Search Results (1,968)

Pseudomonas aeruginosa is a major opportunistic pathogen frequently associated with nosocomial infections, such as pneumonia, urinary tract infections, and wound infections, particularly in immunocompromised or hospitalized patients. These infections are often difficult to treat due to the pathogen’s intrinsic antibiotic resistance and biofilm-forming ability. Therefore, rapid and selective detection of P. aeruginosa is essential for early diagnosis and effective infection control. In this study, a novel surface-imprinted MIP design uniquely combines methacrylamide (MAM), acrylamide (AAM), and vinylpyrrolidone (VP) monomers to generate recognition cavities that are complementary to the surface morphology and physicochemical properties of Pseudomonas aeruginosa cells. Unlike traditional MIP approaches, this surface imprinting strategy provides improved stability and reproducibility, without relying on biological recognition elements like antibodies or aptamers. This novel approach enabled us to achieve an ultralow LOD of 1 CFU/mL over a linear range of 1–10⁴ CFU/mL, demonstrating excellent analytical performance. In addition, the sensor exhibited good reproducibility with an RSD of 5–12%. The novelty of this work lies in the use of a surface-imprinted MIP strategy combined with a multi-monomer system to enhance bacterial recognition and sensing performance. Overall, the proposed MIP-based electrochemical biomimetic sensor offers a rapid, cost-effective, and portable platform with strong potential for the detection of P. aeruginosa in clinical and environmental applications. Full article

Nanobiosensors, with their unique physicochemical properties, are transformative tools for diagnosing and monitoring neurodegenerative diseases and mental disorders. This article systematically reviews the latest progress of nanomaterial systems and integrated sensing modalities in neurological disease diagnosis. First, we clarify the multiple functional roles of nanomaterials in biosensors, including signal amplification, interface optimization, and spatial positioning, and compare the applicable scenarios of various sensing principles based on different nanomaterials. Second, we evaluate the design and integration strategies of molecular recognition elements (antibodies, nucleic acid aptamers, molecularly imprinted polymers, and CRISPR-Cas systems) and discuss their synergistic integration mechanisms for improving detection performance. In terms of detection targets, we focus on three applications: high-sensitivity quantification of established protein biomarkers, real-time monitoring of dynamic neurochemicals (dopamine, serotonin, glutamate), and emerging liquid biopsy targets such as exosomal cargo and circulating microRNAs. Finally, to address the core challenges of biofouling, sensitivity–selectivity trade-offs, and multiplex detection in complex matrices, we propose three breakthrough directions for next-generation diagnostics: deep integration of multimodal and multiplexing platforms, closed-loop chemical brain–computer interfaces (cBCIs), and AI-driven predictive diagnostic models, collectively enabling a transition from passive detection to active sensing and intervention for precise, rapid, and non-invasive neurological disease management. Full article

Background: Gynecological cancers include collections of cancers with diverse cellular and molecular characteristics that often develop drug resistance, making them treatment-resistant. Biomolecule–drug conjugates (BDCs), especially antibody–drug conjugates (ADCs), have revolutionized the targeted therapy of cancer; however, the creation of these entities has so far been achieved by empirical, resource-intensive design methods. Objective: The aim of this review is to critically analyze how AI can be used for the rational design and optimization of high-affinity BDCs for gynecological cancer treatment. Methods and discussion: Recent advances in machine learning (ML)- and deep learning (DL)-based methods to predict biomolecule-target binding affinity, structural compatibility, linker stability, payload selection, trafficking in the cell, and biomolecule resistance mechanisms are summarized. The review also explores the possibilities for incorporation of structural, chemical, biological, and multi-omics data to enhance specificity, efficacy, and safety of conjugates. Besides antibody-based systems, AI-assisted design approaches with peptides, aptamers, and hybrid biomolecular systems are also included. This review also highlights parameters and experimental/numerical validation restrictions related to data quality, interpretability of models, regulatory aspects, etc. Conclusions: AI-based conjugate engineering is increasingly moving BDC development from a largely ‘trial and error’ approach to a more predictive and data-driven approach. While there are still challenges to be addressed in terms of translations and validations, the potential of AI approaches in the field of precision oncology and the development of more personalized treatment is promising in the context of gynecological cancers. Full article

