Search Results (59)

Linker for activation of T cells (LAT) is an essential adaptor protein in early T cell receptor (TCR) signaling that propagates multiple signaling pathways. However, how LAT spatial organization facilitates signal initiation and propagation after TCR triggering is not clear. To differentiate de novo assembly in the plasma membrane from pre-existing LAT vesicles and clusters, we developed imaging protocols and analyses to capture the organization and dynamics of single LAT molecules immediately after TCR engagement. We could observe individual LAT molecules in the plasma membrane that assembled into immobile signaling entities requiring LAT phosphorylation. This step-wise assembly process was temporally highly coordinated via the zeta-chain-associated protein kinase 70 (Zap70)-LAT-growth factor receptor-bound protein 2 (Grb2) pathway. While multiple spatial organization co-existed even within the plasma membrane, our data suggest that de novo plasma membrane assemblies facilitated signal propagation. Full article

With the rise of smart agriculture and the expansion of pig farming, pig aggressive behavior recognition is crucial for maintaining herd health and improving farming efficiency. The differences in background and light variation in different barns can lead to the missed detection and false detection of pig aggressive behaviors. Therefore, we propose a deep learning-based pig aggressive behavior recognition model, in order to improve the adaptability of the model in complex pig environments. This model, combined with MobileNetV2 and Autoformer, can effectively extract local detail features of pig aggression and temporal correlation information of video frame sequences. Both Convolutional Block Attention Module (CBAM) and Advanced Filtering Feature Fusion Pyramid Network (HS-FPN) are integrated into the lightweight convolutional network MobileNetV2, which can more accurately capture key visual features of pig aggression and enhance the ability to detect small targets. We extract temporal correlation information between consecutive frames by the improved Autoformer. The Gate Attention Unit (GAU) is embedded into the Autoformer encoder in order to focus on important features of pig aggression while reducing computational latency. Experimental validation was implemented on public datasets, and the results showed that the classification recall, precision, accuracy, and F1-score of the model proposed in this paper reach 98.08%, 94.44%, 96.23%, and 96.23%, and the parameter quantity is optimized to 10.41 M. Compared with MobileNetV2-LSTM and MobileNetV2-GRU, the accuracy has been improved by 3.5% and 3.0%, respectively. Therefore, this model achieves a balance between recognition accuracy and computational complexity and is more suitable for automatic pig aggression recognition in practical farming scenarios, providing data support for scientific feeding and management strategies in pig farming. Full article

In Mediterranean ecosystems, a thorough understanding of seedling regeneration dynamics as well as a good predictive ability of the process is essential for sustainable forest management. Leveraging the predictive capacity of the multilayer perceptron (MLP) as recognized as artificial intelligence methodology, the authors analyzed a real case study with a dataset encompassing environmental, ecological, and forestry variables. The study focused on the cork oak (Quercus suber, L.) seedling regeneration dynamic, which is a critical process for maintaining ecosystem resilience. A set of 10 MLP with a block from 5 to 50 neurons with hyperbolic tangent (TanH), linear (LIN), and Gaussian (GAUS) activation function were tested and their performance for predictive purposes was compared with traditional quantitative approaches. The MLP configured with 40–50 neurons per activation function (TanH, LIN, GAUS) demonstrated outstanding predictive performance, achieving an area under the curve (AUC) of the receiver operating characteristic and precision-recall scores above 0.80. These models made few prediction errors, effectively explaining the majority of the data variance, as indicated by a high generalized R² and a low mislearning ratio. This approach outperformed traditional statistical models in predicting seedling regeneration. Tree density, stand density index, and acorn number played an important role, influencing the cork oak seedling prediction. In conclusion, the results of this research determined the importance of an AI classification modeling technique in the prediction of cork oak regeneration, providing practical references for future forest management strategy decisions. Full article

