Accurate Separation Research Articles

The molecular mechanism of temperature-dependent phase separation of heat shock factor 1.

Heat shock factor 1 (HSF1) is the critical orchestrator of cell responses to heat shock, and its dysfunction is linked to various diseases. HSF1 undergoes phase separation upon heat shock, and its activity is regulated by post-translational modifications (PTMs). The molecular details underlying HSF1 phase separation, temperature sensing and PTM regulation remain poorly understood. Here, we discovered that HSF1 exhibits temperature-dependent phase separation with a lower critical solution temperature behavior, providing a new conceptual mechanism accounting for HSF1 activation. We revealed the residue-level molecular details of the interactions driving the phase separation of wild-type HSF1 and its distinct PTM patterns at various temperatures. The mapped interfaces were validated experimentally and accounted for the reported HSF1 functions. Importantly, the molecular grammar of temperature-dependent HSF1 phase separation is species specific and physiologically relevant. These findings delineate a chemical code that integrates accurate phase separation with physiological body temperature control in animals.

The cohesin complex: structure and principles of interaction with dna

Accurate duplication and separation of long linear genomic DNA molecules is associated with a number of purely mechanical problems. SMC complexes are key components of the cellular machinery that ensures decatenation of sister chromosomes and compaction of genomic DNA during division. Cohesin, one of the essential eukaryotic SMC complexes, has a typical ring structure with intersubunit pore through which DNA molecules can be threaded. The capacity of cohesin for such topological entrapment of DNA is crucial for the phenomenon of post-replicative association of sister chromatids better known as cohesion. Recently, it became apparent that cohesin and other SMC complexes are in fact motor proteins with a very peculiar movement pattern leading to the formation of DNA loops. This specific process was called loop extrusion. Extrusion underlies multiple cohesin’s functions beyond cohesion, but the molecular mechanism of the process remains a mystery. In this review, we have summarized data on the molecular architecture of cohesin, the influence of ATP hydrolysis cycle on this architecture, and the known modes of cohesin–DNA interactions. Many of the seemingly disparate facts presented here will probably be incorporated in a unified mechanistic model of loop extrusion in a not so far future.

Influence of inlet velocity on the separation performance of a combined hydrocyclone

Hydrocyclone separation exploits centrifugal force to differentiate particles based on their sizes and densities, yet challenges arise when small, dense particles and large, low-density ones settle at similar velocities. To address this, we propose a two-stage combined hydrocyclone for accurate separation. Using numerical simulations, we examine the internal flow field and performance of this system. Our findings reveal that the primary hydrocyclone achieves size-dependent classification, while the secondary one achieves density-dependent sorting. Increasing inlet velocity enhances separation efficiency and accuracy by improving flow field dynamics, albeit at the cost of increased energy consumption and material residence time. Thus, optimizing inlet velocity is vital for maximizing the separation performance and operational efficacy of the combined hydrocyclones.

A 3D printed device for vibration-assisted separation of different-stage mosquito larvae

Mosquitoes, as major vectors of dangerous diseases, demand effective control measures for public health. Larvicides, while offering a potential solution, can exhibit varying effects on different mosquito species and developmental stages during efficacy studies. Standardizing mosquito developmental stages and ensuring optimal, synchronized development rates of various larval stages are crucial for larvicidal experiments and maximizing pupal production. Manual separation of different stages of larvae is labor intensive, time consuming and error prone. Therefore, this study aimed to investigate the use of a stereolithography 3D-printed device for the separation of mosquito larvae. This device is designed to have three modules to collect different larval stages based on their radial size differences. Each module of the device was equipped with small vibration motors to enable vibration-assisted filtration to prevent clogging. The accuracy of the larvae separation device was studied by repeated experiments and collected samples were analyzed under an optical microscope. The 3D-printed device was demonstrated to be orders of magnitude faster and more accurate compared to manual separation process. A larvicidal bioassay was also designed to investigate larvicidal assay impact on the survival of collected L3 and L4 specimens. Overall, it was shown that the presented device carries an important potential for rapid and accurate separation of different size larvae for larvicidal studies.

