Different steps of the fabrication process. by Md. Abu Daud (21485629)

Image 2_G. vaginalis increases HSV-2 infection by decreasing vaginal barrier integrity and increasing inflammation in vivo.tif by Nuzhat Rahman (16660416)

“…The vaginal epithelium of G. vaginalis inoculated mice showed decreased DSG-1 staining compared to other groups, indicating compromised barrier function. …”

Image 5_G. vaginalis increases HSV-2 infection by decreasing vaginal barrier integrity and increasing inflammation in vivo.tif by Nuzhat Rahman (16660416)

“…The vaginal epithelium of G. vaginalis inoculated mice showed decreased DSG-1 staining compared to other groups, indicating compromised barrier function. …”

Image 3_G. vaginalis increases HSV-2 infection by decreasing vaginal barrier integrity and increasing inflammation in vivo.tif by Nuzhat Rahman (16660416)

“…The vaginal epithelium of G. vaginalis inoculated mice showed decreased DSG-1 staining compared to other groups, indicating compromised barrier function. …”

Image 1_G. vaginalis increases HSV-2 infection by decreasing vaginal barrier integrity and increasing inflammation in vivo.tif by Nuzhat Rahman (16660416)

“…The vaginal epithelium of G. vaginalis inoculated mice showed decreased DSG-1 staining compared to other groups, indicating compromised barrier function. …”

Image 4_G. vaginalis increases HSV-2 infection by decreasing vaginal barrier integrity and increasing inflammation in vivo.tif by Nuzhat Rahman (16660416)

“…The vaginal epithelium of G. vaginalis inoculated mice showed decreased DSG-1 staining compared to other groups, indicating compromised barrier function. …”

Decrease of cellular cAMP levels in response to a concentration range of melatonin treatments. by Cathryn S. D. Maienza (20629929)

Decreased clonogenic capacity of U87MG and U251MG glioma cells dependent on SHG-44 concentration. by Denis Mustafov (19137870)

Actual measurement of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Significant gene set results from EGSEA. by Katherine M. Peterson (19746455)

The image illustrates the five steps of the experiment. by Deborah Ribeiro Frazão (9188152)

The distribution map of flat spectral shape index. by Desheng Xie (21439869)

Multiscale QM/MM Simulations Identify the Roles of Asp239 and 1‑OH···Nucleophile in Transition State Stabilization in Arabidopsis thaliana Cell-Wall Invertase 1 by Wijitra Jitonnom (22410515)

“…Deglycosylation is predicted to be the rate-determining step in the reaction, with a calculated overall free-energy barrier of 15.9 kcal/mol, consistent with the experimental barrier (15.3 kcal/mol). …”

Inhibition of PGAM5 and apoptosis prevented <i>T. spiralis</i> larval invasion of Caco-2 monolayer. by Qi Qi Lu (17721401)

Subjects:

Y-27632 synergized with BA to alleviate the decrease in the expression of and abnormal localization of ZO-1 and Occludin in LPS-induced Caco2 cells. by Luqiong Liu (11537092)

Creep failure mode and sketch map of slow-step fractured rock. by Dengke Yang (842532)

Comparison of diffusion simulations: implicit scheme of the GDE with a 30-second time step (blue line), implicit scheme of the PNGM with α = 0.6 and a 15-second time step (green li... by Mouad Klai (20818364)

Modal shape of the gyration platform. by Shan Gao (46743)

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error manual calculation process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”