TSG101 is associated with PEAV macropinocytosis. by Xiongnan Chen (13307178)

TAT.ARC protein administration in the contralateral ventricle decreased lesion volume in subregions of the ischemic territory after 24 h and 72 h after 60 min middle cerebral arter... by stefan donath (2809384)

ASO-miR-129-5p down-regulates miR-129-5p and reduces proliferation and migration of Hep-2 cells by MingHua Li (3522803)

“…<p>. (A) miR-129-5p expression was significantly decreased after ASO-miR-129-5p transfection compared to GFP transfection (control) or untreated Hep-2 cells (Hep-2 cell) measured by real-time RT-PCR. (* <i>P</i><0.05). …”

Image_5_5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas.tif by Jiheng Zhang (11953919)

“…Consequently, we identified four lncRNAs, including LINC00265, CIRBP-AS1, GDNF-AS1, and ZBTB20-AS4, and established a novel m5C-related lncRNAs signature (m5CrLS) that was effective in predicting prognosis. …”

Effects of AD- and UC-MSCs on PSNL-induced pain. by Kanako Miyano (3805288)

Overdiagnosis and overtreatment of thyroid cancer: A population-based temporal trend study by Sabrina Jegerlehner (4110049)

“…The incidence of early stages increased sharply, the incidence of advanced stages increased marginally, and the mortality from thyroid cancer decreased slightly. There was a three- to four-fold increase in the age-standardized annual thyroidectomy rate in both sexes.…”

Supplementary Material for: HIV-1 Nef Interacts with HCV Core, Recruits TRAF2, TRAF5 and TRAF6, and Stimulates HIV-1 Replication in Macrophages by Khan K.A. (4138834)

“…The knockdown of TRAF2, TRAF5 and TRAF6 resulted in decreased NF-κB activation and reduced HIV-1 replication in MDMs. …”

Representative photographs of exoprotein assessment in a 96-well master plate. by Marion Schoof (11999106)

“…Wells A1–3 (black box) contain MH96 (wild-type); A4–6 (red box) contain K18 (non-secretion control); A7–9, E5–8, and H10–12 (purple box) contain LB broth blanks. …”

Groups 5 and 6 Terminal Hydrazido(2−) Complexes: N_β Substituent Effects on Ligand-to-Metal Charge-Transfer Energies and Oxidation States by Ian A. Tonks (1724554)

“…Perturbing the electronic environment of the β (NR₂) nitrogen affects the energy of the lowest-energy charge-transfer (CT) transition in these complexes. For group 5 complexes, increasing the energy of the N_β lone pair decreases the ligand-to-metal CT (LMCT) energy, except for electron-rich niobium dialkylhydrazides, which pyramidalize N_β in order to reduce the overlap between the NbN_α π bond and the N_β lone pair. …”

Structure diagram of ensemble model. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Fitting formula parameter table. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Test plan. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Fitting surface parameters. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Model generalisation validation error analysis. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Empirical model prediction error analysis. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Fitting curve parameters. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Test instrument. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Empirical model establishment process. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Model prediction error trend chart. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”

Basic physical parameters of red clay. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …”