Springer最新文献

The crisis of antimicrobial resistance (AMR) is escalating while the antibiotic pipeline remains stagnant. Our bibliometric analysis of eight decades of literature reveals a critical imbalance: research on AMR has grown, yet fundamental research on antibiotic discovery has declined. Most strikingly, research attention to Actinomycetota, the source of most clinical antibiotics, has sharply decreased since its mid-twentieth-century peak. This therapeutic disinvestment coincides with the intensifying AMR crisis. We argue for a strategic reinvestment in natural product discovery, now enabled by advances in genomics, artificial intelligence, and synthetic biology. These tools can unlock the vast, silent biosynthetic potential of actinobacteria, transforming discovery into a targeted and efficient endeavor. Rebalancing research priorities by coupling this historically proven source with modern technology is essential to revive the antibiotic pipeline. We urge funding agencies and industry to bridge the growing gap between a well characterized problem and a neglected solution.

Cerium dioxide (CeO₂) nanozymes are capable of mimicking the activities of superoxide dismutase (SOD) and catalase (CAT), thereby facilitating the scavenging of reactive oxygen species (ROS). This study aims to synthesize CeO₂ nanozymes with different morphologies by controlling reaction conditions and to elucidate the relationship between morphology and antioxidant and anti-inflammatory activities of the same material. The successful preparation of CeO₂ nanozymes with different morphologies was confirmed by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD). Our findings revealed that CeO₂ nanotubes exhibited the strongest total antioxidant capacity. More importantly, all CeO₂ nanozymes with different morphologies demonstrated excellent ROS scavenging abilities and effectively inhibited the activation of the NF-κB signaling pathway, reduced phosphorylated p65 (P-p65) protein levels, and consequently decreased the release of pro-inflammatory cytokines such as IL-6. This study not only elucidates the structure-activity-anti-inflammatory efficacy relationship of CeO₂ nanozymes but also provides a significant theoretical basis for the development of novel anti-inflammatory nanomedicines.

Understanding environmental drivers of plankton community assembly is critical for predicting ecosystem responses to environmental change in reservoir systems. This study employed environmental DNA (eDNA) metabarcoding to examine how temperature, dissolved oxygen, and spatial gradients structure plankton communities in Singal Reservoir, South Korea, across seasonal and spatial scales from 2021-2022. Water samples were collected from inflow, middle, and outflow zones during spring and autumn, with multi-depth sampling at the central site. The V9 region of 18S rRNA was amplified and sequenced to characterize eukaryotic plankton communities. PERMANOVA analysis revealed that environmental factors explained 39.72% of phytoplankton and 38.62% of zooplankton community variation, with total nitrogen showing the strongest statistical relationship (p = 0.03 for phytoplankton), while temperature and dissolved oxygen patterns revealed important ecological gradients. Phytoplankton communities (130 genera, 5 phyla) showed pronounced seasonal patterns, with autumn exhibiting significantly higher species richness (103 genera) than spring (48 genera) (PERMANOVA: F = 9.52, p = 0.001). Zooplankton communities (43 genera, 2 phyla) displayed similar seasonal trends (F = 7.06, p = 0.001). Spatial analysis demonstrated that sampling location explained 16.7% of zooplankton variance compared to only 1.2% for depth effects, contrasting with expectations about depth effects in shallow reservoirs. Temperature-dissolved oxygen interactions created distinct environmental niches: diatoms preferred high temperature-high oxygen conditions, while dinoflagellates were most common in high temperature-low oxygen environments. Spearman correlations showed environmental preferences, with taxa like Eudiaptomus showing preference for low nutrient conditions (rs = -0.860, p < 0.001 for electrical conductivity). These findings show that environmental selection, especially temperature and dissolved oxygen gradients, are the primary drivers of plankton community structure in reservoir ecosystems, with help predict community responses to climate change and guiding management decisions.

