Plant hypersensitive induced reaction protein facilitates cell death induced by secreted xylanase associated with the pathogenicity of Sclerotinia sclerotiorum.

Necrotrophic fungal plant pathogens employ cell death-inducing proteins (CDIPs) to facilitate infection. However, the specific CDIPs and their mechanisms in pathogenic processes of Sclerotinia sclerotiorum, a necrotrophic pathogen that causes disease in many economically important crop species, have not yet been clearly defined. This study found that S. sclerotiorum secretes SsXyl2, a glycosyl hydrolase family 11 xylanase, at the late stage of hyphal infection. SsXyl2 targets the apoplast of host plants to induce cell death independent of xylanase activity. Targeted disruption of SsXyl2 leads to serious impairment of virulence, which can be recovered by a catalytically impaired SsXyl2 variant, thus supporting the critical role of cell death-inducing activity of SsXyl2 in establishing successful colonization of S. sclerotiorum. Remarkably, infection by S. sclerotiorum induces the accumulation of Nicotiana benthamiana hypersensitive-induced reaction protein 2 (NbHIR2). NbHIR2 interacts with SsXyl2 at the plasma membrane and promotes its localization to the cell membrane and cell death-inducing activity. Furthermore, gene-edited mutants of NbHIR2 displayed increased resistance to the wild-type strain of S. sclerotiorum, but not to the SsXyl2-deletion strain. Hence, SsXyl2 acts as a CDIP that manipulates host cell physiology by interacting with hypersensitive induced reaction protein to facilitate colonization by S. sclerotiorum. These findings provide valuable insights into the pathogenic mechanisms of CDIPs in necrotrophic pathogens and lead to a more promising approach for breeding resistant crops against S. sclerotiorum.

Metabolite discovery through global annotation of untargeted metabolomics data.

Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.

Temporal structured illumination and vision-transformer enables large field-of-view binary snapshot ptychography.

Ptychography, a widely used computational imaging method, generates images by processing coherent interference patterns scattered from an object of interest. In order to capture scenes with large field-of-view (FoV) and high spatial resolution simultaneously in a single shot, we propose a temporal-compressive structured-light Ptychography system. A novel three-step reconstruction algorithm composed of multi-frame spectra reconstruction, phase retrieval, and multi-frame image stitching is developed, where we employ the emerging Transformer-based network in the first step. Experimental results demonstrate that our system can expand the FoV by 20× without losing spatial resolution. Our results offer huge potential for enabling lensless imaging of molecules with large FoV as well as high spatial-temporal resolutions. We also notice that due to the loss of low-intensity information caused by the compressed sensing process, our method so far is only applicable to binary targets.

Multiphoton emission of single CdZnSe/ZnS quantum dots coupled with plasmonic Au nanoparticles.

The fluorescence blinking and low multiphoton emission of quantum dots (QDs) have limited their application in lasing, light-emitting diodes, and so on. Coupling of single QDs to plasmonic nanostructures is an effective approach to control the photon properties. Here plasmon-exciton systems including Au nanoparticles and CdZnSe/ZnS QDs were investigated at the single particle level. With the modulation of the local electromagnetic field, the fluorescence intensity of single QDs is increased, accompanied by a significant suppression in blinking behavior, and the lifetime is shortened from 15 ns to 2 ns. Moreover, the second-order photon intensity correlation at zero lag time g2(0) of coupled single QDs is larger than 0.5, indicating an increased probability of multiphoton emission. The enhancement factors of radiative and nonradiative decay rates of QDs coupled with Au nanoparticles are calculated. The sharply increased radiative decay rate can be comparable to the nonradiative Auger rate, leading to dominated multiple exciton radiative recombination with PL intensity enhancement, suppressed blinking, lifetime shortening, and multiphoton emission. The results of the exciton decay dynamics and emission properties of single QDs in this work are helpful in exploring the mechanism of plasmon-exciton interaction and optoelectronic application of single QDs.

In situ reprogramming of cardiac fibroblasts into cardiomyocytes in mouse heart with chemicals.

Cardiomyocytes are terminal differentiated cells and have limited ability to proliferate or regenerate. Condition like myocardial infarction causes massive death of cardiomyocytes and is the leading cause of death. Previous studies have demonstrated that cardiac fibroblasts can be induced to transdifferentiate into cardiomyocytes in vitro and in vivo by forced expression of cardiac transcription factors and microRNAs. Our previous study have demonstrated that full chemical cocktails could also induce fibroblast to cardiomyocyte transdifferentiation both in vitro and in vivo. With the development of tissue clearing techniques, it is possible to visualize the reprogramming at the whole-organ level. In this study, we investigated the effect of the chemical cocktail CRFVPTM in inducing in situ fibroblast to cardiomyocyte transdifferentiation with two strains of genetic tracing mice, and the reprogramming was observed at whole-heart level with CUBIC tissue clearing technique and 3D imaging. In addition, single-cell RNA sequencing (scRNA-seq) confirmed the generation of cardiomyocytes from cardiac fibroblasts which carries the tracing marker. Our study confirms the use of small molecule cocktails in inducing in situ fibroblast to cardiomyocyte reprogramming at the whole-heart level and proof-of-conceptly providing a new source of naturally incorporated cardiomyocytes to help heart regeneration.

Roadmap on computational methods in optical imaging and holography [invited].

