Dynamic Mass Research Articles

The low primordial heavy noble gas and 244Pu-derived Xe contents of Earth's convecting mantle

Clues to unraveling the origin and history of terrestrial volatiles lie in the noble gas record of Earth's mantle. However, the low abundance of heavy noble gases (Ar-Kr-Xe) in mantle-derived rocks presents a major analytical challenge that limits our understanding of mantle volatile evolution. Here, we employ a new technique of ultrahigh precision dynamic mass spectrometry to measure Ar-Kr-Xe isotopes in mantle-derived gas collected from Mt. Etna (Italy) and Eifel (Germany), which both tap depleted convecting mantle reservoirs. We find that the fractions of primordial Kr-Xe from accretionary sources (≤ 7 % of non-radiogenic, non-fissiogenic isotopes) and 244Pu-derived 136Xe (≤ 9.8 ± 9.3 % of total fissiogenic Xe) are both markedly lower than previously estimated. For Mt. Etna, we find an apparent lack of detectable primordial Xe, which could reflect an additional contribution from recycled atmospheric volatiles from nearby subduction. In addition, slight excesses of 238U-derived fissiogenic Xe relative to the upper mantle composition may reflect the contribution of a crustal component related to the occurrence of a HIMU (“high μ” where μ = 238U/204Pb)-type source in Mt. Etna volcanic products. The low primordial heavy noble gas and 244Pu-derived Xe contents of Earth's convecting mantle, as derived from these new data, requires extensive volatile loss during terrestrial accretion, followed by long-term degassing and pervasive overprinting of primordial heavy noble gases by subduction recycling. In addition, we suggest that quantitative incompatible element (including Pu, U) extraction to the Hadean crust and subsequent reintroduction of U via subduction could have contributed to lowering the ultimate fraction of 244Pu-derived 136Xe in the upper mantle. The differences observed between this study and other upper mantle Xe studies may reflect mantle source heterogeneities (e.g. due to the heterogeneous overprinting of mantle volatiles by subduction) but could also result from analytical inconsistencies and/or subsurface isotope fractionation in natural systems. Future studies are crucial to gain insight into the origin of these different results.

Comparing novel small-angle x-ray scattering approaches for absolute size and number concentration measurements of spherical SiO2 particles to established methods

Biomedical analytical applications, as well as the industrial production of high-quality nano- and sub-micrometre particles, require accurate methods to quantify the absolute number concentration of particles. In this context, small-angle x-ray scattering (SAXS) is a powerful tool to determine the particle size and concentration traceable to the Système international d’unités (SI). Therefore, absolute measurements of the scattering cross-section must be performed, which require precise knowledge of all experimental parameters, such as the electron density of solvent and particles, whereas the latter is often unknown. Within the present study, novel SAXS-based approaches to determine the size distribution, density and number concentrations of sub-micron spherical silica particles with narrow size distributions and mean diameters between 160 nm and 430 nm are presented. For the first-time traceable density and number concentration measurements of silica particles are presented and current challenges in SAXS measurements such as beam-smearing, poorly known electron densities and moderately polydisperse samples are addressed. In addition, and for comparison purpose, atomic force microscopy has been used for traceable measurements of the size distribution and single particle inductively coupled plasma mass spectrometry with the dynamic mass flow approach for the accurate quantification of the number concentrations of silica particles. The possibilities and limitations of the current approaches are critically discussed in this study.

Low-Frequency Flexural Wave Acoustic Insulation Characteristics of a Double-Layer Metamaterial Plate

The effects of geometric parameters and constituent material parameters on the flexural wave bandgap of a locally resonant double-layer metamaterial plate are investigated using the finite element method. Reasonable parameters are obtained through optimization; then, a double-layer plate made of ABS material with added aluminum mass blocks is designed. The results show that it can open the low-frequency (112--124 Hz) flexural wave bandgap at a subwavelength size. The metamaterial plate is modeled as an equivalent spring-mass system, and the frequency range with negative density for the equivalent dynamic mass is consistent with the width of the flexural wave bandgap. The bandgap generation mechanism is further elucidated. Sound insulation performance of double-layer metamaterial panels verified in an acoustic chamber. The maximum amplitude of STL is achieved at the 112 Hz point in the bandgap frequency range, which indicates that the low-frequency bandgap can effectively reduce vibration and noise. These results demonstrate that this novel double-layer metamaterial plate has wide applications in engineering.

