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Abstract Mechanochemistry studies the effect of mechanical force on chemical bonds, bringing opportunities for synthesizing alloys, ceramics, organics, polymers, and biomaterials. A vital issue of applying macro-scale mechanical force to manipulate crystal structures is finding ways to precisely adjust the force directions to break micro-scale target chemical bonds. Inspired by a common technique of driving a wedge into the wood to make wood chopping much easier, a wedging strategy of splitting three-dimensional structured crystalline frameworks and then converting them to nanosheets was proposed, where specific molecules were wedged into crystalline frameworks to drive the directional transmission of mechanical force to break chemical bonds. As a result, various crystalline framework nanosheets including metal−organic framework nanosheets, covalent organic framework nanosheets, and coordination polymer nanosheets were fabricated. This wedging crystal strategy exhibits advantages of operability, flexibility and designability, and furthermore, it is expected to expand mechanochemistry applications in material preparation.

Purpose: Aims to provide an overview of the contemporary epidemiology of malignant orbital tumors by analyzing population-based incidence patterns across various regions worldwide. Methods: In this article, we retrieved orbital malignancy data from the MEDLINE database and analyzed the incidence and prevalence of orbital malignancies worldwide. We performed the literature search by searching on the Mesh terms for malignant orbital tumors (''orbital'', ''tumor'', ''lymphoma'', ''malignant'', ''cancer'', ''incidence'', and ''epidemiology''). All included studies were published between 1993 and 2023 and were written in English. Results: Ocular or ophthalmic lymphoma most frequently occurred in the orbit, with a prevalence ranging from 47% to 54%. The incidence of malignant orbital tumors was increasing in the USA (2.0 per million (1981–1993), Netherlands (0.86 (1981–1985) to 2.49 (2001–2005) per million) and South Korea (0.3–0.8 per million (1999–2016)), respectively. Ophthalmic lymphoma which includes orbit lymphoma was increasing in Canada (0.17–1.47 per million (1992–2010)), Denmark (0.86 per million (1981–1985) to 2.49 per million (2001–2005)), respectively. Conclusions: The predominant primary malignant orbital tumor in adults was lymphoma. Ocular or ophthalmic lymphoma most frequently occured in the orbit. The limited data available suggested an increasing trend in the incidence of malignant orbital tumors in each country included, which were mainly attributed to the increase in lymphoma. Generally, incidence rates were found to increase with advancing age, with no difference between males and females.

Abstract Background Heat and drought stresses usually occur together in nature, and both are expected to increase in frequency and intensity as a result of climate change. The synergistic impacts of these compound climate extremes on potatoes are far from the effects of individual stresses. However, the dynamics of the effects of combined heat and drought stresses on potato physiology and biochemistry have yet to be thoroughly assessed. To elucidate this point, we set up a pot experiment using ‘Atlantic’ potato seedlings as test material. A total of six treatments were set up: CK (normal growth conditions: 21 ℃, 0 PEG), A1B1 (31 ℃, 20% PEG), A1B2 (31 ℃, 10% PEG), A1B3 (31 ℃, 0 PEG), A2B1 (21 ℃, 20% PEG), and A2B2 (21 ℃, 10% PEG), and 15 physiological indices were determined with the stress time of 0, 6, 12 and 18 days. Results After 18 days of stress, the phenotype of potato seedlings was significantly different. Compared with CK, the thickness of potato leaves and palisade tissue increased under heat and drought stress, and the combined stress reduced the photosynthetic efficiency of potato leaves. In all treatments except CK, the chlorophyll content decreased significantly, the antioxidant enzyme activity increased first and then decreased, and the relative conductivity and malondialdehyde content increased significantly. The heat and combined treatment made the content of the osmotic regulator first increase and then decrease, while the treatment of 21 ℃ had no significant change. According to the correlation, principal component and interaction analysis, both heat and drought treatment had significant effects on each index, and the longer the stress time, the greater the effect, and the effect of combined stress was greater than that of single stress. However, after 6 days of stress, the activity of antioxidant enzymes and the content of transparent regulatory substances increased. Conclusions In conclusion, potato can cope with heat, drought and combined stress by adjusting leaf tissue structure, antioxidant enzyme activity and osmotic regulatory substances in a short time. Graphical Abstract

