Differential Phase Research Articles

JK-1, a useful erythroleukemic cell line model to study a controlled erythroid differentiation from progenitors to terminal erythropoiesis

New hematopoietic cell models have recently emerged through immortalization of CD34 cells to study and understand various molecular mechanisms of erythropoiesis. Here, we characterize the JK-1 CML-derived cell line, previously shown to spontaneously differentiate without cytokines. Using an epigenetic differentiation inhibitor that keeps JK-1 in an early differentiation phase, we characterized 2 progenitor stages: BFU-E JK-1 and CFU-E JK-1 with CD34+/CD36− and CD34−/CD36 + phenotypes respectively. Then, using the PFI-1 inducer known to synchronously control the terminal differentiation of JK-1 cells, 5 precursor stages were obtained (ProE, Baso1-2, PolyC, OrthoC) and characterized via cell morphology, CD49a and Band3 markers. Enlarged phenotyping was carried out for the earlier phase, and expression kinetics of membrane proteins such as RhAG, RhD/CE, CD47, DARC and CD44 were performed on each stage of the terminal phase. Furthermore, since JK-1 offers the unique property of covering a broad spectrum of differentiation stages, we explored deeper the GATA2/GATA1 and the non-erythroid/erythroid spectrin ‘switching’. The possibility of obtaining large quantities of JK-1 cells at each stage of differentiation, as shown in this study, as well as the potential to genetically modify these cells, via CrisprCas9, makes their use of considerable interest for studying pathologies occurring during erythropoiesis.

Direct observation of space-charge-induced electric fields at oxide grain boundaries.

Space charge layers (SCLs) formed at grain boundaries (GBs) are considered to critically influence the properties of polycrystalline materials such as ion conductivities. Despite the extensive researches on this issue, the presence of GB SCLs and their relationship with GB orientations, atomic-scale structures and impurity/solute segregation behaviors remain controversial, primarily due to the difficulties in directly observing charge distribution at GBs. In this study, we directly observe electric field distribution across the well-defined yttria-stabilized zirconia (YSZ) GBs by tilt-scan averaged differential phase contrast scanning transmission electron microscopy. Our observation clearly reveals the existence of SCLs across the YSZ GBs with nanometer precision, which are significantly varied depending on the GB orientations and the resultant core atomic structures. Moreover, the magnitude of SCLs show a strong correlation with yttrium segregation amounts. This study provides critical insights into the complex interplay between SCLs, orientations, atomic structures and segregation of GBs in ionic crystals.

Neutron phase filtering for separating phase- and attenuation signal in aluminium and anodic aluminium oxide

Neutron imaging has gained significant importance as a material characterisation technique and is particularly useful to visualise hydrogenous materials in objects opaque to other radiations. Fields of application include investigations of hydrogen in metals as well as metal corrosion, thanks to the fact that neutrons can penetrate metals better than e.g. X-rays and are highly sensitive to hydrogen. However, at interfaces refraction effects sometimes obscure the attenuation image, which is used for hydrogen quantification. Refraction, a differential phase effect, diverts the neutron beam away from the interface in the image leading to intensity gain and intensity loss regions, which are superimposed to the attenuation image, thus obscuring the interface region and hindering quantitative analyses of e.g. hydrogen content in the vicinity of the interface. For corresponding effects in X-ray imaging, a phase filter approach was developed and is generally based on transport-of-intensity considerations. Here, we compare such an approach, that has been adapted to neutrons, with another simulation-based assessment using the ray-tracing software McStas. The latter appears superior and promising for future extensions which enable fitting forward models via simulations in order to separate phase and attenuation effects and thus pave the way for overcoming quantitative limitations at refracting interfaces.

Monoallelic de novo variants in DDX17 cause a neurodevelopmental disorder.