Glyoxalase I (GLYI) is a key enzyme that detoxifies methylglyoxal, a toxic byproduct of glycolysis, and is essential for plant pollination. However, the genome-wide identification and functional analysis of GLYI in Brassica rapa L. (B. rapa) remain limited. This study identified 17 BrGLYI genes (BrGLYI1–BrGLYI17) from the B. rapa genome. The self-compatible line 039-1 and the self-incompatible line GAU-28-5 were used as experimental materials, and Real-Time Quantitative Reverse Transcription PCR (RT-qPCR) was performed to examine the effect of BrGLYI genes on self-compatibility in winter B. rapa. Preliminary results showed that BrGLYI13 exhibited significant tissue specificity, with higher expression in the flowers of 039-1 compared to GAU-28-5. The open reading frame of BrGLYI13 (852 bp) was cloned from both 039-1 and GAU-28-5 cDNA, with no base mutations observed between the two lines. RT-qPCR revealed higher BrGLYI13 expression in the stigma of 039-1 compared to GAU-28-5. Based on the functional conservation and sequence homology, BrGLYI13 is speculated to play a similar role to that of AtGLYI3 in methylglyoxal detoxification and stress response. Furthermore, the knockout of AtGLYI3 resulted in reduced silique lengths and seed numbers. These findings suggest that BrGLYI13 is involved in the self-compatibility response in B. rapa and promotes the silique length and seed number in the Arabidopsis mutant, providing a basis for further research on the mechanisms of self-compatibility in B. rapa. Full article

Single-image super-resolution (SISR) methods based on convolutional neural networks (CNNs) have achieved breakthrough progress in reconstruction quality. However, their high computational costs and model complexity have limited their applications in resource-constrained devices. To address this, we propose the MSWSR (multi-scale wavelet super-resolution) method, a lightweight multi-scale feature selection network that exploits both symmetric and asymmetric feature patterns. MSWSR achieves efficient feature extraction and fusion through modular design. The core modules include a mixed feature module (MFM) and a gated attention unit (GAU). The MFM employs a symmetric multi-branch structure to efficiently integrate multi-scale features and enhance low-frequency information modeling. The GAU combines the spatial attention mechanism with the gating mechanism to further optimize symmetric feature representation capability. Moreover, a lightweight spatial selection module (SSA) adaptively assigns weights to key regions while maintaining structural symmetry in feature space. This significantly improves reconstruction quality in complex scenes. In 4× super-resolution tasks, compared to SPAN, MSWSR improves PSNR by 0.22 dB on Urban100 and 0.26 dB on Manga109 datasets. The model contains only 316K parameters, which is substantially lower than existing approaches. Extensive experiments demonstrate that MSWSR significantly reduces computational overhead while maintaining reconstruction quality, providing an effective solution for resource-constrained applications. Full article

Strategic deep tillage (SDT) practices, such as soil mixing following the application of soil amendments, are promising approaches to alleviate topsoil water repellence and other subsoil constraints and improve crop productivity. However, there is a lack of knowledge on the effect of SDT on soil water dynamics, especially under water-limited environments. This study evaluates the effects of clay incorporation, soil inversion and deep soil mixing on soil water infiltration, surface evaporation rates, soil water storage and subsequent impacts on the below and aboveground growth of wheat (Triticum aestivum L. var Scepter) in controlled environments. Results show that soil mixing significantly improved water infiltration compared to an untreated control. Clay incorporation exhibited the highest bare soil surface evaporation rates immediately and two years post-tillage, leading to substantial water losses under warm and dry ambient conditions. Despite improving soil water storage in deeper layers, high evaporation rates in clay-incorporated soils negatively impacted wheat growth, with reduced shoot biomass and root length density. Conversely, soil inversion and mixing-only treatments demonstrated balanced improvements in water infiltration, soil water use, and wheat shoot biomass. These findings underscore the trade-offs associated with SDT practices, particularly in managing soil water loss and crop productivity in water-limited environments. This study also highlights the need for the careful selection of SDT for soil amelioration strategies tailored to soil types and climatic conditions to enhance agricultural productivity and sustainability. Full article

Developing more effective gold–support synergy is essential for enhancing the catalytic performance of supported gold nanoparticles (AuNPs) in the gas-phase oxidation of ethanol to acetaldehyde (AC) at lower temperatures. This study demonstrates a significantly improved Au–support synergy achieved by copper doping in LaMO₃ (M = Mn, Fe, Co, Ni) perovskites. Among the various Au/LaMCuO₃ catalysts, Au/LaMnCuO₃ exhibited exceptional catalytic activity, achieving an AC yield of up to 91% and the highest space-time yield of 764 g_AC g_Au⁻¹ h⁻¹ at 225 °C. Notably, this catalyst showed excellent hydrothermal stability, maintaining performance for at least 100 h without significant deactivation when fed with 50% aqueous ethanol. Comprehensive characterization reveals that Cu doping facilitates the formation of surface oxygen vacancies on the Au/LaMCuO₃ catalysts and enhances Au–support interactions. The LaMnCuO₃ perovskite stabilizes the crucial Cu⁺ species, resulting in a stable Au-Mn-Cu synergy within the Au/LaMnCuO₃ catalyst, which facilitates the activation of O₂ and ethanol at lower temperatures. The optimization of the reaction conditions further improves AC productivity. Kinetic studies indicate that the cleavages of both the O-H bond and the α-C-H bond of ethanol are the rate-controlling steps. Full article

