RhMED15a-like, a subunit of the Mediator complex, is involved in the drought stress response in Rosa hybrida.

BACKGROUND: Rose (Rosa hybrida) is a globally recognized ornamental plant whose growth and distribution are strongly limited by drought stress. The role of Mediator, a multiprotein complex crucial for RNA polymerase II-driven transcription, has been elucidated in drought stress responses in plants. However, its physiological function and regulatory mechanism in horticultural crop species remain elusive. RESULTS: In this study, we identified a Tail module subunit of Mediator, RhMED15a-like, in rose. Drought stress, as well as treatment with methyl jasmonate (MeJA) and abscisic acid (ABA), significantly suppressed the transcript level of RhMED15a-like. Overexpressing RhMED15a-like markedly bolstered the osmotic stress tolerance of Arabidopsis, as evidenced by increased germination rate, root length, and fresh weight. In contrast, the silencing of RhMED15a-like through virus induced gene silencing in rose resulted in elevated malondialdehyde accumulation, exacerbated leaf wilting, reduced survival rate, and downregulated expression of drought-responsive genes during drought stress. Additionally, using RNA-seq, we identified 972 differentially expressed genes (DEGs) between tobacco rattle virus (TRV)-RhMED15a-like plants and TRV controls. Gene Ontology (GO) analysis revealed that some DEGs were predominantly associated with terms related to the oxidative stress response, such as 'response to reactive oxygen species' and 'peroxisome'. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment highlighted pathways related to 'plant hormone signal transduction', in which the majority of DEGs in the jasmonate (JA) and ABA signalling pathways were induced in TRV-RhMED15a-like plants. CONCLUSION: Our findings underscore the pivotal role of the Mediator subunit RhMED15a-like in the ability of rose to withstand drought stress, probably by controlling the transcript levels of drought-responsive genes and signalling pathway elements of stress-related hormones, providing a solid foundation for future research into the molecular mechanisms underlying drought tolerance in rose.

Dynamic three-dimensional deformation measurement by polarization-multiplexing of full complex amplitude.

This paper provides an extensive discussion of a complex amplitude-based dynamic three-dimensional deformation measurement method, in which the phase and amplitude of the speckle field are used for out-of-plane and in-plane deformation calculation respectively. By determining the optimal polarization states of the speckle field and reference field from the comprehensive analysis of measurement mathematical model in the principle of polarization multiplexing, the 3-step phase-shifting interferograms and one speckle gram can be directly recorded by a polarization camera in a single shot. The out-of-plane deformation would be recovered from the subtraction of speckle phases that are demodulated by a special least square algorithm; speckle gram with improved quality is offered for correlation computation to obtain in-plane deformation. The advancement and significance of the optimized strategy are intuitively demonstrated by comparing the measurement accuracy under different combinations of polarization states. Finally, the dynamic thermal deformation experiment reveals the potential in practical real-time applications.

Optical TTD compensation network-based phase precoding for THz massive MIMO systems.

In sixth generation (6G) communications, terahertz (THz) communication is one of the most important technologies in the future due to its ultra-bandwidth, where hybrid beamforming has been widely used to solve the severe transmission attenuation in the THz band. However, the use of frequency-flat phase shifters in hybrid beamforming leads to the beam split effect. To solve the beam split influence, we propose a novel optical true time delay compensation network (OTTDCN)-based phase precoding structure with low power consumption. In the proposed scheme, the OTTDCN pre-generates multiple beam compensation modes to achieve phase compensation for different frequencies. As a result, the compensated beams can be reoriented toward the target direction at different frequencies. Moreover, a low-complexity beam compensation mode-based hybrid precoding algorithm is proposed, where the selection of the optimal beam compensation modes used for all radio-frequency (RF) chains with finite beam compensation modes is considered. The results show that the OTTDCN-based phase precoding scheme can effectively alleviate the beam split effect with low power consumption and achieve near-optimal performance.

Sedation versus general anesthesia on all-cause mortality in patients undergoing percutaneous procedures: a systematic review and meta-analysis.

