The mediating role of health anxiety on the relationship between health literacy, death anxiety and quality of life by Mahmoud Mohammadi, Azadeh Choobforoushzadeh, Yasser Rezapour Mirsaleh, Elahe Shirovi

“…Table2Direct Effects between Research Variables PT S.EDependentvariableIndependentvariable 0.000.000.005.26-3.86-8.170.24-0.2-0.40.060.160.09 Quality of life Health literacyDeath anxietyHealth anxiety  Table 2 shows that all relationships between variables were significant at the  95% confidence level according to T values ​​(P<0.05).  …”
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Prediction of Crops Cycle with Seasonal Forecasts to Support Decision-Making by Daniel Garcia, Nicolas Silva, João Rolim, Antónia Ferreira, João A. Santos, Maria do Rosário Cameira, Paula Paredes

“…Nevertheless, the forecasts captured the overall increasing temperature trend, interannual variability, and anomaly signals, but with marginal added value over climatological data. …”
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Galactomannan detection in sputum samples of patients with chronic obstructive pulmonary disease: A promising marker for diagnosis of chronic pulmonary aspergillosis? by Sabrieh Asadi Shahi Sarae, Masoud Aliyali, Vida Mortezaee, Hamidreza Jamaati, Hossein Asgarian Omran, Siavash Abedi, Hossein Mehravaran, Jamshid Yazdani Charati, Maryam Sadat Mirenayat, Mihan Pourabdollah, Kosar Najmi, Sabah Mayahi, Mona Ghazanfari, Ahmed Al-Harrasi, Mahdi Abastabar, Mohammad T. Hedayati, Abdullah M.S. Al Hatmi

“…Background and purpose: Diagnosing chronic pulmonary aspergillosis (CPA) is challenging due to nonspecific symptoms, variable radiological findings, and limited mycological evidences. …”
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Development of Women Resilience in the Workplace: A Solution to Break the Glass Ceiling by Farajallah Rahimi, Maral Ahmadi Arpanahi

“…To calculate convergent and divergent validity, we must calculate the values ​​of average variance extracted (AVE) and average squared common variance (ASV).Therefore, for convergent validity, the AVE value of the variables should be greater than 0.5, and for divergent validity, the AVE value of the variables should be greater than their ASV (Rahimi, 2017), which according to Table 1, the AVE value of each of the variables is greater than 0.5 and the AVE value is greater than It is from ASV that it can be said that measurement tools have construct validity. …”
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An Objective Injury Threshold for the Maximum Principal Strain Criterion for Brain Tissue in the Finite Element Head Model and Its Application by Yuting Zhang, Liqun Tang, Yiping Liu, Bao Yang, Zhenyu Jiang, Zejia Liu, Licheng Zhou

“…Although the finite element head model (FEHM) has been widely utilized to analyze injury locations and patterns in traumatic brain injury, significant controversy persists regarding the selection of a mechanical injury variable and its corresponding threshold. This paper aims to determine an objective injury threshold for maximum principal strain (MPS) through a novel data-driven method, and to validate and apply it. …”
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Tailoring Polymeric Scaffolds with <i>Buddleja globosa</i> Extract for Dual Antimicrobial and Biocompatible Wound Healing Applications by Ricardo Ceriani, Daniel A. Cherif-Pino, Pamela Pérez-Basáez, Marcela Escobar, Patricio Leyton, Caroline R. Weinstein-Oppenheimer, Daniel F. Moraga-Espinoza, Tania F. Bahamondez-Canas

“…A standardized <i>Buddleja globosa</i> Hope extract (BG-126), recognized for its therapeutic value, was incorporated into polymeric scaffolds with variable composition to explore their potential in promoting wound healing and controlling infections. …”
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Determinants of coinfection tuberculosis and HIV in prisons in Brazil by Nanci Michele Saita, Rubia Laine de Paula Andrade, Pedro Augusto Bossonário, Rafaele Oliveira Bonfim, Jordana de Almeida Nogueira, Antônio Ruffino Netto, Ricardo Alexandre Arcêncio, Tereza Cristina Scatena Villa, Aline Aparecida Monroe

“…The data were analyzed through frequency distribution and bivariate analysis, testing the association of the dependent variable (tuberculosis/HIV coinfection vs. tuberculosis/HIV non-coinfection) with independent variables (sociodemographic, clinical and diagnostics variables) by calculating the odds ratio and p-value. …”
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Prognostic factors for relapse in patients with clinical stage I testicular cancer: protocol for a Danish nationwide cohort study by Birgitte Grønkær Toft, Thomas Wagner, Birte Engvad, Jakob Lauritsen, Michael Kreiberg, Mikkel Bandak, Josephine Rosenvilde, Ib Jarle Christensen, Anette Pedersen Pilt, Daniel Berney, Gedske Daugaard

“…The available evidence on the prognostic value of the risk factors, however, is hampered by heterogeneity of the study populations included and variable reporting of the histopathological features. …”
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Conserved genome structure and phylogenetic insights for the heterogeneous subfamily of Convallarioideae (Asparagaceae) revealed from plastome data by Shao-De Wu, Ran Meng, Ze-Long Nie, Ming-Yang Song, Xing-Ru Chen, Jun Wen, Ying Meng

“…However, variations were observed in genome size, SSRs, and codon usage across the subfamily. Nine highly variable regions and positive selection genes were identified. …”
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Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma by Bo Lan, Zongyun He, Zhe Chen, Haibing Tao, Tao Liu, Jin Yang