Common wheat production is significantly influenced by abiotic stresses. Identifying the genetic loci for seedling root traits and developing the available molecular markers are crucial for breeding high yielding and stable varieties. In this study, five wheat seedling root traits, including root length (RL), root surface area (RA), root volume (RV), number of root tips (RT), and root dry weight (RW), were measured in the Wp-072/Wp-119 recombinant inbred line (RIL) population. Genotyping was conducted for the RIL population and their parents using the wheat 90K single-nucleotide polymorphism (SNP) chip. In total, three quantitative trait loci (QTLs) for RL (QRL.gau-1DS, QRL.gau-1DL and QRL.gau-4AL), two QTLs for RA (QRA.gau-1D and QRA.gau-2DL), one locus for RV (QRV.gau-6AS), two loci for RW (QRW.gau-2DL and QRW.gau-2AS), and two loci for RT (QRT.gau-3AS and QRT.gau-6DL) were identified, with each explaining 4.5–8.4% of the phenotypic variances, respectively. Among these, QRT.gau-3AS, QRL.gau-4AL, and QRV.gau-6AS overlapped with the previous reports, whereas the other seven QTLs were novel. The favorable alleles of QRL.gau-1DS, QRL.gau-1DL, QRL.gau-4AL, QRA.gau-1D, QRW.gau-2AS, QRV.gau-6AS, QRT.gau-3AS, and QRT.gau-6DL were contributed by Wp-072, whereas the other two loci originated from Wp-119. Additionally, five kompetitive allele-specific PCR (KASP) markers, KASP-RL-1DL for RL, KASP-RA-1D and KASP-RA-2DL for RA, KASP-RW-2AS and KASP-RW-2DL for RW, were developed and validated successfully in 149 wheat accessions. Furthermore, seven candidate genes mainly for plant hormones were selected and validated by quantitative real-time PCR (qRT-PCR). This study provides new loci, new candidate genes, available KASP markers, and varieties for optimizing wheat root system architecture. Full article

Recently, political philosophers have debated the role of religious reasons in public deliberations, such as appealing to religious convictions and religious classics. Exclusivists, such as Rawls, Quong, Hartley, and Watson, argue that democratic governments and citizens should restrict or exclude the use of religious reasons in making laws and policies, while inclusivists, such as Gaus, Vallier, and Billingham, oppose such categorical exclusion. Nevertheless, the debate mainly focuses on the role of religious reasons in public deliberation. In this paper, I will argue that religious behaviors—defined as highly altruistic actions motivated by religious beliefs, such as dedicating substantial time and effort to serving the poor and advancing the common good—can exert positive influences on public deliberation. Through this kind of altruistic action, religious believers can subtly influence non-religious citizens. While religious believers may not rationally persuade non-religious citizens through religious reasoning, the altruistic actions exhibited by religious believers could emotionally inspire admiration and motivate non-religious citizens to learn more about those religions. This enhances mutual understanding among different religious and secular sects and thus improves public deliberation. Furthermore, I argue that the improved understanding fostered by religious behaviors can facilitate exclusivism and inclusivism to overcome certain philosophical challenges, such as the problems of incompleteness and anarchy, which are among the most frequent criticisms directed at exclusivism and inclusivism. Hence, this paper highlights an aspect overlooked in the exclusivism–inclusivism debate: no matter whether the democratic government and citizens should permit or restrict religious reasons, religious behavior is still beneficial in public deliberation. Full article

