Signal Reduction Research Articles

Visible light-activated signal amplification PEC aptasensor for ultrasensitive zearalenone detection based on double Z-type BiOI/g-C3N4@Au/Bi2S3 heterojunctions

Zearalenone (ZEN), also known as F-2 toxin, can enter the body through the food chain and accumulate, leading to DNA break and an abnormal number of chromosomes. Therefore, it is crucial to develop a facile and sensitive method for detecting ZEN. Herein, a visible light-activated signal amplification photoelectrochemical (PEC) aptasensor for ultrasensitive detection of ZEN has been successfully constructed, exploiting the synergistic effect of the Z-type BiOI/g-C3N4/Au heterojunctions, Bi2S3 as a signal enhancer, and the remarkable affinity and specificity of aptamers. The PEC properties and electron transfer mechanism of the double Z-type heterojunctions were thoroughly investigated. When the aptamers captured the ZEN molecules, Bi2S3 and cDNA departed from the electrode, resulting in a reduction in the photocurrent signal. Therefore, the concentration of ZEN can be quantitatively analyzed by measuring the change in the photocurrent response. The constructed PEC aptasensor exhibited exceptional sensitivity and selectivity for ZEN in the concentration range of 0.1 fg⋅mL−1 ––1.0 ng⋅mL−1, with a detection limit of 0.087 fg⋅mL−1 (S/N = 3). Finally, the PEC aptasensor was successfully applied to detect ZEN in actual coix seed samples, providing some guidance for the development of PEC aptasensors for practical medicine monitoring.

Interference of metal ions on the bioluminescent signal of firefly, Renilla, and NanoLuc luciferases in high-throughput screening assays

Bioluminescent high-throughput screening (HTS) assays, based largely on the activity of firefly (FLuc), Renilla (RLuc), and/or NanoLuc (NLuc) luciferases, are widely utilised in research and drug discovery. In this study, we quantify the luciferase-based real-life HTS assay interference from biologically and environmentally relevant metal ions ubiquitously present in buffers, environmental and biological matrices, and as contaminants in plastics and compound libraries. We also provide insights into the cross-effects of metal ions and other key experimental and biological reagents (e.g., buffer types, EDTA, and glutathione) to inform HTS assay design, validation, and data interpretation. A total of 21 ions were screened in three robust HTS assays (“SC” assays) based on the luminescence of FLuc, RLuc, and NLuc luciferases. Three newly optimised HEPES buffer variants (“H” assays) were developed for direct luciferase comparison. Interference in bioluminescent signal generation was quantified by calculating the IC50 values from concentration-dependent experiments for selected highly active and relevant metal ions. Metal ion inhibition mechanisms were probed by variations in specific reagents, EDTA, GSH, and the sequence of addition and buffer composition. In this study, we revealed a significant impact of metal ions’ salts on luciferase-mediated bioluminescence, even at biologically and environmentally relevant concentrations. The extent of signal interference largely aligned with the Irving–Williams series of metal ion–ligand affinities (Cu > Zn > Fe > Mn > Ca > Mg), supporting previous reports on metal ion-dependent FLuc inhibition. However, the absolute magnitude and relative extent of signal reduction by metal ions’ salts differed between SC and H assays and between luciferases, suggesting a complex network of metal ions’ interactions with enzymes, substrates, reactants, and buffer elements. The diversity of the tested conditions and variability of responses provided insights into potential interference mechanisms and synergies that may exacerbate or alleviate interference. The beneficial influence of EDTA and the impact of glutathione, present natively in cells, on bioluminescence readout were pinpointed. Given the ubiquity of metal ions in analysed samples, the causative role in false-positive generation in drug discovery, and the wide breadth of luciferase-based assays used in screening, awareness and quantification of metal influence are crucial for developing assay validation protocols and ensuring reliable screening data, ultimately increasing the critical robustness of bioluminescence-based HTS assays.

