Concentration Of Biomolecules Research Articles

Granular Biomaterials as Bioactive Sponges for the Sequestration and Release of Signaling Molecules.

A major challenge for the regeneration of chronic wounds is an underlying dysregulation of signaling molecules, including inflammatory cytokines and growth factors. To address this, we propose to use granular biomaterials composed of jammed microgels, to enable the rapid uptake and delivery of biomolecules, and provide a strategy to locally sequester and release biomolecules. Sequestration assays on model biomolecules of different sizes demonstrated that granular hydrogels exhibit faster transport than comparable bulk hydrogels due to enhanced surface area and decreased diffusion lengths. To demonstrate the potential of modular granular hydrogels to modulate local biomolecule concentrations, we engineered microgel scaffolds that can simultaneously sequester excess pro-inflammatory factors and release pro-healing factors. To target specific biomolecules, microgels were functionalized with affinity ligands that bind either to interleukin 6 (IL-6) or to vascular endothelial growth factor A (VEGF-A). Finally, disparate microgels were combined into a single granular biomaterial for simultaneous sequestration of IL-6 and release of VEGF-A. Overall, we demonstrate the potential of modular granular hydrogels to locally tailor the relative concentrations of pro- and anti-inflammatory factors. This article is protected by copyright. All rights reserved.

Dynamic Monitoring of Biomolecular Hydrodynamic Dimensions by Magnetization Motion on Quartz Crystal Microbalance.

Hydrodynamic dimension (HD) is the primary indicator of the size of bioconjugated particles and biomolecules. It is an important parameter in the study of solid-liquid two-phase dynamics. HD dynamic monitoring is crucial for precise and customized medical research as it enables the investigation of the continuous changes in the physicochemical characteristics of biomolecules in response to external stimuli. However, current HD measurements based on Brownian motion, such as dynamic light scattering (DLS), are inadequate for meeting the polydisperse sample demands of dynamic monitoring. In this paper, we propose MMQCM method samples of various types and HD dynamic monitoring. An alternating magnetic field of frequency ωm excites biomolecule-magnetic bead particles (bioMBs) to generate magnetization motion, and the quartz crystal microbalance (QCM) senses this motion to provide HD dynamic monitoring. Specifically, the magnetization motion is modulated onto the thickness-shear oscillation of the QCM at the frequency ωq. By analysis of the frequency spectrum of the QCM output signal, the ratio of the magnitudes of the real and imaginary parts of the components at frequency ωq ± 2ωm is extracted to characterize the particle size. Using the MMQCM approach, we successfully evaluated the size of bioMBs with different biomolecule concentrations. The 30 min HD dynamic monitoring was implemented. An increase of ∼10 nm in size was observed upon biomolecular structural stretching. Subsequently, the size of bioMBs gradually reduced due to the continuous dissociation of biomolecules, with a total reduction of 20∼40 nm. This HD dynamic monitoring demonstrates that the release of biomolecules can be regulated by controlling the duration of magnetic stimulation, providing valuable insights and guidance for controlled drug release in personalized precision medicine.

Blood-based cardiometabolic phenotypes in atrial fibrillation and their associated risk: EAST-AFNET 4 biomolecule study.

Atrial fibrillation (AF) and concomitant cardiometabolic disease processes interact and combine to lead to adverse events such as stroke, heart failure, myocardial infarction, and cardiovascular death. Circulating biomolecules provide quantifiable proxies for cardiometabolic disease processes. Their role in defining subphenotypes of AF is not known. This prespecified analysis of the EAST-AFNET4 biomolecule study assigned patients to clusters using polytomous variable latent class analysis (poLCA) based on baseline concentrations of thirteen precisely-quantified biomolecules potentially reflecting ageing, cardiac fibrosis, metabolic dysfunction, oxidative stress, cardiac load, endothelial dysfunction, and inflammation. In each cluster, rates of cardiovascular death, stroke, or hospitalization for heart failure or acute coronary syndrome, the primary outcome of EAST-AFNET 4, were calculated and compared between clusters over median 5.1 years follow-up. Findings were independently validated in a prospective cohort of 748 patients with AF (BBC-AF; median follow up 2.9 years).Unsupervised biomolecule analysis assigned 1586 patients (71 years old, 46% women) into four clusters. The highest-risk cluster was dominated by elevated BMP10, IGFBP7, NT-proBNP, ANGPT2 and GDF15. Patients in the lowest-risk cluster showed low concentrations of these biomolecules. Two intermediate-risk clusters differed by high or low concentrations of hsCRP, IL-6, and D-dimer. Patients in the highest-risk cluster had a 5-fold higher cardiovascular event rate than patients in the low-risk cluster. Early rhythm control was effective across clusters (pinteraction = 0.63). Sensitivity analyses and external validation in BBC-AF replicated clusters and risk gradients. Biomolecule concentrations identify cardiometabolic subphenotypes in patients with atrial fibrillation at high and low cardiovascular risk.