Tropomyosins (Tpms) are rod-shaped proteins that interact head-to-tail to form a continuous polymer along both sides of most cellular actin filaments. Head-to-tail interaction between adjacent Tpm molecules and the formation of an overlap complex between them leads to the assembly of actin filaments with one type of Tpm isoform in time and space. Variations in the affinity of tropomyosin isoforms for different actin structures are proposed as a potential sorting mechanism. However, the detailed mechanisms of the spatio-temporal sorting of Tpms remain elusive. In this study, we investigated the early intermediates during actin–tropomyosin filament assembly, using a skeletal/cardiac Tpm isoform (Tpm1.1) and a cytoskeletal isoform (Tpm1.6) that differ only in the last 27 amino acids. We investigated how the muscle isoform Tpm1.1 and the cytoskeletal isoform Tpm1.6 nucleate domains on the actin filament, and tested whether (1) recruitment is affected by the actin isoform (muscle vs. cytoskeletal) and (2) whether there is specificity in recruiting the same isoform to a domain at these early stages. To address these questions, actin filaments were exposed to low concentrations of fluorescent tropomyosins in solution. The filaments were immobilized onto glass coverslips and the pattern of decoration was visualized by TIRF microscopy. We show that at the early assembly stage, tropomyosins formed multiple distinct fluorescent domains (here termed “cluster”) on the actin filaments. An automated image analysis algorithm was developed and validated to identify clusters and estimate the number of tropomyosins in each cluster. The analysis showed that tropomyosin isoform sorting onto an actin filament is unlikely to be driven by a preference for nucleating on the corresponding muscle or cytoskeletal actin isoforms, but rather is facilitated by a higher probability of incorporating the same tropomyosin isoforms into an early assembly intermediate. We showed that the 27 amino acids at the end of each tropomyosin seem to provide enough molecular information for the attachment of the same tropomyosin isoforms adjacent to each other on an actin filament. This results in the formation of homogeneous clusters composed of the same isoform rather than clusters with mixed isoforms. Full article

Papilionoideae is the most species-rich subfamily of the third largest angiosperm family Fabaceae. One constituent large group, the inverted-repeat-lacking clade (IRLC), is well-known for the broad loss of one IR copy. Accumulating observations of massive plastomic disparities have made IRLC a well-suited model for exploring plastome evolution. However, there is still a large amount left to explore. The present study focused on the plastid tRNA (pttRNA) evolution within Papilionoideae, employing the currently densest sampling strategies for both the IRLC (156) and non-IRLC (109) lineages. Strikingly, our results revealed abundant inter-lineage variabilities in both tRNA sequences and structures, including a 3 nt difference in the average size of trnS-UGA, the consensus sequence disparities across 29 tRNAs, the distinct 3 nt indels in trnA-UGC, and an impressive 248 nt intron loss of IRLC trnI-GAU (potential markers). Additionally, there was unequal stability of the atypical secondary structures in trnS-GGA and trnS-UGA, as well as significantly diverse compositions of substitution events in all compared tRNAs (p < 0.05). Ultimately, these findings not only demonstrate the significant differences and unique markers of IRLC pttRNAs compared to other non-IRLC Papilionoideae, but also draw an important conclusion that the large losses of one IR potentially promote highly diverse evolutionary patterns of IRLC, which could partly compensate for the potential IR-lacking impacts. Full article

Dryas octopetala var. asiatica, a dwarf shrub belonging to the Rosaceae family and native to Asia, exhibits notable plasticity in photosynthesis in response to temperature variations. However, the codon usage patterns and factors influencing them in the chloroplast genome of this species have not yet been documented. This study sequenced and assembled the complete genome of D. octopetala var. asiatica. The annotated genes in the chloroplast genome were analyzed for codon composition through multivariate statistical methods including a neutrality plot, a parity rule 2 (PR2) bias plot, and an effective number of codons (ENC) plot using CodonW 1.4.2 software. The results indicated that the mean GC content of 53 CDSs was 38.08%, with the average GC content at the third codon base position being 27.80%, suggesting a preference for A/U(T) at the third codon position in chloroplast genes. Additionally, the chloroplast genes exhibited a weak overall codon usage bias (CUB) based on ENC values and other indicators. Correlation analysis showed a significant negative correlation between ENC value and GC2, an extremely positive correlation with GC3, but no correlation with GC1 content. These findings highlight the importance of the codon composition at the third position in influencing codon usage bias. Furthermore, our analysis indicated that the CUB of the chloroplast genome of D. octopetala var. asiatica was primarily influenced by natural selection and other factors. Finally, this study identified UCA, CCU, GCU, AAU, GAU, and GGU as the optimal codons. These results offer a foundational understanding for genetic modification and evolutionary dynamics of the chloroplast genome of D. octopetala var. asiatica. Full article

