Highly-efficient selection of aptamers for detecting various HPV subtypes in clinical samples.

Nucleic acid aptamers are of great potentials in diagnostic and therapeutic applications because of their unique molecular recognition capabilities. However, satisfactory aptamers with high affinity and specificity are still in short supply. Herein, we have developed new selection methods allowing the free interactions between the targets and potential aptamers in solution. In our selection system, the protein targets (biotinylated randomly or site-specifically) were first incubated with the random DNA library, followed by the pull-down with the streptavidin magnetic beads or biolayer-interferometry (BLI) sensors. By comparing the two biotinylation strategies (random or site-specific) and two states of the targets (free or immobilized), we have found that the combination of the site-specific biotinylation and free-target strategies was most successful. Based on these highly-efficient selection strategies, HPV L1 aptamers were obtained. By designing the sandwich aptasensor assisted with RCA and CRISPR/Cas12a, we have diagnosed various HPV subtypes in clinical samples, such as easily-collected urine samples. In summary, our new strategy can allow efficient selection of aptamers with high affinity and specificity for clinical applications.

Extraction of Human Limbs Based on Micro-Doppler-Range Trajectories Using Wideband Interferometric Radar.

In this paper, we propose to extract the motions of different human limbs by using interferometric radar based on the micro-Doppler-Range signature (mDRS). As we know, accurate extraction of human limbs in motion has great potential for improving the radar performance on human motion detection. Because the motions of human limbs usually overlap in the time-Doppler plane, it is extremely hard to separate human limbs without other information such as the range or the angle. In addition, it is also difficult to identify which part of the body each signal component belongs to. In this work, the overlaps of multiple components can be solved, and the motions from different limbs can be extracted and classified as well based on the extracted micro-Doppler-Range trajectories (MDRTs) along with a proposed three-dimensional constant false alarm (3D-CFAR) detection. Three experiments are conducted with three different people on typical human motions using a 77 GHz radar board of 4 GHz bandwidth, and the results are validated by the measurements of a Kinect sensor. All three experiments were repeatedly conducted for three different people of different heights to test the repeatability and robust of the proposed approach, and the results met our expectations very well.

Single-shot multispectral quantitative phase imaging of biological samples using deep learning.

Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly spatially sensitive digital holographic microscope assisted by a deep neural network. There are three different wavelengths used in our method: λ=532, 633, and 808 nm. The first step is to get the interferometric data for each wavelength. The acquired datasets are used to train a generative adversarial network to generate multispectral (MS) quantitative phase maps from a single input interferogram. The network was trained and validated on two different samples: the optical waveguide and MG63 osteosarcoma cells. Validation of the present approach is performed by comparing the predicted MS phase maps with numerically reconstructed (F T+T I E) phase maps and quantifying with different image quality assessment metrices.

Optimizing the internal phase reference to shape the output of a multimode optical fiber.

Pre-shaping light to achieve desired amplitude distributions at the tip of a multimode fiber (MMF) has emerged as a powerful method allowing a wide range of imaging techniques to be implemented at the distal facet. Such techniques rely on measuring the transmission matrix of the optically turbid waveguide which scrambles the coherent input light into an effectively random speckle pattern. Typically, this is done by measuring the interferogram between the output speckle and a reference beam. In recent years, an optical setup where the reference beam passes through the MMF has become an attractive configuration because of the high interferometric stability of the common optical path. However, the merits and drawbacks of an internal reference beam remain controversial. The measurement of the transmission matrix is known to depend on the choice of internal reference and has been reported to result in "blind spots" due to phase singularities of the reference beam. Here, we describe how the focussing efficiency of the calibration can be increased by several percent by optimising the choice of internal reference beam.

Fabry-Perot Interferometric Fiber-Optic Sensor for Rapid and Accurate Thrombus Detection.

We present a fiber-optic sensor based on the principles of a Fabry-Perot interferometer (FPI), which promptly, sensitively, and precisely detects blood clot formation. This sensor has two types of sensor tips; the first was crafted by splicing a tapered fiber into a single-mode fiber (SMF), where fine-tuning was achieved by adjusting the tapered diameter and length. The second type is an ultra-compact blood FPI situated on the core of a single-mode fiber. The sensor performance was evaluated via clot-formation-indicating spectrum shifts induced by the varied quantities of a thrombin reagent introduced into the blood. The most remarkable spectral sensitivity of the micro-tip fiber type was approximately 7 nm/µL, with a power sensitivity of 4.1 dB/µL, obtained with a taper fiber diameter and length of 55 and 300 µm, respectively. For the SMF type, spectral sensitivity was observed to be 8.7 nm/µL, with an optical power sensitivity of 0.4 dB/µL. This pioneering fiber-optic thrombosis sensor has the potential for in situ applications, healthcare, medical monitoring, harsh environments, and chemical and biological sensing. The study underscores the scope of optical technology in thrombus detection, establishing a platform for future medical research and application.