Different profiles of soil phosphorous compounds depending on tree species and availability of soil phosphorus in a tropical rainforest in French Guiana

BackgroundThe availability of soil phosphorus (P) often limits the productivities of wet tropical lowland forests. Little is known, however, about the metabolomic profile of different chemical P compounds with potentially different uses and about the cycling of P and their variability across space under different tree species in highly diverse tropical rainforests.ResultsWe hypothesised that the different strategies of the competing tree species to retranslocate, mineralise, mobilise, and take up P from the soil would promote distinct soil 31P profiles. We tested this hypothesis by performing a metabolomic analysis of the soils in two rainforests in French Guiana using 31P nuclear magnetic resonance (NMR). We analysed 31P NMR chemical shifts in soil solutions of model P compounds, including inorganic phosphates, orthophosphate mono- and diesters, phosphonates, and organic polyphosphates. The identity of the tree species (growing above the soil samples) explained > 53% of the total variance of the 31P NMR metabolomic profiles of the soils, suggesting species-specific ecological niches and/or species-specific interactions with the soil microbiome and soil trophic web structure and functionality determining the use and production of P compounds. Differences at regional and topographic levels also explained some part of the the total variance of the 31P NMR profiles, although less than the influence of the tree species. Multivariate analyses of soil 31P NMR metabolomics data indicated higher soil concentrations of P biomolecules involved in the active use of P (nucleic acids and molecules involved with energy and anabolism) in soils with lower concentrations of total soil P and higher concentrations of P-storing biomolecules in soils with higher concentrations of total P.ConclusionsThe results strongly suggest “niches” of soil P profiles associated with physical gradients, mostly topographic position, and with the specific distribution of species along this gradient, which is associated with species-specific strategies of soil P mineralisation, mobilisation, use, and uptake.

Gas Evolution as a Tool to Study Reaction Kinetics Under Biomimetic Conditions.

The field of bioorthogonal chemistry is rapidly growing, presenting successful applications of organic and transition metal-catalysed reactions in cells and living systems (in vivo). The development of such reactions typically proceeds through many iterative steps focused on biocompatibility and fast reaction kinetics to ensure product formation. However, obtaining kinetic data, even under simulated biological (biomimetic) conditions, remains a challenge due to substantial concentrations of salts and biomolecules hampering the use of typically employed solution-phase analytical techniques. In this study, we explored the suitability of gas evolution as a probe to study kinetics under biomimetic conditions. As proof of concept, we show that the progress of two transition metal-catalysed bioorthogonal chemical reactions can be accurately monitored, regardless of the complexity of the medium. As such, we introduce a protocol to gain more insight into the performance of a catalytic system under biomimetic conditions to further progress iterative catalyst development for in vivo applications.