Direct Current Ripple Component Detection Algorithm Based on Improved Variational Mode Decomposition

Background: The development of smart grids requires energy meters that enable accurate measurements. Objective: In response to the current issue where Direct Current (DC) energy meters only measure DC components and not ripple components, we propose to design a novel algorithm to achieve accurate separation of DC components and ripple components in DC signals. Methodology: This patent proposes a precise detection algorithm for ripple components. The algorithm is based on the Wavelet Decomposition combined with Flamingo Search Algorithm-Variational Mode Decomposition (WD-FSA-VMD). Firstly, we analyze the ripple characteristics in the DC signal and use the Wavelet Decomposition (WD) algorithm to separate the ripple components in the DC signal accurately. Secondly, we utilize the Flamingo Search Algorithm (FSA) to optimize the number of modal decompositions and the penalty factor in the Variational Mode Decomposition (VMD). This allows us to accurately extract the ripple components. Finally, we conducted simulation experiments comparing the improved algorithm with the original algorithm. Results: The experimental results indicate that the signal correlation coefficient obtained by the WDFSA- VMD algorithm increases by 82.64% compared to traditional VMD, and it increases by 16.72% compared to the combined Wavelet Decomposition with Whale Optimization Algorithm-Variational Mode De-composition (WD-WOA-VMD). Conclusion: The improved algorithm we proposed has good adaptability and separation performance. It is prospective for the new algorithm to provide a valuable reference to ripple detection technology.

Research and Field Application on Extreme Subdivision Water Injection Technology for Low Permeability Reservoirs

Abstract Low permeability Block A is about to enter the development phase of extremely high water cut. Due to the low overall recovery degree and residual oil scattered sporadically, the efficient development meets more difficulty and conventional residual oil analysis and adjustment methods cannot fulfil the current needs of precise development. To enhance the reservoir utilization degree, we conduct extremely concise zonal water injection experiment from three aspects: sand body description, policies establishment, and proper technique application. In terms of sand body description, four types of sand-body distribution patterns were summarized through fine characterization of vertical, planar, and spatial single sand bodies, clarifying the origin and potential distribution of residual oil. In terms of development policy, numerical simulation and reservoir engineering methods have been comprehensively applied to determine the subdivision combination of injection layers and reasonable water allocation boundaries, and subdivision principles have been established, considering single septation to thin and thick layer with combining enhancing -controlling. In terms of supporting technology, we have studied the small space subdivision process of small compartments, optimized the testing and adjustment methods, and finally achieved accurate separation, strict clamping, and accurate matching of water injection layers. Through the research and practice, it realized the finest septation of the water injection to extremely enhance the subdivision degree and the efficiency of the injection. It also have strengthened the utilization of thin and poor layers and effectively controlled the decline.

Mixed dimensional assembly of biodegradable and antifouling wood-based covalent organic framework composite membranes for rapid and efficient dye/salt separation

Manipulating materials of different dimensions into heterogeneous nanofiltration membranes with unique physicochemical properties and molecular sieving channels provides an effective way for accurate and fast molecular separation. Here we introduce a heterogeneous structure hybrid connection strategy to fabricate biodegradable wood-based covalent organic framework (COF) composite membranes. As a proof of concept, 3D Picea jezoensis (Siebold & Zucc.) Carrière was selected as the substrate of the membrane and in situ growth of 2D iCOF selective layers. Effective modulation of iCOF layers by 1D sulfonated polyaryletherketone (SPEEK-Na) using the “needle and thread” method. The rearrangement of the above multidimensional materials formed charge-regulated properties of laminar nano-channels and smooth hydrophilic contact area, thereby endowing specific molecular transport pathways and sieving capability for efficient dye/salt separation under ultra-low pressure of 0.5 bar. The wood-based heterostructured membranes exhibited high dye rejection (>97 %), low salt rejection (<10 %), and high permeance (172.34 L m−2 h−1 bar−1), which is superior to many reported dye/salt separation membrane materials. In addition, the system exhibited a certain degree of operational stability, good antifouling, and soil biodegradability. Overall, this work enables the design and fabrication of heterostructured separation membranes to be obtained from nature and used in nature, resulting in efficient and sustainable water purification applications.