At the European Union level, approximately 60-70% of soil is in unhealthy or degraded conditions. One of the soil threats is the legacy of industrial pollution, as historic industrial pollutants discharged into the ground continue to pose risks to both the environment and human health. As part of the legislative measures adopted in the late 90 s, Human Health Risk Assessment (HHRA) was introduced as a standardized method for evaluating risks associated with contaminated sites. To support the quantification of these risks, various software tool models were developed. This study reviews 12 HHRA tools for contaminated sites developed across different countries. First, an overview of national legislative frameworks concerning contaminated sites, with a particular focus on the use of HHRA as a decision-making tool, is provided. Subsequently, the study compares and discusses the methodologies adopted by each tool, the exposure pathways and receptors considered, the integrated contaminant databases, and additional features provided by the models. The comparison highlights the diversity of functionalities offered by the different tools, reflecting a lack of harmonization among national regulations regarding contaminated site management. Beyond the need for a harmonized approach at the EU level, potential future developments include the design of more user-friendly interfaces capable of expanding exposure scenarios, updating contaminant lists (including emerging pollutants such as PFAS), integrating uncertainty analysis, incorporating Geographic Information System (GIS)-based visualizations, and integrating artificial intelligence (AI)/machine learning (ML).

A degenerative disease of the patellofemoral joint cartilage, chondromalacia patella (CMP) often results in anterior knee discomfort and functional disability. Determining the best course of therapy and stopping the progression of the disease depend on an accurate and timely diagnosis. In this work, we provide a deep learning architecture based on transformers for the classification of chondromalacia patella using magnetic resonance imaging (MRI) data. We assessed transformer-based designs including Multi-Axis Vision Transformer (MaxViT), Vision Transformer (ViT), and Swin Transformer in addition to convolutional neural network (CNN) based models like Google Network (GoogLeNet), Residual Network 18 (ResNet18), and Mobile Network v2 (MobileNetV2). We evaluated the models' ability to differentiate between cases of chondromalacia patella and normal cases. With an accuracy of 0.9817, precision of 0.9821, recall of 0.9817, and F1-score of 0.9818, Multi-Axis Vision Transformer outperformed all other models on the testing dataset.

This study investigates the impact of maternal high-fat diet (HFD) on the development of hypertension and associated metabolic changes in offspring across multiple generations of Wistar rats. Pregnant female rats were assigned to either a normal standard diet or a HFD during gestation. We assessed body weight, heart weight, systolic blood pressure (SBP), catechol-O-methyl transferase (COMT), and vanillyl mandelic acid (VMA) in first, second, and third-generation offspring. Our findings revealed that HFD offspring exhibited significantly elevated SBP compared to controls in all generations, with the most pronounced increase in F1. In addition, plasma EP, NE, and urinary VMA were markedly increased in F1, attenuated in F2, and remained elevated though less pronounced in F3. Also, the cardiac COMT expression was downregulated in all HFD offspring, most strongly in F1. Furthermore, the body weights were significantly higher in F1 compared to controls, whereas differences were minimal in F2 and F3. Moreover, dyslipidemia (elevated TC, TG, LDL; reduced HDL) was observed in F1 and partially persisted in F2 and F3. Finally, histopathological analysis revealed cardiac hypertrophy, cytoplasmic vacuolation, and pyknotic nuclei in F1, with milder alterations in F2 and F3. These results suggest that maternal HFD during pregnancy might affect the offspring cardiovascular health, potentially mediated by alterations in catecholamine dynamics. The study underscores the importance of maternal nutrition in the context of fetal programming and its implications for the prevention of hypertension and related metabolic disorders in future generations.