Toward Prebiotic Chemistry on Titan: Impact Experiments on Organic Haze Particles

Impacts are critical to producing the aqueous environments necessary to stimulate prebiotic chemistry on Titan’s surface. Furthermore, organic hazes resting on the surface are a likely feedstock of biomolecules. In this work, we conduct impact experiments on laboratory-produced organic haze particles and haze/sand mixtures and analyze these samples for life’s building blocks. Samples of unshocked haze and sand particles are also analyzed to determine the change in biomolecule concentrations and distributions from shocking. Across all samples, we detect seven nucleobases, nine proteinogenic amino acids, and five other biomolecules (e.g., urea) using a blank subtraction procedure to eliminate signals due to contamination. We find that shock pressures of 13 GPa variably degrade nucleobases, amino acids, and a few other organics in haze particles and haze/sand mixtures; however, certain individual biomolecules become enriched or are even produced from these events. Xanthine, threonine, and aspartic acid are enriched or produced in impact experiments containing sand, suggesting these minerals may catalyze the production of these biomolecules. On the other hand, thymine and isoleucine/norleucine are enriched or produced in haze samples containing no sand, suggesting catalytic grains are not necessary for all impact shock syntheses. Uracil, glycine, proline, cysteine, and tyrosine are the most unstable to impact-related processing. These experiments suggest that impacts alter biomolecule distributions on Titan’s surface, and that organic hazes co-occurring with fine-grained material on the surface may provide an initial source for further prebiotic chemistry on Titan.

Multicompartmental coacervate-based protocell by spontaneous droplet evaporation

Hierarchical compartmentalization, a hallmark of both primitive and modern cells, enables the concentration and isolation of biomolecules, and facilitates spatial organization of biochemical reactions. Coacervate-based compartments can sequester and recruit a large variety of molecules, making it an attractive protocell model. In this work, we report the spontaneous formation of core-shell cell-sized coacervate-based compartments driven by spontaneous evaporation of a sessile droplet on a thin-oil-coated substrate. Our analysis reveals that such far-from-equilibrium architectures arise from multiple, coupled segregative and associative liquid-liquid phase separation, and are stabilized by stagnation points within the evaporating droplet. The formation of stagnation points results from convective capillary flows induced by the maximum evaporation rate at the liquid-liquid-air contact line. This work provides valuable insights into the spontaneous formation and maintenance of hierarchical compartments under non-equilibrium conditions, offering a glimpse into the real-life scenario.

Recent Advances in Metallic Nanostructures-Assisted Biosensors for Medical Diagnosis and Therapy.

The field of nanotechnology has witnessed remarkable progress in recent years, particularly in its application to medical diagnosis and therapy. Metallic nanostructures-assisted biosensors have emerged as a powerful and versatile platform, offering unprecedented opportunities for sensitive, specific, and minimally invasive diagnostic techniques, as well as innovative therapeutic interventions. These biosensors exploit the molecular interactions occurring between biomolecules, such as antibodies, enzymes, aptamers, or nucleic acids, and metallic surfaces to induce observable alterations in multiple physical attributes, encompassing electrical, optical, colorimetric, and electrochemical signals. These interactions yield measurable data concerning the existence and concentration of particular biomolecules. The inherent characteristics of metal nanostructures, such as conductivity, plasmon resonance, and catalytic activity, serve to amplify both sensitivity and specificity in these biosensors. This review provides an in-depth exploration of the latest advancements in metallic nanostructures-assisted biosensors, highlighting their transformative impact on medical science and envisioning their potential in shaping the future of personalized healthcare.

Physics-based analytical model for trap assisted biosensing in dual cavity negative capacitance junctionless accumulation mode FET

The design of a ferroelectric-based biosensor for detecting various biomolecules like proteins and DNA has captivated the interest of researchers in early disease diagnostics and treatment monitoring. Doomed by this interest, an analytical model for trap-assisted biosensing in Dual Cavity Negative Capacitance Junctionless Accumulation Mode FET is proposed for detecting various biomolecules. The biomolecules are treated as traps that tunnel through the biosensor's ferroelectric layer. The analytical model is validated through extensive numerical device simulations. The device incorporates the detection of charged and uncharged biomolecules in terms of dielectric constants and biomolecule concentration. The nano-cavities are created inside the gate dielectric stack to collect biomolecules like proteins and DNA. As the biomolecules are infused as traps in cavity areas, electrical properties of the biosensor, like input characteristics, transconductance, threshold voltage, on-state current, and subthreshold swing change. The sensitivity obtained for the proposed biosensor is compared with the existing biosensor and found that it is best suited for susceptible biosensing applications.

