Comprehensive EHMT1 variants analysis broadens genotype-phenotype associations and molecular mechanisms in Kleefstra syndrome.

The shift to a genotype-first approach in genetic diagnostics has revolutionized our understanding of neurodevelopmental disorders, expanding both their molecular and phenotypic spectra. Kleefstra syndrome (KLEFS1) is caused by EHMT1 haploinsufficiency and exhibits broad clinical manifestations. EHMT1 encodes euchromatic histone methyltransferase-1-a pivotal component of the epigenetic machinery. We have recruited 209 individuals with a rare EHMT1 variant and performed comprehensive molecular in silico and in vitro testing alongside DNA methylation (DNAm) signature analysis for the identified variants. We (re)classified the variants as likely pathogenic/pathogenic (molecularly confirming Kleefstra syndrome) in 191 individuals. We provide an updated and broader clinical and molecular spectrum of Kleefstra syndrome, including individuals with normal intelligence and familial occurrence. Analysis of the EHMT1 variants reveals a broad range of molecular effects and their associated phenotypes, including distinct genotype-phenotype associations. Notably, we showed that disruption of the "reader" function of the ankyrin repeat domain by a protein altering variant (PAV) results in a KLEFS1-specific DNAm signature and milder phenotype, while disruption of only "writer" methyltransferase activity of the SET domain does not result in KLEFS1 DNAm signature or typical KLEFS1 phenotype. Similarly, N-terminal truncating variants result in a mild phenotype without the DNAm signature. We demonstrate how comprehensive variant analysis can provide insights into pathogenesis of the disorder and DNAm signature. In summary, this study presents a comprehensive overview of KLEFS1 and EHMT1, revealing its broader spectrum and deepening our understanding of its molecular mechanisms, thereby informing accurate variant interpretation, counseling, and clinical management.

Eye Lens Radiation Dose to Nurses during Cardiac Interventional Radiology: An Initial Study.

Although interventional radiology (IVR) is preferred over surgical procedures because it is less invasive, it results in increased radiation exposure due to long fluoroscopy times and the need for frequent imaging. Nurses engaged in cardiac IVR receive the highest lens radiation doses among medical workers, after physicians. Hence, it is important to measure the lens exposure of IVR nurses accurately. Very few studies have evaluated IVR nurse lens doses using direct dosimeters. This study was conducted using direct eye dosimeters to determine the occupational eye dose of nurses engaged in cardiac IVR, and to identify simple and accurate methods to evaluate the lens dose received by nurses. Over 6 months, in a catheterization laboratory, we measured the occupational dose to the eyes (3 mm dose equivalent) and neck (0.07 mm dose equivalent) of nurses on the right and left sides. We investigated the relationship between lens and neck doses, and found a significant correlation. Hence, it may be possible to estimate the lens dose from the neck badge dose. We also evaluated the appropriate position (left or right) of eye dosimeters for IVR nurses. Although there was little difference between the mean doses to the right and left eyes, that to the right eye was slightly higher. In addition, we investigated whether it is possible to estimate doses received by IVR nurses from patient dose parameters. There were significant correlations between the measured doses to the neck and lens, and the patient dose parameters (fluoroscopy time and air kerma), implying that these parameters could be used to estimate the lens dose. However, it may be difficult to determine the lens dose of IVR nurses accurately from neck badges or patient dose parameters because of variation in the behaviors of nurses and the procedure type. Therefore, neck doses and patient dose parameters do not correlate well with the radiation eye doses of individual IVR nurses measured by personal eye dosimeters. For IVR nurses with higher eye doses, more accurate measurement of the radiation doses is required. We recommend that a lens dosimeter be worn near the eyes to measure the lens dose to IVR nurses accurately, especially those exposed to relatively high doses.

Evaluation of a New Real-Time Dosimeter Sensor for Interventional Radiology Staff.

