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  • 1
    Online Resource
    Online Resource
    Using Machine Learning Methods to Predict Bone Metastases in Breast Infiltrating Ductal Carcinoma Patients
    Frontiers Media SA ; 2022
    In:  Frontiers in Public Health Vol. 10 ( 2022-7-6)
    Details
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2022-7-6)
    Abstract: Breast cancer (BC) was the most common malignant tumor in women, and breast infiltrating ductal carcinoma (IDC) accounted for about 80% of all BC cases. BC patients who had bone metastases (BM) were more likely to have poor prognosis and bad quality of life, and earlier attention to patients at a high risk of BM was important. This study aimed to develop a predictive model based on machine learning to predict risk of BM in patients with IDC. Six different machine learning algorithms, including Logistic regression (LR), Naive Bayes classifiers (NBC), Decision tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), and Extreme gradient boosting (XGB), were used to build prediction models. The XGB model offered the best predictive performance among these 6 models in internal and external validation sets (AUC: 0.888, accuracy: 0.803, sensitivity: 0.801, and specificity: 0.837). Finally, an XGB model-based web predictor was developed to predict risk of BM in IDC patients, which may help physicians make personalized clinical decisions and treatment plans for IDC patients.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    DOI: 10.3389/fpubh.2022.922510
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2711781-9
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  • 2
    Online Resource
    Online Resource
    Spatial-temporal transformer network for multi-year ENSO prediction
    Frontiers Media SA ; 2023
    In:  Frontiers in Marine Science Vol. 10 ( 2023-3-13)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 10 ( 2023-3-13)
    Abstract: The El Niño-Southern Oscillation (ENSO) is a quasi-periodic climate type that occurs near the equatorial Pacific Ocean. Extreme periods of this climate type can cause terrible weather and climate anomalies on a global scale. Therefore, it is critical to accurately, quickly, and effectively predict the occurrence of ENSO events. Most existing research methods rely on the powerful data-fitting capability of deep learning which does not fully consider the spatio-temporal evolution of ENSO and its quasi-periodic character, resulting in neural networks with complex structures but a poor prediction. Moreover, due to the large magnitude of ocean climate variability over long intervals, they also ignored nearby prediction results when predicting the Niño 3.4 index for the next month, which led to large errors. To solve these problem, we propose a spatio-temporal transformer network to model the inherent characteristics of the sea surface temperature anomaly map and heat content anomaly map along with the changes in space and time by designing an effective attention mechanism, and innovatively incorporate temporal index into the feature learning procedure to model the influence of seasonal variation on the prediction of the ENSO phenomenon. More importantly, to better conduct long-term prediction, we propose an effective recurrent prediction strategy using previous prediction as prior knowledge to enhance the reliability of long-term prediction. Extensive experimental results show that our model can provide an 18-month valid ENSO prediction, which validates the effectiveness of our method.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    DOI: 10.3389/fmars.2023.1143499
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2757748-X
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  • 3
    Online Resource
    Online Resource
    A residual network with geographical and meteorological attention for multi-year ENSO forecasts
    Frontiers Media SA ; 2023
    In:  Frontiers in Marine Science Vol. 10 ( 2023-6-28)
    Details
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 10 ( 2023-6-28)
    Abstract: As global temperatures continue to rise, extreme weather phenomena such as El Niño and the Southern Oscillation (ENSO) near the equatorial Pacific Ocean are occurring more frequently and leading to tropical cyclones, droughts, and a series of extreme weather disasters. Accurately predicting ENSO in advance can greatly reduce the serious damage to human society, economy, and ecological environment. However, existing methods often neglect the data relation between geographical regions and meteorological factors, hindering the accuracy of ENSO prediction. Methods To overcome this problem, we propose a residual network with geographical and meteorological attention to capture important geographical information and explore the spatio-temporal correlation of different meteorological factors. Specifically, we propose two main attention modules: (1) the Geographical Semantic Information Enhancement Module (GSIEM), which selectively attends to important geographical regions and filters out irrelevant noise through a spatial-axis attention map, and (2) the Meteorological Factors Discriminating Enhancement Module (MFDEM), which aims to learn the spatio-temporal dependency of different meteorological factors using a learnable channel-axis weight map. We then integrate our proposed two attention modules into the backbone using residual connection, enhancing the model's prediction ability. Results We conducted extensive experimental comparisons and ablation studies to evaluate the performance of our proposed method. The results show that our method outperforms existing state-of-the-art methods in ENSO prediction, with a significant improvement in prediction accuracy. Discussion Our proposed method effectively captures geographical and meteorological information, facilitating accurate ENSO prediction. The attention modules we proposed can effectively filter out irrelevant noise and learn the spatio-temporal dependency of different meteorological factors, contributing to the superior performance of our model. Overall, our study provides a novel approach for ENSO prediction and has great potential for practical applications.