DDX17 is an RNA helicase shown to be involved in critical processes during the early phases of neuronal differentiation. Globally, we compiled a case-series of 11 patients with neurodevelopmental phenotypes harbouring de novo monoallelic variants in DDX17. All 11 patients in our case series had a neurodevelopmental phenotype, whereby intellectual disability, delayed speech and language, and motor delay predominated. We performed in utero cortical electroporation in the brain of developing mice, assessing axon complexity and outgrowth of electroporated neurons, comparing wild-type and Ddx17 knockdown. We then undertook ex vivo cortical electroporation on neuronal progenitors to quantitatively assess axonal development at a single cell resolution. Mosaic ddx17 crispants and heterozygous knockouts in Xenopus tropicalis were generated for assessment of morphology, behavioural assays, and neuronal outgrowth measurements. We further undertook transcriptomic analysis of neuroblastoma SH-SY5Y cells, to identify differentially expressed genes in DDX17-KD cells compared to controls. Knockdown of Ddx17 in electroporated mouse neurons in vivo showed delayed neuronal migration as well as decreased cortical axon complexity. Mouse primary cortical neurons revealed reduced axon outgrowth upon knockdown of Ddx17 in vitro. The axon outgrowth phenotype was replicated in crispant ddx17 tadpoles and in heterozygotes. Heterozygous tadpoles had clear neurodevelopmental defects and showed an impaired neurobehavioral phenotype. Transcriptomic analysis identified a statistically significant number of differentially expressed genes involved in neurodevelopmental processes in DDX17-KD cells compared to control cells. We have identified potential neurodevelopment disease-causing variants in a gene not previously associated with genetic disease, DDX17. We provide evidence for the role of the gene in neurodevelopment in both mammalian and non-mammalian species and in controlling the expression of key neurodevelopment genes.

Imaging atomic-scale magnetism with energy-filtered differential phase contrast method

We propose differential phase contrast (DPC) imaging using energy-filtered electrons to image the magnetic properties of materials at the atomic scale. Compared to DPC measurements with elastic electrons, our simulations predict about two orders of magnitude higher relative magnetic signal intensities and sensitivity to all three vector components of magnetization. Published by the American Physical Society 2024

Introducing FISCAS, a Tool for the Effective Generation of Single Cell MALDI-MSI Data.

We introduce Fluorescence Integrated Single-Cell Analysis Script (FISCAS), which combines fluorescence microscopy with MALDI-MSI to streamline single-cell analysis. FISCAS enables automated selection of tight measurement regions, thereby reducing the acquisition of off-target pixels, and makes use of established algorithms for cell segmentation and coregistration to rapidly compile single-cell spectra. MALDI-compatible staining of membranes, nuclei, and lipid droplets allows the collection of fluorescence data prior to the MALDI-MSI measurement on a timsTOF fleX MALDI-2. Usefulness of the software is demonstrated by the example of THP-1 cells during stimulated differentiation into macrophages at different time points. In this proof-of-principle study, FISCAS was used to automatically generate single-cell mass spectra along with a wide range of morphometric parameters for a total number of roughly 1300 cells collected at 24, 48, and 72 h after the onset of stimulation. Data analysis of the combined morphometric and single-cell mass spectrometry data shows significant molecular heterogeneity within the cell population at each time point, indicating an independent differentiation of each individual cell rather than a synchronized mechanism. Here, the grouping of cells based on their molecular phenotype revealed an overall clearer distinction of the different phases of differentiation into macrophages and delivered an increased number of lipid signals as possible markers compared with traditional bulk analysis. Utilizing the linkage between mass spectrometric data and fluorescence microscopy confirmed the expected positive correlation between lipid droplet staining and the overall signal for triacylglyceride (TG), demonstrating the usefulness of this multimodal approach.

Usage of coil-shaped conductive polymer composite as intrinsically flexible flaw sensing probe

The assessment of buried flaws in the interlayer structure of curved metal is crucial to system safety. To improve the flexibility of eddy current sensor, an intrinsically flexible flaw sensing probe made of coil-shaped conductive polymer composite is proposed. The experimental data show that the response signal of the coil-shaped composite changes at the flaw and increases with the increases of flaw height/length, with a maximum sensitivity of 0.435 mV/mm for differential amplitude and 4.904 °/mm for differential phase. The results show that the height of the characteristic signals in the response signals reflects the change in flaw height, and the length of the characteristic signals in the response signals reflects the change in flaw length. The relative change rate of the coil-shaped composite is higher than that of a metal coil of the same structure. The above results have laid a preliminary foundation for using the coil-shaped composite to detect flaws.

