Results 111 to 120 of about 9,156,502 (281)
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
FEBS Letters, EarlyView.Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
Mechanisms of parasite‐mediated disruption of brain vessels
FEBS Letters, EarlyView.Parasites can affect the blood vessels of the brain, often causing serious neurological problems. This review explains how different parasites interact with and disrupt these vessels, what this means for brain health, and why these processes matter. Understanding these mechanisms may help us develop better ways to prevent or treat brain infections in ...
Leonor Loira +3 more
wiley +1 more source
Multiple ETS family transcription factors bind mutant p53 via distinct interaction regions
FEBS Letters, EarlyView.Mutant p53 gain‐of‐function is thought to be mediated by interaction with other transcription factors. We identify multiple ETS transcription factors that can bind mutant p53 and found that this interaction can be promoted by a PXXPP motif. ETS proteins that strongly bound mutant p53 were upregulated in ovarian cancer compared to ETS proteins that ...
Stephanie A. Metcalf +6 more
wiley +1 more source
Dizhen xuebao由于爆破数据数量有限，利用分类法识别天然地震与爆破会遇到诸多困难。鉴于此，本文建立了高维特征小样本数据集，基于XGBoost模型利用遗传算法（GA）实现对主要影响XGBoost模型分类准确率的迭代次数、最大树深和学习率等三个重要超参数的自主寻优，构建出了GA-XGBoost模型，并将该模型应用于功率谱特征样本集，结果显示：爆破与天然地震的分类准确率高达94.094%；相比于传统的GS-XGBoost模型（准确率91.787%），GA-XGBoost模型在显著提升分类准确率的同时，其运行时间也由409 ...
Hongru Li +5 more
doaj +1 more source
Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks [PDF]
Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time ...
Allan Timmermann, M. Hashem Pesaran
core
The newfound relationship between extrachromosomal DNAs and excised signal circles
FEBS Letters, EarlyView.Extrachromosomal DNAs (ecDNAs) contribute to the progression of many human cancers. In addition, circular DNA by‐products of V(D)J recombination, excised signal circles (ESCs), have roles in cancer progression but have largely been overlooked. In this Review, we explore the roles of ecDNAs and ESCs in cancer development, and highlight why these ...
Dylan Casey, Zeqian Gao, Joan Boyes
wiley +1 more source
Frontiers in Energy ResearchIntroductionAccurate and rapid carbon accounting method for the power industry is crucial to support China’s low-carbon transformation. Currently, carbon emission accounting methods are based on slowly updated fuel statistics or expensive monitoring ...
Bo Peng +4 more
doaj +1 more source
Small-Sample Properties of Censored-Data Rank Tests [PDF]
, 1983 Chmelevsky, D., Kellerer, Albrecht M.
core +1 more source
FEBS Letters, EarlyView.This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva +5 more
wiley +1 more source
A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning
SensorsTo tackle the issue of limited sample data in small sample fault diagnosis for rolling bearings using deep learning, we propose a fault diagnosis method that integrates a KANs-CNN network.
Yang Li, Xiaojiao Gu, Yonghe Wei
doaj +1 more source