultraviolet (VUV) lamp initiated CIMS for on-line gaseous formic and acetic acids analysis. In this work, we present a new CIMS based on VUV lamp, and the ion-molecular reactor is separated into photoionization and chemical ionization zones by a reducer electrode. Acetone was added to the photoionization zone, and the VUV photoionization acetone provided low-energy electrons for methyl iodide to generate I-, and the addition of acetone reduced the amount of methyl iodide by 2/3. In the chemical ionization zone, a headspace vial containing ultrapure water was added for humidity calibration, and the vial changes the sensitivity as a function of humidity from ambiguity to well linear correlation (R2 > 0.95). With humidity calibration, the CIMS can quantitatively measure formic and acetic acids in the humidity range of 0%-88% RH. In this mode, limits of detection of 10 and 50 pptv are obtained for formic and acetic acids, respectively. And the relative standard deviation (RSD) of quantitation stability for 6 days were less than 10.5%. This CIMS was successfully used to determine the formic and acetic acids in the underground parking and ambient environment of the Shandong University campus (Qingdao, China). In addition, we developed a simple model based formic acid concentration to assess vehicular emissions.

Vacuum ammonia stripping from liquid digestate: Effects of pH, alkalinity, temperature, negative pressure and process optimization.

High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste. Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen, which has attracted a lot of attention in recent years. To investigate the parameter effects on the efficiency and mass transfer, five combination conditions (53 °C 15 kPa, 60 °C 20 kPa, 65 °C 25 kPa, 72 °C 35 kPa, and 81 °C 50 kPa) were conducted for ammonia stripping of sludge digestate. The results showed that 80% of ammonia nitrogen was stripped in 45 min for all experimental groups, but the ammonia transfer coefficient varied under different conditions, which increased with the rising of boiling point temperature, and reached the maximum value (39.0 mm/hr) at 81 °C 50 kPa. The ammonia nitrogen removal efficiency was more than 80% for 30 min vacuum stripping after adjusting the initial pH to above 9.5, and adjustment of the initial alkalinity also affects the pH value of liquid digestate. It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency, while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity. In terms of the mechanism of vacuum ammonia stripping, it underwent alkalinity destruction, pH enhancement, ammonia nitrogen dissociation, and free ammonia removal. In this study, two-stage experiments of alkalinity destruction and ammonia removal were also carried out, which showed that the two-stage configuration was beneficial for ammonia removal. It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.

Rapid and accurate detection of cinnamon oil adulteration in perilla leaf oil using atmospheric solids analysis probe-mass spectrometry.

Perilla leaf oil (PLO) is a global premium vegetable oil with abundant nutrients and substantial economic value, rendering it susceptible to potential adulteration by unscrupulous entrepreneurs. The addition of cinnamon oil (CO) is one of the main adulteration avenues for illegal PLOs. In this study, new and real-time ambient mass spectrometric methods were developed to detect CO adulteration in PLO. First, atmospheric solids analysis probe tandem mass spectrometry combined with principal component analysis and principal component analysis-linear discriminant analysis was employed to differentiate between authentic and adulterated PLO. Then, a spectral library was established for the instantaneous matching of cinnamaldehyde in the samples. Finally, the results were verified using the SRM mode of ASAP-MS/MS. Within 3 min, the three methods successfully identified CO adulteration in PLO at concentrations as low as 5% v/v with 100% accuracy. The proposed strategy was successfully applied to the fraud detection of CO in PLO.

Atriplex hortensis var. 'rubra' extracts and purified amaranthin-type pigments reduce oxidative stress and inflammatory response in LPS-stimulated RAW264.7 cells.

The use of direct injection ion mobility mass spectrometry (DI-IM-MS) to detect and identify betacyanin pigments in A. hortensis 'rubra' extracts was explored for the first time, with results compared to conventional LC-MS/MS analysis. The anti-inflammatory activities of leaf and seed extracts, alongside purified amaranthin and celosianin pigments, were investigated using a model of lipopolysaccharide (LPS)-activated murine macrophages. Extracts and purified pigments significantly inhibited the production of prostaglandin E2 and NO by up to 90% and 70%, respectively, and reduced the expression of Il6, Il1b, Nos2, and Cox2. Leaf and seed extracts also decreased secretion of Il6 and Il1b cytokines and reduced protein levels of Nos2 and Cox2. Furthermore, extracts and purified pigments demonstrated potent dose-dependent radical scavenging activity in a cellular antioxidant activity assay (CAA) without any cytotoxic effects. Our research highlights the promising biological potential of edible, climate-resilient A. hortensis 'rubra' as a valuable source of bioactive compounds.