Variable-density solute transport in unconfined coastal aquifers with a subsurface dam

Recently, the influence of subsurface dams on solute transport in coastal aquifers has become a hot research topic. Although many studies have been conducted, the combined effects of subsurface dam and tides on variable-density solute transport remain unclear, and this study aimed to fill this research gap. In the current study, a numerical model representing a 2-D cross-shore coastal aquifer was established. The model simulated cases with and without a subsurface dam, and sensitivity analysis cases with different height and location of the subsurface dam and solute concentration. The results show that a subsurface dam blocks a portion of the solute plume, which can only be discharged by dilution at the edges, thereby altering its discharge pattern and reducing their discharge rate. The addition of a subsurface dam may either prolong or shorten the residence time of solute,depending on the location rather than the height of the subsurface dam. In particular, a more landward subsurface dam would significantly increase the residence time; sensitivity analysis demonstrates that both the landward shift and the height increase of the subsurface dam contribute to a heightened ratio of dynamic mass distribution for the solute plume within the freshwater and saltwater zones of the aquifer, with maximum changes in mass distribution ratios of 87.22% and 300%, respectively. Also, these factors cause the solute to migrate both seaward and landward, respectively, across the primary outflow regions of the aquifer-ocean interface. Results from this study may provide theoretical guidance for the optimal design and environmental impact assessment of subsurface dams.

Longitudinal dynamic single-cell mass cytometry analysis of peripheral blood mononuclear cells in COVID-19 patients within 6 months after viral RNA clearance

This study investigates the longitudinal dynamic changes in immune cells in COVID-19 patients over an extended period after recovery, as well as the interplay between immune cells and antibodies. Leveraging single-cell mass spectrometry, we selected six COVID-19 patients and four healthy controls, dissecting the evolving landscape within six months post-viral RNA clearance, alongside the levels of anti-spike protein antibodies. The T cell immunophenotype ascertained via single-cell mass spectrometry underwent validation through flow cytometry in 37 samples. Our findings illuminate that CD8 + T cells, gamma-delta (gd) T cells, and NK cells witnessed an increase, in contrast to the reduction observed in monocytes, B cells, and double-negative T (DNT) cells over time. The proportion of monocytes remained significantly elevated in COVID-19 patients compared to controls even after six-month. Subpopulation-wise, an upsurge manifested within various T effector memory subsets, CD45RA + T effector memory, gdT, and NK cells, whereas declines marked the populations of DNT, naive and memory B cells, and classical as well as non-classical monocytes. Noteworthy associations surfaced between DNT, gdT, CD4 + T, NK cells, and the anti-S antibody titer. This study reveals the changes in peripheral blood mononuclear cells of COVID-19 patients within 6 months after viral RNA clearance and sheds light on the interactions between immune cells and antibodies. The findings from this research contribute to a better understanding of immune transformations during the recovery from COVID-19 and offer guidance for protective measures against reinfection in the context of viral variants.

Locally multi-resonant meta-shells for broadband vibration suppression

This paper presents the design of a meta-shell with spring-mass resonators periodically attached onto a cylindrical shell to achieve low-frequency, broadband vibration suppression. The dispersion relations of the meta-shell are calculated using Hamilton's principle in conjunction with the plane wave expansion (PWE) method, which is verified by the finite element method (FEM). The bandgaps in different wave propagation directions are observed which is induced by the dynamic negative effective mass density. The effects of different meta-shell parameters on bandgap behavior are investigated, from which the fine-tuning of bandgaps can be achieved. The vibration propagation in finite meta-shells is then studied using FEM and the attenuation of vibration is demonstrated in the frequency range of the bandgap. To further broaden the bandgap frequency range, we propose a gradient configuration of a multi-resonant meta-shell in which the resonant frequencies of multiple sets of resonators comply with equal ratio distribution. Compared with the single-resonator meta-shell, it is shown that a 170.7 % expansion in bandwidth can be achieved while the total mass of the resonators is reduced by 41.5 %. Finally, the vibration suppression performance of the multi-resonant meta-shell is experimentally verified, demonstrating the broadband vibration attenuation in corresponding bandgap frequency ranges. This work shows promising application potentials for the multi-resonant meta-shells in vibration control engineering.

