Scientific Reports[JOURNAL]
Sun
200 papers
Evaluation of autophagy in neonatal rat glial cells in an in vitro model of hypoxic-ischemic injury.
Gebala P, Janowska J, Sypecka J
Sci Rep · 2026 Jul · PMID 42401664 · Full text
The autophagy process is crucial for cell functioning, yet it is still understudied in glial cells during neurodevelopment. To address this, cultures of the main glial cell types in the central nervous system (CNS), incl...
The autophagy process is crucial for cell functioning, yet it is still understudied in glial cells during neurodevelopment. To address this, cultures of the main glial cell types in the central nervous system (CNS), including astrocytes, microglia, oligodendrocyte progenitors, and differentiating oligodendrocytes, were created to examine the impact of an in vitro hypoxia-ischemia (HI) model on autophagy. The HI insult was mimicked by applying temporal oxygen-glucose deprivation (OGD). Since neonatal hypoxic-ischemic insults primarily affect the brain's white matter, the study predominantly focused on oligodendrocytes at different stages of maturation: progenitor cells versus cells that express myelin components (e.g. MBP). The results show that the different glial fractions exhibit varying sensitivity to the applied conditions. Maturing oligodendrocytes were found to be more sensitive to OGD conditions than the progenitor fraction. The OGD procedure was proven to impact the expression of autophagy markers, indicating the activity of this process in response to injury. Western blot analysis of oligodendrocyte progenitor cells (OPCs) showed that the autophagy substrate marker p62 increased after six hours, which may suggest transient inhibition and subsequent activation of autophagy. To verify the involvement of autophagy in the differentiation of neonatal oligodendrocytes, the process was modulated using chloroquine (CQ) treatment. CQ is recognised as an inhibitor of autophagic flux because it disrupts lysosomal acidity and prevents the breakdown of autophagosomes. CQ treatment resulted in the accumulation of autophagosomes. The results suggest that abnormalities in the functioning of glial cells, particularly oligodendrocytes, in response to hypoxic-ischaemic (HI)-like conditions might be associated with altered autophagic flux in response to cellular stress. Transient alterations in autophagy were observed within 24 h of limiting oxygen and glucose supply, and these alterations may contribute to subsequent disorders in oligodendrocyte differentiation. This is recognised as one of the major issues in the pathogenesis of neonatal hypoxia-induced damage. Therefore, modulation of autophagy could be a promising therapeutic approach to prevent these adverse changes.
Pose-derived biomechanical feature profiling and proxy pattern classification of basketball player movements.
Gao Y
Sci Rep · 2026 Jul · PMID 42401663 · Full text
Markerless pose estimation provides a practical approach for extracting movement-related variables from sports video without requiring laboratory-based motion-capture systems. However, pose-derived biomechanical analysis...
Markerless pose estimation provides a practical approach for extracting movement-related variables from sports video without requiring laboratory-based motion-capture systems. However, pose-derived biomechanical analysis must be interpreted carefully when datasets do not contain ground-truth action labels or independently validated biomechanical outcomes. This study developed a computational pipeline for pose-derived biomechanical feature profiling of basketball player movements using annotated gameplay pose data from the TrackID3 × 3 dataset. Frame-level keypoint annotations were processed to derive biomechanical variables, including elbow angles, segment distances, asymmetry measures, and trunk orientation. These variables were organized into short temporal sequences using a sliding-window approach, enabling descriptive analysis of player posture, limb coordination, subset-level variability, and sequence-level feature patterns. Rule-based proxy biomechanical groupings were constructed to facilitate exploratory evaluation of pattern separability within the pose-derived feature space. The pipeline generated a structured pose-derived dataset of 37,134 frame-player observations and showed measurable variation in joint alignment, limb symmetry, and trunk orientation across players and recording conditions. Classification results should be interpreted as proxy-label separability rather than validated prediction of basketball actions or performance outcomes. Future work should incorporate action-level annotations and independent biomechanical validation.
Sound is essential for observers to accurately assess unsuccessful conversations.
Nicoras R, Fischer RL, Hadley LV … +2 more , Naylor G, Smeds K
Sci Rep · 2026 Jul · PMID 42401662 · Full text
Perceiving success in group conversations is central to social life, yet little is known about the extent to which the conversation success perceived by conversational partners aligns with that perceived by third-party o...
Perceiving success in group conversations is central to social life, yet little is known about the extent to which the conversation success perceived by conversational partners aligns with that perceived by third-party observers. This study explores how third-party observers perceive conversation success across three sensory conditions (auditory-visual (AV), visual-only (V), and auditory-only (A)) to identify cues of which sensory domain signal perception of success. In two online experiments, older adults (57.1 years (SD = 6.1), N = 160 per experiment) watched and/or heard audio of 2-minute excerpts of previously recorded four-person conversations. Just as the original interlocutors had done themselves, observers provided continuous judgements of conversation success using a slider and an overall success rating after the conversation. Observers judged conversations in AV and V conditions (Experiment 1) and AV and A conditions (Experiment 2). Across both experiments, observers' overall ratings generally aligned with interlocutors' overall success ratings, showing that success can be assessed without active participation. However, for less successful conversations, observers overestimated success when deprived of auditory information (V condition) but not when deprived of visual information (A condition). These findings suggest that auditory cues provide the most critical information for assessing conversation failure, while visual cues alone may mislead observers.
