Browse Articles

Hippocampal neuronal activity is aligned with action plans

Drivers of spring migration phenology in Rocky Mountain elk

Distinct assembly processes of intestinal and non-intestinal microbes of bark beetles from clues of metagenomic insights

Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models

Analysis of power system transient stability with PSO-optimized distributed generation and HVDC transmission systems

Proposing a machine learning-based model for predicting nonreassuring fetal heart

How can treatment for eye disease be made easier?

SARS-CoV-2 evolution on a dynamic immune landscape

Abstract Since the onset of the pandemic, many SARS-CoV-2 variants have emerged, exhibiting substantial evolution in the virus’ spike protein 1 , the main target of neutralizing antibodies 2 . A plausible hypothesis proposes that the virus evolves to evade antibody-mediated neutralization (vaccine- or infection-induced) to maximize its ability to infect an immunologically experienced population 1,3 . Because viral infection induces neutralizing antibodies, viral evolution may thus navigate on a dynamic immune landscape that is shaped by local infection history. Here we developed a comprehensive mechanistic model, incorporating deep mutational scanning data 4,5 , antibody pharmacokinetics and regional genomic surveillance data, to predict the variant-specific relative number of susceptible individuals over time. We show that this quantity precisely matched historical variant dynamics, predicted future variant dynamics and explained global differences in variant dynamics. Our work strongly suggests that the ongoing pandemic continues to shape variant-specific population immunity, which determines a variant’s ability to transmit, thus defining variant fitness. The model can be applied to any region by utilizing local genomic surveillance data, allows contextualizing risk assessment of variants and provides information for vaccine design.

Inhibition of TGF-β signaling enhances osteogenic potential of iPSC-derived MSCs

Abstract Mesenchymal stem cells (MSCs) represent the most commonly utilized type of stem cell in clinical applications. However, variability in quality and quantity between different tissue sources and donors presents a significant challenge to their use. Induced pluripotent stem cells (iPSCs) are a promising and abundant alternative source of MSCs, offering a potential solution to the limitations of adult MSCs. Nevertheless, a standardized protocol for the differentiation of iPSCs into iPSC-derived mesenchymal stem cells (iMSCs) has yet to be established, as the existing methods vary significantly in terms of complexity, duration, and outcome. Many straightforward methods induce differentiation by culturing iPSCs in MSC media which are supplemented with fetal bovine serum (FBS) or human platelet lysate (hPL), followed by selection of MSC-like cells by passaging. However, in our hands, this approach yielded inconsistent quality of iMSCs, particularly in terms of osteogenic potential and premature senescence. This study examines the impact of the selective TGF-β inhibitor SB431542 on iMSC differentiation, demonstrating that TGF-β inhibition enhances osteogenic potential and reduces premature senescence. Additionally, we present a reliable, xeno-free method for producing high-quality iMSCs that can be adapted for Good Manufacturing Practice (GMP) compliance, thus enhancing the potential for clinical applications.

Relationship between systemic immune response index (SIRI) and COPD: a cross-sectional study based on NHANES 2007–2012

The effects of ethnic sentiment and social differentiation on pastoralists’ willingness to turn out of pasture

Author Correction: FANCD2–FANCI surveys DNA and recognizes double- to single-stranded junctions

Evolution of the Swiss pork production systems and logistics: the impact on infectious disease resilience

Abstract Livestock production systems are complex and evolve over time, affecting their adaptability to economic, political, and disease-related changes. In Europe, disease resilience is crucial due to threats like the African swine fever virus, which jeopardizes pork production stability. The European Union identifies farm production type as a key risk factor for disease spread, making it important to track changes in farm production types to assess disease risk. However, detailed production type data is often lacking in national databases. For Swiss pig farms, we used prediction and clustering algorithms to classify 9’687 − 11’247 trading farms between 2014 and 2019 by one of eleven production types. We then analyzed the pig trade network and stratified farm centrality measures (ICC and OCC) by production type. We found that 145 farms belonging to three production types have substantially higher ICC and OCC than other farms, suggesting that they could be the target of disease surveillance programs. Our predictions until 2025 show an increase both in overall pig trade network connectivity and in proportion of production types with high ICC and OCC, indicating that the structural changes in the Swiss pig production system may increase infectious disease exposure over time.

Blood pressure levels and risk of end-stage renal disease in patients with type 2 diabetes who underwent percutaneous coronary intervention: a nationwide population-based study

Robust and blind video watermarking against online sharing platforms

Retraction: Super-resolution reconstruction of real infrared images acquired with unmanned aerial vehicle

Pressure-Modulated Energy Transfer Dynamics in Mn²⁺-Doped CdS/ZnS Core/Shell Quantum Dots

Retraction: Chemical characteristics of groundwater and source identification in a coastal city

Identification of Cell Receptors Responsible for Recognition and Binding of Lipid Nanoparticles

Identification of antimicrobial peptides from the Ambystoma mexicanum displaying antibacterial and antitumor activity

Antibiotic resistance is a significant healthcare concern. Therefore, identifying target molecules that can serve as antibiotic substitutes is crucial. Among the promising candidates are antimicrobial peptides (AMPs). AMPs are defense mechanisms of the innate immune system which exist in almost all living organisms. Research on the AMPs of some amphibians has shown that, in addition to their antimicrobial effectiveness, AMPs also exhibit anti-inflammatory and anti-carcinogenic properties. In this study, we identify and characterize AMPs deriving from the skin mucus of the axolotl (Ambystoma mexicanum). Upon activity spectrum evaluation of the AMPs, we synthesized and ranked 22 AMPs according to antimicrobial efficacy by means of a prediction tool. To assess the AMPs’ potential as antibacterial and anticarcinogenic compounds, we performed a minimum inhibitory concentration (MIC) assay for efficacy against methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA), and an apoptosis assay on T-47D mammary carcinoma cells. We identified four AMPs that showed significant inhibition of MRSA, of which three also demonstrated anticarcinogenic activity. Gene expression analysis was performed on AMP-stimulated carcinoma cells using a breast cancer-specific RT-PCR array. In cells stimulated with the AMPs, gene expression analysis showed upregulation of tumor suppressor genes and downregulation of oncogenes. Overall, our work demonstrates the antimicrobial and anticarcinogenic activity of axolotl-derived AMPs. The results of this work serve as a basis to further investigate the mode of action and potential use of axolotl AMPs as therapeutic anticancer or antibiotic agents.