Large Concentration Differences Research Articles

Significant influence of urban human activities and marine input on rainwater chemistry in a coastal large city, China

The coastal urban region is generally considered an atmospheric receptor for terrestrial and marine input materials, and rainfall chemistry can trace the wet scavenging process of these materials. Fast urbanization in China's east coastal areas has greatly altered the rainwater chemistry. However, the chemical variations, determinants, and sources of rainfall are unclear. Therefore, the typical coastal city of Fuzhou was selected for 1-year rainwater sampling and inorganic ions were detected to explore above problems. The findings depicted that rainwater ions in Fuzhou were slightly different from those in other coastal cities. Although NO3−, SO42−, Ca2+ and NH4+ dominated the rainwater ions, the marine input Cl− (22 %) and Na+ (11 %) also contributed a considerable percentage to the rainwater ions. Large differences in ion concentrations (2∼28 times) were found in monthly scale due to the rainfall amount. Both natural and anthropogenic determinants influenced the rainwater ions in coastal cities, such as SO2 emission, air SO2 and PM10 content on rainwater SO42−, NO3−, and Ca2+, and soot & dust emission on rainwater SO42−, NO3−, indicating the vital contribution of human activities. Stoichiometry and positive matrix factorization-based sources identification indicated that atmospheric dust/particles were the primary contributor of Ca2+ (83.3 %) and F− (83.7 %), and considerable contributor of SO42− (39.5 %), NO3− (38.3 %) and K+ (41.5 %). Anthropogenic origins, such as urban waste volatilization and fuel combustion emission, contributed 95 % of NH4+, 54.5 % of NO3− and 41.9 % of SO42−, and the traffic sources contribution was relatively higher than fixed emission sources. The marine input represented the vital source of Cl− (77.7 %), Na+ (84.9 %), and Mg2+ (55.3 %). This work highlights the significant influence of urban human activities and marine input on rainwater chemicals and provides new insight into the material cycle between the atmosphere and earth-surface in coastal city.

Simultaneous mass spectrometric quantification of trace amines, their precursors and metabolites

ObjectivesTrace amines are powerful neuromodulators influencing the release and reuptake of catecholamines. These low concentrated endogenous amines impact mood, cognition, and hormone regulation. Dysregulation of trace amines have been associated with a variety of diseases, such as schizophrenia, Parkinson’s disease, migraine, depression and more. Succesfull simultaneous quantification of trace amines, their precursors and metabolites would benefit both research and patient care. Since these compounds have various functional groups and are present in biological matrices with large concentration difference, their simultaneous quantification is an analytical challenge. Our goal was to develop a highly sensitive LC-MS/MS assay to simultaneously quantify trace amines, their precursors and metabolites in plasma. MethodsOur method is based on a simple two-step in-matrix derivatization protocol: propionic anhydride (PA) and 3-Ethyl-1-[3-(dimethylamino)propyl]carbodiimide (EDC) in combination with 2,2,2-trifluoroethylamine (TFEA) followed by online solid phase extraction combined with LC-MS/MS. Fifteen metabolites can be measured simultaneously, three precursors, eight trace amines and four metabolites. Validation of this method was performed according to international validation guidelines. The pre-analytical stability of trace amines was assessed. ResultsThis novel method was successful in quantifying trace amines, their precursors, and metabolites in plasma. Using just 50 µl human plasma, we were able to accomplish limit of quantification for 2-phenylethylamine and N-methyl-phenylethylamine of 0.2 nmol/L and 0.1 nmol/L for tyramine and n-methyltyramine. Inter-and intra-assay imprecision was < 15 % for all analytes. Stability assessment showed susceptibility of certain trace amines e.g. 2-phenylethylamine and N-methyl-phenylethylamine to enzymatic degradation in plasma. The addition of the monoamine oxidase inhibitor pargyline to plasma prevented this enzymatic degradation. ConclusionsWe developed a novel LC-MS/MS method that1) uses a new double derivatization technique, 2) is automated with online SPE, 3) uses far less sample volume then previous methods and 4) detects more components in the same sample (eight trace amines, three precursors, and four metabolites) with high specificity and selectivity. Furthermore, addition of MAO A/B inhibitor prevents degradation and guarantees more accurate quantification of trace amines.