In 2011, the International Commission on Radiological Protection (ICRP) recommended a significant reduction in the lens-equivalent radiation dose limit, thus from an average of 150 to 20 mSv/year over 5 years. In recent years, the occupational dose has been rising with the increased sophistication of interventional radiology (IVR); management of IVR staff radiation doses has become more important, making real-time radiation monitoring of such staff desirable. Recently, the i3 real-time occupational exposure monitoring system (based on RaySafeTM) has replaced the conventional i2 system. Here, we compared the i2 and i3 systems in terms of sensitivity (batch uniformity), tube-voltage dependency, dose linearity, dose-rate dependency, and angle dependency. The sensitivity difference (batch uniformity) was approximately 5%, and the tube-voltage dependency was <±20% between 50 and 110 kV. Dose linearity was good (R2 = 1.00); a slight dose-rate dependency (~20%) was evident at very high dose rates (250 mGy/h). The i3 dosimeter showed better performance for the lower radiation detection limit compared with the i2 system. The horizontal and vertical angle dependencies of i3 were superior to those of i2. Thus, i3 sensitivity was higher over a wider angle range compared with i2, aiding the measurement of scattered radiation. Unlike the i2 sensor, the influence of backscattered radiation (i.e., radiation from an angle of 180°) was negligible. Therefore, the i3 system may be more appropriate in areas affected by backscatter. In the future, i3 will facilitate real-time dosimetry and dose management during IVR and other applications.

Clip Formation in the Complementarity Determining Region of Bevacizumab Lowers Monomer Stability and Affinity for Both FcRn and FcγR: A Comprehensive Characterization of the Clipped Variant Including its Higher Order Structure.

The presence of monoclonal antibody (mAb) fragments in pharmaceutical mAb products is a critical quality attribute and should be controlled for safety. Several mAb fragments derived from clip formation in the complementarity determining regions (CDRs), as well as from cleavage in the hinge region, have been reported. However, the properties of CDR-clipped variants are not fully understood because of difficulties in separating them from intact mAbs under non-denaturing conditions due to similarities in size. We have established a method for separating CDR-clipped variants under non-denaturing conditions using an appropriate size exclusion chromatography column.1 In this report, we provide a comprehensive characterization of a CDR-clipped variant from bevacizumab. The variant exhibited a lower pI, a higher tendency to form dimers, and a lower affinity for both neonatal Fc receptor (FcRn) and Fcγ receptor (FcγR). The effects of clip formation in CDR H3 on the higher order structure were analyzed by hydrogen/deuterium exchange mass spectrometry, and the observed changes in the structures of the VH, CH2, and VL domains were in agreement with the lowered affinity for antigen, FcRn, and FcγR. These findings suggest that clip formation in the CDR may affect the efficacy, safety, and pharmacokinetics of pharmaceutical mAbs.

Comparison of Fine-Tuned Deep Convolutional Neural Networks for the Automated Classification of Lung Cancer Cytology Images with Integration of Additional Classifiers.

OBJECTIVE: It is essential to accurately diagnose and classify histological subtypes into adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small cell lung carcinoma (SCLC) for the appropriate treatment of lung cancer patients. However, improving the accuracy and stability of diagnosis is challenging, especially for non-small cell carcinomas. The purpose of this study was to compare multiple deep convolutional neural network (DCNN) technique with subsequent additional classifiers in terms of accuracy and characteristics in each histology. METHODS: Lung cancer cytological images were classified into ADC, SCC, and SCLC with four fine-tuned DCNN models consisting of AlexNet, GoogLeNet (Inception V3), VGG16 and ResNet50 pretrained by natural images in ImageNet database. For more precise classification, the figures of 3 histological probabilities were further applied to subsequent machine learning classifiers using Naïve Bayes (NB), Support vector machine (SVM), Random forest (RF), and Neural network (NN). RESULTS: The classification accuracies of the AlexNet, GoogLeNet, VGG16 and ResNet50 were 74.0%, 66.8%, 76.8% and 74.0%, respectively. Well differentiated typical morphologies were tended to be correctly judged by all four architectures. However, poorly differentiated non-small cell carcinomas lacking typical structures were inclined to be misrecognized in some DCNNs. Regarding the histological types, ADC were best judged by AlexNet and SCC by VGG16. Subsequent machine learning classifiers of NB, SVV, RF, and NN improved overall accuracies to 75.1%, 77.5%, 78.2%, and 78.9%, respectively. CONCLUSION: Fine-tuning DCNNs in combination with additional classifiers improved classification of cytological diagnosis of lung cancer, although classification bias could be indicated among DCNN architectures.

Mammalian HEMK1 methylates glutamine residue of the GGQ motif of mitochondrial release factors.

