Variation Of Concentration Research Articles

Anthropogenic activities enhance mercury methylation in sediments of a multifunctional lake: Evidence from dissolved organic matter and mercury-methylating microorganisms

Multifunctional lakes are highly susceptible to anthropogenic influences, potentially introducing exogenous pollutants or nutrients into aquatic sediments. This, in turn, affects the mercury (Hg) methylation in the sediments. This study was conducted in the Changshou Lake, a representative multifunctional lake in southwestern China, with a specific focus on investigating the Hg variations, the potential of Hg methylation, and the influential factors affecting the methylation process within sediments across different functional areas. The results revealed significant variations in total Hg concentrations between the ecological culture area (area I), the ecological tourism area (area II), and the wetland protection area (area III), suggesting the possibility of exogenous Hg introduction associated with human activities. Furthermore, sediments from areas I and II displayed a greater potential for Hg methylation. This was ascribed to the enhanced diversity and relative abundance of Hg-methylating microorganisms, especially Geobacteraceae, induced by elevated levels of dissolved organic carbon in these two areas from human activities like historical cage culture. This study provides evidence that anthropogenic activities enhance the process of Hg methylation in the sediments of multifunctional lakes, highlighting the necessity of implementing comprehensive scientific water quality management practices to mitigate the negative impacts of human influences on these unique ecosystems.

Evaluation of Sentinel-2 Based Chlorophyll-a Estimation in a Small-Scale Reservoir: Assessing Accuracy and Availability

Small-scale reservoirs located in river estuaries are a significant water resource supporting agricultural and industrial activities; however, they face annual challenges of eutrophication and algal bloom occurrences due to excessive nutrient accumulation and watershed characteristics. Efficient management of algal blooms necessitates a comprehensive analysis of their spatiotemporal distribution characteristics. Therefore, this study aims to develop a chlorophyll-a (Chl-a) estimation model based on high-resolution satellite remote sensing data from Sentinel-2 multispectral sensors and multiple linear regression. The multiple linear regression (MLR) models were constructed using multiple reflectance-based variables that were collected over 2 years (2021–2022) in an estuarine reservoir. A total of 21 significant input variables were selected by backward elimination from the 2–4 band algorithms as employed in previous Chl-a estimation studies, along with the Sentinel-2 B1-B8A wavelength ratio. The developed algorithm exhibited a coefficient of determination of 0.65. Spatiotemporal variations in Chl-a concentration generated by the algorithm reflected the movement of high Chl-a concentration zones within the body of water. Through this analysis, it turned out that Sentinel-2-based spectral images were applicable to a small-scale reservoir which is relatively long and narrow, and the algorithm estimated changes in concentration levels over the seasons, revealing the dynamic nature of Chl-a distributions. The model developed in this study is expected to support effective algal bloom management and water quality improvement in a small-scale reservoir or similar complex water quality water bodies.

Exposure assessment during paint spraying and drying using PTR-ToF-MS.

Spraying is a common way to distribute occupational products, but it puts worker's health at risk by exposing them to potentially harmful particles and gases. The objective of this study is to use time-resolved measurements to gain an understanding of spray applications at the process level and to compare them to predictions of exposure models. We used proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) at 1-s time resolution to monitor the gas phase concentration of the solvents acetone, ethanol, butyl acetate, xylene and 1-methoxy-2-propy acetate during outdoor spraying and indoor drying of metal plate under various conditions of outdoor air supply. We found that during spraying, gas-phase exposure was dominated by the more volatile solvents acetone and ethanol, which exhibited strong concentration variations due to the outdoor winds. During drying, exposure strongly depended on the strength of ventilation. Under conditions with high supply of outdoor air, our measurements show a near-exponential decay of the solvent concentrations during drying. Conversely, under conditions without outdoor air supply, the drying process required hours, during which the less volatile solvents passed through a concentration maximum in the gas phase, so that the exposure during drying exceeded the exposure during spraying. The concentrations measured during spraying were then compared for each of the substances individually with the predictions of the exposure models ECETOC TRA, Stoffenmanager, and ART using TREXMO. For these conditions, ECETOC TRA and Stoffenmanager predicted exposures in the measured concentration range, albeit not conservative for all solvents and each application. In contrast, ART largely overestimated the exposure for the more volatile solvents acetone and ethanol and slightly underestimated exposure to 1M2PA for one spraying. ECETOC TRA and ART do not have options to predict exposure during drying. Stoffenmanager has the option to predict drying together with spraying, but not to predict the drying phase independently. Our study demonstrates the importance of considering both the spray cloud and solvent evaporation during the drying process. To improve workplace safety, there is a critical need for enhanced exposure models and comprehensive datasets for calibration and validation covering a broader range of exposure situations.

