Signal Variations Research Articles

Phylogenomic data resolved the deep relationships of Gymnogynoideae (Selaginellaceae).

The unresolved phylogenetic framework within the Selaginellaceae subfamily Gymnogynoideae (ca. 130 species) has hindered our comprehension of the diversification and evolution of Selaginellaceae, one of the most important lineages in land plant evolution. Here, based on plastid and nuclear data extracted from genomic sequencing of more than 90% species of all genera except two in Gymnogynoideae, a phylogenomic study focusing on the contentious relationships among the genera in Gymnogynoideae was conducted. Our major results included the following: (1) Only single-copy region (named NR) and only one ribosomal operon was firstly found in Afroselaginella among vascular plants, the plastome structure of Gymnogynoideae is diverse among the six genera, and the direct repeats (DR) type is inferred as the ancestral state in the subfamily; (2) The first strong evidence was found to support Afroselaginella as a sister to Megaloselaginella. Alternative placements of Ericetorum and Gymnogynum were detected, and their relationships were investigated by analyzing the variation of phylogenetic signals; and (3) The most likely genus-level relationships in Gymnogynoideae might be: ((Bryodesma, Lepidoselaginella), (((Megaloselaginella, Afroselaginella), Ericetorum), Gymnogynum)), which was supported by maximum likelihood phylogeny based on plastid datasets, maximum likelihood, and Bayesian inference based on SCG dataset and concatenated nuclear and plastid datasets and the highest proportion of phylogenetic signals of plastid genes.

Optimization of micelle-encapsulated extremely small sized iron oxide nanoparticles as a T1 contrast imaging agent: biodistribution and safety profile

BackgroundIron oxide nanoparticles (IONPs) have been cleared by the Food and Drug Administration (FDA) for various clinical applications, such as tumor-targeted imaging, hyperthermia therapy, drug delivery, and live-cell tracking. However, the application of IONPs as T1 contrast agents has been restricted due to their high r2 values and r2/r1 ratios, which limit their effectiveness in T1 contrast enhancement. Notably, IONPs with diameters smaller than 5 nm, referred to as extremely small-sized IONPs (ESIONs), have demonstrated potential in overcoming these limitations. To advance the clinical application of ESIONs as T1 contrast agents, we have refined a scale-up process for micelle encapsulation aimed at improving the hydrophilization of ESIONs, and have carried out comprehensive in vivo biodistribution and preclinical toxicity assessments.ResultsThe optimization of the scale-up micelle-encapsulation process, specifically employing Tween60 at a concentration of 10% v/v, resulted in ESIONs that were uniformly hydrophilized, with an average size of 9.35 nm and a high purification yield. Stability tests showed that these ESIONs maintained consistent size over extended storage periods and dispersed effectively in blood and serum-mimicking environments. Relaxivity measurements indicated an r1 value of 3.43 mM− 1s− 1 and a favorable r2/r1 ratio of 5.36, suggesting their potential as T1 contrast agents. Biodistribution studies revealed that the ESIONs had extended circulation times in the bloodstream and were primarily cleared via the hepatobiliary route, with negligible renal excretion. We monitored blood clearance and organ distribution using positron emission tomography and magnetic resonance imaging (MRI). Additionally, MRI signal variations in a dose-dependent manner highlighted different behaviors at varying ESIONs concentrations, implying that optimal dosages might be specific to the intended imaging application. Preclinical safety evaluations indicated that ESIONs were tolerable in rats at doses up to 25 mg/kg.ConclusionsThis study effectively optimized a scale-up process for the micelle encapsulation of ESIONs, leading to the production of hydrophilic ESIONs at gram-scale levels. These optimized ESIONs showcased properties conducive to T1 contrast imaging, such as elevated r1 relaxivity and a reduced r2/r1 ratio. Biodistribution study underscored their prolonged bloodstream presence and efficient clearance through the liver and bile, without significant renal involvement. The preclinical toxicity tests affirmed the safety of the ESIONs, supporting their potential use as T1 contrast agent with versatile clinical application.