Extracellular vesicles (EVs) have attracted considerable attention as natural nanocarriers for immune modulation owing to their intrinsic biocompatibility, nanoscale size, and capacity to transport diverse bioactive cargos. In inflammatory diseases, EV-based therapeutics provide unique opportunities to regulate dysregulated immune responses; however, their clinical translation remains constrained by limited cell-specific targeting efficiency and uncontrolled biodistribution. Achieving precise and selective delivery to immune cells and other inflammation-associated cellular components within diseased tissues is therefore critical for maximizing therapeutic efficacy while minimizing off-target effects. This review comprehensively summarizes recent advances in cell-specific EV-targeting strategies for immune modulation in inflammatory diseases, with a particular focus on active targeting approaches enabled by EV surface engineering. A range of targeting ligands, including antibodies, peptides, aptamers, glycans, and membrane proteins, is discussed in the context of enhancing selective interactions between EVs and specific immune cell subsets. Special emphasis is placed on cell-directed targeting strategies toward diverse immune cell populations, including macrophages and T cells, highlighting how rational control of EV–cell interactions can be utilized to reprogram immune phenotypes, suppress pathological inflammation, and restore immune homeostasis. Accordingly, this review integrates recent progress in cell-specific EV targeting into a coherent conceptual framework, which may assist researchers in the rational design of EV-based immunomodulatory therapeutics. Full article

RNA aptamer sensors are promising for environmental and clinical detection, but their poor stability limits practical application. Here, we developed a tRNA-fused strategy to enhance the stability of unmodified RNA aptamer sensors. The tRNA scaffold was fused to the 3′ end of Spinach aptamer to construct tRNA-Spinach. In vitro stability assays showed that tRNA-Spinach retained 50% of its initial fluorescence for 84 days at 25 °C (60% humidity), a 7-fold improvement compared with native Spinach (12 days). The tRNA-fused strategy also doubled the in vivo half-life of Spinach from 20 min to 40 min in KM mice. Based on this strategy, a tobramycin sensor was constructed, which exhibited a LOD of 30 nM, a linear range of 30–100 nM (R² = 0.9905). The biosensor could be detected with a handheld UV lamp within 10 min. This tRNA-fused strategy enables room-temperature storage of RNA aptamer sensors without chemical modification, providing a scalable and cost-effective platform for point-of-care diagnostics in resource-limited settings. Full article

Celiac patients require strict avoidance of gliadin, the primary immunotoxic component of gluten, making sensitive detection essential for food safety. A label-free and reagentless capacitive aptasensor for gliadin detection was developed using an aminated polyethylene terephthalate (PET) thin film as both an insulating layer and functionalization platform. The PET surface was modified via ethylenediamine-mediated aminolysis, enabling covalent immobilization of 5′-NH₂-modified gliadin aptamers through glutaraldehyde crosslinking. Under optimized conditions (23 µm initial PET thickness and 10 µM aptamer), the sensor showed a linear response from 10 to 500 µg/mL gliadin (R² = 0.9792), with a detection limit of 6.0 µg/mL, equivalent to 12 ppm gluten, which is well below the regulatory threshold of 20 ppm for gluten-free labeling. The aptasensor showed excellent correlation with commercial ELISA for 20 gluten-containing soy sauce samples (R² = 0.926) and spike recoveries of 91.7–105.7% in two gluten-free products. Efficient regeneration was achieved with 25 mM arginine (pH 9.0), retaining >80% activity after six cycles. This simple, low-cost, and reusable platform relies solely on a single PET thin film as consumable in a custom-built system with lab-friendly aminolysis conditions. It substantially lowers barriers to functionalized insulating layer fabrication, the primary challenge in capacitive aptasensor development, providing a promising method for on-site gliadin monitoring in gluten-free food safety applications. Full article

