Detection Mode Research Articles

Comparative study of chemometrics-enhanced spectrophotometric and liquid chromatographic techniques for the concurrent measurement of the effective pantoprazole and vincamine renal impairment combination therapy: Greenness, blueness, and whiteness appraisal

Simple, sensitive, and green ultraviolet spectrophotometric with chemometric support and chromatographic methods were designed and verified for the concurrent estimation of pantoprazole (PTZ) and vincamine (VIN). This co-administered mixture was determined for the first time in their pharmaceutical dosage forms with a high percentage of recoveries. Classical least squares (CLS), principle component regression (PCR), and partial least squares (PLS), are the three chemometric techniques applied in UV spectrophotometric analysis. An experimental design with two variables and five levels was utilized for models’ optimization. The optimized techniques were successfully verified and utilized to resolve their extensive zero-order spectral overlap within the wavelength span of 240–310 nm. In the chromatographic technique, the compounds were well separated on BDS HYPERSIL C8 column employing a mobile phase composed of phosphate buffer, 0.2% tri-ethylamine and acetonitrile (55:45% v/v), adjusting pH at 4.25. The flow speed was 1 mL/min using an isocratic mode for elution and UV detection at 230 nm. The studied drugs were separated in less than 5 min. The HPLC Method validation was carried out in accordance with the International Conference on Harmonization (ICH) guidelines. A comparative statistical analysis revealed no significant differences between the outcomes of the developed approaches and the reported spectrophotometric methods. A comprehensive sustainability profiling of the proposed methods was established and compared using the latest Blue Applicability Grade Index (BAGI), along with the most widely applicable metrics for greenness: the Analytical Eco-Scale (AES), GAPI and AGREE metrics, and the recent whiteness evaluation tool (RGB 12).

Characterizing linearity of a large area InGaAs photodiode in direct detection mode, at room temperature, from 100 pA to 10 𝛍A

Characterizing linearity of a large area InGaAs photodiode in direct detection mode, at room temperature, from 100 pA to 10 𝛍A

Repurposing of PSMA-targeted diagnostic and therapeutic agents for the detection and treatment of giant cell tumors of bone

Giant cell tumor of bone (GCTB) is a rare bone tumor often necessitating surgical intervention, radiation therapy, or treatment with bisphosphonates or denosumab. 99mTc-MDP bone scintigraphy for GCTB has limited specificity, and the relatively high uptake of 18F-FDG in GCTB makes it challenging to differentiate it from other benign bone tumors. More specific detection and treatment modalities for GCTB are needed to enhance patient monitoring and outcomes. Prostate Specific Membrane Antigen (PSMA) is present in the neovasculature of various tumors, yet unexplored in GCTB. PSMA-targeted imaging and radiotherapeutic agents Locametz and Pluvicto are a powerful theranostic pair for detecting and treating PSMA-positive metastatic tumors, including those in bone, and thus have considerable potential to be repurposed for GCTB. This study aimed to determine if the vasculature of GCTB was PSMA-positive and whether targeting it with PSMA-specific agents was feasible. Using bone core samples from 28 GCTB patients and 9 negative controls, we present the first robust detection of PSMA on the tumor vasculature of GCTB. To demonstrate the potential repurposed use of PSMA-targeted agents in detecting and treating GCTB, we used a PSMA-specific fluorescent probe (FAM-C6-1298) as a model for these radiopharmaceutical agents. Incubation of fresh GCTB tissue samples with FAM-C6-1298 showed increased fluorescence intensity compared to controls, indicating successful targeting of PSMA in GCTB tissue. In conclusion, our data established that PSMA is not only present in the tumor vasculature of GCTB patient tissue but can be effectively targeted with repurposed PSMA-specific radiopharmaceuticals for diagnosis and therapy.

