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In this study, the solvent extraction and purification of flavonoids from three cultivars (coded as 1, 2 and 3) of Coreopsis tinctoria Nutt. were optimized based on the content of total flavonoids and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capacity. The flavonoids were analyzed and identified by high performance liquid chromatography (HPLC), mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. The results showed that methanol was found to be the best solvent for the extraction of flavonoids. The yield of flavonoids extracted from the first cultivar was the highest, and the total flavonoid content and DPPH radical scavenging capacity of the extract were 65.01 mg/g and 73.59%, respectively. Top 10 most abundant flavonoids were tentatively by HPLC-MS. Eight monomeric compounds were purified from the extract by macroporous resin chromatography, vacuum column chromatography, atmospheric column chromatography and gel permeation chromatography, and these compounds were identified as luteolin, 7,8,3’,4’-tetrahydroxyflavanone, taxifolin, okanin, quercetin, quercetagetin, flavanomarein and marein by MS and NMR spectroscopy. Okanin was determined as the signature flavonoid compound in C. tinctoria Nutt. by HPLC and DPPH radical scavenging activity.

ObjectiveTo analyze the changes in the time intervals between diagnosis and treatment and the influencing factors of diagnosis and treatment delay among rifampicin-resistant tuberculosis (RR-TB) patients from 2016 to 2021 in Yunnan province, to provide a reference for reducing the occurrence of diagnosis and treatment delay in patients. MethodsData of 2 189 RR-TB patients registered in Yunnan province from 2016 to 2021 were extracted from the Tuberculosis Management Information System (TMIS) – a subsystem of the China Disease Prevention and Control Information System – to analyze the time intervals between symptom onset and diagnosis and that between diagnosis and treatment for the patients with different demographic and other characteristics. The time intervals were described in median and percentile 25th/75th (M, P25/P75) days, and multivariate binary logistic regression was used to analyze factors influencing delays in diagnosis and treatment of RR-TB patients. ResultsFor all patients, the median number of days from symptom onset to confirmed diagnosis of RR-TB increased from 50 in 2016 to 109 in 2018, but then decreased annually to 42 in 2021, with a trend of first increasing and then decreasing. The RR-TB patients who underwent conventional drug susceptibility testing and received initial diagnosis at a prefectural or municipal-level medical institution were more likely to have delayed diagnosis, with the odd ratio (OR) and 95% confidence interval (95%CI) of 5.193 (3.750 – 7.193) and 1.449 (1.199 – 1.752), respectively. The median number of days from diagnosis to treatment for the 1 488 RR-TB patients being treated increased slightly from one day in 2016 to 11 days in 2021. The RR-TB patients with the following characteristics were more likely to have treatment delays: being male (OR = 1.309, 95%CI: 1.063 – 1.612), being a farmer (OR = 1.317, 95%CI: 1.022 – 1.698), and being a permanent resident (OR = 4.016, 95%CI: 3.220 – 5.008) ; whereas RR-TB patients of younger age were less likely to have treatment delay, with the OR (95%CI) of 0.676 (0.487 – 0.938), 0.687 (0.494 – 0.954), and 0.663 (0.489 – 0.901) for the patients aged 25 – 34, 35 – 44, and 45 – 55 years respectively, compared with those aged ≥ 65 years. ConclusionDuring 2016 – 2021, the time interval between symptom onset and diagnosis was significantly shortened and the interval between diagnosis and treatment was relatively short for RR-TB patients in Yunnan province but attention still needs to be paid to patients at high risk of delayed diagnosis and treatment.

