Biostimulant-driven enhancement of bioactive compounds in salt-stressed sweet basil (Ocimum basilicum L.)

Basil (Ocimum basilicum L.) is a medicinal and aromatic plant renowned for its bioactive compounds, including phenolics, flavonoids, and essential oils. This study aimed to assess the effects of NaCl-induced salt stress on basil and explore comprehensively for the first time the potential mitigating impacts of various biostimulants. A controlled pot experiment was conducted with NaCl concentrations of 0, 50, and 100 mmol, alongside treatments of Bacillus megaterium (BM), Frateuria aurantia (FA), ascorbic acid (AA), and gibberellic acid (GA). The results showed that BM at 50 mmol NaCl significantly enhanced total antioxidant activity (150.40 mg TE g⁻¹) and total phenolic content (242.17 mg GA 100 g⁻¹). GA at non-saline conditions resulted in the highest carotenoid content (3.42 µg g⁻¹ FW), while BM under non-saline conditions achieved the highest flavonoid content (93.33 mg QE 100 g⁻¹). BM and AA treatments significantly increased salicylic and rosmarinic acids, underscoring the biostimulants' role in enhancing basil's biochemical resilience. Furthermore, biostimulants positively influenced morphological parameters such as plant height, root length, herbal weight, and root weight, with GA and BM treatments exhibiting superior performances under varying salt conditions. The correlation analysis indicated complex interactions among the bioactive compounds, providing insights into their potential roles in basil's biochemical response to saline conditions. These findings underscored the potential of biostimulants to mitigate the adverse effects of salt stress, thereby enhancing basil's resilience and productivity in saline environments. © 2025 SAA

Estimation of soil liquefaction using artificial intelligence techniques: an extended comparison between machine and deep learning approaches

This study investigates the effectiveness of various deep learning (DL) algorithms in predicting soil liquefaction susceptibility. We explore a spectrum of algorithms, including machine learning models such as Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Logistic Regression (LR), alongside DL architectures like Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Bidirectional LSTMs (BiLSTMs), and Gated Recurrent Units (GRUs). The performance of these algorithms is assessed using comprehensive metrics, including accuracy, precision, recall, F1-score, receiver operating characteristic (ROC) curve analysis, and area under the curve (AUC). Cross-entropy loss is employed as the loss function during model training to optimize the differentiation between liquefiable and non-liquefiable soil samples. Our findings reveal that the GRU model achieved the highest overall accuracy of 0.98, followed by the BiLSTM model with an accuracy of 0.95. Notably, the BiLSTM model excelled in precision for class 1, attaining a score of 0.96 on the test dataset. These results underscore the potential of both GRU and BiLSTM models in predicting soil liquefaction susceptibility, with the BiLSTM model’s simpler architecture proving particularly effective in certain metrics and datasets. The findings of this study could assist practitioners in seismic risk assessment by providing more accurate and reliable tools for evaluating soil liquefaction potential, thereby enhancing mitigation strategies and informing decision-making in earthquake-prone areas. This study contributes to developing robust tools for liquefaction hazard assessment, ultimately supporting improved seismic risk mitigation. © The Author(s) 2025

Synthesis, microstructure and radiation protection properties of B2O3–ZnO–K2CO3–PbO ceramic glass system: experimental and theoretical assessment

Ceramic glass is a versatile solid-state material engineered to blend the transparency of glass and the thermal stability of ceramics. This fusion has applications in various technological fields with major considerations like radiation protection, durability, heat resistance, and transparency. İn this study, three different B2O3 ceramic glasses comprising varying amounts of ZnO–K2CO3–PbO (BP ceramic glass) were produced, characterized and scanned with electron microscopy. Energy dispersive spectroscopy (EDS) was deployed to find the elemental composition of prepared samples. The radiation protection parameters such as Mass attenuation coefficient (MAC), Linear attenuation coefficient (LAC), Mean free path (MFP), Effective electron density (Neff), Tenth value layer (TVL), Half Value layer (HVL), Effective atomic number (Zeff), Exposure buildup factor (EBF), Equivalent atomic number (Zeq) and Energy absorption build-up factor (EABF) of B2O3–ZnO–K2CO3–PbO (BP) glass–ceramic systems were investigated by using Phy-X/PSD software. The result shows that the micropores increase with an increase in PbO. The density of BP1, BP2, and BP3 were 2.57, 2.36, and 2.19, respectively. The MAC of BP ceramic glass varies as BP1 > BP2 > BP3, implying that BP1 with higher density and greater PbO content is more efficient in radiation protection mostly at lower photon energy. The findings of this research present credible insights applicable to high-performance ceramic glass design for radiation protection in radiotherapy, nuclear power plants, radioactive waste confinement and other related applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025

Genome-wide screening of mitogen-activated protein kinase (MAPK) gene family and expression profile under heavy metal stress in Solanum lycopersicum