BACKGROUND: The comparison between sedation and general anesthesia (GA) in terms of all-cause mortality remains a subject of ongoing debate. The primary objective of our study was to investigate the impact of GA and sedation on all-cause mortality in order to provide clarity on this controversial topic. METHODS: A systematic review and meta-analysis were conducted, incorporating cohort studies and RCTs about postoperative all-cause mortality. Comprehensive searches were performed in the PubMed, EMBASE, and Cochrane Library databases, with the search period extending until February 28, 2023. Two independent reviewers extracted the relevant information, including the number of deaths, survivals, and risk effect values at various time points following surgery, and these data were subsequently pooled and analyzed using a random effects model. RESULTS: A total of 58 studies were included in the analysis, with a majority focusing on endovascular surgery. The findings of our analysis indicated that, overall, and in most subgroup analyses, sedation exhibited superiority over GA in terms of in-hospital and 30-day mortality. However, no significant difference was observed in subgroup analyses specific to cerebrovascular surgery. About 90-day mortality, the majority of studies centered around cerebrovascular surgery. Although the overall pooled results showed a difference between sedation and GA, no distinction was observed between the pooled ORs and the subgroup analyses based on RCTs and matched cohort studies. For one-year all-cause mortality, all included studies focused on cardiac and macrovascular surgery. No difference was found between the HRs and the results derived from RCTs and matched cohort studies. CONCLUSIONS: The results suggested a potential superiority of sedation over GA, particularly in the context of cardiac and macrovascular surgery, mitigating the risk of in-hospital and 30-day death. However, for the longer postoperative periods, this difference remains uncertain. TRIAL REGISTRATION: PROSPERO CRD42023399151; registered 24 February 2023.

A Foggy Weather Simulation Algorithm for Traffic Image Synthesis Based on Monocular Depth Estimation.

This study addresses the ongoing challenge for learning-based methods to achieve accurate object detection in foggy conditions. In response to the scarcity of foggy traffic image datasets, we propose a foggy weather simulation algorithm based on monocular depth estimation. The algorithm involves a multi-step process: a self-supervised monocular depth estimation network generates a relative depth map and then applies dense geometric constraints for scale recovery to derive an absolute depth map. Subsequently, the visibility of the simulated image is defined to generate a transmittance map. The dark channel map is then used to distinguish sky regions and estimate atmospheric light values. Finally, the atmospheric scattering model is used to generate fog simulation images under specified visibility conditions. Experimental results show that more than 90% of fog images have AuthESI values of less than 2, which indicates that their non-structural similarity (NSS) characteristics are very close to those of natural fog. The proposed fog simulation method is able to convert clear images in natural environments, providing a solution to the problem of lack of foggy image datasets and incomplete visibility data.

Fast and robust calibration method of liquid-crystal spatial light modulator based on polarization multiplexing.

We propose a fast and robust method for calibrating Spatial Light Modulators (SLMs) based on polarization phase-shifting interferometry. Our method effectively calibrates the SLM by addressing both the static aberration and nonlinear phase response, utilizing specially designed gray images loaded sequentially onto the SLM. Notably, we introduce a novel kinoform that effectively eliminates the influence of tilt phase shift between two shots of the polarization camera. This results in a highly accurate phase aberration map and phase modulation curve with exceptional stability, making it an ideal method to calibrate the SLM with exceptional efficiency and precision in real applications.

Flexible dynamic quantitative phase imaging based on division of focal plane polarization imaging technique.

This paper proposes a flexible and accurate dynamic quantitative phase imaging (QPI) method using single-shot transport of intensity equation (TIE) phase retrieval achieved by division of focal plane (DoFP) polarization imaging technique. By exploiting the polarization property of the liquid crystal spatial light modulator (LC-SLM), two intensity images of different defocus distances contained in orthogonal polarization directions can be generated simultaneously. Then, with the help of the DoFP polarization imaging, these images can be captured with single exposure, enabling accurate dynamic QPI by solving the TIE. In addition, our approach gains great flexibility in defocus distance adjustment by adjusting the pattern loaded on the LC-SLM. Experiments on microlens array, phase plate, and living human gastric cancer cells demonstrate the accuracy, flexibility, and dynamic measurement performance for various objects. The proposed method provides a simple, flexible, and accurate approach for real-time QPI without sacrificing the field of view.

Accurate dynamic 3D deformation measurement based on the synchronous multiplexing of polarization and speckle metrology.