ABSTRACT Background Despite significant advances in lung cancer treatment, cisplatin (DDP)‐based chemotherapy remains a cornerstone for managing the disease. However, the prevalence of chemoresistance presents a major challenge, limiting its effectiveness and contributing to poor outcomes. This underscores the urgent need for novel therapeutic strategies to overcome chemoresistance and improve chemotherapy efficacy in lung cancer patients. Exploring approaches to sensitize tumors to cisplatin could enhance treatment responses and overall survival rates. Methods and Results Our study utilized a variety of lung cancer models, including cell lines, mouse models, and patient‐derived organoids, to validate the synergistic cytotoxic effects of dihydroartemisinin (DHA) and cisplatin (DDP). When combined with DDP, we demonstrate that DHA is a promising therapeutic agent that effectively triggers ferroptosis in lung cancer cells, offering a potential strategy for overcoming chemoresistance. Mechanistically, the combination of DHA and DDP synergistically enhances ZIP14 expression, modulating iron homeostasis and upregulating oxidative stress, leading to both in vitro and in vivo ferroptosis. Notably, our findings revealed that the sequential administration of DDP followed by DHA significantly increases ZIP14 expression and induces superior therapeutic outcomes compared to the simultaneous administration or DHA followed by DDP. This observation underscores the importance of the drug administration order in optimizing treatment efficacy, providing new insights into enhancing chemotherapy response in lung cancer. Conclusion Our findings suggest that combining dihydroartemisinin (DHA) with cisplatin (DDP) presents a promising strategy to overcome chemoresistance in lung cancer patients. Importantly, administering DHA during chemotherapy intervals could further optimize treatment outcomes, enhancing the overall efficacy of lung cancer chemotherapy.

Abstract 2D magnetic materials hold substantial promise in information storage and neuromorphic device applications. However, achieving a 2D material with high Curie temperature (TC), environmental stability, and multi‐level magnetic states remains a challenge. This is particularly relevant for spintronic devices, which require multi‐level resistance states to enhance memory density and fulfil low power consumption and multi‐functionality. Here, the synthesis of 2D non‐layered triangular and hexagonal magnetite (Fe3O4) nanosheets are proposed with high TC and environmental stability, and demonstrate that the ultrathin triangular nanosheets show broad antiphase boundaries (bAPBs) and sharp antiphase boundaries (sAPBs), which induce multiple spin precession modes and multi‐level resistance. Conversely, the hexagonal nanosheets display slip bands with sAPBs associated with pinning effects, resulting in magnetic‐field‐driven spin texture reversal reminiscent of “0” and “1” switching signals. In support of the micromagnetic simulation, direct explanation is offer to the variation in multi‐level resistance under a microwave field, which is ascribed to the multi‐spin texture magnetization structure and the randomly distributed APBs within the material. These novel 2D magnetite nanosheets with unique spin textures and spin dynamics provide an exciting platform for constructing real multi‐level storage devices catering to emerging information storage and neuromorphic computing requirements.

Abstract Although strain engineering and soft-clamping techniques for attaining high Q-factors in nanoresonators have received much attention, their impact on nonlinear dynamics is not fully understood. In this study, we show that nonlinearity of high-Q Si3N4 nanomechanical string resonators can be substantially tuned by support design. Through careful engineering of support geometries, we control both stress and mechanical nonlinearities, effectively tuning nonlinear stiffness of two orders of magnitude. Our approach also allows control over the sign of the Duffing constant resulting in nonlinear softening of the mechanical mode that conventionally exhibits hardening behavior. We elucidate the influence of support design on the magnitude and trend of the nonlinearity using both analytical and finite element-based reduced-order models that validate our experimental findings. Our work provides evidence of the role of soft-clamping on the nonlinear dynamic response of nanoresonators, offering an alternative pathway for nullifying or enhancing nonlinearity in a reproducible and passive manner.

With the intensification of global climate change and the increasing complexity of agricultural environments, the improvement of rice stress tolerance is an important focus of current breeding research. This review summarizes the current knowledge on the impact of various abiotic stresses on rice and the associated epigenetic responses (DNA methylation). Abiotic stress factors, including high temperature, drought, cold, heavy metal pollution, and high salinity, have a negative impact on crop productivity. Epigenetic changes are key regulatory factors in plant stress responses, and DNA methylation is one of the earliest discovered and thoroughly studied mechanisms in these epigenetic regulatory mechanisms. The normal growth of rice is highly dependent on the environment, and changes in the environment can lead to rice sterility and severe yield loss. Changes in the regulation of the DNA methylation pathway are involved in rice’s response to stress. Various DNA methylation-regulating protein complexes that function during rice development have been identified. Significant changes in DNA methylation occur in numerous stress-responsive genes, particularly those in the abscisic acid signaling pathway. These findings underscore the complex mechanisms of the abiotic stress response in rice. We propose the effective improvement of tolerance traits by regulating the epigenetic status of rice and emphasize the role of DNA methylation in abiotic stress tolerance, thereby addressing global climate change and ensuring food security.

