查找使用阿拉丁产品的科研文献

An ACET capacitive biosensor for rapid and ultrasensitive detection of sweat uric acid

Yujie Chen,Zhongxi Yu,Haochen Qi,Li Lv,Yun Jiang,Xiaojie Yuan,Qike Yin,Jian Zhang,Lei Zheng

Integrated ACET aptasensor, microfluidic patch, and portable detector. • Rapid sweat collection (10 μL in 15 s) via PDMS capillary micro-channels. • Ultra-low LOD (75.43 aM), wide linear range (0.1 fM–10 pM), and high selectivity (2069: 1). • 2-min turnaround time, 21-day stability, and $ 50 system cost. Hyperuricemia is closely linked to uric acid (UA) levels, and conventional serum UA detection is invasive and time-consuming, limiting its suitability for rapid monitoring. Herein, an alternating current electrothermal (ACET) capacitive aptasensor is developed for fast detection of sweat UA. Benefiting from the powerful ACET effect for target enrichment and ultrasensitive interfacial capacitance sensing, the sensor achieves a low calculated detection limit of 75.43 aM within 30 s, along with a wide linear dynamic range from 0.1 fM to 10 pM and a high selectivity ratio of 2069: 1. A point-of-care testing platform integrating a microfluidic sweat-collection patch and a self-developed portable micro-capacitance detector is further constructed, capable of harvesting 10 μL of sweat within 15 s and testing instantaneous capacitance, allowing the total testing in less than 2 min including a dilution step. The platform is validated using diluted, spiked human sweat samples, demonstrating the feasibility of the sensor for rapid and non-invasive UA detection. Download: Download high-res image (278KB) Download: Download full-size image

Phosphorylation modification of Trichosanthes kirilowii seed protein isolates: An effective foaming enhancement strategy

Hanxiao Bao,Dong Peng,Weiwen Li,Xiangmin Pan,Wanyue Ding,Guosen Li,Ling Dong,Pan Li,Bing Du

4% STP and STMP concentrations reached the maximum grafting of TPI. • Phosphorylation unfolds TPI and formed small surface holes. • Phosphorylation improves the foaming properties of TPI. • Phosphorylated TPI can replace 25% of egg white as a notable food ingredient. The development and utilization of plant protein resources continue to attract considerable attention. Phosphorylation is an effective technique for improving protein functionality, yet its specific influence on Trichosanthes kirilowii protein isolate (TPI) remains unexplored. In this study, TPI was modified through phosphorylation using sodium tripolyphosphate (STP) and sodium trimetaphosphate (STMP), respectively, and the optimum phosphate grafting was achieved at a concentration of 4%, reaching 21.35 ± 1.08 mg/g for STP and 21.98 ± 1.64 mg/g for STMP. Compared with native TPI, phosphorylated TPI increased the absolute Zeta potential and surface hydrophobicity, while Fourier transform infrared spectrometer and X-ray diffraction analyses revealed a transition toward more flexible and disordered secondary structures. X-ray photoelectron spectroscopy analysis further confirmed the covalent incorporation of phosphate groups via P O and P O bonds. These structural modifications enhanced the foaming properties of TPI, with the foaming ability increasing from 40 ± 9.43% to 253.33 ± 18.86% and foaming stability achieving 60.95 ± 0.48%. When applied as a 25% egg white replacer in angel cake, phosphorylated TPI significantly increased batter viscoelasticity, specific volume, and crumb springiness compared to unmodified TPI, while maintaining sensory acceptability. These findings demonstrate that phosphorylation is an effective strategy to substantially improve the foaming properties of TPI. Download: Download high-res image (190KB) Download: Download full-size image

Development of an Olfactory Receptor (OR5K1)-Based Biosensor for Pyrazine Detection in Foods