Optimized detection modality for radio-frequency sensing with a double-resonance alignment magnetometer

In this work, we present a comprehensive and comparative analysis of two detection modalities, i.e., polarization rotation and absorption measurement of light, for a double-resonance alignment magnetometer (DRAM). We derive algebraic expressions for magnetometry signals based on the description of multipole moments. Experiments are carried out using a room-temperature paraffin-coated cesium-vapor cell and measuring either the polarization rotation or absorption of the transmitted laser light. A detailed experimental analysis of the resonance spectra is performed to validate the theoretical findings for various input parameters. The results signify the use of a single isotropic relaxation rate, thus simplifying the data analysis for optimization of the DRAM. The sensitivity measurements are performed and reveal that the polarization-rotation detection mode yields larger signals and better sensitivity than absorption measurement of light. Published by the American Physical Society 2024

Minimal solution to the axion isocurvature problem from nonminimal coupling

The main limitation for preinflationary breaking of Peccei-Quinn (PQ) symmetry is the upper bound on the Hubble rate during inflation from axion isocurvature fluctuations. This leads to a tension between high scale inflation and QCD axions with grand unified theory scale decay constants, which reduces the potential for a detection of tensor modes at next generation cosmic microwave background (CMB) experiments. We propose a mechanism that explicitly breaks PQ symmetry via nonminimal coupling to gravity, that lifts the axion mass above the Hubble scale during inflation and has negligible impact on today’s axion potential. The initially heavy axion gets trapped at an intermediate minimum during inflation given by the phase of the nonminimal coupling, before it moves to its true CP-conserving minimum after inflation. During this stage, it undergoes coherent oscillations around an adiabatically decreasing minimum, which slightly dilutes the axion energy density, while still being able to explain the observed dark matter relic abundance. This scenario can be tested by the combination of next generation CMB surveys like CMB-S4 and LiteBIRD with haloscopes such as ABRACADABRA, DMRadio, or CASPEr-Electric. Published by the American Physical Society 2024

Correlation between proprioception, functionality, patient-reported knee condition and joint acoustic emissions.

Non-invasive assessment of joint status using acoustic emissions (AE) is a growing research area that has the potential to translate into clinical practice. The purpose of this study is to investigate the correlation of the knee's AE with measures of proprioception, self-assessment, and performance, as it can be hypothesised that, AE parameters will correlate with joint function metrics due to AE being recorded during interaction of the articular surfaces. Threshold to detect passive motion (TTDPM), Knee Osteoarthritis Outcome Scores (KOOS) and 5 times sit-to-stand test (5STS) were collected from 51 participant. Knee AE were recorded during cycling with 30 and 60 rpm cadences using two sensors in different frequency ranges and three modes of AE event detection. Weak (0.297, p = 0.048) to moderate (0.475, p = 0.001) Spearman's correlations were observed between longer 5STS time and AE parameters (i.e. higher median absolute energy, signal strength, longer AE event rise time and duration). Similarly, AE parameters shown correlation with lower KOOS, especially in the "Function in Sports and Recreation" and "Activities of Daily Living" subscales with correlation coefficients for higher median amplitude up to 0.441, p = 0.001 and 0.403, p = 0.004, respectively. The correlation with the TTDPM was not detected for most of the AE parameters. Additionally, a lower frequency sensor and 60 rpm cadence AE recordings showed higher correlations. Considering that this study included subjects from the general population and the number of participants with KOOS <70 was relatively small, higher correlations might be expected for clinically confirmed OA cases. Additionally, different ICCs might be expected for alternative signal parameters and proprioception assessment methods. Overall, the study confirms that AE monitoring offers an additional modality of joint assessment that reflects interaction between cartilage surfaces and can complement orthopaedic diagnostics, especially in the context of remote monitoring, drug testing, and rehabilitation.

Basketball player motion detection and motion mode analysis based on biomechanical sensors

Basketball player motion detection and analysis are crucial for optimizing performance and preventing injuries. Traditional methods often rely on visual observation and video analysis, lacking precision and real-time feedback. In this study, a unique novel Intelligent Bayesian tuned-augmented Support Vector Machine (IB-ASVM) was proposed for predicting basketball players’ motion modes and performance analysis using the biomechanical sensor data. Advancements in biomechanical sensors such as accelerometers, gyroscopes, and force sensors are deployed into ESP32 to build a player’s wearable gadget. This gadget provides dynamic players with real-time sensing data. Data are transmitted to the cloud via Wi-Fi 7.0 for motion analysis and this model is stimulated using Arduino IDE. The Kalman Filter reduces noise and smoothens sensor data such as acceleration, and angular velocity. Then, the filtered data is employed in the Discrete Wavelet Transform (DWT) to capture time-frequency characteristics of motion signals, making it ideal for extracting relevant features. The featured data are utilized in the ASVM model to classify and detect the motion modes of the basketball players via IB optimization. The Tensor Flow software is used to implement the IB-ASVM model. The result demonstrates that IB-ASVM most accurately predicts the jump shot, layup, dribbling, running, pivoting, passing, free throw, and motion states of the basketball players. The IB-ASVM model accurately classifies basketball motion states using biomechanical sensor data, enhancing performance optimization and injury prevention through precise motion detection.