Fast repeatable measurement of hydrogen concentration based on a reflective fiber hybrid interferometer probe with vernier effect

A hydrogen (H2) sensor based on hybrid Fabry-Perot interference (FPI) and Michelson interference (MI) with Vernier effect is demonstrated. The optical probe is manufactured by fusing a multimode fiber (MMF) and a double-side hole fiber (DSHF) between a single-mode fiber (SMF) and a hollow core fiber (HCF) filled with polydimethylsiloxane (PDMS) at the end to form a cascaded FP and MI, which can generate a vernier envelope. by fusing a multimode fiber (MMF) and a double-side hole fiber (DSHF) between a single-mode fiber (SMF) and a hollow core fiber (HCF) filled with PDMS at the end. To accomplish H2 sensing, palladium-tungstic oxide (Pd-WO3) powder is attached to the exterior surface of PDMS, which will cause an exothermic redox reaction with H2. The released heat will lead to the volume expansion of PDMS with remarkable thermal response characteristics, and finally cause the movement of the vernier-like spectral envelope with the variation of H2 concentration. The sensitivity of the proposed sensor is 2.2 nm/% in the range of 0 %–1% through the H2 measurement experiment. For H2 with a concentration of 1 %, it has the response time of 28 s and shows good reversibility in the cyclic experiment. In addition, the sensitivity of temperature and relative humidity (RH) is 0.21 nm/°C and 0.0014 nm/%RH, respectively. The proposed sensor adopts a reflective probe, which is compact in structure and small in volume, and shows fast response and excellent repeatability. It has great advantages in H2 measurement in narrow spaces and long distances.

Fate characteristics and risk quantification of cyflumetofen from tomato cultivation to processing based on large–scale applications

Elucidating the fate characteristics of cyflumetofen and its main metabolite 2–TFMBA in tomato from cultivation to processing is crucial for safeguarding the environment and humans from hazardous effects. Cyflumetofen and 2-TFMBA could exist stably in tomato matrices for at least 343 days under frozen and dark conditions according to UHPLC–MS/MS, with a limit of quantitation of 0.001 mg/kg and retention time within 2.12 min. The occurrence, dissipation, and concentration variation of cyflumetofen were reflected by original depositions of 0.02–0.44 mg/kg, half–lives of 1.7–7.2 days, and terminal magnitudes of 0.005–0.30 mg/kg, respectively, with various influencing factors, e.g., climate conditions and tomato cultivars. Additionally, 13.5–59.3% of cyflumetofen was metabolized to 2-TFMBA, showing significant toxicological effects ranging from cultivation to processing. When the concentration decreased by 0.06 mg/kg, cyflumetofen was effectively removed by peeling, while washing was the recommended method for removing 2–TFMBA with a processing factor of 0.70. The comparative dietary risks of sum cyflumetofen were assessed for all life cycle populations using deterministic and probabilistic models. The risk quotients decreased to 1.3–4.8 times during the preparation of home canning tomato paste. Despite the low exposure risk, the potential health hazards of sum cyflumetofen should be considered, given its ubiquity and cumulative effects.