Protein biomarkers can be used for monitoring the occurrence and development of diseases. Accurate, sensitive, and low-cost methods for protein detection can facilitate therapeutic intervention, improve clinical outcome, and reduce economic pressure for patients. Molecularly imprinted polymers (MIPs) have been considered as a type of biomimetic materials for developing biosensing technologies due to their advantages of high stability, low preparation cost, and good reusability over classical biometric recognition elements such as antibodies and aptamers. Electrochemical biosensors have become the most promising technology in sensing applications in view of their high sensitivity, fast response speed, cost-effectiveness, good stability, and ease of miniaturization. Efforts have been made to develop various electrochemical biosensors for protein detection with MIPs as recognition elements. This article provides an overview of the progress in molecular imprinting methods for the design and application of electrochemical protein biosensors. The strategies for imprinting and removing templates and preparing MIPs-modified sensing electrodes are comprehensively discussed. Finally, the challenges and future perspectives of protein-imprinted electrodes are addressed. This work will contribute to the development of innovative analytical devices based on MIPs for monitoring and managing various diseases by determining protein biomarkers. Full article

Capillary electrophoresis (CE) has proven to be an effective technique for aptamer selection. Here, we directly integrated the separation advantages of CE into a live-cell system, thereby establishing an integrated and highly efficient CE-Cell-SELEX screening model for bone microvascular endothelial cells (BMECs) without the need for negative selection. The selection progress was monitored through quantitative real-time fluorescence PCR (qRT-PCR) analysis, which yielded 7 candidate sequences from the amplified library after four rounds of selection. Flow cytometry analysis demonstrated that aptamer T-24 exhibited high affinity for BMECs, with a Kd of 111.86 ± 18.36 nM. Owing to its high affinity and specificity, coupled with its small molecular weight and non-immunogenicity, T-24 holds great potential as a biological probe for the identification and isolation of BMECs. Furthermore, molecular docking was performed by MOE 2022 software to validate the candidate sequences and assist in the identification process. The CE-Cell-SELEX method eliminates the need for negative screening and traditional elution, greatly reduces the screening cycle, and may provide a valuable reference system for the early diagnosis and precise treatment of femoral head ischemia. Full article

In prokaryotes, translation initiation orchestrates protein synthesis through a network of dynamic interactions among the ribosome, mRNA, initiator tRNA^fMet, and initiation factors (IFs). Traditional approaches that rely on radioactive labeling or surface immobilization are hindered by inherent safety risks and methodological constraints. We present a fluorescence-based analytical platform that integrates microscale thermophoresis (MST) as a unified, multiparametric toolkit for comprehensive interrogation of bacterial translation initiation at the molecular level. By systematically applying MST to a panel of fluorescently labeled components—initiator tRNA^fMet, mRNAs, and initiation factors—we quantify assembly pathways and equilibria as initiation progresses from simple bimolecular interactions to higher-order, multicomponent complexes. To broaden the fluorescence toolbox for ribosomal studies, we developed a robust BODIPY-labeling protocol for 70S ribosomes and confirmed preservation of structural integrity and function by nano differential scanning fluorimetry, stopped-flow kinetic assays, and peptide-synthesis activity tests. Our microscale fluorescent system facilitates probing initiation at a variety of steps, since the role of magnesium ions and initiation factors upon 30S initiation complex formation. The same platform can be applied to investigate the effects of different compounds on translation initiation, as demonstrated for a number of antibiotics, aptamers, and antimicrobial peptides. Using this approach, we determined the antibiotic streptomycin dissociation constant for both 30S and 70S ribosomes, which proved identical at 0.3 ± 0.1 μM, and demonstrated the effect of the antimicrobial peptide rumicidin-1 on translation initiation. Offering a cost-effective and high-sensitivity alternative to conventional methods, this approach advances mechanistic understanding of prokaryotic translation and provides a versatile framework for the discovery of novel protein synthesis inhibitors. Full article

