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Magnesium alloys have received a lot of attention in aerospace, automotive, electronic communications and other fields due to their low density, high specific strength and damping performance. However, magnesium alloy sheets prepared by conventional thermomechanical processing usually have a strong basal texture, resulting in poor formability. In this paper, Mg–Mn–Ce alloys with good plastic forming ability were prepared by studying and optimizing the annealing process. Under the low-temperature annealing condition, it can promote the static recrystallization and grain refinement of Mg–Mn–Ce alloy, and also eliminate the internal stress. With the increase of annealing temperature, a large amount of dispersed Mg12Ce as a stable second phase effectively hindered the grain boundary migration, while the nanoscale α-Mn forms a fine second phase to inhibit grain growth, and both of them together greatly stabilize the deformation structure of the alloy, and maintain a good grain organization under the condition of annealing temperature of 300 °C and holding time of 30 min. The present work also improves the Arrhenius constitutive equation for the Mg–Mn–Ce alloy with respect to the degree of deviation, which significantly improves the accuracy of the model in predicting the thermoforming behavior. Meanwhile, to address the shortcomings of the traditional forming method of magnesium alloy, the processing process of spreading the centrifugal casting tube flat is proposed, the forming process is simulated, and the location of easy breakage in the forming process is predicted. These findings provide microanalytical support for the improvement of forming properties of magnesium alloys by annealing.

Magnesium-manganese series alloys, as materials with very low-density value, have excellent mechanical properties and corrosion resistance, and have broad prospects in automotive, aerospace, biomedical and other fields. In this work, the thermal deformation behavior and microstructural evolution of Mg–Mn–Ce alloys were investigated through uniaxial hot stretching experiments on Mg–Mn–Ce alloy plates under different deformation conditions, with the main focus on the plastic deformation mechanism of Mg–Mn–Ce alloys under different forming conditions. The unified viscoplastic constitutive equation for coupled damage is developed and compared with different types of constitutive equation models. Remarkably, the decrease in peak stress with increasing temperature or decreasing strain rate in Mg–Mn–Ce alloys is due to the fact that the internal slip system of the material is more easily activated with increasing temperature. As the temperature increases, the dislocations within the material decrease, which is due to the fact that the temperature increase makes the DRX action progressively stronger than the dislocation action, and the DRX leads to a significant coarsening of the grains at 573 K. In addition, the fracture behavior of the alloy under different deformation conditions has also been investigated, and the fracture pattern of Mg–Mn–Ce alloys transitions from pronounced cleavage fracture to the appearance of dimples and finally to ductile fracture with a large number of dimples as the temperature increases.

This paper developed a radish disease detection system based on a hybrid attention mechanism, significantly enhancing the precision and real-time performance in identifying disease characteristics. By integrating spatial and channel attentions, this system demonstrated superior performance across numerous metrics, particularly achieving 93% precision and 91% accuracy in detecting radish virus disease, outperforming existing technologies. Additionally, the introduction of the hybrid attention mechanism proved its superiority in ablation experiments, showing higher performance compared to standard self-attention and the convolutional block attention module. The study also introduced a hybrid loss function that combines cross-entropy loss and Dice loss, effectively addressing the issue of class imbalance and further enhancing the detection capability for rare diseases. These experimental results not only validate the effectiveness of the proposed method, but also provide robust technical support for the rapid and accurate detection of radish diseases, demonstrating its vast potential in agricultural applications. Future research will continue to optimize the model structure and computational efficiency to accommodate a broader range of agricultural disease detection needs.

This study addresses the challenges of elaeagnus angustifolia disease detection in smart agriculture by developing a detection system that integrates advanced deep learning technologies, including Large Language Models (LLMs), Agricultural Knowledge Graphs (KGs), Graph Neural Networks (GNNs), representation learning, and neural-symbolic reasoning techniques. The system significantly enhances the accuracy and efficiency of disease detection through an innovative graph attention mechanism and optimized loss functions. Experimental results demonstrate that this system significantly outperforms traditional methods across key metrics such as precision, recall, and accuracy, with the graph attention mechanism excelling in all aspects, particularly achieving a precision of 0.94, a recall of 0.92, and an accuracy of 0.93. Furthermore, comparative experiments with various loss functions further validate the effectiveness of the graph attention loss mechanism in enhancing model performance. This research not only advances the application of deep learning in agricultural disease detection theoretically but also provides robust technological tools for disease management and decision support in actual agricultural production, showcasing broad application prospects and profound practical value.

