Association of Nutritional Intake with Physical Activity and Handgrip Strength in Individuals with Airflow Limitation by I Re Heo, Tae Hoon Kim, Jong Hwan Jeong, Manbong Heo, Sun Mi Ju, Jung-Wan Yoo, Seung Jun Lee, Yu Ji Cho, Yi Yeong Jeong, Jong Deog Lee, Ho Cheol Kim

“…However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. …”
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Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007–2018 by Chengcheng Wei, Qian Yang, Qian Yang, Jingke He, Yu Luo, Kun Han, Junkun Li, Shuai Su, Shuai Su, Jindong Zhang, Hongxing Wang, Hongxing Wang, Delin Wang

“…Machine learning with Shapley Additive Explanations (SHAP) was used to determine the relative importance of dietary factors. Sensitivity analysis was conducted to validate the stability of the results.ResultsA higher healthy dietary score was significantly associated with a reduced risk of kidney stone prevalence, as indicated by the Alternative Healthy Eating Index (AHEI) (OR = 0.76, 95% CI 0.69–0.84), the Dietary Approaches to Stop Hypertension Index (DASHI) (OR = 0.67, 95% CI 0.58–0.77), the Healthy Eating Index 2020 (HEI-2020) (OR = 0.80, 95% CI 0.72–0.89), and the Mediterranean Diet Index (MEDI) (OR = 0.81, 95% CI 0.73–0.89). …”
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Pulse pressure after thrombectomy predicts functional outcomes and mortality in acute ischemic stroke with large artery occlusion by Shandong Jiang, Zhongju Tan, Jianru Li, Peizheng Guo, Yuan Yuan, Jun Yu, Liang Xu, Xu Li, Xianyi Chen, Bing Fang, Lingling Yu, Jing Xu, Cong Qian, Chaohui Jing, Yunmei Yang

“…In this study, we systematically analyzed 12 post-procedure BP parameters from 826 acute ischemic stroke patients within 24 h after EVT; 587 cases were included in the final analysis. …”
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Effect of deterioration of swallowing functions on the frailty status in older adults: a longitudinal cohort study by En-Chih Weng, Yoko Hasegawa, Tasuku Yoshimoto, Ma. Therese Sta. Maria, Koutatsu Nagai, Naoko Sato, Kana Tokumoto, Kazuhiro Hori, Hiroshi Kusunoki, Hiromitsu Kishimoto, Ken Shinmura

“…In contrast, logistic regression analysis of frailty progression showed that impaired swallowing function was a significant explanatory variable (OR, 1.53; 95% CI: 1.04–2.21). …”
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Soluble galectin-4 in colorectal cancer is associated with tumor progression, but is not a predictor of the disease outcome by Elena Y. Yakunina, Olga V. Kovaleva, Ruslan A. Zukov, Alexey N. Gratchev, Sergey S. Salamatin, Sofya O. Kochkina, Zaman Z. Mammadli, Nikolay E. Kushlinskii

“…The galectin-4 levels were higher at advanced stages of the disease (p = 0.002) and in the presence of distant metastases (p 0.0001). Cox regression analysis showed that tumor size and distant metastases were independent prognostic factors (hazard ratio (HR) = 3.87; p = 0.0439; HR = 720.4; p = 0.0062, respectively) associated with decreased survival. …”
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INBRX-106: a hexavalent OX40 agonist that drives superior antitumor responses via optimized receptor clustering by William L Redmond, Yoshinobu Koguchi, Melissa J Kasiewicz, Annah S Rolig, Nisha Holay, Bryan Becklund, Anya Polovina, Sae Jeong Ahn, Brendan P Eckelman, Rashi Yadav, Thi Staebler, Noah D Simons, Yaiza Diaz de Durana

“…Costimulatory agonists like OX40 (CD134), a tumor necrosis factor receptor family member critical for T-cell survival and differentiation, have shown preclinical promise but limited clinical success due to suboptimal receptor activation. …”
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PLCH1 overexpression promotes breast cancer progression and predicts poor prognosis through the ERK1/2-EGR1 axis by Jing Li, Fenge Jiang, Congcong Wang, Ping Sun, Lei Song, Jiannan Liu

“…Differential expression analysis was performed using boxplots and statistical tests to assess significance. …”
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Predictors of myocardial fibrosis and loss of epicardial adipose tissue volume in the long-term period after myocardial infarction by O. L. Barbarash, O. V. Gruzdeva, T. B. Pecherina, O. E. Akbasheva, D. A. Borodkina, V. V. Kashtalap, V. N. Karetnikova, A. N. Kokov, N. K. Brel, Yu. A. Dyleva, E. V. Belik, E. G. Uchasova, E. E. Bychkova, A. A. Kuzmina

“…The data were analyzed using descriptive statistics, correlation and ROC analysis, and logistic regression (Statistica 9.0).Results. …”
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The influence of dietary choices: investigation of the relationship dietary inflammatory index and fetal growth restriction by Ayşe Gülçin Baştemur, İclal Sena Gezer, Burcu Kesikli, Atakan Tanaçan, Özgür Kara, Nuray Yazıhan, Dilek Şahin

“…The study aimed to investigate the correlation between maternal DII, total oxidant status (TOS), total antioxidant status (TAS), interleukin-6 (IL-6), interleukin-10 (IL-10), and tumor necrosis factor-alpha (TNF-α) levels in FGR-diagnosed pregnant women. …”
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Maturity of data interoperability cross-organizations in supporting the concept of one employment data at the ministry and regional government levels by Herpita Wahyuni, Dyah Mutiarin, Ulung Pribadi, Nur Syakiran Akmal Ismail, Eko Priyo Purnomo, Wahyudi Kumorotomo