A GC×GC-MS method based on solid-state modulator for non-targeted metabolomics: Comparison with traditional GC-MS method

The formidable challenge posed by the presence of extremely high amounts of compounds and large differences in concentrations in plasma significantly complicates non-targeted metabolomics analyses. In this study, a comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC×GC-qMS) method with a solid-state modulator (SSM) for non-targeted metabolomics in beagle plasma was first established based on a GC-MS method, and the qualitative and quantitative performance of the two platforms were compared. Identification of detected compounds was accomplished utilizing NIST database match scores, retention indices (RIs) and standards. Semi-quantification involved the calculation of peak area ratios to internal standards. Metabolite identification sheets were generated for plasma samples on both analytical platforms, featuring 22 representative metabolites chosen for validating qualitative accuracy, and for conducting comparisons of linearity, accuracy, precision, and sensitivity. The outcomes revealed a threefold increase in the number of identifiable metabolites on the GC×GC-MS platform, with lower limits of quantitation (LLOQs) reduced to 0.5–0.05 times those achieved on the GC-MS platform. Accuracy in quantification for both GC×GC-MS and GC-MS fell within the range of 85–115%, and the vast majority of intra- and inter-day precisions were within the range of 20%. These findings underscore that relative to the conventional GC-MS method, the GC×GC-MS method developed in this study, combined with SSM, exhibits enhanced qualitative capabilities, heightened sensitivity, and comparable accuracy and precision, rendering it more suitable for non-targeted metabolomics analyses.

Three-dimensional double-diffusive convection of conducting fluid under a magnetic field

The work aims to study the convection and diffusion of metallic fluid and the tritium in a cavity under the external magnetic field. The solver based on the finite volume method and the consistent and conservative scheme is developed to solve the Navier–Stokes equation considering the Lorentz force, concentration, and thermal buoyancy. The coupling effects of the magnetic field, the internal volumetric heat source, and the concentration difference between the left and right walls of the cavity are investigated. It is found that both the rotation direction and strength of the main circulation flow are controlled by the concentration buoyancy and the thermal buoyancy only regulates the global flow in the cavity. A larger concentration difference or a stronger internal heat source can lead to unstable flow. However, the stronger magnetic field suppresses the main circulation flow and small secondary vortices. The power law scaling of the Sherwood number vs the ratio of the Rayleigh number of the concentration to the Hartman number based on the force balance agrees with the numerical simulation. Four types of flow modes (large-amplitude low-frequency, large-amplitude high-frequency, small-amplitude low-frequency, and stable modes) are observed under the coupled multi-physics fields of the magnetic field, concentration difference, and heat source. The correlation function describing the influence of magnetic field and concentration strength on mass transfer is concluded.

Rapid identification of the compounds of Bushen Huoxue Prescription based on offline two-dimensional liquid chromatography with high-resolution mass spectrometry and molecular network technology.

The comprehensive and efficient characterization of components in traditional Chinese medicine is crucial for elucidating its active constituents and uncovering its mechanism. Identifying the compounds of the Bushen Huoxue Prescription (BHP) is difficult because of its complex composition and the large difference in concentration among its compounds. In this study, a hydrophilic interaction liquid chromatography coupled with reversed-phase LC (HILIC × RPLC) offline 2D-LC tandem high-resolution mass spectrometry method was established to analyze the total compounds of the BHP. Database screening and molecular networking were performed to identify the compounds. In contrast to conventional 1D chromatography, 2D chromatography increased peak capacity, enriched trace ingredients, and prevented the masking of high-abundance compounds. A total of 165 compounds were identified, and 14 potential compounds needed to be further identified. This study provided an effective method for comprehensively analyzing the complex system of traditional Chinese medicine compounds.