Despite limited reports on glutamine methylation, methylated glutamine is found to be highly conserved in a "GGQ" motif in both prokaryotes and eukaryotes. In bacteria, glutamine methylation of peptide chain release factors 1/2 (RF1/2) by the enzyme PrmC is essential for translational termination and transcript recycling. Two PrmC homologs, HEMK1 and HEMK2, are found in mammals. In contrast to those of HEMK2, the biochemical properties and biological significance of HEMK1 remain largely unknown. In this study, we demonstrated that HEMK1 is an active methyltransferase for the glutamine residue of the GGQ motif of all four putative mitochondrial release factors (mtRFs)-MTRF1, MTRF1L, MRPL58, and MTRFR. In HEMK1-deficient HeLa cells, GGQ motif glutamine methylation was absent in all the mtRFs. We examined cell growth and mitochondrial properties, but disruption of the HEMK1 gene had no considerable impact on the overall cell growth, mtDNA copy number, mitochondrial membrane potential, and mitochondrial protein synthesis under regular culture condition with glucose as a carbon source. Furthermore, cell growth potential of HEMK1 KO cells was still maintained in the respiratory condition with galactose medium. Our results suggest that HEMK1 mediates the GGQ methylation of all four mtRFs in human cells; however, this specific modification seems mostly dispensable in cell growth and mitochondrial protein homeostasis at least for HeLa cells under fermentative culture condition.

Erratum: Derepression of inflammation-related genes link to microglia activation and neural maturation defect in a mouse model of Kleefstra syndrome.

[This corrects the article DOI: 10.1016/j.isci.2021.102741.].

Estimating subjective evaluation of low-contrast resolution using convolutional neural networks.

To develop a convolutional neural network-based method for the subjective evaluation of computed tomography (CT) images having low-contrast resolution due to imaging conditions and nonlinear image processing. Four radiological technologists visually evaluated CT images that were reconstructed using three nonlinear noise reduction processes (AIDR 3D, AIDR 3D Enhanced, AiCE) on a CT system manufactured by CANON. The visual evaluation consisted of two items: low contrast detectability (score: 0-9) and texture pattern (score: 1-5). Four AI models with different convolutional and max pooling layers were constructed and trained on pairs of CANON CT images and average visual assessment scores of four radiological technologists. CANON CT images not used for training were used to evaluate prediction performance. In addition, CT images scanned with a SIEMENS CT system were input to each AI model for external validation. The mean absolute error and correlation coefficients were used as evaluation metrics. Our proposed AI model can evaluate low-contrast detectability and texture patterns with high accuracy, which varies with the dose administered and the nonlinear noise reduction process. The proposed AI model is also expected to be suitable for upcoming reconstruction algorithms that will be released in the future.

A loss-of-function variant in SUV39H2 identified in autism-spectrum disorder causes altered H3K9 trimethylation and dysregulation of protocadherin ß-cluster genes in the developing brain.

Recent evidence has documented the potential roles of histone-modifying enzymes in autism-spectrum disorder (ASD). Aberrant histone H3 lysine 9 (H3K9) dimethylation resulting from genetic variants in histone methyltransferases is known for neurodevelopmental and behavioral anomalies. However, a systematic examination of H3K9 methylation dynamics in ASD is lacking. Here we resequenced nine genes for histone methyltransferases and demethylases involved in H3K9 methylation in individuals with ASD and healthy controls using targeted next-generation sequencing. We identified a novel rare variant (A211S) in the SUV39H2, which was predicted to be deleterious. The variant showed strongly reduced histone methyltransferase activity in vitro. In silico analysis showed that the variant destabilizes the hydrophobic core and allosterically affects the enzyme activity. The Suv39h2-KO mice displayed hyperactivity and reduced behavioral flexibility in learning the tasks that required complex behavioral adaptation, which is relevant for ASD. The Suv39h2 deficit evoked an elevated expression of a subset of protocadherin ß (Pcdhb) cluster genes in the embryonic brain, which is attributable to the loss of H3K9 trimethylation (me3) at the gene promoters. Reduced H3K9me3 persisted in the cerebellum of Suv39h2-deficient mice to an adult stage. Congruently, reduced expression of SUV39H1 and SUV39H2 in the postmortem brain samples of ASD individuals was observed, underscoring the role of H3K9me3 deficiency in ASD etiology. The present study provides direct evidence for the role of SUV39H2 in ASD and suggests a molecular cascade of SUV39H2 dysfunction leading to H3K9me3 deficiency followed by an untimely, elevated expression of Pcdhb cluster genes during early neurodevelopment.

