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In crops, nitrogen directly determines productivity and biomass. However, the improvement of nitrogen utilization efficiency (NUE) is still a major challenge in modern agriculture. Here, we report the characterization of are1 , a genetic suppressor of a rice fd-gogat mutant defective in nitrogen assimilation. ARE1 is a highly conserved gene, encoding a chloroplast-localized protein. Loss-of-function mutations in ARE1 cause delayed senescence and result in 10–20% grain yield increases, hence enhance NUE under nitrogen-limiting conditions. Analysis of a panel of 2155 rice varieties reveals that 18% indica and 48% aus accessions carry small insertions in the ARE1 promoter, which result in a reduction in ARE1 expression and an increase in grain yield under nitrogen-limiting conditions. We propose that ARE1 is a key mediator of NUE and represents a promising target for breeding high-yield cultivars under nitrogen-limiting condition. Understanding the regulatory mechanisms of nitrogen assimilation is crucial for developing crop cultivars with improved nitrogen utilization efficiency (NUE). Here the authors identify a new negative regulator of NUE and mutation of this gene increases 10–20% rice grain yield under nitrogen-limiting field conditions.

Reasonably configuring the concentration distribution of the mixture to achieve partially premixed combustion has been proven to be an effective method for improving energy utilization efficiency. However, due to the significant influence of concentration non-uniformity and flow field disturbances, the combustion behavior and mechanisms of partially premixed combustion have not been fully understood or systematically analyzed. In this study, the partially premixed combustion characteristics of methane–hydrogen–air mixtures in a confined space were investigated, focusing on the combustion behavior and key parameter variation patterns under different equivalence ratios (0.5, 0.7, 0.9) and hydrogen contents (10%, 20%, 30%, 40%). The global equivalence ratio and degree of partial premixing of the mixture were controlled by adjusting the fuel injection pulse width and ignition timing, thereby regulating the concentration field and flow field distribution within the combustion chamber. The constant-pressure method was used to calculate the burning velocity. Results show that as the mixture formation time decreases, the degree of partial premixing increases, accelerating the heat release process, increasing burning velocity, and shortening the combustion duration. It exhibits rapid combustion characteristics, particularly during the initial combustion phase, where flame propagation speed and heat release rate increase significantly. The burning velocity demonstrates a distinct single-peak profile, with the peak burning velocity increasing and its occurrence advancing as the degree of partial premixing increases. Additionally, hydrogen’s preferential diffusion effect is enhanced with increasing mixture partial premixing, making the combustion process more efficient and concentrated. This effect is particularly pronounced under low-equivalence-ratio (lean burn) conditions, where the combustion reaction rate improves more significantly, leading to greater combustion stability. The peak of the partially premixed burning velocity occurs almost simultaneously with the peak of the second-order derivative of the combustion pressure. This phenomenon highlights the strong correlation between the combustion reaction rate and the dynamic variations in pressure.

LESION SIMULATING DISEASE1 (LSD1) is an important negative regulator of programmed cell death (PCD) in Arabidopsis (Arabidopsis thaliana). The loss-of-function mutations in LSD1 cause runaway cell death triggered by reactive oxygen species. LSD1 encodes a novel zinc finger protein with unknown biochemical activities. Here, we report the identification of CATALASE3 (CAT3) as an LSD1-interacting protein by affinity purification and mass spectrometry-based proteomic analysis. The Arabidopsis genome contains three homologous catalase genes (CAT1, CAT2, and CAT3). Yeast two-hybrid and coimmunoprecipitation analyses demonstrated that LSD1 interacted with all three catalases both in vitro and in vivo, and the interaction required the zinc fingers of LSD1. We found that the catalase enzymatic activity was reduced in the lsd1 mutant, indicating that the catalase enzyme activity was partially dependent on LSD1. Consistently, the lsd1 mutant was more sensitive to the catalase inhibitor 3-amino-1,2,4-triazole than the wild type, suggesting that the interaction between LSD1 and catalases is involved in the regulation of the reactive oxygen species generated in the peroxisome. Genetic studies revealed that LSD1 interacted with CATALASE genes to regulate light-dependent runaway cell death and hypersensitive-type cell death. Moreover, the accumulation of salicylic acid was required for PCD regulated by the interaction between LSD1 and catalases. These results suggest that the LSD1-catalase interaction plays an important role in regulating PCD in Arabidopsis.

