Clinical and Diagnostic Significance of Lactate Dehydrogenase and Its Isoenzymes in Animals by Robert Klein, Oskar Nagy, Csilla Tóthová, Frederika Chovanová

“…The activity of LDH and its serum and tissue patterns and composition show great variations between the species. …”
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Geographic variation in the determinants of ectoparasite faunas’ species richness: fleas and gamasid mites parasitic on small mammals from 6 biogeographic realms by Boris R. Krasnov, Vasily I. Grabovsky, Natalia Korallo-Vinarskaya, Maxim V. Vinarski, Angel Luis Robles Fernandez, Irina Khokhlova

“…We conclude that caution is needed in making judgements about the generality of macroecological patterns related to parasites based on the investigations of these patterns in limited numbers of localities and when pooling data on various taxa.…”
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SFMHANet: Surface Fitting Constrained Multidimensional Hybrid Attention Network for Aero-Optics Thermal Radiation Effect Correction by Yu Shi, ShanLin Niu, Lei Wang, Liang Ye, YaoZong Zhang, HanYu Hong

“…In practical application scenarios, the aero-optical thermal radiation patterns in degraded images are not fixed, and types of aero-optics thermal radiation are more variable and complex. …”
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Vowel classification with combining pitch detection and one‐dimensional convolutional neural network based classifier for gender identification by Chia‐Hung Lin, Hsiang‐Yueh Lai, Ping‐Tzan Huang, Pi‐Yun Chen, Chien‐Ming Li

“…Then, in vowel voice signal classification, a one‐dimensional (1D) convolutional neural network (CNN), consisted of a multi‐round 1D kernel convolutional layer, a 1D pooling process, and a vowel classifier that could preliminary divide feature patterns into three level ranges of F0, including adult and children groups. …”
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Intraoperative ICG Dye Monitoring for Identification of Pituitary Adenoma in Endoscopic Transsphenoidal Surgery: A Prospective Observational Study by S. Balaji

“…These variations in intensity, temporal changes in fluorescence, and tissue-specific patterns allowed differentiation of tumor margins and identification of surrounding structures. …”
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Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation by Gunjan Shandilya, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…By boosting feature propagation, this integration increases the model’s ability to recognize minute patterns in cervical cell images, hence increasing classification accuracy. …”
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Enhancement of Chest X-Ray Images to Improve Screening Accuracy Rate Using Iterated Function System and Multilayer Fractional-Order Machine Learning Classifier by Chia-Hung Lin, Jian-Xing Wu, Chien-Ming Li, Pi-Yun Chen, Neng-Sheng Pai, Ying-Che Kuo

“…The accuracy rate is thus improved. Pooling is performed to reduce the dimensions of the feature patterns and speed up complex computations. …”
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Development of an Infant’s Peripheral Motor System Within the First 3 Years of Life as Studied Using Surface Electromyography by Yu. R. Zaripova, A. Yu. Meigal, V. I. Makarova

“…This suggests the continuing «intrauterine» pattern of the motor neuron pool work.…”
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Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review by Viet Long Bui, Angus E. Hughes, Romain Ragonnet, Michael T. Meehan, Alec Henderson, Emma S. McBryde, James M. Trauer

“…Abstract Background Traditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can more accurately represent the complex heterogeneity of TB transmission. …”
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Graph Neural Network Learning on the Pediatric Structural Connectome by Anand Srinivasan, Rajikha Raja, John O. Glass, Melissa M. Hudson, Noah D. Sabin, Kevin R. Krull, Wilburn E. Reddick

“…Architecture exploration experiments were conducted to evaluate the impact of network depth, pooling techniques, and skip connections on the ability of GNN models to capture connectomic patterns. …”
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Meta-Analysis on the Prevalence and Significance of Incidental Findings in the Thyroid Gland Using Other PET Radiopharmaceuticals Beyond [¹⁸F]FDG by Cesare Michele Iacovitti, Domenico Albano, Alessio Rizzo, Arnoldo Piccardo, Marco Cuzzocrea, Gaetano Paone, Pierpaolo Trimboli, Giorgio Treglia

“…The final diagnosis of TIP with a diffuse pattern was a benign condition or represented a physiological uptake. …”
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Superior immunogenicity of inactivated whole virus H5N1 influenza vaccine is primarily controlled by Toll-like receptor signalling. by Felix Geeraedts, Nadege Goutagny, Veit Hornung, Martina Severa, Aalzen de Haan, Judith Pool, Jan Wilschut, Katherine A Fitzgerald, Anke Huckriede