Integration of MALDI-TOF MS and machine learning to classify enterococci: A comparative analysis of supervised learning algorithms for species prediction.

This research focused on distinguishing distinct matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) spectral signatures of three Enterococcus species. We evaluated and compared the predictive performance of four supervised machine learning algorithms, K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), to accurately classify Enterococcus species. This study involved a comprehensive dataset of 410 strains, generating 1640 individual spectra through on-plate and off-plate protein extraction methods. Although the commercial database correctly identified 76.9% of the strains, machine learning classifiers demonstrated superior performance (accuracy 0.991). In the RF model, top informative peaks played a significant role in the classification. Whole-genome sequencing showed that the most informative peaks are biomarkers connected to proteins, which are essential for understanding bacterial classification and evolution. The integration of MALDI-TOF MS and machine learning provides a rapid and accurate method for identifying Enterococcus species, improving healthcare and food safety.

Seasonal changes of chemodiversity along with microbial succession in a municipal wastewater treatment plant.

The relationship between chemodiversity and microbial succession in wastewater treatment plants (WWTPs) is highly intricate and bidirectional. The specific contribution of the microbial community to changes in the composition of dissolved organic matter (DOM) within different biological treatment units remains unclear, as does the reciprocal influence of DOM composition on microbial succession. In this study, spectroscopy ((Excitation-emission matrix) EEM-PARAFAC, Ultraviolet (UV)-spectrum, Fourier transform infrared spectrometer (FT-IR)), Liquid chromatograph mass spectrometer (LC‒MS) and Fourier transform ion cyclotron resonance (FT-ICR) MS along with high-throughput sequencing technology were used to explore the relationship between chemodiversity and microbial succession in WWTPs concerning seasonal changes. The results showed that WWTPs with anaerobic/anoxic/oxic (A2O) processes can metabolize and transform most of the wastewater DOM, and the anaerobic unit has the highest removal rate for fluorescence DOM (FDOM, 14.07%-64.43%); the anaerobic unit increased aliphatic/proteins and lignin-like molecules but decreased relative intensity, while the anoxic unit removed unsaturated hydrocarbons, aromatic structures, and lignin-like substances. The impact of seasonal changes on the composition and removal of FDOM and DOM in wastewater treatment is significant, and the variations that occur during different seasons affect microbial activity, as well as the production, degradation, and transformation of organic compounds throughout the wastewater treatment process. Network analysis shows that Parcubacteria_genera_incertae_sedis plays a crucial role in DOM chemodiversity, highlighting the crucial contribution of microbial communities to both the structure and operation of the entire DOM network. The results in this study could provide some theoretical and practical basis for guiding the process optimization of WWTPs.

Differential proteins from EVs identification based on tandem mass tags analysis and effect of Treg-derived EVs on T-lymphocytes in COPD patients.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a widespread respiratory disease. This study examines extracellular vesicles (EVs) and proteins contained in EVs in COPD. METHODS: Blood samples were collected from 40 COPD patients and 10 health controls. Cytokines including IFN-γ, TNF-α, IL-1ß, IL-6, IL-8, and IL-17, were measured by ELISA. Small EVs samples were extracted from plasma and identified by transmission electron microscope (TEM), nanoparticle tracking analysis (NTA), and Western blot. Protein components contained in EVs were analyzed by Tandem Mass Tags (TMT) to identify differential proteins. Treg-derived EV was extracted and added to isolated CD8+, Treg, and Th17 subsets to assess its effect on T-lymphocytes. RESULTS: ELISA revealed higher levels of all cytokines and flow cytometry suggested a higher proportion of Treg and Th17 cells in COPD patients. After identification, TMT analysis identified 207 unique protein components, including five potential COPD biomarkers: BTRC, TRIM28, CD209, NCOA3, and SSR3. Flow cytometry revealed that Treg-derived EVs inhibited differentiation into CD8+, CD4+, and Th17 cells. CONCLUSION: The study shows that cytokines, T-lymphocyte subsets differences in COPD and Treg-derived EVs influence T-lymphocyte differentiation. Identified biomarkers may assist in understanding COPD pathogenesis, prognosis, and therapy. The study contributes to COPD biomarker research.

