DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions by Chao Cao, Mengli Li, Chunyu Wang, Lei Xu, Quan Zou, Yansu Wang, Wu Han

“…Results To address these issues, we innovatively propose a novel deep graph collaboration learning method for circRNA-miRNA interaction, called DGCLCMI. First, it uses word2vec to encode sequences into word embeddings. …”
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Impact of land–climate interaction on thermo-hydro-mechanical based stability assessment of varved glacial slopes by Deepali Anand, Arindam Dey, Ravi Karangat

“…This research attempts to evaluate the complex consequences of hydrological changes on the stability of slopes and water balance through numerical modeling using the finite element (FE) technique. The real-time climate data from Tawang, Arunachal Pradesh, is chosen which prevalently experiences sub-zero temperatures in the eastern Himalayan belt. …”
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A comprehensive framework of E2–RING E3 interactions of the human ubiquitin–proteasome system by Sjoerd J L van Wijk, Sjoerd J de Vries, Patrick Kemmeren, Anding Huang, Rolf Boelens, Alexandre M J J Bonvin, H Th Marc Timmers

“…Our data provide a detailed, genome‐wide overview of binary E2–E3 interactions of the human ubiquitination system.…”
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SDSS-IV MaNGA: Spatial Evolution of Gas-phase Metallicity Changes Induced by Galaxy Interactions by Hsi-An Pan, Lihwai Lin, Sebastián F. Sánchez, Jorge K. Barrera-Ballesteros, Bau-Ching Hsieh

“…This study investigates the spatial evolution of gas-phase metallicity (i.e., oxygen abundance, 12 + log(O/H)) in these galaxies using integral field unit data from the SDSS-IV MaNGA survey, focusing on changes in metallicity gradients across different stages of interactions—from early encounters to final coalescence. …”
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The Differential and Interactive Effects of Aging and Mental Fatigue on Alpha Oscillations: A Resting-State Electroencephalography Study by Xiaodong Yang, Kaixin Liu, Lei Liu, Yanan Du, Hao Yu, Yongjie Yao, Yu Sun, Chuantao Li

“…<b>Methods:</b> Using resting-state EEG data from an open-access dataset (younger: <i>N</i> = 198; older: <i>N</i> = 227) collected before and after a 2 h cognitive task block, we systematically examined the effects of aging and mental fatigue on alpha (8–13 Hz) oscillations via an aperiodic-corrected power spectrum, the weighted phase lag index (wPLI), and graph theory analysis. …”
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Identification of Therapeutic Targets in Autism Spectrum Disorder through CHD8-Notch Pathway Interaction Analysis. by Hewei Zhang, Shenghao Hua, Daiyan Jiao, Dong Chen, Qin Gu, Chao Bao

“…We intersected these DEGs with genes related to the Notch signaling pathway and performed functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, as well as protein-protein interaction (PPI) analyses, to identify key genes. These key genes were validated using the CHD8-deficient sample dataset GSE85417, resulting in the identification of seven common key genes. …”
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Fabrication of biocidal materials based on the molecular interactions of tetracycline and quercetin with hydroxyapatite via In Silico- and In vitro approaches by Anastasiia M. Isakova, Maxim A. Kutyrev, Aleksandra S. Kudasheva, Elizaveta V. Rogacheva, Lyudmila A. Kraeva, Sergey Shityakov, Mikhail V. Zhukov, Sviatlana A. Ulasevich, Ekaterina V. Skorb

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Recognizing the Role of Historical Houses of Isfahan in Improving the Social Interactions of Residents, Relying on the Lived Experience of People by Pezhman Nazeri Naeini, Maryam Ghasemi Sichani, Mohsen Afshari, Narges Keshti Ara

“…And what are the effective factors on promoting social interactions in historical houses? Therefore, this research seeks to investigate a number of historical houses in Isfahan city, using the classic foundation data research method and using the opinions of people who have a history of living in these houses, the factors affecting the ability to identify the social interactions in these houses. …”
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Wolf-ungulate interactions within the context of wolf's main prey population decline in Central Russian Upland by Anastasia O. Viricheva, Elena M. Litvinova, Maria D. Chistopolova, Andrey D. Poyarkov, Jose A. Hernandez-Blanco

“…Wolves showed a strong preference for Sus scrofa after decreasing its abundance. Dynamic interactions estimated from camera-trap data, using the coefficient of sociality, partly confirmed with analysis of preferences but also depending on other factors. …”
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Navigating challenges in medical english learning: leveraging technology and gamification for interactive education – a qualitative study by Zahra Zolfaghari, Zahra Karimian, Nahid Zarifsanaiey, Amir Yousef Farahmandi

“…Data were collected from September 2023 to February 2024. …”
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Development of an Integrated Human-Computer Interactive Model for Improved User Experience in Gesture-Controlled Smart Mirrors by Ayorinde Joseph Olanipekun, Olubusola Olufunke Nuga, Peter Olamide Onabanjo, Emmanuel Uchechukwu Ogbodo, Samuel Blessing Owusu

“…Key tests conducted include usability test to assess user interaction, functionality test to validate gesture control and mirror operations, data analysis for performance metrics, and visibility test for optimal display quality. …”
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Interactions between gut microbiota, plasma metabolome and brain function in the setting of a HIV cure trial by Alessandra Borgognone, Anna Prats, Anna Prats, Ashish Arunkumar Sharma, Ignacio Martinez-Zalacaín, Ignacio Martinez-Zalacaín, Carles Soriano-Mas, Carles Soriano-Mas, Carles Soriano-Mas, Christian Brander, Christian Brander, Christian Brander, Christian Brander, Bonaventura Clotet, Bonaventura Clotet, Bonaventura Clotet, Bonaventura Clotet, Bonaventura Clotet, José Moltó, José Moltó, José Moltó, Beatriz Mothe, Beatriz Mothe, Beatriz Mothe, Beatriz Mothe, Beatriz Mothe, Rafick-Pierre Sekaly, Roger Paredes, Roger Paredes, Roger Paredes, Roger Paredes, Roger Paredes, Roger Paredes, Roger Paredes, Jose A. Muñoz-Moreno, Jose A. Muñoz-Moreno, Jose A. Muñoz-Moreno

