RdBV NSs2 competes with RSMV P in binding to RdSina and inhibits RdSina-mediated ubiquitination of RSMV P. by Hui Wang (30400)

“…When NSs2-HA was added, the binding between RdSina-Strep and P-His was decreased. (F) <i>In-vitro</i> ubiquitination assay showing that NSs2 inhibits RdSina-mediated ubiquitination of P. …”

Data Sheet 2_Screening of neurotransmitter receptor modulators reveals novel inhibitors of influenza virus replication.pdf by Yarou Gao (20620991)

“…Three representative compounds (isoxsuprine, ciproxifan, and rotigotine) inhibited H1N1 replication in a dose-dependent manner in multiple cell lines, and were effective against H1N1, oseltamivir-resistant H1N1, H3N2, and influenza B strains. …”

Distinct fates of dissolved organic nitrogen in the upper waters of Western Tropical North Pacific by Zhenwei YAN (22464244)

“…DON consumption occurred throughout the water column, with isotopic fractionation factors decreasing systematically with depth (ε = 6.0 ± 1.1‰ at surface to 1.5 ± 0.6‰ at 300 m). …”

Spatiotemporal dynamics of sea ice volume and their potential drivers in Liaodong Bay, China, using Sentinel-3 data over five ice seasons by Hongkun Ling (17858516)

Data and Supplemental Figures from: Effect of pH adjustments on a novel micellar casein-based edible 3D printing formulation by MICHAEL MCANULTY (20690693)

Environmental changes and human activities influence the spatial patterns of plant diversity in Eastern Eurasian Steppe by Danyu Wang (12380464)

Non-linear associations between serum manganese with chronic kidney disease: results from two nationwide studies in the United States and China by Jiliang Zhang (1500367)

“…The non-linear associations revealed that the OR values of CKD were decreased with Mn before reaching the threshold (OR = 0.65 per 1 μg/L increase of Mn in NHANES and 0.98 in CLHLS). …”

Role of macrophages, fibroblasts, and endothelial cells in rheumatoid arthritis (modified)–Expression overlay: PAS-highFIB-highGCX vs. Naive-noFIB-highGCX. by Melissa A. Hausburg (20529229)

“…PAS-highFIB-highGCX versus naïve-noFIB-highGCX log₂ fold-ratio values are overlayed upon the signaling pathway and are displayed as a simple color-intensity scale where magenta indicates increased and green indicates decreased protein abundance in PAS-highFIB-highGCX. …”

Analysis of the hankyphage DNA ends. by Sol Vendrell-Fernández (10053123)

“…(<b>d</b>) Zoom in on the 3′ end of the phage shows decreasing coverage of jmh43 chromosome over a ~ 2,300 nucleotide region indication packaging of a variable size fragment of the chromosome on the 3′ end of the phage of approximately 1–2.3kb. …”

Neurodevelopmental H2AK119ub enrichment within H3K4me3-positive promoters subdues transcription. by Aditya Parmar (22331873)

“…<p><b>(A)</b> Violin plots showing length-scaled abundance of H2AK119ub within H3K4me3 peak regions, P-values and D statistics by Kolmogorov-Smirnov D test (n = 4). …”

Image 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Data Sheet 4_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Data Sheet 6_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Data Sheet 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Data Sheet 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Image 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

Data Sheet 5_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…</p>Results<p>Five mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”

pH sensitive lipid polymeric hybrid nanoparticle (LPHNP) of paclitaxel and curcumin for targeted delivery in breast cancer by Hrishikesh Sarma (14827761)

“…</p> <p>LPHNPs co-loaded with curcumin (CUR) and paclitaxel (PTX) were successfully formulated, achieving a size of 146 nm, a PDI of 0.18, and an entrapment efficiency exceeding 90%. <i>In vitro</i> release studies demonstrated controlled release of CUR and PTX under tumor pH conditions showing 1.6 fold and 1.7 fold higher release in ABS pH 5 in comparison to PBS 7.4 for PTX and CUR respectively. …”

Insight into Greenhouse Gas Emission Characteristics of Light-Duty Vehicles in China Driven by Technological Innovation by Xinping Yang (17371783)

Image 4_Unraveling impact and potential mechanisms of baseline pain on efficacy of immunotherapy in lung cancer patients: a retrospective and bioinformatic analysis.jpg by Zexin Zhang (7507979)

“…A nomogram was constructed based on 6 independent prognostic factors with AUC values of 0.80 for 1-year, 0.73 for 2-year, and 0.80 for 3-year survival. …”