Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.).

Background: The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments. Results: Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1). Conclusions: We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Genome-wide identification of Brassinosteroid insensitive 1-associated receptor kinase 1 genes and expression analysis in response to pathogen infection in cucumber (Cucumis sativus L.).

BACKGROUND: BAK1 (Brassinosteroid insensitive 1-associated receptor kinase 1) plays an important role in disease resistance in plants. However, the function of BAK1 family in cucumber and the decisive genes for disease-resistance remain elusive. RESULTS: Here, we identified 27 CsBAK1s in cucumber, and classified them into five subgroups based on phylogenetic analysis and gene structure. CsBAK1s in the same subgroup shared the similar motifs, but different gene structures. Cis-elements analysis revealed that CsBAK1s might respond to various stress and growth regulation. Three segmentally duplicated pairwise genes were identified in cucumber. In addition, Ka/Ks analysis indicated that CsBAK1s were under positive selection during evolution. Tissue expression profile showed that most CsBAK1s in Subgroup II and IV showed constitutive expression, members in other subgroups showed tissue-specific expression. To further explore whether CsBAK1s were involved in the resistance to pathogens, the expression patterns of CsBAK1s to five pathogens (gummy stem blight, powdery mildew, downy mildew, grey mildew, and fusarium wilt) reveled that different CsBAK1s had specific roles in different pathogen infections. The expression of CsBAK1-14 was induced/repressed significantly by five pathogens, CsBAK1-14 might play an important role in disease resistance in cucumber. CONCLUSIONS: 27 BAK1 genes were identified in cucumber from a full perspective, which have important functions in pathogen infection. Our study provided a theoretical basis to further clarify the function of BAK1s to disease resistance in cucumber.

Emerging Advances around Nanofluidic Transport and Mass Separation under Confinement in Atomically Thin Nanoporous Graphene.

Membrane separation stands as an environmentally friendly, high permeance and selectivity, low energy demand process that deserves scientific investigation and industrialization. To address intensive demand, seeking appropriate membrane materials to surpass trade-off between permeability and selectivity and improve stability is on the schedule. 2D materials offer transformational opportunities and a revolutionary platform for researching membrane separation process. Especially, the atomically thin graphene with controllable porosity and structure, as well as unique properties, is widely considered as a candidate for membrane materials aiming to provide extreme stability, exponentially large selectivity combined with high permeability. Currently, it has shown promising opportunities to develop separation membranes to tackle bottlenecks of traditional membranes, and it has been of great interest for tremendously versatile applications such as separation, energy harvesting, and sensing. In this review, starting from transport mechanisms of separation, the material selection bank is narrowed down to nanoporous graphene. The study presents an enlightening overview of very recent developments in the preparation of atomically thin nanoporous graphene and correlates surface properties of such 2D nanoporous materials to their performance in critical separation applications. Finally, challenges related to modulation and manufacturing as well as potential avenues for performance improvements are also pointed out.

CsMLO8/11 are required for full susceptibility of cucumber stem to powdery mildew and interact with CsCRK2 and CsRbohD.

Powdery mildew (PM) is one of the most destructive diseases that threaten cucumber production globally. Efficient breeding of novel PM-resistant cultivars will require a robust understanding of the molecular mechanisms of cucumber resistance against PM. Using a genome-wide association study, we detected a locus significantly correlated with PM resistance in cucumber stem, pm-s5.1. A 1449-bp insertion in the CsMLO8 coding region at the pm-s5.1 locus resulted in enhanced stem PM resistance. Knockout mutants of CsMLO8 and CsMLO11 generated by CRISPR/Cas9 both showed improved PM resistance in the stem, hypocotyl, and leaves, and the double mutant mlo8mlo11 displayed even stronger resistance. We found that reactive oxygen species (ROS) accumulation was higher in the stem of these mutants. Protein interaction assays suggested that CsMLO8 and CsMLO11 could physically interact with CsRbohD and CsCRK2, respectively. Further, we showed that CsMLO8 and CsCRK2 competitively interact with the C-terminus of CsRbohD to affect CsCRK2-CsRbohD module-mediated ROS production during PM defense. These findings provide new insights into the understanding of CsMLO proteins during PM defense responses.

Stereo Image Restoration via Attention-Guided Correspondence Learning.