TKI Dose Optimization Based on Therapeutic Drug Monitoring（TDM) with Encouraging Outcomes and Well-Tolerated for Chronic Myeloid Leukaemia Patients

Background Imatinib, nilotinib, and dasatinib are tyrosine kinase inhibitors (TKIs) that have become first-line treatments for Philadelphia chromosome-positive chronic myeloid leukemia (CML). Series studies indicated TKIs had a high therapeutic index, which led to the registration of these medications at fixed doses. Therapeutic drug monitoring (TDM) is a strategy for dosage optimization to provide individual treatment through dose adjustment to improve efficacy or avoid TKI-related adverse events (AEs). Objective We prospectively analyzed the outcome based on trough plasma concentrations (Cmin) to manage TKI dosage optimization during imatinib, nilotinib, and dasatinib therapy in patients with CML by 12 months. The primary efficacy endpoint was the rate of MMR at 12 months, the secondary endpoints included the cumulative rate of significant AEs defined as grade 3/4 fluid retention, all grade pleural effusion and pulmonary hypertension, grade 3/4 bilirubin increased, and grade 3/4 hematological toxicity related to TKIs within the first 12 months of therapy. Methods We examined 204 CML patients treated with imatinib, nilotinib, or dasatinib in the first line for CML-CP. We used high-performance liquid chromatography-tandem mass spectrometry (UPLC/MS-MS) to detect the Cmin of TKIs. Dasatinib or imatinib Cmin (24±3h post-dose) and nilotinib Cmin (12±3 h post-dose) were assessed after 7~10 days of therapy. We set the Cmin of imatinib at 1000~1500 ng/mL and that of nilotinib at 600~800 ng/mL, dasatinib at 1~3 ng/ml, respectively. Results Imatinib group (n = 67), Nilotinib group (n = 72), and Dasatinib group (n = 65), respectively. The initial dose of imatinib was 400mg qd, based on Cmin of imatinib was 900~1100ng/mL, there were 17 patients with dose reduction(1 case with 100mg qd, 5 cases with 200mg qd, 11 cases with 300mg qd) and 2 patients increased dose to 500mg qd; The initial dose of nilotinib was 300mg bid, based on Cmin of imatinib was 600~800ng/mL, there were 21 patients with dose reduction( 4 cases with 150mg bid, 16 cases with 450mg daily, 1 cases with 150mg qd) and 1 patients increased to 400mg bid; the initial dose of dasatinib was 100mg qd, based on Cmin of dasatinib was1~3 ng/ml, there were 32 patients with dose reduction(1 case with 20mg qd, 4 cases with 40mg qd, 20 cases with 50mg qd, 7 cases with 70mg qd ). Among the patients treated with imatinib, dasatinib, and nilotinib, no statistically significant associations were observed between gender, age, ELT scores, and plasma trough concentration (p&amp;gt;0.05). Early molecular reaction (EMR BCR: ABL(IS) &amp;lt;10%) was achieved by 83.6% (95% confidence interval [CI], 74.6%-92.5%) in the imatinib group, 87.7% (95% CI, 80.0%-95.4%) in the nilotinib group, and 83.3% (95% CI, 75.0%-91.7%) in the dasatinib group of patients at 3 months. The incidence of MMR at 12 months was 82.1% (95% CI, 73.1%-93.0%) in the imatinib group, 73.8% (95% CI, 64.6%-84.6%) in the nilotinib group, and 75.0% (95% CI, 65.3%-84.7%) in the dasatinib group, respectively. The cumulative incidence of grade 3/4 hematological toxicity was 7.8% (16/204), all-grade pleural effusion was 23.1% (15/65) in the dasatinib group, grade 3/4 bilirubin increased was 6.9% (5/72) in the nilotinib group, and there were no patients with pulmonary hypertension. Conclusion There are large individual differences in plasma trough concentrations in CML patients taking TKIs, the TKI dosage should be adjusted based on target plasma concentrations to maximize efficacy and minimize the incidence of adverse events.