Unexplained infertility affects up to 30% of couples and has been associated with heat shock proteins (HSP) and endometrial stress. HSPs and their co-chaperones are part of a complex network of proteins responsible for maintaining protein homeostasis and cell survival. This exploratory hypothesis-generating study investigated the possible relationship between HSPs and unexplained infertility. Twenty-five women were recruited from an IVF clinic. Eleven were confirmed for unexplained infertility (UI), while fourteen were age- and body mass index (BMI)-matched couples with confirmed male factor infertility (MFI), acting as controls. Blood samples were obtained at day 21 of the luteal phase, and plasma measurement of 19 HSPs and co-chaperones undertaken using the slow off-rate modified aptamer (SomaScan) platform. Welch’s t-test and a permutation test were used to compare group means, and Pearson’s correlations to examine relationships with HSPs. Of the 19 proteins measured, plasma HSP70 was decreased (permutation p = 0.002) in cases with unexplained infertility, while HSC70 and STIP1 were increased (permutation p = 0.017 and p = 0.001, respectively) when compared to MFI control. HSP70 was negatively correlated to both HSC70 and STIP 1 in UI (r = −0.77, permutation p = 0.017; −0.80, permutation p = 0.003, respectively), but not in MFI, whilst HSC70 and STIP1 were positively correlated in both UI and MFI (r = 0.93, permutation p = 0.001; r = 0.65, permutation p = 0.035, respectively). The HSP70-HSC70-STIP1 axis showed HSC70-STIP1 coupling with an inverse relationship with inducible HSP70, findings that may suggest dysregulation of constitutive and stress-inducible chaperone systems in UI. Full article

Imprinted proteins (IPs) are promising materials for producing artificial alternatives to natural recognition systems (antibodies, aptamers, etc.) due to their high sorption properties and specificity. However, contemporary understanding of the imprinting process at the atomic level is rather limited, which hinders the rational design of more efficient IPs. In this paper, we use computational modeling to provide a description of fundamental principles of protein imprinting at the atomic level. We have modeled several potential associates between the protein matrix and template molecules that form during the imprinting process up to the addition of the cross-linking agent. We used bovine serum albumin (BSA) as the protein matrix and 4-hydroxycoumarin (4–HC) as a molecular template. In combination with computational modeling, extensive experimental analyses including isothermal titration calorimetry (ITC) and NMR spectroscopic methods (¹H NMR and diffusion-ordered NMR spectroscopy (DOSY)) were used to evaluate the potential efficiency of imprinted BSA. This study represents a step toward the future rational in silico design of IPs. Full article

Synthetic biology is reshaping in vitro diagnostics (IVD) by enabling programmable and modular biosensing elements that can be integrated into point-of-care testing (POCT) platforms. Compared with conventional assays that depend on fixed chemistries and centralized instrumentation, synthetic biology-based systems offer adaptable molecular recognition, tunable signal processing, and flexible readout formats for decentralized diagnostics. In this review, we present synthetic biology-enabled IVD as programmable biosensing platforms organized into four functional layers: molecular recognition, signal transduction and amplification, output generation, and system integration. We discuss four major enabling modules, including cell-free protein synthesis (CFPS) systems, aptamer and riboswitch sensors, CRISPR-Cas diagnostic platforms, and microfluidic integration technologies. We summarize representative clinical applications from 2021 to 2025 in infectious disease detection, cancer biomarker analysis, and drug metabolism/toxicity screening. In addition, we examine practical considerations beyond analytical sensitivity, including matrix tolerance, workflow complexity, manufacturability, quantitative capability, and regulatory readiness. Finally, we highlight future directions for programmable diagnostics, including AI-assisted biosensor design, multimodal readouts, interoperable platform architectures, and real-world clinical validation. Full article