Epichaperome Inhibition by PU-H71-Mediated Targeting of HSP90 Sensitizes Glioblastoma Cells to Alkylator-Induced DNA Damage

Background: Targeted therapies have been largely ineffective against glioblastoma (GBM) owing to the tumor’s heterogeneity and intrinsic and adaptive treatment resistance. Targeting multiple pro-survival pathways simultaneously may overcome these limitations and yield effective treatments. Heat shock protein 90 (HSP90), an essential component of the epichaperome complex, is critical for the proper folding and activation of several pro-survival oncogenic proteins that drive GBM biology. Methods: Using a panel of biochemical and biological assays, we assessed the expression of HSP90 and its downstream targets and the effects of PU-H71, a highly specific and potent HSP90 inhibitor, on target modulation, downstream biochemical alterations, cell cycle progression, proliferation, migration, and apoptosis in patient-derived glioma stem-like cells (GSCs) with molecular profiles characteristic of GBM, as well as commercial glioma cell lines and normal human astrocytes (NHAs). Results: HSP90 inhibition by PU-H71 in GSCs significantly reduced cell proliferation, colony formation, wound healing, migration, and angiogenesis. In glioma cells, but not NHAs, potent PU-H71-mediated HSP90 inhibition resulted in the downregulation of pro-survival client proteins such as EGFR, MAPK, AKT, and S6. This reduction in pro-survival signals increased glioma cells’ sensitivity to temozolomide, a monofunctional alkylator, and the combination of PU-H71 and temozolomide had greater anticancer efficacy than either agent alone. Conclusions: These results confirm that HSP90 is a strong pro-survival factor in molecularly heterogeneous gliomas and suggest that epichaperome inhibition with HSP90 inhibitors warrants further investigation for the treatment of gliomas.

Dual hot-spot SERS test strip for picomole level analysis of thiram

The misuse and improper disposal of thiram pesticide present significant health and environmental risks, emphasizing the need for highly sensitive detection methods, particularly in food safety. In this study, we introduce a novel approach for thiram detection using surface-enhanced Raman scattering (SERS) test strips with dual hot-spots. Thiram prevents Ag+ from acting as specific bridging molecules in a SERS hotspots model. Initially, the aggregation of 4-aminothiophenol (4-ABT) functionalized silver nanoparticles (AgNPs@4-ABT) can be efficiently triggered by Ag+ ions, simultaneously enhancing the SERS signal of 4-ABT. However, the introduction of thiram inhibits the aggregation of Ag NPs@4-ABT, leading to a reduction in the SERS signal. Based on this principle, we have developed a SERS analysis method for detecting thiram in solution. To address the reliance on initial signal intensity, we translocated the detection system onto cotton fabric. This adjustment not only amplifies the initial signal through the physical aggregation of nanoparticles, creating secondary hotspots, but also improves portability and reduces resource consumption. Compared to the single hotspot solution model, our dual hotspot configuration significantly enhances sensitivity due to the stronger initial signal, achieving an impressive broad linear detection range from 5 × 10−5 to 5 × 10−11 M. This range substantially outperforms the linear range of Ag NPs@4-ABT alone, which spans from 5 × 10−5 to 10−8 M. The SERS test strips exhibit a detection limit as low as 2.56 × 10−12 M, enabling picomolar level analysis. This innovative dual hotspot SERS approach provides a powerful tool for sensitive and practical detection of thiram in safety-critical applications.

Probing coherence properties of shallow implanted NV snsembles under different oxygen terminations

Abstract Nitrogen vacancy (NV) color centers in diamond have shown great potential for various applications in quantum technology due to their long coherence times, high sensitivity to magnetic fields and atomic scale resolution. However, one major challenge in utilizing near surface NV centers is the decoherence caused by spins and charges fluctuating on the surface, which affects the spin properties of the sensors. To reduce the induced noise, various oxygen surface treatments such as low power oxygen plasma treatment and annealing under oxygen atmosphere have been explored to terminate the diamond surface and reduce its impact on NV coherence. We showed that the NV center's coherence time can be enhanced up to a factor of 3 over a large spectral range of noise. Double electron electron resonance (DEER) measurements revealed an extra source of decoherence, scaling similarly as the P1 spin bath. The improvement in coherence times is accompanied with an increase in measured ketone/ether content and reduction of sp2 signal in X-ray photoelectron spectroscopy (XPS) measurements. Finally we compared the performance of different NV ensembles and surface treatments for sensing external proton spins. The oxygen annealing is an effective procedure of enhancing the spin coherence times and reducing broad band spin noise experienced by shallow implanted ensemble NV centers in diamond.