An accurate dynamic 3D deformation measurement method realized by the combination of phase-shifting speckle interferometry and speckle correlation is proposed. By converting the speckle field and the reference field into a circular polarized and linear polarized state, the three-step phase-shifting speckle interferograms and one specklegram were recorded directly and simultaneously within a single image by using a polarization camera. Then, the out-of-plane deformation was demodulated from the synchronous phase-shifting fringe patterns, and the in-plane deformation was measured by performing correlation calculations by using specklegrams with the effect of the reference field ignored. Thus, the full-field 3D deformation was obtained precisely. Experimental results demonstrated the accuracy and dynamic measurement ability of the proposed method, which is compact and feasible for actual dynamic scenes.

Cops5 safeguards genomic stability of embryonic stem cells through regulating cellular metabolism and DNA repair.

The highly conserved COP9 signalosome (CSN), composed of 8 subunits (Cops1 to Cops8), has been implicated in pluripotency maintenance of human embryonic stem cells (ESCs). Yet, the mechanism for the CSN to regulate pluripotency remains elusive. We previously showed that Cops2, independent of the CSN, is essential for the pluripotency maintenance of mouse ESCs. In this study, we set out to investigate how Cops5 and Cops8 regulate ESC differentiation and tried to establish Cops5 and Cops8 knockout (KO) ESC lines by CRISPR/Cas9. To our surprise, no Cops5 KO ESC clones were identified out of 127 clones, while three Cops8 KO ESC lines were established out of 70 clones. We then constructed an inducible Cops5 KO ESC line. Cops5 KO leads to decreased expression of the pluripotency marker Nanog, proliferation defect, G2/M cell-cycle arrest, and apoptosis of ESCs. Further analysis revealed dual roles of Cops5 in maintaining genomic stability of ESCs. On one hand, Cops5 suppresses the autophagic degradation of Mtch2 to direct cellular metabolism toward glycolysis and minimize reactive oxygen species (ROS) production, thereby reducing endogenous DNA damage. On the other hand, Cops5 is required for high DNA damage repair (DDR) activities in ESCs. Without Cops5, elevated ROS and reduced DDR activities lead to DNA damage accumulation in ESCs. Subsequently, p53 is activated to trigger G2/M arrest and apoptosis. Altogether, our studies reveal an essential role of Cops5 in maintaining genome integrity and self-renewal of ESCs by regulating cellular metabolism and DDR pathways.

Sign-singularity solution in single-frame speckle interferometry with vortex-phase modulation.

We propose a sign-singularity solution in single-shot digital speckle interferometry based on vortex-phase modulation. The vortex phase is introduced through the reference beam as variation information by a reflective liquid crystal spatial light modulator. The sign singularity is eliminated with the help of a single spiral speckle fringe pattern. To effectively obtain the deformation phase, the measurement process is specially designed on the consideration of the modulation principle of the vortex phase, which is discussed in terms of theoretical analysis and simulation results. Experiments on out-of-plane deformation measurement reveal the feasibility of the proposed method and suggest the potential in actual dynamic measurement applications.

Single-shot quantitative phase imaging with phase modulation of a liquid crystal spatial light modulator (LC-SLM) under white light illumination.

We propose a novel, to the best of our knowledge, single-shot quantitative phase imaging (QPI) technique with the phase modulation of a liquid crystal spatial light modulator (LC-SLM) under white light illumination. By studying the phase modulation characteristics of an LC-SLM under white light illumination, images captured at different wavelengths are equivalent to those captured at different defocus distances when loading a Fresnel lens pattern on the LC-SLM. Consequently, a color camera is able to simultaneously acquire multi-intensity images at different defocus distances. Finally, the phase is retrieved from a single-shot color image using the transport of intensity equation. To demonstrate the flexibility and accuracy of our method, a photoetched phase object and human red blood cells are quantitatively measured. An investigation of living yeast cells is conducted to verify the dynamic measurement capability. The proposed method provides a simple, efficient, and flexible means to accomplish real-time high-resolution quantitative phase imaging without sacrificing the field of view (FOV), which can be further integrated into a conventional microscope to achieve real-time microscopic QPI.

Feature selection may improve deep neural networks for the bioinformatics problems.