Chromatographic Comparison of Commercially Available Columns for Liquid Chromatography in Polar Pesticide Detection and Quantification Using a Score-Based Methodology.

The detection and quantification of polar pesticides in liquid chromatography coupled with mass spectrometry present significant analytical challenges. This study compares the performance of three LC columns (Hypercarb™, Raptor Polar X™, and Anionic Polar Pesticide™) in separating and quantifying eleven polar pesticides in chicken eggs using a score-based methodology. Analytes include glyphosate, its metabolites, and other high-polarity pesticides like Ethephon, Glufosinate, and Fosetyl aluminum, included in the EU's official control plan. Polar pesticides, characterized by high polarity and hydrophilicity, lead to analytical issues such as poor retention and unconventional peak shapes with traditional reversed-phase methods. Their weak interaction with hydrophobic stationary phases complicates separation, necessitating specific stationary phases to enhance retention and selectivity. This study evaluates these columns' efficacy in complex matrices like chicken eggs and other food samples. Chromatographic separation was performed using a UPLC system coupled with a Q-TOF mass spectrometer; extraction and purification involved freeze-out, centrifugation, and filtration steps. The study highlights the critical role of column selection in achieving accurate and reliable separation and quantification of highly polar analytes in matrices of animal origin, offering in the meantime an easy-to-apply methodology of selection for the right determination of the best chromatographic column for different purposes.

Robust analytical method for the enantiomeric separation of lurasidone hydrochloride: Integrating analytical quality by design and green chemistry principles

Schizophrenia, affecting approximately 1% of the global population, necessitates effective treatments like Lurasidone (LUR). However, the accurate separation of LUR from its enantiomeric impurities remains a significant challenge in pharmaceutical analysis. This study addresses this issue by developing and validating an optimized HPLC method for the simultaneous determination of LUR and its enantiomeric impurity using Analytical Quality by Design (AQbD) principles. The separation was achieved on a Chiralcel OD-H column with isocratic elution employing a hexane-ethanol mixture (92:8, v/v) at a flow rate of 0.9 mL/min, UV detection at 215 nm, and a column temperature of 32 °C. The method was validated using accuracy profiles. Environmental sustainability was assessed using various Green Analytical Chemistry (GAC) metrics, demonstrating favorable greenness attributes. This methodological framework not only enhances pharmaceutical quality control but also promotes sustainability in analytical practices, supporting its application in drug manufacturing and regulatory compliance.

Polyhedral oligomeric silsesquioxane-modulated mesoporous amorphous bimetallic organic frameworks for the efficient isolation of immunoglobulin G

The efficient and accurate separation of immunoglobulin G (IgG) plays a vital role for disease diagnosis and therapy, but it is always hampered by the huge geometric size and complex structure of IgG. In this work, an amorphous Fe/Co bimetallic organic framework (denoted as PMOF-Fe/Co) is fabricated for IgG separation, with octa-carboxyl polyhedral oligomeric silsesquioxane (OCPOSS) as modulator for the first time. Benefiting from the rigid nanostructure and competitive coordination of OCPOSS, the aperture of PMOF-Fe/Co is enlarged to ∼20 nm along with the generation of enormous structural defects, which enables the accommodation of protein species with high molecular weights and large sizes. OCPOSS is also found exerting a positive impact on mediating the specific recognition and adsorption ability of PMOF-Fe/Co towards IgG through metal affinity, hydrophilic and hydrophobic interactions. Consequently, the multimode and multivalent affinity of PMOF-Fe/Co gives rise to an extraordinary adsorption capacity (2691.7 mg g−1) and satisfactory practical application performance. This study is convinced to provide a simple avenue for the efficient separation of specific large-sized proteins, as well as the engineering of abiotic affinity reagents with compositional and architectural complexity.