A direct MIP-interfaced FET sensor for sensitive, selective, and real time biomolecule detection in unamplified samples: Toward POC bioelectronic transduction

Diverse efforts undertaken to mitigate the Debye screening effect of field-effect transistor (FET) biosensors have achieved higher sensitivity. However, the charge transfer or induction mechanism between the captured biomolecules and the sensing surface, resulting in shift of surface potential and, hence, the drain current magnitude, shows poor selectivity for real time detection of ultra-low biomolecule concentration in unamplified samples. Herein, enabling direct interaction of the target molecule with edge passivated thermally reduced graphene oxide, through the template of molecularly imprinted polymer (MIP), specific trap induced characteristic bulges in the noise spectrum has been observed only in the presence of target molecule. Such a phenomenon has not been observed either with antibodies or aptamers as receptors. Hence, the direct interface of MIP with a graphene FET (GFET) results in the generation of an additional electronic label in FET transduction. As a proof of concept, this principle has been validated for serotonin detection in serum in the presence of other neurotransmitters, resulting in detection limit of 0.05 fM in real time, which is more than two orders of magnitude lower than existing reports and, hence, is expected to pave the way for advancing GFET based sensors toward ultrasensitive point-of-care applications without requiring complex machine learning algorithms.

Deep Learning-Based Denoising of CEST MR Data: A Feasibility Study on Applying Synthetic Phantoms in Medical Imaging.

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) provides a novel method for analyzing biomolecule concentrations in tissues without exogenous contrast agents. Despite its potential, achieving a high signal-to-noise ratio (SNR) is imperative for detecting small CEST effects. Traditional metrics such as Magnetization Transfer Ratio Asymmetry (MTRasym) and Lorentzian analyses are vulnerable to image noise, hampering their precision in quantitative concentration estimations. Recent noise-reduction algorithms like principal component analysis (PCA), nonlocal mean filtering (NLM), and block matching combined with 3D filtering (BM3D) have shown promise, as there is a burgeoning interest in the utilization of neural networks (NNs), particularly autoencoders, for imaging denoising. This study uses the Bloch-McConnell equations, which allow for the synthetic generation of CEST images and explores NNs efficacy in denoising these images. Using synthetically generated phantoms, autoencoders were created, and their performance was compared with traditional denoising methods using various datasets. The results underscored the superior performance of NNs, notably the ResUNet architectures, in noise identification and abatement compared to analytical approaches across a wide noise gamut. This superiority was particularly pronounced at elevated noise intensities in the in vitro data. Notably, the neural architectures significantly improved the PSNR values, achieving up to 35.0, while some traditional methods struggled, especially in low-noise reduction scenarios. However, the application to the in vivo data presented challenges due to varying noise profiles. This study accentuates the potential of NNs as robust denoising tools, but their translation to clinical settings warrants further investigation.

In-Cell Stability Prediction of RNA/DNA Hybrid Duplexes for Designing Oligonucleotides Aimed at Therapeutics.

In cells, the formation of RNA/DNA hybrid duplexes regulates gene expression and modification. The environment inside cellular organelles is heterogeneously crowded with high concentrations of biomolecules that affect the structure and stability of RNA/DNA hybrid duplexes. However, the detailed environmental effects remain unclear. Therefore, the mechanistic details of the effect of such molecular crowding were investigated at the molecular level by using thermodynamic and nuclear magnetic resonance analyses, revealing structure-dependent destabilization of the duplexes under crowded conditions. The transition from B- to A-like hybrid duplexes due to a change in conformation of the DNA strand guided by purine-pyrimidine asymmetry significantly increased the hydration number, which resulted in greater destabilization by the addition of cosolutes. By quantifying the individual contributions of environmental factors and the bulk structure of the duplex, we developed a set of parameters that predict the stability of hybrid duplexes with conformational dissimilarities under diverse crowding conditions. A comparison of the effects of environmental conditions in living cells and in vitro crowded solutions on hybrid duplex formation using the Förster resonance energy transfer technique established the applicability of our parameters to living cells. Moreover, our derived parameters can be used to estimate the efficiency of transcriptional inhibition, genome editing, and silencing techniques in cells. This supports the usefulness of our parameters for the visualization of cellular mechanisms of gene expression and the development of nucleic acid-based therapeutics targeting different cells.

