Results 171 to 180 of about 1,306,676 (292)

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

Multivariate analysis of Ixiolirion tataricum (Pall.) Schult. & Schult.f. based on morphological characteristics. [PDF]

Sci Rep
Ghonji M, Khaleghi A, Khadivi A, Tunç Y.   +3 more
europepmc   +1 more source

Metabolic Imbalance Triggers Adaptive Remodeling to Accelerate Diploidization in Murine Haploid Embryonic Stem Cells

Advanced Science, EarlyView.
In this article, Shuai and colleagues demonstrate that metabolic remodeling drives self‐diploidization in murine haploid ESCs (haESCs). Mitochondrial dysfunction and imbalanced pyruvate metabolism underlie this process. Genome‐wide screening using haESCs identifies key mitochondrial quality‐control related genes, enabling a metabolism‐based medium that
Yi Fu, Wenhao Zhang, Yifan Zhang, Yu He, Yi Du, Yiding Zhao, Chunmeng Yao, Shengyi Sun, Xiaoyan Sheng, Qian Gao, Chao Tong, Ling Shuai   +11 more
wiley   +1 more source

Tools for Exploring Multivariate Data: The Package ICS

Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivariate data. It includes as a special case a method for recovering the unmixing matrix in independent components analysis (ICA).
Klaus Nordhausen, Hannu Oja, David E. Tyler   +2 more
core  

The Trichinella Super‐Pangenome Reveals the Evolution of Encapsulation and Predicted Host–Parasite Protein Interactions

Advanced Science, EarlyView.
ABSTRACT The muscle capsule of Trichinella is a critical structure that impedes immune attacks and drug penetration, yet the molecular mechanisms underlying its formation remain poorly understood. Using a high‐quality super‐pangenome comprising 12 Trichinella species, we compared extensive genomic variations between encapsulating and non‐encapsulating ...
Qingbo Lv, Yi Liu, Ning Xu, Xiao Zhang, Yaming Yang, Chengyao Li, Hanhai Mao, Mingyuan Liu, Xiaolei Liu   +8 more
wiley   +1 more source

Holotomography and Multivariate Analysis Reveal Donor-Specific Responses to Antioxidant Supplementation During Stallion Sperm Cryopreservation. [PDF]

Antioxidants (Basel)
Preziosi G, Boni R, Cecchini Gualandi S, Ferrara MA.   +3 more
europepmc   +1 more source

NQO1‐Mediated Anoikis Resistance and Immune Evasion Define a High‐Risk Multi‐Omic Subtype for Precision Management of T1 High‐Grade Bladder Cancer

Advanced Science, EarlyView.
Multi‐omic profiling of T1 high‐grade bladder cancer identifies a high‐risk subtype (T1HG1) driven by NQO1, which couples anoikis resistance with immune evasion. NQO1 orchestrates macrophage–T cell crosstalk suppression via CXCL9 modulation. Pharmacological NQO1 inhibition with skullcapflavone II enhances cisplatin efficacy, representing a promising ...
Bin Guo, Chunru Xu, Shufan Fu, Qiang Cheng, Juan Li, Linkuo Shang, Gaojie Li, Yang Yang, Ying Wang, Yanqing Gong, Shengwei Xiong, Jian Fan, Changwei Yuan, Mei Zhang, Yifan Zuo, Elena Papaleo, Yue Shi, Yuan Liang, Xuesong Li, Hongzhao Li, Weimin Ci   +20 more
wiley   +1 more source

Cardiometabolic Profile Segmentation in Ecuadorian University Students: A Multivariate Analysis of Lipid, Anthropometric, and Demographic Patterns. [PDF]

Int J Environ Res Public Health
Armijo Valverde KG, Morales Caluña ER, Padilla Samaniego MV, Suarez González KD.   +3 more
europepmc   +1 more source

SAS/IML Macros for a Multivariate Analysis of Variance Based on Spatial Signs

Recently, new nonparametric multivariate extensions of the univariate sign methods have been proposed. Randles (2000) introduced an affine invariant multivariate sign test for the multivariate location problem. Later on, Hettmansperger and Randles (2002)
Jaakko Nevalainen, Hannu Oja
core  

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source