Results 111 to 120 of about 169,946 (260)

NMI Regulates Adipose Adaptive Thermogenesis Through TLR4/IRF3 Signaling to Promote Obesity

Advanced Science, EarlyView.
Adipose tissue‐derived NMI is secreted under metabolic stress and suppresses adaptive thermogenesis through TLR4/IRF3 signaling, repressing the PPARα/PGC‐1α/UCP1 thermogenic transcriptional program. Genetic ablation or anti ‐ NMI monoclonal antibody treatment enhances energy expenditure, protects against DIO, and ameliorates adipose tissue inflammation,
Ting‐Ting Li, Xin‐Yuan Zhao, Min Zhang, Zhuang‐Feng Weng, Xiao‐Ran Guo, Ying‐Fang Liu, Qiao‐Ping Wang, Huan‐Huan Liang   +7 more
wiley   +1 more source

Machine learning driven by environmental covariates to estimate high-resolution PM2.5 in data-poor regions. [PDF]

PeerJ, 2022
Jin X, Ding J, Ge X, Liu J, Xie B, Zhao S, Zhao Q.   +6 more
europepmc   +1 more source

Mechanical Activation of Piezo1 Drives Osteoarthritis Through Kdm5c‐Mediated Epigenetic Silencing

Advanced Science, EarlyView.
Excessive mechanical stress activates Piezo1, triggering Ca2+‐dependent cytoskeletal forces that deform the nucleus and reduce H3K4me3. Kdm5c demethylates H3K4me3 at Col2a1 and Runx3 promoters. Kdm5c knockout rescues degradation. Repurposed telmisartan directly inhibits Kdm5c, blocking this axis and showing disease‐modifying efficacy in mouse OA models
Tianyou Kan, Xuran Li, Han Wang, Lin Sun, Yao Wang, Jiangdong Wu, Junqi Cui, Yiqi Yang, Kai Yuan, Linyang Chu, Liao Wang, Hanjun Li, Mengning Yan, Zhifeng Yu   +13 more
wiley   +1 more source

Environment-specific genomic prediction ability in maize using environmental covariates depends on environmental similarity to training data. [PDF]

G3 (Bethesda), 2022
Rogers AR, Holland JB.
europepmc   +1 more source

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

Advanced 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, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

Semiparametric model selection for identification of environmental covariates related to adult groundfish catches and weights. [PDF]

Sci Rep, 2021
Correia HE.
europepmc   +1 more source

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

Advanced 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, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

CHCHD10 Mitigates Alzheimer's Disease‐Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons

Advanced Science, EarlyView.
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas, Ching‐Yao Yang, Kexin Zhang, Liam Wetzel, Dina Bugybayeva, Julia Ferguson, Md Mahmudul Hasan, William Samsa, Nandita Patil, Anshul Dash, Tarini Gowda, Xiongwei Zhu, Feixiong Cheng, Tian Liu   +13 more
wiley   +1 more source

Environmental Covariates for Sampling Optimization and Pest Prediction in Soybean Crops

AgriEngineering
Insect pest infestations can vary due to spatial differences in microclimates and food availability within agroecosystems. Covariates can reflect these environmental conditions. This study tested whether using environmental covariates in two-phase sample
Cenneya Lopes Martins, Maiara Pusch, Wesley Augusto Conde Godoy, Lucas Rios do Amaral   +3 more
doaj   +1 more source

Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision. [PDF]

Theor Appl Genet, 2021
Buntaran H, Forkman J, Piepho HP.
europepmc   +1 more source