Weak ultrasonic guided wave signal recognition based on one-dimensional convolutional neural network denoising autoencoder and its application to small defect detection in pipelines

Pipeline failures are often caused by the expansion of small defects. Structural damage to pipelines can lead to major safety accidents. When ultrasonic guided wave (UGW) technology is used for pipeline failure detection, the echoes produced by small defects manifest as weak UGW signals amidst significant noise. The low amplitude of these signals or complete drowning by noise makes them difficult to recognize. This study innovatively introduces a one-dimensional convolutional neural network denoising autoencoder (1DCNN-based DAE) for noise reduction in UGW signals using deep learning. To improve the conventional DAE, the model incorporated the Parametric Rectified Linear Unit (PReLU) activation function and a CNN for enhanced feature extraction, resulting in the proposed 1DCNN-based DAE. The model is trained on an extensive dataset of mixed signals with strong noise and their corresponding clean signals, enabling autonomous denoising in an unsupervised manner. Additionally, this paper proposes the application of the window-shifted power spectrum method for analyzing the denoised signals to identify and locate pipeline defects. The method involves traversing the signal with a window to intercept fragments, calculating their power, and plotting the power spectrum curve. Defects are then located based on the peak positions of this curve. Numerical simulation and experimental signals were used to validate the proposed method. Simulation results showed that the proposed 1DCNN-based DAE effectively improved the signal-to-noise ratio (SNR) of UGW mixed signals from −9 dB to 21.63 dB, representing an improvement of up to 30.63 dB. Experimental results demonstrated that the method accurately detected weak UGW signals from small defective pipes with a 2 % cross-section loss rate, achieving over 90 % recognition confidence and less than 1.5 % axial positioning error rate. In summary, the proposed 1DCNN-based DAE can effectively improve the SNR of the signal, reduce the noise in the UGW detection signal, and improve the sensitivity of defect identification; the window-shifted power spectrum method has a advantage in the accurate localization of defects.

Abstract B065: FabricaTM: A large-scale data simulation platform isolates tumor signal from cell-free DNA and improves tissue of origin prediction accuracy

Abstract Cell-free DNA (cfDNA) liquid biopsy is a promising non-invasive method for disease detection, but data availability and the complexity of cfDNA composition pose barriers to model development. Cancer prediction models trained on cfDNA data from clinically collected blood samples often struggle to isolate tumor-derived signals from confounding factors, and tissue of origin (TOO) models suffer from small sample sizes of rarer tumor types. To address these challenges, we developed FabricaTM, a platform to generate diverse, large-scale, high-fidelity simulated cfDNA datasets for robust and accurate machine learning (ML) model training. A key advantage of FabricaTM is its ability to enhance ML models by matching confounding variables between non-cancer and cancer samples. We first synthesized age-balanced non-cancer samples, then simulated tumor DNA shedding into circulation from 502 reference biopsy samples across 16 indications, optimizing for final tumor content distributions ranging from 0.001 to 14.2%. All reference non-cancer and biopsy samples consisted of aligned bisulfite sequencing reads from a custom target hybrid capture panel. This approach expanded a non-cancer dataset of 177 samples to 1,212 simulated samples and generated 6,400 simulated cancer cfDNA samples matching the non-cancers in age distribution. We then assessed this dataset for equivalence with clinical data and ability to improve cancer prediction. Non-linear dimensionality reduction and clustering of methylation signal showed simulated samples cluster indistinguishably from 2,290 samples (1,149 non-cancer, 1,141 treatment-naïve cancer) from the CORE-HH clinical study (NCT05435066). A binary cancer prediction model trained on the FabricaTM-generated dataset and evaluated on the CORE-HH dataset showed reduced reliance on age-associated signal (R2=0.15) and increased tuning towards tumor content, with minor cost to sensitivity (<4% at 95% specificity), relative to a model trained and cross-validated on the CORE-HH data (R2=0.60). To evaluate the benefit of these data for TOO prediction, we trained multiclass TOO models using FabricaTM's tumor biopsy reference data with and without the addition of our simulated data for 10 target indication groupings and benchmarked their performance on our clinical dataset. Training with both data types yielded a 10% increase in balanced accuracy. Moreover, peak performance was achieved at different training sample numbers per indication, illustrating FabricaTM's potential to estimate sample size requirements during study design. Our findings suggest FabricaTM-generated data can augment limited datasets to train ML models to identify tumor-specific biomarkers obscured by technical and demographic biases in real-world data. The age-balancing approach is readily applied to other confounders to help models learn true disease signatures. The platform is also adaptable to other diseases and biofluids (e.g., Alzheimer's disease, urine), allowing for extension to diagnostic and screening development beyond cancer and blood across the care spectrum. Citation Format: Kade Pettie, Shiva Farashahi, Jackson Killian, Dorna Kashef, Josh Hubbell, Feras Hantash, Jocelyn Charlton, Kieran Chacko. FabricaTM: A large-scale data simulation platform isolates tumor signal from cell-free DNA and improves tissue of origin prediction accuracy [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B065.

