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Exploring the potential mechanisms of anti-pulmonary fibrosis effects of Luo Han Guo via network pharmacology, molecular docking, and experimental validation

Microbial aerotrophy enables continuous primary production in diverse cave ecosystems

Effect of selenium nano-vaccine on hematological biomarkers and immune biochemical activity of nile tilapia (Oreochromis niloticus) challenged with Streptococcus pyogenes

Abstract Streptococcus pyogenes infection in Nile tilapia causes high mortality and economic loss. This study evaluated the efficacy of a formalin-killed S. pyogenes bacterium loaded on nano-selenium (nano-vaccination) to prevent streptococcal disease outbreaks on farmed tilapia. 120 Nile tilapia fingerlings were allocated into 4 groups: control group: was injected with 0.1mL of normal saline without any challenges, infected group: was injected with 0.1mL of 1 × 10 7 (CFU)mL − 1 , nano-vaccine group: was injected with two doses of nano-vaccine with an interval of 21 days until day 32nd and nano-vaccine bacteria group: was injected with two doses of nano-vaccine then challenge with bacteria after day 32nd. Hematological biomarkers, inflammatory, oxidative stress, antioxidant enzymes, and histology were estimated in the liver. The selenium nano-vaccinated group showed significant improvement in hematological profiles and elevated antioxidant enzyme activity compared with the control. Compared to the unvaccinated fish, the vaccinated fish showed an enhancement in antioxidant capacity and hematological stability after bacterial challenge. In contrast, infected fish showed higher oxidative stress and inflammatory indicators. Selenium nano-vaccination enhanced hematological performance, antioxidant defense, and immune response in Nile tilapia, allowing effective protection against S. pyogenes infection with minimal inflammation and oxidative damage.

High computational density nanophotonic media for machine learning inference

Spatial lipidomics reveals altered lipid profiles in TMEM63A mutant rats with hypomyelination

Abstract Hypomyelinating leukodystrophies (HLDs) are genetic disorders characterized by deficient myelination. While TMEM63A variants are associated with HLD19, the specific lipid alterations in affected brain regions remain to be fully characterized. This study aimed to investigate the spatial distribution of lipid changes in a Tmem63a mutant rat model of hypomyelination. A homozygous Tmem63a c.500G > A p.(G167E) knock-in rat model ( Tmem63a G167E/G167E ) was established. Brain sections from Tmem63a G167E/G167E and Tmem63a WT rats ( n  = 3/group) were analyzed using MALDI-MSI for lipid profiling across nine distinct brain regions. Myelin structure was characterized by transmission electron microscopy (TEM) and g-ratio quantification. Statistical analyses included Mann-Whitney U tests for g-ratio distributions and ROC analysis for feature screening. Out of 702 analyzed features, 124 were differentially expressed. Lipids constituted the most altered class (43 features), including 22 glycerophospholipid, 9 fatty acid, 5 sphingolipid, 5 sterol lipid, and 2 prenol lipid species. These alterations were predominantly observed in white matter-rich regions and gray-white matter junctions. TEM revealed thinner and less dense myelin sheaths in Tmem63a G167E/G167E rats, with a reduced proportion of optimal g-ratios. This study provides a comprehensive spatial lipidomic characterization in a Tmem63a mutant rat model, revealing significant lipid alterations associated with hypomyelination. These findings offer new insights into the pathology of hypomyelination and highlight specific lipid species for future investigation.

Geographics and bacterial networks differently shape the acquired and latent global sewage resistomes

Abstract Antimicrobial resistance genes (ARGs) have rapidly emerged and spread globally, but the pathways driving their spread remain poorly understood. We analyzed 1240 sewage samples from 351 cities across 111 countries, comparing ARGs known to be mobilized with those identified through functional metagenomics (FG). FG ARGs showed stronger associations with bacterial taxa than the acquired ARGs. Network analyses further confirmed this and showed potential for source attribution of both known and novel ARGs. The FG resistome was more evenly dispersed globally, whereas the acquired resistome followed distinct geographical patterns. City-wise distance-decay analyses revealed that the FG ARGs showed significant decay within countries but not across regions or globally. In contrast, acquired ARGs showed decay at both national and regional scales. At the variant level, both ARG groups had significant national and regional distance-decay effects, but only FG ARGs at a global scale. Additionally, we observed stronger distance effects in Sub-Saharan Africa and East Asia compared to North America. Our findings suggest that differential selection and niche competition, rather than dispersal, shape the global resistome patterns. A limited number of bacterial taxa may act as reservoirs of latent FG ARGs, highlighting the need of targeted surveillance to mitigate future resistance threats.

