Artificial intelligence for ultrasound microflow imaging in breast cancer diagnosis.

PURPOSE: To develop and evaluate artificial intelligence (AI) algorithms for ultrasound (US) microflow imaging (MFI) in breast cancer diagnosis. MATERIALS AND METHODS: We retrospectively collected a dataset consisting of 516 breast lesions (364 benign and 152 malignant) in 471 women who underwent B-mode US and MFI. The internal dataset was split into training (n = 410) and test datasets (n = 106) for developing AI algorithms from deep convolutional neural networks from MFI. AI algorithms were trained to provide malignancy risk (0-100%). The developed AI algorithms were further validated with an independent external dataset of 264 lesions (229 benign and 35 malignant). The diagnostic performance of B-mode US, AI algorithms, or their combinations was evaluated by calculating the area under the receiver operating characteristic curve (AUROC). RESULTS: The AUROC of the developed three AI algorithms (0.955-0.966) was higher than that of B-mode US (0.842, P < 0.0001). The AUROC of the AI algorithms on the external validation dataset (0.892-0.920) was similar to that of the test dataset. Among the AI algorithms, no significant difference was found in all performance metrics combined with or without B-mode US. Combined B-mode US and AI algorithms had a higher AUROC (0.963-0.972) than that of B-mode US (P < 0.0001). Combining B-mode US and AI algorithms significantly decreased the false-positive rate of BI-RADS category 4A lesions from 87% to 13% (P < 0.0001). CONCLUSION: AI-based MFI diagnosed breast cancers with better performance than B-mode US, eliminating 74% of false-positive diagnoses in BI-RADS category 4A lesions.

Effectiveness of COVID-19 vaccines against severe outcomes in cancer patients: Real-world evidence from self-controlled risk interval and retrospective cohort studies.

BACKGROUND: The effectiveness of COVID-19 vaccines is generally reduced in cancer patients compared to the general population. However, there are only a few studies that compare the relative risk of breakthrough infections and severe COVID-19 outcomes in fully vaccinated cancer patients versus their unvaccinated counterparts. METHODS: To assess the effectiveness of COVID-19 vaccines in cancer patients, we employed (1) a self-controlled risk interval (SCRI) design, and (2) a retrospective matched cohort design. A SCRI design was used to compare the risk of breakthrough infection in vaccinated cancer patients during the period immediately following vaccination ("control window") and the period in which immunity is achieved ("exposure windows"). The retrospective matched cohort design was used to compare the risk of severe COVID-19 outcomes between vaccinated and unvaccinated cancer patients. For both studies, data were extracted from the Korea Disease Control and Prevention Agency-COVID-19-National Health Insurance Service cohort, including demographics, medical history, and vaccination records of all individuals confirmed with COVID-19. We used conditional Poisson regression to calculate the incidence rate ratio (IRR) for breakthrough infection and Cox regression to estimate the hazard ratio (HR) for severe outcomes. RESULTS: Of 14,448 cancer patients diagnosed with COVID-19 between October 2020 and December 2021, a total of 217 and 3996 cancer patients were included in the SCRI and cohort study respectively. While the risk of breakthrough infections, measured by the incidence rate in the control and exposure windows, did not show statistically significant difference in vaccinated cancer patients (IRR=0.88, 95% CI: 0.64-1.22), the risk of severe COVID-19 outcomes was significantly lower in vaccinated cancer patients compared to those unvaccinated (HR=0.27, 95% CI: 0.22-0.34). CONCLUSION: COVID-19 vaccines significantly reduce the risk of severe outcomes in cancer patients, though their efficacy against breakthrough infections is less evident.

Pathogenic GATA2 genetic variants utilize an obligate enhancer mechanism to distort a multilineage differentiation program.