Derepression of inflammation-related genes link to microglia activation and neural maturation defect in a mouse model of Kleefstra syndrome.

Haploinsufficiency of EHMT1, which encodes histone H3 lysine 9 (H3K9) methyltransferase G9a-like protein (GLP), causes Kleefstra syndrome (KS), a complex disorder of developmental delay and intellectual disability. Here, we examined whether postnatal supply of GLP can reverse the neurological phenotypes seen in Ehmt1 Δ/+ mice as a KS model. Ubiquitous GLP supply from the juvenile stage ameliorated behavioral abnormalities in Ehmt1 Δ/+ mice. Postnatal neuron-specific GLP supply was not sufficient for the improvement of abnormal behaviors but still reversed the reduction of H3K9me2 and spine number in Ehmt1 Δ/+ mice. Interestingly, some inflammatory genes, including IL-1ß (Il1b), were upregulated and activated microglial cells increased in the Ehmt1 Δ/+ brain, and such phenotypes were also reversed by neuron-specific postnatal GLP supply. Il1b inactivation canceled the microglial and spine number phenotypes in the Ehmt1 Δ/+ mice. Thus, H3K9me2 and some neurological phenotypes are reversible, but behavioral abnormalities are more difficult to improve depending on the timing of GLP supply.

Development of Pathological Diagnosis Support System Using Micro-computed Tomography.

In pathological diagnosis, the cutting position of pathological materials is subjectively determined by pathologists. This leads to a low cutting accuracy, which in turn may lead to incorrect diagnoses. In this study, we developed a system that supports the determination of the cutting position by visualizing and analyzing the internal structure of pathological material using micro-computed tomography (CT) before cutting. This system consists of a dedicated micro-CT and cutting support software. The micro-CT system has a fixture for fixing the target, enabling the scanning of easily deformable pathological materials. In the cutting support software, a function that interactively selects the extraction plane while displaying the volume rendering image and outputs a pseudo-histological image was implemented. Our results confirmed that the pseudo-histological image showed the fine structure inside the organ and that the latter image was highly consistent with the pathological image.

Mutual stain conversion between Giemsa and Papanicolaou in cytological images using cycle generative adversarial network.

OBJECTIVE: Papanicolaou and Giemsa stains used in cytology have different characteristics and complementary roles. In this study, we focused on cycle-consistent generative adversarial network (CycleGAN), which is an image translation technique using deep learning, and we conducted mutual stain conversion between Giemsa and Papanicolaou in cytological images using CycleGAN. METHODS: A total of 191 Giemsa-stained images and 209 Papanicolaou-stained images were collected from 63 patients with lung cancer. From those images, 67 images from nine cases were used for testing and the remaining images were used for training. For data augmentation, the number of training images was increased by rotation and inversion, and the images were pipelined to CycleGAN to train the mutual conversion process involving Giemsa- and Papanicolaou-stained images. Three pathologists and three cytotechnologists performed visual evaluations of the authenticity of cell nuclei, cytoplasm, and cell layouts of the test images translated using CycleGAN. RESULTS: As a result of converting Giemsa-stained images into Papanicolaou-stained images, the background red blood cell patterns present in Giemsa-stained images disappeared, and cell patterns that reproduced the shape and staining of the cell nuclei and cytoplasm peculiar to Papanicolaou staining were obtained. Regarding the reverse-translated results, nuclei became larger, and red blood cells that were not evident in Papanicolaou-stained images appeared. After visual evaluation, although actual images exhibited better results than converted images, the results were promising for various applications. DISCUSSION: The stain translation technique investigated in this paper can complement specimens under conditions where only single stained specimens are available; it also has potential applications in the massive training of artificial intelligence systems for cell classification, and can also be used for training cytotechnologist and pathologists.

Optimal phase analysis of electrocardiogram-gated computed tomography angiography in patients with Stanford type A acute aortic dissection.

