The MdHSC70-MdWRKY75 module mediates basal apple thermotolerance by regulating the expression of heat shock factor genes.

Heat stress severely restricts the growth and fruit development of apple (Malus domestica). Little is known about the involvement of WRKY proteins in the heat tolerance mechanism in apple. In this study, we found that the apple transcription factor MdWRKY75 responds to heat and positively regulates basal thermotolerance. Apple plants that overexpressed MdWRKY75 were more tolerant to heat stress, while silencing MdWRKY75 caused the opposite phenotype. RNA-seq and reverse transcription quantitative PCR showed that heat shock transcription factor genes (MdHsfs) could be the potential targets of MdWRKY75. Electrophoretic mobility shift, yeast one-hybrid, ß-glucuronidase, and dual-luciferase assays showed that MdWRKY75 can bind to the promoters of MdHsf4, MdHsfB2a, and MdHsfA1d and activate their expression. Apple plants that overexpressed MdHsf4, MdHsfB2a, and MdHsfA1d exhibited heat tolerance and rescued the heat sensitive phenotype of MdWRKY75-Ri3. In addition, apple heat shock cognate 70 (MdHSC70) interacts with MdWRKY75, as shown by yeast two-hybrid, split luciferase, bimolecular fluorescence complementation, and pull-down assays. MdHSC70 acts as a negative regulator of the heat stress response. Apple plants that overexpressed MdHSC70 were sensitive to heat, while virus-induced gene silencing of MdHSC70 enhanced heat tolerance. Additional research showed that MdHSC70 exhibits heat sensitivity by interacting with MdWRKY75 and inhibiting MdHsfs expression. In summary, we proposed a mechanism for the response of apple to heat that is mediated by the 'MdHSC70/MdWRKY75-MdHsfs' molecular module, which enhances our understanding of apple thermotolerance regulated by WRKY transcription factors.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression.

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

MdERF114 enhances the resistance of apple roots to Fusarium solani by regulating the transcription of MdPRX63.

As the main fungal etiologic agent of apple (Malus domestica) replant disease (ARD), Fusarium solani seriously damages apple roots. Ethylene response factors (ERFs) play an important role in plant resistance to biotic stress. Here, we show that MdERF114 is expressed during F. solani infections and positively regulates the resistance of apple roots to F. solani. Yeast one-hybrid, dual-luciferase, electrophoretic mobility shift assays and determinations of lignin content indicated that MdERF114 directly binds the GCC-box of the MdPEROXIDASE63 (MdPRX63) promoter and activates its expression, resulting in lignin deposition in apple roots and increased resistance to F. solani. We identified a WRKY family transcription factor, MdWRKY75, that binds to the W-box of the MdERF114 promoter. Overexpression of MdWRKY75 enhanced resistance of apple roots to F. solani. MdMYB8 interacted with MdERF114 to enhance resistance to F. solani by promoting the binding of MdERF114 to the MdPRX63 promoter. In summary, our findings reveal that the MdWRKY75-MdERF114-MdMYB8-MdPRX63 module is required for apple resistance to F. solani and the application of this mechanism by Agrobacterium rhizogenes-mediated root transformation provides a promising strategy to prevent ARD.

Learning mapping by curve iteration estimation For real-time underwater image enhancement.

The degradation and attenuation of light in underwater images impose constraints on underwater vision tasks. However, the complexity and the low real-time performance of most current image enhancement algorithms make them challenging in practical applications. To address the above issues, we propose a new lightweight framework for underwater image enhancement. We adopt the curve estimation to learn the mapping between images rather than end-to-end networks, which greatly reduces the requirement for computing resources. Firstly, a designed iterative curve with parameters is used to simulate the mapping from the raw to the enhanced image. Then, the parameters of this curve are learned with a parameter estimation network called CieNet and a set of loss functions. Experimental results demonstrate that our proposed method is superior to existing algorithms in terms of evaluating indexes and visual perception quality. Furthermore, our highly lightweight network enables it to be easily integrated into small devices, making it highly applicable. The extremely short running-time of our method facilitates real-time underwater image enhancement.

The Role of Momentum Partitioning in Covariance Ion Imaging Analysis.

We present results from a covariance ion imaging study, which employs extensive filtering, on the relationship between fragment momenta to gain deeper insight into photofragmentation dynamics. A new data analysis approach is introduced that considers the momentum partitioning between the fragments of the breakup of a molecular polycation to disentangle concurrent fragmentation channels, which yield the same ion species. We exploit this approach to examine the momentum exchange relationship between the products, which provides direct insight into the dynamics of molecular fragmentation. We apply these techniques to extensively characterize the dissociation of 1-iodopropane and 2-iodopropane dications prepared by site-selective ionization of the iodine atom using extreme ultraviolet intense femtosecond laser pulses with a photon energy of 95 eV. Our assignments are supported by classical simulations, using parameters largely obtained directly from the experimental data.

