Chemical Analysis Research Articles

Characterization of the Physicochemical and Energetic Properties of Alchornea cordifolia Leaves and Fruits Harvested in three Regions of Côte d'Ivoire

Aims: This study aims to enhance the nutritional value of the leaves and fruits of Alchornea cordifolia by characterizing the physicochemical compounds through their dosage. Study Design: To solve health problems, humans use different methods, including the use of spontaneous wild plants such as Alchornea cordifolia. Place and Duration of Study: This study was carried out at the Agro-valorization laboratory of the Jean Lorougnon Guédé University of Daloa between November 2023 and July 2024. Methodology: The plant material consisted of leaves and fruits of Alchornea cordifolia harvested from three regions. The characterization of the pH and lipid ash, pH, dry matter, carbohydrates, energy values contents was carried out by official analysis methods (Association of Official Analytical Chemists), proteins by the Kjeldahl method, lipids by the Soxhlet method, fibers by the Weende method, and total and reducing sugars were determined using the UV-VIS spectrophotometry method by spectrophotometric use. Results: the samples analysed contain the highest average content of proteins 15.11% for young leaves, 3.7% lipids, 3.9% pH, 58.69% carbohydrates and 261.63 kcal energy value. In terms of dried leaves, 6.02% ash, 91.80% dry matter and 37.83% fibre. Mature leaves record 6.66% total sugars and 3.2% reducing sugars. Conclusion: In conclusion, these leaves, whether young, dried, or mature, offer a variety of essential nutrients that can meet different nutritional needs, ranging from protein and energy intake to digestion and mineral intake.

Fast and green methodology based on miniaturised liquid–liquid extraction with a hydrophobic natural deep eutectic solvent of opium alkaloids from poppy seed beverages

Currently, the development of environmentally friendly analytical methodologies is a challenge for analytical chemistry. Therefore, the search for solvents to extract analytes of interest from complex matrices has progressed considerably in recent years. In the present work, 15 hydrophobic natural deep eutectic solvents (HNADES) consisting of a mixture of different donors and acceptors in different ratios have been prepared and compared to evaluate the most efficient extraction of opium alkaloids (OA) from fortified water samples. After selecting the most effective one consisting in a mixture of thymol and camphor in the ratio 1:1 ([Thy]:[Cam] 1:1), a rapid analytical methodology to determine OA in poppy seed beverages was optimised and validated for the first time. It was based on a miniaturised liquid–liquid extraction (m-LLE) with 0.5 mL of sample and 0.5 mL of HNADES by vortexing for 1 min, followed by 1 min centrifugation and subsequent analysis by high-performance liquid chromatography with diode array detector (HPLC-DAD). The validation was successful, showing extraction efficiencies between 91 and 107 % for all analytes, low limits of quantification (0.1 µg/mL for all analytes, except for morphine, 0.4 µg/mL) and precision values below 15 %. In addition, the greenness of the method was evaluated, obtaining a 0.79 on the AGREEprep metric scale. Therefore, it was demonstrated that the methodology developed to analyse OAs in poppy seed beverage was efficient, fast, simple and environmentally friendly.

“For the first time someone understood”: A study of noncoherence and heterogeneity in a Swedish autism support and advocacy association

Autism has come to be portrayed as something complex, ambiguous, and heterogeneous. I therefore contend that what is now needed are analytical tools to further explicate the modalities of this heterogeneity and ambiguity. I propose that one way forward is to draw on analytical vocabularies intended for analyses of the (non)coherence of phenomena, more specifically Law et al.’s concept modes of syncretism. I employ this concept to stage a theoretical intervention in the historiography of autism through a close reading of a booklet published by the Swedish Autism and Asperger Association to commemorate its founding 40 years earlier. The analysis shows that the booklet contained several discursive enactments of autism, and that different syncretic practices were used to handle and balance these. I also discuss how modes of syncretism can be useful as an analytical vocabulary for studying other contested and heterogeneous topics, diagnoses, and issues in psychology.

