The TOR inhibitors Rapamycin and AZD-8055 strongly reduce RPS6 phosphorylation and cell proliferation in Vasa2+/Piwi1+ cells. by Eudald Pascual-Carreras (12115380)

“…<i>n</i> = 2–4 biological replicates per condition, with 15 individuals per replicate. Significance levels for Student <i>t</i> test are indicated for adjusted <i>p</i> values: *<i>p</i> < 0.05, ***<i>p</i> < 0.001, ***<i>p</i> < 0.0001. d: day(s), n.s.: non-significant. …”

Responses to speech onset and target nouns in relation to cognitive decline and context. by Elena Bolt (20396190)

Effects of MC treatment on protein expression in DNBS-induced colitis rats. by Jin-Hwa Kim (101817)

Gene expression of the <i>hsp70Ab</i>-group and <i>hsp68</i> genes after baculovirus infection under different heat shock stimuli. by Enrique Paz-Cortés (20988196)

Effects of MC treatment on symptoms and histological changes in DNBS-induced colitis rats. by Jin-Hwa Kim (101817)

KO of iPLA₂γ attenuates development of albuminuria in STZ-induced diabetic nephropathy. by Andrey V. Cybulsky (4007012)

Impact of including phylogenetic eigenvectors on detection of coevolution of gene-expression levels in fungi. by Joshua G. Schraiber (8027060)

Performance of different methods for controlling confounding in Felsenstein’s worst case. by Joshua G. Schraiber (8027060)

Myeloid knockout <i>VANGL2</i> exacerbates the progression of DSS-induced colitis in mice. by Huaji Jiang (16907514)

Down-regulation of VANGL2 in IBD patients triggers overt activation of NLRP3 inflammasome. by Huaji Jiang (16907514)

Lys823 in NLRP3 is essential for its K27-linked ubiquitination and autophagic degradation. by Huaji Jiang (16907514)

VANGL2 specifically inhibits the activation of NLRP3 inflammasome. by Huaji Jiang (16907514)

VANGL2 recruits NLRP3 to OPTN for selective autophagic degradation. by Huaji Jiang (16907514)

VANGL2 recruits MARCH8 to promote the K27-linked ubiquitination of NLRP3. by Huaji Jiang (16907514)

Complexity comparison of different models. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Flow of operation of improved KMA. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Improved DAE based on LSTM. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Autoencoder structure. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Analysis of differential microbiome and classification prediction model between case and control groups. by Chuan Zhang (187157)

“…<p><b>(A)</b> Linear discriminant analysis [LDA; (log10)>2] and (B) effect size (LEfSe) analysis revealed significant differences (P < 0.01) in the microbiota of the case (orange, negative score) and control groups (blue, positive score) groups. …”