Antipyretic effect of inhaled Tetrastigma hemsleyanum polysaccharide on substance and energy metabolism in yeast-induced pyrexia mice via TLR4/NF-κb signaling pathway

Ethnopharmacological relevanceTetrastigma hemsleyanum Diels et Gilg, is one of the perennial evergreen plants with grass vine, which has obvious curative effect on severe infectious diseases. Although Tetrastigma hemleyanum has long been recognized for its capacity of antipyretic and antitoxic, its specific mechanism is unknown. Aim of the studyTo evaluate the antipyretic effect of Tetrastigma hemleyanum polysaccharide (THP) on mice with dry yeast-induced fever, and to explore its specific antipyretic mechanism. MethodsIn this study, THP was administered by aerosol in febrile mice. The rectal temperatures of treated animals were monitored at different time points. Histopathological evaluation and various inflammatory indexes were used to assess inflammatory damage. The concentration variations of the central neurotransmitter, endocrine system, substance and energy metabolism indicators were measured to explore the physiological mechanism. Quantitative real-time PCR, Western bolt and Immunohistochemistry were performed to identify the correlation between antipyretic and TLR4/NF-κB signaling pathway. ResultsTHP reduced the body temperature of febrile mice induced by dry yeast, as well as the levels of thermogenic cytokines and downregulated the contents of thermoregulatory mediators. THP alleviated the pathological damage of liver and hypothalamus caused by fever. In addition, THP decreased the secretion of thyroid hormone, substance and energy metabolism related indicators. Furthermore, THP significantly suppressed TLR4/NF-κB signaling pathway-related indicators. Conclusions: In conclusion, our results suggest that inhaled THP exerts antipyretic effect by mediating the thermoregulatory mediator, decreasing the content of pyrogenic factors to lower the body temperature, and eventually restoring the high metabolic level in the body to normal via inhibiting TLR4/NF-κB signaling pathway. The study provides a reasonable pharmacodynamic basis for the treatment of polysaccharide in febrile-related diseases.

Formulation and Effectiveness Test of 96% Ethanol Extract Anti-Acne Serum Cashew Leaves (Anacardium occidentale L.)

Introduction: Recently, the use of cosmetics to cure acne made from natural ingredients can have a good effect. Cosmetic preparations that are currently developing rapidly are serum preparations because they have better effects, and the moisturizing technology used is based on skin physiology. The natural ingredient in question is cashew leaves, which treat acne caused by Propionibacterium acnes. This research aims to obtain a serum preparation of cashew leaf extract to determine its effectiveness against P. acne and optimize the two ingredients, namely carbopol and triethanolamine (TEA) so that the serum preparation has physical stability that meets predetermined standards.
 Methods: This research is pure experimental research of a qualitative nature to obtain a serum preparation of cashew leaf extract with effectiveness as an anti-acne and using the factorial design method with the optimization factor for carbopol concentration comparison as a gelling agent and TEA as an alkalizing agent. The physical property parameters observed as a response to the equation are spreadability and viscosity using two-way statistical tests, ANOVA, with IBM SPSS statistics 29.0.1.0 software.
 Results: The research results obtained indicate the effectiveness of cashew leaf extract serum preparations against bacteria, such as Propionibacterium acnes. Apart from that, there is no significant difference between the formulas in the spreadability parameters, which means there is no influence from variations in carbopol and TEA concentrations on the physical evaluation of spreadability. Meanwhile, there are significant differences between the formulas in the viscosity parameters, there is an influence of variations in the concentration of carbopol and TEA on the physical evaluation of viscosity.
 Conclusion: Cashew leaf extract serum preparations are effective in treating bacteria Propionibacterium acnes, the cause of acne.