Inert Gas Element as Active Infrared‐Absorption Source and Donor in Silicon for Forbidden‐Wavelength Sensing

AbstractIntrinsic silicon (Si) is forbidden for infrared (IR) sensing at the communication wavelength like 1.31 or 1.55 µm due to the well‐known bandgap limitation. In this work, an unexpected physical picture of using argon (Ar) is identified, which is usually inert to the surrounding chemical environment and used as a protective agent in semiconductor processing, to overcome the IR‐sensing‐forbidden problem in Si. Here, it is shown by an analysis of a dynamic secondary ion mass spectrometer that such a Si, when exposed to laser pulse in Ar gas, can contain a very high dose of Ar up to 1020 cm−3 even after 1300 days. First‐principles calculations, molecular dynamics, and Hall effect measurements reveal that, due to both steric and dynamic repulsions by Ar orbitals to Si dangling bonds, the Ar‐filled‐vacancy produces a much wider defect band inside the gap, which is not only responsible for strong infrared absorption, but also causes a significant increase in n‐type conductivity, both in line with experiments. The study proves that originally inert elements in fact can act as active impurities in semiconductors for advanced applications, which updates the current knowledge of defect physics.

Erratum to “Thin-Film Silicon MEMS for Dynamic Mass Sensing in Vacuum and Air: Phase Noise, Allan Deviation, Mass Sensitivity and Limits of Detection”

Erratum to “Thin-Film Silicon MEMS for Dynamic Mass Sensing in Vacuum and Air: Phase Noise, Allan Deviation, Mass Sensitivity and Limits of Detection”

Analytical method and experimental verification of coupled micro-vibration for spacecraft based on mechanical impedance theory

Micro-vibrations exert detrimental effects on spacecraft that requires extreme precision performance. Dynamic mass method (DMM) is a component-level grounded micro-vibration measurement method, which is widely used in the analysis of coupled interplay between micro-vibration sources and spacecraft. However, this study reveals that all existing research involving DMM contains a fundamental error during its theoretical derivation. In light of this, the root cause of the error is investigated based on the mechanical impedance theory. Building upon this, a modified dynamic mass method (MDMM) is further proposed, and corresponding solution steps are also given, with emphasis on the treatment of gyroscopic effects of reaction wheels (RWs). To validate this analytical method, a grounded micro-vibration measurement system for RWs is designed and established. Micro-vibrations of an RW are measured under both the rigid-mounted and isolated conditions, respectively. Leveraging the physical parameters of the isolator, MDMM is applied to process the micro-vibration data measured under a rigid-mounted condition, which predicts the transmitted data under an isolated condition. The analytical data produced by MDMM agrees well with the measured results, which partially validates the feasibility and effectiveness of the proposed MDMM. This analytical method proposed in this work can serve as a theoretical tool for both measurement and analysis of the coupled micro-vibrations of sources and spacecraft.

Ozone Chemistry on Greasy Glass Surfaces Affects the Levels of Volatile Organic Compounds in Indoor Environments.

The chemistry of ozone (O3) on indoor surfaces leads to secondary pollution, aggravating the air quality in indoor environments. Here, we assess the heterogeneous chemistry of gaseous O3 with glass plates after being 1 month in two different kitchens where Chinese and Western styles of cooking were applied, respectively. The uptake coefficients of O3 on the authentic glass plates were measured in the dark and under UV light irradiation typical for indoor environments (320 nm < λ < 400 nm) at different relative humidities. The gas-phase product compounds formed upon reactions of O3 with the glass plates were evaluated in real time by a proton-transfer-reaction quadrupole-interface time-of-flight mass spectrometer. We observed typical aldehydes formed by the O3 reactions with the unsaturated fatty acid constituents of cooking oils. The formation of decanal, 6-methyl-5-hepten-2-one (6-MHO), and 4-oxopentanal (4-OPA) was also observed. The employed dynamic mass balance model shows that the estimated mixing ratios of hexanal, octanal, nonanal, decanal, undecanal, 6-MHO, and 4-OPA due to O3 chemistry with authentic grime-coated kitchen glass surfaces are higher in the kitchen where Chinese food was cooked compared to that where Western food was cooked. These results show that O3 chemistry on greasy glass surfaces leads to enhanced VOC levels in indoor environments.