In this study, a novel approach integrating multimodal data processing and attention aggregation techniques is proposed for pear tree disease detection. The focus of the research is to enhance the accuracy and efficiency of disease detection by fusing data from diverse sources, including images and environmental sensors. The experimental results demonstrate that the proposed method outperforms in key performance metrics such as precision, recall, accuracy, and F1-Score. Specifically, the model was tested on the Kaggle dataset and compared with existing advanced models such as RetinaNet, EfficientDet, Detection Transformer (DETR), and the You Only Look Once (YOLO) series. The experimental outcomes indicate that the proposed model achieves a precision of 0.93, a recall of 0.90, an accuracy of 0.92, and an F1-Score of 0.91, surpassing those of the comparative models. Additionally, detailed ablation experiments were conducted on the multimodal weighting module and the dynamic regression loss function to verify their specific contributions to the model performance. These experiments not only validated the effectiveness of the proposed method but also demonstrate its potential application in pear tree disease detection. Through this research, an effective technological solution is provided for the agricultural disease detection domain, offering substantial practical value and broad application prospects.

In this study, an advanced method for apricot tree disease detection is proposed that integrates deep learning technologies with various data augmentation strategies to significantly enhance the accuracy and efficiency of disease detection. A comprehensive framework based on the adaptive sampling latent variable network (ASLVN) and the spatial state attention mechanism was developed with the aim of enhancing the model’s capability to capture characteristics of apricot tree diseases while ensuring its applicability on edge devices through model lightweighting techniques. Experimental results demonstrated significant improvements in precision, recall, accuracy, and mean average precision (mAP). Specifically, precision was 0.92, recall was 0.89, accuracy was 0.90, and mAP was 0.91, surpassing traditional models such as YOLOv5, YOLOv8, RetinaNet, EfficientDet, and DEtection TRansformer (DETR). Furthermore, through ablation studies, the critical roles of ASLVN and the spatial state attention mechanism in enhancing detection performance were validated. These experiments not only showcased the contributions of each component for improving model performance but also highlighted the method’s capability to address the challenges of apricot tree disease detection in complex environments. Eight types of apricot tree diseases were detected, including Powdery Mildew and Brown Rot, representing a technological breakthrough. The findings provide robust technical support for disease management in actual agricultural production and offer broad application prospects.

This paper conducts research on the development trend of automobile energy-saving standard system under China’s goal of peak carbon dioxide emissions by 2030. The research first sorted out the carbon dioxide emission standards and regulations of major automobile developed countries in the world, systematically analyzed the current status of China's automobile energy-saving standard system, and proposed the key problems at this stage. With the goal of peak carbon dioxide emissions as the core, the key tasks for the next phase of the construction of the automotive energy-saving standard system are proposed, including comprehensively promoting the formulation of fuel consumption standards for passenger cars and commercial vehicles from 2025 to 2030, and accelerating the construction of NEV energy-saving standard system.

Abstract Background Aldehyde dehydrogenases (ALDHs) are a family of enzymes that catalyze the oxidation of aldehyde molecules into the corresponding carboxylic acid, regulate the balance of aldehydes and protect plants from the poisoning caused by excessive accumulation of aldehydes; however, this gene family has rarely been studied in cotton. Results In the present study, genome-wide identification was performed, and a total of 114 ALDH family members were found in three cotton species, Gossypium hirsutum, Gossypium arboreum and Gossypium raimondii. The ALDH genes were divided into six subgroups by evolutionary analysis. ALDH genes in the same subgroup showed similar gene structures and conserved motifs, but some genes showed significant differences, which may result in functional differences. Chromosomal location analysis and selective pressure analysis revealed that the ALDH gene family had experienced many fragment duplication events. Cis-acting element analysis revealed that this gene family may be involved in the response to various biotic and abiotic stresses. The RT‒qPCR results showed that the expression levels of some members of this gene family were significantly increased under salt stress conditions. Gohir.A11G040800 and Gohir.D06G046200 were subjected to virus-induced gene silencing (VIGS) experiments, and the sensitivity of the silenced plants to salt stress was significantly greater than that of the negative control plants, suggesting that Gohir.A11G040800 and Gohir.D06G046200 may be involved in the response of cotton to salt stress. Conclusions In total, 114 ALDH genes were identified in three Gossypium species by a series of bioinformatics analysis. Gene silencing of the ALDH genes of G. hirsutum revealed that ALDH plays an important role in the response of cotton to salt stress.