OBJECTIVE: To determine the phase that facilitates flap observation of the ascending aorta in Stanford type A acute aortic dissection with perfused false lumen. METHODS: We reconstructed retrospective Electrocardiogram-gated Computed Tomography Angiography images of the ascending aorta of all 20 patients to 20 phases of curved-multiplanar reconstruction in 5% increment. One radiologist created and randomized 10 cross-sectional images of each phase for every patient and two radiologists scored these images on a 5-point scale depending on the degree of flap stoppage. We calculated the average score for each phase of each case and compared them among the three groups. RESULTS: Image scores were significantly better in the 65 %-100 % R-R interval group than those in the 5%-30 % (p < 2e-16) and 35 %-60 % R-R interval groups(p = 7.2e-10). Similar scores were observed in the Heart Rate > 70 group (p = 0.00039, 2.2e-14). Moreover a similar tendency was observed in the arrhythmia group (p = 0.0035, 0.294). No difference was found in the degree of flap stoppage in the 65 %-100 % R-R interval group between the Heart Rate > 70 and Heart Rate ≤ 70 groups (p = 0.466) and between the arrhythmia and non-arrhythmia groups (p = 0.1240). CONCLUSION: In observing the ascending aorta, We obtained a good image at 65 %-100 % R-R interval and similar tendency was observed in the patients with arrhythmia.

Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks.

Cytology is the first pathological examination performed in the diagnosis of lung cancer. In our previous study, we introduced a deep convolutional neural network (DCNN) to automatically classify cytological images as images with benign or malignant features and achieved an accuracy of 81.0%. To further improve the DCNN's performance, it is necessary to train the network using more images. However, it is difficult to acquire cell images which contain a various cytological features with the use of many manual operations with a microscope. Therefore, in this study, we aim to improve the classification accuracy of a DCNN with the use of actual and synthesized cytological images with a generative adversarial network (GAN). Based on the proposed method, patch images were obtained from a microscopy image. Accordingly, these generated many additional similar images using a GAN. In this study, we introduce progressive growing of GANs (PGGAN), which enables the generation of high-resolution images. The use of these images allowed us to pretrain a DCNN. The DCNN was then fine-tuned using actual patch images. To confirm the effectiveness of the proposed method, we first evaluated the quality of the images which were generated by PGGAN and by a conventional deep convolutional GAN. We then evaluated the classification performance of benign and malignant cells, and confirmed that the generated images had characteristics similar to those of the actual images. Accordingly, we determined that the overall classification accuracy of lung cells was 85.3% which was improved by approximately 4.3% compared to a previously conducted study without pretraining using GAN-generated images. Based on these results, we confirmed that our proposed method will be effective for the classification of cytological images in cases at which only limited data are acquired.

Decision Support System for Lung Cancer Using PET/CT and Microscopic Images.

Lung cancer is the most common cancer among men and the third most common among women in the world. Many diagnostic techniques have been introduced to diagnose lung cancer. Positron emission tomography (PET)/computed tomography (CT) examination is an image diagnostic method that performs automatic detection and distinction of lung lesions. In addition, pathological examination by biopsy is performed for lesions that are suspected of being malignant, and appropriate treatment methods are applied according to the diagnosis results. Currently, lung cancer diagnosis is performed through coordination between respiratory, radiation, and pathological diagnosis experts, but there are some tasks, such as image diagnosis, that require a large amount of time and effort to complete. Therefore, we developed a decision support system using PET/CT and microscopic images at the time of image diagnosis, which leads to appropriate treatment. In this chapter, we introduce the proposed system using deep learning and radiomic techniques.

Simplifying the Chemical Structure of Cationic Lipids for siRNA-Lipid Nanoparticles.

We report a potent cationic lipid, SST-02 ((3-hydroxylpropyl)dilinoleylamine), which possesses a simple chemical structure and is synthesized just in one step. Cationic lipids are key components of siRNA-lipid nanoparticles (LNP), which may serve as potential therapeutic agents for various diseases. For a decade, chemists have given enhanced potency and new functions to cationic lipids along with structural complexity. In this study, we conducted a medicinal chemistry campaign pursuing chemical simplicity and found that even dilinoleylmethylamine (SST-01) and methylpalmitoleylamine could be used for the in vitro and in vivo siRNA delivery. Further optimization revealed that a hydroxyl group boosted potency, and SST-02 showed an ID50 of 0.02 mg/kg in the factor VII (FVII) model. Rats administered with 3 mg/kg of SST-02 LNP did not show changes in body weight, blood chemistry, or hematological parameters, while the AST level decreased at a dose of 5 mg/kg. The use of SST-02 avoids a lengthy synthetic route and may thus decrease the future cost of nucleic acid therapeutics.