Effect of Single and Double Moment Microphysics Schemes and Change in Cloud Condensation Nuclei, Latent Heating Rate Structure Associated with Severe Convective System over Korean Peninsula

To investigate the impact of advanced microphysics schemes using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted using Weather Research and Forecasting (WRF) model for a severe mesoscale convective system (MCS) formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation linked with the convective system are improved in the WDM6 simulation. During the developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with the mixing ratio of hydrometeors (cloud, rain, graupel, snow, and ice), the number concentration of cloud and rainwater are also predictable in WDM6. To understand the differences in the vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with the Nr readily available in WDM6. Varied vertical distribution and large differences in rain number concentration and rain particle mass is evident between the schemes. Inclusion of the number concentration of rain and cloud, CCN, along with the mixing ratio of different hydrometers has improved the storm morphology in WDM6. Furthermore, the latent heating (LH) profiles of six major phase transformation processes (condensation, evaporation, freezing, melting, deposition, and sublimation) are also computed from microphysical production terms to deeply study the storm vertical structure. The main differences in condensation and evaporation terms are evident between the simulations due to the varied treatment of warm rain processes and the inclusion of CCN activation in WDM6. To investigate cloud–aerosol interactions, numerical simulation is conducted by increasing the CCN (aerosol) concentration in WDM6, which simulated comparatively improved pattern correlation for rainfall simulation along with intense hydrometer distribution. It can be inferred that the change in aerosol increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution, and subsequent rainfall. Relatively, the WDM6 simulated latent heating profile distribution is more consistent with the ERA5 computed moisture source and sink terms due to the improved formulation of warm rain processes.

Comparison of adsorption-extraction (AE) workflows for improved measurements of viral and bacterial nucleic acid in untreated wastewater

The lack of standardized methods and large differences in virus concentration and extraction workflows have hampered Severe Acute Respiratory Syndrome (SARS-CoV-2) wastewater surveillance and data reporting practices. Numerous studies have shown that adsorption-extraction (AE) method holds promise, yet several uncertainties remain regarding the optimal AE workflow. Several procedural components may influence the recovered concentrations of target nucleic acid, including membrane types, homogenization instruments, speed and duration, and lysis buffer. In this study, 42 different AE workflows that varied these components were compared to determine the optimal workflow by quantifying endogenous SARS-CoV-2, human adenovirus 40/41 (HAdV 40/41), and a bacterial marker gene of fecal contamination (Bacteroides HF183). Our findings suggest that the workflow chosen had a significant impact on SARS-CoV-2 concentrations, whereas it had minimal impact on HF183 and no effect on HAdV 40/41 concentrations. When comparing individual components in a workflow, such as membrane type (MF-Millipore™ 0.45 μm MCE vs. Isopore™ 0.40 μm), we found that they had no impact on SARS-CoV-2, HAdV 40/41, and HF183 concentrations. This suggests that at least some consumables and equipment are interchangeable. Buffer PM1 + TRIzol-based workflows yielded higher concentrations of SARS-CoV-2 than other workflows. HF183 concentrations were higher in workflows without chloroform. Similarly, higher homogenization speeds (5000–10,000 rpm) led to increased concentrations of SARS-CoV-2 and HF183 but had no effect on HAdV 40/41. Our findings indicate that minor enhancements to the AE workflow can improve the recovery of viruses and bacteria from the wastewater, leading to improved outcomes from wastewater surveillance efforts.

Revealing the missing puzzle piece of concentration in regulating Zn electrodeposition.