Comprehensive exposure assessment of residents in a former tin mining area in Kanchanaburi, Thailand.
Musikawan S, Kranrod C, Hosoda M … +10 more , Omori Y, Pluemjit T, Aramrun K, Itthipoonthanakorn T, Kritsananuwat R, Poltabtim W, Kheamsiri K, Sola P, Kudo H, Tokonami S
Sci Rep · 2026 Jul · PMID 42401661 · Full text
This study presents a comprehensive multi-pathway exposure assessment of residents in a former tin-mining community in Kanchanaburi Province, Thailand, underlain by granitic bedrock. Indoor and outdoor radon (Rn), thoron...
This study presents a comprehensive multi-pathway exposure assessment of residents in a former tin-mining community in Kanchanaburi Province, Thailand, underlain by granitic bedrock. Indoor and outdoor radon (Rn), thoron (Rn), and their progeny were measured seasonally, along with terrestrial gamma dose rates, radionuclides in foodstuffs, and Rn in drinking water. The annual mean indoor Rn concentration was 19 ± 10 Bq [Formula: see text], well below the global average. In contrast, Rn progeny accounted for 83% of the total inhalation dose (0.9 mSv), identifying Rn as the dominant inhalation dose contributor within the granitic and thorium-rich environmental setting of E-Tong Village. The annual ingestion dose from drinking water was very low (0.03 mSv). Dietary ingestion was the primary internal exposure pathway (1.47 mSv), driven largely by Po in seafood (1.1 mSv). External gamma-emitting radionuclides contributed 0.45 mSv. The total annual effective dose was estimated at 2.8 mSv, consistent with natural background radiation. Comparisons with a control area suggest that the observed dose levels reflected lithological background rather than residual contamination associated with former mining activities. These findings underscore the need to integrate Rn progeny measurements into radiological risk assessments of granitic regions in Southeast Asia.
Nonlinear compression responses reveal limits of elongation-based design in knitted compression sleeves.
Lee O, Lee Y
Sci Rep · 2026 Jul · PMID 42401660 · Full text
Compression garments are commonly designed using elongation-based pattern reduction, but the validity of this approach under controlled static wearing conditions remains insufficiently verified. This study examined wheth...
Compression garments are commonly designed using elongation-based pattern reduction, but the validity of this approach under controlled static wearing conditions remains insufficiently verified. This study examined whether upper-arm sleeves designed from tensile elongation properties produced consistent compression responses during wear. Three knitted PET/PU fabrics with distinct structural characteristics were tested in wale, course, and bias directions, and 27 sleeve conditions were fabricated using single-layer, identical-material double-layer, and hybrid-material double-layer configurations. Clothing pressure, tissue viscoelastic response (frequency), and perceived compression were assessed. Despite the use of the same elongation-based design logic, compression responses varied substantially with fabric directionality and layering configuration. Bias-direction and several double-layer conditions produced excessive compression or non-wearable states. Layered structures showed nonlinear pressure amplification, indicating that compression was not governed by simple additive or linear effects. Although clothing pressure, tissue response, and perceived compression were generally associated, their magnitudes and rankings were not consistently aligned across conditions. These findings indicate that elongation-based pattern reduction alone may not ensure uniform compression in knitted compression sleeves and suggest the need for an integrated design framework that considers fabric anisotropy, layering structure, tissue response, and wearer perception.
Selective state space U net for linear complexity globally coherent high resolution image segmentation.
Alhudhaif A
Sci Rep · 2026 Jul · PMID 42401659 · Full text
Accurate segmentation of high-resolution images requires the simultaneous preservation of fine-grained spatial details and the modeling of long-range contextual dependencies. Conventional convolutional neural networks ef...
Accurate segmentation of high-resolution images requires the simultaneous preservation of fine-grained spatial details and the modeling of long-range contextual dependencies. Conventional convolutional neural networks efficiently capture local structures but are limited by restricted receptive fields, whereas transformer-based architectures provide global context at the cost of quadratic computational complexity. Recent selective state-space models (SSMs), particularly Mamba-based architectures, offer an attractive alternative by enabling global dependency modeling with linear computational complexity. However, existing vision-oriented implementations largely rely on empirical architectural choices, resulting in fragmented design strategies and limited reproducibility. Here, we introduce Selective State-Space U-Net (SSS-U-Net), a unified architectural framework that systematically formalizes the integration of selective state-space dynamics within encoder-decoder segmentation networks. The proposed framework establishes a comprehensive taxonomy of three macro-integration topologies-sequential, parallel, and bottleneck state-space routing-and defines multi-directional spatial scanning mechanisms that preserve two-dimensional structural coherence while leveraging one-dimensional state-space representations. Furthermore, we provide a standardized design protocol that maps continuous-time selective state-space dynamics onto high-resolution visual domains while maintaining strict linear-complexity scaling. The framework is validated across representative biomedical and industrial imaging benchmarks, including Kvasir-SEG for polyp segmentation and MVTec AD for anomaly detection. Experimental evaluation demonstrates strong predictive performance, achieving 94.2% mean Dice score on Kvasir-SEG and 98.6% pixel-level AUROC on MVTec AD, while maintaining substantially lower memory consumption and computational overhead than attention-based alternatives. Ablation analyses further reveal the complementary roles of selective state-space gating, multi-directional scanning, and hybrid CNN-Mamba feature fusion in improving segmentation fidelity and anomaly localization. These findings establish a reproducible architectural blueprint for integrating selective state-space models into dense prediction systems and provide practical design guidelines for scalable high-resolution image analysis across biomedical, industrial, and resource-constrained vision applications.
