Explore the vast range of titles available.

Higher plants adapt their growth to high temperature by a dramatic change in plant architecture. It has been shown that the transcriptional regulator phytochrome-interacting factor 4 (PIF4) and the phytohormone auxin are involved in the regulation of high temperature-induced hypocotyl elongation in Arabidopsis. Here we report that PIF4 regulates high temperature-induced hypocotyl elongation through direct activation of the auxin biosynthetic gene YUCCA8 (YUC8). We show that high temperature co-upregulates the transcript abundance of PIF4 and YUC8. PIF4-dependency of high temperature-mediated induction of YUC8 expression as well as auxin biosynthesis, together with the finding that overexpression of PIF4 leads to increased expression of YUC8 and elevated free IAA levels in planta, suggests a possibility that PIF4 directly activates YUC8 expression. Indeed, gel shift and chromatin immunoprecipitation experiments demonstrate that PIF4 associates with the G-box-containing promoter region of YUC8. Transient expression assay in Nicotiana benthamiana leaves support that PIF4 directly activates YUC8 expression in vivo. Significantly, we show that the yuc8 mutation can largely suppress the long-hypocotyl phenotype of PIF4-overexpression plants and also can reduce high temperature-induced hypocotyl elongation. Genetic analyses reveal that the shy2-2 mutation, which harbors a stabilized mutant form of the IAA3 protein and therefore is defective in high temperature-induced hypocotyl elongation, largely suppresses the long-hypocotyl phenotype of PIF4-overexpression plants. Taken together, our results illuminate a molecular framework by which the PIF4 transcriptional regulator integrates its action into the auxin pathway through activating the expression of specific auxin biosynthetic gene. These studies advance our understanding on the molecular mechanism underlying high temperature-induced adaptation in plant architecture.

Background The exceptional capabilities of artificial intelligence (AI) in extracting image information and processing complex models have led to its recognition across various medical fields. With the continuous evolution of AI technologies based on deep learning, particularly the advent of convolutional neural networks (CNNs), AI presents an expanded horizon of applications in lung cancer screening, including lung segmentation, nodule detection, false‐positive reduction, nodule classification, and prognosis. Methodology This review initially analyzes the current status of AI technologies. It then explores the applications of AI in lung cancer screening, including lung segmentation, nodule detection, and classification, and assesses the potential of AI in enhancing the sensitivity of nodule detection and reducing false‐positive rates. Finally, it addresses the challenges and future directions of AI in lung cancer screening. Results AI holds substantial prospects in lung cancer screening. It demonstrates significant potential in improving nodule detection sensitivity, reducing false‐positive rates, and classifying nodules, while also showing value in predicting nodule growth and pathological/genetic typing. Conclusions AI offers a promising supportive approach to lung cancer screening, presenting considerable potential in enhancing nodule detection sensitivity, reducing false‐positive rates, and classifying nodules. However, the universality and interpretability of AI results need further enhancement. Future research should focus on the large‐scale validation of new deep learning‐based algorithms and multi‐center studies to improve the efficacy of AI in lung cancer screening.

Tropisms, growth responses to environmental stimuli such as light or gravity, are spectacular examples of adaptive plant development. The plant hormone auxin serves as a major coordinative signal. The PIN auxin exporters, through their dynamic polar subcellular localizations, redirect auxin fluxes in response to environmental stimuli and the resulting auxin gradients across organs underlie differential cell elongation and bending. In this review, we discuss recent advances concerning regulations of PIN polarity during tropisms, focusing on PIN phosphorylation and trafficking. We also cover how environmental cues regulate PIN actions during tropisms, as well as the crucial role of auxin feedback on PIN polarity during bending termination. Finally, the interactions between different tropisms are reviewed to understand plant adaptive growth in the natural environment.