Ruthenium-Anchored Carbon Sphere-Customized Sensor for the Selective Amperometric Detection of Melatonin.

Melatonin (MT), a pineal gland hormone, regulates the sleep/wake cycle and is a potential biomarker for neurodegenerative disorders, depression, hypertension, and several cancers, including prostate cancer and hepatocarcinoma. The amperometric detection of MT was achieved using a sensor customized with ruthenium-incorporated carbon spheres (Ru-CS), possessing C- and O-rich catalytically active Ru surfaces. The non-covalent interactions and ion-molecule adducts between Ru and CS favor the formation of heterojunctions at the sensor-analyte interface, thus accelerating the reactions towards MT. The Ru-CS/Screen-printed carbon electrode (SPCE) sensor demonstrated the outstanding electrocatalytic oxidation of MT owing to its high surface area and heterogeneous rate constants and afforded a lower detection limit (0.27 μM), high sensitivity (0.85 μA μM -1 cm-2), and excellent selectivity for MT with the co-existence of crucial neurotransmitters, including norepinephrine, epinephrine, dopamine, and serotonin. High concentrations of active biomolecules, such as ascorbic acid and tyrosine, did not interfere with MT detection. The practical feasibility of the sensor for MT detection in pharmaceutical samples was demonstrated, comparable to the data provided on the product labels. The developed amperometric sensor is highly suitable for the quality control of medicines because of its low cost, simplicity, small sample size, speed of analysis, and potential for automation.

Highly sensitive label-free biosensor: graphene/CaF2 multilayer for gas, cancer, virus, and diabetes detection with enhanced quality factor and figure of merit

One of the primary goals for the researchers is to create a high-quality sensor with a simple structure because of the urgent requirement to identify biomolecules at low concentrations to diagnose diseases and detect hazardous chemicals for health early on. Recently graphene has attracted much interest in the field of improved biosensors. Meanwhile, graphene with new materials such as CaF2 has been widely used to improve the applications of graphene-based sensors. Using the fantastic features of the graphene/CaF2 multilayer, this article proposes an improvement sensor in the sensitivity (S), the figure of merit (FOM), and the quality factor (Q). The proposed sensor is based on the five-layers graphene/dielectric grating integrated with a Fabry–Perot cavity. By tuning graphene chemical potential (µc), due to the semi-metal features of graphene, the surface plasmon resonance (SPR) waves excited at the graphene/dielectric boundaries. Due to the vertical polarization of the source to the gratings and the symmetry of the electric field, both corners of the grating act as electric dipoles, and this causes the propagation of plasmonic waves on the graphene surface to propagate towards each other. Finally, it causes Fabry–Perot (FP) interference on the surface of graphene in the proposed structure's active medium (the area where the sample is located). In this article, using the inherent nature of FP interference and its S to the environment's refractive index (RI), by changing a minimal amount in the RI of the sample, the resonance wavelength (interferometer order) shifts sharply. The proposed design can detect and sense some cancers, such as Adrenal Gland Cancer, Blood Cancer, Breast Cancer I, Breast Cancer II, Cervical Cancer, and skin cancer precisely. By optimizing the structure, we can achieve an S as high as 9000 nm/RIU and a FOM of about 52.14 for the first resonance order (M1). Likewise, the remarkable S of 38,000 nm/RIU and the FOM of 81 have been obtained for the second mode (M2). In addition, the proposed label-free SPR sensor can detect changes in the concentration of various materials, including gases and biomolecules, hemoglobin, breast cancer, diabetes, leukemia, and most alloys, with an accuracy of 0.001. The proposed sensor can sense urine concentration with a maximum S of 8500 nm/RIU and cancers with high S in the 6000 nm/RIU range to 7000 nm/RIU. Also, four viruses, such as M13 bacteriophage, HIV type one, Herpes simplex type 1, and influenza, have been investigated, showing Maximum S (for second resonance mode of λR(M2) of 8000 nm/RIU (λR(M2) = 11.2 µm), 12,000 nm/RIU (λR(M2) = 10.73 µm), 38,000 nm/RIU (λR(M2) = 11.78 µm), and 12,000 nm/RIU (λR(M2) = 10.6 µm), respectively, and the obtained S for first resonance mode (λR(M1)) for mentioned viruses are 4740 nm/RIU (λR(M1) = 8.7 µm), 8010 nm/RIU (λR(M1) = 8.44 µm), 8100 nm/RIU (λR(M1) = 10.15 µm), and 9000 (λR(M1) = 8.36 µm), respectively.