Although stereo image restoration has been extensively studied, most existing work focuses on restoring stereo images with limited horizontal parallax due to the binocular symmetry constraint. Stereo images with unlimited parallax (e.g., large ranges and asymmetrical types) are more challenging in real-world applications and have rarely been explored so far. To restore high-quality stereo images with unlimited parallax, this paper proposes an attention-guided correspondence learning method, which learns both self- and cross-views feature correspondence guided by parallax and omnidirectional attention. To learn cross-view feature correspondence, a Selective Parallax Attention Module (SPAM) is proposed to interact with cross-view features under the guidance of parallax attention that adaptively selects receptive fields for different parallax ranges. Furthermore, to handle asymmetrical parallax, we propose a Non-local Omnidirectional Attention Module (NOAM) to learn the non-local correlation of both self- and cross-view contexts, which guides the aggregation of global contextual features. Finally, we propose an Attention-guided Correspondence Learning Restoration Network (ACLRNet) upon SPAMs and NOAMs to restore stereo images by associating the features of two views based on the learned correspondence. Extensive experiments on five benchmark datasets demonstrate the effectiveness and generalization of the proposed method on three stereo image restoration tasks including super-resolution, denoising, and compression artifact reduction.

The mechanisms of target and non-target resistance to QoIs in Corynespora Cassiicola.

Corynespora leaf spot, caused by Corynespora cassiicola, is a foliar disease in cucumber. While the application of quinone outside inhibitors (QoIs) is an effective measure for disease control, it carries the risk of resistance development. In our monitoring of trifloxystrobin resistance from 2008 to 2020, C. cassiicola isolates were categorized into three populations: sensitive isolates (S, 0.01 < EC50 < 0.83 µg/mL), moderately resistant isolates (MR, 1.18 < EC50 < 55.67 µg/mL), and highly resistant isolates (HR, EC50 > 56.98 µg/mL). The resistance frequency reached up to 90% during this period, with an increasing trend observed in the annual average EC50 values of all the isolates. Analysis of the CcCytb gene revealed that both MR and HR populations carried the G143A mutation. Additionally, we identified mitochondrial heterogeneity, with three isolates carrying both G143 and A143 in MR and HR populations. Interestingly, isolates with the G143A mutation (G143A-MR and G143A-HR) displayed differential sensitivity to QoIs. Further experiments involving gene knockout and complementation demonstrated that the major facilitator superfamily (MFS) transporter (CcMfs1) may contribute to the disparity in sensitivity to QoIs between the G143A-MR and G143A-HR populations. However, the difference in sensitivity caused by the CcMfs1 transporter is significantly lower than the differences observed between the two populations. This suggests additional mechanisms contributing to the variation in resistance levels among C. cassiicola isolates. Our study highlights the alarming level of trifloxystrobin resistance in C. cassiicola in China, emphasizing the need for strict prohibition of QoIs use. Furthermore, our findings shed light on the occurrence of both target and non-target resistance mechanisms associated with QoIs in C. cassiicola.

Covalently Functionalized Nanopores for Highly Selective Separation of Monovalent Ions.

Biological ion channels possess prominent ion transport performances attributed to their critical chemical groups across the continuous nanoscale filters. However, it is still a challenge to imitate these sophisticated performances in artificial nanoscale systems. Herein, this work develops the strategy to fabricate functionalized graphene nanopores in pioneer based on the synergistic regulation of the pore size and chemical properties of atomically thin confined structure through decoupling etching combined with in situ covalent modification. The modified graphene nanopores possess asymmetric ion transport behaviors and efficient monovalent metal ions sieving (K+ /Li+ selectivity ≈48.6). Meanwhile, it also allows preferential transport for cations, the resulting membranes exhibit a K+ /Cl- selectivity of 76 and a H+ /Cl- selectivity of 59.3. The synergistic effects of steric hindrance and electrostatic interactions imposing a higher energy barrier for Cl- or Li+ across nanopores lead to ultra-selective H+ or K+ transport. Further, the functionalized graphene nanopores generate a power density of 25.3 W m-2 and a conversion efficiency of 33.9%, showing potential application prospects in energy conversion. The theoretical studies quantitatively match well with the experimental results. The feasible preparation of functionalized graphene nanopores paves the way toward direct investigation on ion transport mechanism and advanced design in devices.

Modulation of transport at the interface in the microporous layer for high power density proton exchange membrane fuel cells.

The proton exchange membrane (PEM) fuel cell is a device that demonstrates a significant potential for environmental sustainability, since it efficiently converts chemical energy into electrical energy. The microporous layer (MPL) in PEM fuel cells promotes gas transport and eliminates water. Nevertheless, the power density of PEM fuel cells is restricted by ohmic losses and mass transport losses in conventional MPLs. In this study, we enhanced the power density of proton exchange membrane (PEM) fuel cells through the identification of appropriate materials and the mitigation of mass transport losses occurring at the interface between the microporous layer and the catalyst layer. The incorporation of high electron conductivity, slip behavior at the interface between graphene and water, and rapid water evaporation facilitated by nanoporous graphene effectively address transport-related challenges. We evaluated two types of graphene as potential substitutes for carbon black in the microporous layer (MPL). The enhanced power density (up to 1.1 W cm-2) under all humidity conditions and reduced mass transport resistance (a 75 % reduction compared to carbon black MPL) make them promising candidates for next-generation PEM fuel cells. Furthermore, these findings provide guidance for controlling interfacial mass transport in colloidal systems.

