Category: Nevin Manimala

Commun Biol. 2026 Apr 21. doi: 10.1038/s42003-026-10082-6. Online ahead of print.

ABSTRACT

With the rising prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD), the development of new drugs targeting this condition is particularly urgent. Sabinineoside B, a new compound of phenanthrene alkaloid glycoside isolated from the traditional Chinese herb Sabia parviflora. Through establishing a high-fat diet mouse model and integrating metabolomics, proteomics, and phosphoproteomics analyses, this study elucidated the efficacy and mechanism of Sabinineoside B in treating MASLD, while preliminarily evaluating its pharmacokinetics and safety. Molecular docking, molecular dynamics simulations, drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), pull-down, dual-luciferase reporter gene assays and siRNA techniques were employed to validate the binding interaction between Sabinineoside B and key targets. We found that the Sabinineoside B protein significantly reduces lipid deposition and liver damage in mice on a high-fat diet. Integrated multi-omics analysis and Western blot experiments revealed that Sabinineoside B regulates lipid metabolism and exerts lipid-lowering effects by modulating the PPAR α signaling pathway. Knocking down PPAR α attenuates the regulatory effect of Sabinineoside B on the lipid-lowering pathway, indicating that the molecular mechanism of Sabinineoside B’s lipid-lowering activity may be achieved by targeting PPAR α.

PMID:42014914 | DOI:10.1038/s42003-026-10082-6

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-49918-w. Online ahead of print.

NO ABSTRACT

PMID:42014908 | DOI:10.1038/s41598-026-49918-w

Commun Med (Lond). 2026 Apr 21. doi: 10.1038/s43856-026-01598-3. Online ahead of print.

ABSTRACT

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is an aggressive malignancy where many patients relapse after standard therapy, necessitating novel approaches. Pyroptosis is an inflammatory cell death that can stimulate antitumor immunity. Histone deacetylases are frequently overexpressed in DLBCL and contribute to immune evasion. This study investigates whether combining the HDAC inhibitor chidamide with cisplatin and etoposide induces pyroptosis and enhances antitumor immune responses.

METHODS: We evaluated chidamide combined with cisplatin and etoposide in diffuse large B-cell lymphoma cell lines and syngeneic mouse models. Cell death mechanisms were analyzed using immunoblotting and imaging. Tumor growth and immune cell infiltration were assessed in immunocompetent mice, with the role of adaptive immunity evaluated through CD8-positive T cell depletion. Statistical analyses included analysis of variance where appropriate.

RESULTS: Here we show that chidamide synergistically potentiates cisplatin and etoposide efficacy by upregulating gasdermin E expression and promoting its caspase-3-dependent cleavage, thereby triggering pyroptosis. This combination remodels the tumor microenvironment, increasing infiltration of dendritic cells, natural killer cells, and CD8-positive T cells while reducing immunosuppressive macrophages. Depletion of CD8-positive T cells abolishes the therapeutic benefit, demonstrating their essential role.

CONCLUSIONS: The chidamide-cisplatin-etoposide combination triggers immunogenic pyroptosis via the caspase-3/gasdermin E axis and activates adaptive immunity. This regimen represents a promising therapeutic strategy for relapsed diffuse large B-cell lymphoma warranting clinical investigation.

PMID:42014876 | DOI:10.1038/s43856-026-01598-3

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-45941-z. Online ahead of print.

NO ABSTRACT

PMID:42014863 | DOI:10.1038/s41598-026-45941-z

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-45728-2. Online ahead of print.

ABSTRACT

The incorporation of aluminum dross into cement-based mortars offers potential benefits for environmental sustainability; however, it may adversely affect the mechanical performance of the material. This study integrates experimental testing with statistical analysis to evaluate the influence of aluminum dross on the mechanical properties of mortar specimens exposed to sulfuric acid (pH 1.5). Compressive strength, flexural strength, and mass variation were measured for mortars containing different aluminum dross contents. Following 28 days of water curing, the specimens were immersed in sulfuric acid for periods ranging from 0 to 90 days. The results indicate that exposure to sulfuric acid led to progressive deterioration in all mortar mixtures, with average reductions of 39% in compressive strength after 14 days and about 80% after 90 days. Before acid exposure, increasing aluminum dross content reduced the initial mechanical strength by up to 28% compared with the control mixture. Under prolonged acidic conditions, slag-containing mortars-particularly those incorporating 10% and 15% aluminum dross-exhibited reduced strength loss and enhanced acid resistance compared to slag-free control specimens. Statistical analysis demonstrated strong correlations between mechanical properties, acid exposure duration, and mass loss, whereas the effect of aluminum dross content was less significant. These findings underline both the potential benefits and the practical limitations of using aluminum dross in sustainable cement mortar applications subjected to acidic exposure.

PMID:42014862 | DOI:10.1038/s41598-026-45728-2

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-49546-4. Online ahead of print.