Cynanchum belongs to the Apocynaceae family and is a morphologically diverse genus that includes around 200 shrub or perennial herb species. Despite the utilization of CPGs, few molecular phylogenetic studies have endeavored to elucidate infrafamilial relationships within Cynanchum through extensive taxon sampling. In this research, we constructed a phylogeny and estimated divergence time based on the chloroplast genomes (CPGs) of nine Cynanchum species. We sequenced and annotated nine chloroplast (CP) genomes in this study. The comparative analysis of these genomes from these Cynanchum species revealed a typical quadripartite structure, with a total sequence length ranging from 158,283 to 161,241 base pairs (bp). The CP genome (CPG) was highly conserved and moderately differentiated. Through annotation, we identified a total of 129–132 genes. Analysis of the boundaries of inverted repeat (IR) regions showed consistent positioning: the rps19 gene was located in the IRb region, varying from 46 to 50 bp. IRb/SSC junctions were located between the trnN and ndhF genes. We did not detect major expansions or contractions in the IR region or rearrangements or insertions in the CPGs of the nine Cynanchum species. The results of SSR analysis revealed a variation in the number of SSRs, ranging from 112 to 150. In five types of SSRs, the largest number was mononucleotide repeats, and the smallest number was hexanucleotide repeats. The number of long repeats in the cp genomes of nine Cynanchum species was from 35 to 80. In nine species of Cynanchum, the GC3s values ranged from 26.80% to 27.00%, indicating a strong bias towards A/U-ending codons. Comparative analyses revealed four hotspot regions in the CPG, ndhA-ndhH, trnI-GAU-rrn16, psbI-trnS-GCU, and rps7-ndhB, which could potentially serve as molecular markers. In addition, phylogenetic tree construction based on the CPG indicated that the nine Cynanchum species formed a monophyletic group. Molecular dating suggested that Cynanchum diverged from its sister genus approximately 18.87 million years ago (Mya) and species diversification within the Cynanchum species primarily occurred during the recent Miocene epoch. The divergence time estimation presented in this study will facilitate future research on Cynanchum, aid in species differentiation, and facilitate diverse investigations into this economically and ecologically important genus. Full article

The complex environmental impact makes it difficult to predict wind speed with high precision for multiple wind turbines. Most existing research methods model the temporal dependence of wind speeds, ignoring the spatial correlation between wind turbines. In this paper, we propose a multi-wind turbine wind speed prediction model based on Weighted Diffusion Graph Convolution and Gated Attention Network (WDGCGAN). To address the strong nonlinear correlation problem among multiple wind turbines, we use the maximal information coefficient (MIC) method to calculate the correlation weights between wind turbines and construct a weighted graph for multiple wind turbines. Next, by applying Diffusion Graph Convolution (DGC) transformation to the weight matrix of the weighted graph, we obtain the spatial graph diffusion matrix of the wind farm to aggregate the high-order neighborhood information of the graph nodes. Finally, by combining the DGC with the gated attention recurrent unit (GAU), we establish a spatio-temporal model for multi-turbine wind speed prediction. Experiments on the wind farm data in Massachusetts show that the proposed method can effectively aggregate the spatio-temporal information of wind turbine nodes and improve the prediction accuracy of multiple wind speeds. In the 1h prediction task, the average RMSE of the proposed model is 28% and 33.1% lower than that of the Long Short-Term Memory Network (LSTM) and Convolutional Neural Network (CNN), respectively. Full article

A novel strain of Fusarium oxysporum virus 1 (FoV1) was identified from the Fusarium oxysporum f. sp. niveum strain X-GS16 and designated as Fusarium oxysporum virus 1-FON (FoV1-FON). The full genome of FoV1-FON is 2902 bp in length and contains two non-overlapping open reading frames (ORFs), ORF1 and ORF2, encoding a protein with an unknown function (containing a typical −1 slippery motif G_GAU_UUU at the 3′-end) and a putative RNA-dependent RNA polymerase (RdRp), respectively. BLASTx search against the National Center for the Biotechnology Information (NCBI) non-redundant database showed that FoV1-FON had the highest identity (97.46%) with FoV1. Phylogenetic analysis further confirmed that FoV1-FON clustered with FoV1 in the proposed genus Unirnavirus. FoV1-FON could vertically transmit via spores. Moreover, FoV1-FON was transmitted horizontally from the F. oxysporum f. sp. niveum strain X-GS16 to the F. oxysporum strain HB-TS-YT-1_hyg. This resulted in the acquisition of the F. oxysporum strain HB-TS-YT-1_hyg-V carrying FoV1-FON. No significant differences were observed in the sporulation and dry weight of mycelial biomass between HB-TS-YT-1_hyg and HB-TS-YT-1_hyg-V. FoV1-FON infection significantly increased the mycelial growth of HB-TS-YT-1_hyg, but decreased its virulence to potato tubers and sensitivity to difenoconazole, prochloraz, and pydiflumetofen. To our knowledge, this is the first report of hypovirulence and reduced sensitivity to difenoconazole, prochloraz, and pydiflumetofen in F. oxysporum due to FoV1-FON infection. Full article