Mutations in genes encoding transcription factors inactivate or generate ectopic activities to instigate pathogenesis. By disrupting hematopoietic stem/progenitor cells, GATA2 germline variants create a bone marrow failure and leukemia predisposition, GATA2 deficiency syndrome, yet mechanisms underlying the complex phenotypic constellation are unresolved. We used a GATA2-deficient progenitor rescue system to analyze how genetic variation influences GATA2 functions. Pathogenic variants impaired, without abrogating, GATA2-dependent transcriptional regulation. Variants promoted eosinophil and repressed monocytic differentiation without regulating mast cell and erythroid differentiation. While GATA2 and T354M required the DNA-binding C-terminal zinc finger, T354M disproportionately required the N-terminal finger and N terminus. GATA2 and T354M activated a CCAAT/Enhancer Binding Protein-ε (C/EBPε) enhancer, creating a feedforward loop operating with the T-cell Acute Lymphocyte Leukemia-1 (TAL1) transcription factor. Elevating C/EBPε partially normalized hematopoietic defects of GATA2-deficient progenitors. Thus, pathogenic germline variation discriminatively spares or compromises transcription factor attributes, and retaining an obligate enhancer mechanism distorts a multilineage differentiation program.

A long-term storable gel-laden chip composite built in a multi-well plate enablingin situcell encapsulation for high-throughput liver model.

Hydrogels are widely used as scaffold materials for constructingin vitrothree-dimensional microphysiological systems. However, their high sensitivity to various external cues hinders the development of hydrogel-laden, microscale, and high-throughput chips. Here, we have developed a long-term storable gel-laden chip composite built in a multi-well plate, which enablesin situcell encapsulation and facilitates high-throughput analysis. Through optimized chemical crosslinking and freeze-drying method (C/FD), we have achieved a high-quality of gel-laden chip composite with excellent transparency, uniform porosity, and appropriate swelling and mechanical characteristics. Besides collagen, decellularized extracellular matrix with tissue-specific biochemical compound has been applied as chip composite. As a ready-to-use platform,in situcell encapsulation within the gel has been achieved through capillary force generated during gel reswelling. The liver-mimetic chip composite, comprising HepG2 cells or primary hepatocytes, has demonstrated favorable hepatic functionality and high sensitivity in drug testing. The developed fabrication process with improved stability of gels and storability allows chip composites to be stored at a wide range of temperatures for up to 28 d without any deformation, demonstrating off-the-shelf products. Consequently, this provides an exceptionally simple and long-term storable platform that can be utilized for an efficient tissue-specific modeling and various biomedical applications.

Optimization of Ultrasonic-Assisted Extraction of α-Glucosidase Inhibitors from Dryopteris crassirhizoma Using Artificial Neural Network and Response Surface Methodology.

Dryopteris crassirhizoma Nakai is a plant with significant medicinal properties, such as anticancer, antioxidant, and anti-inflammatory activities, making it an attractive research target. Our study describes the isolation of major metabolites from D. crassirhizoma, and their inhibitory activities on α-glucosidase were evaluated for the first time. The results revealed that nortrisflavaspidic acid ABB (2) is the most potent α-glucosidase inhibitor, with an IC50 of 34.0 ± 0.14 µM. In addition, artificial neural network (ANN) and response surface methodology (RSM) were used in this study to optimize the extraction conditions and evaluate the independent and interactive effects of ultrasonic-assisted extraction parameters. The optimal extraction conditions are extraction time of 103.03 min, sonication power of 342.69 W, and solvent-to-material ratio of 94.00 mL/g. The agreement between the predicted models of ANN and RSM and the experimental values was notably high, with a percentage of 97.51% and 97.15%, respectively, indicating that both models have the potential to be utilized for optimizing the industrial extraction process of active metabolites from D. crassirhizoma. Our results could provide relevant information for producing high-quality extracts from D. crassirhizoma for functional foods, nutraceuticals, and pharmaceutical industries.

Venadaparib Is a Novel and Selective PARP Inhibitor with Improved Physicochemical Properties, Efficacy, and Safety.