The use of drones for studying the behaviour of mammals

Since the advent and wide use of unmanned aerial vehicles (UAVs), they have been increasingly useful in monitoring the abundance, distribution and behaviour of terrestrial and aquatic animals. At present, this technique is actively applied to mammal research. The diversity and relative availability of drones allows for a variety of research tasks to be achieved. The use of UAVs has its advantages and disadvantages, these being discussed in the present review. The study examines the advantages of using UAVs in comparison to other methods, identifies new research opportunities opened up by drones, and emphasizes the advantages of modern analytical tools. The technical limitations of UAVs and the problem of the negative impact of this technique on mammals are discussed. The need to minimize the disturbance of animals during such research is emphasized. In addition, the work summarizes the experience of using UAVs in the studies on Russia’s theriofauna.

Self-DNA in Caenorhabditis elegans Affects the Production of Specific Metabolites: Evidence from LC-MS and Chemometric Studies

The worm Caenorhabditis elegans, with its short lifecycle and well-known genetic and metabolic pathways, stands as an exemplary model organism for biological research. Its simplicity and genetic tractability make it an ideal system for investigating the effects of different conditions on its metabolism. The chemical analysis of this nematode was performed to identify specific metabolites produced by the worms when fed with either self- or nonself-DNA. A standard diet with OP50 feeding was used as a control. Different development stages were sampled, and their chemical composition was assessed by liquid chromatography–mass spectrometry combined with chemometrics, including both principal component analysis and orthogonal partial least squares discriminant analysis tools. The obtained data demonstrated that self-DNA-treated larvae, when arrested in their cycle, showed significant decreases in dynorphin, an appetite regulator of the nematode, and in N-formyl glycine, a known longevity promoter in C. elegans. Moreover, a substantial decrease was also recorded in the self-DNA-fed adults for the FMRF amide neuropeptide, an embryogenesis regulator, and for a dopamine derivative modulating nematode locomotion. In conclusion, this study allowed for the identification of key metabolites affected by the self-DNA diet, providing interesting hints on the main molecular pathways involved in its biological inhibitory effects.

Evaluating the greenness, blueness, and whiteness of spectroscopic and UPLC techniques for the simultaneous measurement of anti-glaucoma drugs and the preservation agent

The pursuit of sustainable solutions is increasingly crucial in contemporary times. We propose inventive research that fulfills the criteria of whiteness and greenness in analytical chemistry. The endeavor aims to advance environmentally conscious techniques for the simultaneous detection of timolol maleate (TIM), dorzolamide HCl (DOR), and benzalkonium Cl (BNZ). The first method employed a sustainable mobile phase consisting of 0.02 M phosphate buffer: ethanol (68:32, v/v), and a flow rate of 0.6 mL/min with retention times 1.274, 1.798, and 2.483 min for DOR, TIM, and BNZ, respectively, with a UV detector at 210 nm. This methodology was easy, fast, and accurate. The approach showed low processing times, peak symmetry, and satisfactory resolution, with correlation values of 0.999. The linearity was between 0.001–0.064, 0.001–0.060 µg mL-1, and 0.001–0.050 µg mL-1for DOR, TIM, and BNZ, respectively. Furthermore, employing water as the solvent, complementary spectrophotometric methods such as Mean Centering of Ratio Spectra (MCR) and Successive Derivative Ratio Spectra (SRDS) were investigated as economical and environmentally friendly substitutes. All procedures demonstrated good linearity (r² > 0.9990), acceptable accuracy, and precision (RSD ≤ 2 %). Furthermore, by proving the superiority of the current work over previously published methods regarding sustainability, analytical performance, economics, and practicality, the real-world implementation of four greenness and whiteness algorithms boosts the approval and overall sustainable development of the proposed methods. The suggested techniques offer low-cost, environmentally friendly substitutes for traditional methods, advancing the field of analytical chemistry towards more sustainable practices and fostering a less destructive future for quality control.

