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Purpose: Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete. Design/methodology/approach: An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R2), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters. Findings: The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance. Originality/value: This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice. [ABSTRACT FROM AUTHOR]

Introduction: In the context of climate variability, rapid and accurate estimation of winter wheat yield is essential for agricultural policymaking and food security. With advancements in remote sensing technology and deep learning, methods utilizing remotely sensed data are increasingly being employed for large-scale crop growth monitoring and yield estimation. Methods: Solar-induced chlorophyll fluorescence (SIF) is a new remote sensing metric that is closely linked to crop photosynthesis and has been applied to crop growth and drought monitoring. However, its effectiveness for yield estimation under various data fusion conditions has not been thoroughly explored. This study developed a deep learning model named BO-CNN-BiLSTM (BCBL), combining the feature extraction capabilities of a convolutional neural network (1DCNN) with the time-series memory advantages of a bidirectional long short-term memory network (BiLSTM). The Bayesian Optimization (BOM) method was employed to determine the optimal hyperparameters for model parameter optimization. Traditional remote sensing variables (TS), such as the Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI), were fused with the SIF and climate data to estimate the winter wheat yields in Henan Province, exploring the SIF's estimation capabilities using various datasets. Results and Discussion: The results demonstrated that the BCBL model, integrating TS, climate, and SIF data, outperformed other models (e.g., LSTM, Transformer, RF, and XGBoost) in the estimation accuracy, with R²=0.81, RMSE=616.99 kg/ha, and MRE=7.14%. Stepwise sensitivity analysis revealed that the BCBL model reliably identified the critical stage of winter wheat yield formation (early March to early May) and achieved high yield estimation accuracy approximately 25 d before harvest. Furthermore, the BCBL model exhibited strong stability and generalization across different climatic conditions. Conclusion: Thus, the BCBL model combined with SIF data can offer reliable winter wheat yield estimates, hold significant potential for application, and provide valuable insights for agricultural policymaking and field management. [ABSTRACT FROM AUTHOR]

Cementum, a bone-like tissue, is an essential component of periodontium, and periodontitis can lead to degenerative changes in the cementum, eventually resulting in tooth loss. The therapeutic strategy for advanced periodontitis is to achieve periodontal regeneration, of which cementum regeneration is a key criterion. Cementoblasts are responsible for cementogenesis, and their mineralization counts in cementum regeneration. However, research is still limited. Thus, novel treatment targets are required. The expression levels of lysine (K)–specific demethylase 6B (KDM6B), fatty acid oxidation (FAO), and cementogenic markers were detected by quantitative polymerase chain reaction, Western blot, immunofluorescence, and immunohistochemical assays. FAO levels were analyzed by assay kit. In vivo, injection of GSK-J4 into mice detected the influence of KDM6B on cementum formation. Chromatin immunoprecipitation sequencing, transcriptomic RNA sequencing, subsequent chromatin immunoprecipitation–quantitative polymerase chain reaction and overexpression of HADHA (hydroxyacyl-coA dehydrogenase trifunctional multienzyme complex subunit alpha) elucidated the KDM6B- Hadha axis. Global lactylation was detected by Western blot. Lactylation proteomics clarified the modified sites of HADHA. Mutating these sites and applying coimmunoprecipitation confirmed their significance. Knockdown of Kdm6b was utilized to assess its regulation on the lactylation of HADHA, FAO, and mineralization levels. FAO and KDM6B expression was elevated during cementoblast mineralization. KDM6B targeted Hadha and activated its transcription, thereby increasing FAO levels and promoting mineralization. Lactylation occurred in the process of mineralization, and KDM6B could regulate the lactylation of HADHA to promote FAO and mineralization. Overexpression of Hadha and the addition of lactate sodium could rescue the inhibition of mineralization by knockdown of Kdm6b. In summary, during cementoblast mineralization, KDM6B regulates HADHA by mediating histone demethylation and lactylation, thereby upregulating FAO and thus promoting mineralization. [ABSTRACT FROM AUTHOR]

Background: Enshi Yulu tea (ESYL) is the most representative of steamed green tea in China, but its aroma formation in processing is unclear. Thus, the ESYL volatiles during the whole industrial processing were investigated using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry., Results: A total of 134 volatiles were identified. Among these, 31 differential volatiles [P < 0.05 and variable importance in projection (VIP) > 1] and 25 key volatiles [relative odor activity value (rOAV) and/or the ratio of each rOAV to the maximum rOAV (ROAV) > 1.0] were screened out, wherein β-ionone and nonanal were the most key odorants. Besides, the sensory evaluation combined with multivariate statistical analysis of volatiles pinpointed spreading, fixation, first drying, and second drying as the key processing steps that have a pronounced influence on the aroma quality of ESYL. Furthermore, the oxidative degradation of unsaturated fatty acids, synthesis of monoterpenes, and degradation of carotenoids were the main metabolic pathway for the formation of key odorants., Conclusion: The study provides comprehensive insights into the volatile characteristics during the industrial processing of ESYL and promote our understanding of the aroma formation in steamed green teas. © 2024 Society of Chemical Industry., (© 2024 Society of Chemical Industry.)