Abstract Background Potato (Solanum tuberosum L.) production is seriously threatened by the oomycete Phytophthora infestans (P. infestans). However, it remains unclear how the two potato cultivars, Q9 (moderately resistant) and Atl (susceptible), initiate distinct defense responses after inoculation with P. infestans. To uncover the underlying process, we investigated the dynamic gene expression profiles and the functions of the differentially expressed genes (DEGs). Results The results showed that the numbers of up-regulated DEGs were 1345, 1063 and 1694 in Q9 and 272, 603 and 2554 in Atl at 1 day post inoculation (dpi), 3 dpi and 5 dpi, respectively. Meanwhile, the down-regulated DEGs were 1557, 1417 and 389 in Q9 and 114, 364 and 2528 in Atl simultaneously. KEGG enrichment analysis revealed that plant-pathogen interaction, phenylpropanoid biosynthesis and MAPK signaling pathway were significantly enriched in Q9 at the later stage. Furthermore, DEGs associated with plant-pathogen interaction and phenylpropanoid biosynthesis showed higher expression levels in Q9 compared to Atl, especially at the later stage. The expressions of eight DEGs were validated by quantitative real-time PCR (qRT-PCR), which further verified the accuracy of the transcriptomics analysis. In addition, DEGs that were exclusively up-regulated and down-regulated in Q9 were analyzed, which may contribute to the resistance of Q9. Transient expression analysis revealed that four DEGs, including StHP1, StMYB2, StHSP3 and StNAC5, exhibited increased tolerance to P. infestans, indicating a positive role in enhancing the resistance of Q9. Conclusion Therefore, the DEGs associated with plant-pathogen interaction, phenylpropanoid biosynthesis and MAPK signaling pathway were involved in regulating late blight, and the expression level of the related genes significantly increased in Q9. In addition, StHP1, StHSP3 and the transcription factors, including StMYB2 and StNAC5, played positive roles in improving the resistance of potato Q9 to P. infestans. These findings provide useful information for further understanding the molecular mechanism of potato resistance to late blight. Furthermore, our study identified novel resistance genes that can be used in resistance breeding and functional research. Graphical abstract

Abstract Background Left atrial myxoma during pregnancy is rare. We present three cases in order to aid in the management. Case Presentation Three cases of left atrial myxoma during pregnancy were presented in this article. Three patients all received multidisciplinary team work and acquired good outcomes. The case 1 had no symptoms and delivered before traditional cardiac surgery. The case 2 and case 3 undergone totally endoscopic minimally invasive cardiac surgery during pregnancy. The case 3 maintained pregnancy to term and gave birth to a healthy baby via vaginal delivery. No relapse of the tumor was observed. Conclusions The management of left atrial myxoma during pregnancy ought to be individualized and combined with the gestational age. If the diagnosis was made in the first two trimesters of pregnancy, totally endoscopic minimally invasive cardiac surgery during pregnancy would be an optimal choice. The patients can benefit from the multidisciplinary team work.

BackgroundProstate cancer (PCa) is the most common non-cutaneous malignancy in men globally. Sappan lignum, which exists in the heartwood of Caesalpinia sappan L., has antitumor effects; however, its exact mechanism of action remains unclear. This study elucidated the underlying mechanisms of Sappan lignum in PCa through network pharmacology approaches and molecular docking techniques. Moreover, the therapeutic effects of Sappan lignum on PCa were verified through in vitro experiments.MethodsThe constituent ingredients of Sappan lignum were retrieved from the HERB database. Active plant-derived compounds of Sappan lignum were screened based on gastrointestinal absorption and gastric drug properties. Disease targets for PCa were screened using unpaired and paired case datasets from the Gene Expression Omnibus. Intersection targets were used for gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Core targets were identified through topological analysis parameters and their clinical relevance was validated through The Cancer Genome Atlas database. The affinity between the phytochemicals of Sappan lignum and core proteins was verified using the molecular docking technique. Validation experiments confirmed the significant potential of Sappan lignum in treating PCa.ResultsTwenty-one plant-derived compounds of Sappan lignum and 821 differentially expressed genes associated with PCa were collected. Among 32 intersection targets, 8 were screened according to topological parameters. KEGG analysis indicated that the antitumor effects of Sappan lignum on PCa were primarily associated with the p53 pathway. The molecular docking technique demonstrated a strong affinity between 3-deoxysappanchalcone (3-DSC) and core proteins, particularly cyclin B1 (CCNB1). CCNB1 expression correlated with clinicopathological features in patients with PCa. Experimental results revealed that 3-DSC exhibited anti-proliferative, anti-migratory, and pro-apoptotic effects on 22RV1 and DU145 cells while also causing G2/M phase cell cycle arrest, potentially through modulating the p53/p21/CDC2/CCNB1 pathway.ConclusionThis research highlights the promising therapeutic potential of Sappan lignum in treating PCa, with a particular focus on targeting the p53 pathway.