Schistosomiasis, caused by Schistosoma species, is notoriously difficult to accurately diagnose with conventional methods. In this study, we present an innovative biosensor that integrates CRISPR–Cas12a technology with nucleic acid aptamers for the highly sensitive detection of Schistosoma japonicum eggs. The biosensor leverages a Y-shaped DNA structure (Y-DNA) that incorporates an aptamer specific to S. japonicum eggs, along with an activator DNA and a segment for immobilization on magnetic nanomaterials. Upon target recognition, the Y-DNA releases the activator, which triggers the collateral cleavage activity of Cas12a, enabling the direct detection of eggs. This system demonstrates remarkable sensitivity, being capable of detecting individual eggs in infected rabbit serum and feces. Moreover, it effectively distinguishes the eggs of S. japonicum from those of other parasitic species. The simplicity, high sensitivity, and rapid detection of our biosensor offer significant potential for improving the diagnosis of schistosomiasis, providing a novel, reliable tool for early detection in clinical settings. Full article

Micro- and nanoplastic (MNP) pollution has emerged as a global environmental and health concern, driving the rapid development of sensor technologies for faster, more sensitive, and field-deployable detection. This review synthesizes recent advances in optical, electrochemical, and biosensor platforms for MNP analysis and compares their analytical performance and practical feasibility. Optical sensors, including plasmonic, spectroscopic, and colorimetric systems, enable label-free and often rapid detection with material discrimination capability, and are well-suited for screening applications, though they commonly exhibit higher detection limits and matrix interference. Electrochemical sensors demonstrate the highest analytical sensitivity overall, frequently reaching low µg L⁻¹ to ng mL⁻¹ levels, with strong potential for miniaturization and on-site deployment; performance is further enhanced by nanostructured electrodes, photoelectrochemical designs, and signal amplification strategies. Biosensors incorporating peptides, aptamers, enzymes, or engineered proteins provide improved polymer selectivity and enable targeted detection, but face challenges related to stability, cross-reactivity, and reproducibility in complex samples. Practically, portable electrochemical and simple optical colorimetric platforms are currently the most feasible for field use, while hybrid bio-electrochemical systems show the highest performance potential. Future research should prioritize robust selective recognition elements, antifouling interfaces, standardized validation protocols, mixed-polymer quantification models, and integration with machine learning to enable reliable, real-world MNP monitoring. Full article

Gold nanospheres (AuNPs) and gold nanoflowers (AuNFs) are widely used as platforms for DNA aptamer functionalization, while conjugation behavior and colloidal tolerance remain important factors affecting subsequent sensing-oriented optimization. In this study, 82-nt thiolated DNA aptamer constructs bearing either 3′-SH or 5′-SH terminal modification were immobilized onto citrate-stabilized AuNPs and AuNFs under matched stepwise salt-aging conditions. Apparent nanoparticle-associated DNA output was estimated by Qubit-based measurement of unbound ssDNA in the supernatant and expressed as mass-based loading output (ng). Under the tested stock-dispersion conditions, AuNP samples showed higher apparent conjugation output than AuNF samples. Specifically, the apparent conjugation yields for AuNPs were 80.65 ± 1.64% (3′-SH) and 84.76 ± 1.98% (5′-SH), whereas those for AuNFs were 66.64 ± 3.36% (3′-SH) and 73.65 ± 1.36% (5′-SH). The corresponding apparent DNA loading outputs were 2329.7 ± 47.4 ng and 2448.7 ± 57.1 ng for AuNPs, and 1925.1 ± 97.0 ng and 2127.4 ± 39.3 ng for AuNFs. DLS size increases and zeta potential shifts toward more negative values were consistent with the formation of a DNA-associated interfacial layer, while TEM images supported morphology retention after conjugation. A qualitative visual salt-challenge assessment indicated that aptamer-functionalized nanoparticles displayed improved resistance to salt-induced aggregation relative to bare particles under the tested conditions. Because the commercially supplied AuNP and AuNF dispersions were not normalized to identical particle number or accessible surface area, the reported values should be interpreted as comparative apparent outputs rather than intrinsic loading capacities. Within this scope, the present study provides a convenient preliminary materials-level evaluation of thiolated aptamer conjugation behavior and may support future glyphosate aptasensor optimization. Full article