Robust Point Cloud Registration for Aircraft Engine Pipeline Systems.

Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line-Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine's piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.

Investigations on diverse dynamics of soliton triplets in mode-locked fiber lasers.

Optical soliton molecules exhibiting behaviors analogous to matter molecules have been the hotspot in the dissipative system for decades. Based on the dispersion Fourier transformation technique, the real-time spectral interferometry has become the popular method to reveal the internal dynamics of soliton molecules. The rising degrees of freedom in pace with the increased constitutes of soliton molecules yield more intriguing sights into the internal motions. Yet the soliton molecules with three or more pulses are rarely investigated owing to the exponentially growing complexity. Here, we present both experimental and theoretical studies on the soliton molecules containing three solitons. Different assemblies of the constitutes are categorized as different types of soliton triplet akin to the geometric isomer, including equally-spaced triplet and unequally-spaced triplet. Typical soliton triplets with different dynamics including regular internal motions, hybrid phase dynamics and complex dynamics involving separation evolution are experimentally analyzed and theoretically simulated. Specifically, the energy difference which remains elusive in experiments are uncovered through the simulation of diverse triplets with plentiful dynamics. Moreover, the multi-dimensional interaction space is proposed to visualize the internal motions in connection with the energy exchange, which play significant roles in the interplays among the solitons. Both the experimental and numerical simulations on the isomeric soliton triplets would release a larger number of degrees of freedom and motivate the potentially artificial configuration of soliton molecules for various ultrafast applications, such as all-optical buffering and multiple encoding for telecommunications.

UIEOGP: an underwater image enhancement method based on optical geometric properties.

Due to the inconsistent absorption and scattering effects of different wavelengths of light, underwater images often suffer from color casts, blurred details, and low visibility. To address this image degradation problem, we propose a robust and efficient underwater image enhancement method named UIEOGP. It can be divided into the following three steps. First, according to the light attenuation effect presented by Lambert Beer's law, combined with the variance change after attenuation, we estimate the depth of field in the underwater image. Then, we propose a local-based color correction algorithm to address the color cast issue in underwater images, employing the statistical distribution law. Finally, drawing inspiration from the law of light propagation, we propose detail enhancement algorithms, each based on the geometric properties of circles and ellipses, respectively. The enhanced images produced by our method feature vibrant colors, improved contrast, and sharper detail. Extensive experiments show that our method outperforms current state-of-the-art methods. In further experiments, we found that our method is beneficial for downstream tasks of underwater image processing, such as the detection of keypoints and edges in underwater images.

Compact single-shot soft X-ray photon spectrometer for free-electron laser diagnostics.

The photon spectrum from free-electron laser (FEL) light sources offers valuable information in time-resolved experiments and machine optimization in the spectral and temporal domains. We have developed a compact single-shot photon spectrometer to diagnose soft X-ray spectra. The spectrometer consists of an array of off-axis Fresnel zone plates (FZP) that act as transmission-imaging gratings, a Ce:YAG scintillator, and a microscope objective to image the scintillation target onto a two-dimensional imaging detector. This spectrometer operates in segmented energy ranges which covers tens of electronvolts for each absorption edge associated with several atomic constituents: carbon, nitrogen, oxygen, and neon. The spectrometer's performance is demonstrated at a repetition rate of 120 Hz, but our detection scheme can be easily extended to 200 kHz spectral collection by employing a fast complementary metal oxide semiconductor (CMOS) line-scan camera to detect the light from the scintillator. This compact photon spectrometer provides an opportunity for monitoring the spectrum downstream of an endstation in a limited space environment with sub-electronvolt energy resolution.

Microwave target location method based on the diamond NV color center.

We propose a method for microwave target source localization based on the diamond nitrogen vacancy color center. We use coherent population oscillation effect and modulation and demodulation techniques to achieve the detection of microwave intensity of microwave target sources, with a minimum detection intensity of 0.59 µW. Positioning of the microwave source was achieved within 50×100c m 2 distance from the system 1 m away using the cubic spline interpolation algorithm and minimum mean squared error. The maximum positioning error was 3.5 cm. This method provides a new, to the best of our knowledge, idea for the passive localization of microwave targets.

Distance correlation application to gene co-expression network analysis.

