Separation Identification Research Articles

Rapid analysis of the chemical constituents in Qiangli Dingxuan tablets using ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry.

Qiangli Dingxuan (QLDX) tablet is a widely recognized traditional Chinese medicine formula that has been extensively used in China for decades to treat vertigo, tinnitus, and dizziness owing to its outstanding therapeutic outcomes. However, the complexity of the chemical components in this tablet makes it challenging to separate and identify these components. This study presented an effective and sensitive strategy for the rapid separation and simultaneous structural identification of QLDX tablet components using ultra-performance liquid chromatography with quadrupole time-of-flight tandem mass spectrometry and the UNIFI platform. Based on retention times, accurate masses, fragment ions, related literature, and authentic standards, 119 compounds were identified or tentatively characterized; these included 9 iridoids, 12 lignans, 21 phenylpropanoids, 27 flavonoids, 7 phthalides, and 43 others. Among them, 36 were confirmed using reference standards. The representative compounds with various chemical structures were studied by analyzing their fragmentation patterns and characteristic ions. In conclusion, this study established a rapid approach for characterizing the chemical constituents in QLDX tablet. The proposed approach provides a basis for qualitative analysis and quality control in the manufacturing process and is beneficial for advancing investigations into the efficacy and mechanism of action of this tablet.

An adaptive voltage control compensator for converters in DC microgrids under fault conditions

This paper proposes a voltage compensator for converters in multi-converter DC microgrids (MG), which enhances the DC-MG behavior under fault conditions. Among the four existing categories in the classification of the faults, this paper focuses on those faults that affect voltage generation of converter-based distributed generation units (DGUs). Such faults conceptually occur from the terminal voltage reference to actual voltage generated by DGUs. To compensate the adverse effects of the faults, an adaptive scheme is proposed, which considers the most general case of the faults by using the time-varying multiplicative and additive fault models. The proposed scheme benefits from an integrated structure, which does not require separate fault detection, isolation, and identification blocks. As an advantage of the proposed approach, it is designed independent of the primary and secondary controllers of DGUs, and hence its performance is not affected by using different primary and secondary controllers. The effectiveness of the proposed scheme is verified under various fault conditions and uncertainty in the system parameters. Using the proposed scheme, the results show that the performance of system under the fault condition is similar to that of the normal operation.

A novel recursive multivariate nonlinear time-series modeling method by using the coupling identification concept

This paper focuses on the modeling problem of complex time-series based on a type of multivariate nonlinear model with colored noise, i.e., the M-RBF-ARMA model. For the purpose of achieving highly accuracy modeling performance under colored noise interference, a novel recursive parameter identification algorithm for the M-RBF-ARMA model is investigated. In the framework of constructing several univariate system and noise sub-identification models using the mixed parameter characteristic of the model, three recursive sub-algorithms are presented by applying the coupling identification concept. Based on the singular value decomposition, a recursive update approach with numerical stability for covariance matrices is given. Then a three-stage coupled average extended recursive algorithm is proposed for the M-RBF-ARMA model by using the interactive strategy, which can implement the separable and interactive identification of different type of parameters. The effectiveness of the proposed algorithm is verified by an illustrative and a real multivariate nonlinear time-series.

Microplastic particles in river sediments and water of southwestern Nigeria: insights on the occurrence, seasonal distribution, composition, and source apportionment.

Microplastics (MPs) are globally recognized as an emerging environmental threat, particularly in the aquatic environment. This study presents baseline data on the occurrence and distribution of MPs in sediments and surface water of major rivers in southwestern Nigeria. Microplastics were extracted by density separation and polymer identification using Fourier transformed infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR). The abundance of MPs in surface sediment and water samples across all locations ranged from 12.82 to 22.90 particle/kg dw and 6.71 to 17.12 particle/L during the dry season and 5.69 to 14.38 particle/kg dw and 12.41 to 22.73 particle/L during the wet season, respectively. On average, fiber constituted the highest percentage of MP in sediments (71%) and water (67%) while foam accounted for the lowest values of 0.6% and 1.7%, respectively. Polypropylene(PP) and polyethylene (PE) were the main MPs across all locations based on Fourier transform infrared spectroscopy (FTIR). MPs of size < 1mm were the most abundant (≥ 55%) on average in both water and sediments. The study identified run-off from human activities and industrial wastewater as potential sources of MP exposure based on positive matrix factorization. The study suggests assessing the impact of different land-use activities on MPs occurrence and distribution in addition to quantifying MPs in seafood as a way forward in food safety management systems for further studies. This study confirmed the occurrence and widespread distribution of MPs in surface water and sediments and provides a database on MP pollution in Nigeria.