MAPKs are one of the essential signal transduction complexes which are responsible for the perception of abiotic stress and for the producing of related transcripts for responding to abiotic stress. For systematical analyzes of the mitogen-activated protein (MAP) kinase gene families and their expression profiles in Solanum lycopersicum L. exposed to diverse heavy metal stresses, 17 SlMAPK genes were studied in comparison with their 159 orthologs from various plant species. The result of phylogenetic analysis revealed that SlMAPKs were divided into four different subgroups (A, B, C, and D) based on their nucleic acid and protein sequence alignments. SlMAPKs including A, B and C group had lower molecular weights and more hydrophobic structures than D group SlMAPKs, while possible extra phosphorylation sites predicted in D-group SLMAPKs. 24 cis regulating elements such as Box 4, TATA-box, ABRE and CAAT-box were detected in their upstream parts of DNA sequences. Also, it was determined that SlMAPKs show interactions with important proteins such as Guanine nucleotide-binding protein beta subunit, heterotrimeric G-protein, protein phosphatase 2C and HY5. The results from our gene expression analyzes, significant increases were found in the expressions of the selected SLMAPK gene with applications of a range of increasing heavy metal concentrations (e.g., by the application of the 400 mM Ni + Pb exposure, a 16-fold increase in the expression of SlMAPK gene was noted). Overall, SlMAPK genes and proteins known were re-evaluated, and the SlMAPKs interactions with some other important proteins were observed. Also, some predictions about the extra phosphorylation sites of SlMAPKs having effects on their functions were done. In addition, the expression levels of SlMAPK genes were monitored under different levels of heavy metal stress exposures. © The Author(s), under exclusive licence to Springer Nature B.V. 2025

Current status, opportunities, and challenges of exosomes in diagnosis and treatment of osteoarthritis

Osteoarthritis (OA) is a progressive joint disease that is a frequent reason for pain and physical dysfunction in adults, with enormous social and economic burden. Although ongoing scientific efforts in recent years have made considerable progress towards understanding of the disease's molecular mechanism, the pathogenesis of OA is still not fully known, and its clinical challenge remains. Thus, elucidating molecular events underlying the initiation and progression of OA is crucial for developing novel diagnostic and therapeutic approaches that could facilitate effective clinical management of the illness. Exosomes, extracellular vesicles containing various cellular components with approximately a diameter of 100 nm, act as essential mediators in physiological and pathological processes by modulating cell-to-cell communications. Exosomes have crucial roles in biological events such as intercellular communication, regulation of gene expression, apoptosis, inflammation, immunity, maturation and differentiation due to their inner composition, which includes nucleic acids, proteins, and lipids. We focus on the roles of exosomes in OA pathogenesis and discuss how they might be used in clinical practice for OA diagnosis and treatment. Our paper not only provides a comprehensive review of exosomes in OA but also contributes to the development efforts of diagnostic and therapeutic tools for OA. © 2025 Elsevier Inc

Fabrication of Free-Standing Hybrid Composite High Capacity Cathodes for Li−S Batteries with Nickel Oxide Polysulfide Adsorbent

This study focuses on enhancing lithium-sulfur (Li−S) battery performance by using nickel(II) oxide (NiO), as polysulfide adsorbent to mitigate the shuttle effect. Polysulfides have been shown to effectively adsorb onto the hydrophilic surfaces of polar metal oxides and thus suppress this effect. In this work, a NiO – reduced Graphene Oxide/Sulfur (NiO-rGO/S) hybrid composite paper was developed for use as a binder-free, flexible cathode. The characterization of the composite films was done through Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, thermogravimetric analysis (TG), field emission gun scanning electron microscopy (FEG-SEM), energy dispersive x-ray spectroscopy (EDS) and x-ray diffraction (XRD). To test adsorption of polysulfides by NiO, ultraviolet-visible (UV-Vis) spectroscopy was applied. Electrochemical performance tests of CR2032 cells were also conducted by cyclic voltammetry (CV), charge-discharge tests, electrochemical impedance spectroscopy (EIS). The NiO-rGO/S cathode, particularly the one containing 2 % NiO, exhibited remarkable performance. It delivered an initial discharge capacity of 1230 mAh g−1, maintaining 1029 mAh g−1 after 300 cycles, with a high capacity retention of 83.1 %. This suggests that the NiO-rGO/S hybrid composite is a promising candidate for improving the efficiency and lifespan of Li−S batteries. © 2024 The Authors. ChemElectroChem published by Wiley-VCH GmbH

Development of free-standing h-BN/rGO/S composite cathodes for Li-S batteries: h-BN content and temperature effect

