Results 251 to 260 of about 1,906,656 (324)

Menthol‐like cooling compounds, including (R)‐(‐)‐carvone, inhibit the human bitter taste receptors for saccharin and acesulfame K

FEBS Open Bio, EarlyView.
We report that some menthol‐like cooling compounds, including (R)‐(‐)‐carvone, act as inhibitors of TAS2R31 and TAS2R43, which are taste receptors responsible for the intrinsic bitter aftertastes of saccharin and acesulfame K. However, there was little correlation between the intensity of the cooling sensation and the potency of bitterness inhibition ...
Miyuu Saito, Takumi Misaka
wiley   +1 more source

A large language model framework for literature-based disease-gene association prediction. [PDF]

Brief Bioinform
Li PH, Sun YY, Juan HF, Chen CY, Tsai HK, Huang JH.   +5 more
europepmc   +1 more source

Microbial profile of the appendix niche in acute appendicitis: a novel sampling approach

FEBS Open Bio, EarlyView.
This study utilized a novel sampling method, ERAT (i.e. endoscopic retrograde appendicitis treatment)‐guided lumen aspiration, to obtain samples from the appendix, and shotgun metagenomic sequencing was performed for in situ characterization of the appendix microbiome in patients with acute appendicitis.
Huimin Ma, Mingfei Wang, Yanhu Feng, Wanqi Zhang, Wenbo Wang, Yanfeng Xie, Guixiang Kong, Jie Feng, Pengfei Wang, Qi Wang, Xiaojun Huang   +10 more
wiley   +1 more source

PhyloMix: enhancing microbiome-trait association prediction through phylogeny-mixing augmentation. [PDF]

Bioinformatics
Jiang Y, Liao D, Zhu Q, Lu YY.
europepmc   +1 more source

Transcriptional regulation of neuropeptide receptors underlies context‐dependent adaptation in Drosophila melanogaster

FEBS Open Bio, EarlyView.
Under environmental changes, the expression level of neuropeptide (NP) and neuropeptide receptor (NPR) genes changes to confer context‐dependent adaptation to the model organism Drosophila melanogaster. Through finding more regulatory elements in the NPR genes in comparison with their ligands (NPs), we found that NPR‐biased transcriptional regulation ...
SeungHeui Ryu, Yanan Wei, Zekun Wu, Tianmu Zhang, DoHoon Lee, Hadi Najafi, Woo Jae Kim   +6 more
wiley   +1 more source

CDPMF-DDA: contrastive deep probabilistic matrix factorization for drug-disease association prediction. [PDF]

BMC Bioinformatics
Tang X, Hou Y, Meng Y, Wang Z, Lu C, Lv J, Hu X, Xu J, Yang J.   +8 more
europepmc   +1 more source

A unified model for Duchenne muscular dystrophy gene involvement in cancer: context‐dependent tumour suppression and oncogenicity

FEBS Open Bio, EarlyView.
We propose a context‐dependent model where the Duchenne muscular dystrophy (DMD) gene acts as a tumour suppressor in aggressive tumours and as an oncogene in less aggressive ones. We propose this model as a unified framework to explain the opposing survival associations with DMD expression and to guide experimental exploration of the dual role of DMD ...
Lee Machado, Leanne Jones, Sonika Divakar, Michael Naidoo, Karen Anthony   +4 more
wiley   +1 more source

HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease. [PDF]

J Transl Med
Su YY, Huang HC, Lin YT, Chuang YF, Sheu SY, Lin CC.   +5 more
europepmc   +1 more source

The impact of Hnrnpl deficiency on transcriptional patterns of developing muscle cells

FEBS Open Bio, EarlyView.
We performed nanopore whole‐transcriptome sequencing comparing RNA from Hnrnpl‐knockdown versus control C2C12 myoblasts to investigate the contributions of Hnrnpl to muscle development. Our results indicate that Hnrnpl regulates the expression of genes involved with Notch signaling and skeletal muscle, particularly splicing patterns of specific muscle ...
Hannah R. Littel, Mekala Gunasekaran, Audrey L. Daugherty, Natalya M. Wells, Johnnie Turner, Christine C. Bruels, Christina A. Pacak, Isabelle Draper, Peter B. Kang   +8 more
wiley   +1 more source

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders. [PDF]

Int J Mol Sci
Wang Y, Lei X, Chen Y, Guo L, Wu FX.
europepmc   +1 more source