PARP inhibitors have been approved by the FDA for use in the treatment of patients with ovarian, breast, pancreatic, and prostate cancers. PARP inhibitors show diverse suppressive effects on PARP family members and PARP-DNA trapping potency. These properties are associated with distinct safety/efficacy profiles. Here, we report the nonclinical characteristics of venadaparib (also known as IDX-1197 or NOV140101), a novel potent PARP inhibitor. The physiochemical properties of venadaparib were analyzed. Furthermore, the efficacy of venadaparib against PARP enzymes, PAR formation, and PARP trapping activities, and growth inhibition of cell lines with BRCA mutations were evaluated. Ex vivo and in vivo models were also established to study pharmacokinetics/pharmacodynamics, efficacy, and toxicity. Venadaparib specifically inhibits PARP-1 and -2 enzymes. Oral administration of venadaparib HCl at doses above 12.5 mg/kg significantly reduced tumor growth in the OV_065 patient-derived xenograft model. Intratumoral PARP inhibition remained at over 90% until 24 hours after dosing. Venadaparib had wider safety margins than olaparib. Notably, venadaparib showed favorable physicochemical properties and superior anticancer effects in homologous recombination-deficient in vitro and in vivo models with improved safety profiles. Our results suggest the possibility of venadaparib as a next-generation PARP inhibitor. On the basis of these findings, phase Ib/IIa studies on the efficacy and safety of venadaparib have been initiated.

Shear-wave elastography-based nomograms predicting 21-gene recurrence score for adjuvant chemotherapy decisions in patients with breast cancer.

PURPOSE: To develop and validate nomograms based on shear-wave elastography (SWE) combined with clinicopathologic features for predicting Oncotype DX recurrence score (RS) for use with adjuvant systemic therapy guidelines. METHODS: In a retrospective study, patients with breast cancer who underwent definitive surgery of the breast between August 2011 and December 2019 were eligible for this study. Those with surgery between August 2011 and March 2019 were assigned to a development set and the rest were assigned to an independent validation set. Clinicopathologic features and SWE elasticity indices were assessed with logistic regression to develop nomograms for predicting RS ≥ 16 and ≥ 26. Analysis of the area under the receiver operating characteristic curve (AUROC) was used to assess the performance of the nomograms. RESULTS: Of a total 381 women (mean age, 51 ± 9 years), 286 (mean age, 51 ± 9 years) were in the development set and 95 (mean age, 51 ± 9 years) in the validation set. All SWE elasticity indices were independently associated with each RS cutoff (odds ratio, 1.006-1.039 for RS ≥ 16; odds ratio, 1.008-1.076 for RS ≥ 26). Nomograms based on SWE combined with clinicopathologic features were developed and validated for RS ≥ 16 (mean elasticity [AUROC, 0.74; 95% CI: 0.68, 0.80] and maximum elasticity [AUROC, 0.74; 95% CI: 0.69, 0.80]) and for RS ≥ 26 (mean elasticity [AUROC, 0.81; 95% CI: 0.73, 0.89], maximum elasticity [AUROC, 0.82; 95% CI: 0.74, 0.89], and elasticity ratio [AUROC, 0.86; 95% CI: 0.80, 0.93]). CONCLUSION: Nomograms based on SWE can predict Oncotype DX RS for use in adjuvant systemic therapy decisions.

Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis.

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate leads to poor survival outcomes. The effect of anticancer drug treatment varies significantly depending on individual patients and the extent of drug resistance. In this study, we developed a validation system based on an organ-on-a-chip integrated with artificial intelligence technologies to predict resistance to anticancer drugs in bladder cancer. As a proof-of-concept, we utilized the gemcitabine-resistant bladder cancer cell line T24 with four distinct levels of drug resistance (parental, early, intermediate, and late). These cells were co-cultured with endothelial cells in a 3D microfluidic chip. A dataset comprising 2,674 cell images from the chips was analyzed using a convolutional neural network (CNN) to distinguish the extent of drug resistance among the four cell groups. The CNN achieved 95.2% accuracy upon employing data augmentation and a step decay learning rate with an initial value of 0.001. The average diagnostic sensitivity and specificity were 90.5% and 96.8%, respectively, and all area under the curve (AUC) values were over 0.988. Our proposed method demonstrated excellent performance in accurately identifying the extent of drug resistance, which can assist in the prediction of drug responses and in determining the appropriate treatment for bladder cancer patients.