Diabetes is closely related to increased production of reactive oxygen species, which leads to oxidative stress, chronic inflammation, and increased apoptosis, especially in kidney tissues. Irisin is a recently discovered myokine with the potential to offer hope for the treatment of many metabolic diseases, while BAIBA is also a newly identified endogenous protective myokine. In this study, the effects of thymoquinone (TIM), known for its antioxidant activity, as well as the possible agonistic interaction between irisin and BAIBA on cellular stress and apoptosis occurring in diabetic kidneys were investigated using immunohistochemical methods. In this study, 35 Sprague Dawley rats were equally separated into five groups: Control, STZ, TIM, BAIBA and STZ + TIM + BAIBA. Type 1 diabetes was induced by a single intraperitoneal injection of streptozotocin (STZ, 50 mg/kg). The same protocol was applied to induce diabetes in the TIM and BAIBA groups. Following induction, TIM (20 mg/kg) and BAIBA (100 mg/kg) were administered daily via gavage for five weeks. In the STZ + TIM + BAIBA group, diabetes was induced similarly, followed by daily oral administration of a combination of TIM and BAIBA at the same doses for five weeks. At the conclusion of the study, kidney samples were obtained and analysed using both histochemical and immunohistochemical methods. Results demonstrated that TIM significantly reduced intersitial fibrosis by 55% in the kidneys. It is revealed that both TIM and BAIBA reduced NF-κB immunointensity by 63% and when used simultaneously by %48. Caspase3 immunointensity was reduced by 38%, 46% and 26% following TIM, BAIBA and TIM + BAIBA administration respectively. Also both TIM and BAIBA was observed to cause positive up-regulation on irisin expression. The findings of this study demonstrated that TIM and BAIBA effectively prevented renal fibrosis and apoptosis in STZ-induced diabetic rats, particularly through the downregulation of NF-κB.

This study explores the feasibility of using headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS) to analyse the volatilome of human melanoma A375 cells. The goal was to identify and characterise the volatile organic compounds (VOCs) and monitor alterations induced by treatment with thapsigargin (TG), a drug known to disrupt calcium homeostasis, thereby inducing endoplasmic reticulum stress and ultimately triggering cell death. Reproducibility of experimental conditions is a major issue in biological experiments, which presents intrinsic variability of the samples to be analysed. In our case, initial analysis revealed a significant batch effect, accounting for 56.88% of the total variance. To address this, external parameter orthogonalisation (EPO) was applied, which successfully reduced the batch variance to just 0.16%. After this correction, the treatment factor became the dominant source of variation, explaining 47.12% of the total variance with strong statistical significance (p-value = 0.001). A supervised classification model using partial least squares discriminant analysis (PLS-DA) was developed and validated to characterise the differences between treated and untreated cells. The model achieved a mean overall accuracy of 92.21% and an area under the curve (AUC) of 0.974, indicating excellent discrimination between the two classes. The robustness of these findings was confirmed by repeated double cross-validation and permutation testing, which showed that the model's predictive ability was not due to random chance. The results demonstrate that TG treatment induces a reproducible and highly discriminant volatilome signature in A375. This suggests that VOCs could potentially serve as biomarkers for monitoring cellular responses to drug treatments.

The genotypic variability of the SARS-CoV-2 virus is extremely high, and the emergence of new strains raises concerns about their possible high virulence and ability to bypass responses of the body's immune system induced by previous infection or vaccination. Therefore, one of the main tasks is to study the pathogenesis of various variants of the virus using experimental animal biomodels of SARS-CoV-2 to quickly find methods and approaches to fighting new viruses. The study was performed on humanized mice of the C57BL/6-Tgtn line. Mice were infected intranasally at different doses with three variants of the SARS-CoV-2 virus. We showed that humanized hACE2 mice, when infected with all three variants of the SARS-CoV-2 virus, showed typical pathological changes in lung consistency comparable to those found in COVID-19 in humans. At a dose of 4 log plaque-forming unit (PFU), all variants showed 100% mortality. In a comparative assessment of different variants of the SARS-CoV-2 virus in hACE2 humanized mouse model, it was found that the Delta variant leads to more severe damage compared to Wuhan or Omicron.