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Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of classification depended on the assessor's experience. This study aimed to develop a universal algorithm for HGSC-subtype classification using deep learning techniques. An artificial intelligence (AI)-based classification algorithm, which replicates the consensus diagnosis of pathologists, was formulated to analyze the morphological patterns and tumor-infiltrating lymphocyte counts for each tile extracted from whole slide images of ovarian HGSC available in The Cancer Genome Atlas (TCGA) data set. The accuracy of the algorithm was determined using the validation set from the Japanese Gynecologic Oncology Group 3022A1 (JGOG3022A1) and Kindai and Kyoto University (Kindai/Kyoto) cohorts. The algorithm classified the four HGSC-subtypes with mean accuracies of 0.933, 0.910, and 0.862 for the TCGA, JGOG3022A1, and Kindai/Kyoto cohorts, respectively. To compare mesenchymal transition (MT) with non-MT groups, overall survival analysis was performed in the TCGA data set. The AI-based prediction of HGSC-subtype classification in TCGA cases showed that the MT group had a worse prognosis than the non-MT group (P = 0.017). Furthermore, Cox proportional hazard regression analysis identified AI-based MT subtype classification prediction as a contributing factor along with residual disease after surgery, stage, and age. In conclusion, a robust AI-based HGSC-subtype classification algorithm was established using virtual slides of ovarian HGSC.

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study developed two convolutional neural network models to detect TILs and to determine their spatial location in whole slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8+T cells and immune gene expressions. Patients with a higher density of intraepithelial TILs had a significantly prolonged overall survival and progression-free survival in multiple cohorts. On the basis of the density of intraepithelial and stromal TILs, patients were classified into three immunophenotypes: immune inflamed, excluded, and desert. The immune-desert subgroup showed the worst prognosis. Gene expression analysis showed that the immune-desert subgroup had lower immune cytolytic activity and T-cell–inflamed gene-expression profile scores, whereas the immune-excluded subgroup had higher expression of interferon-γ and programmed death 1 receptor signaling pathway. The established evaluation method provided detailed and comprehensive quantification of intraepithelial and stromal TILs throughout hematoxylin and eosin–stained slides. It has potential for clinical application for personalized treatment of patients with ovarian cancer.

Squeezing bubbles and impurities out of interlayer spaces by applying force through a few-layer graphene capping layer leads to van der Waals heterostructures with the ultraflat structure free from random electrostatic potential arising from charged impurities. Without the graphene capping layer, a squeezing process with an AFM tip induces applied-force-dependent charges of Δn∼ 2 × 1012cm–2μN–1, resulting in the significant intensity of trions in photoluminescence spectra of MoSe2at low temperature. We found that a hBN/MoSe2/hBN prepared with the “graphene-capping-assisted AFM nano-squeezing method” shows a strong excitonic emission with negligible trion peak, and the residual line width of the exciton peak is only 2.2 meV, which is comparable to the homogeneous limit. Furthermore, in this high-quality sample, we found that the formation of biexciton occurs even at extremely low excitation power (Φph∼ 2.3 × 1019cm–2s–1) due to the enhanced collisions between excitons.

Although cyclooxygenase inhibitors effectively suppress uterine contraction, constriction of the fetal ductus arteriosus (DA) and oligohydramnios are major concerns. Celecoxib, a selective cyclooxygenase 2 inhibitor, is a potential potent tocolytic agent, but there are no studies that have evaluated the beneficial or adverse effects of celecoxib use on fetuses for more than 48 hours in pregnant women. We therefore aimed to evaluate the effect of middle-long-term celecoxib administration on the fetus during the second trimester of pregnancy, particularly in terms of fetal DA and amniotic fluid volume.

To investigate the factors that stratify high-risk cases among subchorionic hematomas (SCHs) patients with persistent vaginal bleeding in early pregnancy.

A water-soluble polymer having galactose pendant groups was prepared by the synthesis and radical polymerization of p-vinylbenzyl galactoside. Copolymerization of the galactoside with p-vinylphenyl acetate and subsequent [125I]labeling by a chloramine-T method afforded a radio-labeled galactose-containing polymer, and the body distribution of the polymer in mice was examined along with that of galactosylated bovine serum albumin (BSA). Both [125I]labeled galactose-containing polymer and [14C]labeled galactosylated BSA highly accumulated in the liver (>90%) soon after intravenous administration. The excretion of the synthetic vinyl polymer from the liver was very slow, and 92% and 63% of the administered radioactivity still remained in the liver 2 and 24 h after the injection, respectively, while only 18% of the radioactivity was recovered 2 h after the injection of [14C]labeled galactosylated BSA.