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  • Frontiers Media SA  (12)
  • 1
    Online Resource
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    Effects of climate change and agricultural expansion on groundwater storage in the Amur River Basin
    Frontiers Media SA ; 2023
    In:  Frontiers in Earth Science Vol. 10 ( 2023-1-9)
    Details
    In: Frontiers in Earth Science, Frontiers Media SA, Vol. 10 ( 2023-1-9)
    Abstract: Since the 1990s, the climate in the Amur River Basin (ARB) has changed, and large-scale wetlands in the region have been reclaimed for paddy fields. The study of the influence of climate change and agricultural expansion on groundwater storage is of great significance to the evaluation of regional water resource balance and the promotion of ecological protection and agricultural development. In this work, the groundwater storage anomaly (GWSA) in the ARB and its drivers were analyzed for the period 2003–2016 using Gravity Recovery and Climate Experiment (GRACE) satellite data, a Global Land Data Assimilation System model, and in situ observations of groundwater levels. Results indicated that 1) the GWSA in the ARB increased at a rate of 2.0–2.4 mm/yr from 2003 to 2016; the GWSA in the upper reaches of the ARB increased, whereas the GWSA in the middle and lower reaches decreased during the study period. 2) The GWSA in the middle and lower reaches of the ARB was greatly influenced by temperature (Tmp) and evapotranspiration (ET). Tmp was positively correlated with GWSA, whereas ET was negatively correlated with GWSA ( p & lt; 0.05). 3) Extreme rainfall had a delayed effect on groundwater recharge. Wetland degradation and agricultural development were the main factors causing the decrease of the GWSA in the middle and lower reaches of the ARB. In summary, temperature and evapotranspiration affect groundwater storage by regulating the water–heat balance, wetland reclamation reduces the regional storage capacity, and the irrigation required for reclaimed farmland is the main source of groundwater loss.
    Type of Medium: Online Resource
    ISSN: 2296-6463
    URL: Article
    DOI: 10.3389/feart.2022.1037688
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2741235-0
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  • 2
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    DataSheet_1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Oncology Vol. 11 ( 2021-9-27)
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    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-9-27)
    Abstract: Predicting hepatocellular carcinoma (HCC) prognosis is important for treatment selection, and it is increasingly interesting to predict prognosis through gene expression data. Currently, the prognosis remains of low accuracy due to the high dimension but small sample size of liver cancer omics data. In previous studies, a transfer learning strategy has been developed by pre-training models on similar cancer types and then fine-tuning the pre-trained models on the target dataset. However, transfer learning has limited performance since other cancer types are similar at different levels, and it is not trivial to balance the relations with different cancer types. Methods Here, we propose an adaptive transfer-learning-based deep Cox neural network (ATRCN), where cancers are represented by 12 phenotype and 10 genotype features, and suitable cancers were adaptively selected for model pre-training. In this way, the pre-trained model can learn valuable prior knowledge from other cancer types while reducing the biases. Results ATRCN chose pancreatic and stomach adenocarcinomas as the pre-training cancers, and the experiments indicated that our method improved the C-index of 3.8% by comparing with traditional transfer learning methods. The independent tests on three additional HCC datasets proved the robustness of our model. Based on the divided risk subgroups, we identified 10 HCC prognostic markers, including one new prognostic marker, TTC36 . Further wet experiments indicated that TTC36 is associated with the progression of liver cancer cells. Conclusion These results proved that our proposed deep-learning-based method for HCC prognosis prediction is robust, accurate, and biologically meaningful.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2021.692774
    DOI: 10.3389/fonc.2021.692774.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2649216-7
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  • 3
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    DataSheet_1.docx
    Frontiers Media SA ; 2019
    In:  Frontiers in Genetics Vol. 10 ( 2019-11-29)
    Details
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 10 ( 2019-11-29)
    Type of Medium: Online Resource
    ISSN: 1664-8021
    URL: Article
    URL: Article
    DOI: 10.3389/fgene.2019.01202
    DOI: 10.3389/fgene.2019.01202.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2606823-0
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  • 4
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    Predicting SARS-CoV-2 infection among hemodialysis patients using multimodal data
    Frontiers Media SA ; 2023
    In:  Frontiers in Nephrology Vol. 3 ( 2023-6-2)
    Details
    In: Frontiers in Nephrology, Frontiers Media SA, Vol. 3 ( 2023-6-2)