Real-time bio-layer interferometry ubiquitination assays as alternatives to western blotting.

Ubiquitination is a crucial cellular pathway enabling normal cellular functions. Abnormalities in the ubiquitination process can lead to cellular dysfunction and cause a range of diseases. Efforts to screen and develop small molecule inhibitors targeting portions of the ubiquitination cascade require rapid and robust methods for detecting ubiquitination. Enormous efforts have been made in the field to detect ubiquitination using various techniques including fluorescence, spectrophotometry, chemiluminescence, NMR, and radioactive tracers. The most common method to detect ubiquitination is western blotting. However, western blotting is time-consuming and difficult to use when seeking fine-grained time course experiments. Here we present the use of bio-layer interferometry to rapidly assay ubiquitination in real-time. An E3 ligase auto-ubiquitination system and a substrate ubiquitination assay have been applied as tests for the newly developed assay. The developed BLI ubiquitination assay provides one-second time resolution and detects the formation of polyubiquitin chains directly on a biosensor-bound target. Results are returned instantaneously, and reagent concentrations are identical to those used by traditional western blot-based ubiquitination assays. The developed BLI ubiquitination assay is a viable alternative to traditional western blot assays to detect ubiquitination in a rapid real-time manner.

Wearable Optical Fiber Sensors in Medical Monitoring Applications: A Review.

Wearable optical fiber sensors have great potential for development in medical monitoring. With the increasing demand for compactness, comfort, accuracy, and other features in new medical monitoring devices, the development of wearable optical fiber sensors is increasingly meeting these requirements. This paper reviews the latest evolution of wearable optical fiber sensors in the medical field. Three types of wearable optical fiber sensors are analyzed: wearable optical fiber sensors based on Fiber Bragg grating, wearable optical fiber sensors based on light intensity changes, and wearable optical fiber sensors based on Fabry-Perot interferometry. The innovation of wearable optical fiber sensors in respiration and joint monitoring is introduced in detail, and the main principles of three kinds of wearable optical fiber sensors are summarized. In addition, we discuss their advantages, limitations, directions to improve accuracy and the challenges they face. We also look forward to future development prospects, such as the combination of wireless networks which will change how medical services are provided. Wearable optical fiber sensors offer a viable technology for prospective continuous medical surveillance and will change future medical benefits.

Dynamic imaging of interfacial electrochemistry on single Ag nanowires by azimuth-modulated plasmonic scattering interferometry.

Direct visualization of surface chemical dynamics in solution is essential for understanding the mechanisms involved in nanocatalysis and electrochemistry; however, it is challenging to achieve high spatial and temporal resolution. Here, we present an azimuth-modulated plasmonic imaging technique capable of imaging dynamic interfacial changes. The method avoids strong interference from reflected light and consequently eliminates the parabolic-like interferometric patterns in the images, allowing for a 67-fold increase in the spatial resolution of plasmonic imaging. We demonstrate that this optical imaging approach enables comprehensive analyses of surface chemical dynamics and identification of previously unknown surface reaction heterogeneity by investigating electrochemical redox reactions over single silver nanowires as an example. This work provides a general strategy for high-resolution plasmonic imaging of surface electrochemical dynamics and other interfacial chemical reactions, complementing existing surface characterization methods.

Magneto-optical trapping in a near-suface borehole.

Borehole gravity sensing can be used in a number of applications to measure features around a well, including rock-type change mapping and determination of reservoir porosity. Quantum technology gravity sensors, based on atom interferometry, have the ability to offer increased survey speeds and reduced need for calibration. While surface sensors have been demonstrated in real world environments, significant improvements in robustness and reductions to radial size, weight, and power consumption are required for such devices to be deployed in boreholes. To realise the first step towards the deployment of cold atom-based sensors down boreholes, we demonstrate a borehole-deployable magneto-optical trap, the core package of many cold atom-based systems. The enclosure containing the magneto-optical trap itself had an outer radius of (60 ± 0.1) mm at its widest point and a length of (890 ± 5) mm. This system was used to generate atom clouds at 1 m intervals in a 14 cm wide, 50 m deep borehole, to simulate how in-borehole gravity surveys are performed. During the survey, the system generated, on average, clouds of (3.0 ± 0.1) × 105 87Rb atoms with the standard deviation in atom number across the survey observed to be as low as 8.9 × 104.

VUV to IR Emission Spectroscopy and Interferometry Diagnostics for the European Shock Tube for High-Enthalpy Research.