Despite achievements in suppressing dendrites and regulating Zn crystal growth, secondary aqueous Zn batteries are still rare in the market. Existing strategies mainly focus on electrode modification and electrolyte optimization, while the essential role of ion concentration in liquid-to-solid electrodeposition is neglected for a long time. Herein, the mechanism of concentration regulation in Zn electrodeposition is investigated in depth by combining electrochemical tests, post hoc characterization, and multiscale simulations. First, initial Zn electrodeposition is thermodynamically controlled epitaxial growth, whereas with the rapid depletion of ions, the concentration overpotential transcends the thermodynamic influence to kinetic control. Then, the evolution of the morphology from 2D sheets to 1D whiskers due to the concentration change is insightfully revealed by the morphological characterization and phase-field modeling. Furthermore, the depth of discharge (DOD) results in large concentration differences at the electrode-electrolyte interface, with a mild concentration distribution at lower DOD generating (002) crystal plane 2D sheets and a heavily varied concentration distribution at higher DOD yielding arbitrarily oriented 3D blocks. As a proof of concept, relaxation is introduced into two systems to homogenize the concentration distribution, revalidating the essential role of concentration in regulating electrodeposition, and two vital factors affecting the relaxation time, i.e., current density and electrode distance, are deeply investigated, demonstrating that the relaxation time is positively related to both and is more sensitive to the electrode distance. This work contributes to reacquainting aqueous batteries undergoing phase transitions and reveals a missing piece of the puzzle in regulating Zn electrodeposition.

Comparison of Gold Nanoparticles Prepared Using Monobasic Sodium Citrate or Sodium Borohydride for Neomycin Determination in Saliva after Solid-Phase Extraction (SPE) on a Molecularly Imprinted Polymer (MIP)

Two distinct spherical gold nanoparticles (AuNPs) were compared for the spectrophotometric determination of neomycin in saliva. The AuNPs were produced using AuCl3 and monobasic sodium citrate (in water bath at 100 °C) under magnetic stirring (AuNPs-citrate) and using HAuCl4 and NaBH4, at room-temperature under mechanical agitation in a commercial reactor (AuNPs-H). Both AuNPs were spherical with diameters of 7.7 nm (AuNPs-H) and 26.1 nm (AuNPs-citrate) and the maximum wavelength of the localized surface plasmon resonance (LSPR) bands were at 511 nm (AuNPs-H) and 529 nm (AuNPs-citrate). Equivalent spectral extinctions were found despite the fact the large difference in concentrations of AuNPs in dispersions: 4.2 × 10−9 mol L−1 for the AuNPs-H and 8.7 × 10−11 mol L−1 for the AuNPs-citrate. Both AuNPs interacted with aminoglycosides (AMG), affecting intensity of the LSPR band as the concentration of AMG increased. The response of the AuNPs-H was more sensitive toward AMG covering the following ranges: 0.6–600 µg L−1 (gentamicin), 7.3–550 µg L−1 (neomycin) and 14–520 µg L−1 (kanamycin). AuNPs-H optical response was more robust in function of the pH with AuNPs-citrate response only observed in acid solution, favoring electrostatic interaction with AMG. Catalytic activity of AuNPs-H, in reducing the 4-phenolate ion, presented a higher rate constant (4.3 × 10−3 s−1) and was used as analytical probe to determine neomycin in saliva after solid phase extraction with a commercially available AMG imprinted polymer enabling quantification to 0.36 μg of the analyte.

A countercurrent chromatography solvent system based on deep eutectic solvents for separation of cis- and trans-crocetin from Gardenia jasminoides Ellis.

Due to the structural similarity and large difference in concentration, the separation of trans- and cis-crocetin has been challenging, and the cis-crocetin is usually neglected. In this work, a countercurrent chromatography method was developed for the quick separation of trans-crocetin and cis-crocetin from the hydrolytic extract of Gardenia jasminoides Ellis. High purity of trans-crocetin (>95%) and cis-crocetin (>91%) were prepared simultaneously for the first time through a novel biphasic system based on deep eutectic solvents, n-heptane/n-butyl alcohol/13mmol/L Na2 CO3 in water/acetamide-benzyltrimethylammonium chloride (4:1, mol/mol) (4:7:9:1, v/v). The addition of deep eutectic solvent significantly improved the separation efficiency. The two targets can be easily recovered from the separation system through simple acidification and precipitation. It has potential for preparative separations on a large scale.