Additive manufacturing of wet-spun chitosan/hyaluronic acid scaffolds for biomedical applications

Additive manufacturing (AM) holds great potential for processing natural polymer hydrogels into 3D scaffolds exploitable for tissue engineering and in vitro tissue modelling. The aim of this research activity was to assess the suitability of computer-aided wet-spinning (CAWS) for AM of hyaluronic acid (HA)/chitosan (Cs) polyelectrolyte complex (PEC) hydrogels. A post-printing treatment based on HA chemical cross-linking via transesterification with poly(methyl vinyl ether-alt-maleic acid) (PMVEMA) was investigated to enhance the structural stability of the developed scaffolds in physiological conditions. PEC formation and the esterification reaction were investigated by infrared spectroscopy, thermogravimetric analysis, evolved gas analysis-mass spectrometry, and differential scanning calorimetry measurements. In addition, variation of PMVEMA concentration in the cross-linking medium was demonstrated to strongly influence scaffold water uptake and its stability in phosphate buffer saline at 37 °C. The in vitro cytocompatibility of the developed hydrogels was demonstrated by employing the murine embryo fibroblast Balb/3T3 clone A31 cell line, highlighting that PMVEMA cross-linking improved scaffold cell colonization. The results achieved demonstrated that the developed hydrogels represent suitable 3D scaffolds for long term cell culture experiments.

Prediction of Spatial Distribution of Heavy Metals in Cultivated Soil Based on Multi-source Auxiliary Variables and Random Forest Model

Spatial prediction of the concentrations of soil heavy metals (HMs) in cultivated land is critical for monitoring cultivated land contamination and ensuring sustainable eco-agriculture. In this study, 32 environmental variables from terrain, climate, soil attributes, remote-sensing information, vegetation indices, and anthropogenic activities were used as auxiliary variables, and random forest (RF), regression Kriging (RK), ordinary Kriging (OK), and multiple linear regression (MLR) models were proposed to predict the concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in cultivated soils. In comparison to those of RK, OK, and MLR, the RF model had the best prediction performance for As, Cd, Cr, Hg, Pb, and Zn, whereas the OK and RK models had highest prediction performance for Cu and Ni, respectively, showing that R2 was the highest, and mean absolute error (MAE) and root mean square error (RMSE) were the lowest. The prediction performance of the spatial distribution of soil HMs under different prediction methods was basically consistent. The high value areas of eight HMs concentrations were all distributed in the southern plain area. However, the RF model depicted the details of spatial prediction more prominently. Moreover, the importance ranking of influencing factors derived from the RF model indicated that the spatial variation in concentrations of the eight HMs in Lanxi City were mainly affected by the combined effects of Se, TN, pH, elevation, annual average temperature, annual average rainfall, distance from rivers, and distance from factories. Given the above, random forest models could be used as an effective method for the spatial prediction of soil heavy metals, providing scientific reference for regional soil pollution investigation, assessment, and management.

Salivary alpha-amylase stress reactivity in advanced-aged marmosets (Callithrix jacchus): Impacts of cognitive function and oral health status.

Salivary alpha-amylase (sAA) is an enzyme found in saliva and is considered a noninvasive biomarker for sympathetic nervous system activity. While a wide range of sAA activity in response to stress has been reported in nonhuman primates, the effects of stress on sAA activity in common marmosets are still unknown. We tested the hypothesis that advanced age and cognitive function may have an impact on stress-related sAA reactivity in marmosets. Thirteen marmosets (nine males and five females) had saliva samples collected during a stressful condition (manual restraint stress) at two different time points, with a 60-min interval. On the next day, the animals underwent the object recognition test (ORT, a type of cognitive test), and then oral examinations. The animals were categorized into two age groups: old (10-13 years), and very old (15-22 years). Irrespective of age, sAA levels showed a significant difference between T1 (mean 2.07 ± 0.86 U/mL) and T2 samples (mean 1.03 ± 0.67 U/mL), with higher values observed at T1 (p < 0.001). The intra-assay coefficients of variation (CV) for low and high sAA concentrations were 10.79% and 8.17%, respectively, while the interassay CVs for low and high sAA concentrations were 6.39% and 4.38%, respectively. Oral health issues were common but did not significantly impact sAA levels. The ORT indicated that the animals could recognize an object placed in the cage 6 h after familiarization. In conclusion, all marmosets showed a higher sAA concentration in the first saliva sample as compared to the second saliva sample collected 1 h later, indicating adaptation to stress. No significant differences in sAA levels were observed between sexes, ORT performance, or oral health. Our results indicate that autonomic responsivity and cognitive (memory) functions were preserved even in very old marmosets.