BACKGROUND: To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear (such as Pearson's correlation) and monotonic (such as Spearman's correlation) dependence metrics, are not enough to observe the nature of real biological systems. Hence, introducing a more informative correlation metric when constructing gene co-expression networks is still an interesting topic. RESULTS: In this paper, we test distance correlation, a correlation metric integrating both linear and non-linear dependence, with other three typical metrics (Pearson's correlation, Spearman's correlation, and maximal information coefficient) on four different arrays (macrophage and liver) and RNA-seq (cervical cancer and pancreatic cancer) datasets. Among all the metrics, distance correlation is distribution free and can provide better performance on complex relationships and anti-outlier. Furthermore, distance correlation is applied to Weighted Gene Co-expression Network Analysis (WGCNA) for constructing a gene co-expression network analysis method which we named Distance Correlation-based Weighted Gene Co-expression Network Analysis (DC-WGCNA). Compared with traditional WGCNA, DC-WGCNA can enhance the result of enrichment analysis and improve the module stability. CONCLUSIONS: Distance correlation is better at revealing complex biological relationships between gene profiles compared with other correlation metrics, which contribute to more meaningful modules when analyzing gene co-expression networks. However, due to the high time complexity of distance correlation, the implementation requires more computer memory.

TPQCI: A topology potential-based method to quantify functional influence of copy number variations.

Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI).

Multichannel photodissociation dynamics in CS2 studied by ultrafast electron diffraction.

The structural dynamics of photoexcited gas-phase carbon disulfide (CS2) molecules are investigated using ultrafast electron diffraction. The dynamics were triggered by excitation of the optically bright 1B2(1Σu+) state by an ultraviolet femtosecond laser pulse centred at 200 nm. In accordance with previous studies, rapid vibrational motion facilitates a combination of internal conversion and intersystem crossing to lower-lying electronic states. Photodissociation via these electronic manifolds results in the production of CS fragments in the electronic ground state and dissociated singlet and triplet sulphur atoms. The structural dynamics are extracted from the experiment using a trajectory-fitting filtering approach, revealing the main characteristics of the singlet and triplet dissociation pathways. Finally, the effect of the time-resolution on the experimental signal is considered and an outlook to future experiments provided.

Disentangling sequential and concerted fragmentations of molecular polycations with covariant native frame analysis.

We present results from an experimental ion imaging study into the fragmentation dynamics of 1-iodopropane and 2-iodopropane following interaction with extreme ultraviolet intense femtosecond laser pulses with a photon energy of 95 eV. Using covariance imaging analysis, a range of observed fragmentation pathways of the resulting polycations can be isolated and interrogated in detail at relatively high ion count rates (∼12 ions shot-1). By incorporating the recently developed native frames analysis approach into the three-dimensional covariance imaging procedure, contributions from three-body concerted and sequential fragmentation mechanisms can be isolated. The angular distribution of the fragment ions is much more complex than in previously reported studies for triatomic polycations, and differs substantially between the two isomeric species. With support of simple simulations of the dissociation channels of interest, detailed physical insights into the fragmentation dynamics are obtained, including how the initial dissociation step in a sequential mechanism influences rovibrational dynamics in the metastable intermediate ion and how signatures of this nuclear motion manifest in the measured signals.

Nonadiabatic Excited State Dynamics of Organic Chromophores: Take-Home Messages.

Nonadiabatic excited state dynamics are important in a variety of processes. Theoretical and experimental developments have allowed for a great progress in this area, while combining the two is often necessary and the best approach to obtain insight into the photophysical behavior of molecules. In this Feature Article we use examples of our recent work combining time-resolved photoelectron spectroscopy with theoretical nonadiabatic dynamics to highlight important lessons we learned. We compare the nonadiabatic excited state dynamics of three different organic molecules with the aim of elucidating connections between structure and dynamics. Calculations and measurements are compared for uracil, 1,3-cyclooctadiene, and 1,3-cyclohexadiene. The comparison highlights the role of rigidity in influencing the dynamics and the difficulty of capturing the dynamics accurately with calculations.

Exogenous Dopamine and MdTyDC Overexpression Enhance Apple Resistance to Fusarium solani.

Fusarium solani, one of the main pathogenic fungi involved in apple replant disease (ARD), is a serious threat to apple growth and development. Dopamine and tyrosine decarboxylase (TyDC), a key enzyme in the dopamine synthesis pathway, have been reported to play an active role in plant responses to biotic and abiotic stresses, but little is known about the functions of dopamine and Malus domestica TyDC (MdTyDC) in the interaction between F. solani and apple roots. In this study, seedlings treated with exogenous dopamine and apple plants overexpressing MdTyDC were inoculated with F. solani; both treatments reduced the root system damage caused by F. solani. After inoculation with F. solani, exogenous dopamine increased dopamine content in the seedlings; alleviated the inhibition of biomass accumulation; increased root metabolic activity, photosynthetic efficiency, and antioxidant enzyme activities; reduced reactive oxygen species accumulation; and upregulated the expression of genes encoding chitinase, ß-1,3-glucanase, and pathogenesis-related proteins. Similar results were observed in MdTyDC-overexpressing apple plants. In addition, the overexpression of MdTyDC increased tyramine content and the deposition of cell wall-bound amines in roots. Overall, our results reveal that exogenous dopamine and overexpression of MdTyDC enhance apple resistance to F. solani, which is an important application for the prevention of ARD.