Raman spectroscopy applied to online monitoring of a bioreactor: Tackling the limit of detection

An in-situ monitoring model of alcoholic fermentation based on Raman spectroscopy was developed in this study. The optimized acquisition parameters were an 80 s exposure time with three accumulations. Standard solutions were prepared and used to populate a learning database. Two groups of mixed solutions were prepared for a validation database to simulate fermentation at different conditions. First, all spectra of the standards were evaluated by principal component analysis (PCA) to identify the spectral features of the target substances and observe their distribution and outliers. Second, three multivariate calibration models for prediction were developed using the partial least squares (PLS) method, either on the whole learning database or subsets. The limit of detection (LOD) of each model was estimated by using the root mean square error of cross validation (RMSECV), and the prediction ability was further tested with both validation datasets. As a result, improved LODs were obtained: 0.42 and 1.55 g·L−1 for ethanol and glucose using a sub-learning dataset with a concentration range of 0.5 to 10 g·L−1. An interesting prediction result was obtained from a cross-mixed validation set, which had a root mean square error of prediction (RMSEP) for ethanol and glucose of only 3.21 and 1.69, even with large differences in mixture concentrations. This result not only indicates that a model based on standard solutions can predict the concentration of a mixed solution in a complex matrix but also offers good prospects for applying the model in real bioreactors.

Measurements of airborne asbestos fibres during refurbishing.

Although the use of asbestos fibres in building materials has been prohibited in Norway since 1985, asbestos-containing materials (ACMs) are still found in many buildings. Lack of knowledge and awareness of these materials may lead to exposure during refurbishing. The aim of this study was to investigate the airborne fibre concentration and classify fibres found during the abatement of various ACMs. The release of fibres during short-term work tasks, such as drilling and sawing, was also investigated. Parallel air samples were collected during asbestos abetment of different building materials and analysed with scanning electron microscope (SEM) and phase-contrast microscope (PCM), respectively. Material samples were analysed with SEM. A real-time fibre monitor was used to measure asbestos during short-term work. The highest fibre concentrations were measured for samples collected during the removal of asbestos insulating boards (1.5-4.5 fibres/cm3 [f/cm3]), and the numbers were relatively similar for SEM and PCM. A large difference in asbestos concentrations was found between SEM and PCM when analysing floor materials, which were probably caused by a high number of gypsum fibres that the PCM operator counted. Thin fibres (<0.2 µm in width) were included in the SEM count and constituted up to 50% of the total fibre concentration for the asbestos cement materials. The presence of other inorganic and organic fibres on these samples probably led to similar results between SEM and PCM. Short-term work led to peak concentrations above 30 f/cm3.

Leaf age and light stress affect the ability to diagnose P status in field grown potatoes.

Phosphorus (P) deficiency is a global issue which can severely impact the yield of crops, including the P demanding and important food crop potato. Diagnosis of P status directly in the field can be used to adapt P fertilization strategies to the needs of the evolving crop during the growing season and is often estimated by analyzing P concentrations in leaf tissue. In this study, we investigate how diagnosis of P status in field grown potato plants is affected by leaf position and time of measurement in a randomized block experiment. The concentrations of many essential plant nutrients are highly dynamic, and large differences in nutrient concentrations were found in potato leaves depending on leaf age and time of sampling. During tuber initiation, P concentrations decreased in a steep gradient from the youngest leaves (0.8%) towards the oldest leaves (0.2%). The P concentrations in the youngest fully expanded leaf decreased by 25-33% within just 7 days, due to a high remobilization of P from source to sink tissue during crop development. 40 days later P concentrations in all leaves were near or below the established critical P concentration of 0.22%. The P concentration in leaf tissue thus depends on sampling time and leaf position on the plant, which in a practical setting might prevent a meaningful interpretation in terms of fertilizer recommendation. The chlorophyll a fluorescence parameter "P-predict", derived from the fluorescence transients, is an alternative to the classical chemical analysis of nutrient concentrations in leaf tissue. P-predict values serve as a proxy for the bioavailable P pool in the leaf and can be measured directly in the field using handheld technology. However, in conditions of high solar irradiation, the P-predict values of the most light-exposed leaf positions, i.e. the younger leaves, were found to be severely impacted by photoinhibition, preventing accurate characterization of the P status in potatoes. Shading the plants can reverse or prevent photoinhibition and restore the diagnostic capabilities of the P-predict approach.

