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Velocimetry of a motion target within 3‐D space is highly desirable in numerous applicable realms, ranging from explosion and shock wave physics, aerospace engineering to astronomical surveys. However, it is challenging to achieve synchronous, real‐time, and photon‐counting 3‐D velocimetry in modern frameworks as they either require separate multi‐directional detections, and cumbersome calculation processes or are confined to achieve in situ measurements. Here, a new conceptual paradigm is proposed to circumvent these constraints using orbital‐angular‐momentum (OAM)‐driven multi‐point Doppler effect at the photon‐counting level. This scheme, emanating from a single‐direction launch of an on‐demand engineered sequence OAM light mode onto a motion surface, enables simultaneous and independent detections of time‐varying Doppler photon‐count events from three orthogonal echo light paths. Concretely, at the range of motion velocity of 0.25–0.5 ms−1, the relative measurement errors of this proof‐of‐principle prototype are below 1.5%, thus achieving high‐accuracy 3‐D velocimetry at the photon‐counting level for the first time. The exploration of the OAM‐photon‐counting 3‐D velocimetry techniques provides unprecedented advantages in potential applications of synchronous, real‐time, high‐efficiency, and long‐range quantum lidar. [ABSTRACT FROM AUTHOR]

Swab sampling is a common method for recovering microbes on various environmental surfaces. Its successful application for a specific target depends on the proper swab method and the following detection assay. Herein, we evaluated critical factors influencing surface swab sampling, aiming to achieve the optimal detection and quantification performance of optical detection for bacterial cells on stainless-steel surfaces. Our results showed the recovery rate of Salmonella enterica (SE1045) cells from the 10 × 10 cm2 stainless-steel surface reached up to 92.71 ± 2.19% when using ammonia bicarbonate-moistened polyurethane foam swabs for gentle collection, followed by ultrasound-assisted release in NH4HCO3 solution. Among the six different foam swabs, the Puritan™ Sterile Large Foam Swab contributed the lowest background noise and highest recovery efficiency when integrated with the optical detection assay. Notably, our method exhibited a strong linear relationship (r 2 = 0.9983) between the detected cell numbers and the theoretical number of SE1045 cells seeded on surfaces in the range of 104–107 Colony Forming Units (CFU), with a limit of detection of 7.2 × 104 CFU 100 cm−2. This integration was completed within 2 h, exhibiting the applicable potential in various settings. [ABSTRACT FROM AUTHOR]

Owing to the unique quantum size effect and surface effect, gold-based nanomaterials (GNMs) are promising for pathogen detection and broad-spectrum antimicrobial activity. This review summarizes recent research on GNMs as sensors for detecting pathogens and as tools for their elimination. Firstly, the need for pathogen detection is briefly introduced with an overview of the physicochemical properties of gold nanomaterials. And then strategies for the application of GNMs in pathogen detection are discussed. Colorimetric, fluorescence, surface-enhanced Raman scattering (SERS) techniques, dark-field microscopy detection and electrochemical methods can enable efficient, sensitive, and specific pathogen detection. The third section describes the antimicrobial applications of GNMs. They can be used for antimicrobial agent delivery and photothermal conversion and can act synergistically with photosensitizers to achieve the precise killing of pathogens. In addition, GNMs are promising for integrated pathogen detection and treatment; for example, combinations of colorimetric or SERS detection with photothermal sterilization have been demonstrated. Finally, future outlooks for the applications of GNMs in pathogen detection and treatment are summarized. [ABSTRACT FROM AUTHOR]

The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as smart dust. Several efforts focused primarily on computing and networking capabilities, but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data were processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation, and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change in the refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. Furthermore, experiments were conducted to detect the flow field of a propeller wake. The experimental results indicate that the wake dissipation times of the propeller in a strong density-stratified water environment are approximately 800 s and 750 s. Following the stabilisation of the wake field density, the laser spot position is observed to be stable at 0.341 mm and 0.441 mm, respectively, with a corresponding refractive index change of 2.99 × 10−6 RIU (refractive index unit) and 3.87 × 10−6 RIU, respectively. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental wake measurements based on the device with the wake measurements based on a CTD (conductivity–temperature–depth) device reveals a consistent trend. The realisation of this detection technique is of great significance for the advancement of research in the field of optical detection of underwater vehicle wake streams. [ABSTRACT FROM AUTHOR]