Longitudinal dissolved oxygen patterns in Atlantic salmon aquaculture sites in British Columbia, Canada

Dissolved oxygen (DO), an important water-quality parameter required to support aquatic life, is a critical factor for determining the general biological health of the aquatic ecosystem, and the concentration of DO is a critical factor in determining salmon growth and welfare. This study used longitudinal DO concentration, recorded hourly from 21 aquaculture sites, each with loggers in three separate cages, in four areas in British Columbia, Canada, between 2015 and 2017. The measurements were evaluated based on the recommended DO concentrations for protection of salmonids from hypoxia. Using a two-stage time-series analysis, we described variations in DO concentrations measured over the study period and their associations with environmental factors. Based on the water quality criteria for DO concentration, 42.3, 56.5, and 1.2% of the hourly DO data from the overall 21 aquaculture sites were classified as ‘optimal’, ‘sub-optimal’, and ‘stressed’, respectively. The frequency of hypoxic episodes differed substantially among seasons, aquaculture sites and even among cages within sites. The effects of environmental variables on DO concentration had markedly different patterns depending on the season. Significant associations with DO concentrations were observed for temperatures in the summer and winter months, and both wind direction and remotely-sensed estimated absorption from phytoplankton [aph(443)] in the winter months. The time-series regression model results showed overall (year-round) associations of temperature, wind speed, and aph(443) with DO concentrations. Describing DO measurements at these aquaculture sites provided an understanding of how much they deviated from the recommended DO concentrations, as well as provide baseline information for future water resource planning, including continued and improved water quality monitoring in aquaculture areas.

Potential of Salvinia molesta as a Copper Phytoremediation Agent based on Gene Expression Analysis

This research explores the rapid environmental impact of the batik industry, particularly concerning batik waste pollution, especially from the heavy metal copper (Cu). Untreated batik waste can have adverse effects on the environment. The study highlights the potential of the water fern plant (Salvinia molesta) as a heavy metal phytoremediator, specifically for Cu, by activating phytochelatin synthase. The research aims to determine the most effective waste concentration for Cu absorption by water ferns, measure the reduction in Cu levels after phytoremediation treatment, evaluate post-phytoremediation water quality, and observe PCS gene expression in the roots and leaves of water ferns. A static method is employed with variations in waste concentrations. Data analysis utilizes one-way ANOVA for Cu level reduction and changes in water quality. The results indicate that the most effective wastewater concentration for absorbing heavy metal copper (Cu) using water fern (Salvinia molesta) is 2%. The highest reduction in heavy metal copper (Cu) concentration after phytoremediation treatment with water fern (Salvinia molesta) is 41.48%. Water quality post-phytoremediation treatment using water fern (Salvinia molesta) at all concentrations exhibits improvement with an increase in dissolved oxygen (DO) levels. The expression of the phytochelatin synthase (PCS) gene in the leaves and roots of water fern (Salvinia molesta) confirms the role of the PCS gene in binding heavy metal copper (Cu) to the plant's vacuole.

Impacts of genetic polymorphisms and cancer cachexia on naldemedine pharmacokinetics and bowel movements in patients receiving opioid analgesics.