IntroductionAlthough restriction of vertical ocular range of motion is known to be the hallmark of progressive supranuclear palsy (PSP), the maximal amplitude of ocular movement has not been quantitatively assessed despite of accumulating evidences of oculomotor dysfunction in Parkinson's disease (PD). Here, we evaluated the maximal oculomotor range and its response to levodopa in PD, and compare findings to atypical parkinsonism.MethodsWe recruited 159 healthy controls (HC) as well as 154 PD, 30 PSP, and 16 multiple system atrophy (MSA) patients. Oculomotor range was assessed using a kinetic perimeter-adapted device for the vertical and horizontal axes (four positions). Parameters were reassessed after levodopa challenge and compared among PD, PSP, and MSA patients.ResultsMaximum oculomotor range in PD patients was reduced as compared to HC. Levodopa improved oculomotor range in all directions; corrective effects of upward range positively correlated with improvements in Unified Parkinson's Disease Rating Scale III and bradykinesia sub-scores among PD patients. Although oculomotor range was markedly restricted among PSP and MSA patients, the beneficial effects of levodopa was less pronounced. Reduced oculomotor range of motion was more significant among PSP as compared to PD or MSA patients; MSA patients did not significantly differ from PD patients. The range of upward gaze was optimally sensitive for differentiating among PD, PSP, and MSA patients.ConclusionMaximum oculomotor range was reduced among PD patients significantly improved by levodopa treatment. Variations in, as well as the positively effects of levodopa on, the range of upward gaze assist diagnostic differentiation among PD, PSP, and MSA patients.

Abstract Background Geranylgeranyl pyrophosphate synthase (GGPS) is a structural enzyme of the terpene biosynthesis pathway that is involved in regulating plant photosynthesis, growth and development, but this gene family has not been systematically studied in cotton. Results In the current research, genome-wide identification was performed, and a total of 75 GGPS family members were found in four cotton species, Gossypium hirsutum, Gossypium barbadense, Gossypium arboreum and Gossypium raimondii. The GGPS genes were divided into three subgroups by evolutionary analysis. Subcellular localization prediction showed that they were mainly located in chloroplasts and plastids. The closely related GGPS contains a similar gene structure and conserved motif, but some genes are quite different, resulting in functional differentiation. Chromosome location analysis, collinearity and selection pressure analysis showed that many fragment duplication events occurred in GGPS genes. Three-dimensional structure analysis and conservative sequence analysis showed that the members of the GGPS family contained a large number of α-helices and random crimps, and all contained two aspartic acid-rich domains, DDxxxxD and DDxxD (x is an arbitrary amino acid), suggesting its key role in function. Cis-regulatory element analysis showed that cotton GGPS may be involved in light response, abiotic stress and other processes. A GGPS gene was silenced successfully by virus-induced gene silencing (VIGS), and it was found that the chlorophyll content in cotton leaves decreased significantly, suggesting that the gene plays an important role in plant photosynthesis. Conclusions In total, 75 genes were identified in four Gossypium species by a series of bioinformatics analysis. Gene silencing from GGPS members of G. hirsutum revealed that GGPS plays an important regulatory role in photosynthesis. This study provides a theoretical basis for the biological function of GGPS in cotton growth and development.

BackgroundAI-based clinical decision support system (CDSS) has important prospects in overcoming the current informational challenges that cancer diseases faced, promoting the homogeneous development of standardized treatment among different geographical regions, and reforming the medical model. However, there are still a lack of relevant indicators to comprehensively assess its decision-making quality and clinical impact, which greatly limits the development of its clinical research and clinical application. This study aims to develop and application an assessment system that can comprehensively assess the decision-making quality and clinical impacts of physicians and CDSS.MethodsEnrolled adjuvant treatment decision stage early breast cancer cases were randomly assigned to different decision-making physician panels (each panel consisted of three different seniority physicians in different grades hospitals), each physician made an independent “Initial Decision” and then reviewed the CDSS report online and made a “Final Decision”. In addition, the CDSS and guideline expert groups independently review all cases and generate “CDSS Recommendations” and “Guideline Recommendations” respectively. Based on the design framework, a multi-level multi-indicator system including “Decision Concordance”, “Calibrated Concordance”, “ Decision Concordance with High-level Physician”, “Consensus Rate”, “Decision Stability”, “Guideline Conformity”, and “Calibrated Conformity” were constructed.Results531 cases containing 2124 decision points were enrolled; 27 different seniority physicians from 10 different grades hospitals have generated 6372 decision opinions before and after referring to the “CDSS Recommendations” report respectively. Overall, the calibrated decision concordance was significantly higher for CDSS and provincial-senior physicians (80.9%) than other physicians. At the same time, CDSS has a higher “ decision concordance with high-level physician” (76.3%-91.5%) than all physicians. The CDSS had significantly higher guideline conformity than all decision-making physicians and less internal variation, with an overall guideline conformity variance of 17.5% (97.5% vs. 80.0%), a standard deviation variance of 6.6% (1.3% vs. 7.9%), and a mean difference variance of 7.8% (1.5% vs. 9.3%). In addition, provincial-middle seniority physicians had the highest decision stability (54.5%). The overall consensus rate among physicians was 64.2%.ConclusionsThere are significant internal variation in the standardization treatment level of different seniority physicians in different geographical regions in the adjuvant treatment of early breast cancer. CDSS has a higher standardization treatment level than all physicians and has the potential to provide immediate decision support to physicians and have a positive impact on standardizing physicians’ treatment behaviors.