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    URL: Article
    DOI: 10.3389/fmars.2023.1195445
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2757748-X
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  • 4
    Online Resource
    Online Resource
    Sigmoido-vesical fistula secondary to sigmoid colon cancer presenting as urinary tract infection with Lactococcus lactis: A case report
    Frontiers Media SA ; 2023
    In:  Frontiers in Oncology Vol. 13 ( 2023-3-1)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 13 ( 2023-3-1)
    Abstract: A colovesical fistula is a pathological communication between the colon and bladder. The symptoms include pneumaturia, fecaluria, and a lower urinary tract infection. The diagnosis is based on clinical symptoms, but the symptoms are not specific. Therefore, confirming the diagnosis is challenging. Urine cultures performed in patients with colovesical fistulas usually show growth of Escherichia coli or mixed growth of bowel organisms. Urinary tract infections caused by Lactococcus lactis are very rare, as it is rarely considered pathogenic in humans. We report the case of a 70-year-old woman who presented with symptoms of a recurrent urinary tract infection. Urine cultures were positive for L. lactis . Abdominopelvic computed tomography (CT) revealed focal thickening of the bladder wall and gas in the bladder. Cystoscopic examination and colonoscopy revealed sigmoid colon cancer and a sigmoido-vesical fistula. Laparoscopic surgical treatment was done. The patient recovered and was discharged 3 weeks later without chemoradiotherapy. On follow-up after 6 months, the patient was asymptomatic and stable. To our knowledge, this is the second reported case of L. lactis infection of the urinary tract and the first reported case in adults. L. lactis infection usually indicates the presence of serious underlying diseases such as malignancies, uncontrolled diabetes, and organ failure.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    DOI: 10.3389/fonc.2023.1054978
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2649216-7
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  • 5
    Online Resource
    Online Resource
    A Bibliometric Analysis of Publications on Spinal Cord Injury Treatment With Glucocorticoids Using VOSviewer
    Frontiers Media SA ; 2022
    In:  Frontiers in Public Health Vol. 10 ( 2022-8-8)
    Details
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2022-8-8)
    Abstract: Spinal cord injury (SCI) has devastating physical and social consequences for patients. Systemic administration of methylprednisolone (MP) at a higher dosage though can reduce neurological deficits following acute SCI. Still, this treatment regimen is controversial, owing to the apparent dose-related side effects and relatively minor improvement in neurological function. Therefore, this study aimed at the bibliometric analysis of published literature related to SCI treatment, which may lead to future research trends. Methods The literature published relating to SCI and using glucocorticoids for its treatment between 1982 and 2022 was collected and scanned in the Web of Science collection database using the keywords glucocorticoid, dexamethasone, MP, corticosteroids, and SCI, followed by using VOSviewer for bibliometric analysis of these articles. Results A total of 1,848 published articles and 7,448 authors on SCI and glucocorticoid usage were identified. The SCI total link strength accounts for 1,341, and MP for 762 has a strong link to neuroprotection and inflammation. The mean citation count for the top 20 most-cited articles was 682 (range: 358–1,828), where most of these were descriptive studies having focused on clinical features. The Journal of Neurotrauma was the highest-ranked journal with 6,010 citations. A total of 69 articles were published by Michael G Fehlings from the University of Toronto with 6,092 citations. The University of Toronto has published 90-related manuscripts with 7,632 citations. In contrast, 800 articles were published in the United States, with 39,633 citations and total link strength of 5,714. The second-ranked country was China, with 241 published articles and 3,403 citations. Conclusions The research published on applying MP in treating SCI has increased with time. Although the United States has made a significant global contribution to this important field of research, it requires rigorous clinical trials designed to verify the therapeutic role of MP in SCI and its appropriate dosage to find solutions for neurological recovery.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    DOI: 10.3389/fpubh.2022.907372