Computational methods have been established as cornerstones in optical imaging and holography in recent years. Every year, the dependence of optical imaging and holography on computational methods is increasing significantly to the extent that optical methods and components are being completely and efficiently replaced with computational methods at low cost. This roadmap reviews the current scenario in four major areas namely incoherent digital holography, quantitative phase imaging, imaging through scattering layers, and super-resolution imaging. In addition to registering the perspectives of the modern-day architects of the above research areas, the roadmap also reports some of the latest studies on the topic. Computational codes and pseudocodes are presented for computational methods in a plug-and-play fashion for readers to not only read and understand but also practice the latest algorithms with their data. We believe that this roadmap will be a valuable tool for analyzing the current trends in computational methods to predict and prepare the future of computational methods in optical imaging and holography. Supplementary Information: The online version contains supplementary material available at 10.1007/s00340-024-08280-3.

Node-downloadable frequency transfer system based on a mode-locked laser with over 100 km of fiber.

To meet the requirements of time-frequency networks and enable frequency downloadability for nodes along the link, we demonstrated the extraction of stable frequency signals at nodes using a mode-locked laser under the condition of 100 km laboratory fiber. The node consists of a simple structure that utilizes widely used optoelectronic devices and enables plug-and-play applications. In addition, the node can recover frequency signals with multiple frequencies, which are useful for scenarios that require different frequencies. Here, we experimentally demonstrated a short-term frequency instability of 2.83 × 10-13@1 s and a long-term frequency instability of 1.18 × 10-15@10,000 s at the node, which is similar to that at the remote site of the frequency transfer system. At the same time, frequency signals with different frequencies also achieved stable extraction with the same performance at the node. Our results can support the distributed application under large-scale time-frequency networks.

Multi-nodes dissemination of stable radio frequency with 10-17 instability over 2000 km optical fiber.

To meet the demand of flexible access for high-precision synchronization frequency, we demonstrate multi-node stable radio frequency (RF) dissemination over a long-distance optical fiber. Stable radio frequency signals can be extracted at any node along the optical fiber, not just at the endpoint. The differential mixing structure (DMS) is employed to avoid the frequency harmonic leakage and enhance the precision. The phase-locked loop (PLL) provides frequency reference for the DMS while improving the signal to noise ratio (SNR) of dissemination signal. We measure the frequency instability of multi-node stable frequency dissemination system (MFDS) at different locations along the 2,000 km optical fiber. The measured short-term instability with average time of 1 s are 1.90 × 10-14 @ 500 km, 2.81 × 10-14 @ 1,000 km, 3.46 × 10-14 @ 1,500 km, and 3.84 × 10-14 @ 2,000 km respectively. The long-term instability with average time of 10,000 s are basically the same at any position of the optical fiber, which is about (6.24 ± 0.05) × 10-17. The resulting instability is sufficient for the propagation of precision active hydrogen masers.

Experimental upstream transmission of continuous variable quantum key distribution access network.

Continuous variable quantum key distribution that can be implemented using only low-cost and off-the-shelf components reveals great potential in practical large-scale realization. Access networks, as a modern network necessity, connect many end-users to the network backbone. In this work, we first demonstrate upstream transmission quantum access networks using continuous variable quantum key distribution. A two-end-user quantum access network is then experimentally realized. Through phase compensation, data synchronization, and other technical upgrades, we achieve a secret key rate of the total network of 390 kbits/s. In addition, we extend the case of a two-end-user quantum access network to the case of a multiplicity of users, and analyze the network capacity in the case of a multiplicity of users by measuring the additive excess noise from different time slots.

Comprehensive assessment of osteoporosis in lumbar spine using compositional MR imaging of trabecular bone.

OBJECTIVES: To comprehensively assess osteoporosis in the lumbar spine, a compositional MR imaging technique is proposed to quantify proton fractions for all the water components as well as fat in lumbar vertebrae measured by a combination of a 3D short repetition time adiabatic inversion recovery prepared ultrashort echo time (STAIR-UTE) MRI and IDEAL-IQ. METHODS: A total of 182 participants underwent MRI, quantitative CT, and DXA. Lumbar collagen-bound water proton fraction (CBWPF), free water proton fraction (FWPF), total water proton fraction (TWPF), bone mineral density (BMD), and T-score were calculated in three vertebrae (L2-L4) for each subject. The correlations of the CBWPF, FWPF, and TWPF with BMD and T-score were investigated respectively. A comprehensive diagnostic model combining all the water components and clinical characteristics was established. The performances of all the water components and the comprehensive diagnostic model to discriminate between normal, osteopenia, and osteoporosis cohorts were also evaluated using receiver operator characteristic (ROC). RESULTS: The CBWPF showed strong correlations with BMD (r = 0.85, p < 0.001) and T-score (r = 0.72, p < 0.001), while the FWPF and TWPF showed moderate correlations with BMD (r = 0.65 and 0.68, p < 0.001) and T-score (r = 0.47 and 0.49, p < 0.001). The high area under the curve values obtained from ROC analysis demonstrated that CBWPF, FWPF, and TWPF have the potential to differentiate the normal, osteopenia, and osteoporosis cohorts. At the same time, the comprehensive diagnostic model shows the best performance. CONCLUSIONS: The compositional MRI technique, which quantifies CBWPF, FWPF, and TWPF in trabecular bone, is promising in the assessment of bone quality. KEY POINTS: • Compositional MR imaging technique is able to quantify proton fractions for all the water components (i.e., collagen-bound water proton fraction (CBWPF), free water proton fraction (FWPF), and total water proton fraction (TWPF)) in the human lumbar spine. • The biomarkers derived from the compositional MR imaging technique showed moderate to high correlations with bone mineral density (BMD) and T-score and showed good performance in distinguishing people with different bone mass. • The comprehensive diagnostic model incorporating CBWPF, FWPF, TWPF, and clinical characteristics showed the highest clinical diagnostic capability for the assessment of osteoporosis.