Three‐step integrated process for isolation and purification of impurities in drug substance by recycling chromatography

AbstractThis work reported the application of a twin‐column recycling chromatography system for the separation of three minor impurities in crude aloe‐emodin. The whole process went through three steps, each using a different mobile phase to separate corresponding impurity, which were integrated and automatically operated in a single device. Despite these impurities peaked closely in high‐performance liquid chromatography, they were successfully purified to a content exceeding 97%. In addition, the lab‐scale separation could reach the yields at the mg‐level. The high efficacy should be mainly attributed to the introduction of a small step solvent gradient between the upstream and downstream columns, which helped to counterbalance the band broadening. This report suggested that such an automated chromatographic system could provide fast and accurate separation of multiple impurities, allow the process of high‐throughput samples, and reduce the time required for purification and recovery of minor impurities in drugs.

Addressing Challenges of Membrane Clogging in AF4-UV-ICPMS Analysis for Size Determination of Trace Elements in Acidic, Organic-Rich Peat Bog Waters.

The analysis of colloid-associated trace elements (TEs) in acidic, organic-rich waters (pH 3.8-5.8) using AF4-UV-ICPMS often necessitates the use of neutral or weakly alkaline carriers (pH 7-8.6). Employing acidic mobile phases has been deemed impractical due to the substantial sorption of colloids onto a 0.3 kDa polyethersulfone (PES) membrane and greatly reduced separation performance. This has greatly restricted the determination of potentially bioavailable forms of TEs (i.e., < 1 kDa) in acidic, organic-rich waters. To address this issue, porewaters from Sphagnum moss and peat were investigated. Membrane clogging was more pronounced in peat porewaters, where a higher deposition rate of dissolved organic matter onto the membrane was observed compared to that in moss waters. This adsorption is driven by membrane-colloid interactions, with colloids in peat porewaters exhibiting weaker electrostatic repulsion due to their higher positive ζ-potentials. Considering the actual pore size and clogging tolerance of the membrane, it is advisable to employ a 5 kDa PES membrane for peat porewaters, while a 1 kDa PES membrane suits moss waters better. Employing the optimal method enables the separation of TEs within the 0.5-20 kDa size range. Operating within a metal-free, ultraclean laboratory, TEs are detectable at the ng·L-1 level. By enabling precise and accurate separation of dissolved TEs into their size species in these peat bog waters at an appropriate pH, this method addresses diverse size profiles. This information is crucial for comprehending the chemical forms, transformations, mobility, and potential bioavailability of TEs in peat bogs.

Rapid determination of chlorate and perchlorate in tea by ion exchange chromatography-tandem mass spectrometry