From polyamine metabolism genes to immunoproteasome subunits: a transcriptome-based screening of candidate biomarkers in Crohn's disease.
Qi H, Ding X, Leng G … +8 more , Zhang M, Luo S, Zhou Y, Yang Y, Yang H, Wang Q, Jin X, Dai L
Sci Rep · 2026 Jul · PMID 42401658 · Full text
This study explored Polyamine metabolism (PM)-related biomarkers and their regulatory processes in Crohn's disease (CD) using three transcriptome datasets (GSE179285, GSE126124, and GSE102133) and 59 PM-related genes (PM...
This study explored Polyamine metabolism (PM)-related biomarkers and their regulatory processes in Crohn's disease (CD) using three transcriptome datasets (GSE179285, GSE126124, and GSE102133) and 59 PM-related genes (PMRGs). Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify candidate genes, resulting in four key candidates: PSMB10, PSMB8, PSMB9, and PSME2, selected from 796 differentially expressed genes (DEGs). Machine learning and expression validation confirmed that PSMB9, PSMB10, and PSME2 were overexpressed in the CD group, with ROC curve analysis revealing AUC values above 0.8 in all three datasets, supporting their potential as biomarkers. Functional enrichment analysis showed their involvement in the degradation of valine, leucine, and isoleucine, and cell adhesion molecules. Immune infiltration analysis, inferred from the same transcriptomic data, showed that the expression levels of these genes were positively correlated with the abundance of 27 immune cell types in CD tissues. Additionally, these biomarkers were linked to other digestive diseases, such as colon disease and proctitis. Notably, CARFILZOMIB demonstrated significant binding to these biomarkers, suggesting a potential mechanistic link that warrants further experimental investigation. This research emphasizes the role of PSMB9, PSMB10, and PSME2 as promising biomarkers for CD and provides a foundation for further exploration of the regulatory mechanisms of PM in CD.
Semantic-guided edge enhancement for graph self-supervised learning in network intrusion detection.
Zhang Y, Hu Y, Zhang B … +1 more , Lu L
Sci Rep · 2026 Jul · PMID 42401657 · Full text
This paper proposes a semantic-guided edge enhancement approach for graph self-supervised learning in network intrusion detection. It aims to address several issues that the existing intrusion detection systems face, suc...
This paper proposes a semantic-guided edge enhancement approach for graph self-supervised learning in network intrusion detection. It aims to address several issues that the existing intrusion detection systems face, such as relying on a large amount of labeled data, struggling to capture complex network topology, and overlooking the internal information of edges. Concretely, to improve the discriminability of the network flow graph, we introduce a new node‑edge‑node attention algorithm for graph enhancement representation. It integrates edge-aware attention and intra-edge feature self-attention collaboratively, thereby assists the model to perceive complex attack behaviors at multiple granular levels effectively. Meanwhile, we devise a semantic-aware contrastive learning framework that collaboratively enhances nodes and edges, which enables view augmentation without corrupting the original graph semantics, forcing the model to learn more robust and discriminative features. Consequently, our method overcomes the scarcity of labeled samples remarkably. In the experiments, seven SOTA methods were contrasted with the proposed one on four public datasets. The results show that the proposed method outperforms existing mainstream models in accuracy, precision, recall, and F1-score, demonstrating its efficient detection performance and strong generalization capability.
Macular degeneration dependent on defense mechanisms conditioned by chemical elements and genetic polymorphism.
Kamiński P, Brodzka S, Baszyński J … +9 more , Paczała R, Stanek E, Rektor K, Grochowalska R, Hromada M, Stuczyński T, Tkaczenko H, Woźniak A, Kurhaluk N
Sci Rep · 2026 Jul · PMID 42401656 · Full text
Macular degeneration MD is a chronic, lifestyle-related eye disease developing in increasingly younger people. The cause is not fully understood, but oxidative stress is among the most critical factors. The subject of ou...