MFID-Net: Multi-scaled feature-fused image dehazing via dynamic weights

Methods based on convolutional neural networks have achieved excellent performance in the image dehazing task. Unfortunately, most of the dehazing methods that exist suffer from loss of detail in the convolution and activation operations and failure to consider the effects of superimposing different intensities of haze, such as under-exposed and over-exposed images. To address these issues, we propose a dynamic dehazing convolution (DDC) based on attentional weight calculation and dynamic weight fusion and a dynamic dehazing activation (DDA) based on the input global context encoding function to address the problem of detail loss. And we propose a multi-scaled feature-fused image dehazing network (MFID-Net) based on DDC and DDA to address the effects of haze superposition. We also design a loss function based on the physical model with dynamic weights. Extensive experimental results demonstrate that the proposed MFID-Net performs favorably against the state-of-the-art algorithms on the hazy dataset while improving further on hazy images with large differences in haze concentration, and producing satisfactory dehazing results. The code is available at https://github.com/awhitewhale/MFID-Net.

Complex Life Histories Alter Patterns of Mercury Exposure and Accumulation in a Pond-Breeding Amphibian.

Quantifying how contaminants change across life cycles of species that undergo metamorphosis is critical to assessing organismal risk, particularly for consumers. Pond-breeding amphibians can dominate aquatic animal biomass as larvae and are terrestrial prey as juveniles and adults. Thus, amphibians can be vectors of mercury exposure in both aquatic and terrestrial food webs. However, it is still unclear how mercury concentrations are affected by exogenous (e.g., habitat or diet) vs endogenous factors (e.g., catabolism during hibernation) as amphibians undergo large diet shifts and periods of fasting during ontogeny. We measured total mercury (THg), methylmercury (MeHg), and isotopic compositions (δ 13C, δ15N) in boreal chorus frogs (Pseudacris maculata) across five life stages in two Colorado (USA) metapopulations. We found large differences in concentrations and percent MeHg (of THg) among life stages. Frog MeHg concentrations peaked during metamorphosis and hibernation coinciding with the most energetically demanding life cycle stages. Indeed, life history transitions involving periods of fasting coupled with high metabolic demands led to large increases in mercury concentrations. The endogenous processes of metamorphosis and hibernation resulted in MeHg bioamplification, thus decoupling it from the light isotopic proxies of diet and trophic position. These step changes are not often considered in conventional expectations of how MeHg concentrations within organisms are assessed.

Development of a population pharmacokinetic model and optimal dosing regimen of leflunomide in Korean population

PurposeLeflunomide is an immunosuppressive drug indicated for the treatment of rheumatoid arthritis (RA). While the pharmacokinetics (PK) of its active metabolite A771726 reportedly show large interindividual variability, no efficient dose individualization strategy is currently available. The goal of this work was to develop a population PK model for A771726 and propose an optimal individualized dosing strategy. MethodsA771726 plasma concentration data were collected from 50 healthy male volunteers participating in two leflunomide PK studies given a single oral dose of 40 mg. Concentrations were elevated in low body weight (WT) subjects and showed multiple peaks. Thus, A771726 PK modeling was conducted incorporating allometry scaling and enterohepatic circulation (EHC). For dose optimization, simulating a set of 1000 virtual subjects from the developed model and dividing the subjects into 5 groups with WT of 50, 60, 70, 80, 90 kg, respectively, the optimal dose was explored that achieves the drug concentration most similar to the target, which was defined as the concentration for the 70 kg subject treated with the current standard dosage regimen (the loading dose of 100 mg QD for 3 days, followed by the maintenance dose of 20 mg QD). ResultsThe data were best described by a two compartment model with first order absorption incorporating EHC with the bile released into the intestine. None of the covariates tested was found to be significant other than WT used in allometry. Simulation showed that the optimal loading dose increased by 15 mg for every 10 kg increment in WT while the optimal maintenance dose was 15 and 25 mg for 50 and 90 kg groups, respectively, and the same (= 20 mg) for the others. Large concentration differences from the target observed in low and high WT groups disappeared when optimal doses were given. ConclusionsThis work demonstrates the importance of a population PK model-based dose optimization approach in maintaining drug therapeutic concentrations in leflunomide treatment.

Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model

Fuel ethanol has drawn extensive attention as renewable energy. However, modeling the fuel ethanol batch fermentation process is still a critical task. The unstructured kinetic model (UKM) is often utilized to model the process, but it encounters two problems due to the large differences in initial glucose concentrations. First, the UKM has poor predictions of the yeast growth, which is a crucial production index. Second, the kinetic parameters of the UKM are time-varying because of the changing environmental conditions. The constant manually set kinetic parameters affect the prediction accuracy. To tackle the problems, we propose a dynamic hybrid model of the fuel ethanol fermentation process. First, a biomass concentration prediction model based on extreme gradient boosting is developed. It predicts the values of biomass concentrations and mycelium growth rate as supplementary mechanism knowledge. Then, we present an artificial neural network-based model to determine the time-varying kinetic parameters. Our model can accurately predict the time series of biomass, ethanol, and glucose concentrations, with RMSEs reaching 0.3323, 1.9295, and 3.0540. Experimental results show that the dynamic hybrid model performs with satisfactory accuracy in modeling the fuel ethanol fermentation process.

Effect of Impurity Doping on Thermoelectric Properties of Melt-Grown Mg&lt;sub&gt;2&lt;/sub&gt;Sn Crystals

We investigated the thermoelectric properties of melt-grown Mg2Sn crystals doped with various impurities such as Al, Bi, Sb, P, In, Ag, Au, W, and Mo; a large difference in the carrier concentration was observed for each impurity. The Bi- and Sb-doped Mg2Sn crystals showed n-type conductivity and had enough electron concentrations in the order of 1019 cm-3 by doping, and the maximum figure of merit (ZT) of 0.35 was observed in the crystal doped with 1.5 at% of Bi at 550 K. The Ag-, P-, In-, Au-, W-, and Mo-doped materials exhibited p-type conductivity. The Ag-doped samples had sufficient hole concentrations of more than 1019 cm-3, and the ZT reached 0.25 in the sample doped with 1.0 at% of Ag at 450 K. The P- and Sb-doped Mg2Sn crystals became dark gray powder within 1–2 weeks, but the crystals doped with the other impurities did not. This result suggested that the oxidation resistance of Mg2Sn crystals varied greatly depending on the type of dopant impurity.

Hostile climate during the Last Glacial Maximum caused sparse vegetation on the north-eastern Tibetan Plateau

Due to insufficient palaeo-environmental records, the vegetation history and hydrology of the Tibetan Plateau during the Last Glacial Maximum (LGM) are uncertain. In this study, a 316-cm-long sediment core covering the last 33.8 thousand years recovered from Koucha Lake on the north-eastern Tibetan Plateau was analysed for pollen, along with total organic carbon (TOC) and total nitrogen (TN), to explore past vegetation and hydrology changes. Alpine desert was widely distributed around the lake with sparse vegetation cover between 33.8 and 16.8 cal ka BP, particularly in the LGM, as inferred from the extremely low pollen concentrations together with high proportions of desert pollen taxa and exogenous arboreal taxa. Alpine steppe developed around the lake thereafter and was replaced by alpine meadow at ca. 7 cal. ka BP, which reflects the increasing effective moisture during the mid and late Holocene. The ancient Koucha Lake existed from 33 to 29 cal ka BP as a shallow lake and probably dried out in the LGM with a sediment hiatus (presence of coarse gravel layer), as suggested by the high and low content of Pediastrum. The current Koucha Lake formed at ca. 20 cal. ka BP with an increase in water level at ca. 16.8 cal ka BP as revealed by faint stratification of the sediments along with higher pollen concentration and presence of Pediastrum and Botryococcus. Our research suggests that pollen concentration should be paid more attention when investigating past vegetation, and that pollen percentages are not comparable among samples with large differences in pollen concentrations.