This work explores the use of ZIF-8, a metal–organic framework (MOF) material, for its use in the optical detection of volatile organic compounds (VOCs) in Fabry–Pérot and surface plasmon resonance (SPR)-based sensors. The experiments have been carried out with ethanol (EtOH) and show response times as low as 30 s under VOC-saturated atmospheres, and the estimated limit of detection is below 4000 ppm for both sensor types. The selectivity towards other VOCs is relatively poor, although the dynamics of adsorption/desorption differ for each VOC and could be used for selectivity purposes. Furthermore, the hydrophobicity of ZIF-8 has been confirmed and the fabricated sensors are insensitive to this compound, which is a very attractive result for its practical use in gas sensing devices. [ABSTRACT FROM AUTHOR]

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Advanced Textile Technology is the property of Zhejiang Sci-Tech University Magazines and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mesoporous silica nanoparticles (MSNs) exhibit highly beneficial characteristics for devising efficient biosensors for different analytes. Their unique properties, such as capabilities for stable covalent binding to recognition groups (e.g., antibodies or aptamers) and sensing surfaces, open a plethora of opportunities for biosensor construction. In addition, their structured porosity offers capabilities for entrapping signaling molecules (dyes or electroactive species), which could be released efficiently in response to a desired analyte for effective optical or electrochemical detection. This work offers an overview of recent research studies (in the last five years) that contain MSNs in their optical and electrochemical sensing platforms for the detection of cancer biomarkers, classified by cancer type. In addition, this study provides an overview of cancer biomarkers, as well as electrochemical and optical detection methods in general. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal–organic frame–based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid–based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios. [ABSTRACT FROM AUTHOR]

For early diabetes identification and management, the progression of an uncomplicated and exceedingly responsive glucose testing technology is crucial. In this study, we present a new sensor incorporating a composite of metal organic framework (MOF) based on cobalt, coated with boronic acid to facilitate selective glucose binding. Additionally, we successfully employed a highly sensitive electro-optical immunosensor for the detection of subtle changes in concentration of the diabetes biomarker glycated haemoglobin (HbA1c), using zeolitic imidazolate framework-67 (ZIF-67) coated with polydopamine which further modified with boronic acid. Utilizing the polymerization characteristics of dopamine and the NH2 groups, a bonding structure is formed between ZIF-67 and 4-carboxyphenylboronic acid. ZIF-67 composite served as an effective substrate for immobilising 4-carboxyphenylboronic acid binding agent, ensuring precise and highly selective glucose identification. The sensing response was evaluated through both electrochemical and optical methods, confirming its efficacy. Under optimized experimental condition, the ZIF-67 based sensor demonstrated a broad detection range of 50–500 mg dL−1, a low limit of detection (LOD) of 9.87 mg dL−1 and a high correlation coefficient of 0.98. Furthermore, the 4-carboxyphenylboronic acid-conjugated ZIF-67-based sensor platform exhibited remarkable sensitivity and selectivity in optical-based detection for glycated haemoglobin within the clinical range of 4.7–11.3%, achieving a LOD of 3.7%. These findings highlight the potential of the 4-carboxyphenylboronic acid-conjugated ZIF-67-based electro-optical sensor as a highly sensitive platform for diabetes detection. [ABSTRACT FROM AUTHOR]

To evaluate underwater sound, a simple non-invasive optical technique based on self-interference to detect low-frequency underwater acoustic signals was demonstrated. Clear self-interference fringes of a laser beam reflected from the surface capillary wave transformed from a low-frequency underwater acoustic signal by a cylinder were observed. This study was also aimed at developing an artificial neural network (ANN) model with input from an optical pattern. The relationship between the optical pattern and the frequency of underwater sound was established, and an optimal combination of hyper-parameters was obtained. By analyzing the fringe region and the fringe interval, the frequency of the underwater acoustic signal and its relative amplitude were measured. A model based on physical optics modified the fringe distribution function, and the theoretical fit with the modified function was in good agreement with experimental observation. The BP-ANN model exhibited good performance in establishing the relationship between the optical pattern and underwater sound. [ABSTRACT FROM AUTHOR]