The European Shock Tube for High-Enthalpy Research is a new state-of-the-art facility, tailored for the reproduction of spacecraft planetary entries in support of future European exploration missions, developed by an international consortium led by Instituto de Plasmas e Fusão Nuclear and funded by the European Space Agency. Deployed state-of-the-art diagnostics include vacuum-ultraviolet to ultraviolet, visible, and mid-infrared optical spectroscopy setups, and a microwave interferometry setup. This work examines the specifications and requirements for high-speed flow measurements, and discusses the design choices for the main diagnostics. The spectroscopy setup covers a spectral window between 120 and 5000 nm, and the microwave interferometer can measure electron densities up to 1.5 × 1020 electrons/m3. The main design drivers and technological choices derived from the requirements are discussed in detail herein.

Influence of Ion Exchange Process Parameters on Broadband Differential Interference.

The paper presents theoretical analyses and experimental investigations of broadband differential interference in planar gradient waveguides made via K+-Na+ ion exchange in BK-7 glass. This technology, due to its large polarimetric dispersion, is especially useful for applications in differential interferometry. We discuss the influence of technological parameters on the operation characteristics of the structure in terms of sensor applications. The refractive index variation in the measured external surroundings affects the modal properties of TE and TM modes and the spectral distribution at the output of the differential interferometer. The optical system described in this work has been designed specifically for use in biological systems where variations in the index of refraction need to be measured.

Quantum wave function reconstruction by free-electron spectral shearing interferometry.

The quantum wave function measurement of a free electron remains challenging in quantum mechanics and is subject to disputes about ψ-ontic/epistemic interpretations of the wave function. Here, we theoretically propose a realistic spectral method for reconstructing quantum wave function of an electron pulse, free-electron spectral shearing interferometry (FESSI). We use a Wien filter to generate two time-delayed replicas of the electron wave packet and then shift one replica in energy using a light-electron modulator driven by a mid-infrared laser. As a direct demonstration, we numerically reconstruct a pulsed electron wave function with a kinetic energy of 10 keV. FESSI is experimentally feasible and enables us to fully determine distinct orders of spectral phases and their physical implications in quantum foundations and quantum technologies, providing a universal approach to characterize ultrashort electron pulses.

From Self-Assembly of Colloidal Crystals toward Ordered Porous Layer Interferometry.

Interferometry-based, reflectometric, label-free biosensors have made significant progress in the analysis of molecular interactions after years of development. The design of interference substrates is a key research topic for these biosensors, and many studies have focused on porous films prepared by top-down methods such as porous silicon and anodic aluminum oxide. Lately, more research has been conducted on ordered porous layer interferometry (OPLI), which uses ordered porous colloidal crystal films as interference substrates. These films are made using self-assembly techniques, which is the bottom-up approach. They also offer several advantages for biosensing applications, such as budget cost, adjustable porosity, and high structural consistency. This review will briefly explain the fundamental components of self-assembled materials and thoroughly discuss various self-assembly techniques in depth. We will also summarize the latest studies that used the OPLI technique for label-free biosensing applications and divide them into several aspects for further discussion. Then, we will comprehensively evaluate the strengths and weaknesses of self-assembly techniques and discuss possible future research directions. Finally, we will outlook the upcoming challenges and opportunities for label-free biosensing using the OPLI technique.

Altimetry Method for an Interferometric Radar Altimeter Based on a Phase Quality Evaluation.

A radar altimeter (RA) is useful to improve autonomous functions such as landing guidance or navigation control of an aircraft. To ensure more precise and safer flights by aircraft, an interferometric RA (IRA) capable of measuring the angle of a target is required. However, the phase-comparison monopulse (PCM) technique used in IRAs has a problem in that an angular ambiguity arises with respect to a target with multiple reflection points, such as terrain. In this paper, we propose an altimetry method for IRAs that reduces the angular ambiguity by evaluating the quality of the phase. The altimetry method as introduced here is sequentially described based on synthetic aperture radar, a delay/Doppler radar altimeter, and PCM techniques. Finally, a phase quality evaluation method is proposed for use in the azimuth estimation process. Aircraft captive flight test results are presented and analyzed, and the validity of the proposed method is examined.

Stabilized free space optical frequency transfer using digitally enhanced heterodyne interferometry.

Free-space continuous-wave laser interferometry using folded links has applications in precision measurement for velocimetry, vibrometry, optical communications, and verification of frequency transfer for metrology. However, prompt reflections from the transceiver optics degrade the performance of these systems, especially when the power of the returning signal is equal to or less than the power of the prompt reflections. We demonstrate phase stabilized free-space continuous-wave optical frequency transfer that exploits the auto-correlation properties of pseudo-random binary sequences to filter out prompt reflections. We show that this system significantly improves the stability and robustness of optical frequency transfer over a 750 m turbulent free-space channel, achieving a best fractional frequency stability of 8 × 10-20 at an integration time of τ = 512 s, and cycle-slip-free periods up to 162 min.

