Fig 2 - by Hyunyoung Jeong (4385848)

Cellular GSH levels in the αA and αB crystallin knockout (KO) mouse retina. by Parameswaran G. Sreekumar (176748)

“…Data, presented as percentage over control age-matched mice, showed a significant 50% decrease in GSH level in the neural retina and a ∼25–30% decrease in the RPE/choroid in αA crystallin KO (αA −/−) and αB crystallin KO (αB −/−) samples. …”

Cyclin G2 is a target molecule of Cn/NFATc2 in follicular keratinocytes. by Atsushi Fujimura (227683)

“…<p>(A) The microarray analysis identified 24 genes that showed down-regulated expression in PHK cells treated with either 11R-VIVIT or CsA; <i>ccng2</i> (cyclin G2) expression showed the greatest decrease after Cn/NFAT inhibition. …”

Image_1_SmTAL-9, a Member of the Schistosoma mansoni Tegument Allergen-Like Family, Is Important for Parasite Survival and a Putative Target for Drug/Vaccine Development.tiff by Wilma Patrícia de Oliveira Santos Bernardes (5922452)

Image_2_SmTAL-9, a Member of the Schistosoma mansoni Tegument Allergen-Like Family, Is Important for Parasite Survival and a Putative Target for Drug/Vaccine Development.tiff by Wilma Patrícia de Oliveira Santos Bernardes (5922452)

Image_3_SmTAL-9, a Member of the Schistosoma mansoni Tegument Allergen-Like Family, Is Important for Parasite Survival and a Putative Target for Drug/Vaccine Development.tiff by Wilma Patrícia de Oliveira Santos Bernardes (5922452)

Reduction of glucose in the culture medium sensitizes breast cancer cells to metformin treatment but not human mammary epithelial MCF10A cells. by Yongxian Zhuang (634693)

“…<p>All cells were treated with different concentrations of metformin (0, 2, 4, 8, 16 mM) in medium containing different levels of glucose (0, 2.5, 5, 10, 15, 25 mM) for one day. Percentage of dead cells was determined using Sytox Green staining. …”

Data obtained from monitoring patients. by Ana Gabriela Gomes Ferrari Strang (17068913)

“…Three decreasing values of immunoglobulin G were a security parameter for stopping the child’s medication in the exposed group (50/61). …”

General characteristics and statistical analysis. by Ana Gabriela Gomes Ferrari Strang (17068913)

“…Three decreasing values of immunoglobulin G were a security parameter for stopping the child’s medication in the exposed group (50/61). …”

S2 File - by Young Chang (3666829)

Postmortem confirmation of tetrode placement. by Alice Berners-Lee (15354255)

The age distribution of the patients. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Comparison experiments. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

External validation comparison results. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Patient characteristics. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Comparison with baseline methods. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

The details of the channel attention module. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Ablation experiments. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

Pathological diagnosis. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”

The details of ECRNet. by Ruijie Wang (5989841)

“…On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. …”