    Abstract: The coronavirus disease 2019 (COVID-19) pandemic has created more devastation among dialysis patients than among the general population. Patient-level prediction models for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are crucial for the early identification of patients to prevent and mitigate outbreaks within dialysis clinics. As the COVID-19 pandemic evolves, it is unclear whether or not previously built prediction models are still sufficiently effective. Methods We developed a machine learning (XGBoost) model to predict during the incubation period a SARS-CoV-2 infection that is subsequently diagnosed after 3 or more days. We used data from multiple sources, including demographic, clinical, treatment, laboratory, and vaccination information from a national network of hemodialysis clinics, socioeconomic information from the Census Bureau, and county-level COVID-19 infection and mortality information from state and local health agencies. We created prediction models and evaluated their performances on a rolling basis to investigate the evolution of prediction power and risk factors. Result From April 2020 to August 2020, our machine learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.75, an improvement of over 0.07 from a previously developed machine learning model published by Kidney360 in 2021. As the pandemic evolved, the prediction performance deteriorated and fluctuated more, with the lowest AUROC of 0.6 in December 2021 and January 2022. Over the whole study period, that is, from April 2020 to February 2022, fixing the false-positive rate at 20%, our model was able to detect 40% of the positive patients. We found that features derived from local infection information reported by the Centers for Disease Control and Prevention (CDC) were the most important predictors, and vaccination status was a useful predictor as well. Whether or not a patient lives in a nursing home was an effective predictor before vaccination, but became less predictive after vaccination. Conclusion As found in our study, the dynamics of the prediction model are frequently changing as the pandemic evolves. County-level infection information and vaccination information are crucial for the success of early COVID-19 prediction models. Our results show that the proposed model can effectively identify SARS-CoV-2 infections during the incubation period. Prospective studies are warranted to explore the application of such prediction models in daily clinical practice.
    Type of Medium: Online Resource
    ISSN: 2813-0626
    URL: Article
    DOI: 10.3389/fneph.2023.1179342
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
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  • 5
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    Table_1.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Plant Science Vol. 14 ( 2023-6-19)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 14 ( 2023-6-19)
    Abstract: Chinese chestnut ( Castanea mollissima ) is an important nut tree species, and its embryo is rich in sugar. We combined metabolomic and transcriptomic data to analyze metabolites and genes related to sugar in two Chinese chestnut cultivars at 60, 70, 80, 90 and 100 days after flowering (DAF). The soluble sugar content of high-sugar cultivar at maturity is 1.5 times that of low-sugar cultivar. Thirty sugar metabolites were identified in embryo, with the most dominant being sucrose. Analysis of the gene expression patterns revealed that the high-sugar cultivar promoted the conversion of starch to sucrose by up-regulating genes related to starch degradation and sucrose synthesis at 90-100 DAF. It also strongly increased the enzyme activity of SUS-synthetic, which may promote sucrose synthesis. Gene co-expression network analysis showed that ABA and peroxide were related to starch decomposition during Chinese chestnut ripening. Our study analyzed the composition and molecular synthesis mechanism of sugar in Chinese chestnut embryos, and provided a new insight into the regulation pattern of high sugar accumulation in Chinese chestnut nuts.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2023.1206585
    DOI: 10.3389/fpls.2023.1206585.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 6
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    Spatiotemporal characteristics and influencing factors of agricultural low-carbon economic efficiency in china
    Frontiers Media SA ; 2022
    In:  Frontiers in Environmental Science Vol. 10 ( 2022-9-12)
    Details
    In: Frontiers in Environmental Science, Frontiers Media SA, Vol. 10 ( 2022-9-12)
    Abstract: Developing low-carbon agriculture can effectively avoid the waste of natural resources, thus contributing to the long-term sustainability of agriculture. This study uses the Super-SBM model to measure agricultural low-carbon economic efficiency (ALEE) in China from 2000 to 2018, then analyzes the spatial-temporal evolution characteristics. Simultaneously, the influencing factors of ALEE are investigated using spatial econometric model. The results show that: (1) In terms of temporal evolution, the ALEE in most provinces is declined over time, with only a few provinces improving. The ALEE in China and the three regions all show an obvious “L” trend of decline first and then stability. (2) From the perspective of spatial differentiation, provinces in eastern region have higher ALEE, while those in central and western regions have lower ALEE. Hainan’s ALEE has an absolute advantage, while Shanxi is the worst. (3) China’s ALEE shows obvious spatial agglomeration characteristics of H-H and L-L agglomeration, which are further enhanced over time. The number of L-L agglomeration provinces gradually increases, indicating that China’s ALEE has not been improved significantly. (4) Economic growth level and Agricultural scientific and Technological progress have effectively improved the ALEE. However, Capital deepening, Government fiscal expenditure, Agricultural planting structure, and Agricultural disaster all have negative impacts. Rural electricity consumption also has a negative impact, but the impact is not significant. To accelerate the development of low-carbon agriculture, all regions must not only pursue a differentiated low-carbon agriculture development path, but also accelerate agricultural transformation, strengthen research and development, and popularize low-carbon agricultural technologies, reduce the input of traditional agricultural means of production, optimize the agricultural industrial structure, and adjust agricultural subsidy policies.