This paper improves the timeliness of satellite mission planning to cope with the rapid response to changes. In this paper, satellite mission planning is investigated. Firstly, the satellite dynamics model and mission planning model are established, and an improved Monte Carlo tree (Improved-MCTS) algorithm is proposed, which utilizes the Monte Carlo tree search in combination with the state uncertainty network (State-UN) to reduce the time of exploring the nodes (At the MCTS selection stage, the exploration of nodes specifically refers to the algorithm needing to decide whether to choose nodes that have already been visited (exploitation) or nodes that have not been visited yet (exploration)). The results show that this algorithm performs better in terms of profit (in this paper, the observation task is given a weight of 0–1, and each planned task will receive a profit; that is, a profit will be assigned at the initial moment) and convergence speed compared to the ant colony algorithm (ACO) and the asynchronous advantage actor critic (A3C).

The mixed state transport properties of type-II superconductors are strongly influenced by the dynamic behavior of quantized magnetic fluxoids around the critical temperature (T_{c}), where a combination of normal and superconducting properties is exhibited. To understand the mixed state transport properties of type-II superconducting NbN ultrathin films (2D) we measured sheet resistance (R_{xx}^{M}) and Hall resistance (R_{xy}^{M}) of a 5-nm-thick NbN film around T_{c} (10.75 K) at temperatures 10.40, 10.68, and 10.77 K. Hall resistance (HR) was measured in external out-of-plane and in-plane magnetic fields up to 6 T, using 100 µA and 1 mA driving current in Van der Pauw geometry. The electric field of applied bias and Lorentz force of applied external magnetic field causes a movement of the normal conducting electrons within each fluxoid. The moving fluxoids cause dissipation and generation of Hall voltage. We developed a macroscopic analysis of the Hall resistance arising from fluxoids, to advance the differentiation between dissipating current and superconducting currents in type-II superconductors at T_{c}. We have extracted the number of normal conducting carriers per fluxoid and areal density and mobility of the fluxoids in dependence on the external magnetic field. This differentiation provides valuable insights into the dissipation mechanisms observed during transport measurements, e.g., after localized heating due to single photon absorption in nanostructured type-II superconductors. Furthermore, the developed macroscopic analysis of Hall resistance of fluxoids shows promising potential for investigating the fundamental aspects of fluxoid-defect interactions in type-II superconductors.

Abstract Background Rice is the second-largest food crop in the world and vulnerable to bacterial leaf streak disease. A thorough comprehension of the genetic foundation of agronomic traits was essential for effective implementation of molecular marker-assisted selection. Results Our study aimed to evaluate the vulnerability of rice to bacterial leaf streak disease (BLS) induced by the gram-negative bacterium Xanthomonas oryzae pv. oryzicola (Xoc). In order to accomplish this, we first analyzed the population structure of 747 accessions and subsequently assessed their phenotypes 20 days after inoculation with a strain of Xoc, GX01. We conducted genome-wide association studies (GWAS) on a population of 747 rice accessions, consisting of both indica and japonica subpopulations, utilizing phenotypic data on resistance to bacterial leaf streak (RBLS) and sequence data. We identified a total of 20 QTLs associated with RBLS in our analysis. Through the integration of linkage mapping, sequence analysis, haplotype analysis, and transcriptome analysis, we were able to identify five potential candidate genes (OsRBLS1—OsRBLS5) that possess the potential to regulate RBLS in rice. In order to gain a more comprehensive understanding of the genetic mechanism behind resistance to bacterial leaf streak, we conducted tests on these genes in both the indica and japonica subpopulations, ultimately identifying superior haplotypes that suggest the potential utilization of these genes in breeding disease-resistant rice varieties. Conclusions The findings of our study broaden our comprehension of the genetic mechanisms underlying RBLS in rice and offer significant insights that can be applied towards genetic improvement and breeding of disease-resistant rice in rapidly evolving environmental conditions.