Clinical responses to naldemedine vary between individuals with advanced cancer. This is a prospective, single-center, observational study aimed to evaluate the influence of genetic polymorphisms and cachexia status on plasma naldemedine and clinical responses. Forty-eight patients being treated with naldemedine for opioid-induced constipation under treatment of cancer pain were enrolled. Plasma naldemedine concentrations were determined on the fourth day or later after administration of naldemedine, and the associations with genotypes, cachexia status, and clinical responses were assessed. Cancer patients exhibited a large variation in the plasma naldemedine concentrations, and it was correlated with serum total protein level. Patients who were homozygous CYP3A5*3 had a higher plasma concentration of naldemedine than those with the *1 allele. ABCB1 genotypes tested in this study were not associated with plasma naldemedine. A negative correlation was observed between the plasma naldemedine concentration and 4β-hydroxycholesterol level. The plasma naldemedine concentration was lower in patients with refractory cachexia than in those with precachexia and cachexia. While serum levels of interleukin-6 (IL-6) and acute-phase proteins were higher in patients with refractory cachexia, they were not associated with plasma naldemedine. A higher plasma concentration of naldemedine, CYP3A5*3/*3, and an earlier naldemedine administration after starting opioid analgesics were related to improvement of bowel movements. Plasma naldemedine increased under deficient activity of CYP3A5 in cancer patients. Cachectic patients with a higher serum IL-6 had a lower plasma naldemedine. Plasma naldemedine, related to CYP3A5 genotype, and the initiation timing of naldemedine were associated with improved bowel movements.

Improved multivariable algorithms for estimating oceanic particulate organic carbon concentration from optical backscattering and chlorophyll-a measurements

The capability to estimate the oceanic particulate organic carbon concentration (POC) from optical measurements is crucial for assessing the dynamics of this carbon reservoir and the capacity of the biological pump to sequester atmospheric carbon dioxide in the deep ocean. Optical approaches are routinely used to estimate oceanic POC from the spectral particulate backscattering coefficient bbp, either directly (e.g., with backscattering sensors on underwater platforms like BGC-Argo floats) or indirectly (e.g., with satellite remote sensing). However, the reliability of algorithms which relate POC to bbp is typically limited due to the complexity of interactions between light and natural assemblages of marine particles, which depend on variations in particle concentration, composition, and size distribution. This study expands on our previous work by analysis of an extended field dataset created with judicious data inclusion criteria with the aim to provide POC algorithms for multiple light wavelengths of measured bbp, which can be useful for applications with in situ optical sensors as well as above-water active or passive measurement systems. We describe an improved empirical multivariable approach to estimate POC from simultaneous measurements of bbp and chlorophyll-a concentration (Chla) to better account for the effects of variable particle composition on the relationship between POC and bbp. The multivariable regression models are formulated using a relatively large dataset of coincident measurements of POC, bbp, and Chla, including surface and subsurface data from the Atlantic, Pacific, Arctic, and Southern Oceans. We show that the multivariable algorithm provides reduced uncertainty of estimated POC across diverse marine environments when compared with a traditional univariate algorithm based on only bbp. We also propose an improved formulation of univariate algorithm based on bbp alone. Finally, we examine performance of several algorithms to estimate POC using our dataset as well as a dataset consisting of optical measurements from BGC-Argo floats and traditional POC measurements collected during a coincident research cruise in the Atlantic Ocean.

An effective magnetic nanobiocomposite: Preparation, characterization and its application for adsorption removal of P-nitroaniline from aquatic environments

In this investigation, a magnetic nanobiocomposite, denoted as CoFe2O4/Activated Carbon integrated with Chitosan (CoFe2O4/AC@Ch), was synthesized based on a microwave-assisted for the efficacious adsorption of P-nitroaniline (PNA). The physicochemical properties of the said nano biocomposite were thoroughly characterized using a suite of analytical methodologies, namely FESEM/EDS, BET, FTIR, XRD, and VSM. The results confirm the successful synthesis of the nanobiocomposite, with its point of zero charge (pHZPC) determined to be 6.4. Adsorptive performance towards PNA was systematically examined over a spectrum of conditions, encompassing variations in PNA concentration (spanning 10–40 mg/L), adsorbent concentration (10–200 mg/L), contact periods (2.5–22.5 min), and solution pH (3–11). Upon optimization, the conditions converged to an adsorbent concentration of 200 mg/L, pH 5, PNA concentration of 10 mg/L, and a contact duration of 22.5 min, under which an impressive PNA adsorption efficacy of 98.6% was attained. Kinetic and isotherm analyses insinuated the adsorption mechanism to adhere predominantly to the pseudo-second-order kinetic and Langmuir isotherm models. The magnetic nanocomposite was recovered and used in 4 cycles, and the absorption rate reached 86%, which shows the good stability of the magnetic nanocomposite in wastewater treatment. Conclusively, these empirical outcomes underscore the viability of the formulated magnetic nanobiocomposite as a potent, recyclable adsorbent for the proficient extraction of PNA from aqueous matrices.