    Type of Medium: Online Resource
    ISSN: 2296-665X
    URL: Article
    DOI: 10.3389/fenvs.2022.980896
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2741535-1
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  • 7
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    Video_4.MP4
    Frontiers Media SA ; 2021
    In:  Frontiers in Medicine Vol. 8 ( 2021-10-1)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 8 ( 2021-10-1)
    Abstract: Background: Myofascial trigger points (MTrPs) injection has been effectively used for the management of chronic painful diseases. Latent MTrPs can induce autonomic nerve phenomena. In our clinic, we observed that allergic rhinitis (AR) symptoms significantly improved when latent MTrPs injection was performed for migraine. Objective: To compare the efficacy and safety between latent MTrPs injection and sublingual immunotherapy (SLIT) in patients with persistent, moderate to severe AR. Methods: This randomized controlled trial was conducted with 112 patients with AR. Patients were randomized to receive SLIT ( n = 56) or latent MTrPs injection. Total nasal symptom score (TNSS, n = 56), nasal symptoms, medication days, and adverse events were evaluated during the 9 months follow-up period after treatment in both groups. Results: Latent MTrPs injection significantly reduced TNSS to a greater level from baseline (from 8.36 ± 1.96 to 4.43 ± 2.18) than SLIT (from 8.66 ± 2.31 to 7.80 ± 2.47) at week 1 ( P & lt; 0.001), and sustained the improvement in symptoms throughout to month 9. Latent MTrPs showed statistically significant differences vs . SLIT for the TNSS reduction both at month 2 (6.59 ± 2.37 vs. 2.64 ± 2.38; p & lt; 0.001) and month 3 (4.59 ± 2.77 vs. 2.62 ± 2.43; p & lt;0.001). Latent MTrPs also showed a better improvement in the onset time of efficacy compared with SLIT. Adverse reactions were few and non-serious in both treatment groups. Conclusions: Latent MTrPs injection significantly improved symptoms and decreased symptom-relieving medication use in patients with AR and was well tolerated. Clinical Trials Registration: Chinese Clinical Trial Registry, ChiCTR1900020590. Registered 9 January 2019, http://www.chictr.org.cn/index.aspx .
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmed.2021.731254
    DOI: 10.3389/fmed.2021.731254.s001
    DOI: 10.3389/fmed.2021.731254.s002
    DOI: 10.3389/fmed.2021.731254.s003
    DOI: 10.3389/fmed.2021.731254.s004
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2775999-4
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  • 8
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    Image_3.JPEG
    Frontiers Media SA ; 2022
    In:  Frontiers in Cardiovascular Medicine Vol. 9 ( 2022-2-21)
    Details
    In: Frontiers in Cardiovascular Medicine, Frontiers Media SA, Vol. 9 ( 2022-2-21)
    Abstract: Familial hypertrophic cardiomyopathy (FHCM), an autosomal dominant disease, is caused by mutations in genes encoding cardiac sarcomeric proteins. E22K, a mutation in the myosin regulatory light chain sarcomere gene, is associated with the development of FHCM. However, the molecular mechanisms by which E22K mutation promotes septal hypertrophy are still elusive. The hypertrophic markers, including beta-myosin heavy chain, atrial natriuretic peptide and B-type natriuretic peptide, were upregulated, as detected by fluorescence quantitative PCR. The gene expression profiles were greatly altered in the left ventricle of E22K mutant mice. Among these genes, nuclear factor of activated T cells ( NFAT ) and protein kinase C-alpha ( PKC- α) were upregulated, and their protein expression levels were also verified to be elevated. The fibrosis markers, such as phosphorylated Smad and transforming growth factor beta receptor, were also elevated in transgenic E22K mice. After receiving 6 weeks of procedural exercise training, the expression levels of PKC-α and NFAT were reversed in E22K mouse hearts. In addition, the expression levels of several fibrosis-related genes such as transforming growth factor beta receptor 1, Smad4, and alpha smooth muscle actin in E22K mouse hearts were also reversed. Genes that associated with cardiac remodeling such as myocyte enhancer factor 2C, extracellular matrix protein 2 and fibroblast growth factor 12 were reduced after exercising. Taken together, our results indicate that exercise can improve hypertrophy and fibrosis-related indices in transgenic E22K mice via PKC-α/NFAT pathway, which provide new insight into the prevention and treatment of familial hypertrophic cardiomyopathy.