Goondapyrones A-J: Polyketide α and γ Pyrone Anthelmintics from an Australian Soil-Derived Streptomyces sp.

An investigation of ×19 soil samples collected under the auspices of the Australian citizen science initiative, Soils for Science, returned ×559 chemically dereplicated microbial isolates, of which ×54 exhibited noteworthy anthelmintic activity against either the heartworm Dirofilaria immitis microfilaria and/or the gastrointestinal parasite Haemonchus contortus L1-L3 larvae. Chemical (GNPS and UPLC-DAD) and cultivation (MATRIX) profiling prompted a detailed chemical investigation of Streptomyces sp. S4S-00196A10, which yielded new anthelmintic polyketide goondapyrones A-J (1-10), together with the known actinopyrones A (11) and C (12). Structures for 1-12 were assigned on the basis of detailed spectroscopic and chemical analysis, with preliminary structure activity relationship analysis revealing selected γ-pyrones >50-fold and >13-fold more potent than isomeric α-pyrones against D. immitis mf motility (e.g., EC50 0.05 μM for 1; EC50 2.7 μM for 5) and H. contortus L1-L3 larvae development (e.g., EC50 0.58 μM for 1; EC50 8.2 μM for 5), respectively.

A First Step Towards Black Soldier Fly Larvae (Diptera: Stratiomyidae) Welfare by Considering Dietary Regimes (Part I).

The insect farming sector is expanding, but knowledge of insect welfare is still limited. This article aims to optimize the dietary regime for "black soldier fly" (Hermetia illucens L., BSF) larvae by applying a holistic view of welfare. Four diets were tested: control (CONTR, commercial laying hen feed), vegetable (VEG), omnivorous (OMN), and carnivorous (MEAT) diet, conducting experiments at a large (2000 larvae) and small scale (100 larvae). Rearing parameters were calculated including the growth rate, substrate reduction, efficiency of conversion of digested food, waste reduction index, and survival rate. Chemical analyses were conducted on BSF larvae and the residual frass. While the MEAT diet appears to be non-well-performing for the larvae, the VEG diet performed comparably to the control diet. Interestingly, the OMN diet demonstrated improved efficiency when evaluating the growth process at both scales. The chemical composition of larvae and frass highlighted the nutritional adequacy of the OMN diet, with the BSF larvae showing adequate protein and lipid content without nutrient catabolism or signs of discomfort. Applying the five freedoms of Brambell's report as a welfare standard for animal rearing and evaluating performance as an indirect indicator of welfare, the OMN diet appears to promote larval welfare in rearing practices.

Finite element modeling for analyzing the production of high-strength steel sheets for automobile parts

Abstract An investigation was conducted on developing components from high-strength steel sheet grade 590, with a thickness of 2.40 millimeters using finite element analysis, with a focus on predicting springback and deviation behavior. This study centered on the manufacturing process of a Member C inner workpiece. The research comprised a comprehensive examination of chemical composition, microstructural analysis, and mechanical property testing to establish suitable material models for the forming process. The purpose of this study was to evaluate the accuracy of three separate material models, namely the Barlat89 yield criteria, the Y-U model, and the Barlat89 yield criteria+Y-U model. A cyclic tension-compression tests was used to determine the parameters of the Barlat89 yield criteria+Y-U model, which were then confirmed using the 1-element model. The manufactured samples predicted bend angles and the results of the experimental measurements were very consistent. Barlat89 yield criteria, Y-U model, and Barlat89 yield criteria+Y-U kinematic hardening model were used to predict the strain distribution springback and deviation behavior within the produced components. The results indicated that all three material models produced similar results concerning strain distribution. The material model based on Barlat89 yield criteria+Y-U model was determined to have the least inaccuracy when all seven sections were averaged, with angle 1L equaling 93.66 degrees and angle 1R equaling 93.13 degrees, underscoring its superior performance in predicting springback. The deviation behavior from the three material model simulations was very comparable. Consequently, it can be concluded that the Barlat89 yield criteria+Y-U model represented the most precise and suitable choice for simulating the formation of the Member C inner component.