Abstract Scanning electron microscopy (SEM) is a crucial tool for analyzing submicron-scale structures. However, the attainment of high-quality SEM images is contingent upon the high conductivity of the material due to constraints imposed by its imaging principles. For weakly conductive materials or structures induced by intrinsic properties or organic doping, the SEM imaging quality is significantly compromised, thereby impeding the accuracy of subsequent structure-related analyses. Moreover, the unavailability of paired high–low quality images in this context renders the supervised-based image processing methods ineffective in addressing this challenge. Here, an unsupervised method based on Cycle-consistent Generative Adversarial Network (CycleGAN) was proposed to enhance the quality of SEM images for weakly conductive samples. The unsupervised model can perform end-to-end learning using unpaired blurred and clear SEM images from weakly and well-conductive samples, respectively. To address the requirements of material structure analysis, an edge loss function was further introduced to recover finer details in the network-generated images. Various quantitative evaluations substantiate the efficacy of the proposed method in SEM image quality improvement with better performance than the traditional methods. Our framework broadens the application of artificial intelligence in materials analysis, holding significant implications in fields such as materials science and image restoration.

We used field experimental data to evaluate the ability of the agricultural production system model (APSIM) to simulate soil P availability, maize biomass and grain yield in response to P fertilizer applications on a fluvo-aquic soil in the North China Plain. Crop and soil data from a 2-year experiment with three P fertilizer application rates (0, 75 and 300 kg P2O5 ha−1) were used to calibrate the model. Sensitivity analysis was carried out to investigate the influence of APSIM SoilP parameters on the simulated P availability in soil and maize growth. Crop and soil P parameters were then derived by matching or relating the simulation results to observed crop biomass, yield, P uptake and Olsen-P in soil. The re-parameterized model was further validated against 2 years of independent data at the same sites. The re-parameterized model enabled good simulation of the maize leaf area index (LAI), biomass, grain yield, P uptake, and grain P content in response to different levels of P additions against both the calibration and validation datasets. Our results showed that APSIM needs to be re-parameterized for simulation of maize LAI dynamics through modification of leaf size curve and a reduction in the rate of leaf senescence for modern stay-green maize cultivars in China. The P concentration limits (maximum and minimum P concentrations in organs) at different stages also need to be adjusted. Our results further showed a curvilinear relationship between the measured Olsen-P concentration and simulated labile P content, which could facilitate the initialization of APSIM P pools in the NCP with Olsen-P measurements in future studies. It remains difficult to parameterize the APSIM SoilP module due to the conceptual nature of the pools and simplified conceptualization of key P transformation processes. A fundamental understanding still needs to be developed for modelling and predicting the fate of applied P fertilizers in soils with contrasting physical and chemical characteristics.

Intermetallic nanoparticles (i‐NPs) have received considerable attention as high‐performance catalysts for diverse catalytic applications. However, high‐entropy i‐NPs have been rarely reported due to particle growth and phase separation in the multicomponent alloy. In this study, for the first time, an integrated approach of template and structure transformation is introduced to synthesize a series of sub ≈ 5 nm multicomponent i‐NPs with varying compositions. Firstly, ultrathin PtCu nanosheets (NSs) are directly converted into bimetallic PtCu i‐NPs. Furthermore, these PtCu NSs are also used as templates for epitaxial growth of the other metals, followed by annealing to obtain high‐loading, novel compositions and uniform i‐NPs with ternary, quaternary, and quinary compositions, including high‐entropy i‐NPs. Interestingly, L10 intermetallic phases are obtained when Fe is introduced. As a proof‐of‐concept application, these high‐entropy i‐NPs showed superior catalytic performance for the hydrogen evolution reaction , which can be attributed to the negatively shifted d‐band center of Pt, thereby resulting in reduced H* adsorption energy at Pt sites as supported by density functional theory calculations. Overall, this research presents a promising method for the development of i‐NPs with various compositions.

The precipitation behavior of Cu-bearing ultra-low carbon steel after step quenching and tempering at 923 K for 0.5–2.5 h was investigated. The size, quantity, and characteristic distribution of nano-precipitates were analyzed using transmission electron microscopy, and the microstructure of B2 (an ordered structure belonging to the body-centered cubic structure), 9R (a special triclinic lattice that has characteristics of rhombohedral structure), 3R (a special triclinic lattice like 9R), and FCT (face-centered tetragonal lattices) were accurately determined. The relationship between nano-precipitates and mechanical properties under different heat treatment processes was obtained, revealing that nano-precipitates effectively enhanced the yield strength of Cu-bearing ultra-low carbon steel. There were two forms of crystal structure evolution sequence of precipitation: B2→multi twin 9R→detwined 9R→FCT→FCC and B2→multi-twin 9R→detwinned 9R→3R→FCT→FCC. The morphology of the precipitated particles during the growth process changed from spherical to ellipsoidal and finally to rod-shaped. It was proven that a stable 3R structure existed due to the coexistence of 9R, 3R, and FCT structures in the same precipitate particle.