Temperature-Sensitive Sensors Modified with Poly(N-isopropylacrylamide): Enhancing Performance through Tailored Thermoresponsiveness.

The development of temperature-sensitive sensors upgraded by poly(N-isopropylacrylamide) (PNIPAM) represents a significant stride in enhancing performance and tailoring thermoresponsiveness. In this study, an array of temperature-responsive electrochemical sensors modified with different PNIPAM-based copolymer films were fabricated via a "coating and grafting" two-step film-forming technique on screen-printed platinum electrodes (SPPEs). Chemical composition, grafting density, equilibrium swelling, surface wettability, surface morphology, amperometric response, cyclic voltammograms, and other properties were evaluated for the modified SPPEs, successively. The modified SPPEs exhibited significant changes in their properties depending on the preparation concentrations, but all the resulting sensors showed excellent stability and repeatability. The modified sensors demonstrated favorable sensitivity to hydrogen peroxide and L-ascorbic acid. Furthermore, notable temperature-induced variations in electrical signals were observed as the electrodes were subjected to temperature fluctuations above and below the lower critical solution temperature (LCST). The ability to reversibly respond to temperature variations, coupled with the tunability of PNIPAM's thermoresponsive properties, opens up new possibilities for the design of sensors that can adapt to changing environments and optimize their performance accordingly.

Identification method of circumferential declination based on amplitude reduction of pipeline ultrasonic internal inspection signals

ABSTRACT The echo signal of ultrasonic internal inspection is highly sensitive to the incident deflection angle between the probe and the measured surface of the pipeline, which is the key factor affecting the accuracy of ultrasonic inspection. In practical engineering, the echo signal of ultrasonic inspection is easy to be interfered by the external environment, which makes it difficult to identify the deflection angle. The data of defect echo signal under different circumferential declination were collected by the pipeline ultrasonic internal inspection system, and the characteristics of signal variation in time domain under different circumferential declination were analysed. The results show that the existence of circumferential declination reduced the absolute value of the overall amplitude of ultrasonic echo signal. A signal processing method based on amplitude reduction is proposed to reduce the sampling random error. Comparative analysis shows that the circumferential declination can be identified based on amplitude reduction method, and the accuracy of ultrasonic recognition can be improved. By extracting the characteristic value of waveform, the empirical formula is obtained. Within 2°, the maximum deviation is 0.137°. The research results have certain guiding significance for the identification of circumferential declination in practical engineering.

Unraveling psilocybin's therapeutic potential: behavioral and neuroplasticity insights in Wistar-Kyoto and Wistar male rat models of treatment-resistant depression.

Our study aimed to unravel the unknown mechanisms behind the exceptional efficacy of Psilocybin (PSI) in treating treatment-resistant depression (TRD). Focusing on Wistar-Kyoto (WKY) rats with a TRD phenotype and Wistar (WIS) rats as a normative comparison, we investigated behavioral and neuroplasticity-related responses to PSI, striving to shed light on the distinctive features of its antidepressant effects. We set out to assess the behavioral impact of acute and prolonged PSI administration on WKY and WIS rats, employing Novel Object Recognition (NORT), Social Interaction (SI), and Forced Swimming Test (FST). Our secondary objectives involved exploring strain-specific alterations in neuroplasticity-related parameters, including brain-derived neurotrophic factor (BDNF) and activity-regulated cytoskeleton-associated protein (Arc). Conducting post-acute and extended assessments after a single PSI administration, we applied behavioral tests and biochemical analyses to measure serum BDNF levels and neuroplasticity-related parameters in the prefrontal cortex. Statistical analyses were deployed to discern significant differences between the rat strains and assess the impact of PSI on behavioral and biochemical outcomes. Our findings uncovered significant behavioral disparities between WKY and WIS rats, indicating passive behavior and social withdrawal in the former. PSI demonstrated pronounced pro-social and antidepressant effects in both strains, each with its distinctive temporal trajectory. Notably, we identified strain-specific variations in BDNF-related signaling and observed the modulation of Arc expression in WKY rats. Our study delineated mood-related behavioral nuances between WKY and WIS rat strains, underscoring the antidepressant and pro-social properties of PSI in both groups. The distinct temporal patterns of observed changes and the identified strain-specific neuroplasticity alterations provide valuable insights into the TRD phenotype and the mechanisms underpinning the efficacy of PSI.

