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Significance Drought stress induces the accumulation of the plant stress hormone abscisic acid (ABA). ABA then quickly activates the protein kinase OST1/SnRK2.6 to phosphorylate a number of proteins in guard cells, resulting in stomatal closure to reduce transpirational water loss. How SnRK2.6 is deactivated and how ABA signaling may be desensitized are unclear. This study found that nitric oxide (NO) resulting from ABA signaling causes S-nitrosylation of SnRK2.6 at a cysteine residue close to the kinase catalytic site, which blocks the kinase activity. Dysfunction of S-nitrosoglutathione (GSNO) reductase causes GSNO overaccumulation in guard cells and ABA insensitivity in stomatal regulation. This work thus reveals how ABA-induced NO functions in guard cells to inactivate SnRK2.6 to negatively feedback regulate ABA signaling. The phytohormone abscisic acid (ABA) plays important roles in plant development and adaptation to environmental stress. ABA induces the production of nitric oxide (NO) in guard cells, but how NO regulates ABA signaling is not understood. Here, we show that NO negatively regulates ABA signaling in guard cells by inhibiting open stomata 1 (OST1)/sucrose nonfermenting 1 (SNF1)-related protein kinase 2.6 (SnRK2.6) through S-nitrosylation. We found that SnRK2.6 is S-nitrosylated at cysteine 137, a residue adjacent to the kinase catalytic site. Dysfunction in the S-nitrosoglutathione (GSNO) reductase (GSNOR) gene in the gsnor1-3 mutant causes NO overaccumulation in guard cells, constitutive S-nitrosylation of SnRK2.6, and impairment of ABA-induced stomatal closure. Introduction of the Cys137 to Ser mutated SnRK2.6 into the gsnor1-3/ost1-3 double-mutant partially suppressed the effect of gsnor1-3 on ABA-induced stomatal closure. A cysteine residue corresponding to Cys137 of SnRK2.6 is present in several yeast and human protein kinases and can be S-nitrosylated, suggesting that the S-nitrosylation may be an evolutionarily conserved mechanism for protein kinase regulation.

Background and aims As drought threatens the yield and quality of maize ( Zea mays L.), it is important to dissect the molecular basis of maize drought tolerance. Flavonoids, participate in the scavenging of oxygen free radicals and alleviate stress-induced oxidative damages. This study aims to dissect the function of flavonoids in the improvement of maize drought tolerance. Methods Using far-infrared imaging screening, we previously isolated a drought overly insensitivity ( doi ) mutant from an ethyl methanesulfonate (EMS)-mutagenized maize library and designated it as doi57 . In this study, we performed a physiological characterization and transcriptome profiling of doi57 in comparison to corresponding wild-type B73 under drought stress. Results Under drought stress, doi57 seedlings displayed lower leaf-surface temperature (LST), faster water loss, and better performance in growth than B73. Transcriptome analysis reveals that key genes involved in flavonoid biosynthesis are enriched among differentially expressed genes in doi57 . In line with these results, more flavonols and less hydrogen peroxide (H 2 O 2 ) were accumulated in guard cells of doi57 than in those of B73 with the decrease of soil water content (SWC). Moreover, the capacity determined from doi57 seedling extracts to scavenge oxygen free radicals was more effective than that of B73 under the drought treatment. Additionally, doi57 seedlings had higher photosynthetic rates, stomatal conductance, transpiration rates, and water use efficiency than B73 exposed to drought stress, resulting in high biomass and greater root/shoot ratios in doi57 mutant plants. Conclusion Flavonoids may facilitate maize seedling drought tolerance by lowering drought-induced oxidative damage as well regulating stomatal movement.