Efficacy of the da Vinci robot versus thoracoscopic surgery for patients with mediastinal tumors of different body mass index: a multicenter propensity score-matched study.

BACKGROUND: The purpose of the present study was to evaluate the efficacy and safety of da Vinci robot-assisted thoracoscopic surgery (RATS) versus video-assisted thoracoscopic surgery (VATS) for the treatment of patients with mediastinal tumors of different body mass indices (BMI). METHODS: A retrospective cohort study was used to collect 260 patients with mediastinal tumors admitted to three medical centers in China from December 2020 to March 2024. These patients underwent mediastinal tumor resection by RATS (n = 125) or VATS (n = 135). Propensity score matching (PSM) analysis was performed for the both groups, and further, the patients were divided into the N-BMI group (18.5 kg/m2 ≤ BMI < 25 kg/m2) and the H-BMI group (BMI ≥ 25 kg/m2) based on their BMI to compare patients' surgery-related information. RESULTS: The RATS group had more advantages than the VATS group in terms of intraoperative blood loss, total postoperative drainage, postoperative drainage time, and postoperative hospital stay. As for hospitalization costs, the VATS group was more advantageous. In the H-BMI group, subgroup analysis showed a statistically significant difference in shorter operative time and lower incidence of postoperative complications in the RATS group. CONCLUSION: RATS has technical and short-term efficacy advantages in comparison with VATS, although it has the drawback of high costs associated with the treatment of mediastinal tumors. In the patients with mediastinal tumors of H-BMI, RATS can achieve better short-term outcomes and safety, especially in the reduction of the incidence of postoperative complications.

Cover crop root exudates impact soil microbiome functional trajectories in agricultural soils.

BACKGROUND: Cover cropping is an agricultural practice that uses secondary crops to support the growth of primary crops through various mechanisms including erosion control, weed suppression, nutrient management, and enhanced biodiversity. Cover crops may elicit some of these ecosystem services through chemical interactions with the soil microbiome via root exudation, or the release of plant metabolites from roots. Phytohormones are one metabolite type exuded by plants that activate the rhizosphere microbiome, yet managing this chemical interaction remains an untapped mechanism for optimizing plant-soil-microbiome interactions. Currently, there is limited understanding on the diversity of cover crop phytohormone root exudation patterns and our aim was to understand how phytochemical signals selectively enrich specific microbial taxa and functionalities in agricultural soils. RESULTS: Here, we link variability in cover crop root exudate composition to changes in soil microbiome functionality. Exudate chemical profiles from 4 cover crop species (Sorghum bicolor, Vicia villosa, Brassica napus, and Secale cereal) were used as the chemical inputs to decipher microbial responses. These distinct exudate profiles, along with a no exudate control, were amended to agricultural soil microcosms with microbial responses tracked over time using metabolomes and genome-resolved metatranscriptomes. Our findings illustrated microbial metabolic patterns were unique in response to cover crop exudate inputs over time, particularly by sorghum and cereal rye amended microcosms. In these microcosms, we identify novel microbial members (at the genera and family level) who produced IAA and GA4 over time. Additionally, we identified cover crop exudates exclusively enriched for bacterial nitrite oxidizers, while control microcosms were discriminated for nitrogen transport, mineralization, and assimilation, highlighting distinct changes in microbial nitrogen cycling in response to chemical inputs. CONCLUSIONS: We highlight that root exudate amendments alter microbial community function (i.e., N cycling) and microbial phytohormone metabolisms, particularly in response to root exudates isolated from cereal rye and sorghum plants. Additionally, we constructed a soil microbial genomic catalog of microorganisms responding to commonly used cover crops, a public resource for agriculturally relevant microbes. Many of our exudate-stimulated microorganisms are representatives from poorly characterized or novel taxa, revealing the yet to be discovered metabolic reservoir harbored in agricultural soils. Our findings emphasize the tractability of high-resolution multi-omics approaches to investigate processes relevant for agricultural soils, opening the possibility of targeting specific soil biogeochemical outcomes through biological precision agricultural practices that use cover crops and the microbiome as levers for enhanced crop production. Video Abstract.