Amine-impregnated natural inorganic nanotubes via layer-by-layer electrostatically self-assembly approach for efficient CO2 adsorption

Developing cost-effective and high-performance solid amine adsorbents has considered as an important way to alleviate the greenhouse effect. How to precisely regulate its pore structure and surface interface characteristics, and how to cooperate to optimize the dynamic mass transfer and adsorption–desorption behavior of gas in the adsorbent are still challenging work. Herein, we demonstrated a facile and efficient approach to construct polyethyleneimine (PEI) impregnated halloysite nanotubes (HNTs) as an emerging nanocomposite for CO2 capture. Based on the natural electrostatic differences of inner and outer walls for HNTs, the hollow tubular structures of adsorbents were constructed by selective surface modification and layer-by-layer electrostatic self-assembly technology to improve the CO2 uptake capacity and cyclic stability, in which poly(sodium-p-styrene sulfonate) (PSS) and PEI were used as polyanionic and polycationic layer, respectively, to coat the inner walls of HNTs. The loading capacity of PSS-PEI composite ionic layers in HNTs and the influence of PSS polyanionic layer on PEI dispersion were specifically discussed according to the CO2 uptake capacity, adsorption heat, thermodynamics and kinetics of the adsorbents. The optimal PEI20-0.5PHNTs adsorbent exhibited a higher CO2 uptake of 0.87 mmol/g at 80 °C in the flow of 40 vol% N2/60 vol% CO2 than that of PEI20-HNTs, owing to the high amine efficiency due to the uniform dispersion of PEI in the electrostatic composite ionic layers. Furthermore, PEI20-0.5PHNTs reached 75 % of the maximum adsorption capacity at the 5th min of the adsorption process and released the most heat during adsorption at − 18.28 kJ/mol due to the presence of electrostatic composite ionic layers. PEI20-0.5PHNTs showed excellent cyclic stability with a slight loss of 7.4 %. The electrostatic self-assembled adsorbent obtained by layer-by-layer loading of PSS and PEI based on the unique surface charge characteristics of HNTs is an inspiration for the synthesis of cost-effective solid amine adsorbents for practical CO2 capture and separation.

Gluon mass generation from renormalons and resurgence

We establish a link between the concepts of infrared renormalons, infrared fixed point, and dynamical nonperturbative mass generation of gluons in pure Yang-Mills theories. By utilizing recent results in the resurgent analysis of renormalons through non-linear ordinary differential equations, we develop a new description for the gluon propagator, thereby realizing the Schwinger mechanism. Specifically, this approach leads to a nonperturbative, dynamic mass generation for Yang-Mills gauge bosons in the deep infrared region, a phenomenon closely associated with color confinement. Furthermore, we present arguments about the limit of applicability of the Borel-Ecalle resummation of the renormalons by comparing it with the Kallen-Lehman representation of the gluon propagator.

Single particle inductively coupled plasma mass spectrometry metrology: Revisiting the transport efficiency paradigm

Transport efficiency has become a critical parameter in single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) since it is involved in the calibrations to determine different measurands (element mass per particle, particle size and particle number concentration). Specific methods for its determination based on the use of particle standards have been developed and widely applied (particle frequency and particle size methods). A refined indirect method not relying on particle standards is also available (dynamic mass flow method). A number of discrepancies on the accuracy of these methods and their adequacy have become evident, making a revision of the topic pertinent. In fact, the application of the particle frequency and particle size methods determine the transport efficiencies corresponding to the particles or the dissolved element respectively, whereas the solvent transport efficiency is actually measured by the dynamic mass flow method. The use of each of these methods requires assuming different conditions that must be considered. These conditions, together with the sources of bias associated to each method are critically discussed to provide a holistic and harmonized view of transport efficiency in the context of SP-ICP-MS metrology.

Simultaneous vibration isolation and energy harvesting via a new negative stiffness system with inertial amplifier

The negative stiffness system provides significant vibration isolation. The conversion of mechanical energy from structural vibrations into electrical energy is an effective method of energy harvesting. In this paper, a new negative stiffness system (NSS) with inertial amplifier for vibration isolation and energy harvesting is established, whose main purpose is to achieve good vibration isolation effect while the system can achieve the purpose of energy harvesting. Inertial amplifiers are used to improve the dynamic effective mass of the system, thereby reducing the natural frequency of the system. Using the multi-scale method, the amplitude-frequency response equation of the system is derived and the amplitude-frequency characteristic curve is plotted. The Lyapunov exponent, the root mean square of the voltage of the piezoelectric system and the basin of attraction are introduced to analyze the energy harvesting performance of the system. Numerical results show that the inertial amplifier improves the vibration isolation capacity of the negative stiffness structure in the low-frequency band. There is a correlation between the basin of attraction, the Lyapunov exponent, and the root mean square of voltage.