Ion exchange chromatography-tandem mass spectrometry (IEC-MS/MS) has recently become the preferred method for detecting ionic substances in tea. In this study, an IEC-MS/MS method was developed for the rapid determination of chlorate and perchlorate residues in tea samples. The optimal sample extraction process, pretreatment column, and chromatographic and mass spectrometric conditions were systematically investigated. In the optimal process, the tea samples were ultrasonically extracted with methanol-water (13∶7, v/v), and a PRiME HLB SPE column was used to purify the sample extract. An AceChrom Hybri-A IEC column (150 mm×2.1 mm, 5.0 μm) was used for separation, and 100 mmol/L ammonium acetate-acetonitrile (40∶60, v/v) was used as the mobile phase for isocratic elution. The flow rate was 0.3 mL/min, the column temperature was 40 ℃, and the injection volume was 5.0 μL. The mass spectrometric data were collected in negative electrospray ionization mode combined with multiple reaction monitoring (MRM) mode to achieve the rapid and accurate separation and qualitative analysis of the desired chemical components. Quantification was performed using the internal standard (IS) method. The measurement results showed a good linear relationship when the mass concentrations of chlorate and perchlorate were between 2.00-200 and 1.00-100 μg/L, respectively, with correlation coefficients (r2) greater than 0.9990. The average recoveries of chlorate and perchlorate at three spiked levels of low, medium, and high ranged from 88.54% to 97.25% with relative standard deviations (RSDs, n=7) of 3.2%-5.2%. The limits of detection for chlorate and perchlorate were 12.0 and 8.0 μg/kg, respectively, while the limits of quantification were 40.0 and 26.6 μg/kg, respectively. The results of tests conducted to assess the linearity, specificity, accuracy, precision, and applicability of the method to the analysis of chlorate and perchlorate in 15 tea samples collected from a local market demonstrated its validity for the routine analysis of tea samples. The proposed method is simple, rapid, sensitive, and accurate, and can meet requirements for the rapid screening and quantitative analysis of residual trace chlorate and perchlorate in large quantities of tea samples.

Explainable Feature Engineering for Multi-Modal Tissue State Monitoring Based on Impedance Spectroscopy.

One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features.

Fractional synchrosqueezing transform for enhanced multicomponent signal separation

The precise separation of multicomponent signals encounters numerous challenges due to the complexity of signals and widespread interference. Synchrosqueezing Transform (SST) is one of the important technologies for improving the accurate separation of multicomponent signals, but it faces challenges in terms of the difficulty and effectiveness of squeezing. This paper introduces a multicomponent signal separation method based on innovative Fractional Synchrosqueezing Transform (FrSST). FrSST rearranges along the fractional frequency axis, improving the accuracy of time–frequency ridges and, consequently, enhancing the precision of multicomponent signal separation. In the signal reconstruction process, chirp multiplication and energy rearrangement compensate for chirp bases’ effects, boosting energy concentration and reconstruction potential. Utilizing improved ridges from FrSST ensures effective signal reconstruction. Simulation comparisons demonstrate that, with varying SNRs from − 5 to 15 dB, the reconstructed components based on FrSST exhibit favorable approximation to the original signal components. Furthermore, as the sample size increases, the proposed algorithm shows satisfactory computational efficiency.

Fatty acid composition of blood serum and erythrocyte membranes in men with steatosis and steatohepatitis with normal transaminase activity

Aim. To study the characteristics of the fatty acid (FA) profi le of blood serum and erythrocyte membranes in patients with two forms of fatty liver disease (metabolic + alcoholic): steatosis and steatohepatitis with normal transaminase activity.Materials and methods. We examined 33 men (50.7 ± 9.6 years) with fatty liver disease (metabolic and alcoholic) with fi brosis F ≤ 1 (FibroTest). According to the ActiTest results, patients were divided into groups of steatosis – with minimal (A0–1) activity (n = 17) and steatohepatitis – with moderate/severe (A2–3) necroinfl ammatory activity (n = 16). The FA composition of blood serum and erythrocyte membranes was studied using gas chromatography/mass spectrometry Agilent 7000B (Agilent Technologies, Inc., USA). Methods of unpaired statistics using volcano plot and discriminant analysis based on orthogonal least squares (Orthogonal Partial Least Squares Discriminant Analysis, OPLS-DA), ROC analysis were applied.Results. Volcano plot analysis showed that in patients with fatty liver disease (metabolic and alcoholic) with normal transaminase activity, serum levels of stearic C18:0 (p = 0.016), arachidic C20:0 (p = 0.023), ratio saturated / polyunsaturated fatty acids (PUFA) (p = 0.001) were statistically signifi cantly higher in the steatohepatitis group compared with the steatosis group. The total content in the blood serum of all PUFA (p = 0.003), margaric C17:0 (p = 0.011), the sum of two omega-3 PUFA – eicosapentaenoic acid (C20:5n-3) and docosahexaenoic acid (C22:6n-3) (p = 0.04), the total content of all omega-3 PUFA (p = 0.042) were statistically signifi cantly lower in patients with steatohepatitis. OPLS-DA demonstrated fairly accurate separation of steatohepatitis and steatosis using individual FA and their ratios. When individual FA and their ratios were included in the analysis, a model was obtained with AUC = 0.827 (95% confi dence interval 0.499–1.0), sensitivity 82.2% and specifi city 80.7%.Conclusion. FA in blood serum and erythrocyte membranes appear to be promising biomarkers of steatohepatitis with normal levels of transaminases.