Metastable Oxygen-Induced Light-Enhanced Doping in Mixed Sn-Pb Halide Perovskites.

Mixed Sn-Pb halide perovskites are promising absorber materials for solar cells due to the possibility of tuning the bandgap energy down to 1.2-1.3 eV. However, tin-containing perovskites are susceptible to oxidation affecting the optoelectronic properties. In this work, we investigated qualitatively and quantitatively metastable oxygen-induced doping in isolated ASnxPb1-xI3 (where A is methylammonium or a mixture of formamidinium and cesium) perovskite thin films by means of microwave conductivity, structural and optical characterization techniques. We observe that longer oxygen exposure times lead to progressively higher dark conductivities, which slowly decay back to their original levels over days. Here oxygen acts as an electron acceptor, leading to tin oxidation from Sn2+ to Sn4+ and creation of free holes. The metastable oxygen-induced doping is enhanced by exposing the perovskite simultaneously to oxygen and light. Next, we show that doping not only leads to the reduction in the photoconductivity signal but also induces long-term effects even after loss of doping, which is thought to derive from consecutive oxidation reactions leading to the formation of defect states. On prolonged exposure to oxygen and light, optical and structural changes can be observed and related to the formation of SnOx and loss of iodide near the surface. Our work highlights that even a short-term exposure to oxygen immediately impairs the charge carrier dynamics of the perovskite, while structural perovskite degradation is only noticeable upon long-term exposure and accumulation of oxidation products. Hence, for efficient solar cells, exposure of mixed Sn-Pb perovskites to oxygen during production and operation should be rigorously blocked.

Effect of interfacial thermal resistance on the near-field photoacoustic signal from gold nanorod in water: a numerical study.

The near-field photoacoustics of gold nanoparticle in water has received much attention for its biomedical applications and is strongly affected by the gold-water interfacial thermal resistance. However, the effect of interfacial thermal resistance on near-field photoacoustics has been very little studied. Here we present the numerical simulations of near-field photoacoustic signal generation from a single gold nanorod in water by considering different thermal resistances at the gold-water interface. It is shown that, different from the reported reduction of far-field photoacoustic signals by interfacial thermal resistance, enhancement of near-field photoacoustic signals is obtained with the typical gold-water interfacial thermal resistance. Further analysis reveals that the higher rate of net heat transfer to the surrounding water at the typical interfacial thermal resistance, which corresponds to faster thermal expansion of the surrounding water, accounts for such enhancement of near-field photoacoustic signal and that the enhancement of near-field photoacoustic amplitude is mainly present at a distance within thermal diffusion length.

Integrated Imaging Probe and Bispecific Antibody Development Enables In Vivo Targeting of Glypican-3-Expressing Hepatocellular Carcinoma.