Objective: To understand the geographic differences and variations in the functional components of brown rice cores collected from global rice germplasms. Methods: Four functional components, γ-aminobutyric acid (GABA), resistant starch (RS), total flavonoids, and alkaloids, in brown rice from 690 mini-core collections from 31 countries from five continents and the International Rice Research Institute, were analyzed using a spectrophotometry colorimetric method, and the results were statistically validated. Conclusion: The highest average amounts of functional components were obtained in Asian germplasms, except for GABA, and total flavonoids were highest in brown rice from Europe and Oceania, followed by Asia. The highest coefficient of variation for GABA was observed in Asia; that for RS and total flavonoids was observed in Africa, followed by Asia; and that for alkaloids was observed in America, followed by Asia. Overall, Asian countries were the most prominent and representative zones with the highest genotypic potential for functional components of brown rice. Forty-one rice accessions with enriched functional components originated mostly from biodiversity-rich areas in China, followed by those in the Philippines. Late sowing favored the enrichment of these components in brown rice. The current study provides a reference for rice breeding with enriched functional constituents, and guidelines for screening functional rice that could be used for human chronic disease research.

Objective: Preterm birth (PTB) is considered as a public health problem and one of the main risk factors related to the global disease burden. The purpose of this study aims to explore the influence of exposure to major air pollutants at different pregnancies on PTB.Methods: The relationship between air pollutants and PTB in China was collected from cohort studies and case-control studies published before 30 April 2022. Meta-analysis was carried out with STATA 15.0 software.Results: A total of 2,115 papers were retrieved, of which 18 papers met the inclusion criteria. The comprehensive effect of pollutant exposure and PTB were calculated. PM2.5 during entire pregnancy and O3 exposure during third trimester were positively associated with preterm birth. Every 10 μg/m3 increase in the average concentration of PM2.5 during the whole pregnancy will increase the risk of premature delivery by 4%, and every 10 μg/m3 increase in the average concentration of O3 in the third trimester will increase the risk of premature delivery by 1%.Conclusion: Exposure to PM2.5 entire prenatal pregnancy and O3 in third trimester is associated with an increased risk of preterm birth occurrence.

Abstract Background Heterosis is widely used in agriculture. However, its molecular mechanisms are still unclear in plants. Here, we develop, sequence, and record the phenotypes of 418 hybrids from crosses between two testers and 265 rice varieties from a mini-core collection. Results Phenotypic analysis shows that heterosis is dependent on genetic backgrounds and environments. By genome-wide association study of 418 hybrids and their parents, we find that nonadditive QTLs are the main genetic contributors to heterosis. We show that nonadditive QTLs are more sensitive to the genetic background and environment than additive ones. Further simulations and experimental analysis support a novel mechanism, homo-insufficiency under insufficient background (HoIIB), underlying heterosis. We propose heterosis in most cases is not due to heterozygote advantage but homozygote disadvantage under the insufficient genetic background. Conclusion The HoIIB model elucidates that genetic background insufficiency is the intrinsic mechanism of background dependence, and also the core mechanism of nonadditive effects and heterosis. This model can explain most known hypotheses and phenomena about heterosis, and thus provides a novel theory for hybrid rice breeding in future.

Layered metal-organic frameworks attract interests for optoelectronics and spintronics. Here, the authors report a strategy to tune interlayer charge transport and thermoelectric properties via side-chain induced control of the layer spacing.

Roadbed construction typically employs layered and staged filling, characterized by a periodic feature of ‘layered filling—filling interval’. The load and settlement histories established during staged construction offer crucial insights into long-term deformation under filling loads. However, models often rely solely on post-construction settlement data, neglecting the rich filling data. To accurately predict composite foundation ground (CFG) settlement, an LSTM–Transformer deep learning model is used. Five factors from the ‘fill height–time–foundation settlement’ curve are extracted as input variables. The first-layer LSTM model’s gate units capture long-term dependencies, while the second-layer Transformer model’s self-attention mechanism focuses on key features, efficiently and accurately predicting ground settlement. The model is trained and analyzed based on the newly constructed Changsha–Zhuzhou–Xiangtan intercity railway section CSLLXZQ-1, which has a CFG pile composite foundation. The research shows that the proposed LSTM–Transformer model for the settlement prediction of composite foundations has an average absolute error, mean absolute percentage error, and root mean square error of 0.224, 0.563%, and 0.274, respectively. Compared to SVM, LSTM, and Transformer neural network models, it demonstrates higher prediction accuracy, indicating better reliability and practicality. This can provide a new approach and method for the settlement prediction of newly constructed CFG composite foundations.