Non-cancer health risks in firefighters: a systematic review.

osFirefighters are occupationally exposed to hazardous factors that may increase their risk of disease. However, non-cancer disease risk in firefighters has not been systematically examined. This systematic review aimed to identify non-cancer disease risk in firefighters and determine whether the risk differs according to job characteristics. We searched the Cochrane Library, Embase, PubMed, and KoreaMed databases using relevant keywords from their inception to April 30, 2021. The Risk of Bias Assessment Tool for Non-randomized Studies version 2.0 was used to assess the quality of evidence. Due to study heterogeneity, a narrative synthesis was presented. The systematic literature search yielded 2,491 studies, of which 66 met the selection and quality criteria. We confirmed that the healthy worker effect is strong in firefighters as compared to the general population. We also identified a significant increase in the incidence of lumbar disc herniation, lower back pain, angina pectoris, acute myocardial infarction, and post-traumatic stress disorder (PTSD) in firefighters compared to other occupational groups. Contradictory results for the risk of PTSD and anxiety disorders related to rank were reported. Sufficient evidence for increased risk of lumbar disc herniation, lower back pain, angina pectoris, acute myocardial infarction, and PTSD was available. The risk of non-cancer diseases varied depending on job type, years of service, and rank. However, caution should be exercised when interpreting the results because the classification criteria for firefighters' jobs and ranks differ by country.

Stepwise molecular mechanisms responsible for chemoresistance in bladder cancer cells.

Chemotherapy resistance is an obstacle to cancer therapy and is considered a major cause of recurrence. Thus, understanding the mechanisms of chemoresistance is critical to improving the prognosis of patients. Here, we have established a stepwise gemcitabine-resistant T24 bladder cancer cell line to understand the molecular mechanisms of chemoresistance within cancer cells. The characteristics of the stepwise chemoresistance cell line were divided into 4 phases (parental, early, intermediate, and late phases). These four phase cells showed increasingly aggressive phenotypes in vitro and in vivo experiments with increasing phases and revealed the molecular properties of the biological process from parent cells to phased gemcitabine-resistant cell line (GRC). Taken together, through the analysis of gene expression profile data, we have characterized gene set of each phase indicating the response to anticancer drug treatment. Specifically, we identified a multigene signature (23 genes including GATA3, APOBEC3G, NT5E, MYC, STC1, FOXD1, SMAD9) and developed a chemoresistance score consisting of that could predict eventual responsiveness to gemcitabine treatment. Our data will contribute to predicting chemoresistance and improving the prognosis of bladder cancer patients.

Antibody-mediated delivery of a viral MHC-I epitope into the cytosol of target tumor cells repurposes virus-specific CD8+ T cells for cancer immunotherapy.