Preanchoring Enabled Directional Modification of Atomically Thin Membrane for High-Performance Osmotic Energy Generation.

Salinity gradient energy is an environmentally friendly energy source that possesses potential to meet the growing global energy demand. Although covalently modified nanoporous graphene membranes are prospective candidates to break the trade-off between ion selectivity and permeability, the random reaction sites and inevitable defects during modification reduce the reaction efficiency and energy conversion performance. Here, we developed a preanchoring method to achieve directional modification near the graphene nanopores periphery. Numerical simulation revealed that the improved surface charge density around nanopores results in exceptional K+/Cl- selectivity and osmotic energy conversion performance, which agreed well with experimental results. Ionic transport measurements showed that the directionally modified graphene membranes achieved an outstanding power density of 81.6 W m-2 with an energy conversion efficiency of 35.4% under a 100-fold salinity gradient, outperforming state-of-the-art graphene-based nanoporous membranes. This work provided a facile approach for precise modification of nanoporous graphene membranes and opened up new ways for osmotic power harvesting.

Case report of epileptic seizure during awake craniotomy of functional area glioma and literature study.

Intraoperative seizure is the most prevalent and serious complication of awake craniotomy in functional areas, which may not only trigger complications of the surgical procedure or even the failure of awake craniotomy but also may result in adverse consequences to patients. The influencing factors of intraoperative seizures are unclear, and only the possible influencing factors can be acquired from the examination and summary of existing cases to offer guidance for the seizure prevention of intraoperative epilepsy.

Natural variation in STAYGREEN contributes to low-temperature tolerance in cucumber.

Low-temperature (LT) stress threatens cucumber production globally; however, the molecular mechanisms underlying LT tolerance in cucumber remain largely unknown. Here, using a genome-wide association study (GWAS), we found a naturally occurring single nucleotide polymorphism (SNP) in the STAYGREEN (CsSGR) coding region at the gLTT5.1 locus associated with LT tolerance. Knockout mutants of CsSGR generated by clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 exhibit enhanced LT tolerance, in particularly, increased chlorophyll (Chl) content and reduced reactive oxygen species (ROS) accumulation in response to LT. Moreover, the C-repeat Binding Factor 1 (CsCBF1) transcription factor can directly activate the expression of CsSGR. We demonstrate that the LT-sensitive haplotype CsSGRHapA , but not the LT-tolerant haplotype CsSGRHapG could interact with NON-YELLOW COLORING 1 (CsNYC1) to mediate Chl degradation. Geographic distribution of the CsSGR haplotypes indicated that the CsSGRHapG was selected in cucumber accessions from high latitudes, potentially contributing to LT tolerance during cucumber cold-adaptation in these regions. CsSGR mutants also showed enhanced tolerance to salinity, water deficit, and Pseudoperonospora cubensis, thus CsSGR is an elite target gene for breeding cucumber varieties with broad-spectrum stress tolerance. Collectively, our findings provide new insights into LT tolerance and will ultimately facilitate cucumber molecular breeding.

Slip-Enhanced Transport by Graphene in the Microporous Layer for High Power Density Proton-Exchange Membrane Fuel Cells.

Proton exchange membrane (PEM) fuel cells are a promising and environmentally friendly device to directly convert hydrogen energy into electric energy. However, water flooding and gas transport losses degrade its power density owing to structural issues (cracks, roughness, etc.) of the microporous layer (MPL). Here, we introduce a green material, supercritical fluid exfoliated graphene (s-Gr), to act as a network to effectively improve gas transport and water management. The assembled PEM fuel cell achieves a power density of 1.12 W cm-2. This improved performance is attributed to the reduction of cracks and the slip of water and gas on the s-Gr surface, in great contrast to the nonslip behavior on carbon black (CB). These findings open up an avenue to solve the water and gas transport problem in porous media by materials design with low friction and provide a new opportunity to boost high power density PEM fuel cells.

Unsupervised Low-Light Video Enhancement With Spatial-Temporal Co-Attention Transformer.