Abstract B20-type MnSi is the prototype magnetic skyrmion material. Thin films of MnSi show a higher Curie temperature than their bulk counterpart. However, it is not yet clear what mechanism leads to the increase of the Curie temperature. In this work, we grow MnSi films on Si(100) and Si(111) substrates with a broad variation in their structures. By controlling the Mn thickness and annealing parameters, the pure MnSi phase of polycrystalline and textured nature as well as the mixed phase of MnSi and MnSi1.7 are obtained. Surprisingly, all these MnSi films show an increased Curie temperature of up to around 43 K. The Curie temperature is likely independent of the structural parameters within our accessibility including the film thickness above a threshold, strain, cell volume and the mixture with MnSi1.7. However, a pronounced phonon softening is observed for all samples, which can tentatively be attributed to slight Mn excess from stoichiometry, leading to the increased Curie temperature.

Genetic basis of the drought tolerance of upland rice is unclear. Here, the authors report the cloning of a COBRA-like protein encoding gene DROT1 and reveal that it is repressed by ERF3 and activated by ERF71 to help control the balance between growth and drought tolerance in upland rice.

Unmanned aerial vehicle (UAV) remote sensing technology is vigorously driving the development of digital cities. For experimental objects such as large, protruding, and structurally complex steel truss railway bridge structures, commonly used oblique photography and cross-circular photography techniques can lead to blurring, missing, or lower accuracy of fine texture in the models. Therefore, this paper proposes a real-scene three-dimensional modeling method that combines oblique photography with inclined photography and compares it with oblique photography and cross-circular photography techniques. Experimental results demonstrate that the model generated by combining oblique photography with inclined photography exhibits clearer textures, more complete lines, and higher accuracy, meeting the accuracy requirements of 1:500 topographic map control points. This method plays a beneficial auxiliary role in the inspection of ailments such as steel structure coating corrosion and high-strength bolt loss in steel truss railway arch bridges.

To address the incomplete image data collection of close-to-ground structures, such as bridge piers and local features like the suspension cables in bridges, obtained from single unmanned aerial vehicle (UAV) oblique photography and the difficulty in acquiring point cloud data for the top structures of bridges using single terrestrial laser scanners (TLSs), as well as the lack of textural information in TLS point clouds, this study aims to establish a high-precision, complete, and realistic bridge model by integrating UAV image data and TLS point cloud data. Using a particular large-scale dual-track bridge as a case study, the methodology involves aerial surveys using a DJI Phantom 4 RTK for comprehensive image capture. We obtain 564 images circling the bridge arches, 508 images for orthorectification, and 491 images of close-range side views. Subsequently, all images, POS data, and ground control point information are imported into Context Capture 2023 software for aerial triangulation and multi-view image dense matching to generate dense point clouds of the bridge. Additionally, ground LiDAR scanning, involving the placement of six scanning stations both on and beneath the bridge, was conducted and the point cloud data from each station are registered in Trimble Business Center 5.5.2 software based on identical feature points. Noise point clouds are then removed using statistical filtering techniques. The integration of UAV image point clouds with TLS point clouds is achieved using the iterative closest point (ICP) algorithm, followed by the creation of a TIN model and texture mapping using Context Capture 2023 software. The effectiveness of the integrated modeling is verified by comparing the geometric accuracy and completeness of the images with those obtained from a single UAV image-based model. The integrated model is used to generate cross-sectional profiles of the dual-track bridge, with detailed annotations of boundary dimensions. Structural inspections reveal honeycomb surfaces and seepage in the bridge piers, as well as painted rust and cracks in the arch ribs. The geometric accuracy of the integrated model in the X, Y, and Z directions is 1.2 cm, 0.8 cm, and 0.9 cm, respectively, while the overall 3D model accuracy is 1.70 cm. This method provides technical reference for the reconstruction of three-dimensional point cloud bridge models. Through 3D reconstruction, railway operators can better monitor and assess the condition of bridge structures, promptly identifying potential defects and damages, thus enabling the adoption of necessary maintenance and repair measures to ensure the structural safety of the bridges.