Macular degeneration MD is a chronic, lifestyle-related eye disease developing in increasingly younger people. The cause is not fully understood, but oxidative stress is among the most critical factors. The subject of our research is the wet form of MD. The tested materials were whole blood and plasma from 84 patients with exudative MD and from 127 healthy volunteers, from SW Poland. The concentration of toxic metals (Hg, Cd, Pb, As, Be), macroelements (Ca, Mg, Na, K, P) and microelements (Mn, Fe, Zn, Cu, Se, Mo, Cr, Li, V, Co, Ag, Ba, Ti, Tl, Sr, Al, Ni, Sn, B, Sb) was analyzed (ICP-MS) in the blood to determine environmental exposure. The activity of antioxidant enzymes (superoxide dismutase SOD, catalase CAT, glutathione peroxidase GPx, glutathione reductase GR) was determined to demonstrate the ability to eliminate the effects of reactive oxygen species ROS. The activity of nonenzymatic antioxidant mechanisms (reduced glutathione GSH, bilirubin, uric acid, vitamins A and E) was examined to assess the body's ability to activate defense mechanisms against ROS. The intensity of lipoperoxidation (malondialdehyde, MDA), and the importance of ceruloplasmin CP in patients with exudative MD and their exposure to oxidative stress were determined. The presence of glutathione-S-transferase GST polymorphisms (GSTT1, GSTM1) was examined to determine their role in generating MD. The genetic polymorphism of interleukin-4 IL-4 and vascular endothelial growth factor VEGF-A was analyzed, and it was determined whether there is a genetic burden that can potentially increase the chance of developing MD. The activity of SOD, CAT, GPx, and GR, and the activity of nonenzymatic antioxidants (GSH, bilirubin, uric acid, all-trans retinol, and alpha-tocopherol) were determined using Cayman kits and HPLC chromatography. MDA was determined using Cayman reagents, and CP was determined using Wuhan reagents. In our exudative MD patients, P, Ca, Mn, Fe, Cu, and Zn were most involved in interactions, whereas in the control group, Pb, Ca, Mn, Zn, and Ba were most important. In the analysis of antioxidant parameters, significant differences were found between the studied groups for SOD, CAT, GPx, bilirubin, all-trans retinol, alpha-tocopherol, and uric acid. Also, MDA and CP showed significant differences. In MD patients and healthy individuals, many correlations were found. Significant differences were noted for IL-4 in the frequency of the T allele in MD patients, and for Sr. The frequency distributions of GSTT1 and GSTM1 polymorphisms showed no significant differences between the groups, whereas differences were observed for all-trans retinol. Changes within VEGF-A genotypes showed no significant differences between the studied groups (p > 0.5). Due to the presence of mutagenic substances in the environment, the changed genome plays an important role in MD development. The pathogenic process can be observed by analyzing the effectiveness of enzymatic and nonenzymatic mechanisms. The low diagnostic value of MDA and CP for patients with MD was indicated. The results highlighted the significant role of environmental factors and indicated new directions for research into MD etiology. They identified new parameters to be considered when examining predisposition to this disease (Na, P, Cr, Mn, Ba, MDA, bilirubin, A and E vitamins, SOD, CAT, GPx, IL-4). We compare the aspects we examine holistically, making this the first study of this type. Despite many elements of MD development being known so far, there are still many unanswered questions in this field that will require further analysis, especially regarding K, Pb, As, Hg, Cd, Sr, Al, Ba, V, Fe, mutations in IL-4, GSTM1, and GSTT1.
Serum vitamin D level in children with bronchiolitis.
Aung TSS, Khine MM
Sci Rep · 2026 Jul · PMID 42401655 · Full text
Acute bronchiolitis is the most common lower respiratory tract infection during the first year of life. Vitamin D is an important contributing factor to the increasing incidence and severity of bronchiolitis over the pas...
Acute bronchiolitis is the most common lower respiratory tract infection during the first year of life. Vitamin D is an important contributing factor to the increasing incidence and severity of bronchiolitis over the past three decades. Numerous international studies have suggested that low vitamin D levels are associated with the severity of bronchiolitis. This study aimed to determine serum vitamin D levels in infants hospitalized with acute bronchiolitis in Myanmar. A cross-sectional analytical study was conducted in medical units of Yankin Children's Hospital from August 2022 to July 2023. A total of seventy-five children aged one to twelve months old were included and the Wang clinical severity score was assessed for severity categorization. A total of 75 children, 86% of the study population, were in the one-to-six-month- old age group and only ten children, 13.3%, were in the six-month to one -year-old age group. According to the Wang clinical severity score, severe bronchiolitis was found in 64% of the study population, and non-severe bronchiolitis was detected in 36%. In this study, the mean vitamin D level in the studied population was 44.29 ± 19.55 nmol/L in non-severe bronchiolitis patients and 35.31 ± 15.83 nmol/ L in severe bronchiolitis patients. In the present study, it is found out that 16 children with severe bronchiolitis cases were vitamin D deficient, and only one child with non- severe bronchiolitis cases were vitamin D deficient. Among the 54 vitamin D insufficient children, 59.3% were severe bronchiolitis, 40.7% were non-severe bronchiolitis cases. Among the 48 cases of severe bronchiolitis, none of them had sufficient vitamin D level. A non-parametric Spearman's rank correlation analysis demonstrated a statistically significant, moderate inverse correlation between serum vitamin D levels and the Wang clinical severity score level ([Formula: see text] = -0.41; P < 0.001), establishing that lower vitamin D concentrations strongly correlate with greater clinical severity. It was noted that each one-point increase in the Wang clinical severity score was independently associated with a decrease of 2.95 nmol/L in serum vitamin D concentration (B = -2.95; 95% CI: -4.97 to -0.93; P = 0.005). Neither age (B = -0.21 per month; 95% CI: -1.96 to 1.54; P = 0.814) nor gender (female versus male, B = 2.84; 95% CI: -5.87 to 11.55; P = 0.518) achieved statistical significance in the analysis of the study. In this study, lower serum vitamin D levels were associated with a higher Wang severity score, but the clinical significance is limited by small sample size, lack of confounder control, and absence of seasonality data. Causal inference cannot be made.
