Results 81 to 90 of about 407,846 (278)

FGFR Like1 drives esophageal cancer progression via EMT, PI3K/Akt, and notch signalling: insights from clinical data and next‐generation sequencing analysis

FEBS Open Bio, EarlyView.
Clinical analysis reveals significant dysregulation of FGFRL1 in esophageal cancer (EC) patients. RNAi‐coupled next‐generation sequencing (NGS) and in vitro study reveal FGFRL1‐mediated EC progression via EMT, PI3K/Akt, and Notch pathways. Functional assays confirm its role in tumor growth, migration, and invasion.
Aprajita Srivastava, Anoop Saraya, Deepak Gunjan, Rinu Sharma   +3 more
wiley   +1 more source

Cutaneous Melanoma Drives Metabolic Changes in the Aged Bone Marrow Immune Microenvironment

Aging and Cancer, EarlyView.
Melanoma, the deadliest form of skin cancer, increasingly affects older adults. Our study reveals that melanoma induces changes in iron and lipid levels in the bone marrow, impacting immune cell populations and increasing susceptibility to ferroptosis.
Alexis E. Carey, Murilo Ramos Rocha, Cheyenne Palm, Vania Wang, Denys Balandin, Ethan Black, Kevin Y. Zhang, Fan Huang, Daniel J. Zabransky, Yash Chhabra, Mareike Peters, Gabriel Ghiaur, Ashani Weeraratna   +12 more
wiley   +1 more source

Portable Low‐Field Magnetic Resonance Imaging in People With Human Immunodeficiency Virus

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The aging population of people with HIV (PWH) raises heightened concerns regarding accelerated aging and dementia. Portable, low‐field MRI (LF‐MRI) is an innovative technology that could enhance access and facilitate routine monitoring of PWH.
Annabel Sorby‐Adams, Malachi Keo, Jennifer Guo, Daire Daly, Richard Ahern, Kimon Zachary, Gregory Robbins, Rajesh T. Gandhi, Bragi Sveinsson, Adam de Havenon, Kevin N. Sheth, Otto Rapalino, Juan Eugenio Iglesias Gonzales, W. Taylor Kimberly, Shibani S. Mukerji   +14 more
wiley   +1 more source

Interpretable deep learning for guided structure-property explorations in photovoltaics

, 2018
The performance of an organic photovoltaic device is intricately connected to its active layer morphology. This connection between the active layer and device performance is very expensive to evaluate, either experimentally or computationally.
Ganapathysubramanian, Baskar, Ghosal, Sambuddha, Kokate, Apurva, Pokuri, Balaji Sesha Sarath, Sarkar, Soumik   +4 more
core  

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky, Cara Joyce, H. Jeremy Bockholt, Paul A. Rudnick, William H. Adams, Fiona McAllister, Justin W. Smock, Michael A. Newton, Jane S. Paulsen   +8 more
wiley   +1 more source

Bridging text and crystal structures: literature-driven contrastive learning for materials science

Machine Learning: Science and Technology
Understanding structure–property relationships is an essential yet challenging aspect of materials discovery and development. To facilitate this process, recent studies in materials informatics have sought latent embedding spaces of crystal structures to
Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Kotaro Saito, Naoya Chiba, Yoshitaka Ushiku, Kanta Ono   +6 more
doaj   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source