In this study, an Angelica keiskei (A. keiskei) Jiaosu (FAK) was prepared by yeast fermentation to investigate its anti-obesity effect on high-fat diet (HFD)-fed mice. 70 SPF grade male C57BL/6J mice were randomly divided into 7 groups (n = 10): blank control group (N), high-fat model group (M), positive control group (Orl), unfermented control group (NF), high-dose intervention group (FH), medium-dose intervention group (FM), and low-dose intervention group (FL). The results showed that FAK intervention significantly reduced the body weight, Lee’s index and liver index of HFD-fed mice (P < 0.05). Compared with M group, the serum levels of triglyceride (TG), total cholesterol (TC), leptin and glucose (GLU) in FH group were remarkably decreased and that of interleukin-27 (IL-27) were increased (P < 0.05). The levels of TG, and TC in the liver of mice were also markedly decreased in the FH group (P < 0.05). HE staining results showed that the liver cells in the three intervention groups had less degeneration and fatty vacuoles in the cytoplasm, and the liver cords were orderly arranged compared with that of M group. Furthermore, FAK significantly inhibited epididymal adipose tissue cell expansion induced by HFD. FAK up-regulated the protein expression levels of p-AMPK and PPARα to promote lipolysis and down-regulated the expression of PPARγ to reduce lipid synthesis (P < 0.05). Additionally, the results of gut microbiota showed that after the intervention, a decrease trend of F/B value and Deferribacterota was noticed in the FH group compared with M group. At the genus level, FAK intervention significantly increased that of Ileiobacterium compared to the M group (p < 0.05). A rising trend of norank_f_Muribaculaceae, Lactobacillus, and Bifidobacterium were also observed in the HF group. Conclusively, these findings demonstrated that FAK intervention can effectively improve obesity in mice caused by HFD and the potential mechanisms was related to the regulation of serum levels of leptin and IL-27, lipogenesis and lipolysis in adipose tissue and gut microbiota composition.

The grain number per panicle (GNP) is an important yield component. Identifying naturally favorable variations in GNP will benefit high-yield rice breeding. Here, we performed a genome-wide association study using a mini-core collection of 266 cultivated rice accessions with deep sequencing data and investigated the phenotype for three years. Three genes, i.e., TOTOU1 (TUT1), Grain height date 7 (Ghd7), and Days to heading 7/Grain height date 7.1/Pseudo-Response Regulator37 (DTH7/Ghd7.1/OsPRR37), which regulate GNP, were found in the quantitative trait loci (QTL) identified in this study. A stable QTL, qGNP1.3, which showed a strong correlation with variations in GNP, was repeatedly detected. After functional and transgenic phenotype analysis, we identified a novel gene, regulator of grain number 1a (RGN1a), which codes for protein kinase, controlling GNP in rice. The RGN1a mutation caused 37.2%, 27.8%, 51.2%, and 25.5% decreases in grain number, primary branch number per panicle, secondary branch number per panicle, and panicle length, respectively. Furthermore, breeding utilization analysis revealed that the additive effects of the dominant allelic variants of RGN1a and DTH7 played a significant role in increasing the grain number per panicle in japonica rice. Our findings enrich the gene pool and provide an effective strategy for the genetic improvement of grain numbers.

BackgroundObservational studies suggest that ulceration is considered to be a negative prognostic factor for cutaneous melanoma. However, the impact of ulceration over different subgroups (e.g. AJCC Stage, thickness level) are controversial and its true causal effect on survival is lack of studies in the view of treating ulceration as an exposure.ObjectiveTo explore the true causal effect of ulceration on melanoma’s survival by adopting a combination of methods to discover proper adjustment set and confirming its correctness through a variety of means.MethodsA minimal sufficient adjustment set (MSAS) was found using directed acyclic graphs (DAG) to adjust the effect of causality. Sensitivity analysis was conducted to diagnose potential confounders in addition to MSAS. Cox models were built to analyze the causality in-depth and the model was validated using a novel method. Lastly, stratified effects of ulceration were examined to illustrate its impact within subgroups.ResultsHazard ratio (HR) of ulceration after adjustment by MSAS variables was 1.99 (95% CI=1.88-2.09). The sensitivity analysis of propensity score matching and E-value both demonstrated that variables other than MSAS do not have great influence on ulceration and MSS relationship. The HR of ulceration in AJCC Stage, thickness level, invasion level and tumor extension were all monotonically decreased from 5.76 to 1.57, 4.03 to 1.78, 2.75 to 1.78 and 2.65 to 1.71 respectively.ConclusionUlceration in all subgroups were shown to have a significantly negative impact on MSS and its magnitude of effect was monotonically decreased as the disease progressed. The true effect of ulceration can be adjusted by MSAS and its correctness was validated through a variety of approaches.