Selective detection of ionic liquid fluorescence probes for visual colorimetry of different metal ions

At present, the fast distinction of different metal ions in pure water media is not only a great challenge, but also drives the protection of water quality in environmental water bodies. In this paper, a novel ionic liquid fluorescent probe Glycolic Acid-L-Arginine (GA-L-Arg) was rationally created and designed through an in-depth study of ionic liquids. It is also used as an innovative multi-ion fluorescent probe for colorimetric detection and separate identification of Fe3+ and Co2+ in aqueous solutions of various metal ions. GA-L-Arg has excellent water solubility due to the strong hydrophilicity of Glycolic Acid and L-Arginine. The probe showed high sensitivity, extremely significant selectivity, and great pH stability for Fe3+ and Co2+ in pure water. The GA-L-Arg structure and the mechanism of Fe3+ and Co2+ detection were analyzed by infrared spectroscopic characterization and quantum chemical calculations. More importantly, the distinct colorimetric partitioning of Fe3+ and Co2+ was performed by the unique extraction of Fe3+ in the presence of the fluorescent probe and buffer solution.

Short disordered termini and proline-rich domain are major regulators of UBQLN1/2/4 phase separation

Highly homologous ubiquitin-binding shuttle proteins UBQLN1, UBQLN2, and UBQLN4 differ in both their specific protein quality control functions and their propensities to localize to stress-induced condensates, cellular aggregates, and aggresomes. We previously showed that UBQLN2 phase separates in vitro, and that the phase separation propensities of UBQLN2 deletion constructs correlate with their ability to form condensates in cells. Here, we demonstrated that full-length UBQLN1, UBQLN2, and UBQLN4 exhibit distinct phase behaviors in vitro. Strikingly, UBQLN4 phase separates at a much lower saturation concentration than UBQLN1. However, neither UBQLN1 nor UBQLN4 phase separates with a strong temperature dependence, unlike UBQLN2. We determined that the temperature-dependent phase behavior of UBQLN2 stems from its unique proline-rich region, which is absent in the other UBQLNs. We found that the short N-terminal disordered regions of UBQLN1, UBQLN2, and UBQLN4 inhibit UBQLN phase separation via electrostatics interactions. Charge variants of the N-terminal regions exhibit altered phase behaviors. Consistent with the sensitivity of UBQLN phase separation to the composition of the N-terminal regions, epitope tags placed on the N-termini of the UBQLNs tune phase separation. Overall, our in vitro results have important implications for studies of UBQLNs in cells, including the identification of phase separation as a potential mechanism to distinguish the cellular roles of UBQLNs and the need to apply caution when using epitope tags to prevent experimental artifacts.

Enhancement of Seismic Phase Identification Using Polarization Filtering and Array Analysis

ABSTRACT Seismic arrays play a crucial role in identifying weak signals in the seismic wavefield based on their expected slowness and backazimuth values. However, their resolution power is limited when studying phases with similar horizontal slownesses and arrival times, such as receiver-side or source-side reverberations and converted phases. Therefore, we investigate the benefit of applying polarization filtering to three-component seismograms before stacking to remove undesired signals and increase the signal-to-noise ratio of the array. Customized polarization filters enable more sophisticated wavefield separation and robust phase identification on vespagrams. However, selecting the suitable polarization filter requires a balance between noise reduction and the preservation of desired signals. We find that degree-of-polarization filters generally excel in suppressing incoherent noise. On the other hand, some filters, for example, based solely on ellipticity, do not yield notable enhancements for body waves and may even produce adverse effects, specifically for phases that arrive late in the seismogram. We demonstrate these findings using data recorded by AlpArray and surrounding permanent stations.