Glypican-3 (GPC3) is a proteoglycan with high sensitivity and specificity for hepatocellular carcinoma (HCC). We describe the integrated development and validation of a GPC3-targeting optical imaging probe and T cell-redirecting antibody (TRAB) as a theranostic strategy for the detection and treatment of HCC. A novel TRAB targeting GPC3 on HCC tumor cells and the CD3 T-cell receptor as well as a distinct GPC3-specific optical imaging probe were developed from a short peptide. The efficacy of GPC3/CD3 TRAB was evaluated in vitro using IFNγ release and calcein-AM assays. Patient-derived xenografts were used to assess the in vivo efficacy of GPC3/CD3 TRAB and the GPC3 imaging probe for the detection of GPC3+ HCC. GPC3/CD3 TRAB caused a dose-dependent escalation in IFNγ release from inactive peripheral blood T cells (P = 0.001) and higher tumor-cell lysis (P = 0.01) compared with controls in vitro. Intratumorally injected GPC3/CD3 TRAB resulted in significant prolongation of tumor doubling time in the GPC3+ tumors, with an associated reduction of tumor fluorescent signal from the HiLyte 488-conjugated GPC3-specific peptide on optical imaging. These data demonstrate that HCC cell targeting using a GPC3/CD3 TRAB derived from a small peptide enabled effective T-cell activation and induction of a cytotoxic response toward GPC3+ HCC tumor cells both in vitro and in vivo. GPC3-specific optical imaging enabled the detection of the GPC3+ HCC cells and noninvasive monitoring of tumor response to adoptive immunotherapy. The integrated development of a targeted therapeutic and molecular imaging probe provides a promising paradigm for the development of cancer theranostics.

Method for Noise Reduction by Averaging the Filtering Results on Circular Displacements Using Wavelet Transform and Local Binary Pattern

Algorithms for noise reduction that use the translation invariant wavelet transform indirectly are spatially selective filtering algorithms in the wavelet domain. These algorithms use the undecimated wavelet transform to accurately determine the coefficients corresponding to the contours in the images, these being processed differently from the other wavelet coefficients. The use of the undecimated wavelet transform in image noise reduction applications leads not only to an improvement in terms of Mean Square Error (MSE), but also in terms of the content quality of the processed images. In the case of noise reduction procedures by truncation of wavelet coefficients, artifacts appear, especially in the approximation of singularities, due to some pseudo-Gibbs phenomena. These artifacts, which appear locally, are troublesome in the case of object recognition applications from images acquired in conditions of nonuniform illumination and low contrast. In this work we propose a method of feature extractor based on undecimated wavelet transform (UWT) and local binary pattern (LBP). The results obtained on images acquired from drones in adverse conditions show promising results in terms of accuracy. The authors show that the displacement-invariant wavelet transform is an very good method of compression and noise reduction in signals.

Enhanced Electrochemiluminescence of Luminol and-Dissolved Oxygen by Nanochannel-Confined Au Nanomaterials for Sensitive Immunoassay of Carcinoembryonic Antigen.

Simple development of an electrochemiluminescence (ECL) immunosensor for convenient detection of tumor biomarker is of great significance for early cancer diagnosis, treatment evaluation, and improving patient survival rates and quality of life. In this work, an immunosensor is demonstrated based on an enhanced ECL signal boosted by nanochannel-confined Au nanomaterial, which enables sensitive detection of the tumor biomarker-carcinoembryonic antigen (CEA). Vertically-ordered mesoporous silica film (VMSF) with a nanochannel array and amine groups was rapidly grown on a simple and low-cost indium tin oxide (ITO) electrode using the electrochemically assisted self-assembly (EASA) method. Au nanomaterials were confined in situ on the VMSF through electrodeposition, which catalyzed both the conversion of dissolved oxygen (O2) to reactive oxygen species (ROS) and the oxidation of a luminol emitter and improved the electrode active surface. The ECL signal was enhanced fivefold after Au nanomaterial deposition. The recognitive interface was fabricated by covalent immobilization of the CEA antibody on the outer surface of the VMSF, followed with the blocking of non-specific binding sites. In the presence of CEA, the formed immunocomplex reduced the diffusion of the luminol emitter, resulting in the reduction of the ECL signal. Based on this mechanism, the constructed immunosensor was able to provide sensitive detection of CEA ranging from 1 pg·mL-1 to 100 ng·mL-1 with a low limit of detection (LOD, 0.37 pg·mL-1, S/N = 3). The developed immunosensor exhibited high selectivity and good stability. ECL determination of CEA in fetal bovine serum was achieved.