Pyrazines are the key odorants in food contributing to baked and nutty aromas. In order to improve practicality, a novel electrochemical olfactory biosensor for pyrazine analysis was developed using an olfactory receptor (OR5K1) as the recognition element and AuNPs-PB/ZIF-8@SWCNT/Ti3C2MXene as the sensing matrix. The sensing application and molecular recognition mechanism of OR5K1 toward pyrazines were explored using molecular docking and in silico site-directed mutagenesis. We explored the sensing application and molecular recognition mechanism of OR5K1 toward pyrazines using molecular docking and in silico site-directed mutagenesis. The sensor achieved a linear detection range of 10−14to 10−9M with a low detection limit of 10−14M. The biosensor exhibited significantly higher current responses toward pyrazine compounds compared to interfering substances, including ethanol, hexanal, acetone, and phenol, demonstrating excellent selectivity, and retained 79% of its initial signal after 12 days of storage, indicating good stability. The change in the reduction peak current (ΔI) in the presence of pyrazine was used as an analytical signal. When applied to four malt samples (pilsner, munich, crystal, and caramel malts), the biosensor showed ΔI responses ranging from 4.6 ± 0.2 µA to 108 ± 6 µA, which corresponded well with the total pyrazine contents determined by GC-TOF/MS (0.092–0.391 mg/kg), with a correlation coefficient of 0.96. Molecular docking revealed binding energies ranging from −3.9 to −6.0 kcal/mol, suggesting spontaneous interactions between OR5K1 and pyrazines, with Leu14, Met81, Asn84, Phe17, Phe85, and Lys90 identified as potential key residues and hydrogen bonds, hydrophobic interactions, and π−π stacking as primary driving forces. This work provides a sensitive and selective biosensor for pyrazine detection, and the elucidated recognition mechanism offers a molecular basis for understanding roasted aroma perception, supporting applications in food quality control and flavor analysis. Collectively, this study offers new insights for designing olfactory receptor-based electrochemical biosensors and facilitates future exploration of food aroma–receptor interaction mechanisms.

Quantitative Analysis of Multiple Serum Tumor Biomarkers by an Interpretable Stacked Ensemble Model

Boyu Wu,Jiawei Chen,Yanheng Huang,Pan Li,Qingmei Deng,Ronglu Dong,Liangbao Yang

Surface-enhanced Raman spectroscopy (SERS) offers exceptional sensitivity and specificity for biomolecular detection, particularly in analyzing serum tumor biomarkers. However, its application is hindered by spectral complexity and matrix interference. Although machine learning (ML) has shown promise in SERS data analysis, existing quantitative models for biomarker detection lack generalizability and interpretability. To address these challenges, we developed an interpretable stacked ensemble model (ISEM) that integrates feature selection, ensemble learning, and explainable artificial intelligence (XAI) for quantifying 12 serum tumor biomarkers. To ensure reliable quantitative analysis, we validated the acquired SERS data using uniform and reproducible Au nanoparticle substrates. Preprocessing, least absolute shrinkage, and selection operator (LASSO) feature selection were employed to establish a foundation for accurate quantification. Subsequently, 12 serum tumor biomarkers were quantified, demonstrating the superior performance of ISEM, which achieved a high predictive accuracy, with R2 values exceeding 0.9 for all biomarkers. Crucially, based on the quantitative results, we provided molecular-level interpretability for structure-spectrum correlations using Shapley additive explanations (SHAP), revealing how glycosylation reactions, matrix interference, and spectral overlap influence prediction accuracy. Furthermore, the capability of ISEM to quantify multiple biomarkers in unseen samples was confirmed through validation of its generalizability. Our study establishes an ensemble-driven, interpretable framework for quantitative biomarker analysis in a complex biological matrix, demonstrating significant potential for early cancer diagnosis and screening.

An ultrasensitive CRISPR/Cas12a based electrochemical biosensor for detection of toxigenic Clostridioides difficile

Mengqing Cheng,Xinyue Chen,Hongrui Cheng,Xianglin Gao,Haoyue Ao,Xinyang Bao,Xiaojun Song,Yulei Tai,Dazhi Jin,Lei Zhang