Hydroxylated transformation products obtained after UV irradiation of the current-use brominated flame retardants hexabromobenzene, pentabromotoluene, and pentabromoethylbenzene

Hexabromobenzene (HBB), pentabromotoluene (PBT), and pentabromoethylbenzene (PBEB) are current-use brominated flame retardants (cuBFRs) which have been repeatedly detected in environmental samples. Since information on hydroxylated transformation products (OH-TPs) was scarcely available, the three polybrominated compounds were UV irradiated for 10 min in benzotrifluoride. Fractionation on silica gel enabled the separate collection and identification of OH-TPs. For more insights, aliquots of the separated OH-TPs were UV irradiated for another 50 min (60 min total UV irradiation time). The present investigation of polar UV irradiation products of HBB, PBT, and PBEB was successful in each case. Altogether, eight bromophenols were detected in the case of HBB (three Br3-, four Br4-, and one Br5-isomer), and nine OH-TPs were observed in the case of PBT/PBEB (six Br3- and three Br4-congeners). In either case, Br➔OH exchange was more relevant than H➔OH exchange. Also, such exchange was most relevant in meta- and ortho-positions. As a further point, and in agreement with other studies, the transformation rate decreased with decreasing degree of bromination. UV irradiation of HBB additionally resulted in the formation of tri- and tetrabrominated dihydroxylated compounds (brominated diphenols) that were subsequently identified. These dihydroxylated transformation products were found to be more stable than OH-TPs.

Pseudomonas chlororaphis L5 and Enterobacter asburiae L95 biocontrol Dickeya soft rot diseases by quenching virulence factor modulating quorum sensing signal.

Virulence factor modulating (VFM) is a quorum sensing (QS) signal shared by and specific to Dickeya bacteria, regulating the production of plant cell wall degrading enzymes (PCWDEs) and virulence of Dickeya. High polarity and trace of VFM signal increase the difficulty of signal separation and structure identification, and thus limit the development of quorum quenching strategy to biocontrol bacterial soft rot diseases caused by Dickeya. In order to high-throughput screen VFM quenching bacteria, a vfmE-gfp biosensor VR2 (VFM Reporter) sensitive to VFM signal was first constructed. Subsequently, two bacterial strains with high quenching efficiency were screened out by fluorescence intensity measurement and identified as Pseudomonas chlororaphis L5 and Enterobacter asburiae L95 using multilocus sequence analysis (MLSA). L5 and L95 supernatants reduced the expression of vfm genes, and both strains also decreased the production of PCWDEs of D. zeae MS2 and significantly reduced the virulence of D. oryzae EC1 on rice seedlings, D. zeae MS2 on banana seedlings, D. dadantii 3937 on potato and D. fangzhongdai CL3 on taro. Findings in this study provide a method to high-throughput screen VFM quenching bacteria and characterize novel functions of P. chlororaphis and E. asburiae in biocontrolling plant diseases through quenching VFM QS signal.

Research progress on structure, structure-activity relationship, and biological activity of Aconiti Lateralis Radix Praeparata polysaccharides

Aconiti Lateralis Radix Praeparata polysaccharides(AP) are a class of bioactive macromolecules extracted from the herbs of Aconiti Lateralis Radix Praeparata and its various processed products. Since the AP was first separated in 1986, its pharmacological effects include immune regulation, anti-tumor, anti-depression, organ protection, hypoglycemia, and anti-inflammatory had been found. In recent years, with the development of polysaccharide extraction, separation, and structure identification technologies, more than 20 kinds of AP have been separated from Aconiti Lateralis Radix Praeparata and its processed products, and they have ob-vious differences in relative molecular weight, monosaccharide composition, glycosidic bond, structural characteristics, and biological activities. In particular, AP may be dissolved, degraded, or allosteric under the complex processing environment of fermentation, soaking, cooking, etc., leading to the diversified structure of AP, which provides a possibility for further understanding of the structure-activity relationship of AP. Therefore, this study systematically reviewed the research progress on the structure and structure-activity relationship of AP, summarized the biological activity and potential action mechanism of AP, and discussed the technical challenges in the development and application of AP, so as to promote the quality control and further development and utilization of AP.