Machine learning-based prediction of E. coli infection in hospitalized patients using a no-code analytical framework.
Gharib M, Abdel-Haliem MEF, Nassar NM
Sci Rep · 2026 Jul · PMID 42401654 · Full text
Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs. Among the causative pathogens, Escherichia coli (E. coli) is one of t...
Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs. Among the causative pathogens, Escherichia coli (E. coli) is one of the most frequently isolated microorganisms, particularly in urinary tract infections (UTIs), bloodstream infections, and surgical site infections. Early and accurate prediction of E. coli infection in hospitalized patients remains a significant clinical challenge, yet it has the potential to substantially improve patient outcomes. In addition, identifying patient-related risk factors can support targeted infection control strategies. This study aims to evaluate a no-code machine learning (ML) approach for early prediction of E. coli infection and to identify associated risk factors. ML techniques provide a powerful alternative by enabling the analysis of high-dimensional and heterogeneous datasets, facilitating the discovery of hidden patterns and supporting individualized risk prediction. In this study, a total of 300 clinical samples was collected as a training dataset from hospitalized patients between July 2024 and February 2025 across multiple units of Zagazig University Hospital, Sharkia, Egypt. An independent internal validation dataset of 100 samples was collected during May 2026 from the same hospital, its purpose was to evaluate model generalizability on completely unseen data. Bacterial isolates were identified using standard biochemical methods. Data analysis was performed using the Orange visual programming platform, implementing a modular ML pipeline that integrates data preprocessing, feature handling, model training, and performance evaluation within a no-code environment. The Naive Bayes model, shows potential for predicting E. coli infection in hospitalized patients. The model is intended to predict E. coli infection at the time of specimen collection, before culture results are finalized, depending on clinical data. However, further validation in larger, multi-center prospective cohorts is needed before clinical implementation.
Simplex-anchored regressors for fast global optimization-oriented miniaturization of microwave circuits.
Koziel S, Pietrenko-Dabrowska A
Sci Rep · 2026 Jul · PMID 42401653 · Full text
The small physical size of high-frequency components is an essential prerequisite in an increasing number of applications. While size reduction of microwave circuits can be achieved with a suitable choice of architecture...
The small physical size of high-frequency components is an essential prerequisite in an increasing number of applications. While size reduction of microwave circuits can be achieved with a suitable choice of architecture, ensuring the best available compromise between electrical parameters and size necessitates meticulous adjustment of all system dimensions. Due to the complexity of electrically small structures, parameter adjustment should be executed globally. Nevertheless, it is an expensive endeavor because it entails a large number of system evaluations executed through electromagnetic (EM) simulation. This article introduces an innovative approach to expedited miniaturization of microwave passives, in which the primary goal is miniaturization, while the conditions imposed on performance metrics are treated as constraints. Our framework operates in three stages, including parameter space pre-screening, machine-learning (ML)-driven globalized search, and gradient-based fine-tuning. The first stage involves random sampling aimed at identifying the most promising parameter space region. The ML process launched therein employs simplex-based regression models, the use of which contributes to a competitive computational efficiency. On the other hand, the final tuning improves design quality at a low cost, as it is realized as a local optimization process. The performance of the suggested algorithm is illustrated using two planar devices and demonstrated to be superior to several benchmark methods. The major advantages of our technique include low running costs, equivalent to only a few dozen full-wave analyses, and straightforward implementation.
Valorization of Moringa oleifera pericarp via semi-synthetic sugar-based enone derivatives with anticancer potential: phytochemical isolation, cytotoxic evaluation, and dual EGFR/CAIX targeting.
Majed M, Galala AA, Othman DIA … +2 more , Amer MM, Abouzeid S
Sci Rep · 2026 Jul · PMID 42401652 · Full text
Moringa oleifera pericarp, an underutilized agro-waste, was investigated as a potential source of anticancer agents. In this study, bioassay-guided fractionation of the pericarp extract led to the identification of the e...