Tumoral heterogeneity has proven to be a leading cause of difference in prognosis and acquired drug resistance. High intratumor heterogeneity often means poor clinical response and prognosis. Histopathological subtypes suggest tumor heterogeneity evolved during the progression of lung adenocarcinoma, but the exploration of its molecular mechanisms remains limited. In this work, we first verified that transcriptional patterns of a set of differentially expressed genes profoundly revealed the histologic progression of lung adenocarcinoma. Next, a predictive model based on the transcriptional patterns was established to accurately distinguish histologic subtypes. Two crucial genes were identified and used to construct a tumor heterogeneous scoring model (L2SITH) to stratify patients, and we found that patients with low heterogeneity score had better prognosis. Low L2SITH scores implied low tumor purity and beneficial tumor microenvironment. Moreover, L2SITH effectively identified cohorts with better responses to anti–PD-1 immunotherapy.

The Salmonella flagellar secretion apparatus is a member of the type III secretion (T3S) family of export systems in bacteria. After completion of the flagellar motor structure, the hook-basal body (HBB), the flagellar T3S system undergoes a switch from early to late substrate secretion, which results in the expression and assembly of the external, filament propeller-like structure. In order to characterize early substrate secretion-signals in the flagellar T3S system, the FlgB, and FlgC components of the flagellar rod, which acts as the drive-shaft within the HBB, were subject to deletion mutagenesis to identify regions of these proteins that were important for secretion. The β-lactamase protein lacking its Sec-dependent secretion signal (Bla) was fused to the C-terminus of FlgB and FlgC and used as a reporter to select for and quantify the secretion of FlgB and FlgC into the periplasm. Secretion of Bla into the periplasm confers resistance to ampicillin. In-frame deletions of amino acids 9 through 18 and amino acids 39 through 58 of FlgB decreased FlgB secretion levels while deleting amino acid 6 through 14 diminished FlgC secretion levels. Further PCR-directed mutagenesis indicated that amino acid F45 of FlgB was critical for secretion. Single amino acid mutagenesis revealed that all amino acid substitutions at F45 of FlgB position impaired rod assembly, which was due to a defect of FlgB secretion. An equivalent F49 position in FlgC was essential for assembly but not for secretion. This study also revealed that a hydrophobic patch in the cleaved C-terminal domain of FlhB is critical for recognition of FlgB at F45.

In this paper, three different shapes of indenters were used to perform quasi-static out-of-plane uniaxial compression and indentation tests on three commercial hexagonal aluminum honeycombs with different densities. In order to distinguish the different tearing conditions of the single-layer and double-layer aluminum honeycomb walls during indentation, a new indentation experiment was designed. By controlling the shape of pattern and the location of indentation, different tearing conditions in indentation experiment were measured separately. The deformation mode of the aluminum honeycomb when pressed was analyzed. It is found that as the size of the pattern increases, the peak stress of the indentation experiment decreases significantly. As the size of the indenter increases, the platform stress of aluminum honeycomb shows a downward trend and tends to approach the compression platform stress, while the tear strength remains basically stable within a certain scale. As the size of the indenter continues to increase, the proportion of tearing force to the total indenting force gradually decreases, and the tearing strength loses its stability. At this time, the tear strength can no longer be used as a stable mechanical parameter to measure the tearing condition during indentation.