Kalman filtering-enhanced short-delay self-heterodyne interferometry for linewidth measurement.

We demonstrate an extended Kalman filtering-enhanced linewidth measurement in short-delay self-heterodyne interferometry (SDSHI). We found that a modified SDSHI trace closely resembles a biased cosine wave, which would enable convenient linewidth estimation by its uniform envelope contrast without any correction factor. Experimentally, we adopted this approach for kHz laser linewidth measurement, taking advantages of extended Kalman filtering (EKF) to adaptively track the cosine wave. Apart from the measurement noise suppression, this approach could use as many data points as possible in the noisy trace to make a linewidth estimation at each tracked data point, from which we can deduce valuable statistical parameters such as the mean and standard deviation. This approach involves no more equipment than conventional SDSHI and sophisticated EKF so that it can be easily implemented. Therefore, we believe it will find wide applications in ultra-narrow laser linewidth measurement.

Atom Interferometric Imaging of Differential Potentials Using an Atom Laser.

Interferometry is a prime technique for modern precision measurements. Atoms, unlike light, have significant interactions with electric, magnetic, and gravitational fields, making their use in interferometric applications particularly versatile. Here, we demonstrate atom interferometry to image optical and magnetic potential landscapes over an area exceeding 240 µm×600 µm. The differential potentials employed in our experiments generate phase imprints in an atom laser that are made visible through a Ramsey pulse sequence. We further demonstrate how advanced pulse sequences can enhance desired imaging features, e.g., to image steep potential gradients. A theoretical discussion is presented that provides a semiclassical analysis and matching numerics.

Scrutinization of land subsidence rate using a supportive predictive model: Incorporating radar interferometry and ensemble soft-computing.

Land subsidence is a huge challenge that land and water resource managers are still facing. Radar datasets revolutionize the way and give us the ability to provide information about it, thanks to their low cost. But identifying the most important drivers need for the modeling process. Machine learning methods are especially top of mind amid the prediction studies of natural hazards and hit new heights over the last couple of years. Hence, putting an efficient approach like integrated radar-and-ensemble-based method into practice for land subsidence rate simulation is not available yet which is the main aim of this research. In this study, the number of 52 pairs of radar images were used to identify subsidence from 2014 to 2019. Then, using the simulated annealing (SA) algorithm the key variables affecting land subsidence were identified among the topographical parameters, aquifer information, land use, hydroclimatic variables, and geological and soil factors. Afterward, three individual machine learning models (including Support Vector Machine, SVM; Gaussian Process, GP; Bayesian Additive Regression Tree, BART) along with three ensemble learning approaches were considered for land subsidence rate modeling. The results indicated that the subsidence varies between 0 and 59 cm in this period. Comparing the Radar results with the permanent geodynamic station exhibited a very strong correlation between the ground station and the radar images (R2 = 0.99, RMSE = 0.008). Parsing the input data by the SA indicated that key drivers are precipitation, elevation, percentage of fine-grained materials in the saturated zone, groundwater withdrawal, distance to road, groundwater decline, and aquifer thickness. The performance comparison indicated that ensemble models perform better than individual models, and among ensemble models, the nonlinear ensemble approach (i.e., BART model combination) provided better performance (RMSE = 0.061, RSR = 0.42, R2 = 0.83, PBIAS = 2.2). Also, the distribution shape of the probability density function in the non-linear ensemble model is much closer to the observations. Results indicated that the presence of significant fine-grained materials in unconsolidated aquifer systems can clarify the response of the aquifer system to groundwater decline, low recharge, and subsequent land subsidence. Therefore, the interaction between these factors can be very dangerous and intensify subsidence.

Time-domain full-field optical coherence tomography with digital confocal line scanning.

Full-field optical coherence tomography (FF-OCT) is a camera-based interferometric microscopy technique that can image deep in tissue with high spatial resolution. However, the absence of confocal gating leads to suboptimal imaging depth. Here, we implement digital confocal line scanning in time-domain FF-OCT by exploiting the row-by-row detection feature of a rolling-shutter camera. A digital micromirror device (DMD) is used in conjunction with the camera to produce synchronized line illumination. An improvement in the SNR by an order of magnitude is demonstrated on a sample of a US Air Force (USAF) target mounted behind a scattering layer.

Drug screening at single-organoid resolution via bioprinting and interferometry.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.