“…Abstract Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to use multiple machine learning algorithms to exploring the significant factors associated with synchronous BM in these patients. …”
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The Partial Pressure of CO2 and Fluxes of CO2 in Semarang Bay, Indonesia by Max Rudolf Muskananfola, Nurul Latifah, Agus Hartoko, Sigit Febrianto, Johan Christian Winterwerp

“…The flux of carbon dioxide at the sea surface between seawater and atmosphere is essential for mitigating atmospheric CO2.  The aims of this study were to assess the variation of CO2 partial pressure seawater (pCO2sea) and CO2 flux and to analyse the water quality variable which has the larger influence on CO2 flux in the waters of Semarang Bay. …”
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Development and validation of the machine learning model for acute exacerbation of chronic obstructive pulmonary disease prediction based on inflammatory biomarkers by Ye Zhu, Meng Wang, Xin-Nan Gu, Cen Wang, Su-Min Deng

“…AECOPD risk increased significantly with rising MLR and NLR values, while ELR showed a negative correlation with AECOPD risk. …”
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Evaluation of the Young, Deadly, Syphilis Free multi-media campaign in remote Australia. by Belinda D'Costa, Roanna Lobo, Amanda Sibosado, Justine E Leavy, Gemma Crawford, James Ward

“…A 22-item young people survey assessed campaign awareness, exposure, message recognition and diagnostics (proximal variables); along with intended behaviour and knowledge and attitudes (mediator variables). …”
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TEENAGE PREGNANCY PREDICTION INDEX DURING THE ONLINE LEARNING PERIOD OF THE COVID-19 PANDEMIC by Eny Qurniyawati, Santi Martini, Fariani Syahrul, Jayanti Dian Eka Sari, Rahayu Lubis, Nayla Mohamed Gomaa Nasr

“…Introduction: The impact of the pandemic on adolescents' lives showed that 55.1% stress and 40% anxiety due to online learning along with an increase in teenage pregnancy. Aims: To determine the predictive index of risk variables for teen pregnancy throughout the COVID-19 pandemic's online learning period. …”
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Mechanical properties and damage characterization of cracked granite after cyclic temperature action by Xiankai Bao, Lingyu Wang, Guangqin Cui, Jianlong Qiao, Baolong Tian, Shunjia Huang, Lizhi Wang

“…The damage variable quickly reached its maximum, and the development of internal microcracks in the specimen is highly orderly. …”
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Improving pediatric care in Uganda with a digital platform and quality improvement initiative: A retrospective review of Smart Triage + QI. by Rebecca Goertzen, Yashodani Pillay, James Karugaba, Ivan Aine Aye Ishebukara, Ahmad Asdo, Dustin Dunsmuir, Justine Behan, Charly Huxford, Stefanie K Novakowski, Fredson Tusingwire, Ronald Kasyaba, Gloria Kakuru, John Khisa, Stephen Businge, Mike Kyewalyanga, Niranjan Kissoon, J Mark Ansermino

“…The trajectories of the variables were assessed using linear regression with time as the explanatory variable.…”
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Microbiological hazards associated with the use of water in the post‐harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVH). Part 3 (Fr... by EFSA BIOHAZ Panel (EFSA Panel on Biological Hazards), Ana Allende, Avelino Alvarez‐Ordóñez, Valeria Bortolaia, Sara Bover‐Cid, Alessandra De Cesare, Wietske Dohmen, Laurent Guillier, Lieve Herman, Liesbeth Jacxsens, Lapo Mughini‐Gras, Maarten Nauta, Jakob Ottoson, Luisa Peixe, Fernando Perez‐Rodriguez, Panagiotis Skandamis, Elisabetta Suffredini, Jen Banach, Bin Zhou, Maria Teresa daSilva Felício, Laura Martino, Winy Messens, Angela Botteon

“…Industrial data indicated that the fresh‐whole FVH sector is characterised by very variable operational cycle duration (between 8 and 900 h), large product volumes (e.g. more than 6000 tonnes) and process water at 2.8–25.0°C. …”
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Selenization Optimization of Preparation Process of Polysaccharide from Dendrobium huoshanense and Its Inhibitory Effect on α-Amylase by Wanxue CAO, Jiao LI, Qiang TAO, Xuanxuan FAN, Jiting LU, Naifu CHEN, Naidong CHEN

“…Objectives: This study aimed to optimize the selenization process of polysaccharides derived from Dendrobium huoshanense (DHP) and to investigate the inhibitory effects and mechanisms of both DHP and selenium-enriched DHP (Se-DHP) on α-amylase activity. …”
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THE ROLE OF INTRATUMORAL DENDRITIC CELLS IN THE PROGRESSION OF SQUAMOUS CELL CARCINOMAS by L. N. Bondar, L. A. Tashireva, O. V. Savenkova, E. L. Choynzonov, V. M. Perelmuter

“…The aim of the study was to summarize data on the role of tumor-associated dendritic cells (DC) in the formation of squamous cell carcinoma microenvironment, their participation in the development of immune inflammatory responses in the tumor stroma and relation to tumor progression.Material and Methods. …”
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Influence of transfusions, hemodialysis and extracorporeal life support on hyperferritinemia in critically ill patients. by Cornelia Knaak, Friederike S Schuster, Peter Nyvlt, Patrick Heeren, Claudia Spies, Thomas Schenk, Paul La Rosée, Gritta Janka, Frank M Brunkhorst, Gunnar Lachmann

“…To identify the influence of transfusions, hemodialysis, and ECLS on ferritin change, multivariable linear regression analysis with ferritin change between two measurements as dependent variable was performed.<h4>Results</h4>A total of 268 patients was analyzed. …”
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