Automatic Landslide Detection in Gansu, China, Based on InSAR Phase Gradient Stacking and AttU-Net

Landslides are the most serious geological disaster in our country, causing economic losses. Because they go undetected, a large number of landslides that have caused disasters are not in the catalogue. At present, Interferometric Synthetic Aperture Radar (InSAR) has been widely used in the identification of landslides. However, it is time-consuming, inefficient, etc., to survey landslides throughout our large country. In the context of massive SAR data, this problem is more obvious. Therefore, based on the current technique of using differential interferogram phase gradient stacking to avoid phase unwrapping errors, a landslide phase gradient dataset has been constructed. To validate the dataset’s effectiveness and applicability, deep learning methods were introduced, applying the dataset to four networks: U-Net, Attention-Unet, Bisenet v2, and Deeplab v3. The results indicate that the phase gradient dataset performs well across different models, with the Attention-Unet network demonstrating the best performance. Specifically, the precision, recall, and accuracy on the test dataset were 0.8771, 0.8712, and 0.9834, respectively, and the accuracy on the validation dataset was 0.8523. Finally, in this paper, the model is applied to landslide identification in Gansu Province, China, during 2022-2023, and a total of 1882 landslides are found. These landslides are mainly concentrated in the south of Gansu Province, where the terrain is relatively undulating. The results show that this method can quickly and accurately realize landslide automatic identification in a wide area and provide technical support for large-scale landslide disaster surveys.

Exploring deep learning models for 4D-STEM-DPC data processing

For the study of magnetic materials at the nanoscale, differential phase contrast (DPC) imaging is a potent tool. With the advancements in direct detector technology, and consequent popularity gain for four-dimensional scanning transmission electron microscopy (4D-STEM), there has been an ongoing development of new and enhanced ways for STEM-DPC big data processing. Conventional algorithms are experimentally tailored, and so in this article we explore how supervised learning with convolutional neural networks (CNN) can be utilized for automated and consistent processing of STEM-DPC data. Two different approaches are investigated, one with direct tracking of the beam with regression analysis, and one where a modified U-net is used for direct beam segmentation as a pre-processing step. The CNNs are trained on experimentally obtained 4D-STEM data, enabling them to effectively handle data collected under similar instrument acquisition parameters. The model outputs are compared to conventional algorithms, particularly in how they process data in the presence of strong diffraction contrast, and how they affect domain wall profiles and width measurement.

Static X-ray differential phase contrast imaging via bidirectional-misalignment grating

Grating-based X-ray differential phase contrast imaging (GB-DPCI) offers excellent imaging contrast for soft tissues. Limited by the phase stepping of gratings, the conventional GB-DPCI leads to a high radiation dose. This study presents a static GB-DPCI method employing an analyzer grating with a misaligned structure in both vertical and horizontal directions. A signal retrieval algorithm is developed for this method to permit the use of neighboring pixels on the detector to approximate multiple phase stepping positions, thereby obtaining the phase contrast signal in a single exposure. This study reduces high radiation doses and time-consumption caused by phase stepping. The presented method is validated with datasets from a laboratory X-ray tube and synchrotron radiation. Considering synchrotron results as example, minimal improvements in Feature Similarity Index Measure are 2.48%, 6.31%, and 7.06% for absorption, dark field, and phase contrasts, and in Information-Weight Structure Similarity Index Measure are 3.24%, 16.07%, and 8.61%.