Nanowire-like phosphorus modulated carbon-based iron nanozyme with oxidase-like activity for sensitive detection of choline and dye degradation

Choline is mainly supplemented through food intake, lack of choline would result in diseases like liver cirrhosis, hardening of the arteries, or neurodegenerative disorders. The accurate detection of choline is important for human health. Herein, a novel nanowire-like phosphorus/nitrogen co-doped carbon-based iron nanozyme (Fe-NPC) with outstanding oxidase-like activity was synthesized, and the influence of phosphorus doping on oxidase-like activity was explored. Proper phosphorus doping was found to enhance the oxidase-like activity of Fe-NPC by increasing surface defects, promoting iron loading, and modulating chemical environment of central site. The oxidase-like activity of Fe-NPC was successfully applied to colorimetric-fluorescent dual mode detection of choline, and good linear relationship in the ranges of 3–200 μM were achieved with LODs of 1.95 and 1.50 μM, respectively. The fluorescent detection was constructed based on the fluorescence quenching of silicon quantum dots (Si QDs) by quinone-imine. The quenching mechanism was attributed to FRET due to the large spectra overlap, reduced fluorescence lifetime and proper donor−acceptor distance. The successful application to the detection of choline in milk proved the practicability of the proposed sensing method. The oxidase-like properties of Fe-NPC was further used in the degradation of cationic dye methyl blue, high degradation efficiency of 74 % was achieved within 5 min under optimal conditions, proving the enormous potential of Fe-NPC for application in environment protection.

High-Precision Measurement Method for Small Angles Based on the Defect Spot Mode of the Position-Sensitive Detector

The paper proposes and verifies a small-angle measurement method based on the defect spot mode of the position-sensitive detector (PSD). With the output characteristics of the PSD in the defect spot mode and the size transformation properties of a focused beam, the measurement sensitivity can be significantly improved. Calibration experiments with the piezoelectric transducer (PZT) indicate that compared with the current PSD-based autocollimation method, the proposed method can improve the sensitivity of small-angle measurement by 57 times, and the measurement sensitivity of the proposed method can be further improved by optimizing the system parameters, while the proposed method has the advantages of a simple system and high real-time performance. Therefore, the proposed method is expected to be used in high-precision motion error detection, as well as in shape and position measurement.

A Retrospective Analysis of Jordan's National COVID-19 Call Center: Operations, Effectiveness, and Lessons Learned.

Contact tracing has been a cornerstone of non-pharmaceutical interventions to control the COVID-19 epidemic, with highly mixed effectiveness internationally. In Jordan, the Ministry of Health (MOH) collaborated with the Jordan Nurses and Midwives Council and the USAID Local Health System Sustainability Project to set up a call center for contact tracing of COVID-19. This study described the operation and assessed the effectiveness of Jordan's COVID-19 call center activities in reaching COVID-19 cases and their contacts. A retrospective observational design was conducted using data from all calls made by the COVID-19 call center cases between November 2020 and April 2022. Data were collected from initial and follow-up calls to PCR-confirmed COVID-19 cases and their contacts. Data on socio-demographics, symptoms, and contact tracing activities were recorded. The study focused on key outcomes, including call success rates, the number of cases and contacts reached, and the role of different detection modes in identifying cases. During the study period, the call center attempted to contact 1,027,911 COVID-19 cases, successfully reaching 802,525 cases (78.1%). Follow-up calls were made to 1,126,334 cases, with a success rate of 74%. The call center appeared particularly valuable during the initial period of the pandemic until it was overwhelmed by the significantly more transmissible Omicron variant of the virus. Two weaknesses were identified: gaps in reaching non-Jordanian citizen cases and difficulty in keeping up with case volume during the Omicron wave of February-March 2022, when reported cases peaked at over 20,000 per day. One-third of all reached cases said that they had been referred for testing through contact tracing. Contact tracing activities led by the MOH were instrumental in identifying new cases, optimizing resource allocation, improving surveillance and data systems, targeting vulnerable population, and supporting mitigation strategies to combat the COVID-19 pandemic in Jordan.