‘Rhythmite’, Ca29(SiO4)8Cl26, an Anthropogenic Phase from the Chelyabinsk Coal Basin (Ural, Russia) with a Complex Modular Structure Related to α-Ca3SiO4Cl2 (‘Albovite’): Crystal Structure, Raman Spectra, and Thermal Expansion

‘Rhythmite’, Ca29(SiO4)8Cl26, an anthropogenic calcium chloride silicate from the Chelyabinsk coal basin (South Ural, Russia), was investigated using chemical microprobe analysis, in situ single-crystal X-ray diffraction analysis (27–727 °C), and Raman spectroscopy. ‘Rhythmite’ is orthorhombic, Pnma: a = 17.0749(6), b = 15.1029(5), c = 13.2907(4) Å, and V = 3427.42(18) Å3 (R1 = 0.045). The crystal structure of ‘rhythmite’ consists of a porous framework formed by Ca-O bonds and SiO4 tetrahedra with additional Ca2+ cations and Cl− anions in the structure interstices. The framework is built up from multinuclear [Ca15(SiO4)4]14+ fundamental building blocks (FBBs) cut from the crystal structure of α-Ca3SiO4Cl2 (‘albovite’). The FBBs are linked by sharing common Ca atoms to form a network with an overall pcu topology. The empirical chemical formula was calculated as Ca29.02(Si7.89Al0.05P0.05)Ʃ7.99O32Cl26 (on the basis of Cl + O = 58). ‘Rhythmite’ is stable up to 627 °C and expands slightly anisotropically (αmax/αmin = 1.40) in the ab and bc planes and almost isotropically in the ac plane (α33/α11 = 1.02) with the following thermal expansion coefficients (×106 °C−1): α11 = 14.6(1), α22 = 20.5(4), α33 = 15.0(3), and αV = 50.1(6) (room temperature). During expansion, the silicate tetrahedra remain relatively rigid with average bond length changes of less than 0.5%. A structural complexity analysis indicates that ‘rhythmite’ is complex, with IG,total = 920.313 (bits/u.c.), which significantly exceeds the average value of structural complexity for silicates and is caused by the modular framework construction and the presence of a large number of independent positions in the crystal structure.

Chemical and Transcriptomic Analyses Provide New Insights into Key Genes for Ginsenoside Biosynthesis in the Rhizome of Panax japonicus C. A. Meyer.

Panax japonicus C. A. Meyer is renowned for its significant therapeutic effects and is commonly used worldwide. Its active ingredients, triterpenoid saponins, show variation in content among different tissues. The tissue-specific distribution of saponins is potentially related to the expression of vital genes in the biosynthesis pathway. In this study, the contents of five saponins (ginsenoside Ro, chikusetsusaponin IV, chikusetsusaponin IVa, ginsenoside Rg1, and ginsenoside Rb1) in three different tissues were determined by HPLC. Transcriptome sequencing analysis identified differentially expressed genes (DEGs) involved in triterpenoid saponin biosynthesis, highlighting significant correlations between saponin contents and the expression levels of 10 cytochrome p450 monooxygenase (CYP) and 3 UDP-glycosyltransferase (UGT) genes. Cloning, sequencing, and prokaryotic expression of UGT genes confirmed the molecular weights of UGT proteins. Gene sequence alignment and phylogenetic analysis provided preliminary insights into UGT gene functions. Meanwhile, the function of one UGT gene was characterized in the yeast. These findings advance our understanding of the triterpenoid saponin biosynthesis in P. japonicus and support future research in traditional Chinese medicine (TCM) and synthetic biology.