MOTIVATION: Deep neural network (DNN) algorithms were utilized in predicting various biomedical phenotypes recently, and demonstrated very good prediction performances without selecting features. This study proposed a hypothesis that the DNN models may be further improved by feature selection algorithms. RESULTS: A comprehensive comparative study was carried out by evaluating 11 feature selection algorithms on three conventional DNN algorithms, i.e. convolution neural network (CNN), deep belief network (DBN) and recurrent neural network (RNN), and three recent DNNs, i.e. MobilenetV2, ShufflenetV2 and Squeezenet. Five binary classification methylomic datasets were chosen to calculate the prediction performances of CNN/DBN/RNN models using feature selected by the 11 feature selection algorithms. Seventeen binary classification transcriptome and two multi-class transcriptome datasets were also utilized to evaluate how the hypothesis may generalize to different data types. The experimental data supported our hypothesis that feature selection algorithms may improve DNN models, and the DBN models using features selected by SVM-RFE usually achieved the best prediction accuracies on the five methylomic datasets. AVAILABILITY AND IMPLEMENTATION: All the algorithms were implemented and tested under the programming environment Python version 3.6.6. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Development of point diffraction interferometer by a dimension-reduction-based phase-shifting algorithm.

To avoid exhaustive calibration of the shifter device in point diffraction interferometers, we present a dimension-reduction-based method to reconstruct the phase map from more phase-shifting fringe patterns with three or more frames. The proposed method assumes that the intensity space can be described adequately by the sine and cosine of multiple phase shifts introduced, which are the basis of the intensity space. Then, low-dimensional approximations of high-dimensional intensity spaces are determined by the newly developed reduced basis decomposition technique. Finally, the phase is reconstructed using the low-dimensional surrogates of the intensity spaces without the knowledge of accurate phase steps. Numerical and experimental studies demonstrated that the proposed method outperforms the existing popular phase reconstruction techniques in terms of accuracy and efficiency. Moreover, the performance of the proposed method is not limited by variations in the background and modulation, unlike the existing phase-shifting-algorithm-based approaches.

Two-frame fringe pattern phase demodulation using Gram-Schmidt orthonormalization with least squares method.

Gram-Schmidt (GS) orthogonal normalization is a fast and efficient two-frame fringe phase demodulation method. However, the precision of the GS method is limited due to the residual background terms and noise, as well as several approximation operations in the GS method. To obtain a phase map with higher accuracy, we propose an algorithm combining GS orthogonal normalization and least squares iterative (LSI) phase shift algorithm (GS&LSI). In our method, the phase was first obtained using GS method, and then a refinement operation using LSI was adopted to get the final wrapped phase map. Because of the LSI process, the demodulation result is greatly improved in many cases. Simulation and experimental result are presented to validate the potential of the proposed method.

Photonic high-fidelity storage and Doppler frequency shift of broadband RF pulse signals.

A microwave photonic system which can simultaneously realize the functions of rapidly tunable Doppler frequency shift (DFS) and high fidelity storage of broadband RF signals is proposed and verified. Single-sideband carrier-suppression modulation combined with dual-AOM frequency shifting ensures large-range and fast-responding DFS. And time-gated semiconductor amplifier (SOA) based fiber delay loop can realize high-fidelity RF pulse storage with high extinction ratio switching and amplification characteristics of time-gated SOA. A spurious rejection ratio greater than 40 dB, tuning range of DFS greater than ± 3 MHz, response speed of DFS less than 30 ns, and high fidelity storage of 4 GHz-12 GHz RF signals with greater than 381 circulations (corresponding 80 us delay time) are realized by the proposed structure. The maximum signal-to-noise ratio (SNR) is 13.6 dB within 381 circulations. Based on the experimental data, the simulation results show that the delay time also could be extended to 10 times more.

Rapid and robust two-dimensional phase unwrapping via deep learning.

Two-dimensional phase unwrapping algorithms are widely used in optical metrology and measurements. The high noise from interference measurements, however, often leads to the failure of conventional phase unwrapping algorithms. In this paper, we propose a deep convolutional neural network (DCNN) based method to perform rapid and robust two-dimensional phase unwrapping. In our approach, we employ a DCNN architecture, DeepLabV3+, with noise suppression and strong feature representation capabilities. The employed DCNN is first used to perform semantic segmentation to obtain the segmentation result of the wrapped phase map. We then combine the wrapped phase map with the segmentation result to generate the unwrapped phase. We benchmarked our results by comparing them with well-established methods. The reported approach out-performed the conventional path-dependent and path-independent algorithms. We also tested the robustness of the reported approach using interference measurements from optical metrology setups. Our results, again, clearly out-performed the conventional phase unwrap algorithms. The reported approach may find applications in optical metrology and microscopy imaging.