Differential Phase Analysis for Volcanic Tremor Detection and Source Location

AbstractWe present observations showing that during episodes of volcanic tremors, the phase of inter‐station cross‐correlations becomes stable. We propose a new quantity, the phase coherence, to identify the differential phase stability in recordings obtained from a single pair of stations, which is extrapolated to the seismic network. Then, we present a new approach based on the estimation of differential travel times through the differential phase measurements, to locate the sources of tremors occurring at the end of 2015 at the Klyuchevskoy Volcanic Group in Kamchatka, Russia. We present evidence supporting the existence of two types of activity happening simultaneously during the tremor episode: the main tremor source, originating from a region located between 7 and 9 km depth under the main volcanoes, and the widespread occurrence of weak low‐frequency earthquakes occurring at random locations. We show how the phase coherence and the differential phases can be used to provide information on the stability of the tremor source position and to estimate its location.

Optimization of culture conditions to generate vascularized multi-lineage liver organoids with structural complexity and functionality

Hepatic organoids (HOs), primarily composed of hepatobiliary cells, do not represent the pathogenesis of liver diseases due to the lack of non-parenchymal cells. Multi-lineage liver organoids (mLOs) containing various cell types found in the liver offer a promising in vitro disease model. However, their structural complexity remains challenging to achieve due to the difficulty in optimizing culture conditions that meet the growth need of all component cell types. Here, we demonstrate that cystic HOs generated from hPSCs can be expanded long-term and serve as a continuous source for generating complex mLOs. Assembling cystic HOs with hPSC-derived endothelial and hepatic stellate cell-like cells under conventional HO culture conditions failed to support the development of multiple cell types within mLOs, resulting in biased differentiation towards specific cell types. In contrast, modulating the cAMP/Wnt/Hippo signaling pathways with small molecules during assembly and differentiation phases efficiently generate mLOs containing both hepatic parenchymal and non-parenchymal cells. These mLOs exhibited structural complexity and functional maturity, including vascular network formation between parenchymal lobular structures, cell polarity for bile secretion, and the capacity to respond to fibrotic stimuli. Our study underscores the importance of modulating signaling pathways to enhance mLO structural complexity for applications in modeling liver pathologies.

Relationship between Newly Fallen Snow Density and Polarimetric Parameters Obtained from X-Band Radar Observations along the Sea of Japan Coast in January 2021

Abstract The density of newly fallen snow ρN is an important parameter for assessing accumulated snowfall depth. We examined the relationships between polarimetric parameters of X-band radar and the ρN in dry snow cases with ground temperatures less than 0°C. Our study was based on observations at Niigata Prefecture, Japan, along the coastal region of the Sea of Japan. This region is subjected primarily to sea-effect snow during the winter monsoon season, and convective clouds and rimed snow are common. We assumed that snow particles that accumulated on the ground originated from altitudes above an altitude with a temperature of −15°C, and we focused on the ratio of the differential phase KDP to radar reflectivity Zh, which is influenced by both aspect ratio and inverse particle size. We found that KDP/Zh at an altitude with a temperature of −15°C exhibited a greater magnitude for lower ρN values. Its correlation coefficient was the best among the polarimetric parameters that we examined. The difference in ice crystal flatness is highlighted rather than the difference in size because aggregation growth has not progressed at this altitude. On the basis of this result, we propose an empirical relationship between KDP/Zh at an altitude with a temperature of −15°C and ρN on the ground, thereby facilitating the estimation of snowfall depth by combining the estimated ρN with the liquid equivalent snowfall rate from, for example, Zh or KDP. Significance Statement This study aims to estimate the density of newly fallen (just-accumulated) snow from polarimetric radar observations. Understanding the newly fallen snow density will help to determine the exact snowfall depth. Focusing on polarimetric parameters at an altitude with a temperature of −15°C, we conducted radar and ground-based observations of snow particles and found that the newly fallen snow density of dry snow can be estimated. We were able to highlight the difference in ice crystal flatness before aggregation growth progressed by focusing on higher altitudes.