Clostridioides difficile ( C. difficile ) infection (CDI) represents a formidable global healthcare challenge, necessitating the development of rapid, accurate, and cost-effective diagnostic platforms to mitigate nosocomial transmission and improve patient outcomes. Compared with the conventional methods, CRISPR/Cas systems featured by specific target reorganization by a single chain RNA, coupled with electrochemical technology enables highly sensitive detection of various biomarkers. However, their application to CDI has remained unexplored due to the lack of tailored crRNAs. Herein, we present the integration of CRISPR/Cas12a with electrochemical transduction for the direct detection of C. difficile . A novel crRNA was engineered to specifically recognize the toxin B gene ( tcdB ), activating the trans-cleavage activity of Cas12a upon target binding. This cascade triggers the cleavage of immobilized ssDNA reporters on the electrode surface, generating measurable amperometric signal changes. The developed biosensor demonstrates exceptional performance, achieving a detection limit of pM level for tcdB DNA within 40 min, while exhibiting high specificity against non-target pathogens and robust stability over 7 days. This work establishes a rapid and reliable CRISPR-electrochemical diagnostic platform, offering significant potential for point-of-care CDI management.

An HSP90-Inhibitory Thermosensitive Hydrogel Enhances Photothermal Therapy Against Triple-Negative Breast Cancer

Ke Wang,Tao Xu,Ruixiao Li,Chao Tao,Weiyi Chen,Shiying Mao,Meiling Zhou,Bin Liao,Jinlu Shang,Li Deng

Thermosensitive MGA@Gel enables prolonged intratumoral retention and controlled release. • GA-mediated HSP90 inhibition reduces thermotolerance and enhances PTT efficacy. • MGA@Gel exhibits stable photothermal performance with rapid heating. • MGA@Gel achieves effective tumor inhibition with good biocompatibility in 4T1 mice. Triple-negative breast cancer (TNBC) is highly aggressive and prone to recurrence, and durable therapeutic efficacy is often difficult to achieve with monotherapy. Photothermal therapy (PTT) offers advantages such as minimal invasiveness and spatiotemporal controllability and induces tumor cell death through localized hyperthermia. However, thermal stimulation simultaneously activates protective heat-stress responses in tumor cells, among which the inducible upregulation of heat shock protein 90 (HSP90) enhances thermotolerance and consequently compromises the efficacy of PTT. To overcome this limitation, we proposed a synergistic strategy based on HSP90 inhibition to induce tumor cell apoptosis while sensitizing tumors to PTT, and constructed an intratumorally injectable thermosensitive hydrogel for localized drug delivery. The HSP90 inhibitor geldanamycin (GA) was loaded into mesoporous polydopamine (MPDA) to form MGA, which was subsequently encapsulated within a PNIPAM/β-glucan composite thermosensitive hydrogel, yielding MGA@Gel. Both in vitro and in vivo studies demonstrated that MGA@Gel markedly enhanced antitumor efficacy under near-infrared (NIR) laser irradiation and effectively suppressed HSP90-associated heat-stress tolerance. Notably, in a 4T1 tumor-bearing mouse model, a single intratumoral injection established a sustained local drug depot. When combined with NIR laser irradiation, this system enabled efficient tumor suppression, pronounced downregulation of HSP90 signaling, increased apoptosis, and reduced tumor cell proliferation. These findings confirm that GA, by blocking the heat-stress protective pathway, effectively potentiates the antitumor effects of PTT. Overall, we developed a thermosensitive in situ hydrogel delivery system that enhances PTT via HSP90 inhibition, thereby overcoming tumor thermoresistance and providing a promising strategy for precise local treatment of TNBC.

RMScratcher: An edge-AI platform for high-throughput analysis of rodent scratching behavior