Contribution of multiway calibration to White Analytical Chemistry.

In this article, the compatibility between second- and third-order calibration and White Analytical Chemistry (WAC) is exposed and discussed. The WAC concept and the principles on which it is based are briefly presented. Multiway calibration methods, which consist of performing analyte(s) quantification by processing second- or higher-order instrumental data using chemometric models, are analyzed in light of their contribution to the whiteness of an analytical method. Special emphasis is directed towards the chemometric property called "second-order advantage," which offers the possibility of modeling sample interferences without either needing to remove them nor knowing their identity. With the purpose of illustrating to the analytical community the valuable contribution of multiway calibration to the development of white methodologies, some examples selected from our laboratory are here presented.

Antimicrobial, anticancer and photocatalytic dye degradation activities of silver nanoparticles phytosynthesized from Secamone emetica aqueous leaf extract

Secamone emetica (Family: Apocynaceae) is traditionally used for several ailments among indigenous people due to the bioactive components present in it. Nanomedicine has undergone impressive modifications and the development of new drugs with significant healthcare outcomes. The purpose of the present study was to green synthesize and characterize silver nanoparticles (Ag-NPs) using aqueous leaf extract of S. emetica, and to study their in vitro antimicrobial, anticancer and photocatalytic dye degradation activities. Various spectroscopic and microscopic analytical tools were used to characterize the Ag-NPs. Selective G+ve, G−ve bacteria and fungal species were used to test the Ag-NPs antibacterial and antifungal activity. Anticancer efficacy of the Ag-NPs was appraised by MTT test using MDA-MB 231 human breast cancer cells. Degradation of Rhodamine B dye by the Ag-NPs under visible light was assessed. The characterization studies confirmed the formation of Ag-NPs which were crystalline cubical symmetry with an average size of 26.69 nm. Dose dependent antimicrobial activity displayed a maximum zone of inhibition of 22.39 mm against E. coli followed by 21.28 mm against S. aureus at 100 µL/mL concentration of Ag-NPs. The IC50 value of synthesized Ag-NPs on MDA-MB 231 cell lines was 0.5 μg/mL. The Ag-NPs catalyst degraded 96 % of Rhodamine B dye in 150 min under visible light. Phytosynthesized Ag-NPs showed strong antimicrobial and anticancer properties and also revealed excellent dye degradation capacity. It is possible to further utilize the biosynthesized Ag-NPs as a possible source of antimicrobial, anticancer, and dye-degradation activities.

Flags, sports, and the common good: the nationalism that advances the gambling industry

This study investigates how nationalist sentiments enable the gambling industry to capitalize on national markets. With the help of qualitative content analytical tools, we analyzed 500 curated social media posts targeting Finnish and Swedish audiences. The study compared narrative templates, identifying speaker positions (inside/outside sociocultural context) and types of nationalist connotations (surface-level/in-depth). The results are displayed in a four-field matrix that reveals that Finland’s state gambling monopoly, Veikkaus, leverages ‘cultural nationalism’ to highlight its social role, portraying itself as a supporter of Finnish values, sports, and civil society. In contrast, international gambling companies and former domestic monopolies in Sweden’s license-based regulatory system use more mechanical, ‘sports-nationalist’ symbols, though the former monopoly companies occasionally refer to traditional Swedish cultural identity symbols. Compared to Veikkaus, the Swedish operators approach the national market as commercial outsiders, seeking public trust through sports associations. The study sheds light on how regulatory systems shape digital capitalist strategies for targeting national consumers on the social media.

