Explore the vast range of titles available.

Background Osteoporosis and cardiovascular disease (CVD) are age-related diseases. It is reported that patients with CVD have a higher risk of bone loss. This retrospective study sought to reveal the association between osteoporosis and CVD in Chinese women. Although epidemiological evidence has indicated a relationship between the two, clinical data in southeast China are lacking. Methods In total, 2873 participants completed the baseline survey from January 2007 to October 2019, and 2039 were included in this retrospective study. We divided all subjects into an osteoporosis group and a non-osteoporosis group based on their bone mineral density (BMD). Dual-energy X-ray absorptiometry (DXA) was used to examine BMD. The general information came from the questionnaire survey. Cardiovascular diseases were defined by asking participants at the first visit and checking relevant medical records if they had suffered from hypertension, coronary heart disease, or cerebral infarction. Results According to the criterion, the osteoporosis group had 678 subjects, and the non-osteoporosis group had 1361 subjects. Subjects in the osteoporosis group had a significantly higher prevalence of hypertension and coronary heart disease. Besides, the proportion of subjects who drank tea and drank milk were relatively higher in the osteoporosis group. The odds ratio (OR) for suffering from osteoporosis was high if the patients had hypertension. Conclusions This study indicated that Chinese postmenopausal women with osteoporosis had a higher prevalence of hypertension. Hypertension was significantly associated with osteoporosis.

Schistosomiasis is characterized by egg-induced hepatic granulomas and subsequent fibrosis. Monocyte-derived macrophages play critical and plastic roles in the progression and regression of liver fibrosis, adopting different polarization phenotypes. Mammalian STE20-like protein kinase 1 (MST1), a serine/threonine kinase, has been established to act as a negative regulator of macrophage-associated inflammation. However, the specific role of MST1 in Schistosoma -induced liver fibrosis has not been fully understood. In this study, we demonstrate that macrophage MST1 functions as an inhibitor of inflammation and fibrosis following infection with Schistosoma japonicum (S . japonicum) . Mice with macrophages-specific Mst1 knockout (termed Mst1 △M/△M ) mice developed exacerbated liver pathology, characterized by larger egg-induced granulomas, and increased fibrosis post infection. This was accompanied by enhanced production of proinflammatory cytokines (IL1B, IL6, IL23, TNFA and TGFB) and a shift in macrophage phenotype towards Ly6C high . Mechanistically, MST1 activation by soluble egg antigen (SEA) promoted PPARγ-mediated CD36 expression, enhancing phagocytosis and consequently upregulation of fibrolytic genes such as Arg1 and Mmps . Conversely, MST1 deletion leads to up-regulation of pro-inflammatory genes instead of fibrolytic genes in macrophages, accompanied by decreased expression of CD36 and impaired phagocytosis. Furthermore, the ablation of MST1 enhances NF-κB activation in S . japonicum -infected and SEA-stimulated macrophages, resulting in increased production of proinflammatory cytokines. Overall, our data identified MST1 as a novel regulator for egg-induced liver fibrosis via modulation of macrophage function and phenotype by CD36-mediated phagocytosis and suppression of NF-κB pathway.

Accurate segmentation of cardiac MR images using deep neural networks is crucial for cardiac disease diagnosis and treatment planning, as it provides quantitative insights into heart anatomy and function. However, achieving high segmentation accuracy relies heavily on extensive, precisely annotated datasets, which are costly and time-consuming to obtain. This study addresses this challenge by proposing a novel data augmentation framework based on a condition-guided diffusion generative model, controlled by multiple cardiac labels. The framework aims to expand annotated cardiac MR datasets and significantly improve the performance of downstream cardiac segmentation tasks. The proposed generative data augmentation framework operates in two stages. First, a Label Diffusion Module is trained to unconditionally generate realistic multi-category spatial masks (encompassing regions such as the left ventricle, interventricular septum, and right ventricle) conforming to anatomical prior probabilities derived from noise. Second, cardiac MR images are generated conditioned on these semantic masks, ensuring a precise one-to-one mapping between synthetic labels and images through the integration of a spatially-adaptive normalization (SPADE) module for structural constraint during conditional model training. The effectiveness of this augmentation strategy is demonstrated using the U-Net model for segmentation on the enhanced 2D cardiac image dataset derived from the M&M Challenge. Results indicate that the proposed method effectively increases dataset sample numbers and significantly improves cardiac segmentation accuracy, achieving a 5% to 10% higher Dice Similarity Coefficient (DSC) compared to traditional data augmentation methods. Experiments further reveal a strong correlation between image generation quality and augmentation effectiveness. This framework offers a robust solution for data scarcity in cardiac image analysis, directly benefiting clinical applications.