Sensitive detection of K-ras gene by a dual-mode “on-off-on” sensor based on bipyridine ruthenium-MOF and bis-enzymatic cleavage technology

This study developed a dual-mode “on-off-on” sensor based on a bipyridine ruthenium metal–organic framework (Ru-MOF) and dual enzyme cleavage technology for the sensitive detection of the K-ras gene. The sensor combines electrogenerated chemiluminescence (ECL) and fluorescence (FL) detection modes, achieving high sensitivity and specificity in detecting the K-ras gene through catalytic hairpin assembly (CHA) and dual enzyme cleavage reactions. Experimental results showed that the detection limits for the K-ras gene were 0.044 fM (ECL) and 0.16 fM (FL), demonstrating excellent selectivity and stability during detection. Through testing actual samples, the sensor has shown potential for application in complex biological environments. This method offers an efficient and reliable new tool for cancer diagnosis and treatment.

Detection of Earth’s free oscillation and analysis of the non-synchronous oscillation phenomenon of normal modes

Earth’s free oscillation can provide essential constraints for refining Earth models, inverting seismic source mechanisms, and studying the deep internal structure of the Earth. Large earthquakes can simultaneously excite numerous normal modes. Due to the Earth’s ellipticity, rotation, and internal heterogeneities, these normal modes undergo splitting, with the frequencies of singlets of normal modes becoming very close (only a few µHz apart). This imposes greater demands on the detection of normal modes. This paper introduces a novel method for normal mode detection based on the normal time–frequency transform (NTFT). Compared to classical FT spectrum methods and recent optimal sequence estimation (OSE), the proposed method not only detects more weak normal modes but also reveals the spatial distribution of the phase of each normal mode. Taking the detection of 0S2 as an example, the phase measurements of each singlet are spatially inconsistent. This phenomenon can provide prior information for other methods, such as product spectrum analysis (PSA), spherical harmonic stacking (SHS), multistation experiments (MSE), and OSE. Additionally, understanding the phase distribution patterns contributes to further study of geological structures, offering crucial foundational data and observational support.

Recent Developments of Hybrid Fluorescence Techniques: Advances in Amyloid Detection Methods.

Amyloid fibrils are formed from various pathological proteins. Monitoring their aggregation process is necessary for early detection and treatment. Among the available detection techniques, fluorescence is simple, intuitive, and convenient due to its sensitive and selective mode of detection. It has certain disadvantages like poor photothermal stability and detection state limitation. Research has focused on minimising the limitation by developing hybrid fluorescence techniques. This review focuses on the two ways fluorescence (intrinsic and extrinsic) has been used to monitor amyloid fibrils. In intrinsic/label free fluorescence: i) The fluorescence emission through aromatic amino acid residues like phenylalanine (F), tyrosine (Y) and tryptophan (W) is present in amyloidogenic peptides/protein sequence. And ii) The structural changes from alpha helix to cross-β-sheet structures during amyloid formation contribute to the fluorescence emission. The second method focuses on the use of extrinsic fluorophores to monitor amyloid fibrils i) organic dyes/small molecules, ii) fluorescent tagged proteins, iii) nanoparticles, iv) metal complexes and v) conjugated polymers. All these fluorophores havetheir own limitations. Developing them into hybrid fluorescence techniques and converting it into biosensors can contribute to early detection of disease.