Social fish use different submission signals depending on spatial position

Abstract Animals often possess multiple distinct threat signals which indicate their level of aggressive motivation or resource holding potential. In contrast, the diversity of submission signals is considerably lower. Still, some social species exhibit multiple distinct submission signals which could have different strategic functions or serve to enhance signal transmission. In the current study, we examine submission signalling in the daffodil cichlid (Neolamprologus pulcher), a cooperatively breeding fish which produces two distinct submission signals: a tail quiver, and a head-up posture. Observing interactions within stable social groups revealed that submission signal selection depends on the location of the interaction, with tail quivers being preferentially displayed near the substrate, and head-up postures being deployed when the interaction takes place further away from the substrate. Our findings suggest that variation in submission signalling in daffodil cichlids may serve to enhance signal transmission across spatial contexts rather than to convey distinct information.

Simple hydrated electron-induced electrochemiluminescence determination of alkaline phosphatase with novel time-resolved internal standard strategy at boron doped diamond electrodes

Hydrated electrons were generated at boron doped diamond electrodes in fully aqueous solutions during cathodic pulse polarization and utilized for the electrochemiluminescence (ECL) determination of alkaline phosphatase (ALP) by adapting one of the most common fluorescent methods. In this approach, highly fluorescent 4-methylumbelliferyl (MU) is enzymatically generated from non-fluorescent 4-methylumbelliferyl phosphate (MUP) substrate and chemically excited in the presence of oxidizing radicals and reducing hydrated electrons. A novel time-resolved internal standard strategy is presented to counter matrix effects to certain degree and to lower signal variation among concurrent measurements. In this unique approach, the cathodic ECL signals of MU and Tb(III)-chelate were separated on the basis of their exceptionally different excited state lifetimes. This enabled more precise determination of ALP by simply measuring the ratio of ECL emissions during and after cathodic excitation pulse with simple two-electrode, single photomultiplier tube setup. The ratiometric ECL signals in the absence and presence of 1.0 % serum (v/v) were interchangeable whereas ratiometric signal recovery in the presence of 10.0 % serum was ∼85 %.

Influence of detector temperature on Doppler signal quality of laser Doppler velocimeter

Enhancing the quality of Doppler signal holds paramount importance for the utilization of Laser Doppler Veolcimeter in velocity measurement of high-speed vehicles, underwater vehicles, and aerial vehicles. This paper discusses the variation of Doppler signal and noise with bias voltage at different temperatures, ultimately deriving the relationship between the signal-to-noise ratio of Doppler signal and detector temperature as well as bias voltage. And a linear correlation is established between detector temperature and optimal bias voltage. Furthermore, A bias control circuit for temperature compensation is designed for maximizing signal-to-noise ratio of Laser Doppler Velocimeter under varying temperatures.