New Formulation of Platelet-Rich Plasma Enriched in Platelet and Extraplatelet Biomolecules Using Hydrogels.

Platelet-rich plasma (PRP) is an autologous biologic product used in several fields of medicine for tissue repair due to the regenerative capacity of the biomolecules of its formulation. PRP consists of a plasma with a platelet concentration higher than basal levels but with basal levels of any biomolecules present out of the platelets. Plasma contains extraplatelet biomolecules known to enhance its regenerative properties. Therefore, a PRP containing not only a higher concentration of platelets but also a higher concentration of extraplatelet biomolecules that could have a stronger regenerative performance than a standard PRP. Considering this, the aim of this work is to develop a new method to obtain PRP enriched in both platelet and extraplatelet molecules. The method is based on the absorption of the water of the plasma using hydroxyethyl acrylamide (HEAA)-based hydrogels. A plasma fraction obtained from blood, containing the basal levels of platelets and proteins, was placed in contact with the HEAA hydrogel powder to absorb half the volume of the water. The resulting plasma was characterized, and its bioactivity was analyzed in vitro. The novel PRP (nPRP) showed a platelet concentration and platelet derived growth factor (PDGF) levels similar to the standard PRP (sPRP), but the concentration of the extraplatelet growth factors IGF-1 (p < 0.0001) and HGF (p < 0.001) were significantly increased. Additionally, the cells exposed to the nPRP showed increased cell viability than those exposed to a sPRP in human dermal fibroblasts (p < 0.001) and primary chondrocytes (p < 0.01). In conclusion, this novel absorption-based method produces a PRP with novel characteristics compared to the standard PRPs, with promising in vitro results that could potentially trigger improved tissue regeneration capacity.

A biospectroscopic approach toward colorectal cancer diagnosis from bodily fluid samples via ATR–MIR spectroscopy combined with multivariate data analysis

In this study, a biospectroscopic approach was reported for the detection of spectral changes and biomarkers for the diagnosis of colorectal cancer (CC) cases from different bodily fluids (blood plasma, blood serum, saliva and colonoscopy disinfection/wash fluids) by using attenuated total reflection–mid infrared (ATR–MIR) spectroscopy. To recognize the molecular level changes in the spectral characteristics of CC and their healthy/control (CH) groups, different multivariate data analyses (HCA, LDA, PCA and SIMCA) were successfully performed over the data of ATR–MIR spectroscopy. Two hundred specimens were characterized in detail over the data of spectral regions (4000–650 cm−1 and regions V–XXII). The findings revealed that significant changes were clearly observed in the concentrations of lipid, protein, nucleic acid and carbohydrate biomolecules for cancer cases based upon their necessity to overcome energy requirements. Supervised multivariate data methodology SIMCA, presented an excellent classification for the studied groups; similarly 100% of the specimens from different bodily fluids were correctly classified by supervised methodology LDA. As a result, the developed ATR–MIR methodology for the classification of CC and their healthy groups highlighted a rapid cancer diagnosis approach from different bodily fluids; therefore, it could be guide to make well decision before histopathological assessment and to screen CC populations existing in society.