Assessing the severity of COVID-19 waves: beware of surveillance bias

Abstract Background Indicators to assess the severity of epidemic waves during the COVID-19 pandemic were influenced by differences in detection modalities over time, leading to surveillance bias. We compared four indicators across three pandemic periods to assess surveillance bias. Methods We used data from one region of Switzerland. We compared seroprevalence, cases, hospitalizations, and deaths during three periods (period 1: Feb-Oct 2020, including the 1st wave; period 2: Oct 2020-Feb 2021, including the 2nd wave; period 3: Feb-Aug 2021, including the 3rd wave and after the start of the vaccination campaign). Data were retrieved from the Swiss Federal Office of Public Health or population-based studies. We compared each indicator to a reference indicator (seroprevalence during periods 1 and 2 and hospitalizations during period 3). We also assessed the timeliness of the indicators, i.e., the duration from data generation to the availability of the information to decision-makers. Results According to seroprevalence estimates, the severity of the 2nd wave was slightly larger (by a ratio of 1.4) than the severity of the 1st wave. Compared to seroprevalence, cases largely overestimated the 2nd wave severity (2nd vs 1st wave ratio: 6.5) while hospitalizations (ratio: 2.2) and deaths (ratio: 2.9) were more suitable to compare the severity of these waves. According to hospitalizations, the 3rd wave severity was slightly smaller (by ratio of 0.7) than the 2nd wave. Compared to hospitalizations, cases or deaths slightly underestimated the 3rd wave severity (3rd vs 2nd wave ratio for cases: 0.5; for deaths: 0.4) and seroprevalence was very biased due to high vaccination rates. Across all waves, timeliness for cases and hospitalizations was better than for deaths or seroprevalence. Conclusions To assess the severity of pandemic waves accounting for surveillance bias, different types of indicators must be used across time. Key messages • Differences in detection modalities over time can skew the assessment of the severity of COVID-19 pandemic waves, leading to surveillance bias. • The effectiveness of indicators in describing the severity of COVID-19 pandemic waves depends on the type of indicator used and the stage of the pandemic.

A Novel Carbon Dot-Bromothymol Blue System for Ratiometric Colorimetric-Fluorometric Sensing of Glutathione in Urine: A Smartphone-Compatible Approach.

This study presents a novel dual-modal approach for glutathione (GSH) detection using blue and yellow dual-emission carbon dots (BY-CDs) and bromothymol blue (BTB) at pH 8.0. The method employs both colorimetric and fluorometric detection modes, offering a new perspective on GSH quantification. BTB's blue coloration induces selective fluorescence quenching of the CDs' 610nm emission peak, with minimal effect on the 445nm peak. Upon GSH addition, the quinonoid structure (blue color) of BTB transforms to its benzenoid form (yellow color). This transformation triggers fluorescence restoration at 610nm and significant quenching at 445nm, enabling ratiometric fluorescence analysis (F610/F445). Concurrently, colorimetric detection is also ratiometric, based on measuring the ratio between the emerging yellow color peak (435nm) and the decreasing blue color peak (618nm) (A435/A618). The state-of-the-art aspect of this detection method lies in the strategic choice of dual-emission CDs and a dye with distinct absorption spectra that closely match the emission spectra of the CDs. This unique combination allows for dual detection with opposite responses in the two detection modes, enhancing selectivity and reliability. The probe was thoroughly characterized, and its detection mechanism was elucidated using various spectroscopic techniques. The method shows excellent linearity, a broad detection range, and low detection limits for both fluorometry (0.02 - 10.0μM, 5.88nM) and colorimetry (1.0 - 35.0μM, 301.25nM). Additionally, a smartphone-based platform was developed for colorimetric GSH determination, enhancing the method's potential for on-site analysis. The assay's practicality was validated through successful application to human urine samples, yielding excellent recovery values (97.33% to 99.13%).

Black hole spectroscopy with ground-based atom interferometer and space-based laser interferometer gravitational wave detectors

Gravitational wave (GW) detection allows us to test general relativity in entirely new regimes. A prominent role takes the detection of quasi-normal modes (QNMs), which are emitted after the merger of a binary black hole (BBH) when the highly distorted remnant emits GWs to become a regular Kerr black hole (BH). The BH uniqueness theorems of Kerr black hole solutions in general relativity imply that the frequencies and damping times of QNMs are determined solely by the mass and spin of the remnant BH. Therefore, detecting QNMs offers a unique way to probe the nature of the remnant BH and to test general relativity. We study the detection of a merging BBH in the intermediate-mass range, where the inspiral–merger phase is detected by space-based laser interferometer detectors TianQin and LISA, while the ringdown is detected by the ground-based atom interferometer (AI) observatory AION. The analysis of the ringdown is done using the regular broadband mode of AI detectors as well as the resonant mode optimizing it to the frequencies of the QNMs predicted from the inspiral–merger phase. We find that the regular broadband mode allows constraining the parameters of the BBH with relative errors of the order 10−1 and below from the ringdown. Moreover, for a variety of systems considered, the frequencies and the damping times of the QNMs can be determined with relative errors below 0.1 and 0.2, respectively. We further find that using the resonant mode can improve the parameter estimation for the BBH from the ringdown by a factor of up to three. Utilizing the resonant mode significantly limits the detection of the frequency of the QNMs but improves the detection error of the damping times by around two orders of magnitude.