Recent advancements in flow control using plasma actuators and plasma vortex generators

AbstractFlow‐control techniques have attracted significant attention in many scientific areas due to their ability to improve the effectiveness and regulate the flow of aerodynamic devices. This study explores the latest developments in flow‐control techniques, specifically concentrating on the cutting‐edge technologies of plasma vortex generators (PVGs) and actuators. By taking advantage of the ionization of gases or air, plasma actuators have become a viable method for modifying an object's aerodynamic properties without needing physical moving parts. These actuators create localized plasma discharges that interact with the surrounding flow to provide accurate separation control, boundary‐layer dynamics, and aerodynamic forces on aircraft wings, wind turbine blades, and other surfaces. PVG, which produce controlled vortical structures, offer a novel way to manipulate airflow with plasma actuators. These generators create swirling motions through plasma discharges that can be used in various technical applications, such as automotive, marine, and aviation, to modify boundary layers, reduce drag, and improve lift characteristics. This study offers an overview of recent work, focusing on the theoretical underpinnings, experimental validations, and practical applications of plasma‐based flow‐control technologies. Advances in plasma‐generating techniques, computational modeling approaches, and experimental configurations to optimize and comprehend the intricate fluid–structure interactions are covered in the debate. Moreover, the study delves into incorporating plasma‐based flow management into cars, renewable energy systems, and next‐generation aerospace designs, highlighting the possibility of increased agility, decreased emissions, and efficiency. It also discusses the difficulties and potential paths for developing these technologies further for use in business and industry, highlighting the necessity of dependable, scalable, and durable solutions. Finally, this study summarizes the most recent advancements in vortex generators and plasma actuators for flow control. It demonstrates how they have the power to revolutionize fluid dynamics and aerodynamics in a variety of engineering fields.

Adaptive mode decomposition method based on fault feature orientation and its application to compound fault diagnosis of planetary gearboxes

Abstract Planetary gearboxes often experience multiple component failures during service, which can accelerate the degradation and failure of industrial equipment. Accurate separation and identification of multiple faults is an important means of ensuring the safe and stable operation of equipment. However, different faults can interact with each other, along with the influence of background noise, making it challenging to accurately extract faults with relatively weak energy among multiple faults. This difficulty leads to the problems of potential misdiagnosis and underdiagnosis. To address this issue, an adaptive mode decomposition method based on fault feature orientation (AMD-FF) is proposed in this paper. Initially, a fault impact indicator (FII) is constructed based on period-weighted kurtosis of envelope spectral and correlated combination negentropy to effectively characterize the impulsiveness and periodicity of fault features. Furthermore, with the objective of maximizing the FII, an adaptive decomposition of the original signal is designed based on blind convolution theory using a finite-impulse response filter group. Subsequently, a variable weight particle swarm optimization is employed to adaptively optimize the key decomposition parameters. Finally, the data of industrial-grade planetary gear transmission test rig are collected to validate the proposed method for compound fault diagnosis of planetary gearboxes. The results indicate that the AFMD-FF can effectively separate and extract compound faults in planetary gearboxes, demonstrating superior fault separation and diagnostic performance compared to the fault mode decomposition (FMD) and adaptive FMD. This method offers a novel approach to diagnosing compound faults in rotating equipment in industrial scenarios.

