Decreased Frequencies of Th17 and Tc17 Cells in Patients Infected with Avian Influenza A (H7N9) Virus by Jiaqi Bao, Dawei Cui, Xiaochen Wang, Qianda Zou, Dejian Zhao, Shufa Zheng, Fei Yu, Li Huang, Yuejiao Dong, Xianzhi Yang, Guoliang Xie, Weizhen Chen, Yu Chen

“…Taken together, our results indicate immune disorder in acute H7N9 infection and a restored Th17 and Tc17 cell frequency might serve as a biomarker for predicting recovery in patients infected with this virus.…”
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Opposite outcomes of triglyceride-glucose index and associated cardiovascular mortality risk in type 2 diabetes mellitus participants by different obesity criteria by Hui Huang, Jing Tian, Jiahui Xu, Qingguang Chen, Mengjie Cai, Hao Lu, Fan Gong

“…A totally opposite relationship appeared between TyG index and CVD mortality based on how obesity was defined using BMI or WC in the T2DM participants, suggesting a reevaluation of BMI’s accuracy in predicting mortality risk.…”
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Flunarizine as a Candidate for Drug Repurposing Against Human Pathogenic Mammarenaviruses by Chukwudi A. Ofodile, Ikemefuna C. Uzochukwu, Fortunatus C. Ezebuo, InnocentMary Ejiofor, Mercy Adebola, Innocent Okpoli, Beatrice Cubitt, Haydar Witwit, Chetachi B. Okwuanaso, Ngozi Onyemelukwe, Juan Carlos de la Torre

“…Our in silico docking screen identified five drugs (dexamethasone, tadalafil, mefloquine, ergocalciferol, and flunarizine) with strong predicted binding affinity to LASV proteins involved in the formation of the vRNP. …”
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The future of plant lectinology: Advanced technologies and computational tools by Vinicius J.S. Osterne, Kyria S. Nascimento, Benildo S. Cavada, Els J.M. Van Damme

“…Additionally, computational methods—including molecular docking, molecular dynamics simulations, and machine learning pipelines—support predictions of lectin structures and binding properties, underpinning experimental efforts. …”
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Assessment of ozone impact on forest vegetation using visible foliar injury, AOT40F exposure index and MDA concentration in two meteorologically contrasting years by Radek Novotný, Leona Vlasáková, Vít Šrámek, Václav Buriánek, Nina Benešová

“…The findings suggest that the AOT40F capability for predicting damage to vegetation is limited and highlight the importance of future research focusing on stomatal O3 flux-based approaches.…”
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Validation of <i>Monilinia fructicola</i> Putative Effector Genes in Different Host Peach (<i>Prunus persica</i>) Cultivars and Defense Response Investigation by Lucia Landi, Annamaria Lucrezia D’Ortenzio, Sarah Mojela Makau, Rita Milvia De Miccolis Angelini, Gianfranco Romanazzi

“…<i>M. fructicola</i> putative virulence factors have been predicted by genome investigations. The pathogen interaction with the host was validated. …”
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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

“…This study proposes a machine learning-based approach for predicting the level of students' comprehension with regard to a certain topic. …”
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Axial Compression Behavior of Novel Latticed Columns with CFST Tubes and Corrugated Steel Plates for Industrial Structures by Xuan Zhao, Ningning Zhang, Zhaohui Hu, Xian Li, Ying Nie, Jun Liu

“…Furthermore, a model for predicting the axial compression bearing capacity of latticed columns with CFST tubes and corrugated steel plates was proposed.…”
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Impact of Frequency Heterogeneity on Mutually Synchronized Spatially Distributed 24 GHz PLLs by Christian Hoyer, Jens Wagner, Frank Ellinger

“…Previous research has proposed theoretical frameworks that can predict the synchronized states of such designs. However, these frameworks do not account for the dynamic behavior that occurs during initial synchronization. …”
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Data from Emergency Medical Service Activities: A Novel Approach to Monitoring COVID-19 and Other Infectious Diseases by Daniele del Re, Luigi Palla, Paolo Meridiani, Livia Soffi, Michele Tancredi Loiudice, Martina Antinozzi, Maria Sofia Cattaruzza

“…<b>Conclusions</b>: This novel approach, combined with a machine learning predictive approach, could be a powerful public health tool to signal the start of disease outbreaks and monitor the spread of infectious diseases.…”
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The Association between KIF6 Single Nucleotide Polymorphism rs20455 and Serum Lipids in Filipino-American Women by Irma B. Ancheta, Cynthia A. Battie, Dan Richard, Christine V. Ancheta, Nancy Borja-Hart, Annabelle S. Volgman, Yvette Conley

