Functional characterization of GF-TTMn synaptic defects of mutant L1CAM protein expressions in <i>nrg¹⁴</i>;P[nrg180^ΔFIGQY] background. by Sirisha Kudumala (470461)

“…However, in most responding animals that had a decreased ability to follow at a one-to-one ratio at 100 Hz, the Response Latency was increased indicating a reduction in synaptic strength for the GF to TTMn connection.…”

Aspergillus fumigatus G-protein coupled receptors GprM and GprJ are important for the regulation of the cell wall integrity pathway, secondary metabolite production, and virulence by Gustavo Goldman (8849927)

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

Data Sheet 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

Image 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

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

“…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”

DataSheet1_D-Cysteine Ethyl Ester Reverses the Deleterious Effects of Morphine on Breathing and Arterial Blood–Gas Chemistry in Freely-Moving Rats.docx by Paulina M. Getsy (11465254)

Distinct Roles of MicroRNA-1 and -499 in Ventricular Specification and Functional Maturation of Human Embryonic Stem Cell-Derived Cardiomyocytes by Ji-Dong Fu (196646)

“…</p> <h3>Methods and Results</h3><p>We hypothesized that miRs that figure prominently in cardiac differentiation are differentially expressed in differentiating, developing, and terminally mature human cardiomyocytes (CMs). As a first step, we mapped the miR profiles of human (h) embryonic stem cells (ESCs), hESC-derived (hE), fetal (hF) and adult (hA) ventricular (V) CMs. 63 miRs were differentially expressed between hESCs and hE-VCMs. …”

Upshift of Phase Transition Temperature in Nanostructured PbTiO₃ Thick Film for High Temperature Applications by Jungho Ryu (1587565)

“…A large-signal effective <i>d</i>_33,eff value of >60 pm/V is achieved at room temperature. …”

Upshift of Phase Transition Temperature in Nanostructured PbTiO₃ Thick Film for High Temperature Applications by Jungho Ryu (1587565)

“…A large-signal effective <i>d</i>_33,eff value of >60 pm/V is achieved at room temperature. …”

Upshift of Phase Transition Temperature in Nanostructured PbTiO₃ Thick Film for High Temperature Applications by Jungho Ryu (1587565)

“…A large-signal effective <i>d</i>_33,eff value of >60 pm/V is achieved at room temperature. …”

Additional file 3 of Sub-minute acquisition with deep learning-based image filter in the diagnosis of colorectal cancers using total-body 18F-FDG PET/CT by Entao Liu (385423)

Intracellular Zn2+ Promotes Extracellular Matrix Remodeling in Dexamethasone-Treated Trabecular Meshwork by ying Liu (18009823)

Growth and contents of organic and inorganic solutes in amaranth under salt stress by Renata Velasques Menezes (10448393)

Pain evaluation in newborns using the Neonatal Facial Activity Coding scale during blood gases analysis by Isis de Oliveira Pinheiro (10477598)

After 48 h of incubation IFNγ dose-dependently induced an arrest in the S-phase of the cell cycle of BON cells by Michael Höpfner (56461)