Results 151 to 160 of about 279,412 (303)

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

open access: yesAdvanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee   +9 more
wiley   +1 more source

Generating functions and short recursions, with applications to the moments of quadratic forms in noncentral normal vectors [PDF]

open access: yes
Using generating functions, the top-order zonal polynomials that occur in much distribution theory under normality can be recursively related to other symmetric functions (power-sum and elementary symmetric functions, Ruben, Hillier, Kan, and Wang ...
Grant Hillier, Xiaolu Wang, Raymond Kan
core  

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

open access: yesAdvanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li   +6 more
wiley   +1 more source

Neuron‐Derived MIF Engages VCAM1 to Fuel a Self‐Amplifying CXCL8 Loop That Drives Perineural Invasion and Metastasis in Gastric Cancer

open access: yesAdvanced Science, EarlyView.
Neuron‐derived MIF binds VCAM1 on gastric cancer cells and activates ERK/STAT3 signaling, leading to CXCL8 transcription and secretion. Tumor‐derived CXCL8 subsequently stimulates neuronal CXCR2 to enhance MIF production, establishing a self‐amplifying MIF–VCAM1–CXCL8 positive‐feedback loop that promotes perineural invasion, tumor progression, and ...
Xunjun Li   +13 more
wiley   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

open access: yesAdvanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao   +4 more
wiley   +1 more source

On observational variance learning for multivariate Bayesian time series and related models [PDF]

open access: yes
This thesis is concerned with variance learning in multivariate dynamic linear models (DLMs). Three new models are developed in this thesis. The first one is a dynamic regression model with no distributional assumption of the unknown variance matrix.
Triantafyllopoulos, K.
core  

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