Flow reversal for hybrid nanofluid with heat generation and slip effect in Darcy porous medium: The stability analysis

This investigation focuses on the flow reversal and separation of hybrid nanofluid, with heat generation and first-order velocity slip, in a Darcy porous medium. The Choi–Eastman nanofluid model is used to formulate the hybrid nanofluid mathematical model. Suitable similarity transformations convert partial differential equations into a system of ordinary differential equations. The resultant systems are numerically solved by implementing the shooting approach. Multiple solutions are found for this current problem, and intriguingly, the velocity and temperature profiles of these two solution branches exhibit opposing characteristics. In conclusion, conducting a stability study on these two alternative solutions is worthwhile to determine which solution is more realistic and stable. The temporal stability test reveals that only the first solution is stable or physically valid. The important outcomes of this study, based on the stable solutions, are as follows: (i) the hybrid nanofluid’s Nusselt number, skin friction, and velocity rise when the inclined magnetic parameter rises, (ii) the value of the smallest eigenvalue increases with higher values of the inclined magnetic parameter, and (iii) the thickness of momentum and thermal boundary layers is thinner for the first solution than the second solution. Additionally, the identification of flow separation and reversal points is valuable for aerospace technology, following the Prandtl theory. Finally, this study provides streamlined patterns to enhance the understanding of fluid flow behavior.

RP-HPLC Separation and 1H NMR Identification of a Yellow Fluorescent Compound-Riboflavin (Vitamin B2)-Produced by the Yeast Hyphopichia wangnamkhiaoensis.

The yeast Hyphopichia wangnamkhiaoensis excretes a brilliant yellow fluorescent compound into its growth culture. In this study, we isolated and identified this compound using reverse-phase high-performance liquid chromatography-diode array detector (RP-HPLC-DAD) as well as 1H NMR and UV-Vis spectroscopy. Two of the three RP-HPLC-DAD methods used successfully separated the fluorescent compound and involved (1) a double separation step with isocratic flow elution, first on a C18 column and later on a cyano column, and (2) a separation with a linear gradient elution on a phenyl column. The wavelengths of maximum absorption of the fluorescent compound-containing HPLC fractions (~224, 268, 372, and 446 nm) are in good agreement with those exhibited by flavins. The 1H NMR spectra revealed methyl (δ 2.30 and 2.40) and aromatic proton (δ 7.79 and 7.77) signals of riboflavin. The 1H NMR spectra of the samples spiked with riboflavin confirmed that the brilliant yellow fluorescent compound is riboflavin. The maximum excitation and emission wavelengths of the fluorescent compound were 448 and 528 nm, respectively, which are identical to those of riboflavin.

Market Structure, Oligopsony Power, and Productivity

I examine the effects of oligopsony power on allocative efficiency and income redistribution by studying a size regulation in the Chinese tobacco industry that led to ownership consolidation. I show that separate identification of input price markdowns, goods price markups, and productivity is challenging when a subset of inputs is nonsubstitutable, which often holds for materials, and construct and estimate a model to overcome this challenge. I find that the regulation increased input price markdowns by 37 percent on average. This increase in oligopsony power led to a decline in allocative efficiency and redistributed income away from rural households. (JEL D24, D31, G32, G34, L13, L66, P31)

PredLLPS_PSSM: a novel predictor for liquid-liquid protein separation identification based on evolutionary information and a deep neural network.

The formation of biomolecular condensates by liquid-liquid phase separation (LLPS) has become a universal mechanism for spatiotemporal coordination of biological activities in cells and has been widely observed to directly regulate the key cellular processes involved in cancer cell pathology. However, the complexity of protein sequences and the diversity of conformations are inherently disordered, which poses great challenges for LLPS protein calculations and experimental research. Herein, we proposed a novel predictor named PredLLPS_PSSM for LLPS protein identification based only on sequence evolution information. Because finding real and reliable samples is the cornerstone of building predictors, we collected anew and collated the LLPS proteins from the latest versions of three databases. By comparing the performance of the position-specific score matrix (PSSM) and word embedding, PredLLPS_PSSM combined PSSM-based information and two deep learning frameworks. Independent tests using three existing independent test datasets and two newly constructed independent test datasets demonstrated the superiority of PredLLPS_PSSM compared with state-of-the-art methods. Furthermore, we tested PredLLPS_PSSM on nine experimentally identified LLPS proteins from three insects that were not included in any of the databases. In addition, the powerful Shapley Additive exPlanation algorithm and heatmap were applied to find the most critical amino acids relevant to LLPS.