Existing low-light video enhancement methods are dominated by Convolution Neural Networks (CNNs) that are trained in a supervised manner. Due to the difficulty of collecting paired dynamic low/normal-light videos in real-world scenes, they are usually trained on synthetic, static, and uniform motion videos, which undermines their generalization to real-world scenes. Additionally, these methods typically suffer from temporal inconsistency (e.g., flickering artifacts and motion blurs) when handling large-scale motions since the local perception property of CNNs limits them to model long-range dependencies in both spatial and temporal domains. To address these problems, we propose the first unsupervised method for low-light video enhancement to our best knowledge, named LightenFormer, which models long-range intra- and inter-frame dependencies with a spatial-temporal co-attention transformer to enhance brightness while maintaining temporal consistency. Specifically, an effective but lightweight S-curve Estimation Network (SCENet) is first proposed to estimate pixel-wise S-shaped non-linear curves (S-curves) to adaptively adjust the dynamic range of an input video. Next, to model the temporal consistency of the video, we present a Spatial-Temporal Refinement Network (STRNet) to refine the enhanced video. The core module of STRNet is a novel Spatial-Temporal Co-attention Transformer (STCAT), which exploits multi-scale self- and cross-attention interactions to capture long-range correlations in both spatial and temporal domains among frames for implicit motion estimation. To achieve unsupervised training, we further propose two non-reference loss functions based on the invertibility of the S-curve and the noise independence among frames. Extensive experiments on the SDSD and LLIV-Phone datasets demonstrate that our LightenFormer outperforms state-of-the-art methods.

Recent developments in the cleavage, functionalization, and conjugation of proteins and peptides at tyrosine residues.

Peptide and protein selective modification at tyrosine residues has become an exploding field of research as tyrosine constitutes a robust alternative to lysine and cysteine-targeted traditional peptide/protein modification protocols. This review offers a comprehensive summary of the latest advances in tyrosine-selective cleavage, functionalization, and conjugation of peptides and proteins from the past three years. This updated overview complements the extensive body of work on site-selective modification of peptides and proteins, which holds significant relevance across various disciplines, including chemical, biological, medical, and material sciences.

Knee Flexion-Assisted Method for Human-Exoskeleton System.

The knee has gradually become an important research target for the lower extremity exoskeleton. However, the issue that whether the flexion-assisted profile based on the contractile element (CE) is effective throughout the gait is still a research gap. In this study, we first analyze the effective flexion-assisted method through the passive element's (PE) energy storage and release mechanism. Specifically, ensuring assisting within an entire joint power period and the human's active movement is a prerequisite for the CE-based flexion-assisted method. Second, we design the enhanced adaptive oscillator (EAO) to ensure the human's active movement and the integrity of the assistance profile. Third, a fundamental frequency estimation based on discrete Fourier transform (DFT) is proposed to shorten the convergence time of EAO significantly. The finite state machine (FSM) is designed to improve the stability and practicality of EAO. Finally, we demonstrate the effectiveness of the prerequisite condition for the CE-based flexion-assisted method by using electromyography (EMG) and metabolic indicators in experiments. In particular, for the knee joint, CE-based flexion assistance should be within an entire joint power period rather than just in the negative power phase. Ensuring the human's active movement will also significantly reduce the activation of antagonistic muscles. This study will aid in designing assistive methods from the perspective of natural human actuation and apply the EAO to the human-exoskeleton system.

GWAS reveals novel loci and identifies a pentatricopeptide repeat-containing protein (CsPPR) that improves low temperature germination in cucumber.

Low temperatures (LTs) negatively affect the percentage and rate of cucumber (Cucumis sativus L.) seed germination, which has deleterious effects on yield. Here, a genome-wide association study (GWAS) was used to identify the genetic loci underlying low temperature germination (LTG) in 151 cucumber accessions that represented seven diverse ecotypes. Over two years, phenotypic data for LTG i.e., relative germination rate (RGR), relative germination energy (RGE), relative germination index (RGI) and relative radical length (RRL), were collected in two environments, and 17 of the 151 accessions were found to be highly cold tolerant using cluster analysis. A total of 1,522,847 significantly associated single-nucleotide polymorphism (SNP) were identified, and seven loci associated with LTG, on four chromosomes, were detected: gLTG1.1, gLTG1.2, gLTG1.3, gLTG4.1, gLTG5.1, gLTG5.2, and gLTG6.1 after resequencing of the accessions. Of the seven loci, three, i.e., gLTG1.2, gLTG4.1, and gLTG5.2, showed strong signals that were consistent over two years using the four germination indices, and are thus strong and stable for LTG. Eight candidate genes associated with abiotic stress were identified, and three of them were potentially causal to LTG: CsaV3_1G044080 (a pentatricopeptide repeat-containing protein) for gLTG1.2, CsaV3_4G013480 (a RING-type E3 ubiquitin transferase) for gLTG4.1, and CsaV3_5G029350 (a serine/threonine-protein kinase) for gLTG5.2. The function for CsPPR (CsaV3_1G044080) in regulating LTG was confirmed, as Arabidopsis lines ectopically expressing CsPPR showed higher germination and survival rates at 4°C compared to the wild-type, which preliminarily illustrates that CsPPR positively regulates cucumber cold tolerance at the germination stage. This study will provide insights into cucumber LT-tolerance mechanisms and further promote cucumber breeding development.

