221 research outputs found

    Type IIs restriction based combinatory modulation technique for metabolic pathway optimization

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    Additional file 1: Table S1. Oligonucleotides used in this study

    Impacts of fertilization methods on Salvia miltiorrhiza quality and characteristics of the epiphytic microbial community

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    Plant epiphytic microorganisms have established a unique symbiotic relationship with plants, which has a significant impact on their growth, immune defense, and environmental adaptation. However, the impact of fertilization methods on the epiphytic microbial community and their correlation with the yield and quality of medicinal plant was still unclear. In current study, we conducted a field fertilization experiment and analyzed the composition of epiphytic bacterial and fungal communities employing high throughput sequencing data in different organs (roots, stems, and leaves) of Salvia miltiorrhiza, as well as their correlation with plant growth. The results showed that fertilization significantly affected the active ingredients and hormone content, soil physicochemical properties, and the composition of epiphytic microbial communities. After fertilization, the plant surface was enriched with a core microbial community mainly composed of bacteria from Firmicutes, Proteobacteria, and Actinobacteria, as well as fungi from Zygomycota and Ascomycota. Additionally, plant growth hormones were the principal factors leading to alterations in the epiphytic microbial community of S. miltiorrhiza. Thus, the most effective method of fertilization involved the application of base fertilizer in combination with foliar fertilizer. This study provides a new perspective for studying the correlation between microbial community function and the quality of S. miltiorrhiza, and also provides a theoretical basis for the cultivation and sustainable development of high-quality medicinal plants

    The influence of high worry on static and dynamic insular functional connectivity

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    Worry is a form of repetitive negative thought. High worry-proneness is one risk factor leading to anxiety disorder. Several types of research indicated that anxiety disorder was highly associated with disrupted interoception. The insula is consistently considered to play a key role in interoception. However, the relationship between worry and the interoception network is poorly investigated in worry-prone individuals. Thus, it is essential to identify the neural characteristic of high worry-proneness subjects. A total of 32 high worry-proneness (HWP) subjects and 25 low worry-proneness (LWP) subjects were recruited and underwent magnetic resonance imaging scanning. Six subregions of insula were chosen as regions of interest. Then, seed-based static and dynamic functional connectivity were calculated. Increased static functional connectivity was observed between the ventral anterior insula and inferior parietal lobule in HWP compared to LWP. Decreased static functional connectivity was found between the left ventral anterior insula and the pregenual anterior cingulate cortex. Decreased dynamic functional connectivity was also shown between the right posterior insula and the inferior parietal lobule in HWP. Moreover, a post-hoc test exploring the effect of changed function within the insular region confirmed that a significant positive relationship between static functional connectivity (ventral anterior insula–inferior parietal lobule) and dynamic functional connectivity (posterior insula–inferior parietal lobule) in LWP but not in HWP. Our results might suggest that deficient insular function may be an essential factor related to high worry in healthy subjects

    Characteristics of tumor infiltrating lymphocyte and circulating lymphocyte repertoires in pancreatic cancer by the sequencing of T cell receptors

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    Pancreatic cancer has a poor prognosis and few effective treatments. The failure of treatment is partially due to the high heterogeneity of cancer cells within the tumor. T cells target and kill cancer cells by the specific recognition of cancer-associated antigens. In this study, T cells from primary tumor and blood of sixteen patients with pancreatic cancer were characterized by deep sequencing. T cells from blood of another eight healthy volunteers were also studied as controls. By analyzing the complementary determining region 3 (CDR3) gene sequence, we found no significant differences in the T cell receptor (TCR) repertoires between patients and healthy controls. Types and length of CDR3 were similar among groups. However, two clusters of patients were identified according to the degree of CDR3 overlap within tumor sample group. In addition, clonotypes with low frequencies were found in significantly higher numbers in primary pancreatic tumors compared to blood samples from patients and healthy controls. This study is the first to characterize the TCR repertoires of pancreatic cancers in both primary tumors and matched blood samples. The results imply that specific types of pancreatic cancer share potentially important immunological characteristics

    Understanding the Mechanism of Deep Learning Frameworks in Lesion Detection for Pathological Images with Breast Cancer

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    With the advances of scanning sensors and deep learning algorithms, computational pathology has drawn much attention in recent years and started to play an important role in the clinical workflow. Computer-aided detection (CADe) systems have been developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing misdetections. In this study, we conducted four experiments to demonstrate that the features learned by deep learning models are interpretable from a pathological perspective. In addition, classifiers such as the support vector machine (SVM) and random forests (RF) were used in experiments to replace the fully connected layers and decompose the end-to-end framework, verifying the validity of feature extraction in the convolutional layers. The experimental results reveal that the features learned from the convolutional layers work as morphological descriptors for specific cells or tissues, in agreement with the diagnostic rules in practice. Most of the properties learned by the deep learning models summarized detection rules that agree with those of experienced pathologists. The interpretability of deep features from a clinical viewpoint not only enhances the reliability of AI systems, enabling them to gain acceptance from medical experts, but also facilitates the development of deep learning frameworks for different tasks in pathological analytics

    Association of antioxidants use with the risk of dementia among community-dwelling adults in the United Kingdom biobank

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    BackgroundData regarding the association between antioxidant supplementation and incident dementia are limited.MethodsWe included 494,632 adults (54.5% females) aged 40–71 years at baseline from the United Kingdom Biobank in the final analysis. Incident dementia was ascertained using hospital inpatient and death records up to January 2021.ResultsOver a median follow-up of 11.9 years, 7,128 new cases of all-cause dementia, 2,772 cases of Alzheimer’s disease, and 1,397 cases of vascular dementia were recorded. The hazard ratio (95% CI) for incident dementia associated with zinc supplementation was 0.84 (0.74–0.96), and the association remained significant after adjusting for all confounders (0.84 (0.74–0.96)). In the full model, zinc supplementation was associated with a reduced risk of Alzheimer’s disease [HR (95% CI): 0.71 (0.57–0.88)]. There was no significant association between zinc supplementation and the risk of vascular dementia. No significant associations with incident dementia were observed for other antioxidant supplementation. The association between zinc supplementation and incident dementia was significant among individuals with [HR (95% CI): 0.34 (0.15–0.77)] and without cataract [0.87 (0.77–0.99)] but it was stronger among those with cataract (p value for interaction = 0.0271).ConclusionOur findings suggest that zinc supplementation may help reduce the risk of all-cause dementia and Alzheimer’s disease in middle-aged or older adults, especially among those with cataracts
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