Moran Zhang,Xin Zeng,Min Chen,Jinxuan Liu,Li Li,Hongxiang Chen,Fangyi Chen

Automated platform enables detailed and unbiased quantification of scratching behavior. • High-throughput processing increases efficiency and reduces manual effort. • Improved YOLOv8s balances efficiency and precision for fine-grained behavioral detection. • Immediate analytics support on-the-fly experimental monitoring and adjustments • Compact edge-computing design ensures scalable and easy deployment in laboratories Background Quantitative analysis of rodent scratching is essential for studying somatosensory and neuroimmune mechanisms, yet scalable and high-throughput analysis remains challenging. New method We developed RMScratcher, a compact platform combining multi-channel acquisition with Jetson TX2–based edge computing and an enhanced YOLOv8s framework. Incorporating GhostConv and Context Aggregation modules, the system achieves efficient and accurate detection of bouts, touch, duration and scratching region. Results RMScratcher achieved > 95% accuracy in distinguishing scratching from other behaviors, reliably quantified bout, touch and duration, and scratching region. Performance was robust across multiple rodent models and experimental conditions. Comparison with existing methods Manual scoring is slow and prone to bias, while existing automated tools often lack throughput and generalizability. Crucially, there is no known literature that identifies the scratching region. RMScratcher provides these capabilities with minimal hardware requirements. Conclusions RMScratcher extends the methodological toolkit for behavioral neuroscience by integrating video recording with intelligent computation. The platform facilitates reproducible studies of somatosensory function, neuroimmune interactions, behavioral phenotyping, and the neural mechanisms underlying abnormal sensory behaviors. Download: Download high-res image (169KB) Download: Download full-size image

An integrated platform for high-throughput analysis and sorting of single mammalian cells

Xiuyun Li,Anle Ge,Zhidian Diao,Wenjie Zhao,Lingyan Kan,Sijun Luo,Wei Gao,Xixian Wang,Jian Xu,Bo Ma

Single mammalian cell heterogeneity plays a critical role in biological research. However, current microfluidic platforms for single-cell analysis still face the challenge of simultaneously achieving high-efficiency capture, cost-effective target cell sorting, and functional integration. To overcome these challenges, we developed a novel microfluidic platform for high-throughput single-cell analysis and sorting. This platform integrates multiple functions, including high-efficiency capture, online incubation, in situ detection, and target sorting. The chip employs a cost-effective polydimethylsiloxane-indium tin oxide (PDMS-ITO) glass configuration with arrayed capture microstructures, achieving average capture efficiency exceeding 93% for mammalian cells (RAW264.7, HCT116, and MCF7) across a size range of approximately 10–20 μm. The platform allows online incubation and artificial intelligence (AI)-assisted detection using both bright-field and fluorescent imaging. Cell viability rates consistently exceeded 80% after 24 h incubation and live/dead staining. A laser-induced microbubble strategy enabled precise releasing target single cells which were subsequently collected in a 96-well plate. In addition, the platform was applied to evaluate heterogeneity in reactive oxygen species (ROS) responses among macrophages, revealing intercellular differences under stimulation. This high-throughput, cost-effective platform combines high capture efficiency, advanced detection, and cell sorting functionality, demonstrating its utility for single mammalian cell heterogeneity studies and downstream applications.

3D printable dynamic hydrogel via entangled biomolecular coacervate towards an ECM-like scaffold

Weiqiang Wang,Xuan Wang,Dongdong Hu,Xiaoqing Song,Jiaying Qiu,Jiajia Gao,Yutong Liu,Yixuan Tao,Honghua Ge

The extracellular matrix (ECM) is a dynamic, hierarchically structured network essential for mechanical support and regulation of cell behavior. Mimicking its complexity in synthetic materials remains a major challenge. Here, we present a straightforward strategy to fabricate ECM-inspired, dynamically phase-separated hydrogels (DyPS-MAPgel) by methacrylation of mussel adhesive proteins (MAPs), followed by metal ion-induced phase separation and in situ photopolymerization. Leveraging the intrinsic ability of MAPs to undergo biomolecular phase separation and subsequent covalent crosslinking, the resulting hydrogels exhibit tunable mechanical properties, strong tissue adhesion, self-healing, antibacterial, and antioxidant activities. Importantly, DyPS-MAPgels support stem cell proliferation and lineage-specific differentiation both in vitro and in vivo through integrin-dependent mechanotransduction pathways. This work demonstrates the potential of phase separation–mediated assembly as a robust strategy for constructing ECM-mimetic materials and provides insights into ECM-cell interactions. Our findings offer a versatile platform for regenerative medicine applications, including bioadhesion, 3D bioprinting, and tissue engineering.