(10–13)-oriented semipolar GaN growth on (10–10) m-plane ScAlMgO4 substrate

Abstract We report the growth of a GaN layer on (10–10) m-plane ScAlMgO4 (SAM) substrate. The GaN layer demonstrated (10–13) preference growth orientation. The anisotropy of the crystalline quality was distinctly observed through X-ray rocking curve taken across the sample surface over various azimuths across the orthogonal directions [0001] and [1–210] of the SAM substrate. Notably, the crystalline quality exhibited gradual degradation as the substrate is rotated around its surface normal away from the c-direction [0001] of the SAM substrate toward the a-direction [11–20]. Additionally, basal stacking faults in the (10–13)-oriented GaN were observed along [0001] direction using scanning transmission electron microscopy. Moreover, the selected area electron diffraction analysis was utilized to confirm the (10–13) growth orientation that was found to be consistent with the X-ray diffraction result. The (10–13) GaN layer exhibited a metal face through integrated differential phase contrast imaging.

Performance analysis of a 400-Gbps DWDM-FSO system using advanced modulation formats and under adverse weather conditions

Free space optical (FSO) systems offer an attractive and cost-effective solution for providing communication services in remote regions, as they allow secure transmission without the need for licensing and with lower deployment costs. However, the performance of FSO systems can be significantly impacted by atmospheric turbulences, creating considerable challenges to their deployment. To meet the expanding bandwidth requirements in optical networks, dense wavelength division multiplexing (DWDM) has emerged as a viable option. The development of a 400-Gbps DWDM-FSO system with advanced modulation formats is the subject of this paper. To ensure efficient energy conservation in such a system, power consumption needs to be minimized while maintaining performance level; this calls for optimization of different components within the system. The system is made up of 10 channels and each channel can transmit data at 40 Gbps. Various modulation schemes like carrier-suppressed return-to-zero, modified duo binary return-to-zero, differential phase shift keying, and duo binary return-to-zero are studied for their impact on system performance parameters Q-factor and bit error rate (BER) in C-band around 1550 nm wavelengths. The assessment is also extended to the effects that changing FSO length, input power, and data rate have on these two parameters as well as an evaluation regarding how differing atmospheric conditions influence the FSO system’s effectiveness.

Assessing Vulnerabilities in Line Length Parameterization and the Per-Unit-Length Paradigm for Phase Modulation and Figure-of-Merit Evaluation in 60 GHz Liquid Crystal Phase Shifters

The figure-of-merit (FoM) is a crucial metric in evaluating liquid crystal (LC) phase shifters, significantly influencing the selection of superior device candidates. This paper identifies, for the first time, a fundamental limitation in the widely-used High-Frequency Structure Simulator (HFSS), a closed-source commercial tool, when modeling reconfigurable delay line phase shifters (RDLPS) based on LC at millimeter-wave (mmW) frequencies for Beyond 5G (B5G) and Sixth-Generation (6G) applications. Specifically, the study reveals unreliable predictions of differential phase shifts (DPS) when using the line length parameterization (LLP) approach, with an accuracy of only 47.22%. These LLP-induced inaccuracies lead to misleading FoM calculations, potentially skewing comparative analyses against phase shifters implemented with different geometries or advanced technologies. Additionally, the per-unit-length (PUL) paradigm, commonly employed by microwave circuit engineers for evaluating and optimizing microwave transmission line designs, is also found to have limitations in the context of mmW RDLPS based on LC. The PUL methodology underestimates the FoM by 1.38206°/dB for an LC coaxial RDLPS at 60 GHz. These findings underscore a critical symmetry implication, where the assumed symmetry in phase shift response is violated, resulting in inconsistent performance assessments. To address these challenges, a remediation strategy based on a scenario-based “Length-for-π” (LFP) framework is proposed, offering more accurate performance characterization and enabling better-informed decision-making in mmW phase shifter design.