BACKGROUND: Redirecting pre-existing virus-specific cytotoxic CD8+ T lymphocytes (CTLs) to tumors by simulating a viral infection of the tumor cells has great potential for cancer immunotherapy. However, this strategy is limited by lack of amenable method for viral antigen delivery into the cytosol of target tumors. Here, we addressed the limit by developing a CD8+ T cell epitope-delivering antibody, termed a TEDbody, which was engineered to deliver a viral MHC-I epitope peptide into the cytosol of target tumor cells by fusion with a tumor-specific cytosol-penetrating antibody. METHODS: To direct human cytomegalovirus (CMV)-specific CTLs against tumors, we designed a series of TEDbodies carrying various CMV pp65 antigen-derived peptides. CMV-specific CTLs from blood of CMV-seropositive healthy donors were expanded for use in in vitro and in vivo experiments. Comprehensive cellular assays were performed to determine the presentation mechanism of TEDbody-mediated CMV peptide-MHC-I complex (CMV-pMHCI) on the surface of target tumor cells and the recognition and lysis by CMV-specific CTLs. In vivo CMV-pMHCI presentation and antitumor efficacy of TEDbody were evaluated in immunodeficient mice bearing human tumors. RESULTS: TEDbody delivered the fused epitope peptides into target tumor cells to be intracellularly processed and surface displayed in the form of CMV-pMHCI, leading to disguise target tumor cells as virally infected cells for recognition and lysis by CMV-specific CTLs. When systemically injected into tumor-bearing immunodeficient mice, TEDbody efficiently marked tumor cells with CMV-pMHCI to augment the proliferation and cytotoxic property of tumor-infiltrated CMV-specific CTLs, resulting in significant inhibition of the in vivo tumor growth by redirecting adoptively transferred CMV-specific CTLs. Further, combination of TEDbody with anti-OX40 agonistic antibody substantially enhanced the in vivo antitumor activity. CONCLUSION: Our study offers an effective technology for MHC-I antigen cytosolic delivery. TEDbody may thus have utility as a therapeutic cancer vaccine to redirect pre-existing anti-viral CTLs arising from previously exposed viral infections to attack tumors.

"Thank You for Listening": An Exploratory Study Regarding the Lived Experience and Perception of Medical Errors Among Those Who Receive Care.

The issue of medical errors, or adverse events caused within a health care context or by a health care provider, is largely under-researched. While the experience and perspective of health care professionals regarding medical errors have been explored, little attention is paid to the health care consumers regarding their perceptions and experiences. Therefore, there is a need to better understand the public's views on medical errors to enhance patient safety and quality care. The current study sought to examine Australian public perceptions and experiences, especially concerning what errors had occurred, the perceived sources of the errors, and if the errors had been reported. This paper reports the qualitative findings of an online survey for Australian residents who have accessed or received medical services at any time in Australia. Responses from 304 surveys were analyzed and discussed, including demographic information and key themes about medical errors, which were categorized into engagement and patients' voices being heard, the quality of care being provided, and the system's accountability. Based on the findings, the study highlights the importance of effective health professional-patient communication, enhanced capacity to deliver high quality care, and improved mechanism for error reporting and resolution where patients feel safe and confident about positive changes being made.

Added value of abbreviated breast magnetic resonance imaging for assessing suspicious microcalcification on screening mammography-a prospective study.

OBJECTIVES: To investigate the added diagnostic value of abbreviated breast magnetic resonance imaging (MRI) for suspicious microcalcifications on screening mammography. METHODS: This prospective study included 80 patients with suspicious calcifications on screening mammography who underwent abbreviated MRI before undergoing breast biopsy between August 2017 and September 2020. The abbreviated protocol included one pre-contrast and the first post-contrast T1-weighted series. MRI examinations were interpreted as either positive or negative based on the visibility of any significant enhancement. The positive predictive value (PPV) was compared before and after the MRI. RESULTS: Of the 80 suspicious microcalcifications, 33.8% (27/80) were malignant and 66.2% (53/80) were false positives. Abbreviated MRI revealed 33 positive enhancement lesions, and 25 and two lesions showed true-positive and false-negative findings, respectively. Abbreviated MRI increased PPV from 33.8 (27 of 80 cases; 95% CI: 26.2%, 40.8%) to 75.8% (25 of 33 cases; 95% CI: 62.1%, 85.7%). A total of 85% (45 of 53) false-positive diagnoses were reduced after abbreviated MRI assessment. CONCLUSIONS: Abbreviated MRI added significant diagnostic value in patients with suspicious microcalcifications on screening mammography, as demonstrated by a significant increase in PPV with a potential reduction in unnecessary biopsy. KEY POINTS: • Abbreviated breast magnetic resonance imaging increased the positive predictive value of suspicious microcalcifications on screening mammography from 33.8 (27/80 cases) to 75.8% (25/33 cases) (p < .01). • Abbreviated magnetic resonance imaging helped avoid unnecessary benign biopsies in 85% (45/53 cases) of lesions without missing invasive cancer.