An active marker-based strategy for Anti-inflammatory Enhancement of Qiangli Pipa Syrup

Wenpei Chen,Bing Zhao,Xinkai Xu,Xuanming Chen,Jingxue Guo,Zhixing Liao,Junjie Qiu,Yichen Wang,Xuesong Liu,Yong Chen,Hong Li,Su Zeng,Tengfei Xu

Ethnopharmacological relevance Qiangli Pipa Syrup (PPS) is a well-established classical traditional Chinese medicine (TCM) formula, historically utilized in clinical practice for treating respiratory ailments, particularly cough, phlegm, and various forms of inflammation of the lung and throat. While its traditional efficacy is well-recognized, the current quality control paradigms, which primarily focus on chemical marker consistency (Q-markers), often fail to guarantee consistent therapeutic efficacy in modern clinical settings. Therefore, a novel approach is urgently needed to link the established traditional use with reliable efficacy in the context of modern quality standards. Aim of the study In the present study, we have proposed a novel concept of "active markers" (A-markers), which is defined as endogenous metabolites that are associated with pharmacodynamic efficacies of TCM. Material and methods By integrating cellular metabolomics and pharmacodynamic analysis, systematically screen and validate these A-markers. Results we have revealed two endogenous metabolites (leucine and phenylalanine) could act as candidate A markers to enhance the anti-inflammatory ability of Qiangli Pipa Syrup (PPS) in vitro and in vivo. Conclusion The present results indicate that the activity metabolites are not only biomarkers but also can be regarded as functional effectors to exhibit enhanced effects with exogenous Q-markers. Furthermore, the feasible A-marker framework offers a conceptual and methodological strategy to bridge the gap between chemical consistency and efficacy consistency in TCM, and providing a new avenue for TCM Pharmacodynamic Potentiation and quality control.

An Amphipathic Supramolecular Networks of Catechol-Functionalized Grafted Terpolymer for Oil–Water Separation

Cheng Cheng,Lijun Liu

Fine surfactant-stabilized emulsion separation from industrial produced water remains a critical challenge, as conventional membranes suffer from severe fouling, poor dual-phase adaptability, and limited stability. Herein, a high-performance oil–water separation membrane was fabricated via RAFT polymerization and dopamine post-functionalization, constructing a catechol-functionalized supramolecular network stabilized by hydrogen bonding and π-π stacking. This work features three core innovations: a well-defined catechol-functionalized PDMA- g -PEG-co-PDA terpolymer, liquid-triggered adaptive wettability without external stimuli, and a robust supramolecular network for enhanced mechanical and antifouling properties. The membrane exhibits exceptional hydration capability, realizing molecular discrimination of oil–water mixtures via distinct diffusion kinetics. It achieves > 99% separation efficiency for all tested oil-in-water/water-in-oil emulsions at a high flux of ~850 L·m −2 ·h −1 and maintains > 99% efficiency after 15+ recyclable cycles. This intelligent amphipathic membrane addresses key limitations of traditional separation materials, offering a sustainable high-throughput solution for industrial oily wastewater treatment and environmental remediation, advancing the design of adaptive separation materials.

An efficient method to prepare silver-loaded SMA microspheres with high electrical conductivity

QinYa Nong,XiangYun Zhao,JiaFu Yu,JiaYing Huang,Ying Wang,YingXue Zhang,Hao Qian

An effective method for preparing conductive composite microspheres based on poly(styrene‑alt‑maleic anhydride) (SMA) microspheres was developed. Cross‑linked SMA microspheres were first synthesized via self‑stabilized precipitation polymerization of styrene and maleic anhydride using divinylbenzene as the crosslinker. Based on the high reactivity of the maleic anhydride groups, abundant amino groups were modified on the surface of SMA microspheres by 1,4‑butanediamine (SMA-NH2 microspheres). These amino groups served as effective anchoring sites for the dense immobilization of silver nanoparticles (AgNPs) through in-situ reduction, creating highly active catalytic centers. Subsequent secondary silver growth, mediated by ascorbic acid, facilitated the formation of a uniform and continuous silver shell.The resulting SMA@Ag microspheres exhibited excellent electrical conductivity, reaching 2578 S/cm. Notably, this amine-mediated strategy obviates the conventional requirement for heavy-metal-based sensitizers and activators (e.g., Sn2+, Pd2+), thereby streamlining the process and enhancing its environmental sustainability. This approach provides a straightforward and eco-friendly route for the production of high-performance conductive polymer composites.