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace. [ABSTRACT FROM AUTHOR]

Vascular endothelial growth factor (VEGF) is an indispensable element in many physiological processes, while alterations in its level in the circulating system are signs of pathology-associated diseases. Therefore, its precise and selective detection is critical for clinical applications to monitor the progression of the pathology. In this study, an optical immunoassay biosensor was developed as a model study for detecting recombinant VEGF165. The VEGF165 sample was purified from recombinant Kluyveromyces lactis GG799 yeast cells. Indirect ELISA was used during the detection, wherein iron oxide nanoparticles (FeNPs) were utilized to obtain optical signals. The FeNPs were synthesized in the presence of lactose p-amino benzoic acid (LpAB). VEGF165 antibody was conjugated to the LpAB-FeNPs through EDC/NHS chemistry to convert the iron oxide nanoparticles into VEGF165 specific probes. The specificity of the prepared system was tested in the presence of potential serum-based interferents (i.e., glucose, urea, insulin, C-reactive protein, and serum amyloid A), and validation studies were performed in a simulated serum sample. The proposed immunoassay showed a wide detection range (0.5 to 100 ng/mL) with a detection limit of 0.29 ng/mL. These results show that the developed assay could offer a sensitive, simple, specific, reliable, and high-throughput detection platform that can be used in the clinical diagnostics of VEGF. [ABSTRACT FROM AUTHOR]

Detection of mycotoxins in food is essential due to their potential harm to human and animal health. However, developing affordable and rapid methods for their detection, particularly with the necessary selectivity to differentiate between various mycotoxins, remains a challenge. Herein, we present low-cost paper-based sensing platforms modified with curcumin, a natural polyphenolic compound, for the electrochemical and optical detection of ochratoxin A (OTA). By exploiting the fluorescence quenching effect of OTA on curcumin through Förster energy transfer, we successfully conducted optical detection with LODs of 0.09 ng mL−1 and a linear range of 0.5 to 15 ng mL−1. Additionally, by using electrochemical impedance spectroscopy and a portable instrument, we detected OTA with a limit of detection (LOD) as low as 0.045 ng mL−1. These sensitivity levels meet the requirements established by food regulatory agencies for monitoring food quality in relation to OTA contamination. Our curcumin-modified paper-based sensors offer a compelling combination of simplicity in manufacturing and cost-effectiveness, underscoring their potential for routine food quality monitoring, especially concerning ochratoxin A.

The distribution of tiny sensors over a specific area was first proposed in the late 1990s as a concept known as smart dust. Several efforts focused primarily on computing and networking capabilities, but quickly ran into problems related to power supply, cost, data transmission, and environmental pollution. To overcome these limitations, we propose using paper-based (confetti-like) chemosensors that exploit the inherent selectivity of chemical reagents, such as colorimetric indicators. In this work, cheap and biodegradable passive sensors made from cellulose could successfully indicate the presence of hazardous chemicals, e.g., strong acids, by a significant color change. A conventional color digital camera attached to a drone could easily detect this from a safe distance. The collected data were processed to define the hazardous area. Our work presents a combination of the smart dust concept, chemosensing, paper-based sensor technology, and low-cost drones for flexible, sensitive, economical, and rapid detection of hazardous chemicals in high-risk scenarios.