Abstract Genetic basis and network studies underlying synergistic biomass accumulation of roots and shoots (SBA) are conducive for rational design of high-biomass rice breeding. In this study, association signals for root weight, shoot weight, and the ratio of root-to-shoot mass (R/S) were identified using 666 rice accessions by genome-wide association study, together with their sub-traits, root length, root thickness and shoot length. Most association signals for root weight and shoot weight did not show association with their sub-traits. Based on the results, we proposed a top-to-bottom model for SBA, i.e. root weight, shoot weight and R/S were determined by their highest priority in contributing to biomass in the regulatory pathway, followed by a lower priority pathway for their sub-traits. Owing to 37 enriched clusters with more than two association signals identified, the relationship among the six traits could be also involved in linkage and pleiotropy. Furthermore, a discrimination of pleiotropy and LD at sequencing level using the known gene OsPTR9 for root weight, R/S and root length was provided. The results of given moderate correlation between traits and their corresponding sub-traits, and moderate additive effects between a trait and the accumulation of excellent alleles corresponding to its sub-traits supported a bottom-to-top regulation model for SBA. This model depicted each lowest-order trait (root length, root thickness and shoot length) was determined by its own regulation loci, and competition among different traits, as well as the pleiotropy and LD. All above ensure the coordinated development of each trait and the accumulation of the total biomass, although the predominant genetic basis of SBA is still indistinguishable. The presentation of the above two models and evidence of this study shed light on dissecting the genetic architecture of SBA.

Lodging is one of the major abiotic stresses, affecting the total crop yield and quality. The improved lodging resistance and its component traits potentially reduce the yield losses. The section modulus (SM), bending moment at breaking (M), pushing resistance (PR), and coefficient of lodging resistance (cLr) are the key elements to estimate the lodging resistance. Understanding the genetic architecture of lodging resistance–related traits will help to improve the culm strength and overall yield potential. In this study, a natural population of 795 globally diverse genotypes was further divided into two (indica and japonica) subpopulations and was used to evaluate the lodging resistance and culm strength–related traits. Significant diversity was observed among the studied traits. We carried out the genome-wide association evaluation of four lodging resistance traits with 3.3 million deep resolution single-nucleotide polymorphic (SNP) markers. The general linear model (GLM) and compressed mixed linear model (MLM) were used for the whole population and two subpopulation genome-wide association studies (GWAS), and a 1000-time permutation test was performed to remove the false positives. A total of 375 nonredundant QTLs were observed for four culm strength traits on 12 chromosomes of the rice genome. Then, 33 pleiotropic loci governing more than one trait were mined. A total of 4031 annotated genes were detected within the candidate genomic region of 33 pleiotropic loci. The functional annotations and metabolic pathway enrichment analysis showed cellular localization and transmembrane transport as the top gene ontological terms. The in silico and in vitro expression analyses were conducted to validate the three candidate genes in a pleiotropic QTL on chromosome 7. It validated OsFBA2 as a candidate gene to contribute to lodging resistance in rice. The haplotype analysis for the candidate gene revealed a significant functional variation in the promoter region. Validation and introgression of alleles that are beneficial to induce culm strength may be used in rice breeding for lodging resistance.