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Cultural Heritage Color Regeneration: Interactive Genetic Algorithm Optimization Based on Color Network and Harmony Models by Zhonghua Jiang, Qianlong Xia, Zhizhou Wang, Kaiwei Zhu, Qianyu Su, Jiajun Wang, Yirui Huang, Bo Wu, Yan Hong

“…Then, a dataset of 10,743 color and color rating data points is used to train 12 color harmony prediction models, with the most efficient stacking model selected to improve the efficiency of user evaluation of color schemes. …”
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Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer. by Jian Gong, Carolyn M Hutter, Polly A Newcomb, Cornelia M Ulrich, Stephanie A Bien, Peter T Campbell, John A Baron, Sonja I Berndt, Stephane Bezieau, Hermann Brenner, Graham Casey, Andrew T Chan, Jenny Chang-Claude, Mengmeng Du, David Duggan, Jane C Figueiredo, Steven Gallinger, Edward L Giovannucci, Robert W Haile, Tabitha A Harrison, Richard B Hayes, Michael Hoffmeister, John L Hopper, Thomas J Hudson, Jihyoun Jeon, Mark A Jenkins, Jonathan Kocarnik, Sébastien Küry, Loic Le Marchand, Yi Lin, Noralane M Lindor, Reiko Nishihara, Shuji Ogino, John D Potter, Anja Rudolph, Robert E Schoen, Petra Schrotz-King, Daniela Seminara, Martha L Slattery, Stephen N Thibodeau, Mark Thornquist, Reka Toth, Robert Wallace, Emily White, Shuo Jiao, Mathieu Lemire, Li Hsu, Ulrike Peters, CCFR and GECCO

“…To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). …”
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Interactions among breed, farm intensiveness and cow productivity on predicted enteric methane emissions at the population level by Gustavo Martínez-Marín, Stefano Schiavon, Franco Tagliapietra, Alessio Cecchinato, Hugo Toledo-Alvarado, Giovanni Bittante

“…This would be useful for the genetic improvement, the environmental certification of farms, and for setting prices in milk payment schemes.HIGHLIGHTS Causes of variation of the FTIR predicted EME were studied at population level using data from 6,430 herds and 1,759,706 milk spectra records Reliable daily EME estimates were achieved from 6 six informative fatty acids predicted from milk spectra EME was influenced by the interaction breed × level of herd intensiveness and, to a lesser extent, by the individual production level…”
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A new method for diagnosing effective radiative forcing from aerosol–cloud interactions in climate models by B. M. Duran, C. J. Wall, C. J. Wall, N. J. Lutsko, T. Michibata, P.-L. Ma, Y. Qin, M. L. Duffy, M. L. Duffy, B. Medeiros, M. Debolskiy

“…We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. …”
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Temperature and excipient mediated modulation of monoclonal antibody interactions revealed by kD, rheology, and Raman spectroscopy by Olivia Noelle Eskens, Sabitoj Singh Virk, Akashdeep Singh Virk, Deepika Venkataramani, Maureen Crames, Maria Calderon Vaca, Matthew Matusewicz, Connor Smith, Joshin George, Collin Taylor, Michael S. Marlow, Samiul Amin

“…Using an orthogonal analytical framework comprising diffusion interaction parameter (kD) measurements, high-shear rheometry, and Raman spectroscopic profiling, we interrogated mAb solutions at ~ 80 and 160 mg/mL across a physiologically and industrially relevant thermal window (5–45 °C). …”
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Interaction between post-tumor inflammation and vascular smooth muscle cell dysfunction in sepsis-induced cardiomyopathy by Rui Liu, Lina Jia, Lin Yu, Detian Lai, Qingzhu Li, Bingyu Zhang, Enwei Guo, Kailiang Xu, Qiancheng Luo

“…This study aims to elucidate the interaction between post-tumor inflammation, intratumor heterogeneity, and the dysfunction of VSMC in SIC, as well as to evaluate the therapeutic potential of exercise training and specific pharmacological interventions.MethodsTranscriptomic data from NCBI and GEO databases were analyzed to identify differentially expressed genes (DEGs) associated with SIC. …”
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Association of serum uric acid-to-high-density lipoprotein cholesterol ratio (UHR) with risk of myocardial infarction among individuals with diabetes: a cross-sectional analysis us... by Shibo Sun, Hongtao Xu, Li Liu, Zhongqiu Luan, Chunyan Liu, Fumin Zhi

“…Methods This cross-sectional study included 7039 adult participants from the NHANES 2005–2020 data set. The association between UHR and MI risk was examined using UHR quartile grouping, multivariable logistic regression, and restricted cubic spline (RCS) analyses. …”
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Fast-ion phase-space tomography with wave–particle interactions in the ion cyclotron frequency range as prior by M. Rud, L.G. Eriksson, J. Eriksson, P.C. Hansen, O. Hyvärinen, H. Järleblad, Ye.O. Kazakov, S.B. Korsholm, M. Nocente, J. Rasmussen, B.C.G. Reman, A. Snicker, A. Valentini, Y. Dong, D. Moseev, M. Salewski

“…We find that the addition of ICRF physics as prior information improves the reconstruction of a test ICRF-heated fast-ion distribution function in ITER using synthetic data based on the planned collective Thomson scattering sightlines and the planned gamma-ray spectroscopy sightlines. …”
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