Plant functional traits mediate the response magnitude of plant-litter-soil microbial C: N: P stoichiometry to nitrogen addition in a desert steppe

Global nitrogen deposition is significantly altering the carbon (C), nitrogen (N) and phosphorus (P) stoichiometry in terrestrial ecosystems, yet how N deposition simultaneously affects plant-litter-soil-soil microbial stoichiometry in arid grassland is still unclear. In a five-year experimental study conducted in a desert steppe in Northern China, we investigated the effects of N addition on the C:N:P stoichiometry of plants, litter, soil, and soil microbes. We also used structural equation modelling (SEM) exploring the direct or indirect effects of N addition, plant species diversity, functional traits and diversity, soil microbial diversity, soil pH, soil electrical conductivity (EC) and moisture on the stoichiometry in plant-soil system. The results showed that N addition increased the N, P concentrations and N:P in plants, the N concentration and N:P in litter, and the C, N concentrations, C:P and N:P in microbes. Conversely, it decreased the C:N and C:P in plants, and litter C:N. Functional traits, functional dispersion (FDis), soil pH and EC accounted for a substantial proportion of the observed variations in elemental concentrations (from 42 % to 69 %) and stoichiometry (from 9 % to 73 %) across different components. SEM results showed that N addition decreased C:N and C:P in plants and litter by increasing FDis and leaf N content, while increased plant and litter N:P by decreasing leaf C content and increasing specific leaf area, respectively. Furthermore, N addition increased microbial C:P by increasing leaf thickness. We also found the mediating effects of soil pH and EC on C:N, C:P of litter and microbial N:P. Overall, our research suggests that plant functional traits as key predictors of nutrient cycling responses in desert steppes under N addition. This study extends the application of plant functional traits, enhances our understanding of C and nutrient cycling and facilitates predicting the response of desert steppes to N deposition.

Clinical algorithm model based on cfDNA to predict SLE disease activity.

Circulating cell-free DNA (cfDNA) has been widely used as a new liquid-biopsy marker. Dysregulation of cfDNA has been found in patients with systemic lupus erythematosus (SLE). However, the detailed association between cfDNA and SLE has not been thoroughly studied. Plasma samples were collected from 88 patients with active SLE and 39 patients with inactive SLE. The cfDNA concentration was determined, and the length and distribution of cfDNA fragments were verified. cfDNA concentrations were significantly higher in patients with active SLE than in patients with inactive SLE (0.4 [0.18-0.897] ng/µL vs 0.249 [0.144-0.431] ng/µL; p = .043). cfDNA fragments were enriched in the ranges of 153-198 bp and 300-599 bp. cfDNA concentrations were associated with the reduction of the anti-double-stranded DNA (dsDNA) antibodies titer (r = -0.301, p = .034). The presence of anti-U1 ribonucleoprotein (p = .012), anti-Sjogren syndrome A (p = .024), anti-dsDNA (p = .0208), and anti-nucleosome antibodies (p = .0382) might associate to the variation of cfDNA concentration. Reduced cfDNA concentration was associated with renal damage in active SLE patients (0.31 [0.11-0.73] ng/µL vs 0.65 [0.27-1.53] ng/µL; p = .009). The Active index, a combination model including cfDNA concentration and other clinical indices, had an area of 0.886 under the receiver operating characteristics curve for distinguishing active SLE. The Active index was positively correlated with the SLE disease activity index score (r = 0.6724, p < .0001). Through systematic stratified analysis and clinical algorithm model, this study found that plasma cfDNA concentration is closely related to SLE disease severity, which has guiding significance for the future clinical application of cfDNA in SLE.