The nonlinear connection between relative fat mass and non-alcoholic fatty liver disease in the Japanese population: an analysis based on data from a cross-sectional study.

BACKGROUND: Relative fat mass (RFM) is a newly developed, sex-specific anthropometric formula designed to estimate total body fat percentage. However, research investigating the correlation between RFM and the risk of non-alcoholic fatty liver disease (NAFLD) remains limited. This study evaluates the association between RFM and the risk of NAFLD within the Japanese population. METHODS: This study including 14,250 Japanese adults who underwent physical examinations at Murakami Memorial Hospital between 2004 and 2015. We employed binary logistic regression to elucidate the direct relationship between RFM levels and the incidence of NAFLD. Additionally, a generalized additive model (GAM) coupled with smooth curve fitting techniques was utilized to map the non-linear association. RESULTS: The cohort had an average age of 43.53 ± 8.89 years, with a male majority of 52.00%. NAFLD was identified in 17.59% of the participants. After adjusting for confounding factors, a significant positive correlation between RFM and NAFLD risk was observed (OR: 1.15, 95%CI: 1.10-1.21, P < 0.0001 for females; OR: 1.15, 95%CI: 1.10-1.19, P < 0.0001 for males). Additionally, a non-linear relationship between RFM and the incidence of NAFLD was detected in both genders. The RFM threshold was identified as 34.95 for women and 23.40 for men. RFM was positively associated with the risk of NAFLD when RFM was below the respective threshold (OR: 1.29, 95%CI: 1.19-1.40, P < 0.0001 for females; OR: 1.23, 95%CI: 1.17-1.29, P < 0.0001 for males), whereas no significant association was found when RFM was above the threshold (OR: 1.05, 95%CI: 0.98-1.12, P = 0.1829 for females; OR: 1.01, 95%CI: 0.95-1.08, P = 0.7392 for males). CONCLUSION: Our findings suggest a positive, nonlinear relationship between RFM and the risk of NAFLD, with a saturation effect. These results imply that maintaining RFM at a lower level may be advantageous in mitigating the risk of NAFLD.

Aggregatibacter aphrophilus-associated Sphenoid Sinusitis Causing Orbital Cellulitis, Meningitis, and Venous Sinus Thrombosis.

We herein report an 81-year-old woman with no significant medical history who developed a fever, headache, and right eyelid swelling. Magnetic resonance imaging (MRI) showed eye proptosis, sphenoid opacity, enlarged cavernous sinus, and dilated right superior ophthalmic vein (SOV). Subsequent enhanced MRI revealed intraventricular debris and thrombosis in the right SOV and the left transverse and sigmoid sinuses. Blood cultures were positive for Aggregatibacter aphrophilus, as identified by mass spectrometry. The patient responded well to antibiotics, anticoagulants, and surgical drainage of sphenoid sinusitis. To our knowledge, this is the first case of A. aphirophilus sphenoid sinusitis causing orbital cellulitis, meningitis, and venous sinus thrombosis.

Assessment of diagnostic value of ultrasound and multi-slice spiral computed tomography in acute appendicitis: a retrospective study.