Using ADTS and CNN methods to effectively monitor CD, crosstalk, and OSNR in an optical network

The article presents the results of a method based on asynchronous delay-tap sampling (ADTS) and convolutional neural network (CNN) for determining simultaneously occurring disturbances described using the chromatic dispersion (CD), crosstalk and optical signal-to-noise ratio (OSNR) parameters. The ADTS method was used to generate training and test data for the convolutional network, which in turn was used to learn to recognize interference from said data. The tests were carried out for a transmission speed of 10 Gbit/s and for on-off keying (OOK) and differential phase shift keying (DPSK) modulation. Very good results were obtained in recognizing simultaneously occurring phenomena. Accuracy of over 99% was achieved for CD and crosstalk for DPSK modulation and over 98% for OOK modulation. In the case of amplified spontaneous emission (ASE) noise, slightly weaker results were obtained, above 95–96% for both modulations. Based on the conducted research, it was determined that the use of ADTS and CNN methods enables monitoring of simultaneously occurring CD, crosstalk, and ASE noise in the physical layer of the optical network, while maintaining the requirements for modern monitoring systems.

Ferromagnetism in High Entropy Cantor alloy triggered and tuned by severe plastic deformation

The process of severe plastic deformation (SPD) introduces unique conditions to materials, leading to the emergence of novel properties. This research specifically investigates the observation of deformation-induced ferromagnetism resulting from SPD processing. High-pressure torsion (HPT) is utilized to process both single-phase and nanocomposite high entropy alloys (HEAs). Vibrating sample magnetometry (VSM) confirms that HPT processing triggers the development of ferromagnetic properties. The distribution and alignment of magnetic domains post-SPD treatment are further examined using differential phase contrast scanning transmission electron microscopy (DPC STEM). Atom probe tomography (APT) analysis suggests that this phenomenon stems from the localized enrichment of ferromagnetic elements, particularly Ni, induced by deformation. This observation underscores the ‘cocktail effect’ in HEAs, whereby interactions between different elements has led to this unique magnetic behavior. Additionally, deliberate mechanical mixing of the CoCrFeMnNi alloy with a HfNbTaTiZr HEA, comprising non-ferromagnetic constituents, introduces a large rotational strain that alters the ferromagnetic properties. This mixing facilitates a transition from a random orientation of magnetic domains, as seen in the HPT-processed single CoCrFeMnNi alloy, to a coordinated alignment within the nanocomposite HEA.

Two phases of gonadal sex differentiation in zebrafish with ZZ/ZW sex determination system

Zebrafish sex chromosomes have been identified in the wild Nadia (NA) strain, and its sex determination belongs to the female-heterogametic ZZ/ZW system. Here, we investigate the correlation between ZZ/ZW sex chromosomes in the NA strain with sex-related factors, and sort out the complicated process of sex determination in zebrafish. Two phases exist during zebrafish sex differentiation. In the first phase, ZW gonads differentiate into juvenile ovary while ZZ gonads remain indifferent. In the second phase, ZW gonads either continue ovary development or undergo female-to-male transition, while ZZ gonads undergo direct male development. The W chromosome may contribute to the first phase while the abundance of germ cells and other factors may be involved in the second phase of sex differentiation in zebrafish.

Ultra-fast Digital DPC Yielding High Spatio-temporal Resolution for Low-Dose Phase Characterization.

In the scanning transmission electron microscope, both phase imaging of beam-sensitive materials and characterization of a material's functional properties using in situ experiments are becoming more widely available. As the practicable scan speed of 4D-STEM detectors improves, so too does the temporal resolution achievable for both differential phase contrast (DPC) and ptychography. However, the read-out burden of pixelated detectors, and the size of the gigabyte to terabyte sized data sets, remain a challenge for both temporal resolution and their practical adoption. In this work, we combine ultra-fast scan coils and detector signal digitization to show that a high-fidelity DPC phase reconstruction can be achieved from an annular segmented detector. Unlike conventional analog data phase reconstructions from digitized DPC-segment images yield reliable data, even at the fastest scan speeds. Finally, dose fractionation by fast scanning and multi-framing allows for postprocess binning of frame streams to balance signal-to-noise ratio and temporal resolution for low-dose phase imaging for in situ experiments.