Structure-activity relationship of novel (benzoylaminophenoxy)phenol derivatives as anti-prostate cancer agents.

The androgen receptor (AR) is a ligand-inducible transcription factor belonging to the nuclear receptor superfamily, and is a target molecule for development of drugs to treat prostate cancer. However, AR antagonists in clinical use, such as flutamide (3a) and bicalutamide (4), encounter resistance after several years of hormone therapy, predominantly due to mutations of AR. Thus, although some new-generation AR antagonists have been developed, novel types of AR antagonists are still required to treat drug-resistant prostate cancer. We previously reported a novel (benzoylaminophenoxy)phenol derivative 10a, which is structurally distinct from conventional AR antagonists. Here, we systematically examined the structure-activity relationship of (benzoylaminophenoxy)phenol derivatives on the inhibitory activity on the prostate cancer cell proliferations. We found that the 4-[4-(benzoylamino)phenoxy]phenol backbone is important for anti-prostate cancer activity. Introduction of a small substituent at the 2 position of the central benzene ring (B ring) increases the activity. Among the synthesized compounds, 19a and 19b exhibited the most potent inhibitory activity toward dihydrotestosterone-induced proliferation of several androgen-dependent cell lines, SC-3 (wild-type AR), LNCaP (T877A AR), and 22Rv1 (H874Y AR), but interestingly also inhibited proliferation of AR-independent PC-3 cells. These compounds, which have a different pharmacophore from conventional AR antagonists, are promising drug candidates for the treatment of prostate cancer.

Biochemical validation of EHMT1 missense mutations in Kleefstra syndrome.

Kleefstra syndrome (KS) (9q34 deletion syndrome) is a rare autosomal dominant disorder characterized by intellectual disability, frequently coupled with a spectrum of complex physical and clinical manifestations. As the euchromatic histone methyltransferase-1 gene (EHMT1, GLP, or KMT1D) within the 9q34 region is deleted or mutated in most of the individuals with KS, its absence or defect in one allele is speculated to cause the major symptoms of the syndrome. Most of the EHMT1 mutations are frameshift or nonsense mutations, but two individuals with KS were reported to possess EHMT1 missense mutations. These two mutations have been predicted to cause a defective enzymatic function, but precise biochemical validation was not conducted. Therefore, we validated these two mutations by performing in vitro histone methyltransferase (HMT) activity assay and found that C1073Y and R1197W mutations severely affected the HMT activity. Additionally, the same amino-acid substitutions in mouse GLP induced impairment of in vivo GLP function. Furthermore, these two EHMT1 mutants showed defective heterocomplex formation with G9a (partner HMT) which is essential for their in vivo HMT function. Conclusively, our biochemical characterization clearly demonstrates that the previously reported two missense mutations of EHMT1 deteriorate HMT activity and GLP function, which presumably cause KS.

Development of nonsteroidal glucocorticoid receptor modulators based on N-benzyl-N-(4-phenoxyphenyl)benzenesulfonamide scaffold.

N-Benzyl-N-(4-phenoxyphenyl)benzenesulfonamide derivatives were developed as a novel class of nonsteroidal glucocorticoid receptor (GR) modulators, which are promising drug candidates for treating immune-related disorders. Focusing on the similarity of the GR and progesterone receptor (PR) ligand-binding domain (LBD) structures, we adopted our recently developed PR antagonist 10 as a lead compound and synthesized a series of derivatives. We found that the N-(4-phenoxyphenyl)benzenesulfonamide skeleton serves as a versatile scaffold for GR antagonists. Among them, 4-cyano derivative 14m was the most potent, with an IC50 value of 1.43µM for GR. This compound showed good selectivity for GR; it retained relatively weak antagonistic activity toward PR (IC50 for PR: 8.00µM; 250-fold less potent than 10), but showed no activity toward AR, ERα or ERß. Interestingly, the 4-amino derivative 15a exhibited transrepression activity toward NF-κB in addition to GR-antagonistic activity, whereas 14m did not. The structure-activity relationship for transrepression was different from that for GR-antagonistic activity. Computational docking simulations suggested that 15a might bind to the ligand-binding pocket of GR in a different manner from 14m. These findings open up new possibilities for developing novel nonsteroidal GR modulators with distinctive activity profiles.