Unraveling gluon jet quenching through [formula omitted] production in heavy-ion collisions

Jet quenching has long been regarded as one of the key signatures for the formation of quark-gluon plasma in heavy-ion collisions. Despite significant efforts, the separate identification of quark and gluon jet quenching has remained as a challenge. Here we show that J/ψ in high transverse momentum (pT) region provides a uniquely sensitive probe of in-medium gluon energy loss since its production at high pT is particularly dominated by gluon fragmentation. Such gluon-dominance is first demonstrated for the baseline of proton-proton collisions within the framework of leading power non-relativistic quantum chromodynamics factorization formalism. We then use the linear Boltzmann transport model combined with hydrodynamics for the simulation of jet-medium interaction in nucleus-nucleus collisions. The satisfactory description of experimental data on both nuclear modification factor RAA and elliptic flow v2 reveals, for the first time, that the gluon jet quenching is the driving force for high pTJ/ψ suppression. This novel finding is further confirmed by the data-driven Bayesian analyses of relevant experimental measurements, from which we also obtain the first quantitative extraction of the gluon energy loss distribution in the quark-gluon plasma.

Machine learning-driven 3D plasmonic cellulose sensor for in situ rapid SERS detection of bisphenol compounds in water sample

Rapid component separation and accurate identification of bisphenols compounds (BPs) in real water sample remain an attractive challenge due to the trace amounts and structural similarities of BPs, and complexity of real samples. Here, we designed and synthesized chemically modified cellulose p-toluenesulfonate (CTSA) to encapsulate octadecylamine-modified gold nanoparticles (Au-ODA), obtaining 3D plasmonic cellulose (Au@CTSA). Simultaneously, by virtue of the high surface area in the 3D network of CTSA and the solvent volatile deposition, BPs in water were in situ extracted and concentrated in Au@CTSA microspheres. Since the 3D network of Au@CTSA supports the formation of “hotspots”, the number of “hotspots” available is greatly improved, enabling excellent SERS detection of BPs. Based on the collected SERS spectra, machine learning was utilized to analyze the overall profile of BPs, which eliminated the subjective judgment of the concentration by the Au@CTSA sensor using a single characteristic peak. In this way, the accuracy of identification of BPs was significantly improved. The machine learning-driven Au@CTSA sensor realized the detection of traces bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) in water sample, pushing quantitative detection of different concentrations of BPs and contributing facile indicators for water quality monitoring.

Thermodynamic Theory of Phase Separation in Nonstoichiometric Si Oxide Films Induced by High-Temperature Anneals

High-temperature anneals of nonstoichiometric Si oxide (SiOx, x &lt; 2) films induce phase separation in them, with the formation of composite structures containing amorphous or crystalline Si nanoinclusions embedded in the Si oxide matrix. In this paper, a thermodynamic theory of the phase separation process in SiOx films is proposed. The theory is based on the thermodynamic models addressing various aspects of this process which we previously developed. A review of these models is provided, including: (i) the derivation of the expressions for the Gibbs free energy of Si oxides and Si/Si oxide systems, (ii) the identification of the phase separation driving forces and counteracting mechanisms, and (iii) the crystallization behavior of amorphous Si nanoinclusions in the Si oxide matrix. A general description of the phase separation process is presented. A number of characteristic features of the nano-Si/Si oxide composites formed by SiOx decomposition, such as the local separation of Si nanoinclusions surrounded by the Si oxide matrix; the dependence of the amount of separated Si and the equilibrium matrix composition on the initial Si oxide stoichiometry and annealing temperature; and the correlation of the presence of amorphous and crystalline Si nanoinclusions with the presence of SiOx (x &lt; 2) and SiO2 phase, respectively, in the Si oxide matrix, are explained.