Zwitterionic nanospheres engineered co-polymer composite membrane for precise protein-protein separation via dynamic self-assembly micelle deposition

The accurate protein-protein separation is important but technically challenging. Achieving such a precise separation using membrane requires the selective channels with appropriate pore geometry structure and high anti-fouling property. In this study, polyethersulfone-b-poly(sulfobetaine methyl methacrylate) (PES-b-PSBMA) was synthesized and engineered onto polysulfone (PSF) ultrafiltration (UF) membrane to fabricate zwitterionic nanospheres engineered co-polymer (ZN-e-CoP) composite membrane via dynamic self-assembly micelle deposition. On the one hand, self-assembly zwitterionic nanospheres were used as blocks to construct hydrophilic layers with size-dependent sieving channels, endowing ZN-e-CoP composite membranes with enhanced permselectivity and protein-protein separation abilities, meanwhile zwitterionic groups from nanospheres reinforced the structure stability of nanospheres/nanospheres and nanospheres/membrane via multiple intermolecular interactions. On the other hand, zwitterionic nanospheres can induce to produce the hydration layer enveloping themselves by binding water molecules, where hydration layer acts as a protective barrier on the membrane surface, impeding the protein adhesion. Hence, ZN-e-CoP_1a composite membrane exhibited superior separation properties with Lysozyme/Bovine Serum Albumin (BSA) separation factor of 18.1 and 95.4 % rejection against BSA, 10.1 and 2.3 times, respectively, higher these of pristine PSF membrane (1.8 and 42.1 %), without obviously sacrificing water flux. Simultaneously, hydration layer enables the ZN-e-CoP_1a membrane with enhanced anti-fouling performance and durability during the long-term operations. The proposed approach opens new pathways to fabricate excellent anti-fouling membranes for precise protein-protein separation.

Low-rank prior-based Fast-RPCA for clutter filtering and noise suppression in non-contrast ultrasound microvascular imaging

Accurate and real-time separation of blood signal from clutter and noise signals is a critical step in clinical non-contrast ultrasound microvascular imaging. Despite the widespread adoption of singular value decomposition (SVD) and robust principal component analysis (RPCA) for clutter filtering and noise suppression, the SVD’s sensitivity to threshold selection, along with the RPCA’s limitations in undersampling conditions and heavy computational burden often result in suboptimal performance in complex clinical applications. To address those challenges, this study presents a novel low-rank prior-based fast RPCA (LP-fRPCA) approach to enhance the adaptability and robustness of clutter filtering and noise suppression with reduced computational cost. A low-rank prior constraint is integrated into the non-convex RPCA model to achieve a robust and efficient approximation of clutter subspace, while an accelerated alternating projection iterative algorithm is developed to improve convergence speed and computational efficiency. The performance of the LP-fRPCA method was evaluated against SVD with a tissue/blood threshold (SVD1), SVD with both tissue/blood and blood/noise thresholds (SVD2), and the classical RPCA based on the alternating direction method of multipliers algorithm through phantom and in vivo non-contrast experiments on rabbit kidneys. In the slow flow phantom experiment of 0.2 mm/s, LP-fRPCA achieved an average increase in contrast ratio (CR) of 10.68 dB, 9.37 dB, and 8.66 dB compared to SVD1, SVD2, and RPCA, respectively. In the in vivo rabbit kidney experiment, the power Doppler results demonstrate that the LP-fRPCA method achieved a superior balance in the trade-off between insufficient clutter filtering and excessive suppression of blood flow. Additionally, LP-fRPCA significantly reduced the runtime of RPCA by up to 94-fold. Consequently, the LP-fRPCA method promises to be a potential tool for clinical non-contrast ultrasound microvascular imaging.