Indirect detection of lead(II), cadmium(II) and mercury(II) on a microfluidic electrophoresis chip.

Water environments contaminated by heavy metal ions present significant challenges because these pollutants do not degrade naturally, leading to their gradual bioaccumulation in animals and plants, which ultimately poses an insurmountable threat to human health. Therefore, rapid and accurate detection of heavy metal ions in water is of great significance for environmental protection and disease prevention. In this work, we developed a novel method based on microfluidic electrophoresis coupled with indirect chemiluminescence for the immediate detection of Cd(II), Pb(II) and Hg(II) heavy metal ions. The displacement of the Co(II) ions within the chemiluminescence mixture by the above migrating sample cations caused a measurable reduction in the background signal. The results showed that the detection limits of Cd(II), Pb(II) and Hg(II) ions under the best detection conditions were 5.83 × 10-8 M, 5.38 × 10-8 M and 2.09 × 10-8 M, respectively, which were 1-2 orders of magnitude lower than those of the indirect UV method and 1 order of magnitude lower than that of the indirect laser induced detection method. This method can provide a possibility for the rapid detection of multiple heavy metal ions in actual water environments.

High-sensitive detection of organophosphate and carbamate pesticide residues in milk based on bioluminescence method

Organophosphorus pesticides (OPs) and carbamate pesticides (CBs) are the most commonly used pesticides in agricultural cultivation. The pesticide residues in plant products can easily enter dairy cows through feed, resulting in the pesticide low-concentration residues in milk. Traditional acetylcholinesterase (AChE) inhibition-based colorimetric methods have low sensitivity and could not satisfy the detection of low-concentrations of OPs and CBs residues in dairy products. In this study, we combined firefly luciferase (FLuc)-mediated bioluminescence with the inhibition of AChE-catalyzed substrate activity by pesticides to develop a highly sensitive and rapid method for detecting OPs and CBs residues in milk. AChE breaks down D-luciferin acetate to produce D-luciferin, which is recognized by the FLuc and emits luminescence in the presence of ATP. However, the presence of OPs and CBs inhibits AChE, causing the reduction or disappearance of the luminescence signal. The luminescence signal can be detected using a hand-held luminescence photometer, eliminating the need for large instrumentation. The AChE-FLuc system accurately detected OPs and CBs in milk within 30 min, with detection limits of 7.89 ng/mL and 1.75 ng/mL, respectively. The sensitivity of this method is approximately ten times higher than that of traditional AChE inhibition methods, meeting the pesticide residue limits in milk set by China and the European Union.

RNA lipid nanoparticles as efficient in vivo CRISPR-Cas9 gene editing tool for therapeutic target validation in glioblastoma cancer stem cells

In vitro and ex-vivo target identification strategies often fail to predict in vivo efficacy, particularly for glioblastoma (GBM), a highly heterogenous tumor rich in resistant cancer stem cells (GSCs). An in vivo screening tool can improve prediction of therapeutic efficacy by considering the complex tumor microenvironment and the dynamic plasticity of GSCs driving therapy resistance and recurrence. This study proposes lipid nanoparticles (LNPs) as an efficient in vivo CRISPR-Cas9 gene editing tool for target validation in mesenchymal GSCs. LNPs co-delivering mRNA (mCas9) and single-guide RNA (sgRNA) were successfully formulated and optimized facilitating both in vitro and in vivo gene editing. In vitro, LNPs achieved up to 67 % reduction in green fluorescent protein (GFP) expression, used as a model target, outperforming a commercial transfection reagent. Intratumoral administration of LNPs in GSCs resulted in ∼80 % GFP gene knock-out and a 2-fold reduction in GFP signal by day 14. This study showcases the applicability of CRISPR-Cas9 LNPs as a potential in vivo screening tool in GSCs, currently lacking effective treatment. By replacing GFP with a pool of potential targets, the proposed platform presents an exciting prospect for therapeutic target validation in orthotopic GSCs, bridging the gap between preclinical and clinical research.