Moringa oleifera pericarp, an underutilized agro-waste, was investigated as a potential source of anticancer agents. In this study, bioassay-guided fractionation of the pericarp extract led to the identification of the ethyl acetate fraction as the most active fraction, showing notable antioxidant, antimicrobial, and cytotoxic activities. Subsequent purification afforded three compounds: 4-(α-L-rhamnopyranosyloxy)-benzaldehyde (M), 4-(α-L-rhamnopyranosyl) benzyl alcohol (M), and 4-(hydroxymethyl) phenol-1-O-β-D-glucopyranosyl-(1''→3')-O-α-L-rhamnopyranoside (M). The major constituent, M, was semi-synthetically modified by Steglich esterification with cinnamic acid and crotonic acid to yield two sugar-based enone derivatives, S1 and S2. Structural elucidation was performed using IR, MS, and NMR spectroscopy. The cytotoxic activity of the isolated and semi-synthesized compounds was evaluated against HepG2 and HCT116 cancer cell lines, and selectivity was assessed using normal WI-38 fibroblasts. Among the tested compounds, S2 exhibited the most potent cytotoxicity, with IC values of 5.97 ± 0.19 µM and 11.52 ± 0.37 µM against HepG2 and HCT116 cells, respectively, together with favorable selectivity. In addition, S2 showed strong inhibitory activity against epidermal growth factor receptor tyrosine kinase (EGFR-TK) and carbonic anhydrase IX (CAIX), with ICvalues of 0.40 ± 0.008 µM and 0.27 ± 0.01 µM, respectively. Molecular docking and 100-ns molecular dynamics simulations supported the stable binding of S2 within the active sites of EGFR-TK and CAIX, and MM-GBSA calculations confirmed its favorable binding free energy. Structure-activity relationship analysis suggested that the α,β-unsaturated carbonyl moiety significantly contributed to the observed anticancer activity. These findings highlight M. oleifera pericarp as a promising source of bioactive glycosylated phenolic scaffolds and identify S2 as a potential dual-target anticancer lead for further development.
Continental-scale assessment of spatial food market accessibility in Africa using open geospatial data.
Benassai-Dalmau R, Voukelatou V, Schifanella R … +3 more , Fiandrino S, Paolotti D, Kalimeri K
Sci Rep · 2026 Jul · PMID 42401651 · Full text
Food market accessibility is a critical yet underexplored dimension of food systems, particularly in low- and middle-income countries. In this paper, we present a continent-wide assessment of spatial food market accessib...
Food market accessibility is a critical yet underexplored dimension of food systems, particularly in low- and middle-income countries. In this paper, we present a continent-wide assessment of spatial food market accessibility in Africa, integrating open geospatial data from OpenStreetMap and the World Food Programme. We compare three complementary metrics: travel time to the nearest market, market availability within a 30-minute threshold, and an entropy-based measure of spatial distribution, to quantify accessibility across diverse settings. We find pronounced disparities in accessibility: rural and economically disadvantaged populations face substantially longer travel times and reduced market availability, with some areas requiring several hours of travel. These accessibility patterns align with socioeconomic stratification, as measured by the Relative Wealth Index, and moderately correlate with food insecurity levels, assessed using the Integrated Food Security Phase Classification. Overall, results suggest that access to food markets reflects broader geographic and economic inequalities and plays a relevant role in shaping food security outcomes. Despite limitations related to incomplete and spatially heterogeneous market data coverage, this framework provides a scalable, data-driven approach for identifying relative structural market accessibility gaps, supporting equitable infrastructure planning and spatially informed food security analyses across diverse African contexts.
A color image encryption method based on a CML-ECA neurodynamic chaotic system and TV-BST architecture.
Xie X, Yang S, Ning H … +2 more , Zhou Y, Zhang K
Sci Rep · 2026 Jul · PMID 42401650 · Full text
Existing chaotic image encryption schemes have made progress in improving keystream randomness and dynamic substitution; however, the coupling between the underlying chaotic dynamics, S-box construction, and the overall...
Existing chaotic image encryption schemes have made progress in improving keystream randomness and dynamic substitution; however, the coupling between the underlying chaotic dynamics, S-box construction, and the overall encryption architecture remains limited, especially for high-resolution color images. To address this issue, this paper proposes a color image encryption method that integrates a CML-ECA neurodynamic chaotic system with a TV-BST-based permutation-diffusion framework. Specifically, an ECA-CML composite chaotic model is first established, in which a local-entropy adaptive coupling strategy is combined with Wilson-Cowan excitatory-inhibitory neurodynamic feedback to modulate the Logistic-sine control parameters and lattice states, thereby generating spatiotemporal chaotic sequences with enhanced sensitivity, entropy, and finite-precision robustness. The resulting chaotic flow is then used to construct an initial S-box through a Fisher-Yates shuffle, which is further optimized by a genetic mechanism under joint cryptographic objectives to obtain a high-quality chaotic S-box. At the architecture level, the TV-BST module performs key-dependent row-column permutation for global scrambling, while each color channel undergoes forward and backward chained diffusion together with S-box substitution. Experimental results show that the proposed method produces nearly uniform histograms, low adjacent-pixel correlation, high key sensitivity, and NPCR/UACI values close to their theoretical expectations. In addition, the scheme exhibits robustness against common disturbances such as noise contamination and cropping attacks. These results indicate that the proposed co-designed framework provides an effective and secure solution for color image encryption.
GA₃ and NAA foliar application enhances fruit set, quality, and storage performance in 'Fengtang' plum by regulating endogenous hormonal balance.
Wu P, Shang L, Jiang Y … +4 more , Wang L, Tang B, Shen X, Chen H
Sci Rep · 2026 Jul · PMID 42401649 · Full text
The development of the high-value 'Fengtang' plum industry in Guizhou Province is constrained by a low fruit set rate and inconsistent fruit quality. This study investigated the efficacy of exogenous plant growth regulat...