A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis.

This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients exhibiting suspicious microcalcification in screening mammograms between July 2007 and December 2019. Five pre-trained DCNN models and an ensemble model were used to classify the microcalcifications as either malignant or benign. Approximately one million images from the ImageNet database had been used to train the five DCNN models. Herein, 1121 mammographic images were used for individual model fine-tuning, 198 for validation, and 260 for testing. Gradient-weighted class activation mapping (Grad-CAM) was used to confirm the validity of the DCNN models in highlighting the microcalcification regions most critical for determining the final class. The ensemble model yielded the best AUC (0.856). The DenseNet-201 model achieved the best sensitivity (82.47%) and negative predictive value (NPV; 86.92%). The ResNet-101 model yielded the best accuracy (81.54%), specificity (91.41%), and positive predictive value (PPV; 81.82%). The high PPV and specificity achieved by the ResNet-101 model, in particular, demonstrated the model effectiveness in microcalcification diagnosis, which, in turn, may considerably help reduce unnecessary biopsies.

Anti-osteoclastogenic Effects of Indole Alkaloids Isolated from Barley (Hordeum vulgare Var. Hexastichon) Grass.

As part of our continuous program to identify new potential candidates for controlling osteolytic bone diseases from natural products, the alkaloid fraction of barley (Hordeum vulgare var. hexastichon) grass (HVA) significantly inhibited RANKL-induced osteoclast formation and protected mice from LPS-induced bone loss. A phytochemical investigation of HVA afforded nine indole alkaloids, including one new compound [hordeumin A (1)] and eight known analogues (2-9). Of them, four (1, 2, 4, and 5) were anti-osteoclastogenic compounds. Of these four, compound 5 significantly suppressed RANKL-induced osteoclast formation, actin ring formation, and bone resorption in a concentration-dependent manner. It also suppressed the RANKL-induced NF-κB and MAPK signaling pathways and the activation of c-Fos and NFATc1. Compound 5 also reduced the expression levels of osteoclast-specific marker genes, including TRAP, CtsK, DC-STAMP, OSCAR, and MMP9. Our findings suggest that HVA and its alkaloid constituents could be valuable candidates for the prevention and treatment of osteolytic bone diseases.

Inhibition of tumor progression and M2 microglial polarization by extracellular vesicle-mediated microRNA-124 in a 3D microfluidic glioblastoma microenvironment.

Background: Glioblastoma (GBM) is one of the most aggressive types of brain cancer. GBM progression is closely associated with microglia activation; therefore, understanding the regulation of the crosstalk between human GBM and microglia may help develop effective therapeutic strategies. Elucidation of efficient delivery of microRNA (miRNA) via extracellular vesicles (EVs) and their intracellular communications is required for therapeutic applications in GBM treatment. Methods: We used human GBM cells (U373MG) and human microglia. MiRNA-124 was loaded into HEK293T-derived EVs (miR-124 EVs). Various anti-tumor effects (proliferation, metastasis, chemosensitivity, M1/M2 microglial polarization, and cytokine profile) were investigated in U373MG and microglia. Anti-tumor effect of miR-124 EVs was also investigated in five different patient-derived GBM cell lines (SNU-201, SNU-466, SNU-489, SNU-626, and SNU-1105). A three-dimensional (3D) microfluidic device was used to investigate the interactive microenvironment of the tumor and microglia. Results: MiR-124 EVs showed highly efficient anti-tumor effects both in GBM cells and microglia. The mRNA expression levels of tumor progression and M2 microglial polarization markers were decreased in response to miR-124 EVs. The events were closely related to signal transducer and activator of transcription (STAT) 3 signaling in both GBM and microglia. In 3D microfluidic experiments, both U373MG and microglia migrated to a lesser extent and showed less-elongated morphology in the presence of miR-124 EVs compared to the control. Analyses of changes in cytokine levels in the microfluidic GBM-microglia environment showed that the treatment with miR-124 EVs led to tumor suppression and anti-cancer immunity, thereby recruiting natural killer (NK) cells into the tumor. Conclusions: In this study, we demonstrated that EV-mediated miR-124 delivery exerted synergistic anti-tumor effects by suppressing the growth of human GBM cells and inhibiting M2 microglial polarization. These findings provide new insights toward a better understanding of the GBM microenvironment and provide substantial evidence for the development of potential therapeutic strategies using miRNA-loaded EVs.

