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  • Frontiers Media SA  (3)
  • 1
    Online Resource
    Online Resource
    Table_1.DOCX
    Frontiers Media SA ; 2022
    In:  Frontiers in Aging Neuroscience Vol. 13 ( 2022-1-18)
    Details
    In: Frontiers in Aging Neuroscience, Frontiers Media SA, Vol. 13 ( 2022-1-18)
    Abstract: We aimed to examine the association between serum cotinine and leukocyte telomere length (LTL) and the intermediate effects of body mass index (BMI) and C-reactive protein (CRP) on modulating the association. This study included 4,047 adults from the 1999 to 2002 National Health and Nutrition Examination Survey. In the combined sample, after adjusting for age, race, sex, physical activity, and alcohol use, the total effect of serum cotinine on LTL was significant (standardized regression coefficient, β = −0.049, p = 0.001) without BMI and CRP included in the model. With inclusion of BMI but without CRP in the model, the direct effect of cotinine on LTL in its absolute value increased to β = −0.053 ( p & lt; 0.001), and the suppression effect of BMI was estimated at 8.8%. With inclusion of CRP but without BMI in the model, the direct effect of cotinine on LTL in its absolute value decreased to β = −0.040 ( p = 0.008), and the mediation effect of CRP was estimated at 16.9%. With inclusion of both BMI and CRP in the model, BMI and CRP still had significant suppression and mediation effects, respectively, on the cotinine-LTL association. These findings suggest that weight and inflammation have different roles in the inverse association between serum cotinine and LTL.
    Type of Medium: Online Resource
    ISSN: 1663-4365
    URL: Article
    URL: Article
    DOI: 10.3389/fnagi.2021.827465
    DOI: 10.3389/fnagi.2021.827465.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2558898-9
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  • 2
    Online Resource
    Online Resource
    Table_1.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Oncology Vol. 13 ( 2023-2-23)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 13 ( 2023-2-23)
    Abstract: Patients with tumors generally present with accompanying activation of the coagulation system, which may be related to tumor stage. To our knowledge, few studies have examined the activation of the coagulation system in reference to lymph node metastasis within gastric cancer. This study aimed to investigate the correlation between multiple coagulation-related factors and lymph node metastasis in patients with gastric cancer after excluding the influence of tumor T stage. Materials and methods We retrospectively evaluated the relationship between lymph node metastasis and coagulation-related factors in 516 patients with T4a stage gastric cancer. We further analyzed influencing factors for lymph node metastasis and verified the predictive value of maximum amplitude (MA, a parameter of thromboelastography which is widely used to assess the strength of platelet-fibrinogen interaction in forming clots) in reference to lymph node metastasis. Results Platelet counts (P=0.011), fibrinogen levels (P=0.002) and MA values (P=0.006) were statistically significantly higher in patients with T4a stage gastric cancer presenting with lymph node metastasis than in those without lymph node metastasis. Moreover, tumor N stage was statistically significantly and positively correlated with platelet count (P & lt;0.001), fibrinogen level (P=0.003), MA value (P & lt;0.001), and D-dimer level (P=0.010). The MA value was an independent factor for lymph node metastasis (β=0.098, 95% CI: 1.020-1.193, P=0.014) and tumor N stage (β=0.059, 95% CI: 0.015-0.104, P=0.009), and could be used to predict the presence of lymph node metastasis in patients with gastric cancer (sensitivity 0.477, specificity 0.783, P=0.006). The independent influencing factors for MA value mainly included platelet levels, fibrinogen levels, D-dimer and hemoglobin levels; we found no statistically significant correlations with tumor diameter, tumor area, and other evaluated factors. Conclusion We conclude that MA value is an independent influencing factor for lymph node metastasis and tumor N stage in patients with T4a stage gastric cancer. The MA value has important value in predicting the presence or absence of lymph node metastasis in patients with gastric cancer. Clinical trial registration http://www.chictr.org.cn , identifier ChiCTR2200064936.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2023.1099857
    DOI: 10.3389/fonc.2023.1099857.s001
    DOI: 10.3389/fonc.2023.1099857.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2649216-7
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  • 3
    Online Resource
    Online Resource
    DataSheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Marine Science Vol. 9 ( 2022-9-13)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 9 ( 2022-9-13)
    Abstract: Sea ice recognition is one of the main tasks for sea ice monitoring in the Arctic and is also applied for the detection of other ocean phenomena. The Surface Wave Investigation and Monitoring (SWIM) instrument, as an innovative remote sensor that operates at multiple small incidence angles, is different from existing sensors with moderate and normal incidence modes for sea ice monitoring. Sea ice recognition at small incidence angles has rarely been studied. Moreover, SWIM uses a discrimination flag of sea ice and sea water to remove sea ice from sea wave products. Therefore, this research focuses on sea ice recognition in the Arctic based on SWIM data from October 2020 to April 2021. Eleven features are first extracted, and applied for the analysis of the waveform characteristics using the cumulative probability distribution (CPD) and mutual information measurement (MIM). Then, random forest (RF), k-nearest neighbor (KNN) and support vector machine (SVM) classifiers are built, and their abilities of sea ice recognition are assessed. The optimal classifier is the KNN method with Euclidean distance and k equal to 11. Feature combinations are also used to separate sea ice and sea water based on the KNN method to select the optimal combination. Thus, the optimal classifier-feature assembly at each small incidence angle is established, and the highest overall accuracy reaches 97.1%. Moreover, the application of the optimal classifier–feature assemblies is studied, and its performance is fairly good. These assemblies yield high accuracies in the short- and long-term periods of sea ice recognition, and the overall accuracies are greater than 93.1%. So, the proposed method satisfies the SWIM requirement of removing the sea ice effect. Moreover, sea ice extents and edges can be extracted from SWIM sea ice recognition results at a high level of precision greater than 94.8%. As a result, the optimal classifier–feature assemblies based on SWIM data express the effectiveness of the SWIM approach in sea ice recognition. Our work not only highlights the new sea ice monitoring technology of remote sensing at small incidence angles, but also studies the application of SWIM data in sea ice services.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    URL: Article
    DOI: 10.3389/fmars.2022.986228
    DOI: 10.3389/fmars.2022.986228.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2757748-X
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