Ship detection serves as a core foundational task for marine environmental perception. However, in real marine scenarios, dense vessel traffic often causes severe target occlusion while multi-scale targets, asymmetric vessel geometries, and harsh conditions (e.g., haze, low illumination) further degrade image quality. These factors pose significant challenges to vision-based ship detection methods. To address these issues, we propose M2S-YOLOv8, an improved framework based on YOLOv8, which integrates three key enhancements: First, a Multi-Scale Asymmetry-aware Parallelized Patch-wise Attention (MSA-PPA) module is designed in the backbone to strengthen the perception of multi-scale and geometrically asymmetric vessel targets. Second, a Deformable Convolutional Upsampling (DCNUpsample) operator is introduced in the Neck network to enable adaptive feature fusion with high computational efficiency. Third, a Wasserstein-Distance-Based Weighted Normalized CIoU (WA-CIoU) loss function is developed to alleviate gradient imbalance in small-target regression, thereby improving localization stability. Experimental results on the Unmanned Vessel Zhoushan Perception Dataset (UZPD) and the open-source Singapore Maritime Dataset (SMD) demonstrate that M2S-YOLOv8 achieves a balanced performance between lightweight design and real-time inference, showcasing strong potential for reliable deployment on edge devices of unmanned marine platforms.

Recent studies have demonstrated that brain meningeal lymphatic vessels (MLVs) act as a drainage path directly into the cervical lymph nodes (CLNs) for macromolecules contained in the cerebrospinal fluid (CSF). However, the role of MLVs during CNS viral infection remains unexplored. Here, we found that infection with several neurotropic viruses in mice promotes MLV expansion but also causes impaired MLV-mediated drainage of macromolecules. Notably, MLVs could drain virus from the CNS to CLNs. Surgical ligation of the lymph vessels or photodynamic ablation of dorsal MLVs increased neurological damage and mortality of virus-infected mice. By contrast, pretreatment with vascular endothelial growth factor C promoted expansion of functional MLVs and alleviated the effects of viral infection. Together, these data indicate that functional MLVs facilitate virus clearance, and MLVs represent a critical path for virus spreading from the CNS to the CLNs. MLV-based therapeutic strategies may thus be useful for alleviating infection-induced neurological damage. This study finds that during acute viral infection of the CNS, meningeal lymphatic vessels (MLVs) can transport virus from the CNS to draining cervical lymph nodes. VEGF-C-induced expansion of functional MLVs facilitated virus clearance.

Root gravitropic bending represents a fundamental aspect of terrestrial plant physiology. Gravity is perceived by sedimentation of starch-rich plastids (statoliths) to the bottom of the central root cap cells. Following gravity perception, intercellular auxin transport is redirected downwards leading to an asymmetric auxin accumulation at the lower root side causing inhibition of cell expansion, ultimately resulting in downwards bending. How gravity-induced statoliths repositioning is translated into asymmetric auxin distribution remains unclear despite PIN auxin efflux carriers and the Negative Gravitropic Response of roots (NGR) proteins polarize along statolith sedimentation, thus providing a plausible mechanism for auxin flow redirection. In this study, using a functional NGR1-GFP construct, we visualized the NGR1 localization on the statolith surface and plasma membrane (PM) domains in close proximity to the statoliths, correlating with their movements. We determined that NGR1 binding to these PM domains is indispensable for NGR1 functionality and relies on cysteine acylation and adjacent polybasic regions as well as on lipid and sterol PM composition. Detailed timing of the early events following graviperception suggested that both NGR1 repolarization and initial auxin asymmetry precede the visible PIN3 polarization. This discrepancy motivated us to unveil a rapid, NGR-dependent translocation of PIN-activating AGCVIII kinase D6PK towards lower PMs of gravity-perceiving cells, thus providing an attractive model for rapid redirection of auxin fluxes following gravistimulation.