PURPOSE: Ultrasound and multi-slice spiral computed tomography (CT) are frequently used to assist the diagnosis of acute appendicitis (AA), and the examination results may vary among different demographics. This study aimed to compare the diagnostic accuracy of ultrasound and CT for AA. METHODS: We performed a retrospective analysis of patients diagnosed with AA who underwent emergency surgery at our hospital from March 2021 to August 2023, with postoperative pathological results as the gold standard. Differences in the diagnostic accuracy of ultrasound and CT for different types of AA, age groups, and body mass index (BMI) values were then analyzed. RESULTS: The overall sample comprised 279 confirmed cases of AA, with 64 cases of simple appendicitis, 127 cases of suppurative appendicitis, and 88 cases of gangrenous appendicitis. For these three pathological classifications, the diagnostic accuracy of ultrasound was 68.75% (44/64), 73.22% (93/127), and 81.81% (72/88), respectively, while the diagnostic accuracy of CT was 71.87% (46/64), 82.67% (105/127), and 90.90% (80/88), respectively. There was no statistically significant difference in the overall diagnostic accuracy between the two methods (P > 0.05). Subgroup analysis showed no difference in diagnostic accuracy between the two methods for patients with normal BMI (P > 0.05). However, for overweight, obese, and elderly patients, CT provided significantly better diagnostic accuracy than ultrasound (P < 0.05). CONCLUSION: While ultrasound and CT have similar diagnostic accuracy for different pathological types of AA, CT is more accurate for overweight, obese, and elderly patients.

Higher Plasma Copper Exposure was Adversely Associated with Skeletal Muscle Indicators in Chinese Children Aged 6-9 Years: A Cross-Sectional Study.

It is unclear whether blood concentrations of copper (Cu), magnesium (Mg), and calcium (Ca) influence skeletal muscle mass and strength in children. We aimed to explore the associations between plasma Cu, Mg, and Ca and skeletal muscle indicators in Chinese children. A total of 452 children aged 6 to 9 years old were recruited for this cross-sectional study. Whole body lean soft tissue mass (WLSTM), trunk lean soft tissue mass (TLSTM), and appendicular skeletal muscle mass (ASMM) were measured using dual-energy X-ray absorptiometry. Parameters of these indicators divided by Height2 (Ht2) and Weight (Wt) at the corresponding sites were calculated. Handgrip strength was also measured. Parameters of skeletal muscle indicators and handgrip strength that were below the sex-specific 20th percentile were considered low levels. Plasma concentrations of Cu, Mg, and Ca were measured using ICP-MS. After adjusting for several potential covariates, among the total subjects, for every one standard deviation increase in Cu concentrations, there was a 0.939% decrease in WLSTM/Wt, a 0.415% decrease in TLSTM/Wt, and a 0.47% decrease in ASMM/Wt. For every one standard deviation increase in Cu concentrations, there was a higher odd (OR: 1.36, 95%CI 1.06, 1.75) of low WLSTM/Wt, TLSTM/Wt (OR: 1.33, 95%CI 1.03, 1.71), ASMM/Ht2 (OR: 1.32, 95%CI 1.02, 1.69), as well as ASMM/Wt (OR: 1.56, 95%CI 1.23, 1.99). No significant associations were found between Mg, Ca, and most skeletal muscle indicators. Higher plasma Cu concentrations were adversely associated with skeletal muscle indicators at multiple sites in Chinese children.

Does Perceived Nuisance Abundance of Water Plants Match with Willingness-to-Pay for Removal? Contrasts Among Different User Categories.

Dense beds of water plants can be perceived as nuisance, but this perception, however, may not be similar for different user categories, and this may affect their willingness-to-pay (WTP) for plant removal. A questionnaire survey was used to test this for residents and visitors and find underlying socio-cultural or economic drivers. We studied five cases where nuisance water plant growth is managed: the rivers Otra (Norway) and Spree (Germany), and the lakes Kemnade (Germany), Grand-Lieu (France), and Hartbeespoort Dam (South Africa). We used a different payment vehicle for residents (annual household tax) and visitors (tourist tax). The survey included questions on days spent on specific types of activity per year, the importance attached to different functions and activities, overall environmental attitude, perception of the plants, socio-demographic respondent characteristics and WTP for increased plant removal. We observed no increase in WTP for increased removal in most sites. The two most important drivers of variation in current WTP were income, and whether respondents were engaged in boating and angling and thus perceived the plants negatively. Variation in WTP among sites was considerable, and mainly related to the mixture of activities among respondents. Differences between residents and visitors were less important than those among sites. Our observations bear importance for water management: information on differences in experienced nuisance among user categories and the frequency of use by these categories is useful as guidance for the design and implementation of any plant removal plan.