Histopathological characterisation of trunk-dominant canine pemphigus foliaceus, and comparison with classic facial and insecticide-triggered forms.

While the clinical features were described recently, the histopathological characterisation of trunk-dominant canine pemphigus foliaceus (PF) is lacking, and whether it differs from classic facial or insecticide-triggered PF is unknown. This study describes the histopathological findings of trunk-dominant PF, and compares the results to classic facial and insecticide-triggered PF. Skin biopsies from 103 dogs with clinically characterised trunk-dominant (n = 33), classic facial (n = 26) and insecticide-triggered PF (n = 44) were included. Histological sections, randomised and blinded, were scored for over 50 morphological parameters of pustules, epidermis, dermis, adnexa and crusts. Intact pustule area and width were measured by digital microscopy. In trunk-dominant PF, 77 intact pustules were predominantly subcorneal (0.0019-1.940 mm2 area, 0.0470-4.2532 mm wide), and contained from one to over 100 acantholytic keratinocytes. Pustules had boat acantholytic cells, corneocytes, perinuclear eosinophilic rings, neutrophil rosettes, acantholytic cell necrosis, rafts, cling-ons and/or eosinophils. Peripustular epidermal spongiosis, necrosis and lymphocyte exocytosis occurred, as did follicular pustules. Mixed dermal inflammation often contained eosinophils. Trunk-dominant PF did not differ from the other PF groups except for few parameters, such as having fewer rafts (p = 0.003). Additional autoimmune inflammatory patterns occurred in all PF groups. Trunk-dominant PF and other canine PF variants are histologically similar, which indicates shared pathomechanisms. The identification of common boat acantholytic cells and corneocyte separation has implications for the mechanisms of acantholysis. The diversity of histopathological and polyautoimmunity features support complicated immune mechanisms. Finally, results indicate that diagnostic biopsies cannot differentiate between these PF variants in dogs.

A sustainable emulsion for separation and Raman identification of microplastics and nanoplastics

The extensive occurrence of small plastic particles in the environment and our foods, and the resulting hazardous effects to nature and people have become an issue of increasing concern worldwide. The currently established approaches and tools for the elimination of the emerging contaminants, in particular micro- and nano-scale plastic particles, from environmental and food matrices have been often limited to the use of poorly sustainable materials and complicated preparation/operation. Here we show a conceptually new strategy for the removal of microplastics and nanoplastics using an olive oil-based emulsion. By emulsifying naturally occurring olive oil, water and emulsifiers at an oil-to-water ratio of 5:12, a stable O/W emulsion can be produced by mechanical agitation, which can adsorb onto microplastics and nanoplastics via hydrophobic interactions. Upon demulsification, interestingly, the tiny plastic particles can be enriched at an efficiency up to ∼87%, attributable to the affinity-driven encapsulation of the plastics by the merged oil phase. We further demonstrate the emulsion affords the removal of tiny plastic particles from seawater, tea leaves, soil and toothpaste supernatants at considerably low concentration levels in efficiencies of 75%, 80%, 83% and 82%, respectively, while preserving uncompromised performance. The identification of the extracted plastics has been achieved using Raman spectroscopy, which has implications in health risk assessment and clarification of the contamination route. Given the high removal efficiency, green feature and generality of the emulsion coupled with Raman fingerprints, sustainable materials for the depollution of microplastics and nanoplastics are within reach.

Parametric identification of ultrasonic guided wave aliasing modes based on dispersion effect

Ultrasonic guided wave is suitable for non-destructive testing of engineering components due to its advantages such as slow energy attenuation, large detection range, and strong defect recognition ability. However, because of their multi-mode and dispersion characteristics, it is difficult to directly use their echo signals to locate defect. To address this problem, this paper proposed an adaptive modes separation and parameterized identification (AMS-PI) model for guided wave aliasing modes. Firstly, based on the differences in vibration characteristics between different modes, a fixed frequency decomposition model for the guided wave signals was constructed, achieving the separation of aliasing modes. Secondly, based on the difference in dispersion characteristics between different guided wave modes, a parameterized identification model for guided wave modes was constructed. Finally, the effectiveness of the proposed model was demonstrated through weld defect localization experiments.