Metal-organic frameworks (MOFs) have been widely considered as ideal platforms for the preparation of biomimetic catalysts, but it remains challenging to fabricate MOF-based enzyme-like catalysts with optimal activity. Here, we leverage the inherent flexibility of MOFs and propose a novel trans-functionalization strategy to construct a carbonic anhydrase (CA) mimic by the structural transformation from ZIF-L to ZIF-8. Theoretical and experimental results reveal that during the structural transformation, the hydroxyl group will preferentially coordinate with the interlayer Zn clusters to form the CA-like active center Zn-N3-OH. Therefore, more accessible active centers are generated on the as-prepared ZIF-8-OH, resulting in substantially enhanced catalytic activity in the hydrolysis of para-nitrophenyl acetate.

Fiber sensors, with their high sensitivity and flexibility, have contributed to the integration of wearable technologies into everyday clothing, enabling both comfortability and efficient data collection. Meanwhile, the rapid advancements in machine learning have substantially boosted the capability of wearable technology to process intricate information collected from the human body and environment. This work offers a comprehensive review of wearable devices that utilize both fiber sensors and machine learning. Various fiber sensors are discussed based on their working principles and dimensions, and an overview of the machine learning algorithms that have been applied with these fiber sensors is presented. Additionally, the advantages, limitations, and concerns of different approaches are highlighted, paving the way for the future development of intelligent wearable devices and systems.

The intermittent and random nature of wind brings great challenges to the accurate prediction of wind power; a single model is insufficient to meet the requirements of ultra-short-term wind power prediction. Although ensemble empirical mode decomposition (EEMD) can be used to extract the time series features of the original wind power data, the number of its modes will increase with the complexity of the original data. Too many modes are unnecessary, making the prediction model constructed based on the sub-models too complex. An entropy ensemble empirical mode decomposition (eEEMD) method based on information entropy is proposed in this work. Fewer components with significant feature differences are obtained using information entropy to reconstruct sub-sequences. The long short-term memory (LSTM) model is suitable for prediction after the decomposition of time series. All the modes are trained with the same deep learning framework LSTM. In view of the different features of each mode, models should be trained differentially for each mode; a rule is designed to determine the training error of each mode according to its average value. In this way, the model prediction accuracy and efficiency can make better tradeoffs. The predictions of different modes are reconstructed to obtain the final prediction results. The test results from a wind power unit show that the proposed eEEMD-LSTM has higher prediction accuracy compared with single LSTM and EEMD-LSTM, and the results based on Bayesian ridge regression (BR) and support vector regression (SVR) are the same; eEEMD-LSTM exhibits better performance.

Warming radiative forced effect (RFE) derived from atmospheric amines attracts lots of attentions because of their contributions to brown carbons. Herein, the enhanced influence of amines (methyl-, dimethyl-, and trimethylamine) on cooling RFE of mineral particles is first confirmed at visible wavelengths. Present results state heterogeneous uptake and oxidation reactions of atmospheric amines are feasible on mineral particle at clean/polluted conditions, which are proofed by related thermodynamics and kinetics data obtained using combined classical molecular dynamics and density function theory methods. Based on mineral particles, simple forcing efficiency (SFE) results explain that amine uptake induces at least 11.8% - 29.5% enhancement on cooling RFE of amine-mineral particles at visible wavelengths. After amines' heterogeneous oxidation, oxidized amine-mineral particles' cooling RFE are furthermore enhanced due to increased oxygen contents. Moreover, oxidized trimethylamine-mineral particle under clean condition shows 45.6% - 47.1% SFE increment at 400-600 nm, which is at least 13.5% higher than that of itself under polluted condition, due to high-oxygen-content product formation through trimethylamine autoxidation. Our results suggest cooling RFE derived from atmospheric amines can be equally important to their warming RFE on atmosphere. It is necessary to update heterogeneous oxidation mechanism and kinetics data of amines in atmospheric model in order to accurately evaluate the whole RFE caused by amines on atmosphere. [ABSTRACT FROM AUTHOR]