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2711781-9
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  • 6
    Online Resource
    Online Resource
    Generation and Comprehensive Analysis of Host Cell Interactome of the PA Protein of the Highly Pathogenic H5N1 Avian Influenza Virus in Mammalian Cells
    Frontiers Media SA ; 2017
    In:  Frontiers in Microbiology Vol. 8 ( 2017-04-28)
    Details
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 8 ( 2017-04-28)
    Type of Medium: Online Resource
    ISSN: 1664-302X
    URL: Article
    DOI: 10.3389/fmicb.2017.00739
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2017
    detail.hit.zdb_id: 2587354-4
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  • 7
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    Online Resource
    Risk factors in the development of gastric adenocarcinoma in the general population: A cross-sectional study of the Wuwei Cohort
    Frontiers Media SA ; 2023
    In:  Frontiers in Microbiology Vol. 13 ( 2023-1-12)
    Details
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 13 ( 2023-1-12)
    Abstract: Several risk factors have been identified for the development of gastric adenocarcinoma (GAC), where the control group was usually a healthy population. However, it is unclear at what stage known risk factor exert their influence toward the progression to cancer. Based on the Wuwei Cohort, we enrolled 1,739 patients with chronic non-atrophic gastritis (no-CAG), 3,409 patients with chronic atrophic gastritis (CAG), 1,757 patients with intestinal metaplasia (IM), 2,239 patients with low-grade dysplasia (LGD), and 182 patients with high-grade dysplasia (HGD) or GAC to assess the risk factors between each two consecutive stages from no-CAG to GAC/HGD using adjusted logistic regression. We found that different groups of risk factors were associated with different stages. Age, occupation of farmer, low annual family income, Helicobacter pylori ( H. pylori ) infection, drinking, eating hot food, histories of gastritis and peptic ulcer were associated with the development of CAG. Age, illiteracy, H. pylori infection, smoking, eating hot food, eating quickly, and histories of gastritis and gallbladder diseases were associated with the progression to IM from CAG. Male, occupation of farmer and history of peptic ulcer were associated with the development of LGD from IM. Age, male and polyp history appeared to be risk factors associated with the development of GAC/HGD from LGD. In conclusion, it seems that most risk factors function more as a set of switches that initiated the GAC carcinogenesis. H. Pylori eradication and control of other risk factors should be conducted before IM to decrease the incidence of GAC.
    Type of Medium: Online Resource
    ISSN: 1664-302X
    URL: Article
    DOI: 10.3389/fmicb.2022.1024155
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2587354-4
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  • 8
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    Data_Sheet_1.PDF
    Frontiers Media SA ; 2023
    In:  Frontiers in Nutrition Vol. 10 ( 2023-2-27)
    Details
    In: Frontiers in Nutrition, Frontiers Media SA, Vol. 10 ( 2023-2-27)
    Abstract: Previous studies have shown that both hand grip strength (HGS) and the modified Glasgow Prognostic Score (mGPS) are associated with poor clinical outcomes in patients with liver cancer. In spite of this, no relevant studies have been conducted to determine whether the combination of HGS and mGPS can predict the prognosis of patients with liver cancer. Accordingly, this study sought to explore this possibility. Methods This was a multicenter study of patients with liver cancer. Based on the optimal HGS cutoff value for each sex, we determined the HGS cutoff values. The patients were divided into high and low HGS groups based on their HGS scores. An mGPS of 0 was defined as low mGPS, whereas scores higher than 0 were defined as high mGPS. The patients were combined into HGS-mGPS groups for the prediction of survival. Survival analysis was performed using Kaplan–Meier curves. A Cox regression model was designed and adjusted for confounders. To evaluate the nomogram model, receiver operating characteristic curves and calibration curves were used. Results A total of 504 patients were enrolled in this study. Of these, 386 (76.6%) were men (mean [SD] age, 56.63 [12.06] years). Multivariate analysis revealed that patients with low HGS and high mGPS had a higher risk of death than those with neither low HGS nor high mGPS (hazard ratio [HR],1.50; 95% confidenc e interval [CI],1.14–1.98; p  = 0.001 and HR, 1.55; 95% CI, 1.14–2.12, p  = 0.001 respectively). Patients with both low HGS and high mGPS had 2.35-fold increased risk of death (HR, 2.35; 95% CI, 1.52–3.63; p   & lt; 0.001). The area under the curve of HGS-mGPS was 0.623. The calibration curve demonstrated the validity of the HGS-mGPS nomogram model for predicting the survival of patients with liver cancer. Conclusion A combination of low HGS and high mGPS is associated with poor prognosis in patients with liver cancer. The combination of HGS and mGPS can predict the prognosis of liver cancer more accurately than HGS or mGPS alone. The nomogram model developed in this study can effectively predict the survival outcomes of liver cancer.