Class-incremental learning (CIL) in deep neural networks is affected by catastrophic forgetting (CF), where acquiring knowledge of new classes leads to the significant degradation of previously learned representations. This challenge is particularly severe in medical image analysis, where costly, expertise-dependent annotations frequently contain pervasive and hard-to-detect noisy labels that substantially compromise model performance. While existing approaches have predominantly addressed CF and noisy labels as separate problems, their combined effects remain largely unexplored. To address this critical gap, this paper presents a dual-stage clean-sample selection method for Incremental Noisy Label Learning (DSCNL). Our approach comprises two key components: (1) a dual-stage clean-sample selection module that identifies and leverages high-confidence samples to guide the learning of reliable representations while mitigating noise propagation during training, and (2) an experience soft-replay strategy for memory rehearsal to improve the model’s robustness and generalization in the presence of historical noisy labels. This integrated framework effectively suppresses the adverse influence of noisy labels while simultaneously alleviating catastrophic forgetting. Extensive evaluations on public medical image datasets demonstrate that DSCNL consistently outperforms state-of-the-art CIL methods across diverse classification tasks. The proposed method boosts the average accuracy by 55% and 31% compared with baseline methods on datasets with different noise levels, and achieves an average noise reduction rate of 73% under original noise conditions, highlighting its effectiveness and applicability in real-world medical imaging scenarios.

Marine bacterioplankton perform a very important role in the cycles of carbon, nitrogen, phosphorus, and other elements in coastal waters. The impacts of environmental factors on bacterial community structure are dynamic and ongoing. This study investigated the spatiotemporal distributions of elements and their influences on bacterioplankton communities in the coastal waters around the Changli Gold Coast National Nature Reserve in northern China. The results demonstrate the significant temporal variability of phosphorus, nitrogen, and carbon in spring and summer, influenced by natural environmental factors and anthropogenic activities. In spring, increased biological activity, particularly phytoplankton growth, may elevate TOC and POC levels near the river estuaries, while in summer, microbial decomposition likely stabilized carbon concentrations. The seasonal variation in the bacterioplankton community was obvious. Bacteroidetes were enriched in spring samples and Cyanobacteriota proliferated in summer. The dominated genera in the spring, including Planktomarina, an unclassified NS5_marine_group (belonging to Flavobacteriaceae), and the OM43_clade (Methylophilaceae), showed significant positive correlation with salinity, TDP, TOC, POP, and DO levels, while Synechococcus_CC9902 (Synechococcus), PeM15_unclassified (Actinobacteria), and HIMB11 (Rhodobacteraceae), which all dominate in summer samples, are significantly positively correlated with TN, TDN, temperature, and ammonium levels. In summer in particular, the increase in human activities and river inputs greatly improves nutrient levels and promotes the propagation of photosynthetic microorganisms. These results indicate that the nutrient elements and environmental physical conditions are affected by seasonal changes and human activities, which have significant effects on the community structure of bacterioplankton. This study highlights the importance of ongoing monitoring in estuarine coastal areas, especially in protected areas like the Changli Reserve, to manage eutrophication risks and maintain ecological balance.

Although the detailed biosynthetic mechanism is still unclear, the unique secondary metabolites of Ginkgo biloba , including ginkgolic acids (GAs) and terpene trilactones, have attracted increasing attention for their potent medicinal, physiological and biochemical properties. In particular, GAs have shown great potential in the fields of antibacterial and insecticidal activities, making it urgent to elucidate their biosynthetic mechanism. In this study, we systematically revealed the landscape of metabolic-transcriptional regulation across continuous growth stages of G. biloba seeds (GBS) based on multi-omics mining and experimental verification, and successfully identified all major types of GAs and terpene trilactones along with more than a thousand kinds of other metabolites. The phenological changes and the essential gene families associated with these unique metabolites were analyzed in detail, and several potential regulatory factors were successfully identified based on co-expression association analysis. In addition, we unexpectedly found the close relationship between large introns and the biosynthesis of these secondary metabolites. These genes with large introns related to the synthesis of secondary metabolites showed higher gene expression and expression stability in different tissues or growth stages. Our results may provide a new perspective for the study of the regulatory mechanism of these unique secondary metabolites in GBS.