Study of Noise Reduction and Identification of Internal Damage Signals in Wire Ropes

Mining wire rope, a frequently used load-bearing element, suffers various forms of damage over extended periods of operation. Damage occurring within the wire rope, which is not visible to the naked eye and is difficult to detect accurately with current technology, is of particular concern. Consequently, the identification of internal damage assumes paramount importance in ensuring mine safety. This study proposes a wire rope internal damage noise reduction and identification method, first of all, through a three-dimensional magnetic dipole model to achieve the detection and analysis of the internal damage of the wire rope. Simultaneously, a sensor system capable of accurately detecting the internal damage of wire rope is developed and validated through experimentation. A novel approach is proposed to address the noise reduction issue in the design process. This approach utilizes a particle swarm optimization variational modal decomposition method to enhance the signal-to-noise ratio. Additionally, a dual-attention mode, which combines channel attention and spatial attention, is integrated into the CNN-GRU network model. This network model is specifically designed for the detection of internal damage in steel wire ropes. The proposed method successfully achieves quantitative identification of internal damage in steel wire ropes. The experimental findings demonstrate that this approach is capable of efficiently detecting internal damage in wire rope and possesses the capacity to quantitatively identify such damage, enabling adaptive identification of wire rope.

Wall conditions in WEST during operations with a new ITER grade, actively cooled divertor

Future fusion reactors like ITER and DEMO will have all-tungsten (W) walls and long pulses. These features will make wall conditioning more difficult than in most of the existing devices. The W Environment Steady-state Tokamak (WEST) is one of the few long pulse (364 s) fusion devices with actively cooled W plasma-facing components in the world. WEST is a unique test bed to study impurity migration and plasma density control via reactor relevant wall conditioning techniques. The phase II of WEST operations began in 2022, after the installation of a new lower divertor, now entirely equipped with actively cooled, ITER grade, W monoblocks. After pump down, we baked WEST between 90 °C and 170 °C for ∼2 weeks. After 82.5 h at 90 °C and 33 h at 170 °C, vacuum conditions were stable with a vessel pressure of 6x10-5 Pa and mass spectra dominated by H2 molecules. While at 170 °C, we performed ∼40 h of D2 glow discharge cleaning (GDC) and ∼5 h of glow discharge boronization (GDB), using a 15 %-85 % B2D6-He mix and a total boron mass of ∼12 g. This was the very first GDB at such high temperature for WEST. The whole wall conditioning sequence led to a ∼10 times reduction of the H2O signal as well as to a ∼3 times reduction of the O2 signal, according to mass spectra. Once back to 70 °C, the vessel pressure was 5.5x10-6 Pa and plasma restart was seamless with ∼30 s cumulated over the very first 5 pulses and an Ohmic radiated power fraction Frad = 0.6, showing successful conditioning of the new ITER grade divertor. The effect of the first, ‘hot’ GDB faded with a characteristic cumulative injected energy of 2.45 GJ and saturation towards Frad ∼0.8. After 1.4 h and 7.5 GJ of cumulative plasma time and injected energy, we carried out a second GDB, this time at 70 °C. This ‘cold’ GDB initially led to a much lower Ohmic Frad = 0.3–0.4 but the effect lasted ∼7 times less, with a characteristic cumulative injected energy of 0.37 GJ. At the end of the campaign, we cumulated ∼3h and ∼30 GJ through repetitive, minute long pulses without any boronization. Throughout this 4-weeks-long experiment, Frad in the 4 MW heating phase evolved only marginally (from 0.5 to 0.55). This increase is mostly due to the build-up of re/co-deposited layers on both lower divertor targets.