One of the emerging techniques nowadays is retro-reflection/cat's eye effect-based optical detection and location. The prior detection (before firing) of hidden snipers and various other surveillance devices has been a great challenge. Most of the military weapon systems have common optical or electro-optical sights. One of the techniques can be detection of the retro-reflection from the aiming optical or electro-optical targets. In future the retro-reflection-based communication with UAVs is also into consideration. For development of retro-reflection-based devices, the understanding of the behaviour of the retro-reflection from various targets is crucial. In this paper, studies have been carried out through simulation and experimentation to study the behaviour of retro-reflection for various possible targets. [ABSTRACT FROM AUTHOR]

The multifunctionality of an A3B mixed-substituted porphyrin, namely 5-(4-carboxyphenyl)-10,15,20-tris(4-methylphenyl)porphyrin (5-COOH-3MPP), was proven due to its capacity to detect procaine by different methods, depending on the polymer matrix in which it is incorporated. The hybrid nanomaterial containing k-carrageenan and AuNPs (5-COOH-3MPP-k-carrageenan-AuNPs) was able to optically detect procaine in the concentration range from 5.76 × 10−6 M to 2.75 × 10−7 M, with a limit of detection (LOD) of 1.33 × 10−7 M. This method for the detection of procaine gave complementary results to the potentiometric one, which uses 5-COOH-3MPP as an electroactive material incorporated in a polyvinylchloride (PVC) membrane plasticized with o-NPOE. The detected concentration range by this ion-selective membrane electrode is wider (enlarged in the field of higher concentrations from 10−2 to 10−6 M), linearly dependent with a 53.88 mV/decade slope, possesses a detection limit of 7 × 10−7 M, a response time of 60 s, and has a certified stability for a working period of six weeks. [ABSTRACT FROM AUTHOR]

Optical detection of partial discharge (PD) is an important way to reflect the insulation status of equipment. C4F7N/CO2 gas mixture is one of the most potential substitutes for SF6 at present, but there is a lack of research on its optical PD characteristics and diagnostic methods. In this paper, a PD multispectral array detection platform that can collect 7 characteristic bands is constructed, and 4 kinds of PD defects are produced. The similarities and differences of the PD multispectral characteristics in phase distribution, energy distribution, and feature stacking map under the conditions of 5 different ratios of C4F7N/CO2 gas mixture and pure SF6 gas are analyzed. Finally, a novel method of PD diagnosis based on multispectral features (MF) and k-nearest neighbors (KNN) is proposed. The experimental results show that the fault recognition accuracy in pure SF6 can reach 96.2%. The recognition rate of C4F7N/CO2 gas mixture is above 88%, and the highest accuracy rate is 91.1%. This method has a guiding significance for the PD diagnosis of environmentally friendly gas-insulated equipment, and provides a new route for traditional PD detection and diagnosis.

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation, and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change in the refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. Furthermore, experiments were conducted to detect the flow field of a propeller wake. The experimental results indicate that the wake dissipation times of the propeller in a strong density-stratified water environment are approximately 800 s and 750 s. Following the stabilisation of the wake field density, the laser spot position is observed to be stable at 0.341 mm and 0.441 mm, respectively, with a corresponding refractive index change of 2.99 × 10−6 RIU (refractive index unit) and 3.87 × 10−6 RIU, respectively. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental wake measurements based on the device with the wake measurements based on a CTD (conductivity–temperature–depth) device reveals a consistent trend. The realisation of this detection technique is of great significance for the advancement of research in the field of optical detection of underwater vehicle wake streams.

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.

This work explores the use of ZIF-8, a metal–organic framework (MOF) material, for its use in the optical detection of volatile organic compounds (VOCs) in Fabry–Pérot and surface plasmon resonance (SPR)-based sensors. The experiments have been carried out with ethanol (EtOH) and show response times as low as 30 s under VOC-saturated atmospheres, and the estimated limit of detection is below 4000 ppm for both sensor types. The selectivity towards other VOCs is relatively poor, although the dynamics of adsorption/desorption differ for each VOC and could be used for selectivity purposes. Furthermore, the hydrophobicity of ZIF-8 has been confirmed and the fabricated sensors are insensitive to this compound, which is a very attractive result for its practical use in gas sensing devices.

Mesoporous silica nanoparticles (MSNs) exhibit highly beneficial characteristics for devising efficient biosensors for different analytes. Their unique properties, such as capabilities for stable covalent binding to recognition groups (e.g., antibodies or aptamers) and sensing surfaces, open a plethora of opportunities for biosensor construction. In addition, their structured porosity offers capabilities for entrapping signaling molecules (dyes or electroactive species), which could be released efficiently in response to a desired analyte for effective optical or electrochemical detection. This work offers an overview of recent research studies (in the last five years) that contain MSNs in their optical and electrochemical sensing platforms for the detection of cancer biomarkers, classified by cancer type. In addition, this study provides an overview of cancer biomarkers, as well as electrochemical and optical detection methods in general.