Optimization of brightness in a Nd:YAG laser by maximizing the single-mode power factor with an intra-cavity spatial light modulator.

We report a simple and effective approach for designing resonators with high brightness and high mode discrimination based on optimizing the single-mode power factor of the fundamental mode, which represents the total power extracted by the fundamental mode from the gain medium. By optimizing the single-mode power factor of the fundamental mode, the cavity can be designed to operate in mono-mode, increasing mode purity and improving brightness significantly. Our method is verified on a digital laser with a spatial light modulator as the rear mirror, and the loaded phase profile is acquired by a simulated annealing algorithm. As a result, the optimized resonator with a Fresnel number of 7.2 operates in a single fundamental mode, and the brightness of the output beam yields 240% and 276% improvement, compared with conventional plane-plane and plane-concave resonators, respectively. This approach is ready to be applied to more sophisticated mode selection and may serve as a general method for designing cavities with high efficiency and high brightness.

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery.

BACKGROUND: Gene co-expression networks are widely studied in the biomedical field, with algorithms such as WGCNA and lmQCM having been developed to detect co-expressed modules. However, these algorithms have limitations such as insufficient granularity and unbalanced module size, which prevent full acquisition of knowledge from data mining. In addition, it is difficult to incorporate prior knowledge in current co-expression module detection algorithms. RESULTS: In this paper, we propose a novel module detection algorithm based on topology potential and spectral clustering algorithm to detect co-expressed modules in gene co-expression networks. By testing on TCGA data, our novel method can provide more complete coverage of genes, more balanced module size and finer granularity than current methods in detecting modules with significant overall survival difference. In addition, the proposed algorithm can identify modules by incorporating prior knowledge. CONCLUSION: In summary, we developed a method to obtain as much as possible information from networks with increased input coverage and the ability to detect more size-balanced and granular modules. In addition, our method can integrate data from different sources. Our proposed method performs better than current methods with complete coverage of input genes and finer granularity. Moreover, this method is designed not only for gene co-expression networks but can also be applied to any general fully connected weighted network.

Effect of dynamic correlation on the ultrafast relaxation of uracil in the gas phase.

The photophysics and photochemistry of DNA/RNA nucleobases have been extensively investigated during the past two decades, both experimentally and theoretically. The ultrafast relaxation of the canonical nucleobases following photoexcitation is of significant interest when it comes to understanding how nature has ensured their photostability. Here we study the excited state dynamics of uracil which is a nucleobase found in RNA. Although theory and experiment have shed significant light on understanding the photoexcited dynamics of uracil, there are still disagreements in the literature about specific details. In order to examine how the dynamics is influenced by the underlying electronic structure theory, we have performed non-adiabatic excited state dynamics simulations of uracil using on-the-fly trajectory surface hopping methodology on potential energy surfaces calculated at different electronic structure theory levels (CASSCF, MRCIS, XMS-CASPT2, TD-DFT). These simulations reveal that the dynamics are very sensitive to the underlying electronic structure theory, with the multi-reference theory levels that include dynamic correlation, predicting that there is no trapping on the absorbing S2 state, in contrast to predictions from lower level electronic structure results. The dynamics are instead governed by ultrafast decay to the ground state, or trapping on the dark S1 state.

NV center pumped and enhanced by nanowire ring resonator laser to integrate a 10 µm-scale spin-based sensor structure.

In this work, we propose a 10 µm-scale spin-based sensor structure, which mainly consists of a nanowire (NW) ring resonator laser, nitrogen-vacancy (NV) defects in a nanodiamond (ND) and a microwave (MW) antenna. The NW laser was bent into a ring with a gap to pump the NV defects in the ND which was assembled in the gap with the diameter of ∼8 µm. And the fluorescent light of NV defects was enhanced by the NW ring resonator about 8 times. Furthermore, the NW laser pulse was produced by the optical switch and a simple plus-sequences was designed to get the Rabi oscillation signal. Based on the Rabi oscillation, a Ramsey-type sequence was used to detect the magnetic field with the sensitivity of 83 nT √Hz-1 for our 10 µm-scale spin-based sensor structure. It proves the spin state in our structure allows for coherent spin manipulation for more complex quantum control schemes. And our structure fulfills the fundamental requirements to develop chip-scale spin-based sensors.