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A cross-age odyssey of cognitive reading attributes: a scoping review by Muhamad Firdaus Mohd Noh, Mohd Effendi Ewan Mohd Matore, Nur Ainil Sulaiman

“…A distinctive pattern emerges in the assessment of cognitive reading skills across age groups, with adult readers evaluated on a wider array of attributes that encompass both fundamental skills and higher order cognitive abilities. …”
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Age-Related Features of Reactive Catecholamine Shifts in the Spinal Cord in Acute Somatic Pain: Experimental Study by V. G. Ovsyannikov, A. V. Kapliyev

“…In prepubertal and sexually mature male rats, there was a reduction in the spinal CA pool, but due to different components: to A and NA in 35-day rats and to A and DA in 3-month ones.Conclusion. …”
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Transfer of Periodic Phenomena in Multiphase Capillary Flows to a Quasi-Stationary Observation Using U-Net by Bastian Oldach, Philipp Wintermeyer, Norbert Kockmann

“…Artificial Intelligence is now the state of the art for recognizing patterns in images or analyzing datasets that are too large for humans to handle. …”
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SAGEFusionNet: An Auxiliary Supervised Graph Neural Network for Brain Age Prediction as a Neurodegenerative Biomarker by Suraj Kumar, Suman Hazarika, Cota Navin Gupta

“…<b>Methods:</b> In this study, we propose SAGEFusionNet, a GNN architecture specifically designed to enhance brain age prediction and assess PD-related brain ageing patterns using T1-weighted structural MRI (sMRI). SAGEFusionNet learns important ROIs for brain age prediction by incorporating ROI-aware pooling at every layer to overcome the above challenges. …”
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How socioeconomic status moderates the stunting-age relationship in low-income and middle-income countries by S V Subramanian, Christian Bommer, Sebastian Vollmer

“…We aim to fill this gap by providing an in-depth analysis of the role of socioeconomic status (SES) as a moderator for the stunting-age pattern.Methods Epidemiological and socioeconomic data from 72 Demographic and Health Surveys (DHS) were used to calculate stunting-age patterns by SES quartiles, derived from an index of household assets. …”
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Distinct Proteasome Subpopulations in the Alveolar Space of Patients with the Acute Respiratory Distress Syndrome by S. U. Sixt, R. Alami, J. Hakenbeck, M. Adamzik, A. Kloß, U. Costabel, P. R. Jungblut, B. Dahlmann, J. Peters

“…Proteasomes purified from pooled ARDS BAL supernatant showed an altered enzyme activity ratio. …”
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Food composition of the diet in relation to changes in waist circumference adjusted for body mass index. by Dora Romaguera, Lars Ängquist, Huaidong Du, Marianne Uhre Jakobsen, Nita G Forouhi, Jytte Halkjær, Edith J M Feskens, Daphne L van der A, Giovanna Masala, Annika Steffen, Domenico Palli, Nicholas J Wareham, Kim Overvad, Anne Tjønneland, Heiner Boeing, Elio Riboli, Thorkild I Sørensen

“…<h4>Conclusion</h4>A dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation.…”
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Analysis of Carbon Sequestration Capacity and Economic Losses Under Multiple Scenarios in Major Grain-Producing Regions of China: A Case Study of the Urban Agglomeration the Huaihe... by Junhao Cheng, Wenfeng Hu, Mengtian Zheng, Xiaolong Jin, Junqiang Yao, Shuangmei Tong, Fei Guo

“…The results indicate that the following: (1) From 2000 to 2020, CS kept on declining, with cultivated land and forest land being the dominant carbon pools, accounting for over 86% of the total CS. (2) From a “city–grid–raster” perspective, the spatial pattern of high-value hot spots of CS remained stable, and the overall pattern remained unchanged under multi-scenario simulation, yet the overall carbon sink center of gravity shifted to the southwest. (3) The top five driving factors are elevation, slope, NDVI, GDP per capita, and population density, accounting for 77.2% of the total driving force. (4) The carbon sequestration capacity at the county scale continued to weaken, and the overall capacity presented the following order: 2035 Farmland protection scenario (FPS) > 2035 Natural development scenario (NDS) > 2035 Urban development scenario (UDS). …”
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