    Type of Medium: Online Resource
    ISSN: 2297-055X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fcvm.2022.808163
    DOI: 10.3389/fcvm.2022.808163.s001
    DOI: 10.3389/fcvm.2022.808163.s002
    DOI: 10.3389/fcvm.2022.808163.s003
    DOI: 10.3389/fcvm.2022.808163.s004
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2781496-8
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  • 9
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    Data_Sheet_1.pdf
    Frontiers Media SA ; 2022
    In:  Frontiers in Cardiovascular Medicine Vol. 9 ( 2022-3-17)
    Details
    In: Frontiers in Cardiovascular Medicine, Frontiers Media SA, Vol. 9 ( 2022-3-17)
    Abstract: Heart failure is characterized by the inability of the heart to pump effectively and generate proper blood circulation to meet the body’s needs; it is a devastating condition that affects more than 100 million people globally. In spite of this, little is known about the mechanisms regulating the transition from cardiac hypertrophy to heart failure. Previously, we identified a cardiomyocyte-enriched gene, CIP, which regulates cardiac homeostasis under pathological stimulation. Here, we show that the cardiac transcriptional factor GATA4 binds the promotor of CIP gene and regulates its expression. We further determined that both CIP mRNA and protein decrease in diseased human hearts. In a mouse model, induced cardiac-specific overexpression of CIP after the establishment of cardiac hypertrophy protects the heart by inhibiting disease progression toward heart failure. Transcriptome analyses revealed that the IGF, mTORC2 and TGFβ signaling pathways mediate the inhibitory function of CIP on pathologic cardiac remodeling. Our study demonstrates GATA4 as an upstream regulator of CIP gene expression in cardiomyocytes, as well as the clinical significance of CIP expression in human heart disease. More importantly, our investigation suggests CIP is a key regulator of the transition from cardiac hypertrophy to heart failure. The ability of CIP to intervene in the onset of heart failure suggests a novel therapeutic avenue of investigation for the prevention of heart disease progression.
    Type of Medium: Online Resource
    ISSN: 2297-055X
    URL: Article
    URL: Article
    DOI: 10.3389/fcvm.2022.857049
    DOI: 10.3389/fcvm.2022.857049.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2781496-8
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  • 10
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    DataSheet1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Pharmacology Vol. 12 ( 2021-10-18)
    Details
    In: Frontiers in Pharmacology, Frontiers Media SA, Vol. 12 ( 2021-10-18)
    Abstract: Mechanical ventilation is an indispensable life-support treatment for acute respiratory failure in critically ill patients, which is generally believed to involve uncontrolled inflammatory responses. Oxytocin (OT) has been reported to be effective in animal models of acute lung injury. However, it is not clear whether Oxytocin has a protective effect on ventilator-induced lung injury (VILI). Therefore, in this study, we aimed to determine whether OT can attenuate VILI and explore the possible mechanism of this protection. To this end, a mouse VILI model was employed. Mice were pretreated with OT 30 min before the intraperitoneal injection of saline or nigericin and ventilation for 4 h, after which they were euthanized. Pathological changes, lung wet/dry (W/D) weight ratio, myeloperoxidase (MPO) activity, the levels of inflammatory cytokines [i.e., interleukin (IL)-1β, IL-6, and IL-18] in lung tissues and bronchoalveolar lavage fluid (BALF), and expression of NLRP3, Toll-like receptor 4 (TLR4), caspase-1, nuclear factor (NF)-κB, and GSDMD in lung tissues were measured. OT treatment could reduce pathological injury, the W/D ratio, and MPO activity in VILI mice. Our data also indicated that OT administration alleviated the expression of TLR4/My-D88 and the activation of NF-κB, NLRP3, and caspase-1 in lung tissues from the VILI mice model. Furthermore, OT also decreased the levels of IL-1β, IL-6, and IL-18 in the bronchoalveolar lavage fluid. Moreover, the OT administration may alleviate the activation of GSDMD partially through its effects on the NLRP3-mediated pathway. Collectively, OT exerted a beneficial effect on VILI by downregulating TLR4-and NLRP3-mediated inflammatory pathways.
    Type of Medium: Online Resource
    ISSN: 1663-9812
    URL: Article
    URL: Article
    DOI: 10.3389/fphar.2021.722907
    DOI: 10.3389/fphar.2021.722907.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2587355-6
    SSG: 15,3
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