Photometric invariant stereo matching method.

A robust stereo matching method based on a comprehensive mathematical model for color formation process is proposed to estimate the disparity map of stereo images with noise and photometric variations. The band-pass filter with DoP kernel is firstly used to filter out noise component of the stereo images. Then the log-chromaticity normalization process is applied to eliminate the influence of lightning geometry. All the other factors that may influence the color formation process are removed through the disparity estimation process with a specific matching cost. Performance of the developed method is evaluated by comparing with some up-to-date algorithms. Experimental results are presented to demonstrate the robustness and accuracy of the method.

Non-null testing for aspheric surfaces using elliptical sub-aperture stitching technique.

We propose an elliptical sub-aperture stitching (ESAS) method to measure the aspheric surfaces. In our method, the non-null configuration is used to overcome the disadvantages of the null testing. By adding the dynamic tilt, the different local nearly null fringe patterns are obtained and the corresponding phase data in the elliptical masks is extracted with negligible retrace errors. In order to obtain the full aperture result, a stitching algorithm is developed to stitch all the phase data together. We firstly show the principle of our method. Then the performance of the proposed method is analyzed by simulation experiments. In the end, practical examples are given to demonstrate the correctness of the proposed method. The stitching result shows a good agreement with the full-aperture null testing result.

Importance of DNA nanotechnology for DNA methyltransferases in biosensing assays.

DNA methylation is the process by which specific bases on a DNA sequence acquire methyl groups under the catalytic action of DNA methyltransferases (DNMT). Abnormal changes in the function of DNMT are important markers for cancers and other diseases; therefore, the detection of DNMT and the selection of its inhibitors are critical to biomedical research and clinical practice. DNA molecules can undergo intermolecular assembly to produce functional aggregates because of their inherently stable physical and chemical properties and unique structures. Conventional DNMT detection methods are cumbersome and complicated processes; therefore, it is necessary to develop biosensing technology based on the assembly of DNA nanostructures to achieve rapid analysis, simple operation, and high sensitivity. The design of the relevant program has been employed in life science, anticancer drug screening, and clinical diagnostics. In this review, we explore how DNA assembly, including 2D techniques like hybridization chain reaction (HCR), rolling circle amplification (RCA), catalytic hairpin assembly (CHA), and exponential isothermal amplified strand displacement reaction (EXPAR), as well as 3D structures such as DNA tetrahedra, G-quadruplexes, DNA hydrogels, and DNA origami, enhances DNMT detection. We highlight the benefits of these DNA nanostructure-based biosensing technologies for clinical use and critically examine the challenges of standardizing these methods. We aim to provide reference values for the application of these techniques in DNMT analysis and early cancer diagnosis and treatment, and to alert researchers to challenges in clinical application.

Influence of environmental filtering and spatial processes on macroinvertebrate community in urban lakes in the Taihu Lake Basin, China.

Studies identifying the relative importance of multiple ecological processes in macroinvertebrate communities in urban lakes at a basin scale are rare. In this study, 14 urban lakes in the Taihu Lake Basin were selected to explore the relative importance of environmental filtering and spatial processes in the assembly of macroinvertebrate communities. Our findings revealed significant spatiotemporal variations in macroinvertebrate communities, both between lakes and across seasons. We found that environmental filtering exerted a greater influence on taxonomic total beta diversity and its individual components (species turnover and nestedness) compared to spatial processes. Key environmental variables such as water depth, water temperature, total dissolved solids, chlorophyll a, and lake surface area were found to be crucial in shaping macroinvertebrate communities within these urban lakes. The observed high spatial heterogeneity in environmental conditions, along with intermediate basin areas, good connectivity and short distances between lakes, and the high dispersal ability of dominant taxa, likely contributed to the dominance of environmental filtering in macroinvertebrate community assembly. Our study contributes to a better understanding of the underlying mechanisms governing macroinvertebrate community assembly in urban lakes, thereby providing valuable insights for studies on community ecology and water environmental protection in urban lakes.