Background Insulin resistance and visceral adiposity are established pathophysiological drivers of cardiovascular disease (CVD). The triglyceride‒glucose (TyG) index and the Chinese visceral adiposity index (CVAI) are respective indicators of these conditions. However, the association of their combination, the TyG-CVAI, with the risk of new-onset CVD in the general population remains unclear. This study aimed to investigate this relationship using data from a large national cohort. Methods This prospective study included participants in the China Health and Retirement Longitudinal Study (CHARLS) who lacked CVD at baseline. The TyG-CVAI was calculated and used to categorize participants into quartiles. The primary endpoint was the incidence of new-onset CVD. Kaplan‒Meier analysis was performed to assess the cumulative incidence, while multivariable Cox proportional hazards models were used to estimate risk ratios (HRs) and 95% confidence intervals (CIs). The nonlinearity of the relationship was examined using restricted cubic splines (RCSs), and the predictive performance of the TyG-CVAI was evaluated and compared to that of its components using receiver operating characteristic (ROC) curve analysis. Results Among the 7977 participants, 1221 ultimately developed a CVD. Kaplan‒Meier analysis showed a significantly higher cumulative incidence of CVD with increasing TyG-CVAI quartiles (log-rank P  < 0.001). After full adjustment for demographic, lifestyle, and cardiometabolic risk factors, participants in the highest quartile (Q4) had a significantly higher CVD risk (HR = 1.64, 95% CI 1.35–2.00) than those in the lowest quartile (Q1). RCS analysis revealed a significant nonlinear association between the TyG-CVAI and CVD risk, with a threshold at 778.62; below this point, no significant association was observed, whereas above it, each unit increase in the index conferred a 47% higher CVD risk (HR 1.47, 95% CI 1.31–1.64;  P  < 0.001). Furthermore, the TyG-CVAI (AUC = 0.6315) outperformed the TyG index (AUC = 0.5938) and the CVAI (AUC = 0.5851) alone in predicting the risk of CVD. Conclusions In this national cohort of middle-aged and older Chinese adults, a higher TyG-CVAI was independently and nonlinearly associated with an increased risk of new-onset CVD, demonstrating superior predictive value over its individual components. The TyG-CVAI may serve as a simple and effective integrated tool for the early identification of high-risk individuals for primary CVD prevention. Graphical abstract

The function of miR165/166 in plant growth and development has been extensively studied, however, its roles in abiotic stress responses remain largely unknown. Here, we report that reduction in the expression of miR165/166 conferred a drought and cold resistance phenotype and hypersensitivity to ABA during seed germination and post-germination seedling development. We further show that the ABA hypersensitive phenotype is associated with a changed transcript abundance of ABA-responsive genes and a higher expression level of ABI4, which can be directly regulated by a miR165/166 target. Additionally, we found that reduction in miR165/166 expression leads to elevated ABA levels, which occurs at least partially through the increased expression of BG1, a gene that is directly regulated by a miR165/166 target. Taken together, our results uncover a novel role for miR165/166 in the regulation of ABA and abiotic stress responses and control of ABA homeostasis.

The high mutability of human immunodeficiency virus type 1 (HIV-1) and the widespread use of antiretroviral drugs have rendered genetic diversity and pre-treatment drug resistance (PDR) significant obstacles to the success of antiretroviral therapy (ART). However, the research on the epidemiological and spatial distribution characteristics of PDR in Ningxia is still insufficient. A cross-sectional study utilized pre-treatment blood samples collected between 2020 and 2021 from the biorepository in May 2024. Partial pol gene sequences were obtained through plasma collection and RNA extraction. Drug resistance analysis was performed using the Stanford University HIVdb algorithm. Molecular network were constructed using Cytoscape 3.10.0. Spatial analysis and visualization were further conducted using ArcGIS10.8.1. 95 sequences were obtained, among which 7 HIV-1 genotypes were detected and CRF07_BC (67.37%, 64/95) was the predominant one. Drug resistance mutations (DRMs) were detected in 13.68%(13/95) of the sequences. The risk of PDR occurrence was higher among individuals with CRF07_BC strain types. The 24 sequences of CRF07_BC, CRF01_AE, and URF subtypes grouped into nine transmission clusters in the molecular network, with CRF07_BC showing the highest integration and clustering rates. HIV-1 infections resistant to PDR were observed in all five cities in NHAR, accompanied by cross-city transmission. Additionally, seven imported sequences were detected, comprising CRF07_BC, CRF01_AE, and C subtypes, along with three sequences of CRF55_01B with high similarity to nonlocal sequences. From 2020 to 2021, the HIV-1 diversity increased significantly in NHAR, with the prevalence of PDR reaching moderate levels and evidence of resistance transmission. The districts and counties under the jurisdiction of Yinchuan City emerged as hotspots for both pre-treatment HIV/AIDS patients and the distribution of resistant strains. It is imperative to enhance PDR testing and implement targeted interventions in key areas to minimize the emergence and dissemination of resistant virus variants.