Analytical chemistry applied to medical and diagnostic analysis has recently focused on the development of cost-effective biosensors able to monitor the health status or to assess the level of specific biomarkers that can be indicative of several diseases. The improvement of technologies relating to the possibility of the non-invasive sampling of biological fluids, as well as sensors for the detection of analytical signals and the computational capabilities of the systems routinely employed in everyday life (e.g., smartphones, computers, etc.), makes the complete integration of self-standing analytical devices more accessible. This review aims to discuss the biosensors that have been proposed in the last five years focusing on two principal detecting approaches, optical and electrochemical, which have been employed for quantifying different kinds of target analytes reaching detection limits below the clinical sample levels required. These detection principles applied to point-of-care (POC) devices have been extensively reported in literature, and even the limited examples found on the market are based on these strategies. This work will show the latest innovations considering the integration of optical and electrochemical detection with the most commonly reported analytical platforms for POC applications such as paper-based or wearable and implantable devices. [ABSTRACT FROM AUTHOR]

Biosensors are analytical devices that use biological interactions to detect and quantify single molecules, clinical biomarkers, contaminants, allergens, and microorganisms. By coupling bioreceptors with transducers, such as nucleic acids or proteins, biosensors convert biological interactions into electrical signals. Electrochemical and optical transductions are the most widely used methods due to their high detection capability and compatibility with miniaturization. Biosensors are valuable in analytical chemistry, especially for health diagnostics, as they offer simplicity and sensitivity. Despite their usefulness, challenges persist in immobilizing biorecognition elements on the transducer surface, leading to issues such as loss of sensitivity and selectivity. To address these problems, the introduction of nanomaterials, in particular magnetic nanoparticles (MNPs) and magnetic beads, has been implemented. MNPs combine their magnetic properties with other interesting characteristics, such as their small size, high surface-to-volume ratio, easy handling, and excellent biocompatibility, resulting in improved specificity and sensitivity and reduced matrix effects. They can be tailored to specific applications and have been extensively used in various fields, including biosensing and clinical diagnosis. In addition, MNPs simplify sample preparation by isolating the target analytes via magnetic separation, thus reducing the analysis time and interference phenomena and improving the analytical performance of detection. The synthesis and modification of MNPs play a crucial role in adjusting their properties for different applications. This review presents an overview of the synthesis and surface modifications of magnetic nanoparticles and their contributions to the development of biosensors and bioassays for their applications across different areas. The future challenges of MNP synthesis and integration in assays are focused on their stability, multiplex detection, simplification and portability of test platforms, and in vivo applications, among other areas of development. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Novichok-like or fourth-generation agents (FGAs) are chemical warfare agents (CWAs) which have been gaining attention since their use in assassination attempts on Sergei Skripal and Alexei Navalny. Due to their physicochemical properties, these substances are difficult to detect by implemented technologies, resulting in massive response efforts if their occurrence is suspected in a civilian environment. In this work, an approach is presented that uses handheld forensic light sources to visually detect surfaces contaminated with Novichok. More than 100 different wavelength combinations were applied to seven substances chosen to represent the newly listed schedule 1 subgroups in the Annex on Chemicals of the Chemical Weapons Convention. One waveband was identified as promising, which allowed the optical detection of all tested substances. Several surfaces, which could be affected in case of a possible attack using novichok-like nerve agents, were also successfully evaluated. The proposed procedure could be implemented for CBRN responders and security agencies to significantly reduce response efforts, thereby diminishing the overall threat posed by this group of chemicals (FGAs). This procedure was also extended to carbamates and CWAs.

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.