GALNT2 sustains glioma stem cells by promoting CD44 expression.

Glioblastoma (GBM) is the most prevalent and malignant brain tumor and is highly resistant to currently available treatment. In this study, we reveal that polypeptide N-acetylgalactosaminyltransferase 5 (GALNT2) expression level was elevated in GBM, IDH1 wildtype glioma, and GBM stem cells (GSCs). GALNT2 increased expression correlated with GBM patients' unfavorable clinical outcomes. Functionally, targeting GALNT2 blocks GSCs cell proliferation, self-renewal, and malignant invasion through repressing CD44 expression. Most importantly, we first provide evidence suggesting that STAT3 activates GALNT2 expression at the transcriptional level by directly binding to the GALNT2 promoter. Through a rational screening, we found a GALNT2 inhibitor that dramatically suppresses GSCs self-maintenance in vitro and in vivo. Collectively, we uncovered the critical function of GALNT2 in promoting GSCs self-maintenance and GBM progression and may provide a new potential drug for GBM clinical therapy.

SiamBAN: Target-Aware Tracking With Siamese Box Adaptive Network.

Variation of scales or aspect ratios has been one of the main challenges for tracking. To overcome this challenge, most existing methods adopt either multi-scale search or anchor-based schemes, which use a predefined search space in a handcrafted way and therefore limit their performance in complicated scenes. To address this problem, recent anchor-free based trackers have been proposed without using prior scale or anchor information. However, an inconsistency problem between classification and regression degrades the tracking performance. To address the above issues, we propose a simple yet effective tracker (named Siamese Box Adaptive Network, SiamBAN) to learn a target-aware scale handling schema in a data-driven manner. Our basic idea is to predict the target boxes in a per-pixel fashion through a fully convolutional network, which is anchor-free. Specifically, SiamBAN divides the tracking problem into classification and regression tasks, which directly predict objectiveness and regress bounding boxes, respectively. A no-prior box design is proposed to avoid tuning hyper-parameters related to candidate boxes, which makes SiamBAN more flexible. SiamBAN further uses a target-aware branch to address the inconsistency problem. Experiments on benchmarks including VOT2018, VOT2019, OTB100, UAV123, LaSOT and TrackingNet show that SiamBAN achieves promising performance and runs at 35 FPS.

Biomimetic Nanosonosensitizers Combined with Noninvasive Ultrasound Actuation to Reverse Drug Resistance and Sonodynamic-Enhanced Chemotherapy against Orthotopic Glioblastoma.

Glioblastoma (GBM) is the most devastating brain tumor and highly resistant to conventional chemotherapy. Herein, we introduce biomimetic nanosonosensitizer systems (MDNPs) combined with noninvasive ultrasound (US) actuation for orthotopic GBM-targeted delivery and sonodynamic-enhanced chemotherapy. MDNPs were fabricated with biodegradable and pH-sensitive polyglutamic acid (PGA) and the chemotherapeutic agent and sonosensitizer doxorubicin (DOX), camouflaged with human GBM U87 cell membranes. MDNPs presented homologous targeting accumulation and in vivo long-term circulation ability. They effectively passed through the blood-brain barrier (BBB) under US assistance and reached the orthotopic GBM site. MDNPs exhibited controllable US-elicited sonodynamic effect by generation of reactive oxygen species (ROS). ROS not only induced cancer cell apoptosis but also downregulated drug-resistance-related factors to disrupt chemoresistance and increase sensitivity to chemotherapy. The in vivo study of orthotopic GBM treatments further proved that MDNPs exhibited US-augmented synergistic antitumor efficacy and strongly prolonged the survival rate of mice. The use of low-dose DOX and the safety of US enabled repeated treatment (4 times) without obvious cardiotoxicity. This effective and safe US-enhanced chemotherapy strategy with the advantages of noninvasive brain delivery and high drug sensitivity holds great promise for deep-seated and drug-resistant tumors.