Boronic acid ester-based hydrogel as surface-enhanced Raman scattering substrates for separation, enrichment, hydrolysis and detection of hydrogen peroxide residue in dairy product all-in-one

Rapid and selective separation, enrichment and detection of trace residue all-in-one in complex samples is a major challenge. Hydrogels with molecular sieve properties can selectively separate and enrich target analytes, and the combination with high sensitivity detection of surface-enhanced Raman scattering (SERS) is expected to achieve the above all-in-one detection. Herein, the core-shell structured Au@poly(N-isopropylacrylamide)-phenylboronic acid hydrogel (Au@PNIP-VBA) with boronic acid ester groups was prepared by thermally initiated polymerization. The boronic acid ester groups in hydrogel are selectively hydrolyzed by hydrogen peroxide (H2O2) to hydroxyl structures, leading to a reduction in SERS signals. The Au@PNIP-VBA hydrogel has molecular sieve properties and high SERS activity, making it suitable for separation, enrichment, hydrolysis and detection of H2O2 all-in-one. A rapid SERS method was developed for analysis of H2O2 based on the Au@PNIP-VBA hydrogel with the linear range of 8.5 × 10−2-6.8 mg L−1 and the detection limit of 33 μg L−1. The method was successfully applied to the determination of H2O2 residue in fresh milk, pure milk, yogurt and camel milk, with the recoveries were in the range of 82.2%–109.3% and the relative standard deviations were 2.8%–8.3%. This efficient all-in-one strategy has the advantages of simple sample pre-treatment, rapid analysis (30 min) and high sensitivity, making it highly promising for food quality and safety analysis.

Ce-doped magnesium borate glass-ceramic for optically stimulated luminescence dosimetry

Despite intensive research in optically stimulated luminescence (OSL) dosimetry, the number of materials with suitable properties for practical application remains limited. Among these, magnesium tetraborate (MgB4O7) has attracted attention as a potential host because of its effective atomic number, similar to those of water and living tissues, and the possibility of producing neutron-sensitive material by controlling the content of the 10B isotope. Specifically, Ce-doped MgB4O7 has been proposed as a promising OSL material for 2D dosimetry because of its rapid luminescence. While the literature on polycrystalline sintered MgB4O7:Ce is extensive, the objective of this work is to produce this material in glass-ceramic form, offering many advantages such as excellent formability into complex shapes, rapid mass production, easily controlled microstructure, and higher density (zero porosity) compared to conventional powder-sintered materials, potentially leading to dosimetric improvements. This paper describes the synthesis route and the effects of various thermal treatments of magnesium borate glass and the resulting glass-ceramics, along with their fundamental dosimetric properties. The samples heat-treated at 814 °C for 3 h (GC814) exhibited the most intense and stable thermoluminescence peaks, accounting for their lowest signal fading among the investigated treatment conditions. However, during the OSL readout, diminished intensity was observed. Analysis of the GC814 emission spectrum revealed TL peaks predominantly outside the used optical filter's primary transmittance range, likely contributing to the OSL signal reduction. Regardless of the thermal-treatment condition, all the samples presented excellent repeatability of the OSL response, with standard deviations ranging from 0.1 % to 0.7 %, underscoring the advantages of glass-ceramics over sintered ceramics. From step-annealing analysis, an optimal preheat treatment temperature was identified, and the activation energy of the three main peaks was determined. The encouraging results indicate the potential of this glass-ceramic as a practical OSL dosimeter and justify further investigation to optimize its OSL properties.

Design of a triple-functional polyA-probe: Toward a facile electrochemical aptasensor for vanillin detection

This study successfully developed an electrochemical aptasensor based on a triple-functional biotin-modified poly-adenine (polyA) probe (Bio-TPP) for one-step ultrasensitive detection of vanillin (VAN). The Bio-TPP was self-assembled onto a gold electrode (AuE) via its polyA sequence, followed by conjugation with PtPd@Ni-Co layered double hydroxides labeled with streptavidin and thionine (SA/Thi/PtPd@Ni-Co LDH), which generated electrochemical signals. Importantly, in the presence of VAN, the specific substrate sequence of a Mg²⁺-dependent DNAzyme in the Bio-TPP hybridized with the output DNAzyme strand generated by the specific recognition between the aptamer (Apt) and VAN. And, with the help of Mg²⁺, the DNAzyme amplification reaction was triggered. This led to a significant reduction in the electrochemical signals, enabling highly sensitive detection of VAN. Benefiting from the precise and flexible design of the Bio-TPP, this aptasensor offered a new detection method, exhibiting excellent performance with a wide linear range of 1×10−6-10 μM and a detection limit of 0.30 pM. Additionally, this assay possessed good selectivity, reproducibility, and stability, which held great potential in bioanalysis.