Monitoring Suspended Sediment Transport in the Lower Yellow River using Landsat Observations

The spatiotemporal variations in suspended sediment concentration (SSC) in the lower reaches of the Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding the spatiotemporal distribution characteristics of SSC in water holds crucial implications for environmental protection and reservoir operation management. Based on daily-scale SSC monitoring data from four hydrological stations in the lower Yellow River, this study established an SSC remote sensing model applicable to Landsat series satellite data. The independent variable of the model, Rrs(NIR)/(Rrs(G) + Rrs(R) + Rrs(SWIR)), demonstrated sensitivity to water bodies with different SSC values. Distinctive spatiotemporal characteristics in sediment transport were observed across the lower Yellow River. Spatially, the SSC values in the Sanmenxia and Xiaolangdi reservoirs were notably lower than those in other river sections, averaging 1008.42 ± 602.83 mg/L and 1177.89 ± 627.95 mg/L, respectively. Over time, the majority of the river sections (96%) exhibited decreasing trends in SSC during 1984–2022, particularly in the downstream Xiaolangdi reservoir, with average SSC values of 4265.58 ± 1101.77 mg/L in the 1980s and 1840.80 ± 2255.15 mg/L in the 2020s. Seasonal variations in SSC were prominent, with higher summer concentrations, averaging 5536.43 ± 2188.77 mg/L (2020s summer) and 814.11 ± 158.27 mg/L (2020s winter). Reductions in SSC during 1984–2022 primarily occurred in summer, weakening its seasonal variability in the lower Yellow River. Water discharge emerged as a critical factor influencing suspended sediment transport, with SSC increasing in high-water-flow months. Following the construction of the Xiaolangdi reservoir, the relationship between SSC and water discharge at different stations underwent notable alterations. This study enhances our understanding of the spatiotemporal dynamics of suspended sediment transport in the lower Yellow River, providing valuable insights for utilizing long-term Landsat series data in the dynamic monitoring of river sediment transport.

ZnO-Au Hybrid Metamaterial Thin Films with Tunable Optical Properties

ZnO-Au nanocomposite thin films have been previously reported as hybrid metamaterials with unique optical properties such as plasmonic resonance properties and hyperbolic behaviors. In this study, Au composition in the ZnO-Au nanocomposites has been effectively tuned by target composition variation and thus resulted in microstructure and optical property tuning. Specifically, all the ZnO-Au nanocomposite thin films grown through the pulsed laser deposition (PLD) method show obvious vertically aligned nanocomposite (VAN) structure with the Au nanopillars embedded in the ZnO matrix. Moreover, the average diameter of Au nanopillars increases as Au concentration increases, which also leads to the redshifts in the surface plasmon resonance (SPR) wavelength and changes in the hyperbolic behaviors of the films. As a whole, this work discusses how strain-driven tuning of optical properties and microstructure resulted through a novel Au concentration variation approach which has not been previously attempted in the ZnO-Au thin film system. These highly ordered films present great promise in the areas of sensing, waveguides, and nanophotonics to name a few.

Implementation of a Fractional-Inductor (α

In this paper, the realization of a fractional-order inductor of order less than 0.5 has been realized, where, semiconducting Quantum dots of Zirconium (Zr QDs) is the key component. When a TEM (Transverse Electromagnetic Mode) is used to design a fractional-inductor using a conducting core, it yields a fractional order of 0.5 which is also mathematically derived in this work. Here, in place of conducting fluid, different concentrations of Zr QDs in ethanol have been used which show different phase shifts of the current (less than 45°) with respect to voltages. These experimentally found results, confirm the realization of fractional-inductor of order α < 0.5.The fabricated device works perfectly with a temperature range of −10 °C to 45 °C with an aging of ≈ 1.5 years. Also, the fabricated inductor has been used in an integrating circuit, which shows the change in roll-off-rate, and cut-off-frequency variations with respect to the variation in concentration of Zr QDs in the ethanol solution as the core of fractional-inductor. These experimental values show a good agreement with the simulation with a maximum error percentage of 10 %.