A phase 1 study of dimdazenil to evaluate the pharmacokinetics, food effect and safety in Chinese healthy subjects

Background and objective: As a partial positive allosteric modulator of the gamma-aminobutyric acid A (GABAA) receptor, dimdazenil was used for the treatment of insomnia with the potential to alleviate associated side effects compared to full agonists. The objective of this trial is to assess the safety, tolerability, food effect and pharmacokinetics following single and multiple doses of dimdazenil in Chinese healthy subjects.Methods: In this phase 1 trial, 36 healthy subjects aged ≥18 years were assigned to receive a single dose of 1.5, 2.5, or 5 mg dimdazenil, with each dose cohort consisting of 12 subjects, and 14 subjects were assigned to receive a multiple 2.5 mg daily dose of dimdazenil for 5 days. Safety, tolerability, and pharmacokinetic characteristics were evaluated.Results: Of the 50 subjects enrolled and 49 completed the trial, the incidences of treatment-emergent adverse events (AEs) in the single-dose groups of 1.5, 2.5, and 5 mg were 16.7%, 58.3% and 66.7% respectively, while 61.5% in the multiple-dose group. There were no serious AEs, deaths, AEs leading to discontinuation or AEs of requiring clinical intervention in any treatment groups. The most treatment-emergent AEs were dizziness (n = 4, 8.2%), hyperuricemia (n = 2, 6.1%), upper respiratory tract infection (n = 2, 6.1%), diastolic blood pressure decreased (n = 2, 6.1%), blood TG increased (n = 2, 6.1%) and RBC urine positive (n = 2, 6.1%). All AEs were mild-to-moderate and transient, and no severe AEs were documented in any study phase. The PK profile of dimdazenil and its active metabolite Ro46-1927 was linear across 1.5–5 mg oral doses in humans. The median Tmax for dimdazenil was in the range of 0.5–1.5 h, and the apparent terminal t1/2z ranged from 3.50 to 4.32 h. Taking Dimdazenil with food may delay Tmax and decrease Cmax, without affecting the total exposure (AUC). No relevant accumulations of dimdazenil and Ro 46–1927 were observed in multiple-dose group.Conclusion: Dimdazenil was generally well tolerated in healthy Chinese subjects after single and 5 days-multiple dosing. The pharmacokinetic properties of dimdazenil are compatible with a drug for the treatment of insomnia.Clinical Trial Registration: chinadrugtrials.org.cn, identifier CTR2020197

Comparative observations on the squamous-columnar junction of Von Ebner’s glandular duct at the bottom of vallate papillae in dogs, rats, mice and human

Background: This paper aims to comparatively observe similarities of squamous-columnar junction (SCJ) at the opening of Von Ebner's glandular ducts at the vallate papillae in dogs, mice, rats and humans, lay a foundation for the selection of the model in future study of the carcinogenesis in SCJ at vallate papillae. Materials and methods: The localization of the vallate papillae in three laboratory animals and humans was comparatively observed. The differences of SCJ at vallate papillae were comparatively observed by Alcian blue, immunohistochemistry and HE staining. Results: Anatomically, the canine vallate papillae were most similar to those of humans in location, whereas mice and rats only had a single, Ω-shaped, vallate papilla lying directly anterior to the posterior border of the intermolar eminence. In histology, the SCJ of dogs lacked a transition zone similar to that of the human SCJ, and there was glandular epithelium secreting acidic mucus at the opening of the rats’ Von Ebner's glandular ducts. All of this suggested that the histological structure of SCJ in rats and dogs is more distinct from that of humans, whereas the histological structure of SCJ at vallate papilla in mice was more similar. Conclusions: The structure of SCJ at vallate papilla in mice is most similar to that of humans, so we conclude that mouse is the most suitable model for studying tumorigenesis in SCJ at vallate papillae in these three common laboratory animals

A miR-155–Peli1–c-Rel pathway controls the generation and function of T follicular helper cells

MicroRNA (miRNA) deficiency impairs the generation of T follicular helper (Tfh) cells, but the contribution of individual miRNAs to this phenotype remains poorly understood. In this study, we performed deep sequencing analysis of miRNAs expressed in Tfh cells and identified a five-miRNA signature. Analyses of mutant mice deficient of these miRNAs revealed that miR-22 and miR-183/96/182 are dispensable, but miR-155 is essential for the generation and function of Tfh cells. miR-155 deficiency led to decreased proliferation specifically at the late stage of Tfh cell differentiation and reduced CD40 ligand (CD40L) expression on antigen-specific CD4+T cells. Mechanistically, miR-155 repressed the expression of Peli1, a ubiquitin ligase that promotes the degradation of the NF-κB family transcription factor c-Rel, which controls cellular proliferation and CD40L expression. Therefore, our study identifies a novel miR-155-Peli1-c-Rel pathway that specifically regulates Tfh cell generation and functionC. Xiao is a Pew Scholar in Biomedical Sciences. This study is supported by the PEW Charitable Trusts, Cancer Research Institute, Lupus Research Institute, National Institutes of Health (grants R01AI087634, R01AI089854, R56AI110403, and R56AI121155 to C. Xiao and grants R01AI103646 and R01AI108651 to L.-F. Lu), National Natural Science Foundation of China (grant 31570882 to W.-H. Liu, grant 31570883 to N. Xiao, and grant 31570911 to G. Fu), 1000 Young Talents Program of China (grant K08008 to N. Xiao), the Fundamental Research Funds for the Central Universities of the People’s Republic of China (grant 20720150065 to N. Xiao and G. Fu), the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, Information and Communications Technology, and Future Planning (grant NRF-2015R1C1A1A01052387 to S.G. Kang), and a 2016 research grant from Kangwon National University (to S.G. Kang

Stimuli-Responsive Drug Delivery Systems for the Diagnosis and Therapy of Lung Cancer

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer death worldwide. Numerous drugs have been developed to treat lung cancer patients in recent years, whereas most of these drugs have undesirable adverse effects due to nonspecific distribution in the body. To address this problem, stimuli-responsive drug delivery systems are imparted with unique characteristics and specifically deliver loaded drugs at lung cancer tissues on the basis of internal tumor microenvironment or external stimuli. This review summarized recent studies focusing on the smart carriers that could respond to light, ultrasound, pH, or enzyme, and provided a promising strategy for lung cancer therapy

Table8_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.XLSX

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p

DataSheet1_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.PDF

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p

Table3_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.XLSX

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p

Table5_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.XLSX

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p

Table6_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.XLSX

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p

Table1_Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines.XLSX

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.</p