Optical immunosensors are one of the most popular categories of immunosensors with applications in many fields including diagnostics and environmental and food analysis. The latter field is of particular interest not only for scientists but also for regulatory authorities and the public since food is essential for life but can also be the source of many health problems. In this context, the current review aims to provide an overview of the different types of optical immunosensors focusing on their application for the determination of pathogenic bacteria in food samples. The optical immunosensors discussed include sensors based on evanescent wave transduction principles including surface plasmon resonance (SPR), fiber-optic-, interferometric-, grating-coupler-, and ring-resonator-based sensors, as well as reflectometric, photoluminescence, and immunosensors based on surface-enhanced Raman scattering (SERS). Thus, after a short description of each transduction technique, its implementation for the immunochemical determination of bacteria is discussed. Finally, a short commentary about the future trends in optical immunosensors for food safety applications is provided. [ABSTRACT FROM AUTHOR]

Novichok-like or fourth-generation agents (FGAs) are chemical warfare agents (CWAs) which have been gaining attention since their use in assassination attempts on Sergei Skripal and Alexei Navalny. Due to their physicochemical properties, these substances are difficult to detect by implemented technologies, resulting in massive response efforts if their occurrence is suspected in a civilian environment. In this work, an approach is presented that uses handheld forensic light sources to visually detect surfaces contaminated with Novichok. More than 100 different wavelength combinations were applied to seven substances chosen to represent the newly listed schedule 1 subgroups in the Annex on Chemicals of the Chemical Weapons Convention. One waveband was identified as promising, which allowed the optical detection of all tested substances. Several surfaces, which could be affected in case of a possible attack using novichok-like nerve agents, were also successfully evaluated. The proposed procedure could be implemented for CBRN responders and security agencies to significantly reduce response efforts, thereby diminishing the overall threat posed by this group of chemicals (FGAs). This procedure was also extended to carbamates and CWAs. [ABSTRACT FROM AUTHOR]

The optical detection of a nanosecond laser pulse in transparent ferrimagnetic single crystals of yttrium iron garnet and yttrium orthoferrite in the IR range at room temperature was experimentally studied. A linearly polarized neodymium laser (wavelength 1.06 μm) operating in the Q-switched mode was used as the source of electromagnetic radiation. The pulse duration was about 20 ns, and the peak power ∼10 MW. It was found that the ferrimagnetic detector has a sufficient response time to detect nanosecond laser pulses. The amplitude of the detected signal strongly depends on the external bias magnetic field and correlates well with the nonlinearity of the static magnetization curve of the ferrimagnetic crystal sample used. [ABSTRACT FROM AUTHOR]

Cell-based screening methods are increasingly used in diagnostics and drug development. As a result, various research groups from around the world have been working on this topic to develop methods and algorithms that increase the degree of automation of various measurement techniques. The field of computer vision is becoming increasingly important and has therefore a significant influence on the development of various processes in modern laboratories.In this work we describe an approach for detecting two height information, the phase boundary of a cell pellet and the bottom edge of the tube, and thereby a method for determining the highest point of the topology. The starting point for the development of the method described are cells obtained by various procedures and stabilized by a fixative. Centrifugation of the tube causes the cells to settle to the bottom of the tube, resulting in a cell pellet with a clear phase boundary between the cells and the fixative. For further studies, the supernatant fixative has to be removed without reducing the number of cells. The fixative is to be extracted automatically by a liquid robot, which is only possible by accurately determining the cell pellet height. Due to centrifugation, an uneven topology is formed, which is why the entire phase boundary must be examined to detect the highest point of the cell pellet.For this approach, the tube to be examined, which contains the cells and the fixative, is rotated 360° in defined small steps after centrifugation. During rotation, an image is captured in each step, after which a defined image area is separated from the center of the image and merged into a panoramic image. This produces a panoramic image of the cell topology which represents the complete phase boundary, the boundary located on the outside of the tube. This panoramic image is modified through various image processing steps to extract and detect the phase boundary. Various image processing algorithms from the OpenCV library are used. In the first step, the panoramic image is convolved with a Gaussian blur filter to reduce noise. In the following step, a black and white image is generated by a thresholding process. This black and white image, or binary image, is convolved with a Sobel operator in the x and y directions and the results are superimposed. This overlaid image shows the top edge of the cell pellet and other edges located in the image. A logical exclusion method of the obtained boundaries is used for the detection of the phase boundary. To detect the tube bottom, a multilevel model was trained in advance with an appropriate data set. This model can detect and localize in near real time the tube bottom in an image.By using the two-height information of the different boundaries, phase boundary and tube bottom, the highest point of the cell pellet can be detected. This information is then passed on to a higher-level process so that the liquid robot can approach this point with the pipette tip to remove the excess fixative. By determining the highest point, the probability of being able to remove a larger amount of fixative without reducing the number of cells is highest. This ensures that post-processing studies have the largest possible number of cells available with complete automation.