Fault detection and isolation for multi-type sensors in nuclear power plants via a knowledge-guided spatial–temporal model

Sensor faults in nuclear power plants (NPPs) have the potential to propagate negative impacts on system stability, leading to false alarms and accident misdiagnosis. Existing methods seldom concurrently consider complex spatial–temporal correlations among multi-type sensors in the primary circuit. This study presents a novel sensor fault detection and isolation scheme named the knowledge-guided spatial–temporal model (KGSTM), using the knowledge-guided recurrent unit (KGRU) and the concurrent detection strategy. To organically express part and whole interdependencies from inherent sensor layout, several graphs are specifically designed with pertinent domain knowledge. KGRU consists of the multi-graph convolutional network (MGCN) for fusing various spatial information and the gate recurrent unit (GRU) for extracting dynamic temporal features, further obtaining precise reconstructed signals and residuals. The concurrent detection strategy can explicitly quantify abnormal behaviors to detect and isolate faulty sensors by characterizing spatial–temporal signal variation. Numerical results on two real-world datasets from a pressurized water reactor (PWR) with simulated faults illustrate that the KGSTM has superior performance over various state-of-the-art methods in terms of signal reconstruction and fault detection.

Determination of the vector velocity of artificial ionospheric irregularities based on Doppler measurements by the bi-static scatter method of HF radio signals propagating over long radio paths

During experiments on the modification of the high-latitude ionosphere by high-power HF radio waves of ordinary or extraordinary polarization of the EISCAT/Heating facility (Tromsø, Norway) in 2013, 2016, and 2019, Doppler measurements of diagnostic HF radio signals over long radio paths were carried out by the bistatic scatter method. We studied characteristics of Doppler frequency variations in bistatic scattered radio signals, using the experimental results obtained along radio paths of different lengths (up to ~8500 km) and orientation. We examined numerical dependences of the Doppler frequency variations in a radio signal on the azimuth of the wave vector of a radio wave incident onto an artificially disturbed region, on the bistatic scattering angle, and on the azimuthal direction of irregularity motion in an artificially disturbed region of the ionosphere. From simultaneous measurements of the Doppler frequency fD of the radio signal along two diagnostic radio paths, we numerically estimated the velocity vector of irregularities in the artificially disturbed region of the ionosphere. The total vector velocity of artificial ionospheric irregularities can be calculated from measurements of the Doppler frequency shift along several long diagnostic radio paths after preliminary analysis of experimental observations with the results of trajectory modeling of diagnostic HF radio signals.

Определение вектора скорости искусственных ионосферных неоднородностей по данным доплеровских измерений методом ракурсного рассеяния КВ радиосигналов, распространяющихся на протяженных радиотрассах

During experiments on the modification of the high-latitude ionosphere by high-power HF radio waves of ordinary or extraordinary polarization of the EISCAT/Heating facility (Tromsø, Norway) in 2013, 2016, and 2019, Doppler measurements of diagnostic HF radio signals over long radio paths were carried out by the bistatic scatter method. We studied characteristics of Doppler frequency variations in bistatic scattered radio signals, using the experimental results obtained along radio paths of different lengths (up to ~8500 km) and orientation. We examined numerical dependences of the Doppler frequency variations in a radio signal on the azimuth of the wave vector of a radio wave incident onto an artificially disturbed region, on the bistatic scattering angle, and on the azimuthal direction of irregularity motion in an artificially disturbed region of the ionosphere. From simultaneous measurements of the Doppler frequency fD of the radio signal along two diagnostic radio paths, we numerically estimated the velocity vector of irregularities in the artificially disturbed region of the ionosphere. The total vector velocity of artificial ionospheric irregularities can be calculated from measurements of the Doppler frequency shift along several long diagnostic radio paths after preliminary analysis of experimental observations with the results of trajectory modeling of diagnostic HF radio signals.

Middle-Late Holocene climate change in an East Asian sandy land: Perspectives from the phytolith record of different geomorphic units