    Type of Medium: Online Resource
    ISSN: 2296-861X
    URL: Article
    URL: Article
    DOI: 10.3389/fnut.2023.1062117
    DOI: 10.3389/fnut.2023.1062117.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2776676-7
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  • 9
    Online Resource
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    DataSheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Oncology Vol. 12 ( 2022-7-11)
    Details
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-7-11)
    Abstract: Cachexia is one of the most common complications affecting lung cancer patients that seriously affects their quality-of-life and survival time. This study aimed to analyze the predictors and prognostic factors of lung cancer cachexia as well as to develop a convenient and accurate clinical prediction tool for oncologists. Methods In this multicenter cohort study, 4022 patients with lung cancer were retrospectively analyzed. The patients were randomly categorized into training and verification sets (7:3 ratio). Univariate and multivariate logistic regression analyses were performed to determine the risk factors of cachexia in patients with lung cancer. Cox regression analysis was applied to determine independent prognostic factors in the patients with lung cancer cachexia. Meanwhile, two nomograms were established and evaluated by time-dependent receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Results Stage, serum albumin, ALI, anemia, and surgery were independent risk factors for cachexia in patients with lung cancer. Patients with lung cancer cachexia have a shorter survival time. Sex, stage, serum albumin, ALI, KPS score, and surgery served as independent prognostic factors for patients with lung cancer cachexia. The area under the curves (AUCs) of diagnostic nomogram in the training and validation sets were 0.702 and 0.688, respectively, the AUCs of prognostic nomogram in the training set for 1-, 3-, and 5-year were 0.70, 0.72, and 0.75, respectively, while in the validation set the AUCs were 0.71, 0.75, and 0.79, respectively. The calibration curves and DCA of the two nomograms were consistent and the clinical benefit rate was high. Conclusion Cachexia brings an additional economic burden and worsens the prognosis of lung cancer patients. The two nomograms can accurately screen and predict the probability of occurrence of cachexia in lung cancer and the prognosis of patients with lung cancer cachexia, and guide clinical work.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    URL: Article
    URL: Article
    DOI: 10.3389/fonc.2022.890745
    DOI: 10.3389/fonc.2022.890745.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 10
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    DataSheet_1.docx
    Frontiers Media SA ; 2023
    In:  Frontiers in Immunology Vol. 14 ( 2023-3-30)
    Details
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 14 ( 2023-3-30)
    Abstract: Colorectal cancer (CRC) is among the most common malignant cancers worldwide, and its development is influenced by inflammation, nutrition, and the immune status. Therefore, we combined C-reactive protein (CRP), albumin, and lymphocyte, which could reflect above status, to be the CRP-albumin-lymphocyte (CALLY) index, and evaluated its association with overall survival (OS) in patients with CRC. Methods The clinicopathological and laboratory characteristics of 1260 patients with CRC were collected from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. Cox regression analysis was performed to assess the association between the CALLY index and OS. A nomogram including sex, age, the CALLY index and TNM stage was constructed. The Concordance Index (C-index) was utilized to evaluate the prognostic value of the CALLY index and classical CRC prognostic factors, such as modified Glasgow prognostic score (mGPS), neutrocyte to lymphocyte ratio (NLR), systemic immune inflammation index (SII), and platelet to lymphocyte ratio (PLR), as well as to assess the prognostic value of the nomogram and TNM stage. Results Multivariate Cox regression analyses demonstrated that the CALLY index was independently associated with OS in patients with CRC [Hazard ratio (HR) = 0.91, 95% confidence interval (CI) = 0.87-0.95, P & lt;0.001]. The CALLY index showed the highest prognostic value (C-index = 0.666, 95% CI = 0.638-0.694, P & lt;0.001), followed by mGPS, NLR, SII, and PLR. The nomogram demonstrated higher prognostic value (C-index = 0.784, 95% CI = 0.762-0.807, P & lt;0.001) than the TNM stage. Conclusion The CALLY index was independently associated with OS in patients with CRC and showed higher prognostic value than classical CRC prognostic factors. The nomogram could provide more accurate prognostic prediction than TNM stage.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    URL: Article
    URL: Article
    DOI: 10.3389/fimmu.2023.1131496
    DOI: 10.3389/fimmu.2023.1131496.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2606827-8
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