Self-demixing of mRNA copies buffers mRNA:mRNA and mRNA:regulator stoichiometries

Cellular homeostasis requires the robust control of biomolecule concentrations, but how do millions of mRNAs coordinate their stoichiometries in the face of dynamic translational changes? Here, we identified a two-tiered mechanism controlling mRNA:mRNA and mRNA:protein stoichiometries where mRNAs super-assemble into condensates with buffering capacity and sorting selectivity through phase-transition mechanisms. Using C.elegans oogenesis arrest as a model, we investigated the transcriptome cytosolic reorganization through the sequencing of RNA super-assemblies coupled with single mRNA imaging. Tightly repressed mRNAs self-assembled into same-sequence nanoclusters that further co-assembled into multiphase condensates. mRNA self-sorting was concentration dependent, providing a self-buffering mechanism that is selective to sequence identity and controls mRNA:mRNA stoichiometries. The cooperative sharing of limiting translation repressors between clustered mRNAs prevented the disruption of mRNA:repressor stoichiometries in the cytosol. Robust control of mRNA:mRNA and mRNA:protein stoichiometries emerges from mRNA self-demixing and cooperative super-assembly into multiphase multiscale condensates with dynamic storage capacity.

A numerical study of sample preconcentration using ion concentration polarization in single microfluidic channels with dual ion-selective membranes

In this work, we investigated three single straight microchannel designs for the microfluidic biomolecule concentration device, including one traditional single channel and two innovative channels. These microchannels utilized the ion concentration polarization (ICP) phenomenon to preconcentrate very dilute sample biomolecules. By numerically solving coupled equations, Nernst–Planck, Poisson, and Navier–Stokes with appropriate boundary conditions, we provide insight into the ICP phenomenon and the preconcentration mechanism. From the detailed modeling results, we clarify the influence of important working parameters, including electric potentials, the ion-selective membrane dimensions, the channel dimensions, and the ionic strength of buffer solution on the formation of ICP and the enrichment rate of the charged biomolecules. These modeling results for various working conditions of the preconcentration systems highlight the advantage of generating a stronger electric field to preconcentrate biomolecules of two innovative channel designs over the conventional one. The findings are useful tips for the design and optimization of preconcentration microfluidic devices.

Application of hybrid Au@Ag nanostructures in fiber optic biosensor for rapid detection of C-reactive protein

Elevated levels of C-reactive protein (CRP) in the bloodstream are a well-established marker of systemic inflammation in humans. Research on the application of hybrid plasmon material for optical fiber sensor application to sensitively monitor C-reactive protein concentration based on the hybrid material particles has been proposed in this study. Specifically, Au@Ag nanoparticles are coated onto the optical fiber surface by a self-assembled monolayer using an NH2 bridge. CRP antigens are then immobilized onto the surface of Au@Ag NPs to selectively detect CRP and improve sensor sensitivity. The limit of detection for this fiber sensor is 2.4 × 10−5 mg/L. The selectivity of the sensor was also demonstrated in media containing bovine serum albumin (BSA) and glucose. These findings represent an important step toward the development of biosensors capable of monitoring extremely low concentrations of biomolecules in vivo, thereby supporting early disease detection and diagnosis.

Highly sensitive fiber SPR sensor based on InSe nanosheets

Surface plasmon resonance (SPR) optical fiber sensors exhibit advantages such as small size, immunity to electromagnetic interference, and corrosion resistance, and are currently widely applied in the field of biodetection. However, their sensitivity and reusability are still limited in detecting biomolecules, trace concentrations, and weak signals. This paper proposes an approach by utilizing indium selenide (InSe) nanoflakes to enhance the surface electric field strength of the metal layer. InSe is a two-dimensional material that exhibits higher charge carrier mobility and refractive index compared to traditional two-dimensional materials, thereby promoting electron transfer and inducing a larger SPR effect. By testing the sensors composed of InSe nanosheets with different thicknesses, it is found that the sensitivity of InSe nanosheets with a thickness of 40 nm is up to 4655.76 nm/RIU, which is much higher than the sensitivity of traditional Au film sensors and 52 % higher than that of MoS2-Au film SPR sensors with the same structure. Moreover, the sensor has a higher FOM value of 33.25 RIU−1 and shows excellent characteristics in repeatability and stability experiments. In this paper, a new method is proposed to enhance the sensitivity of SPR sensors and realize the monitoring of lower biomolecule concentration and weak signal. In addition, the great potential of indium selenide nanosheets in optical applications is emphasized.