The phytohormone auxin is the major coordinative signal in plant development 1 , mediating transcriptional reprogramming by a well-established canonical signalling pathway. TRANSPORT INHIBITOR RESPONSE 1 (TIR1)/AUXIN-SIGNALING F-BOX (AFB) auxin receptors are F-box subunits of ubiquitin ligase complexes. In response to auxin, they associate with Aux/IAA transcriptional repressors and target them for degradation via ubiquitination 2 , 3 . Here we identify adenylate cyclase (AC) activity as an additional function of TIR1/AFB receptors across land plants. Auxin, together with Aux/IAAs, stimulates cAMP production. Three separate mutations in the AC motif of the TIR1 C-terminal region, all of which abolish the AC activity, each render TIR1 ineffective in mediating gravitropism and sustained auxin-induced root growth inhibition, and also affect auxin-induced transcriptional regulation. These results highlight the importance of TIR1/AFB AC activity in canonical auxin signalling. They also identify a unique phytohormone receptor cassette combining F-box and AC motifs, and the role of cAMP as a second messenger in plants. Adenylate cyclase activity in TIR1/AFB, the canonical auxin receptor, has an essential role in auxin-mediated root growth inhibition in land plants.

This study investigates the factors influencing the scale dependence of dispersivity and the dispersivity upscaling theory in heterogeneous sediments. A series of tracer experiments are first conducted to reveal the evolution of dispersivity across scales. These experiments contain various sedimentary structures, including several nearly‐homogeneous column tests, a heterogeneous column test, a horizontally stratified tank experiment, a randomly filled tank experiment, and a three‐dimensional tank experiment utilizing an analogous simulation to a field‐scale site. The impact of impervious boundaries, sedimentary architectures, and heterogeneity on the dispersivity scaling is assessed by controlling transport distance, setup dimension, facies volume proportions, and facies distribution. Finally, the Lagrangian‐based models, applicable for bounded and unbounded sediments, are employed to examine the relationship between various heterogeneous structures and dispersivity variations. The results indicate that the transport uncertainty introduced by dispersivity scaling is relatively weak in nearly‐homogeneous or stratified media but prominent in complex heterogeneous media. Hydraulic conductivity variance and space correlation structure in sediments contribute greatly to the value and increased rate of dispersivity. The predictive capabilities of transport models can be significantly improved by incorporating detailed facies indicator data and accounting for sediment heterogeneity. Although the impervious boundary enhances longitudinal dispersion by restricting transverse dispersion, the promoting effect decreases with the boundary spacing. The Lagrangian‐based models with detailed facies indicator data effectively capture the dispersivity variation trend with travel distance. The complementary use of the bounded and unbounded models can help better identify the scale‐dependent dispersivities, ultimately leading to more effective contaminant mitigation strategies. Plain Language Summary Dispersivity is a measure that helps us understand the speed and extent to which contaminants spread in the subsurface. It is a challenging factor to consider when simulating the movement of pollutants in the subsurface. In this study, we conducted several experiments to examine how dispersivity changes with the distance that contaminants travel. We used Lagrangian‐based models to analyze the relationships between the different scales and the evolution of dispersivity. Our findings show that the rate at which dispersivity increases with distance is influenced by the arrangement of different soil layers (facies) and the differences in how easily water can pass through them (permeability). The presence of an impermeable boundary affects dispersivity by limiting the spread of contaminants in certain directions. We found that both types of Lagrangian‐based models (bounded and unbounded) can accurately represent the changes in dispersivity seen in our experiments, but the bounded model is slightly more accurate. Key Points Multiple experiments are conducted to study the scale dependence of dispersivity Dispersivity variation in different sediments across scales is evaluated The impact of impervious boundaries on dispersivity scaling is investigated