“…The genotype distribution was 23% Trp/Trp, 51% Arg/Trp, and 26% Arg/Arg. Genotype did not predict the presence of CHD risk factors. Moreover, LDL-C, HDL-C, and triglycerides mean values did not vary as a function of genotype. …”
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Saprotrophic Wood Decay Ability and Plant Cell Wall Degrading Enzyme System of the White Rot Fungus <i>Crucibulum laeve</i>: Secretome, Metabolome and Genome Investigations by Alexander V. Shabaev, Olga S. Savinova, Konstantin V. Moiseenko, Olga A. Glazunova, Tatyana V. Fedorova

“…Multiple copies of the family AA1_1, AA3_2, AA7 and LPMOs CAZyme genes, as well as eight genes encoding proteins of the YvrE superfamily (COG3386), which includes sugar lactone lactonases, were predicted in the <i>C. laeve</i> genome. According to metabolic pathway analysis, the litter saprotroph <i>C. laeve</i> can catabolize D-gluconic and D-galacturonic acids, and possibly other aldonic acids, which seems to confer certain ecological advantages.…”
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IoT-Based Multisensors Fusion for Activity Recognition via Key Features and Hybrid Transfer Learning by Ahmad Jalal, Danyal Khan, Touseef Sadiq, Moneerah Alotaibi, Sultan Refa Alotaibi, Hanan Aljuaid, Hameedur Rahman

“…Key features are extracted using techniques such as ORB (Oriented FAST and Rotated BRIEF), MSER (Maximally Stable Extremal Regions), DFT (Discrete Fourier Transform), and KAZE for image data, and LPCC (Linear Predictive Cepstral Coefficients), PSD (Power Spectral Density), AR Coefficient, and entropy for sensor data. …”
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Optimizing NZEB performance: A review of design strategies and case studies by Mohanad M. Ibrahim, María Jose Suarez-Lopez, Ahmed A. Hanafy, Micheal A. William

“…The paper examines the revolutionary impact of artificial intelligence (AI) on enhancing NZEB performance, highlighting applications such as predictive energy analytics, intelligent HVAC systems, and real-time energy management. …”
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Pleiotropic effects of rabeprazole at acid-related diseases by A. V. Zaborovsky, I. V. Mayev, D. N. Andreyev, L. A. Tararina

“…Interleukin genetic polymorphism investigation may be useful at assessment of cytokine status in AP patients to predict the outcomes and to develop the personalized approach to treatment and prophylaxis.…”
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Hyperleptinemia, Adiposity, and Risk of Metabolic Syndrome in Older Adults by Suruchi Mishra, Tamara B. Harris, Trisha Hue, Iva Miljkovic, Suzanne Satterfield, Nathalie de Rekeneire, Mira Mehta, Nadine R. Sahyoun

“…Multivariate logistic regression was used to determine the association between leptin and metabolic syndrome (defined per NCEP ATP III) incidence after 6 years of follow-up among 1,120 men and women. Results. Leptin predicted metabolic syndrome in men (P for trend = 0.0002) and women (P for trend = 0.0001). …”
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DNA barcoding: how many earthworm species are there in the south of West Siberia? by S. V. Shekhovtsov, N. E. Bazarova, D. I. Berman, N. A. Bulakhova, E. V. Golovanova, S. V. Konyaev, T. M. Krugova, I. I. Lyubechanskii, S. E. Peltek

“…This method employs short fragments of the genome to identify species, and allows one to work with specimens that cannot be identified by conventional techniques, as well as to search for new species and predict their phylogenetic affinities. As the target sequence we took a fragment of the mitochondrial cytochrome oxidase 1 (cox1) gene. …”
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Estimation of the potential geographical distribution of invasive peach fruit fly under climate change by integrated ecological niche models by Farman Ullah, Yuan Zhang, Hina Gul, Muhammad Hafeez, Nicolas Desneux, Yujia Qin, Zhihong Li

“…Taken together, these predictive results support the quarantine of B. zonata for high-risk countries and provide in-depth information on how climatic changes may affect its possible geographic range.…”
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Associations of Salivary BPIFA1 Protein in Chronic Periodontitis Patients with Type 2 Diabetes Mellitus by Yue Guo, Lin-Na Guo, Jun-Fei Zhu, Chen-Yi Tang, Yun-Zhi Feng, Hou-De Zhou

“…BPIFA1 protein is rich in saliva and might be used as a potential predictive biomarker of T2DM, especially in patients with severe periodontitis and nonperiodontitis. …”
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Calculation of GIC in the North Island of New Zealand Using MT Data and Thin‐Sheet Modeling by K. Mukhtar, M. Ingham, C. J. Rodger, D. H. Mac Manus, T. Divett, W. Heise, E. Bertrand, M. Dalzell, T. Petersen

“…MT data in the period range 2–30 min are used to predict GIC associated with the sudden storm commencement and rapid variations in the magnetic field. …”
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