This study aims to improve the properties of Li-S batteries and overcome their disadvantages by utilizing hexagonal boron nitride (h-BN) nanocomposites with unique features that provide advantages in their applications. For this purpose, composite films were produced using h-BN with superior mechanical and chemical properties along with reduced graphene oxide (rGO) possessing high electrical conductivity. Free-standing and flexible h-BN/rGO/S composite paper electrodes containing different weight ratios of functionalized h-BN were prepared. The obtained binder-free composite papers were employed as cathodes in Li-S batteries and applied at different temperatures. In this study, the structural, morphological, and thermal analyses of the composite cathodes were conducted using X-ray diffraction (XRD), field emission gun scanning electron microscopy (FEG-SEM), energy dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM) and thermogravimetric analysis (TGA). The optical measurements were carried out by Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy and ultraviolet–visible spectroscopy (UV–Vis). After assembling CR2032 button cells, electrochemical performance tests were applied to assess the charge–discharge capacities. A high discharge capacity of 427 mAh g−1 was achieved after 1000 cycles. As a result, h-BN/rGO-based composites have been developed as environmentally friendly and metal-free materials, further enhancing the electrochemical performance and electron transport of lithium batteries. © 2025 Elsevier B.V

Corrigendum to “Physical, chemical and radiation shielding properties of metakaolin-based geopolymers containing borosilicate waste glass” [Radiat. Phys. Chem. 224 (2024) 112075] (Radiation Physics and Chemistry (2024) 224, (S0969806X2400567X), (10.1016/j.radphyschem.2024.112075))

In the above-mentioned article, the authors regret that the Funding section should be only for Jouf University as below. This work was funded by the Deanship of Scientific Research at Jouf University under grant No. (DSR-2021-03-03132). The article is now correct online. The authors apologise for inconvenience caused. © 2024 The Author(s

Assessment of pollution in Alibeykoy Dam Lake (Istanbul, Türkiye) and its influent streams: Phytoplankton composition and heavy metal accumulation

In this study, the pollution levels of Alibeykoy Dam Lake were assessed by examining phytoplankton distribution, physicochemical parameters, nutrient content, and heavy metal concentrations. Alibeykoy Dam is a critical drinking water source for the Istanbul metropolitan area. Water samples were collected from the lake and six influent streams (Cebeci, Pirincci, Sidan, Bolluca, Gulgen, and Kocaman) in January, February, May, and September of 2021. A total of 36 taxa from seven divisions were identified, including Bacillariophyta (14), Charophyta (2), Chlorophyta (9), Cryptophyta (1), Cyanobacteria (3), Euglenozoa (4), and Miozoa (3). Diatoms were found to be the dominant group in terms of species richness and abundance. The dominant species recorded in each site were as follows: Microcystis aeruginosa in Alibeykoy Dam and Sidan Creek, Cyclotella ocellata in Cebeci and Gulgen Creeks, Scenedesmus sp. in Pirincci Creek, Navicula cryptocephala in Bolluca Creek, and Sphaerocystis planctonica in Kocaman Creek. Mesotrophic and eutrophic phytoplankton species suggested that the lake is nearing eutrophic conditions. This conclusion was further supported by high concentrations of heavy metals and nutrients detected in the water samples. This research is significant because it provides a comprehensive understanding of the ecological status of Alibeykoy Dam Lake, a critical resource for drinking water in Istanbul. The study highlights potential risks associated with eutrophication and heavy metal accumulation by identifying pollution levels and dominant species. These findings are vital for implementing effective water resource management strategies, ensuring the lake's sustainability, and protecting public health. Practitioner Points: The pollution rate of Alibeykoy Dam Lake was determined. The presence of mesotrophic and eutrophic species of phytoplankton indicated the lake's trophic structure. The measurements were done to estimate the lake's heavy metal and nutrient contents. © 2025 Water Environment Federation

Estimating the crashworthiness performances of crushboxes using artificial neural network; [Einschätzung der Crashsicherheit von Schockabsorbersystemen mittels künstlicher neuronaler Netzwerke]

Studies on the development of energy absorbing systems that minimize vehicle chassis damage in traffic accidents are increasing day by day. Many designs have been made in the studies on crushboxes used to absorb the energy released in the event of an accident. These design works are quite costly and take a long time. In this study, to design crushboxes faster and more economically was estimated using artificial neural network. The input layer of the artificial neural network model consists of three different materials, thicknesses (between 0.8 and 2.2 mm) and three different initial speeds. In the artificial neural network model, 42 different models were created by changing the different training functions (training, trainlm and trainrp), transfer functions (tansig and logsig) and the number of neurons in the hidden layer (between 9 and 33). R2 and root mean square error (RMSE) methods were used to evaluate the efficiency of artificial neural network models. The training function was found to be highly accurate (R2: 0.99999 and root mean square error: 0.314727E-05) when the training function was “trainlm” and the number of neurons in the hidden layer was 33. The training and testing results of the artificial neural network model show that artificial neural networks can be used to estimate the specific energy absorption/energy/peak crush force value of crushboxes. © 2024 Wiley-VCH GmbH