The development of the high-value 'Fengtang' plum industry in Guizhou Province is constrained by a low fruit set rate and inconsistent fruit quality. This study investigated the efficacy of exogenous plant growth regulators (PGRs)-gibberellic acid (GA) and naphthaleneacetic acid (NAA), applied individually or in combination at flowering-on improving fruit set, yield, growth dynamics, quality, and storage characteristics. Treatments included foliar sprays of 100 mg L GA, 30 mg L NAA, 100 mg L GA + 30 mg L NAA, and a distilled water control (CL). Results demonstrated that the 100 mg L GA treatment significantly increased the [GA + IAA + tZ (trans-zeatin, a natural endogenous cytokinin)]/ABA ratio in pistils, achieving a fruit set rate of 4.13% (2.32 times that of CL) and boosting yield by 48.65% compared with CL. This treatment also significantly enhanced fruit weight (increased by 27.98 g), vertical diameter (increased by 9.42 mm), fruit shape index (increased by 0.14), and fruit firmness (increased by 1.68 N cm) at maturity. Furthermore, GA application significantly elevated key quality parameters, including vitamin C (2.49 mg 100 g), total phenols (0.52 mg g), and total flavonoids (0.36 mg g). During storage, GA-treated fruit exhibited a delayed decline in firmness (1.35 times that of CL) and maintained higher levels of soluble sugars (1.15 times that of CL) and soluble solids content (SSC, 1.17 times that of CL). While the NAA treatment improved fruit weight (increased by 28.19 g) and vertical diameter (increased by 8.39 mm), its overall effect was inferior to that of GA. The combined GA + NAA treatment showed no significant improvement over GA alone for most parameters. In conclusion, foliar application of 100 mg L GA at flowering effectively regulates endogenous hormonal balance, significantly enhances fruit set, yield, quality, and storage characteristics in 'Fengtang' plum, establishing it as the optimal PGR protocol for high-quality and high-yield cultivation.
Elucidating the tolerance mechanisms of faba bean (Vicia faba L.) to bean broomrape (Orobanche crenata Forssk.) infested soil.
Abdelkader M, Elkordy A, Abdelaal K … +2 more , Said AA, Ridwan ARM
Sci Rep · 2026 Jul · PMID 42401648 · Full text
Bean broomrape is one of the most destructive parasitic weeds limiting faba bean production in many Mediterranean and Middle Eastern countries. This study aims to investigate the susceptibility of Faba bean genotypes to...
Bean broomrape is one of the most destructive parasitic weeds limiting faba bean production in many Mediterranean and Middle Eastern countries. This study aims to investigate the susceptibility of Faba bean genotypes to Bean Broomrape infestation. A field experiment was conducted to evaluate nine Faba bean cultivars with diverse genetic backgrounds. The tested cultivars were Sakha 1, Misr 3, Mariout 2, Giza 429, Giza 843, Giza 716, Nubaria 1, Nubaria 3, and Wadi 1. Giza 429 had the highest plant (73 cm), and Nubaria 1 had the greatest root fresh weight (39.3 g). Giza 429 produced the highest seed yield (3.2 t/ha) and the lowest Bean Broomrape dry weight (40.3 g/m). In contrast, Nubaria 1 was the most susceptible, with severe yield reduction (0.87 t/ha) and high infestation (110.4 g/m). Physio-biochemical analyses revealed that resistant cultivars (Giza 429, Misr 3) had increased antioxidant activity and phenolic content, while showing reduced proline. Tolerant cultivars had larger vascular cylinder diameters, wider xylem vessels, and thicker phloem tissue, which enhances nutrient transport and structural resistance to Bean Broomrape. Susceptible cultivars displayed reduced vascular development and smaller xylem vessel areas. Giza 429 is a promising genetic resource for breeding programs aimed at enhancing tolerance to broomrape. The findings highlight the potential contributions of biochemical defense responses and root anatomical adaptations to tolerance mechanisms in faba bean under O. crenata infestation.
Composition engineered GNS/CNT Hybrid nanocomposites with enhanced thermal stability and tunable optical properties via one-step methane CVD.
Abdelhakim MM, Khalil AAI, Alshershby M … +1 more , Salah A
Sci Rep · 2026 Jul · PMID 42401647 · Full text
Graphene nanosheet/carbon nanotube (GNS/CNT) hybrid nanocomposites were produced using a one-step methane CVD method, employing a Mo-Mg-Fe catalytic system. This facilitated the concurrent growth and integration of graph...
Graphene nanosheet/carbon nanotube (GNS/CNT) hybrid nanocomposites were produced using a one-step methane CVD method, employing a Mo-Mg-Fe catalytic system. This facilitated the concurrent growth and integration of graphitic elements. The impact of the Mo/Mg ratio on structural development, oxide chemistry, defect density, and thermal stability was examined in detail. SAED, TEM, and SEM revealed the coexistence of wrinkled graphene sheets linked with CNTs, while EDS and STEM showed even C, O, Mg, Mo, and Fe distribution. Raman indicated low defects (I/I ≈ 0.14), I/I = 0.33, and A/A ≈ 0.43, which reveals that samples have common characteristics of few to multilayer graphene structures. FTIR reflected Mo/Mg-dependent oxide and surface chemistry, and UV-Vis revealed broad, enhanced optical absorption. TGA conducted in an inert atmosphere demonstrated remarkable enhanced thermal stability, characterized by negligible mass loss (2-6%) up to 1000 °C; this stability is ascribed to the formation of Mo-assisted carbides and the mitigation of Mg volatilization. The CVD method creates hybrids that are structurally low in defects. These hybrids show improved thermal stability and allow for the adjustment of their physical and chemical properties. As a result, these findings confirm that changing the catalyst's composition is a useful way to design carbon nanohybrids with multiple functions.
pH-sensitive gelatin-montmorillonite-cerium oxide nanocarriers for controlled quercetin delivery and machine learning release prediction.