PRINCIPLES OF MATHEMATICAL SIMULATION OF MINING VEHICLES USING APPLIED MATHEMATICAL SOFTWARE

The transportation of rock mass and coal in mining operations relies heavily on the efficiency and reliability of mining transport systems. This study delves into the intricate dynamics of chassis functions during transportation, emphasizing the critical role of transmitting dynamic stresses and mass to the road or rail structures. With a focus on increasing productivity, modern mining locomotives and heavy dump trucks now carry substantial adhesion adhesive weights, allowing for the hauling of heavier loads even on steep slopes. The integration of scientific simulations and research-based design methods aids in identifying and managing dynamic loading effects within mining vehicle chassis. This approach minimizes the transfer of dynamic loads onto the bolster structure, enhancing system reliability and operational efficiency. Computer-aided software plays a vital role in stream-lining the development process, reducing the need for costly physical prototypes and extensive testing in challenging mining environments. The study outlines simplified calculation schemes for mining transport utilities, balancing the need for accuracy with computational efficiency. By utilizing mathematical models and simulation techniques, the dynamics of mine locomotives and dump trucks can be accurately evaluated, guiding design decisions and operational strategies. The application of Lagrange equations and software tools like “Wolfram Mathematica” facilitates the generation of differential equations for dynamic analysis, providing insights into vehicle dynamics and road interactions. Overall, this research underscores the importance of advanced modeling and simulation techniques in optimizing mining transport systems, enhancing safety, productivity, and reliability in demanding mining environments. Purpose. To highlight the application of mathematical software as an instrument for mechanical system dynamics study, that allows scientifically substantiate the usage of new technical solutions during their development. Method. Development a system of differential equations using Lagrange equations of the 2nd order, which are solved in Wolfram Mathematica. Preparation of initial conditions and mass-inertia data can be done by any known software. The generalized mathematical model can be used for any vehicle suspending unnecessary coordinates. Results. Implementation of new technical solutions without scientific ground could be resulted in difficulties while exploitation. For its removal necessary to receive dynamical characteristics. Existing engineering calculation methods are not suitable, especially because of tight time and limited financing. The customized mathematical models can be developed and solved on demand using available software. A scientific novelty. Enhancement of theoretical and experimental research become possible owing to the usage of mod- ern approaches of dynamic systems simulation using applied mathematical software Wolfram Mathematica. Obtained model can be modified in few operation from one mass task into multibody system with maximum 69 free displacements (coordinates). Practical value. The possibility to receive customized simulation model fast, verified with increased quality for scientific purposes.

Perspective on quantitative phase imaging to improve precision cancer medicine.

Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states. This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection. We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging. QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research. QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.

Machine learning prediction of concrete frost resistance and optimization design of mix proportions

This study explores nine machine learning (ML) methods, including linear, non-linear and ensemble learning models, using nine concrete parameters as characteristic variables. Including the dosage of cement (C), fly ash (FA), Ground granulated blast furnace slag (GGBS), coarse aggregate (G), fine aggregate (S), water reducing agent (WRA) and water (W), initial gas content (GC) and number of freeze-thaw cycles (NFTC), To predict relative dynamic elastic modulus (RDEM) and mass loss rate (MLR). Based on the linear correlation analysis and the evaluation of four performance indicators of R2, MSE, MAE and RMSE, it is found that the nonlinear model has better performance. In the prediction of RDEM, the integrated learning GBDT model has the best prediction ability. The evaluation indexes were R2 = 0.78, MSE = 0.0041, MAE = 0.0345, RMSE = 0.0157, SI = 0.0177, BIAS = 0.0294. In the prediction of MLR, ensemble learning Catboost algorithm model has the best prediction ability, and the evaluation indexes are R2 = 0.84, MSE = 0.0036, RMSE = 0.0597, MAE = 0.0312, SI = 5.5298, BIAS = 0.1772. Then, Monte Carlo fine-tuning method is used to optimize the concrete mix ratio, so as to obtain the best mix ratio.