Key Message: Overexpression of general transcription factor OsTFIIB5 in rice affects seedling growth, plant height, flowering time, panicle architecture, and seed protein/starch levels and involves modulation of expression of associated genes. TFIIB, a key general transcription factor (GTF), plays a critical role in pre-initiation complex (PIC) formation and facilitates RNA polymerase II-mediated transcription. In humans and yeast, TFIIB is encoded by a single gene; however, in plants it is encoded by a multigene family whose products may perform specialized transcriptional functions. The role of plant TFIIBs, particularly in monocots, remains largely unexplored. This study presents the first functional characterization of the rice TFIIB gene, OsTFIIB5 (LOC&#95;Os09g36440), during development. Expression profiling of OsTFIIB5 revealed differential patterns across various developmental stages, with pronounced transcript accumulation during seed development. Overexpression of OsTFIIB5 impacted multiple stages of plant growth and development, leading to phenotypic changes such as altered seedling growth, reduced plant height, early heading, altered panicle architecture, decreased yield, and changes in seed storage substances. Notably, there were no effects on seed germination, pollen development, and grain size. Reduction in shoot length and plant height was linked to altered expression of genes involved in gibberellin (GA) biosynthesis, signalling, and deactivation. Overexpression of OsTFIIB5 enhanced the expression of genes involved in the photoperiodic flowering pathway, resulting in early panicle emergence. Higher expression levels of OsTFIIB5 also induced the accumulation of seed storage proteins (SSPs), while reducing starch content and altering the proportions of amylose and amylopectin in seeds. These findings suggest that OsTFIIB5 functions as a transcriptional regulator, governing multiple aspects of rice growth and development., Competing Interests: Declarations. Conflict of interest: The authors declare no conflict of interest., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As great potential recycling strategy, the direct regeneration of spent LiCoO 2 (LCO) is beneficial for lowering environmental pollutions and promoting global sustainability. However, owing to the using of binder and electrolyte, some fluorine impurities would be remained into spent materials. Considering the doping behaviors of F-elements, their suitable content introducing would facilitate the energy-storage abilities of regenerated LCO. Herein, through the tailored introduction of F-elements, spent LCO are successfully regenerated with physical-chemical evolutions. Benefitting from the existed oxygen vacancies, the diffusion energy-barrier of F-elements is reduced from 1.73 eV to 0.61 eV, facilitating the establishment of gradient F-doped subsurface, along with the formation of rigid CoO 5 F. Meanwhile, excess F-elements (1 wt %, as a threshold) lead to the formation of LiF passivation layer on the surface. Thus, the as-optimized sample displays a considerable capacity of 154.4 mAh g -1 even at 5.0 C, with retention rate (88.3 %) in 3.0-4.5 V. Supported by detailed electrochemical and kinetic analysis, the structural advantages are confirmed to boost the improved redox activity of Co-ions and the alleviating of irreversible oxygen-release. Give this, the work is anticipated to reveal the evolutions of regenerated LCO with the introduced F-elements, whilst providing the practical regeneration strategies toward excellent high-voltage properties., (© 2024 Wiley-VCH GmbH.)

Aiming at the further extension of the application scope of traditional molecular muscles, a novel bispyrene-functionalized chiral molecular [c2]daisy chain was designed and synthesized. Taking advantage of the unique dimeric interlocked structure of molecular [c2]daisy chain, the resultant chiral molecular muscle emits strong circularly polarized luminescence (CPL) attributed to the pyrene excimer with a high dissymmetry factor (g lum ) value of 0.010. More importantly, along with the solvent- or anion- induced motions of the chiral molecular muscle, the precise regulation of the pyrene stacking within its skeleton results in the switching towards either "inversed" state with sign inversion and larger g lum values or "down" state with maintained handedness and smaller g lum values, making it a novel multistate CPL switch. As the first example of chiral molecular muscle-based CPL switch, this proof-of-concept study not only successfully widens the application scopes of molecular muscles, but also provides a promising platform for the construction of novel smart chiral luminescent materials for practical applications., (© 2024 Wiley-VCH GmbH.)

Per- and polyfluoroalkyl substances (PFASs), comprising over 9,000 persistent synthetic organic contaminants, are extensively found in the environment and pose significant risks to both human and ecological health. Among the strategies for addressing PFAS contamination, adsorption processes have proven to be cost-effective. Traditional sorbents such as ion-exchange resins and activated carbon have been found to exhibit low adsorption capacities and slow equilibration times. Recent innovations in porous materials, including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), and porous organic polymers (POPs), however, offer significant improvements in the efficiency of PFAS adsorption. This review thoroughly examines the latest advancements in these materials, analyzing their mechanisms of adsorption, and concludes by suggesting directions for future research that could further enhance their effectiveness in PFAS management., (© 2024 Wiley-VCH GmbH.)

Primary squamous cell carcinoma of the liver (PSCCL) is a rare intrahepatic primary tumor. Due to a lack of distinctive clinical presentations and radiological features, early diagnosis is challenging. The present study, describes a patient who initially presented with symptoms indicative of cholecystitis but was misdiagnosed with cholangiocarcinoma. It is hypothesized that fluctuations in carcinoembryonic antigen levels during laboratory tests can significantly aid the diagnosis, treatment and prognosis of tumors. Furthermore, imaging studies are essential for the early diagnosis of PSCCL and the exclusion of metastatic squamous cell carcinoma. [ABSTRACT FROM AUTHOR]