The security of car driving is of interest due to the growing number of motor vehicles and frequent occurrence of road traffic accidents, and the combination of advanced driving assistance system (ADAS) and vehicle-road cooperation can prevent more than 90% of traffic accidents. Lane detection, as a vital part of ADAS, has poor real-time performance and accuracy in multiple scenarios, such as road damage, light changes, and traffic jams. Moreover, the sparse pixels of lane lines on the road pose a tremendous challenge to the task of lane line detection. In this study, we propose a model that fuses non bottleneck skip residual connections and an improved attention pyramid (IAP) to effectively obtain contextual information about real-time scenes and improve the robustness and real-time performance of current lane detection models. The proposed model modifies the efficient residual factorized pyramid scene parsing network (ERF-PSPNet) and utilizes skip residual connections in non bottleneck-1D modules. A decoder with an IAP provides high-level feature maps with pixel-level attention. We add an auxiliary segmenter and a lane predictor side-by-side after the encoder, the former for lane prediction and the latter to assist with semantic segmentation for classification purposes, as well as to solve the gradient disappearance problem. On the CULane dataset, the F1 metric reaches 92.20% in the normal scenario, and the F1 metric of the model is higher than the F1 metrics of other existing models, such as ERFNet-HESA, ENet_LGAD, and DSB+LDCDI, in normal, crowded, night, dazzling light and no line scenarios; in addition, the mean F1 of the nine scenarios reached 74.10%, the runtime (time taken to test 100 images) of the model was 5.88 ms, and the number of parameters was 2.31M, which means that the model achieves a good trade-off between real-time performance and accuracy compared to the current best results (i.e., a running time of 13.4 ms and 0.98M parameters).

Cortical gamma band oscillations (GBO, 30–80 Hz, typically ∼40 Hz) are involved in higher cognitive functions such as feature binding, attention, and working memory. GBO abnormalities are a feature of several neuropsychiatric disorders associated with dysfunction of cortical fast-spiking interneurons containing the calcium-binding protein parvalbumin (PV). GBO vary according to the state of arousal, are modulated by attention, and are correlated with conscious awareness. However, the subcortical cell types underlying the state-dependent control of GBO are not well understood. Here we tested the role of one cell type in the wakefulness-promoting basal forebrain (BF) region, cortically projecting GABAergic neurons containing PV, whose virally transduced fibers we found apposed cortical PV interneurons involved in generating GBO. Optogenetic stimulation of BF PV neurons in mice preferentially increased cortical GBO power by entraining a cortical oscillator with a resonant frequency of ∼40 Hz, as revealed by analysis of both rhythmic and nonrhythmic BF PV stimulation. Selective saporin lesions of BF cholinergic neurons did not alter the enhancement of cortical GBO power induced by BF PV stimulation. Importantly, bilateral optogenetic inhibition of BF PV neurons decreased the power of the 40-Hz auditory steady-state response, a read-out of the ability of the cortex to generate GBO used in clinical studies. Our results are surprising and novel in indicating that this presumptively inhibitory BF PV input controls cortical GBO, likely by synchronizing the activity of cortical PV interneurons. BF PV neurons may represent a previously unidentified therapeutic target to treat disorders involving abnormal GBO, such as schizophrenia.

Interleukin 15 (IL-15) is one of the most important cytokines that regulate the biology of natural killer (NK) cells 1 . Here we identified a signaling pathway—involving the serine-threonine kinase AKT and the transcription factor XBP1s, which regulates unfolded protein response genes 2 , 3 —that was activated in response to IL-15 in human NK cells. IL-15 induced the phosphorylation of AKT, which led to the deubiquitination, increased stability and nuclear accumulation of XBP1s protein. XBP1s bound to and recruited the transcription factor T-BET to the gene encoding granzyme B, leading to increased transcription. XBP1s positively regulated the cytolytic activity of NK cells against leukemia cells and was also required for IL-15-mediated NK cell survival through an anti-apoptotic mechanism. Thus, the newly identified IL-15–AKT–XBP1s signaling pathway contributes to enhanced effector functions and survival of human NK cells. Yu and colleagues show that the transcription factor XBP1s positively regulates the cytolytic activity of human NK cells and is required for the IL-15-mediated survival of NK cells.