Power transformer is one of the main equipment in power transmission and distribution network. Thus, it is important to ensure optimal operation of power transformer for an efficient supply of energy to utilities. One of the main components of a power transformer is the transformer insulation system, namely, transformer insulation oil and transformer insulation paper. This review provides an in-depth discussion on the reactions that occur in the insulation system of the power transformer. These include, oxidation, hydrolysis, pyrolysis, partial discharge, and arcing. The reaction mechanisms, conditions and the relationship between these reactions are thoroughly analysed in this review. Apart from that, this review also provides an inclusive discussion on the state-of-the-art methods used to monitor the byproducts formed from the mentioned reactions. These methods were developed to overcome the limitation of conventional methods that are complex and costly. Moreover, it presents an impartial evaluation of the challenges and prospects in making the power transformer monitoring system more efficient in terms of cost and time. Information corroborated in this review is expected to provide an important roadmap for future research in monitoring the condition of power transformer.

Puffiness is one of the dominant postharvest disorders in easy-peeling citrus cultivars. In this study, the structural changes between healthy and puffy Satsuma mandarin were investigated and the potential of using optical methods for disorder detection was explored. To gain more insight in this disorder, the external appearance and internal quality attributes were first compared between healthy and puffy Iwasaki Satsuma mandarins at three harvest times. Although no consistent differences were observed in the appearance of fruits, the soluble solids content and Brix minus acid values in puffy mandarin were found to be higher compared to the corresponding healthy fruit. The structural properties of the flavedo and albedo tissue layer in the peel were quantified from X-ray CT scans. Whilst no differences were observed in the size of the oil glands in the flavedo, the pore size in the albedo of puffy mandarin was found to be larger with later harvest. The bulk optical properties of the intact fruit were estimated from laser scatter images with a metamodel calibrated on optical phantoms. The reduced scattering coefficient (μ s ') for the intact fruit was found to be lower in puffy mandarin relative to healthy fruit. The distinction between healthy and puffy mandarin based on μ s ' was further validated on Goku Wase Satsuma mandarin. The results obtained indicate that healthy and puffy mandarin can be separated well based on their μ s ' at all the selected wavelengths. This provides a basis for the non-destructive optical detection of puffing disorder at an early stage. [Display omitted] • External and internal attributes were compared between healthy and puffy mandarin. • Thickness of both flavedo and albedo tissue layers was lower in puffy mandarin. • Pore size in the albedo of puffy mandarin was larger at a later harvest time. • The μ s ' of the intact fruit was lower in the puffy than the healthy mandarin. [ABSTRACT FROM AUTHOR]

MicroRNA (miRNA) are constituted of approximately 22 nucleotides and play an important role in the regulation of many physiological functions and diseases. In the last 10 years, an increasing interest has been recorded in studying the expression profile of miRNAs in cancer. Real time-quantitative polymerase chain reaction (RT-qPCR), microarrays, and small RNA sequencing represent the gold standard techniques used in the last 30 years as detection methods. The advent of nanotechnology has allowed the fabrication of nanostructured biosensors which are widely exploited in the diagnostic field. Nanostructured biosensors offer many advantages: (i) their small size allows the construction of portable, wearable, and low-cost products; (ii) the large surface–volume ratio enables the loading of a great number of biorecognition elements (e.g., probes, receptors); and (iii) direct contact of the recognition element with the analyte increases the sensitivity and specificity inducing low limits of detection (LOD). In this review, the role of nanostructured biosensors in miRNA detection is explored, focusing on electrochemical and optical sensing. In particular, four types of nanomaterials (metallic nanoparticles, graphene oxide, quantum dots, and nanostructured polymers) are reported for both detection strategies with the aim to show their distinct properties and applications. [ABSTRACT FROM AUTHOR]