The accuracy of the regional palaeoclimate reconstruction is vital for ecological restoration and future climate predictions. Clarifying the regional climate signal on different geomorphological units within the same region plays a key role in regional climate researches. Here, we select the Horqin Sandy Land as the research area, and collect sedimentary from two typical geomorphological units (interdune lowlands: ML profile, DBS profile; dunes: CS profile, FX profile) as the research objects. The regional averaging method is employed to isolate distinct climate signals originating from interdune lowlands (IC-Score (Peat)) and dunes (IC-Score (Dune)), alongside an amalgamated climate signal (IC-Score (Peat&Dune)) synthesized from these two geomorphological units. This methodological approach facilitates the identification of variations in climate signals that collectively encapsulate the broader regional context. Meanwhile, local microclimate signals from dunes (IC-D-Value (Dune)) and interdune lowlands (IC-D-Value (Peat)) were separately analyzed to examine microclimate changes on different geomorphological units. The results indicate that different sedimentary carriers on various geomorphological units capture the local climate characteristics of their own units while recording regional climate changes. IC-D-Value (Peat) reflects ‘warm-humid’ climate, and IC-D-Value (Dune) represents ‘cold-dry’ climate. Climate signals derived from diverse geomorphological units exhibit the capacity to portray overarching regional climate patterns, yet they manifest variations concerning both semi-quantitative and quantitative climate parameters, notably temperature and precipitation. A regional average method is used to synthesize climate signals from different geomorphological units, which is more advantageous in documenting regional climate change. Regional climate signal reveals a change from warm-humid (9300 ∼ 4000 cal yr BP) to cold-dry (4000 ∼ 2000 cal yr BP) and then to slightly warm-humid (2000 ∼ 560 cal yr BP). Furthermore, regional climate signal shows the significant ∼ 2000-yr，∼1000-yr, ∼500-yr periodicities since 7300 cal yr BP, and solar activities are identified as one of the important driving factors.

The relative brain signal variability increases in the behavioral variant of frontotemporal dementia and Alzheimer's disease but not in schizophrenia.

Overlapping symptoms between Alzheimer's disease (AD), behavioral variant of frontotemporal dementia (bvFTD), and schizophrenia (SZ) can lead to misdiagnosis and delays in appropriate treatment, especially in cases of early-onset dementia. To determine the potential of brain signal variability as a diagnostic tool, we assessed the coefficient of variation of the BOLD signal (CVBOLD) in 234 participants spanning bvFTD (n = 53), AD (n = 17), SZ (n = 23), and controls (n = 141). All underwent functional and structural MRI scans. Data unveiled a notable increase in CVBOLD in bvFTD patients across both datasets (local and international, p < 0.05), revealing an association with clinical scores (CDR and MMSE, r = 0.46 and r = -0.48, p < 0.0001). While SZ and control group demonstrated no significant differences, a comparative analysis between AD and bvFTD patients spotlighted elevated CVBOLD in the frontopolar cortices for the latter (p < 0.05). Furthermore, CVBOLD not only presented excellent diagnostic accuracy for bvFTD (AUC 0.78-0.95) but also showcased longitudinal repeatability. During a one-year follow-up, the CVBOLD levels increased by an average of 35% in the bvFTD group, compared to a 2% increase in the control group (p < 0.05). Our findings suggest that CVBOLD holds promise as a biomarker for bvFTD, offering potential for monitoring disease progression and differentiating bvFTD from AD and SZ.

A scan-specific quality control acquisition for clinical whole-body (WB) MRI protocols

Objective. Image quality in whole-body MRI (WB-MRI) may be degraded by faulty radiofrequency (RF) coil elements or mispositioning of the coil arrays. Phantom-based quality control (QC) is used to identify broken RF coil elements but the frequency of these acquisitions is limited by scanner and staff availability. This work aimed to develop a scan-specific QC acquisition and processing pipeline to detect broken RF coil elements, which is sufficiently rapid to be added to the clinical WB-MRI protocol. The purpose of this is to improve the quality of WB-MRI by reducing the number of patient examinations conducted with suboptimal equipment. Approach. A rapid acquisition (14 s additional acquisition time per imaging station) was developed that identifies broken RF coil elements by acquiring images from each individual coil element and using the integral body coil. This acquisition was added to one centre’s clinical WB-MRI protocol for one year (892 examinations) to evaluate the effect of this scan-specific QC. To demonstrate applicability in multi-centre imaging trials, the technique was also implemented on scanners from three manufacturers. Main results. Over the course of the study RF coil elements were flagged as potentially broken on five occasions, with the faults confirmed in four of those cases. The method had a precision of 80% and a recall of 100% for detecting faulty RF coil elements. The coil array positioning measurements were consistent across scanners and have been used to define the expected variation in signal. Significance. The technique demonstrated here can identify faulty RF coil elements and positioning errors and is a practical addition to the clinical WB-MRI protocol. This approach was fully implemented on systems from two manufacturers and partially implemented on a third. It has potential to reduce the number of clinical examinations conducted with suboptimal hardware and improve image quality across multi-centre studies.