Microbial mineralization of organic matter has a significant impact on the global biogeochemical cycle. This report confirms the role of Marinifilaceae in organic degradation in the oceans, with a contribution to ocean carbon cycling that has previously been underestimated. Transfer of animal and plant detritus of both terrestrial and marine origins to the deep sea occurs on a global scale. Microorganisms play an important role in mineralizing them therein, but these are yet to be identified in situ . To observe key bacteria involved, we conducted long-term in situ incubation and found that members of the family Marinifilaceae (MF) occurred as some of the most predominant bacteria thriving on the new inputs of plant and animal biomasses in the deep sea in both marginal and oceanic areas. This taxon is diverse and ubiquitous in marine environments. A total of 11 MAGs belonging to MF were retrieved from metagenomic data and diverged into four subgroups in the phylogenomic tree. Based on metagenomic and metatranscriptomic analyses, we described the metabolic features and in situ metabolizing activities of different subgroups. The MF-2 subgroup, which dominates plant detritus-enriched cultures, specializes in polysaccharide degradation and lignin oxidation and has high transcriptional activities of related genes in situ . Intriguingly, members of this subgroup encode a nitrogen fixation pathway to compensate for the shortage of nitrogen sources inside the plant detritus. In contrast, other subgroups dominating the animal tissue-supported microbiomes are distinguished from MF-2 with regard to carbon and nitrogen metabolism and exhibit high transcriptional activity for proteolysis in situ . Despite these metabolic divergences of MF lineages, they show high in situ transcriptional activities for organic fermentation and anaerobic respiration (reductions of metal and/or dimethyl sulfoxide). These results highlight the role of previously unrecognized Marinifilaceae bacteria in organic matter mineralization in marine environments by coupling carbon and nitrogen cycling with metal and sulfur. IMPORTANCE Microbial mineralization of organic matter has a significant impact on the global biogeochemical cycle. This report confirms the role of Marinifilaceae in organic degradation in the oceans, with a contribution to ocean carbon cycling that has previously been underestimated. It was the dominant taxon thriving on plant and animal biomasses in our in situ incubator, as well as in whale falls and wood falls. At least 9 subgroups were revealed, and they were widely distributed in oceans globally but predominant in organic-matter-rich environments, with an average relative abundance of 8.3%. Different subgroups display a preference for the degradation of different macromolecules (polysaccharides, lignin, and protein) and adapt to their environments via special metabolic mechanisms.

In response to the growing market demand for Litopenaeus vannamei, a variety of single-species, high-density, intensive, and high-yield aquaculture modes have arisen. These aquacultural systems are teeming with microorganisms, which play roles in water quality and host health. To uncover the prokaryotic community composition across cultivation modes, we investigated the prokaryotic community composition at two fractionated sizes in the water of three culture modes of Litopenaeus vannamei, including high-level pond culture, biofloc technology (BFT), and pond culture. The 16S rRNA gene high-throughput sequencing results indicated that the taxa particularly enriched by high-level pond culture modes were mainly Deltaproteobacteria, while Alpha- and Gammaproteobacteria and Flavobacteria were enriched in the BFT culture modes. The pond culture enriched Bacteroidetes, Sphingobacteriia, Actinobacteria, and Cyanobacteria. PCoA analysis showed that for the pond samples, there were significant differences in the community composition compared with the samples from the other two modes. However, the high-level pond and biofloc samples showed similar community compositions. Furthermore, Canonical Correspondence Analysis (CCA) and Variance Partitioning Analysis (VPA) revealed that NH4+-N, salinity (Sal), and NO3−-N were key factors affecting the aquaculture communities.

On 13 December 2012, Chang'e-2 conducted a successful flyby of the near-Earth asteroid 4179 Toutatis at a closest distance of 770 ± 120 meters from the asteroid's surface. The highest-resolution image, with a resolution of better than 3 meters, reveals new discoveries on the asteroid, e.g., a giant basin at the big end, a sharply perpendicular silhouette near the neck region and direct evidence of boulders and regolith, which suggests that Toutatis may bear a rubble-pile structure. Toutatis' maximum physical length and width are (4.75 × 1.95 km) ±10%, respectively and the direction of the + z axis is estimated to be (250 ± 5°, 63 ± 5°) with respect to the J2000 ecliptic coordinate system. The bifurcated configuration is indicative of a contact binary origin for Toutatis, which is composed of two lobes (head and body). Chang'e-2 observations have significantly improved our understanding of the characteristics, formation and evolution of asteroids in general.

Marine microorganisms exert a profound influence on global carbon cycling and ecological relationships. Mixotrophy, characterized by the simultaneous utilization of both autotrophic and heterotrophic nutrition, has a significant impact on the global carbon cycling. This report characterizes a group of uncultivated bacteria Arcobacteraceae that thrived on the “hot time” of bulky particulate organic matter and exhibited mixotrophic strategy during the in situ organic mineralization. Compared with clades A and B, more unique metabolic pathways were retrieved in clade C, including the reverse tricarboxylic acid pathway for carbon fixation, thiosulfate disproportionation, methane oxidation, and fatty acid oxidation. Global metatranscriptomic data from the Tara Oceans expeditions confirmed the ubiquitous distribution and extensive transcriptional activity of Arcobacteraceae with the expression of genes putatively involved in carbon fixation, methane oxidation, multiple sulfur compound oxidation, and denitrification across all oceanic regions and depths.