Leveraging Machine Learning for Sophisticated Rental Value Predictions: A Case Study from Munich, Germany

There has been very limited research conducted to predict rental prices in the German real estate market using an AI-based approach. From a general perspective, conventional approaches struggle to handle large amounts of data and fail to consider the numerous elements that affect rental prices. The absence of sophisticated, data-driven analytical tools further complicates this situation, impeding stakeholders, such as tenants, landlords, real estate agents, and the government, from obtaining the accurate insights necessary for making well-informed decisions in this area. This paper applies novel machine learning (ML) approaches, including ensemble techniques, neural networks, linear regression (LR), and tree-based algorithms, specifically designed for forecasting rental prices in Munich. To ensure accuracy and reliability, the performance of these models is evaluated using the R2 score and root mean squared error (RMSE). The study provides two feature sets for model comparison, selected by particle swarm optimisation (PSO) and CatBoost. These two feature selection methods identify significant variables based on different mechanisms, such as seeking the optimal solution with an objective function and converting categorical features into target statistics (TSs) to address high-dimensional issues. These methods are ideal for this German dataset, which contains 49 features. Testing the performance of 10 ML algorithms on two sets helps validate the robustness and efficacy of the AI-based approach utilising the PyTorch framework. The findings illustrate that ML models combined with PyTorch-based neural networks (PNNs) demonstrate high accuracy compared to standalone ML models, regardless of feature changes. The improved performance indicates that utilising the PyTorch framework for predictive tasks is advantageous, as evidenced by a statistical significance test in terms of both R2 and RMSE (p-values < 0.001). The integration results display outstanding accuracy, averaging 90% across both feature sets. Particularly, the XGB model, which exhibited the lowest performance among all models in both sets, significantly improved from 0.8903 to 0.9097 in set 1 and from 0.8717 to 0.9022 in set 2 after being combined with the PNN. These results showcase the efficacy of using the PyTorch framework, enhancing the precision and reliability of the ML models in predicting the dynamic real estate market. Given that this study applies two feature sets and demonstrates consistent performance across sets with varying characteristics, the methodology may be applied to other locations. By offering accurate projections, it aids investors, renters, property managers, and regulators in facilitating better decision-making in the real estate sector.

Introduction to Nuclear Forensics Analysis Techniques

Abstract Nuclear forensics is the interdisciplinary branch of forensic science that deals with the analysis and examination of nuclear or other radioactive materials, or of evidence that is contaminated with radionuclides in the context of legal proceedings under international or national law related to nuclear security. To control and avoid the threat of terrorism posed by illicit trafficking and mismanagement, nuclear and other radioactive materials must be strictly regulated. Thus, the goal of nuclear forensic analysis is to discover what radioactive materials were confiscated, how, when, and where they were manufactured, and what their intended applications were. Nuclear forensic scientist has a wide array of analytical tools to use for detecting signatures in radioactive materials. These individual techniques can be sorted into three broad categories: bulk analysis tools, imaging tools, and microanalysis tools. Particular interest in nuclear forensics is particle morphology, isotopic composition of a material, presence of impurities, and microstructure. These properties can vary between materials of different origins due to varying processing or geological conditions, thus, allowing for discrimination of material history and prediction of provenance. This review article presents many key analytical techniques and discusses the main application and challenges of the most common techniques currently used in nuclear forensics analysis.

Unveiling the dynamic evolution of innovation networks in emerging economies: A complex network approach

AbstractThe innovation network of enterprises in emerging economies is a complex system, comprising numerous interconnected elements. In the context of a dynamic and volatile market, innovation entities evolve the evolution of the local world through collaborative innovation and interactions. To accurately replicate the actual dynamics of the enterprise innovation network, an in‐depth analysis is essential to delineate the growth and reduction mechanisms of diverse nodal entities. This research, based on the classical complex network paradigm, proposes a model that is based on preferential attachment and pruning mechanisms. This model reflects the evolutionary trajectory of enterprise innovation networks and was subjected to simulation analysis using MATLAB. The findings prove that simulation is an effective analytical tool for understanding the evolutionary mechanisms of innovation networks within emerging economies. The model clearly demonstrates the complex evolution of enterprise innovation networks, providing both theoretical foundations and practical guidance for strategic resource allocation and network governance within corporate environments.