“…This research uses a mixed-method research approach that examines preparedness, understanding, command style, and ethos in relation to the maturity of E-Government Interoperability across Organizations in Central and Regional Governments in Processing One Employment Data. Regression analysis and hypothesis testing are carried out using SEM-PLS (Structural Equation). …”
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The characteristics of new-onset myasthenia gravis after COVID-19 outbreak: a cross-sectional study by Yanzhen Huang, Yu Wu, Shaodan Zhou, Xianting Que, Ailing Jiang, Danli Shi, Ting Lu, Yanlan Chen, Ziqun Lin, Chao Liu, Yishuang Wen, Shuyi Zhang, Wen Huang

“…This study aimed to explore the clinical characteristics of new-onset MG patients after COVID-19 and analyze factors affecting their disease improvement. …”
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Construction and Validation of a Hospital Mortality Risk Model for Advanced Elderly Patients with Heart Failure Based on Machine Learning by Shang S, Wei M, Lv H, Liang X, Lu Y, Tang B

“…Among all the models, the extreme gradient boosting (XGB) model performed the best, with an area under the curve (AUC) value of 0.933, a sensitivity of 0.79, a specificity of 0.89, a recall of 0.79, and an F1 score of 0.59 on the validation set. The SHAP analysis showed that CRP, BMI, NT-ProBNP, D-dimer, and GSP were the main influencing factors for death.Conclusion: This study successfully constructed a prediction model for the in-hospital death risk of advanced elderly patients with HF, and the XGB model exhibited excellent prediction performance. …”
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Sustainable development of mortgage lending: economic challenges and prospects by J.S. Mukhamedov, T.S. Sokira, Z. Kuldasheva

“…Drawing on data from The Global Economy (2023), the study explores how mortgage programs in developed countries affect the ratio of banking sector assets to GDP, providing a global benchmark. A detailed analysis of mortgage trends from 2007 to 2023 reveals important patterns and correlations between macroeconomic factors and mortgage loan dynamics in both countries. …”
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Climate Variability and Farmers’ Perception in Southern Ethiopia by Befikadu Esayas, Belay Simane, Ermias Teferi, Victor Ongoma, Nigussie Tefera

“…The study applied a nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests to detect the magnitude and statistical significance of climate variability and binary logit regression model to find factors influencing farm households’ perceptions about climate variability over three agroecological zones (AEZs). …”
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A mixed method impact assessment of the use of aerial logistics to improve maternal health and emergencies outcomes in the Ashanti Region of Ghana by Pedro Kremer, Florence Haruna, Christina Briegleb, Maame Esi Amoah, Kenneth Fosu Oteng, Stephanie Boadi, Samuel Dwomoh, Adwoa Bentil, Emmanuel Tinkorang

“…Pre-exposure years were 2017–2020, and post-exposure years were 2021–2022. Statistical analysis involved univariate explorations, T-tests, ANOVAs, and Zero-Inflated Poisson regressions, adjusting for factors like poverty. …”
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Parental role in paediatric cancer treatment decision making at Tikur Anbessa Specialized Hospital, Ethiopia: A mixed method study by Daniel Betemariem, Leul Deribe, Aklil Hailu, Haileyesus Adam, Nataliya Berbyuk Lindström

“…Additionally, 11 in-depth interviews were conducted with selected parents. Logistic regression and thematic analysis were used to analyze the quantitative and qualitative data, respectively. …”
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Epidemiology of the global burden of atrial fibrillation among women of child-bearing age, 1990–2021: insights from the Global Burden of Disease Study 2021 by Shuwen Chen, Junpeng Xiong, Peiyang Zheng, Ronghui Yu

“…Age-standardized rates (ASRs) of incidence, prevalence, disability-adjusted life years (DALYs), and mortality rate were calculated from 1990 to 2021. Joinpoint regression and Bayesian age-period-cohort analysis were applied to assess temporal trends, regional disparities, and to project future AF burden. …”
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Breathing time: a longue-durée multidisciplinary study of respiratory illnesses and airborne diseases in Switzerland (16th–21st century CE) by Tobias Hofstetter, Aude Fauvel, Silke Grabherr, Negahnaz Moghaddam

“…This graphical presentation is a breakthrough in the field of RIAD research in Switzerland and further enabled to assess internal data coherence and trend evolutions by means of joinpoint regression analysis.Main results include the confirmation of the considerable impact of industrialization on the respiratory health of peri-alpine populations. …”
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Investigating the Relationship Between Nurses’ Attitudes About Old Age and Age Discrimination in Caring For the Elderly Hospitalized in Hospitals in Kashan City, Iran, in 2022 by Ameneh Baseri Arani, Mohammad Javad Tarrahi, Majid Rahimi

“…This research includes two questionnaires that measure attitudes about old age, namely the Kogan attitudes toward older people scale and measures of discriminatory practices against the elderly. To analyze the results using descriptive statistics (prevalence and average) and inferential statistical tests, including the Chi-square test, independent t test, and variance analysis with the Pearson correlation coefficient or the Spearman correlation coefficient, were employed. …”
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Dietary patterns derived by Gaussian graphical models and metabolic profiles among overweight and obese individuals by Reyhaneh Mokhtari Hemami, Mohammad Asghari-Jafarabadi, Mahdieh Abbasalizad Farhangi, Maedeh Alipour

“…GGM was utilized to explore the networks of participants’ dietary intake, and the association between these networks and risk factors related to MetS was assessed using logistic regression. …”
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