Real-Time Cardiac Abnormality Monitoring and Nursing for Patient Using Electrocardiographic Signals.

Cardiovascular disease nursing is a critical clinical application that necessitates real-time monitoring models. Previous models required the use of multi-lead signals and could not be customized as needed. Traditional methods relied on manually designed supervised algorithms, based on empirical experience, to identify waveform abnormalities and classify diseases, and were incapable of monitoring and alerting abnormalities in individual waveforms. This research reconstructed the vector model for arbitrary leads using the phase space-time-delay method, enabling the model to arbitrarily combine signals as needed while possessing adaptive denoising capabilities. After employing automatically constructed machine learning algorithms and designing for rapid convergence, the model can identify abnormalities in individual waveforms and classify diseases, as well as detect and alert on abnormal waveforms. Effective noise elimination was achieved, obtaining a higher degree of loss function fitting. After utilizing the algorithm in Section 3.1 to remove noise, the signal-to-noise ratio increased by 8.6%. A clipping algorithm was employed to identify waveforms significantly affected by external factors. Subsequently, a network model established by a generative algorithm was utilized. The accuracy for healthy patients reached 99.2%, while the accuracy for APB was 100%, for LBBB 99.32%, for RBBB 99.1%, and for P-wave peak 98.1%. By utilizing a three-dimensional model, detailed variations in electrocardiogram signals associated with different diseases can be observed. The clipping algorithm is effective in identifying perturbed and damaged waveforms. Automated neural networks can classify diseases and patient identities to facilitate precision nursing.

Droplet Micro-Sensor and Detection of Respiratory Droplet Transmission.

Droplet transmission is the primary infection route for respiratory diseases like COVID-19 and influenza, but small and low-cost wearable droplet detection devices are a significant challenge. Herein, a respiratory droplet micro-sensor based on graphene oxide quantum dots (GOQDs) assembled onto SiO2 microspheres by the nebulized natural deposition is presented. Benefiting from the energy dissipation of the microsphere to droplets, the sensor can detect droplets as far as 2 m from coughing. With this sensor, droplet signal variations caused by some factors like distance, speech, angles, and wind directions are explored, and the effectiveness of different protective measures in preventing droplet transmission is evaluated. This droplet detection technology is expected to be utilized for the development of personal detection and protection devices against infectious respiratory diseases.

A Pressure and Proximity Sensor Based on Laser-Induced Graphene.

Smart wearable devices are extensively utilized across diverse domains due to their inherent advantages of flexibility, portability, and real-time monitoring. Among these, flexible sensors demonstrate exceptional pliability and malleability, making them a prominent focus in wearable electronics research. However, the implementation of flexible wearable sensors often entails intricate and time-consuming processes, leading to high costs, which hinder the advancement of the entire field. Here, we report a pressure and proximity sensor based on oxidized laser-induced graphene (oxidized LIG) as a dielectric layer sandwiched by patterned LIG electrodes, which is characterized by high speed and cost-effectiveness. It is found that in the low-frequency range of fewer than 0.1 kHz, the relative dielectric constant of the oxidized LIG layer reaches an order of magnitude of 104. The pressure mode of this bimodal capacitive sensor is capable of detecting pressures within the range of 1.34 Pa to 800 Pa, with a response time of several hundred milliseconds. The proximity mode involves the application of stimulation using an acrylic probe, which demonstrates a detection range from 0.05 mm to 37.8 mm. Additionally, it has a rapid response time of approximately 100 ms, ensuring consistent signal variations throughout both the approach and withdrawal phases. The sensor fabrication method proposed in this project effectively minimizes expenses and accelerates the preparation cycle through precise control of laser processing parameters to shape the electrode-dielectric layer-electrode within a single substrate material. Based on their exceptional combined performance, our pressure and proximity sensors exhibit significant potential in practical applications such as motion monitoring and distance detection.