Simulating the Dynamics of Oscillating Differential Equations of Mass in Motion

This research explores the practical implementation and simulation of oscillatory differential equations concerning objects in motion. The methodology incorporates power series polynomials, ensuring adherence to the fundamental properties of these functions. The novel approach is applied to various oscillatory differential equations, encompassing harmonic motion, spring motion, dynamic mass motion, Betiss and Stiefel equations, and nonlinear differential equations. The results demonstrate computational reliability, showcasing enhanced accuracy and quicker convergence compared to currently examined methods. Dynamic motion, Genesio, Harmonic motion, Mass, Spring of motion

Elucidation of active components and target mechanism in Jinqiancao granules for the treatment of prostatitis and benign prostatic hyperplasia

Ethnopharmacological relevanceProstatitis and benign prostatic hyperplasia (BPH) are inflammations of the prostate gland, which surrounds the urethra in males. Jinqiancao granules are a traditional Chinese medicine used to treat kidney stones and this medicine consists of four herbs: Desmodium styracifolium (Osbeck) Merr., Pyrrosia calvata (Baker) Ching, Plantago asiatica L. and stigma of Zea mays L. Aim of the studyWe hypothesized that Jinqiancao granules could be a potential therapy for prostatitis and BPH, and this work aimed to elucidate active compounds in Jinqiancao granules and their target mechanisms for the potential treatment of the two diseases. Materials and methodsJinqiancao granules were commercially available and purchased. Database-driven data mining and networking were utilized to establish a general correlation between Jinqiancao granules and the two diseases above. Ultra-performance liquid chromatography-mass spectrometry was used for compound separation and characterization. The characterized compounds were evaluated on four G-protein coupled receptors (GPCRs: GPR35, muscarinic acetylcholine receptor M3, alpha-1A adrenergic receptor α1A and cannabinoid receptor CB2). A dynamic mass redistribution technique was applied to evaluate compounds on four GPCRs. Nitric acid (NO) inhibition was tested on the macrophage cell line RAW264.7. Molecular docking was conducted on GPR35-active compounds and GPR35 crystal structure. Statistical analysis using GEO datasets was conducted. ResultsSeventy compounds were isolated and twelve showed GPCR activity. Three compounds showed potent GPR35 agonistic activity (EC50 < 10 μM) and the GPR35 agonism action of PAL-21 (Scutellarein) was reported for the first time. Docking results revealed that the GPR35-targeting compounds interacted at the key residues for the agonist-initiated activation of GPR35. Five compounds showed weak antagonistic activity on M3, which was confirmed to be a disease target by statistical analysis. Seventeen compounds showed NO inhibitory activity. Several compounds showed multi-target properties. An experiment-based network reflected a pharmacological relationship between Jinqiancao granules and the two diseases. ConclusionsThis study identified active compounds in Jinqiancao granules that have synergistic mechanisms, contributing to anti-inflammatory effects. The findings provide scientific evidence for the potential use of Jinqiancao granules as a treatment for prostatitis and BPH.

Encapsulation of Fennel and Basil Essential Oils in β-Cyclodextrin for Novel Biopesticide Formulation.

β-cyclodextrin (β-CD) is a good host for the encapsulation of fennel and basil essential oils (FEO and BEO, respectively) and the formation of inclusion complexes (ICs) using the co-precipitation method. According to the results of the GC/MS analysis conducted in this study, monoterpenes and monoterpenoids were the dominant chemical groups in total FEO, while in BEO, these two groups occurred along with sesquiterpenes and sesquiterpenoids. The presence of dominant compounds from both EOs was validated using the FT-IR spectra of ICs, which indicated successful complexation. Analyses conducted using SPME/GC-MS showed the continuous emission of volatiles over 24 h from both ICs. Under SEM, particles of both ICs appeared to have a rectangular or rhomboid morphology and few aggregates. The insecticidal properties of EOs and ICs with β-CD were tested on the Colorado potato beetle (CPB) as a model pest. The inclusion complex of β-CD with FEO altered the developmental dynamic and body mass of the CPB. The initial increase in the proteolytic activity of CPB larvae fed with potato plants sprayed with ICs was not maintained for long, and the proteolytic efficacy of treated larvae remained in line with that of the control larvae. Future investigations will focus on manipulating the volume of EOs used and the treatment duration for optimal efficacy and potential application.