Background: Necroptosis has been identified recently as a newly recognized programmed cell death that has an impact on tumor progression and prognosis, although the necroptosis-related gene (NRGs) potential prognostic value in skin cutaneous melanoma (SKCM) has not been identified. The aim of this study was to construct a prognostic model of SKCM through NRGs in order to help SKCM patients obtain precise clinical treatment strategies.Methods: RNA sequencing data collected from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed and prognostic NRGs in SKCM. Depending on 10 NRGs via the univariate Cox regression analysis usage and LASSO algorithm, the prognostic risk model had been built. It was further validated by the Gene Expression Omnibus (GEO) database. The prognostic model performance had been assessed using receiver operating characteristic (ROC) curves. We evaluated the predictive power of the prognostic model for tumor microenvironment (TME) and immunotherapy response.Results: We constructed a prognostic model based on 10 NRGs (FASLG, TLR3, ZBP1, TNFRSF1B, USP22, PLK1, GATA3, EGFR, TARDBP, and TNFRSF21) and classified patients into two high- and low-risk groups based on risk scores. The risk score was considered a predictive factor in the two risk groups regarding the Cox regression analysis. A predictive nomogram had been built for providing a more beneficial prognostic indicator for the clinic. Functional enrichment analysis showed significant enrichment of immune-related signaling pathways, a higher degree of immune cell infiltration in the low-risk group than in the high-risk group, a negative correlation between risk scores and most immune checkpoint inhibitors (ICIs), anticancer immunity steps, and a more sensitive response to immunotherapy in the low-risk group.Conclusions: This risk score signature could be applied to assess the prognosis and classify low- and high-risk SKCM patients and help make the immunotherapeutic strategy decision.

Rice panicle architecture affects grain number per panicle and thereby grain yield. Many genes involved in control of panicle architecture have been identified in the past decades. According to their effect on phenotype, these genes are divided into three categories: panicle branch and lateral spikelets, multifloret spikelets, and panicle type. We review these genes, describe their genetic regulatory network, and propose a strategy for using them in rice breeding. These findings on rice panicle architecture may facilitate related studies in other crops.

The yield of rice is mostly affected by three factors, namely, panicle number, grain number and grain weight. Variation in panicle and grain numbers is mainly caused by tiller and panicle branches generated from axillary meristems (AMs). MOC1 encodes a putative GRAS family nuclear protein that regulates AM formation. Although several alleles of MOC1 have been identified, its variation in germplasm resources remains unclear. In the present study we characterized a novel moc1 allele named gnp6 which has a thymine insertion in the coding sequence of the SAW motif in the GRAS domain. This mutation causes arrested branch formation. The SAW motif is necessary for nuclear localization of GNP6/MOC1 where it functions as a transcription factor or co-regulator. Haplotype analysis showed that the coding region of GNP6/MOC1 was conserved without any non-synonymous mutations in 240 rice accessions. However, variation in the promoter region might affect the expression of it and its downstream genes. Joint haplotype analysis of GNP6/MOC1 and MOC3 showed that haplotype combinations H9, H10 and H11, namely MOC1-Hap1 in combination with MOC3-Hap3, MOC3-Hap4 or MOC3-Hap5 could be bred to promote branch formation. These findings will enrich the genetic resources available for rice breeders.

Abstract Background Plant senescence is a complicated process involving multiple regulations, such as temperature, light, reactive oxygen species (ROS), endogenous hormone levels, and diseases. Although many such genes have been characterized to understand the process of leaf senescence, there still remain many unknowns, and many more genes need to be characterized. Results We identified a rice mutant nbl1 with a premature leaf senescence phenotype. The causative gene, OsNBL1, encodes a small protein with 94 amino acids, which is conserved in monocot, as well as dicot plants. Disruption of OsNBL1 resulted in accelerated dark-induced leaf senescence, accompanied by a reduction in chlorophyll content and up-regulation of several senescence-associated genes. Notably, the nbl1 mutant was more susceptible to rice blast and bacterial blight but more tolerant to sodium chloride. Several salt-induced genes, including HAK1, HAK5, and three SNAC genes, were also up-regulated in the nbl1 mutant. Additionally, the nbl1 mutant was more sensitive to salicylic acid. Plants overexpressing OsNBL1 showed delayed dark-induced senescence, consistent with a higher chlorophyll content compared to wild-type plants. However, the overexpression plants were indistinguishable from the wild-types for resistance to the rice blast disease. OsNBL1 is a multi-organelle localized protein and interacts with OsClpP6, which is associated with senescence. Conclusions We described a novel leaf senescence mutant nbl1 in rice. It is showed that OsNBL1, a multi-organelle localized protein which interacts with a plastidic caseinolytic protease OsClpP6, is essential for controlling leaf senescence, disease resistance, and salt tolerance.