A dual-mode nanoprobe was constructed to detect Bax messenger RNA (mRNA), consisting of gold nanotriangles (AuNTs), a Cy5-modified recognition sequence, and a thiol-modified DNA sequence. Bax mRNA is one of the key pro-apoptotic factors in the apoptosis pathway. Raman enhancement and fluorescence quenching of the signal group Cy5 were performed using AuNTs as substrates. The thiol-modified nucleic acid chain is partially complementary to the Cy5-modified nucleic acid chain to form a double strand and is linked to the AuNTs by the Au–S bond. When Bax mRNA is present, the Cy5-modified strand specifically binds to it to form a more stable duplex, making Cy5 far away from AuNTs, and SERS signal is weakened while fluorescence signal is enhanced. The nanoprobe can be used for the quantitative detection of Bax mRNA in vitro. Combined with the high sensitivity of SERS and the visualization of fluorescence, this method has good specificity and can be used for in situ imaging and dynamic monitoring of Bax mRNA during deoxynivalenol (DON) toxin–induced apoptosis of HepG2 cells. DON plays a pathogenic role mainly by inducing cell apoptosis. The results confirmed that the proposed dual-mode nanoprobe has good versatility in various human cell lines. [ABSTRACT FROM AUTHOR]

The global need for accurate and efficient cancer cell detection in biomedicine and clinical diagnosis has driven extensive research and technological development in the field. Precision, high-throughput, non-invasive separation, detection, and classification of individual cells are critical requirements for successful technology. Lab-on-a-chip devices offer enormous potential for solving biological and medical problems and have become a priority research area for microanalysis and manipulating cells. This paper reviews recent developments in the detection of cancer cells using the microfluidics-based lab-on-a-chip method, focusing on describing and explaining techniques that use optical phenomena and a plethora of probes for sensing, amplification, and immobilization. The paper describes how optics are applied in each experimental method, highlighting their advantages and disadvantages. The discussion includes a summary of current challenges and prospects for cancer diagnosis. [ABSTRACT FROM AUTHOR]

3D printed opto-microfluidic autonomous analyzer for photometric applications performs the automation of analytical micro-processes. The proposed device was designed under restrictions of small size and low energy consumption, which allow its portability for in-situ, on line and real time analysis. The autonomous process and auto-calibration consists of four functions: control and data acquisition; hydrodynamic: fluid pumping and flow injection; optical detection and wireless communication. All electronics systems where controlled with a virtual instrument interface. In the experiments carried out to measure fluorides, the results obtained were very close to those obtained with laboratory equipment. The consumption of reagents was 50% less and waste was reduced by 80%. The cost of the portable and autonomous microanalyzer is 75% less than large and robust laboratory equipment.

The multifunctionality of an A3B mixed-substituted porphyrin, namely 5-(4-carboxyphenyl)-10,15,20-tris(4-methylphenyl)porphyrin (5-COOH-3MPP), was proven due to its capacity to detect procaine by different methods, depending on the polymer matrix in which it is incorporated. The hybrid nanomaterial containing k-carrageenan and AuNPs (5-COOH-3MPP-k-carrageenan-AuNPs) was able to optically detect procaine in the concentration range from 5.76 × 10−6 M to 2.75 × 10−7 M, with a limit of detection (LOD) of 1.33 × 10−7 M. This method for the detection of procaine gave complementary results to the potentiometric one, which uses 5-COOH-3MPP as an electroactive material incorporated in a polyvinylchloride (PVC) membrane plasticized with o-NPOE. The detected concentration range by this ion-selective membrane electrode is wider (enlarged in the field of higher concentrations from 10−2 to 10−6 M), linearly dependent with a 53.88 mV/decade slope, possesses a detection limit of 7 × 10−7 M, a response time of 60 s, and has a certified stability for a working period of six weeks.