The present study concerns the re-scour of a submarine pipeline after its scour-sagging-burial by modeling a tilting pipeline with varying embedment along the pipeline axis. The effect of the tilting angle on characteristics of three-dimensional scour was investigated, in terms of the scour topographies, the scour depth, as well as the scour propagation along the pipeline. Two previously undetected scour topographies, i.e., sand ripples that extend along the pipeline axis in the downstream direction of the pipeline and scour pits below the pipeline perpendicular to the pipeline axis, were found to significantly affect the development of the scour propagation and the scour depth. The whole scour propagation along the pipeline can be divided into the rapid scouring phase and the slow scouring phase. The transition point between the two phases takes place at the initial embedment-to-diameter ratio of 0.3. With the increase of the incident angle from 0° to 45°, the scour propagation rate increases during the rapid scouring phase but decreases during the slow scouring phase. A predictive model of the scour propagation rate was established based on the erosion characteristics of sediment and the shear stress magnification factor under the pipeline. The newly predictive model of scour propagation rate is found to provide satisfactory results for a tilting submarine pipeline under different flow incident angles.

With the rapid development of the Internet and the increasing popularity of mobile devices, the availability of digital image resources is increasing exponentially. How to rapidly and effectively retrieve and organize image information has been a hot issue that urgently must be solved. In the field of image retrieval, image auto-annotation remains a basic and challenging task. Targeting the drawbacks of the low accuracy rate and high memory resource consumption of current multilabel annotation methods, this study proposed a CM-supplement network model. This model combines the merits of cavity convolutions, Inception modules and a supplement network. The replacement of common convolutions with cavity convolutions enlarged the receptive field without increasing the number of parameters. The incorporation of Inception modules enables the model to extract image features at different scales with less memory consumption than before. The adoption of the supplement network enables the model to obtain the negative features of images. After 100 training iterations on the PASCAL VOC 2012 dataset, the proposed model achieved an overall annotation accuracy rate of 94.5%, which increased by 10.0 and 1.1 percentage points compared with the traditional convolution neural network (CNN) and double-channel CNN (DCCNN). After stabilization, this model achieved an accuracy of up to 96.4%. Moreover, the number of parameters in the DCCNN was more than 1.5 times that of the CM-supplement network. Without increasing the amount of memory resources consumed, the proposed CM-supplement network can achieve comparable or even better annotation effects than a DCCNN.

The prefabricated recyclable supporting structure (PRSS) is an innovative support system that integrates a steel skeleton with polymer waterproof technology. Earth berms are extensively adopted to support the PRSS, but there is limited understanding on the factors influencing their behavior in circular excavations. In this paper, a numerical model is first validated with a case history in Henan, China. Afterwards, the geometric parameters of the earth berms, including the height (H), the top width (B1), and the bottom width (B2), on the behavior of the PRSS, are investigated. It is shown that, by increasing the height, top width and bottom width of earth berms, the lateral deflections, and bending moments of supporting piles, as well as the ground surface settlements, tend to decrease. However, the reduction effect of these parameters diminishes as well. Moreover, the raised effective formation level considering the effect of the earth berms on stability and deformation analyses is discussed. The factor of the safety of the excavation is almost doubled when axisymmetric conditions are considered compared to plane strain conditions. In deformation analysis, the raised effective formation level increases with the height of the earth berms until a steady value is reached.

In the context of a rapidly expanding global population, mulberry leaf protein emerges as an emerging source of plant protein, with most applications currently at Technology Readiness Level (TRL), presenting substantial potential for application in functional foods and nutraceuticals. This paper analyzes three key advantages of mulberry leaf protein. Firstly, the abundant and inexpensive production of mulberry leaves establishes a solid foundation for large-scale protein extraction. Secondly, advancements in the preparation processes and production technology for mulberry leaf protein have further enhanced its viability. Thirdly, mulberry leaf protein boasts excellent nutritional value and outstanding functional properties, along with multiple biological activities, including antioxidant effects, aging delay, and blood-pressure-lowering activity. These superior qualities considerably broaden its range of applications. Furthermore, this paper evaluates existing research (before 30 June 2025) while exploring prospective avenues for future investigation. The findings of this review are important for enhancing the understanding of the potential applications of mulberry leaf protein in food science and nutrition. The aim is to provide new ideas for the efficient utilization of mulberry leaf protein resources and the establishment of a global food security system.