Pourmadadi M, Khanjari J, Mohammadi Shabestari S … +4 more , Fallahi F, Zamanlui Benisi S, Ajalli N, Rajabzad H
Sci Rep · 2026 Jul · PMID 42401646 · Full text
In this study, a novel pH-responsive hybrid nanocarrier with a water-in-oil-in-water (W/O/W) emulsion structure was developed using gelatin (G) as a biocompatible polymer, montmorillonite (MMT) as a layered diffusion bar...
In this study, a novel pH-responsive hybrid nanocarrier with a water-in-oil-in-water (W/O/W) emulsion structure was developed using gelatin (G) as a biocompatible polymer, montmorillonite (MMT) as a layered diffusion barrier, and cerium oxide nanoparticles (CeO₂) as a multifunctional stabilizing agent for pH-responsive and controlled delivery of quercetin (QC). The nanocarriers were synthesized via a double-emulsion method and comprehensively characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and dynamic light scattering (DLS) with zeta potential analysis. The optimized G/MMT/CeO@QC nanocarriers exhibited a uniform nanoscale size (39.3 nm) and a high negative zeta potential (- 38.6 mV), indicating excellent colloidal stability. Incorporation of MMT and CeO₂ significantly enhanced drug loading and encapsulation efficiency (43.0% and 84.5%, respectively) compared to the MMT-free G/CeO₂@QC system, due to synergistic effects of layered silicate confinement, gelatin-mediated hydrogen bonding, and CeO-driven Lewis acid-base coordination. In vitro release studies demonstrated pronounced pH sensitivity, with sustained release at physiological pH (60% at pH 7.4 after 96 h) and accelerated release under tumor-mimicking acidic conditions (95% at pH 5.4). To further interpret the release kinetics, machine learning-assisted, shape-constrained data analysis was employed to provide time-resolved and physically consistent insights into pH-dependent release behavior. Kinetic modeling confirmed Higuchi and Korsmeyer-Peppas-controlled diffusion mechanisms. Cytocompatibility and anticancer activity were evaluated using the MTT assay on A549 lung cancer cells and L929 fibroblasts. Blank nanocarriers were non-toxic (> 95% cell viability), while drug-loaded nanocarriers achieved selective cytotoxicity (A549 viability reduced to 55% with 93% viability in L929 cells), outperforming free QC. Overall, this tri-component hybrid system provides a multifunctional nanoscale platform with controlled drug release, high encapsulation efficiency, and tumor-selective cytotoxicity, demonstrating strong potential as a pH-responsive nanocarrier for lung cancer therapy.
Enhancing brain tumor detection through deep learning and explainable AI techniques.
Hassan SA, Hathah A, Elnokity OE … +4 more , Morfeq A, Abdelfattah W, Ateya AA, Elsawy N
Sci Rep · 2026 Jul · PMID 42401645 · Full text
Brain tumors are a leading cause of cancer-related mortality, and manual MRI screening remains time-consuming and observer-dependent. Deep learning (DL) offers automated detection, but clinical translation requires rigor...
Brain tumors are a leading cause of cancer-related mortality, and manual MRI screening remains time-consuming and observer-dependent. Deep learning (DL) offers automated detection, but clinical translation requires rigorous validation and interpretability. This study introduces a DL framework for brain tumor detection that addresses two major challenges in medical AI: limited dataset availability and lack of interpretability. Preliminary experiments identified InceptionV3 optimized with Nadam as the optimal architecture. To ensure robust validation, this model was retrained using patient-wise stratified fivefold cross-validation on 90% of the data incorporating augmentation and minority oversampling to prevent data leakage. This achieved an overall accuracy of 98.3 ± 0.9%. The final model was then trained on the entire development set using the optimal configuration, thereby leveraging all available labeled data to maximize learning capacity and enhance generalization. Performance evaluation was conducted on three levels: (i) a held out internal test set (10% of the data) for internal assessment, (ii) an external dataset of 3000 unseen images for independent validation, and (iii) quantitative explainable AI (XAI) analyses performed on both internal and external test datasets. The proposed model achieved perfect classification metrics on the internal test set, with 100% accuracy and minimal loss (0.01), and demonstrated strong generalizability on the external dataset with 96% accuracy and minimal loss (0.11). Quantitative XAI analysis demonstrated high faithfulness (Grad-CAM vs. occlusion sensitivity correlation exceeded 0.8), causal importance (top-10% occlusion drop 44% vs. 9% for random occlusion), and specificity to learned weights (Spearman correlation ≈ - 0.01). The proposed pipeline establishes a rigorous, transparent framework for data-limited medical imaging, demonstrating high diagnostic performance with clinically aligned explanations and providing a reliable foundation for trustworthy AI in brain tumor detection.
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