Integrative analysis of saliva-derived exosomal proteome and lipidome for the diagnosis of esophageal squamous cell carcinoma by Wei Zhong, Jian Liu, Junhua Xie, Zhiyan Zhang, Zhiwen Gong, Zhixiang Yan, Qingdong Cao

“…The proteomic characteristics of ESCC were primarily manifested in immune responses, disruption of tissue structural homeostasis, and enhanced antifungal and antimicrobial humoral immune responses. …”
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Optimized enrichment of murine blood–brain barrier vessels with a critical focus on network hierarchy in post-collection analysis by Hanaa Abdelazim, Audra Barnes, James Stupin, Ranah Hasson, Carmen Muñoz-Ballester, Kenneth L. Young, Stefanie Robel, James W. Smyth, Samy Lamouille, John C. Chappell

“…Positioned between upstream arteries and downstream veins, these microvessels have unique structural features, such as the absence of vascular smooth muscle cells (vSMCs) and a relatively thin basement membrane, to facilitate highly efficient yet selective exchange between the circulation and the brain interstitium. …”
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New approach of PV and thermal modeling to develop feasible cooling solutions for PV in buildings by Cornago Iñaki, Ezquer Mikel, Sorbet Francisco Javier, Kalms Alicia, Diarce Gonzalo, Irulegi Olatz, Zaversky Fritz

“…This work presents a straightforward Building Applied PhotoVoltaic-Thermal element, characterized by its ease of implementation, utilizing conventional photovoltaic modules and standard supporting structures to form a narrow air ventilation channel with the roof of the building. …”
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Addressing System Challenges in Mental Health Services Research for Youth in the Child Welfare System: Insights From the Foster Care Family Navigator Trial by Marina Tolou‐Shams, Megan Ramaiya, Jannet L. Salas, Adrian Aguilera, Martha Shumway, Brian Borsari, Emily Dauria, Jill D. Berrick

“…Systems‐level challenges that impacted proposed research trial design and data collection included: (1) Limited system staff time and compensation processes; (2) Staff training and knowledge; and (3) System disruptions. …”
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A φSa3int (NM3) Prophage Domestication in Staphylococcus aureus Leads to Increased Virulence Through Human Immune Evasion by Roshan Nepal, Ghais Houtak, George Bouras, Sholeh Feizi, Gohar Shaghayegh, Keith Shearwin, Mahnaz Ramezanpour, Alkis James Psaltis, Peter‐John Wormald, Sarah Vreugde

“…Further, φSa3int prophage domestication led to reduced phagocytosis implying φSa3int prophage mediates escape of S. aureus from human innate immunity. Our data further show that in addition to adding novel prophage‐encoded virulence, φSa3int prophage domestication also affects the expression of non‐prophage (bacterial) genes and suppresses expression of structural proteins of resident prophages. …”
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MDNN-DTA: a multimodal deep neural network for drug-target affinity prediction by Xu Gao, Xu Gao, Mengfan Yan, Mengfan Yan, Chengwei Zhang, Chengwei Zhang, Gang Wu, Gang Wu, Jiandong Shang, Jiandong Shang, Congxiang Zhang, Congxiang Zhang, Kecheng Yang, Kecheng Yang

“…One notable strength of our method is its ability to accurately predict DTA directly from the sequences of the target proteins, obviating the need for protein 3D structures, which are frequently unavailable in drug discovery. …”
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Adsorptive Removal of Bisphenol A by Polyethylene Meshes Grafted with an Amino Group-Containing Monomer, 2-(Dimethylamino)ethyl Methacrylate by Kazunori Yamada, Saori Terada, Rena Yamamoto, Dương Cẩm Anh, Takaya Naitou, Sakura Yamamoto

“…The cycle of adsorption at pH 8.0 and desorption in a NaOH solution at 100 mM was repeated five times without loss or structural damage. These results indicate PE-g-PDMAEMA meshes can be used as a regenerative adsorbent for BPA removal from aqueous medium.…”
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Minimally invasive nephrectomy for inflammatory renal disease by Paula Andrea Peña, Lynda Torres-Castellanos, Germán Patiño, Stefanía Prada, Luis Gabriel Villarraga, Nicolás Fernández

“…Our experience supports that releasing the kidney first and leaving the hilum for the end is a safe approach when vascular structures are embedded into a single block of inflammatory and scar tissue.…”
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Assisted Parkinsonism Diagnosis Using Multimodal MRI—The Role of Clinical Insights by Tobias Meindl, Alexander Hapfelmeier, Tobias Mantel, Angela Jochim, Jonas Deppe, Silke Zwirner, Jan S. Kirschke, Yong Li, Bernhard Haslinger

“…The most discriminatory variables were responsiveness to levodopa, vertical gaze palsy, and the volumes of subcortical structures, including the red nucleus. Conclusion Machine‐learning‐assisted classification of MR‐imaging biomarkers gathered in routine care can assist in the diagnosis of parkinsonian syndromes as part of the diagnostic workup. …”
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Caregivers’ lived experiences of childhood probable pneumonia through a gendered lens in western Kenya by Sarah Hawi Ngere, Charles Olang'o, Kennedy Ochola, Patience Oduor, Caleb K. Sagam, Benard Ochieng, Dickens Omondi, Norbert Peshu, Erick Nyambedha