NO ABSTRACT

PMID:42014844 | DOI:10.1038/s41598-026-49546-4

NPJ Digit Med. 2026 Apr 21. doi: 10.1038/s41746-026-02638-x. Online ahead of print.

ABSTRACT

Parental divorce is common and linked to adverse mental health outcomes and reduced well-being in children and adolescents, yet digital interventions for this group remain scarce. This study reports on a randomized controlled trial of a digital intervention (SES NXT) for children and adolescents aged 3-17 experiencing parental divorce. Participants (n = 866) were randomized to either SES NXT (n = 449) or a waitlist control group (n = 417). At 12-week follow-up from baseline, the intervention group showed medium to large improvements across all primary and secondary mental health and well-being outcomes versus the waitlist control group, as measured by the Strength and Difficulty Questionnaire (SDQ). Primary outcomes included emotional symptoms, total difficulties, and impairment (Cohen’s (d) = 0.66-0.71, all p’s < 0.001). Secondary outcomes included conduct problems, hyperactivity, peer problems, and prosocial behavior (Cohen’s (d) = 0.47-0.56, all p’s < 0.001). Findings are discussed through the Divorce-Stress-Adjustment framework and within the Northern European (Danish) cultural context.

PMID:42014835 | DOI:10.1038/s41746-026-02638-x

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-49838-9. Online ahead of print.

ABSTRACT

As the scale and complexity of underground structures continue to increase, seismic dynamic analysis places higher demands on numerical computing capacity. In this study, a seismic time-history analysis framework based on high-performance parallel computing is adopted, and a refined three-dimensional finite element model with more than five million elements is established to assess the feasibility of large-scale three-dimensional seismic analysis for complex underground structures. In addition, the dynamic response characteristics of a fully prefabricated underground metro station under E2-level earthquake excitation are systematically analysed. The displacement and stress responses of the soil-station system exhibit pronounced spatial non-uniformity, with high-response regions mainly distributed in the lower part of the model, along the soil-structure interface, and at structural geometric transitions and connection zones. Statistical results from representative monitoring points indicate that the locations of peak acceleration and peak displacement do not fully coincide. Further analysis shows that Kobe-wave input mainly amplifies the response without changing the dominant system-level response pattern, whereas changes in CHC joint stiffness primarily affect local response levels and the distribution of high-response regions. Taken together, these findings suggest that, with appropriate modelling and solution strategies, large-scale three-dimensional numerical simulations can effectively characterise the system-level dynamic response of fully prefabricated underground metro stations and provide a practical basis for the seismic assessment of complex underground structures.

PMID:42014818 | DOI:10.1038/s41598-026-49838-9

Sci Rep. 2026 Apr 21. doi: 10.1038/s41598-026-49819-y. Online ahead of print.

ABSTRACT

Grain number estimation plays a crucial role in agriculture, serving as a key indicator for crop yield and quality assessment. With advances in computer vision, automatic grain detection has become a significant research area, where deep learning methods have shown remarkable promise. This study proposes a vision transformer model called Swin Transformer, which leverages hierarchical attention mechanisms across shifted windows to effectively capture both local and global features of grains in complex imagery. The model achieves the highest accuracy of 98%, outperforming baseline traditional CNN (ResNet-50) and DINO models in grain counting tasks. To support and validate model performance, explainable AI (XAI) techniques such as Grad-CAM and LIME are employed, highlighting the interpretability and focus of the model on relevant grain regions. Furthermore, a comprehensive empirical analysis is conducted using multiple statistical tests to evaluate the model’s robustness and generalizability across various grain morphological parameters, establishing the Swin Transformer as a powerful and interpretable solution for intelligent grain counting in agricultural data analytics.

PMID:42014763 | DOI:10.1038/s41598-026-49819-y

Sci Data. 2026 Apr 21;13(1):631. doi: 10.1038/s41597-026-07290-4.

ABSTRACT

The expansion of wind energy is a key strategy for mitigating global climate change. To support this goal, consistent global-scale datasets of existing wind turbines are essential for planning the future deployment of wind energy. Here, we introduce GOWIRES, a comprehensive global dataset of onshore wind turbines. GOWIRES provides detailed information on 416,417 horizontal-axis wind turbines (HAWT) across 89 countries. The dataset includes geographic coordinates, key technical specifications, and site-specific environmental characteristics for each wind turbine. In addition, GOWIRES provides historical (1989-2018) and future (2030-2059) site-specific wind resource data. Wind resources are characterized by mean wind speed, mean wind power density, Weibull parameters, power law exponents, and air density. Future Weibull parameters are based on simulations from 13 statistically downscaled global climate models under the SSP2-4.5 and SSP5-8.5 scenarios. GOWIRES is a valuable resource for energy and climate research, as well as for applications in wind energy development, grid and infrastructure planning, and policy-making.

PMID:42014750 | DOI:10.1038/s41597-026-07290-4