Cell passage number drives transcriptomic drift as an overlooked factor in experimental reproducibility

Abstract The reproducibility of scientific research has been increasingly challenged in recent years. While extrinsic factors (e.g., cross-contamination, mycoplasma infection, serum variability) are well-studied, the role of intrinsic attributes like cell passage number remains underexplored. Using two tumor cell lines (ACHN and Renca), we employed RNA sequencing to analyze transcriptomic dynamics across passages (P3 to P39). Results revealed a nonlinear transcriptomic shift: mid-passage cells (P10/P11, P17) showed heightened activity in cell cycle, metabolism, and stress response, whereas low (P3) and high passages (P24/P39) exhibited stable and similar profiles. KEGG analysis indicated significant alterations in signaling, immune, and metabolic pathways during passaging. This study demonstrates that passage number shapes transcriptional landscapes and impacts experimental reproducibility. We advocate for strict passage control and explicit reporting of passage information to enhance reliability. These findings underscore the need for standardized cell culture practices to improve research reproducibility.

Observation of nonreciprocal transverse localization of light

Dynamic conditional survival nomogram for non-early-stage infiltrating ductal carcinoma based on SEER database

A yeast surface display platform for characterizing CAR T cell responses to cancer antigens

Abstract Chimeric antigen receptor (CAR) T cells have become an established immunotherapy with promising results for the treatment of hematological malignancies. However, modulation of the targeted antigen’s surface level in cancer cells affects the quality and safety of CAR-T cell therapy. Here we present an engineered yeast-based antigen system for simulation of cancer cells with precise regulation of surface-antigen densities, providing a tool for controlled activation of CAR T cells and systematic assessment of antigen density effects. This S ynthetic C ellular A dvanced S ignal A dapter (SCASA) system uses G protein-coupled receptor signaling to control cancer antigen densities on the yeast surface and provides a customizable platform allowing selectable signal inputs and modular pathway engineering for precise output fine-tuning. In relation to CD19+ cancers, we demonstrate synthetic cellular communication between CD19-displaying yeast and human CAR T cells as well as applications in high-throughput characterization of different CAR designs. We show that yeast is an alternative to conventional technologies (e.g. microbeads) and can provide higher activation control of clinically derived CAR T cells in vitro, relative to cancer cells. In summary, we present a customizable yeast-based platform for high-throughput characterization of CAR-T cell functionality and show potential applications within therapeutic T cells in clinical settings.

Vaccine side effects after vaccination against COVID-19 in employees at an University Hospital in Austria

Mutual friction and vortex Hall angle in a strongly interacting Fermi superfluid

Comparative study of machine learning methods for carbon metering in power generation enterprises

Generative discovery of partial differential equations by learning from math handbooks

The association of defective pleural sRAGE production with the recurrence of malignant pleural effusion after Talc pleurodesis

Determining molecular structure, coordination geometry, and molecular symmetry using a continuous symmetry operation measure software

Bifurcation-based wide-range vacuum pressure micro-sensor

Measuring Hall voltage and Hall resistance in an atom-based quantum simulator

Biomphalaria snails release immune proteins in aquaculture water that influence egg production and development

4D printed deformation labels with machine learning for monitoring and preservation of respiring climacteric fruits

Abstract 4D printed labels that change color and shape were developed to achieve the dual functions of quality assessment and maintenance of respiring climacteric fruits. The effect of addition of essential oil emulsion and different geometric structures on deformation as well as the corresponding mechanisms were explored. Cast, 3D printed, and 4D printed labels were compared based on their responses to fruit quality and compatibility with machine learning. The addition of emulsion significantly affected the degree of deformation by altering the printing fidelity, hydrophilicity, and flexibility of the network structure. Geometric designs (Including printing layers, filament intersection angles, and infill ratios) changed both the direction and degree of deformation. Unlike cast and 3D printed labels, 4D printed labels simultaneously changed color and shape in response to variations in humidity and carbon dioxide levels in the package, enabling more accurate visual monitoring the turning points of fruit quality. The MobileNet model achieved recognition accuracy of 97% for 4D printed labels, which played an active role in achieving intelligent warnings. Additionally, deformation along with microstructure destruction positively impacted the controlled release of essential oils through a non-Fickian mechanism, resulting in a better preservation effect.