“…Contribution: This study’s findings emphasise the necessity of a holistic approach when developing intervention geared towards improving healthcare-seeking behaviour by considering the subtler factors beyond structural, social and economic influences.…”
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Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys by Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey

“…A detailed case study of tungsten (W) demonstrates that data on pure W alone is insufficient for modeling complex defects in uMLIPs, underscoring the critical importance of advanced machine learning architectures and diverse datasets, which include over 100 million structures spanning all elements. …”
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Association Between Anatomic and Clinical Indicators of Injury Severity After Moderate-Severe Traumatic Brain Injury: A Pilot Study Using Multiparametric Magnetic Resonance Imaging by Dmitry Esterov, Ziying Yin, Trevor Persaud, Xiang Shan, Mathew C. Murphy, Richard L. Ehman, John Huston III, Allen W. Brown

“…Future larger studies could lead to the development of prediction models that integrate clinical data with anatomical (MRI), structural (DTI), and mechanical (MRE) changes caused by TBI, to inform prognosis and care planning.…”
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Machine Learning for Long COVID Inference Based on the Acute Phase: A Case Study in Healthcare Professionals by Caio B. S. Maior, Sandrely P. Silva, Isis D. Lins, Ana Lisa Gomes, Marcio C. Moura

“…Since 2021, the COVID-19 pandemic has affected global health, economies, and societal structures, leading to great attention to new research and awareness. …”
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Investigation of biomolecular dynamics by sensitivity-enhanced 1H–2H CPMAS NMR using matrix-free dynamic nuclear polarization by Thomas Biedenbänder, Aryana Rodgers, Mirjam Schröder, Liliya Vugmeyster, Björn Corzilius

“…Molecular dynamics of functional groups contain valuable information about structural properties and functional activities in biomolecules. …”
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Predicting Solar Flares Using a Convolutional Neural Network with Extreme-ultraviolet Images by Yun Yang, Yi Wei Ni, P. F. Chen, Xue Shang Feng

“…The main advantage of this model lies in that it can effectively leverage the historical and spatial information of the source active regions as well as the interaction information from the surrounding active regions or other structures. This information, which cannot be provided by the data from a single active region alone, is demonstrated to be crucial in predicting solar flares. …”
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From Centralization to Decentralization: Blockchain’s Role in Transforming Social Media Platforms by Bidita Sarkar Diba, Jayonto Dutta Plabon, Nishat Tasnim, Mehjabin Hossain, Durjoy Mistry, Sourav Sarker, M. F. Mridha, Yuichi Okuyama, Jungpil Shin

“…Blockchain is influencing the social media platforms by promising to solve the biggest issues of today, such as privacy concerns and content moderation, and the ability to provide a decentralized system for the management of social media platforms through cryptographic techniques and distributed structures. Conventionally, social media systems are based on central architectures that may indirectly solve the problems of data privacy and platform responsibility since there are increased threats, including identity theft and fake news spread across such systems. …”
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Modelling economics students’ use of ChatGPT and academic performance: insights from self-determination theory and epistemic curiosity by Bernard Yaw Sekyi Acquah, Francis Arthur, Iddrisu Salifu, Enoch Mensah, Ernest Opoku, Sharon Abam Nortey, Solomon Adjatey Tetteh

“…The study used adapted scales of ICAP (i.e. measuring the use of ChatGPT), “desire to learn (DFL), self-efficacy (SE), beliefs about the future (BAF), epistemic curiosity (EP) and perceived academic performance (AP)”. Data were analysed using “partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA)”. …”
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Changes of EEG beta band power and functional connectivity during spaceflight: a retrospective study by Adrián Quivira-Lopesino, María Sevilla-García, Pablo Cuesta, Sandra Pusil, Ricardo Bruña, Patrique Fiedler, Ana Maria Cebolla, Guy Cheron, Michael Funke, Fernando Maestu

“…Astronauts often report temporary neurological symptoms, such as disorientation, visual disturbances, and motor issues, potentially linked to structural and electrophysiological brain changes. To investigate this, electroencephalography (EEG) is a reliable tool to study brain activity in space, measuring oscillatory activity and functional connectivity (FC). …”
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Advancing 6G: Survey for Explainable AI on Communications and Network Slicing by Haochen Sun, Yifan Liu, Ahmed Al-Tahmeesschi, Avishek Nag, Mohadeseh Soleimanpour, Berk Canberk, Huseyin Arslan, Hamed Ahmadi

“…With the evolution of the 6G networks, characterized by ultra-low latency, massive data rates, and intricate network structures, the need for transparency, interpretability, and fairness in AI-driven decision-making has become more urgent than ever. …”
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Taming Mambas for 3D Medical Image Segmentation by Luca Lumetti, Vittorio Pipoli, Kevin Marchesini, Elisa Ficarra, Costantino Grana, Federico Bolelli

“…CNNs are constrained by a local receptive field, whereas Transformers are hindered by their substantial memory requirements as well as their data hunger, making them not ideal for processing 3D medical volumes at a fine-grained level. …”
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