Ecohydrological role of groundwater outflows in the functioning of the ecotone zone in Lake Jaczno, Poland

The research determined the influence of natural groundwater outflows from the spring peat bog on the water supply and its quality in Lake Jaczno. Lake Jaczno is located in the Suwalski Landscape Park (SLP) in the Podlaskie Voivodeship, north-east Poland. The research was conducted from April 2009 to October 2010 and from September 2022 to September 2023. Water samples were collected from spring areas, shallow groundwater, and from Lake Jaczno. Fieldwork involved measuring flow, temperature, water electrolytic conductivity (EC), dissolved oxygen (DO) concentration, water oxygen saturation (WS), and water reaction (pH). Chemical analyses of water samples were carried out in the laboratory. Findings indicate that groundwater, spring water, and lake water in the SLP maintain high quality, with no significant changes in chemical composition over the past decades. Additionally, the physical water parameters display low temporal variability. The EC in the tested waters oscillates around 500 μS∙cm–1. Both spring and lake waters are well oxygenated (97–100%). Biogenic element concentrations exhibit higher variability, influenced by flora development in areas with natural groundwater outflows. High oxygenation of water contributes to increased concentrations of nitrates. The analysed waters exhibited similarity in the concentration and structure of phosphorus forms. Additionally, sediment chemical parameters at Lake Jaczno suggests a buffering capacity in the transitional zones between water and land. Despite similarities in chemical composition, sediment granulometry suggests low permeability, potentially restricting exchange between groundwater and surface waters. Monitoring springs in these environments is important due to their impact on quantity and quality of water in the analysed areas.

Spatiotemporal Variation Characteristics and Source Identification of Nitrogen in the Baiyangdian Lake Water, China

To study the characteristics and sources of nitrogen in the Baiyangdian Lake, this research conducted water quality monitoring during three hydrological periods (normal period, flood period, and dry period), and 165 pieces of routine water quality monitoring data were collected from the three national control sections for Baiyangdian Lake and its inflow rivers. By integrating water chemical analysis with multivariate statistical techniques, the study comprehensively investigated the spatiotemporal variation patterns of nitrogen in Baiyangdian Lake and identified the sources of nitrogen pollution. The results showed that the concentration of total nitrogen (TN) was highest during the dry period, reaching an average of 0.924 mg/L, and 31.3% of the sites exceeded the national Grade III surface water quality standard, reflecting a potential risk of nitrogen pollution. Based on the ion ratio method and principal component analysis (PCA), the main sources of nitrogen pollution in Baiyangdian Lake were identified as manure and domestic sewage, with agricultural fertilizers also having a certain impact on water nitrogen pollution. In addition, the study also compared the nitrogen concentration in Baiyangdian Lake with several important lakes in China. The results showed that the concentrations of TN and ammonium nitrogen (NH4+-N) in Baiyangdian Lake are lower than those in lakes in areas with similar human activity intensity, indicating that the water quality of Baiyangdian is relatively good. This study can provide a scientific basis for water quality management and pollution prevention for Baiyangdian Lake.

Neurotoxic mixture effects of chemicals extracted from blood of pregnant women.

Human biomonitoring studies typically capture only a small and unknown fraction of the entire chemical universe. We combined chemical analysis with a high-throughput in vitro assay for neurotoxicity to capture complex mixtures of organic chemicals in blood. Plasma samples of 624 pregnant women from the German LiNA cohort were extracted with a nonselective extraction method for organic chemicals. 294 of >1000 target analytes were detected and quantified. Many of the detected chemicals as well as the whole extracts interfered with neurite development. Experimental testing of simulated complex mixtures of detected chemicals in the neurotoxicity assay confirmed additive mixture effects at concentrations less than individual chemicals' effect thresholds. The use of high-throughput target screening combined with bioassays has the potential to improve human biomonitoring and provide a new approach to including mixture effects in epidemiological studies.