Investigating luminescence-depth profiles from rocks with different lithologies

Understanding of the attenuation of light into a rock surface is fundamental to the successful modelling of the luminescence profile in rock resulting from prolonged daylight exposure. Here, we investigate this light attenuation. Variations in apparent attenuation is first examined using the variation of luminescence signals with depth, modelled in two different ways to obtain attenuation coefficients. These results are compared with direct measurement of optical attenuation for three different rock types (sandstone, basalt, and granite). We conclude that global fitting of different exposure times using a constant but unknown μ gives rise to larger errors than free fitting, where we allow μ to be different for each exposure time. Our results show that because of differences in lithology and distribution of luminescent minerals, the direct measurement of optical attenuation overestimates the attenuation based on luminescence signals.

Portable Saliva Sensor Based on Dual Recognition Elements for Detection of Caries Pathogenic Bacteria.

Dental caries is one of the most common diseases affecting more than 2 billion people's health worldwide. In a clinical setting, it is challenging to predict and proactively guard against dental cavities prior to receiving a confirmed diagnosis. Streptococcus mutans (S. mutans) in saliva has been recognized as the main causative bacterial agent that causes dental caries. High sensitivity, good selectivity, and a wide detection range are incredibly important factors to affect S. mutans detection in practical applications. In this study, we present a portable saliva biosensor designed for the early detection of S. mutans with the potential to predict the occurrence of dental cavities. The biosensor was fabricated using a S. mutans-specific DNA aptamer and S. mutans-imprinted polymers. Methylene blue was utilized as a redox probe in the sensor to generate current signals for analysis. When S. mutans enters complementarily S. mutans cavities, it blocks electron transfer between methylene blue and the electrode, resulting in decreases in the reduction current signal. The signal variations are associated with S. mutans concentrations that are useful for quantitative analysis. The linear detection range of S. mutans is 102-109 cfu mL-1, which covers the critical concentration of high caries risk. The biosensor exhibited excellent selectivity toward S. mutans in the presence of other common oral bacteria. The biosensor's wide detection range, excellent selectivity, and low limit of detection (2.6 cfu mL-1) are attributed to the synergistic effect of aptamer and S. mutans-imprinted polymers. The sensor demonstrates the potential to prevent dental caries.

Variation of stable isotope signals in precipitation during Typhoon In-Fa (2021), Eastern China

ABSTRACT High-resolution stable isotope precipitation records are crucial for understanding the mechanism of isotope variations during typhoon precipitation events. We present hourly stable isotope time series of precipitation during Typhoon InFa (2021) in Kunshan and Yangzhou, in the lower reaches of the Yangtze River, Eastern China. Precipitation δ18O in Kunshan and Yangzhou ranged from −1.3‰ to −12.3‰ and −2.8‰ to −17.1‰, respectively. Both δ18O time series shifted to more negative values as the typhoon approached. The evolution of precipitation δ18O during the typhoon is likely caused by a combination of Rayleigh distillation and microphysical processes. Precipitation δ18O values in Yangzhou are more negative than those in Kunshan with a lag of ~14 h. This was mainly controlled by further continuous rainout processes during the movement of Typhoon InFa from Kunshan to Yangzhou and higher condensation efficiency. This study improves our understanding of the mechanisms underlying stable isotope changes during typhoon precipitation.