ObjectiveDevelopment of an effective mucosal vaccine to induce specific immune responses against Foot-and-mouth disease virus (FMDV).ResultsFor this purpose, the FMDV VP1 gene (SPVP1) was optimized and synthesized based on the codon bias of Lactococcus lactis (L. lactis), and then incorporated in the plasmid pNZ8148. L. lactis NZ9000 containing the pNZ8148-SPVP1 recombinant plasmid was used as an oral delivery vehicle to induce anti-FMDV mucosal and systemic immune responses in mice. After confirmation that the SPVP1 protein was expressed successfully in the recombinant L. latic, the mice were orally challenged with NZ9000-pNZ8148, NZ9000-pNZ8148-SPVP1, phosphate-buffered saline as a mock infection group, or with inactivated vaccine as a positive group. Mice immunized with NZ9000-pNZ8148-SPVP1 produced high levels of mucosal secretory IgA (sIgA), antigen-specific serum IgG, IgA, and neutralizing antibodies, and developed stronger cell-mediated immune reactions and significant T spleen lymphocyte proliferation. Furthermore, the recombinant group generated much higher levels of IFN-γ, IL-2, IL-4, IL-5, and IL-10 than the other groups.ConclusionsPotent immune responses were successfully elicited in mice with FMDV VP1 delivered through L. lactis.

Background Although low-dose computed tomography (LDCT) screening effectively reduces LC mortality in high-risk individuals with a history of smoking in China, the feasibility and efficacy of lung cancer screening (LCS) in individuals who never smoked versus individuals who smoked remains unclear. Methods We conducted a retrospective analysis of prospective cohort studies at the National Cancer Center (NCC) in China from January 2006 to December 2022. A comprehensive LCS initiative was undertaken, involving 30,468 participants (54.5% male). Participants underwent LCS using LDCT. Potential malignancies were managed through joint consensus between patients and their physicians. Epidemiology, screening eligibility criteria, and LC detection rates and survival outcomes were compared between individuals who smoked and individuals who never smoked. Results Among 30,468 participants, 339 LCs were pathologically confirmed in 289 patients. The LC detection rate was 0.9% (289/30,468) overall, 0.8% in individuals who smoked (71/9,042), and 1.0% in individuals who never smoked (218/21,426). In individuals who smoked, LC detection rates were 0.5% (21/4516) and 1.1% (50/4526) in the < 20 and ≥ 20 pack-year subgroups, respectively ( P  = 0.001). Early-stage LC (stage 0 or I) was detected in 73.8% of the individuals who smoked and in 78.8% of individuals who never smoked, while advanced LC (stage III–IV) was found 8.8% of individuals who smoked and 4.2% of individuals who never smoked, respectively. Significant differences in histologic types were found between individuals who smoked and individuals who never smoked ( P  = 0.01), although adenocarcinoma was the most prevalent in both groups, at 83.0% and 78.8%, respectively. The median nodule size was 9.9 mm (IQR, 8.0–13.8) in individuals who smoked and 9.2 mm (IQR, 6.8–13.6) in individuals who never smoked ( P  = 0.228). Individuals who never smoked tended to favour surgical treatment alone (88.0%) more than individuals who smoked (81.3%). The 10-year survival rate was higher in individuals who never smoked (92.6%) than in individuals who smoked (88.8%). Only 15.6% (45/289) of patients with LC met the United States Preventive Services Task Force (USPSTF) criteria for LDCT eligibility, while 29.0% (84/289) met the China guideline for the screening and early detection of lung cancer (CGSL) criteria. Median follow-up for those followed was 25.4 (IQR, 13.7–43.3) months. Conclusions LDCT screening improves early LC detection and treatment outcomes for both individuals who smoked and individuals who never smoked. Significant differences exist in epidemiology, histologic type, and survival between these groups. The USPSTF and CGSL criteria miss a significant number of LC cases, particularly among individuals who never smoked. Integrating individuals who never smoked into LCS programs is essential, yet it comes with its own challenges, such as managing radiation risks, allocating resources effectively, and considering financial aspects. Consequently, there is an urgent need for LCS programs in China to better identify the “high-risk” non-smoker population susceptible to LC and to ensure that potential risks associated with screening are reduced.