Metabolism of Diterpenoids Derived from the Bark of Cinnamomum cassia in Human Liver Microsomes.

Cinnamomum cassia L. is used as a spice and flavoring agent as well as a traditional medicine worldwide. Diterpenoids, a class of compounds present in C. cassia, have various pharmacological effects, such as anti-inflammatory, antitumor, and antibacterial activities; however, there are insufficient studies on the metabolism of diterpenoids. In this study, the metabolism of seven diterpenoids, namely, anhydrocinnzeylanol, anhydrocinnzeylanine (AHC), cinncassiol A, cinncassiol B, cinnzeylanol, cinnzeylanone, and cinnzeylanine, obtained from the bark of C. cassia was studied in human liver microsomes (HLMs). All studied diterpenoids, except for AHC, exhibited strong metabolic stability; however, AHC was rapidly metabolized to 3% in HLMs in the presence of ß-NADPH. Using a high-resolution quadrupole-orbitrap mass spectrometer, 20 metabolites were identified as dehydrogenated metabolites (M1-M3), dehydrogenated and oxidated metabolites (M4-M10), mono-oxidated metabolites (M11-M13), or dioxidated metabolites (M14-M20). In addition, CYP isoforms involved in AHC metabolism were determined by profiling metabolites produced after incubation in 11 recombinant cDNA-expressed CYP isoforms. Thus, the diterpenoid compound AHC was identified in a metabolic pathway involving CYP3A4 in HLMs.

PTP1B inhibition studies of biological active phloroglucinols from the rhizomes of Dryopteris crassirhizoma: Kinetic properties and molecular docking simulation.

By various chromatographic methods, 30 phloroglucinols (1-30) were isolated from a methanol extract of Dryopteris crassirhizoma, including two new dimeric phloroglucinols (13 and 25). The structures of the isolates were confirmed by HR-MS, 1D, and 2D NMR as well as by comparison with the literature. The protein tyrosine phosphatase 1B (PTP1B) effects of the isolated compounds (1-30) were evaluated using sodium orthovanadate and ursolic acid as a positive control. Among them, trimeric phloroglucinols 26-28 significantly exhibited the PTP1B inhibitory effects with the IC50 values of 1.19 ± 0.13, 1.00 ± 0.04, 1.23 ± 0.05 µM, respectively. In addition, the kinetic analysis revealed compounds 26-28 acted as competitive inhibitors against PTP1B enzyme with Ki values of 0.63, 0.61, 1.57 µM, respectively. Molecular docking simulations were performed to demonstrate that these active compounds can bind with the catalytic sites of PTP1B with negative binding energies and the results are in accordance with that of the kinetic studies. In vitro and in silico results suggest that D. crassirhizoma rhizomes together with compounds 26-28 are potential candidates for treating type 2 diabetes.

Suppression of Osteoarthritis progression by post-natal Induction of Nkx3.2.

Osteoarthritis (OA) is an incurable joint disease affecting 240 million elderly population, and major unmet medical needs exist for better therapeutic options for OA. During skeletal development, Nkx3.2 has been shown to promote chondrocyte differentiation and survival, but to suppress cartilage hypertrophy and blood vessel invasion. Here we show that Nkx3.2 plays a key role in osteoarthritis (OA) pathogenesis. Marked reduction of Nkx3.2 expression was observed in three different murine OA models. Consistent with these findings, analyses of surgery-induced and age-driven OA models revealed that cartilage-specific post-natal induction of Nkx3.2 can suppress OA progression in mice. These results suggest that Nkx3.2 may serve as a promising target for OA drug development.