RICTOR regulates UGCG expression via transcription factor Zinc Finger X-linked (ZFX). by Mohammad Nafees Ansari (22232505)

“…<b>(L, M)</b> Fold change (mean ± SEM, <i>n</i> = 5) in ceramides (L) and glucosylceramides (M) confirms a decrease in ceramides and an increase in glucosylceramides in MCF-7_ZFX^OE cells. …”

Changes in cytokine production over the second week of culture. by Nils Ågren (21474419)

“…The decrease in IFN-γ production between days 9 and 14 was significant in all groups. …”

PRMT5 regulates alternative splicing landscape under hypoxia. by Srinivas Abhishek Mutnuru (22513457)

“…<p><b>A)</b> Pie chart showing distribution of different types of significant AS events (FDR < 0.05) in shCTRL vs. shPRMT5 MDA-MB-231 cells under hypoxia. …”

[A] Histopathological images of pancreas, liver, kidney, and heart tissues from the studied rat groups, stained with H&E. by Mohamed Lotfy (18599184)

SLC response kinematics at 6 dpf. by Morgan Barnes (7876373)

“…<p>(A-B) C1 is the first C-bend performed. The angle and duration of the C1 bend is significantly decreased in 24 + fish (p < 0.0001 and p < 0.05) compared to the 24- fish and the C1 angle is decreased in 72 + fish (p < 0.05). …”

SLC response kinematics at 28 dpf. by Morgan Barnes (7876373)

“…<p>(A-B) C1 is the first C-bend performed. The angle and duration of the C1 bend is not significantly altered at this time point. …”

Cortical and subcortical regions feature distinct early and late responses during audition. by Sarah H. McGill (22505225)

“…The mean no-stimulus trial spectrograms were subtracted from the mean maximum-intensity trial spectrograms, and a cluster-based permutation testing was employed to identify significant differences between the conditions (p < 0.05, 5000 iterations). …”

Passive listening and go/No-go tasks feature comparable electrophysiological responses. by Sarah H. McGill (22505225)

“…The mean no-stimulus trial spectrograms were subtracted from the mean maximum-intensity trial spectrograms, and a cluster-based permutation testing was employed to identify significant differences between the conditions (p < 0.05, 5000 iterations). …”

Characterization of Developmentally Dynamic Promoters (DDPs). by Jiang Tan (260415)

Pediatric CPP with Praat and ADSV (Joshi et al., 2025) by Ashwini Joshi (21594817)

“…Age and <i>F</i>0 are significant predictors of CPP; however, the observed increase in CPP with increasing age in males is primarily due to the substantial decrease in <i>F</i>0 postpuberty. …”

Heat map showing correlations between comet assay parameters, and warm and cold ischemia times. by Miroslava Jandová (22553132)

“…<p>Red values are significant at p < 0.05. Negative values mean that there is a “the more, the less” relationship between the quantities, i.e., as one quantity increases, the other quantity decreases. …”

Effect size distribution and intersections of transcript usage response upon stimulation with <i>M</i>. <i>leprae</i> sonicate by T1R-free (LEP) and T1R-destined (T1R) leprosy pati... by Wilian Correa-Macedo (11813183)

“…<p>(<b>A</b>) Strip plot presenting the distribution of the mean fitted proportion difference (PΔ) between stimulated and non-stimulated samples by group. …”

MDSC inhibition was correlated with Trp metabolism in 17ZR101-infected lungs. by Qi Xu (134661)

“…(f) Volcano plot analysis of the significantly increased or decreased metabolites. n=6/group. …”

<i>ADH7, FABP5, ALDH1A1, CRABP-2, PPARγ</i> and <i>VEGFA</i> mRNA and ADH7, FABP5, CRABP-2, PPARγ and VEGFA protein levels in limbal stromal cells (LSCs) and aniridia limbal stroma... by Shuailin Li (11907158)

“…Furthermore, 0.078 and 0.313 μg/mL travoprost treatment significantly decreased ADH7 protein levels in LSCs (p = 0.039; p < 0.001) and 0.313 μg/mL travoprost treatment significantly increased ADH7 protein levels in AN-LSCs, compared to their untreated controls (p = 0.039) <b>(B, C)</b>. …”

Dataset visualization diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

Dataset sample images. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

Performance comparison of different models. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

C2f and BC2f module structure diagrams. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

YOLOv8n detection results diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”

YOLOv8n-BWG model structure diagram. by Yaojun Zhang (389482)

“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”