Results 101 to 110 of about 472,976 (271)

A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections – CORRIGENDUM

open access: yesEnvironmental Data Science, 2023
Xavier-Andoni Tibau   +5 more
doaj   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

open access: yesFEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

open access: yesFEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel   +13 more
wiley   +1 more source

Deep Koopman operators for causal discovery

open access: yesCommunications Physics
Causal discovery aims to identify cause-effect mechanisms for better scientific understanding, explainable decision-making, and more accurate modeling.
Juan Nathaniel   +6 more
doaj   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

open access: yesFEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura   +2 more
wiley   +1 more source

Data-driven causal behaviour modelling from trajectory data: A case for fare incentives in public transport

open access: yesJournal of Public Transportation
Behaviour modelling has been widely explored using both statistical and machine learning techniques, primarily relying on analyzing correlations to understand passenger responses under different conditions and scenarios.
Yuanyuan Wu   +4 more
doaj   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

open access: yesMolecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero   +11 more
wiley   +1 more source

Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks

open access: yesMathematics
Causal discovery from time-series data seeks to capture both intra-slice (contemporaneous) and inter-slice (time-lagged) causal relationships among variables, which are essential for many scientific domains.
Rujia Shen   +6 more
doaj   +1 more source

Cytoplasmic p21 promotes stemness of colon cancer cells via activation of the NFκB pathway

open access: yesMolecular Oncology, EarlyView.
Cytoplasmic p21 promotes colorectal cancer stem cell (CSC) features by destabilizing the NFκB–IκB complex, activating NFκB signaling, and upregulating BCL‐xL and COX2. In contrast to nuclear p21, cytoplasmic p21 enhances spheroid formation and stemness transcription factor CD133.
Arnatchai Maiuthed   +10 more
wiley   +1 more source

Small dataset augmentation with radial basis function approximation for causal discovery using constraint-based method

open access: yesETRI Journal
Causal analysis involves analysis and discovery. We consider causal discovery, which implies learning and discovering causal structures from available data, owing to the significance of interpreting causal relationships in various fields.
Chan Young Jung, Yun Jang
doaj   +1 more source

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