A position-based method for detecting orbital angular momentum modes

Abstract Due to the inherent limitations of current Orbital Angular Momentum (OAM) mode detection methods and constraints posed by the physical size of receiving antennas, accurately identifying higher-order OAM modes represents a significant challenge. Therefore, there is a pressing necessity to overcome these hurdles. This paper introduces a new approach to OAM mode detection that exploits positional information. Our methodology ascertains the OAM mode by examining the phase and position data of the electric field at any two randomly chosen points within the energy's spatial distribution radiated by vortex electromagnetic waves. This innovation promises not only to precisely detect higher-order OAM modes but also grants greater versatility in the placement of receiving antennas. Moreover, the study delves into the correlation between the electric field phase of vortex electromagnetic waves, the azimuth angle, and the receiving distance. The validity of our approach is confirmed through both simulation outcomes and experimental data derived from physical tests.&amp;#xD;

The Study of Sensing Elements Parameters Optimization for Developed Biosensor of SARS-CoV-2 Detection

New advancements in developing sensitive and selective biosensors have demonstrated outstanding potential for Deoxyribonucleic Acid (DNA biosensors). The detection mode of DNA biosensors primary depends on a particular DNA hybridization that precisely occurs on the surface of the physical transducer that can only be detected using high-performance assays due to slight current changes. The analytical performance (sensitivity) of the DNA biosensor is conclusively rely on the confluence constructing of the sensing surface, which must be optimized. Thus, in this study, the sensing elements of the developed biosensors were optimized for detecting RNA of SARS-CoV-2. This optimization included concentration of nanomaterials (carbon quantum dots), probe density (concentration of DNA probe) and concentration of linker (APTES). It was observed that 0.15 % V/V of concentration CQD, 0.1μM of DNA probe and 36% V/V of APTES were the optimum parameters which provided their maximum response during electrical measurements and increased the sensitivity of the developed biosensor for SARS-CoV-2 detection.

A human cadaveric model for venous air embolism detection tool development.

A human cadaveric model combining standard lung protective mechanical ventilation and modified cardiac bypass techniques was developed to allow investigation into automated modes of detection of venous air emboli (VAE) prior to in vivo human or animal investigations. In this study, in order to create an artificial cardiopulmonary circuit in a cadaver that could mimic VAE physiology, the direction of flow was reversed from conventional cardiac bypass. Normal saline was circulated in isolation through the heart and lungs as opposed to the peripheral organs by placing the venous cannula into the aorta and the arterial cannula into the inferior vena cava with selective ligation of other vessels. Mechanical ventilation and this reversed cardiac bypass scheme allowed preliminary detection of VAE independently but not in concert in our current simulation scheme due to pulmonary edema in the cadaver. A limited dissection approach was used initially followed by a radical exposure of the great vessels, and both proved feasible in terms of air signal detection. We used electrical impendence as a preliminary tool to validate detection in this cadaveric model however we theorize that it would work for echocardiographic, intravenous ultrasound or other novel modalities as well. A cadaveric model allows monitoring technology development with reduced use of animal and conventional human testing.

Carbon dots for pathogen detection and imaging: recent breakthroughs and future trends.

As a class of carbon-based nanomaterials, carbon dots (CDs) have gained a lot of interest for a variety of applications. They offer distinctive optical, chemical, and structural characteristics along with favourable attributes such as low cost, availability of abundant functional groups, remarkable chemical inertness, high stability, exceptional biocompatibility, and ecofriendliness. This review discusses synthesis methods, structural characteristics, and surface modifications of CDs, specific for pathogen detection. Furthermore, it delves into the mechanisms that govern the interaction between pathogens and CDs. In addition, the study explores the use of CDs in a number of detection modalities, such as optical, electrochemical, and electrochemiluminescence, emphasising real-time pathogen monitoring. Moreover, both the challenges and opportunities related to the application of CDs-based detection and imaging methods are highlighted in field and clinical contexts.