Results 101 to 110 of about 159,661 (256)

Fosl2 Regulates FSH‐Dependent Follicle Maturation Through Feedback Amplification of FSH/FSHR Signaling

Advanced Science, EarlyView.
This study identifies a FOSL2‐driven positive feedback loop that amplifies FSH/FSHR signaling. During FSH‐dependent follicle maturation, FSH induces Fosl2 expression via the cAMP‐PKA‐CREB cascade. FOSL2 in turn binds the promoters of Fshr and estrogen‐biosynthesis genes to enhance their transcription, thereby increasing Fshr mRNA level and amplifying ...
Hongru Shi, Chaoli Chen, Zaohong Ran, Jianning Liao, Zian Wu, Xiaodong Wang, Yongheng Zhao, Wenkai Ke, Bowen Tan, Yun Liu, Youqiang Su, Wei Ren, Xiang Li, Changjiu He   +13 more
wiley   +1 more source

Multiple Imputation by Chained Equations (MICE): Implementation in Stata

Journal of Statistical Software, 2011
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors studies in medicine, multiple imputation is becoming the standard route to estimating models with missing covariate data under a missing-at-random ...
Patrick Royston, Ian R. White
doaj  

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

Advanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar, Yannaël Bossard, Rachel Sava, Tobias Gänswein, Lorenca Sadiraj, Jean‐Samuel Dupré, Manuel Schröter, J. Gray Camp, Fernando Cardes, Julian Bartram, Andreas Hierlemann   +10 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

Advanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen, Jiahui Xie, Yi Liao, Junyu Li, Longqi Liu, Xin Gao, Hongmin Cai   +6 more
wiley   +1 more source

A comparative analysis of missing data imputation techniques on sedimentation data

Ain Shams Engineering Journal
Sediment data pertains to various hydrological variables with complex sediment hydrodynamics such as sedimentation rates which are often incompletely presented. Thus, the availability of sedimentation data is of utmost necessity for data accessibility. A
Wing Son Loh, Lloyd Ling, Ren Jie Chin, Sai Hin Lai, Kar Kuan Loo, Choon Sen Seah   +5 more
doaj   +1 more source

Non-Bayesian multiple imputation [PDF]

, 2005
Abstract: Multiple imputation is a method specifically designed for variance estimation in the presence of missing data. Rubin’s combination formula requires that the imputation method is “proper” which essentially means that the imputations are random draws from a posterior distribution in a Bayesian framework.
openaire   +2 more sources

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

MiR‐940 Suppresses Ferroptosis by Controlling Expression of Key Regulatory Genes

Advanced Science, EarlyView.
A CRISPR‐based screening identified miR‐940 as a critical suppressor of ferroptosis in cancer. By coordinating the downregulation of pro‐ferroptotic genes with the upregulation of GPX4, miR‐940 establishes a regulatory network that protects against ferroptosis and correlates with poor clinical outcomes in distinct cancer entities.
Andrea Kolak, Juliane Tschuck, Stefanie A. I. Weiß, Daniel Kaemena, Karolin Klimm, Ana Galhoz, Larissa Ringelstetter, Myles Fennell, Juliane Merl‐Pham, Anna Artati, Stefanie Strasser, Ralph Garippa, Michael Witting, Hans Zischka, Joel A. Schick, Stefanie M. Hauck, Michael P. Menden, Michelle Vincendeau, Brent R. Stockwell, Kamyar Hadian   +19 more
wiley   +1 more source

One-sample missing DNA-methylation value imputation

BMC Bioinformatics
Background Currently, the most popular methods for missing DNA-methylation value imputation rely on exploiting methylation patterns across multiple samples from the same population.
Christelle Kemda Ngueda, Julia Palm, Flavia Remo, André Scherag, Lutz Leistritz   +4 more
doaj   +1 more source