Results 131 to 140 of about 296,784 (294)

Engineered Living Systems With Self‐Organizing Neural Networks: From Anatomy to Behavior and Gene Expression

Advanced Science, EarlyView.
Ectodermal tissue excised from Xenopus embryos self‐organizes into a three‐dimensional mucociliary organoid. Here, we generate a neural variant, termed neurobot, by implanting neural precursor cells. Neurobots develop mature neurons, adopt distinct morphologies, exhibit more complex motility, and respond differentially to neuroactive compounds. Imaging
Haleh Fotowat, Laurie O'Neill, Léo Pio‐Lopez, Megan M. Sperry, Patrick Erickson, Tiffany Lin, Michael Levin   +6 more
wiley   +1 more source

Stochastic Nanoscale Biophysical Cues as a Basis for the Induction of Glioblastoma‐Like Transcriptional Programs in Astrocytes

Advanced Science, EarlyView.
Stochastic nanoscale physical cues induce glioblastoma (GBM)‐associated transcriptional traits in naïve astrocytes leading to spontaneous formation of spheroids. Cells within spheroids express activated‐MMP2 and a differential gene expression pattern involving P53 and NOTCH3, providing evidence for a role for changes in brain topography, as observed in
Laurent Starck, Tobias Butelmann, Sabrina Hogan, Melika Sarem, Bernd Heimrich, Ritwick Sawarkar, Marie‐Françoise Ritz, Gregor Hutter, V. Prasad Shastri   +8 more
wiley   +1 more source

Evaluating the Utilities of Foundation Models in Single‐Cell Data Analysis

Advanced Science, EarlyView.
This study delivers the first systematic, task‐level evaluation of single‐cell foundation models across eight core analytical tasks. By benchmarking 10 leading models with the scEval framework, it reveals where foundation models truly add value, where task‐specific methods still dominate, and provides concrete, reproducible guidelines to steer the next
Tianyu Liu, Kexing Li, Yuge Wang, Hongyu Li, Hongyu Zhao   +4 more
wiley   +1 more source

Neuid: A Novel Neuron‐Enriched LncRNA that Connects Epigenetic Gene Silencing to Alzheimer's Disease

Advanced Science, EarlyView.
ABSTRACT The increasing evidence that non‐coding RNAs can become deregulated during pathogenesis is dramatically expanding the space for drug discovery beyond the protein‐coding genome. Long noncoding RNAs (lncRNAs) are emerging as key regulators of cellular function, yet most remain uncharacterized.
Ranjit Pradhan, Zorica Petrovic, M. Sadman Sakib, Sophie Schröder, Dennis Manfred Krüger, Tonatiuh Pena, Eren Diniz, Susanne Burkhardt, Anna‐Lena Schütz, Verena Gisa, Iga Grzadzielewska, Karl Toischer, Thor D. Stein, Jan Krzysztof Blusztajn, Ivana Delalle, Jelena Radulovic, Farahnaz Sananbenesi, Andre Fischer   +17 more
wiley   +1 more source

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

Advanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño, Víctor M. de la Oliva Roque, Javier‐Ignacio Ramirez‐Lopez, David P. Kreil, Joaquín Dopazo, Carlos Loucera   +5 more
wiley   +1 more source

An Increasing Misalignment Between Crop Distribution and Environmental Resources Under Climate Change in China

Advanced Science, EarlyView.
Climate change reshapes the spatial alignment between crop production and environmental resources. Using multi‐source data and a crop model, integrated climatic, water, and soil endowments for maize and wheat are quantified and compared with harvest distributions.
Zheng'e Su, Zhentao Zhang, Jin Zhao, Xia Liang, Chuang Zhao, Zhijuan Liu, Minghao Zhuang, Jing Sun, Bo Lu, Ke Liu, Johannes W. M. Pullens, Matthew T. Harrison, Deli Chen, Xiaoguang Yang   +13 more
wiley   +1 more source

Cohort‐Scale Spatial Autocorrelation for Tumor Prediction in Mid‐Infrared Pathology and Spatial Biomarker Discovery Using MALDI Imaging Lipidomics

Advanced Science, EarlyView.
Computational annotation of various tissue types in heterogeneous samples such as colorectal cancer liver metastasis (CRLM) using spatial autocorrelation analysis on non‐destructive mid‐infrared (MIR) imaging data enabled correlative multimodal mass spectrometry imaging (MSI) for spatial investigation of lipid tumor marker candidates. The method can be
Miriam F. Rittel, Nikolas Ebert, Denis Abu Sammour, Sebastian Graf, Björn C. Fröhlich, Emrullah Birgin, Shad A. Mohammed, Nuh N. Rahbari, Axel Wellmann, Oliver Wasenmüller, Cleo‐Aron Weis, Stefan Schmidt, Carsten Hopf   +12 more
wiley   +1 more source

His‐MMDM: Multi‐Domain and Multi‐Omics Translation of Histopathological Images with Diffusion Models

Advanced Science, EarlyView.
His‐MMDM is a diffusion model‐based framework for scalable multi‐domain and multi‐omics translation of histopathological images, enabling tasks from virtual staining, cross‐tumor knowledge transfer, and omics‐guided image editing. ABSTRACT Generative AI (GenAI) has advanced computational pathology through various image translation models.
Zhongxiao Li, Tianqi Su, Bin Zhang, Wenkai Han, Sibin Zhang, Guiyin Sun, Yuwei Cong, Xin Chen, Jiping Qi, Yujie Wang, Shiguang Zhao, Hongxue Meng, Peng Liang, Xin Gao   +13 more
wiley   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source