Background As global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for cancer treatment. Objective This study aims to systematically analyze the current applications, research trends, and challenges of digital twin technology in tumor therapy, while exploring future directions. Methods Relevant literature up to 2024 was retrieved from PubMed, Web of Science, and other databases. Data visualization was performed using R and VOSviewer software. The analysis includes the research initiation and trends, funding models, global research distribution, sample size analysis, and data processing and artificial intelligence applications. Furthermore, the study investigates the specific applications and effectiveness of digital twin technology in tumor diagnosis, treatment decision-making, prognosis prediction, and personalized management. Results Since 2020, research on digital twin technology in oncology has surged, with significant contributions from the United States, Germany, Switzerland, and China. Funding primarily comes from government agencies, particularly the National Institutes of Health in the U.S. Sample size analysis reveals that large-sample studies have greater clinical reliability, while small-sample studies emphasize technology validation. In data processing and artificial intelligence applications, the integration of medical imaging, multi-omics data, and AI algorithms is key. By combining multimodal data integration with dynamic modeling, the accuracy of digital twin models has been significantly improved. However, the integration of different data types still faces challenges related to tool interoperability and limited standardization. Specific applications of digital twin technology have shown significant advantages in diagnosis, treatment decision-making, prognosis prediction, and surgical planning. Conclusion Digital twin technology holds substantial promise in tumor therapy by optimizing personalized treatment plans through integrated multimodal data and dynamic modeling. However, the study is limited by factors such as language restrictions, potential selection bias, and the relatively small number of published studies in this emerging field, which may affect the comprehensiveness and generalizability of our findings. Moreover, issues related to data heterogeneity, technical integration, and data privacy and ethics continue to impede its broader clinical application. Future research should promote international collaboration, establish unified interdisciplinary standards, and strengthen ethical regulations to accelerate the clinical translation of digital twin technology in cancer treatment.

Pseudouridine (Ψ) is widely distributed in mRNA and various non-coding RNAs in yeast and mammals, and the specificity of its distribution has been determined. However, knowledge about Ψs in the RNAs of plants, particularly in mRNA, is lacking. In this study, we performed genome-wide pseudouridine-sequencing in Arabidopsis and for the first time identified hundreds of Ψ sites in mRNA and multiple Ψ sites in non-coding RNAs. Many predicted and novel Ψ sites in rRNA and tRNA were detected. mRNA was extensively pseudouridylated, but with Ψs being under-represented in 3′-untranslated regions and enriched at position 1 of triple codons. The phenylalanine codon UUC was the most frequently pseudouridylated site. Some Ψs present in chloroplast 23S, 16S, and 4.5S rRNAs in wild-type Col-0 were absent in plants with a mutation of SVR1 (Suppressor of variegation 1), a chloroplast pseudouridine synthase gene. Many plastid ribosomal proteins and photosynthesis-related proteins were significantly reduced in svr1 relative to the wild-type, indicating the roles of SVR1 in chloroplast protein biosynthesis in Arabidopsis. Our results provide new insights into the occurrence of pseudouridine in Arabidopsis RNAs and the biological functions of SVR1, and will pave the way for further exploiting the mechanisms underlying Ψ modifications in controlling gene expression and protein biosynthesis in plants.

High-volume blended slag cements (HVBSC), with over 70% GGBS replacement, offer a promising route to reduce clinker use and utilise industrial by-products. This review examines HVBSC hydration mechanisms, reaction products (C-(A)-S-H, LDH), strength development, and durability challenges. Strategies to enhance early-age performance are discussed, alongside the need for multiphysics modelling. A conceptual framework is proposed to guide HVBSC development and scaling in suitable regional contexts.

In this paper, we study numerical algorithms based on Physics-Informed Neural Networks (PINNs) for solving a mixed Stokes/Darcy model that describes a fluid flow coupled with a porous media flow. A Hard Constrained Parallel PINN (HC-PPINN) is proposed for the mixed model, in which the boundary conditions are enforced by modified the neural network architecture. Numerical experiments with different settings are conducted to demonstrate the accuracy and efficiency of our method by comparing it with the methods based on vanilla PINNs for the mixed model.

MicroRNAs (miRNAs) regulate gene expression and play critical roles in growth and development as well as stress responses in eukaryotes. miRNA biogenesis in plants requires a processing complex that consists of the core components DICER-LIKE 1 (DCL1), SERRATE (SE) and HYPONASTIC LEAVES (HYL1). Here we show that inactivation of functionally redundant members of the SnRK2 kinases, which are the core components of abscisic acid (ABA) and osmotic stress signaling pathways, leads to reduction in miRNA accumulation under stress conditions. Further analysis revealed that the steady state level of HYL1 protein in plants under osmotic stress is dependent on the SnRK2 kinases. Additionally, our results suggest that the SnRK2 kinases physically associate with the miRNA processing components SE and HYL1 and can phosphorylate these proteins in vitro. These findings reveal an important role for the SnRK2 kinases in the regulation of miRNA accumulation and establish a mechanism by which ABA and osmotic stress signaling is linked to miRNA biogenesis.