In diabetes mellitus, death of β cell in the pancreas occurs throughout the development of the disease, with loss of insulin production. The maintenance of β cell number is essential to maintaining normoglycemia. SNAPIN has been found to regulate insulin secretion, but whether it induces β cell proliferation remains to be elucidated. This study aimed to explore the physiological roles of SNAPIN in β cell proliferation. SNAPIN expression increases with the age of mice and SNAPIN is down-regulated in diabetes. KEGG pathway and GO analysis showed that SNAPIN- interacting proteins were enriched in cell cycle regulation. B cell cycle was arrested in the S phase, and cell proliferation was inhibited after SNAPIN knockdown. The expression of CDK2, CDK4 and CCND1 proteins in the S phase of the cell cycle were reduced after SNAPIN knockdown, whereas they were increased after overexpression of SNAPIN. In addition, insulin protein and mRNA levels also increased or decreased after SNAPIN knockdown or overexpression, respectively. Conclusions: Our data indicate that SNAPIN mediates β cells proliferation and insulin secretion, and provide evidences that SNAPIN might be a pharmacotherapeutic target for diabetes mellitus.

Context: In vitro and in vivo research has shown that curcumin can alleviate diabetes and the relevant complications. Objective: To investigate the effect of curcumin on gestational diabetes (GD). Materials and methods: C57 BL/KsJdb/+(db/+) mice and C57 BL/KsJ+/+ mice (10–12 weeks old) were divided into four groups (n = 15): normal pregnancy (C57 BL/KsJ+/+), GD (C57 BL/KsJdb/+), GD plus low dose curcumin (50 mg/kg, orally gavage every day) and GD plus high dose curcumin (100 mg/kg, orally gavage every day). The tolerance of glucose and insulin were measured on gestation day 10. Body weight at birth and litter size of offspring were investigated, and the expression of oxidative stress factors [thiobarbituric acid reactive substance (TBARS), glutathione (GSH), superoxide dismutase (SOD) and catalase (CAT)] and AMP-activated protein kinase (AMPK), phospho-AMPK, histone deacetylases 4 (HDAC4), pHDAC4 and glucose-6-phosphatase (G6Pase) in the livers were analyzed by ELISA and Western blot on gestation day 20. Results: High dose curcumin could partly ameliorate the intolerance of glucose and insulin, and completely restore the litter size and the body weight of GD mice through decreased TBARS expression (p

Some studies have demonstrated that acrylamide (AA) was correlated with oxidative stress, resulting in physical damage. The jackfruit flake was an immature pulp that contained a high level of antioxidant activity. This study aimed to assess the defensive efficacy of jackfruit flake in AA-induced oxidative stress before and after simulated gastrointestinal digestion. Our results indicate that the total polyphenol content of Jackfruit flake digest (Digestive products of jackfruit flake after gastrointestinal, JFG) was diminished; however, JFG had raised the relative antioxidant capacity compared to Jackfruit flake extract (JFE). Additionally, the results of High Performance Liquid Chromatography-Mass Spectrometry (HPLC-MS) implied that a proportion of compounds were degraded/converted into other unknown and/or undetected metabolites. Further, by high content analysis (HCA) techniques, JFG markedly reduced cytotoxicity and excessive production of reactive oxygen species (ROS) in cells, thereby alleviating mitochondrial disorders. In this study, it may be converted active compounds after digestion that had preferable protective effects against AA-induced oxidative damage.

The safety of food additives has been widely concerned. Using single additives in the provisions of scope is safe, but the combination of additives, may induce additive, synergy, antagonism and other joint effects. This study investigated the cytotoxicity of aspartame (AT) together with potassium sorbate (PS). Thiazolyl Blue Tetrazolium Bromide (MTT) assay indicated that AT and PS had IC50 values of 0.48 g/L and 1.25 g/L at 24 h, respectively. High content analysis (HCA) showed that both AT and PS had a negative effect on mitochondrial membrane potential (MMP), reactive oxygen species (ROS) and DNA damage while the joint group behaved more obviously. The biochemical assays revealed typical cell morphological changes and the activation of cytochrome c and caspase-3 verified apoptosis induced by AT together with PS. With dissipation of MMP and increase of cell membrane permeability (CMP), it indicated AT together with PS-induced apoptosis was mediated by mitochondrial pathway. Meanwhile, p53 were involved in DNA damage, and the ratio of Bax/Bcl-2 was increased. Moreover, excessive ROS induced by AT together with PS is a key initiating factor for apoptosis. All these results proved that p53 was involved in apoptosis via mitochondria-mediated pathway and the process was regulated by ROS.