Inhibitory Effects of Baicalin on the Expression and Activity of CYP3A Induce the Pharmacokinetic Changes of Midazolam in Rats

Baicalin, a flavonoid compound isolated from Scutellaria baicalensis, has been shown to possess antiinflammatory, antiviral, antitumour, and immune regulatory properties. The present study evaluated the potential herb-drug interaction between baicalin and midazolam in rats. Coadministration of a single dose of baicalin (0.225, 0.45, and 0.90 g/kg, i.v.) with midazolam (10 mg/kg, i.v.) in rats resulted in a dose-dependent decrease in clearance (CL) from 25%  (P<0.05) to 34%  (P<0.001) with an increase in AUC0−∞ from 47%  (P<0.05) to 53%  (P<0.01). Pretreatment of baicalin (0.90 g/kg, i.v., once daily for 7 days) also reduced midazolam CL by 43%  (P<0.001), with an increase in AUC0−∞ by 87%  (P<0.01). Multiple doses of baicalin decreased the expression of hepatic CYP3A2 by approximately 58%  (P<0.01) and reduced midazolam 1′-hydroxylation by 23%  (P<0.001) and 4′-hydroxylation by 21%  (P<0.01) in the liver. In addition, baicalin competitively inhibited midazolam metabolism in rat liver microsomes in a concentration-dependent manner. Our data demonstrated that baicalin induced changes in the pharmacokinetics of midazolam in rats, which might be due to its inhibition of the hydroxylation activity and expression of CYP3A in the liver

Streaming Voice Conversion Via Intermediate Bottleneck Features And Non-streaming Teacher Guidance

Streaming voice conversion (VC) is the task of converting the voice of one person to another in real-time. Previous streaming VC methods use phonetic posteriorgrams (PPGs) extracted from automatic speech recognition (ASR) systems to represent speaker-independent information. However, PPGs lack the prosody and vocalization information of the source speaker, and streaming PPGs contain undesired leaked timbre of the source speaker. In this paper, we propose to use intermediate bottleneck features (IBFs) to replace PPGs. VC systems trained with IBFs retain more prosody and vocalization information of the source speaker. Furthermore, we propose a non-streaming teacher guidance (TG) framework that addresses the timbre leakage problem. Experiments show that our proposed IBFs and the TG framework achieve a state-of-the-art streaming VC naturalness of 3.85, a content consistency of 3.77, and a timbre similarity of 3.77 under a future receptive field of 160 ms which significantly outperform previous streaming VC systems.Comment: The paper has been submitted to ICASSP202

the spinal level in rats

Abstract: The present study was aimed to examine if protein kinase C (PKC) activation is necessarily involved in both the c-fos protein expression in the nocuously-activated c-fos protein-like immunoreactive (Fos-LI) neurons and the concomitant opioid receptor-mediated modulation in the dorsal horn circuitry of the spinal cord. Formalin was injected into a hindpaw of rats 5 min after the rats were pretreated with intrathecal (i.t.) administration of chelerythrine (Chel) , an inhibitor of PKC, naloxone (Nal), combined administration of these two (Chel + Nal), or vehicle (n=5 in each group),respectively. By using immunocytochemical techniques, the formalin-induced Fos-LI neurons in the lumbar dorsal horn were calculated 1 h after formalin injection. The results showed that: (1) i.t. Chel significantly reduced the number of Fos-LI neurons in the dorsal horn of the spinal cord on the side ipsilateral to the formalin injection, showing a decrease by 60.3% (P&lt;0.001) as compared to that observed in the i.t.vehicle group; (2) i.t. Nal significantly increased the number of Fos-LI neurons in the ipsilateral dorsal horn, with an increase of 46.0% (P&lt;0.01) as compared to that in the i.t.vehicle group , the highest percentage increase being found in the deeper laminae of the dorsal horn; and (3) i.t. Chel + Nal also exhibited a significant decrease in Fos-LI neurons in the ipsilateral dorsal horn as compared to i.t. Nal group, showing a reduction of 53.2%, a value similar to that in the i.t. Chel group. These results suggest that: (1) PKC plays a role in the c-fos protein expression only in nearly one half of the Fos-LI neurons in the dorsal horn; and (2) PKC is possibly not involved in the concomitant modulaion on the nociception mediated by µ-(and also partly δ-) opioid receptors in the spinal cord

An anoikis-related gene signature predicts prognosis and reveals immune infiltration in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.Materials and methodsWe downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The “pRRophetic” R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.ResultsA total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.ConclusionThe novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC

Nitrogen acquisition by plants and microorganisms in a temperate grassland

Nitrogen (N) limitation is common in most terrestrial ecosystems, often leading to strong competition between microorganisms and plants. The mechanisms of niche differentiation to reduce this competition remain unclear. Short-term 15N experiments with NH4+, NO3-, and glycine were conducted in July, August and September in a temperate grassland to evaluate the chemical, spatial and temporal niche differentiation by competition between plants and microorganisms for N. Microorganisms preferred NH4+ and NO3-, while plants preferred NO3-. Both plants and microorganisms acquired more N in August and September than in July. The soil depth had no significant effects on microbial uptake, but significantly affected plant N uptake. Plants acquired 67% of their N from the 0-5 cm soil layer and 33% from the 5-15 cm layer. The amount of N taken up by microorganisms was at least seven times than plants. Although microorganisms efficiently compete for N with plants, the competition is alleviated through chemical partitioning mainly in deeper soil layer. In the upper soil layer, neither chemical nor temporal niche separation is realized leading to strong competition between plants and microorganisms that modifies N dynamics in grasslands

Efficacy of using cancer stem cell markers in isolating and characterizing liver cancer stem cells

Recent evidence suggests that a subset of hepatocellular carcinomas (HCCs) are derived from liver cancer stem cells (LCSCs). In order to isolate and characterize LCSCs, reliable markers that are specific to these cells are required. We evaluated the efficacy of a range of cancer stem cell (CSC) markers in isolating and characterizing LCSCs. We show that the most widely used CSC markers are not specific to LCSCs. By western analysis, protein expression of the common markers showed no significant difference between HCC tumor tissues and adjacent non-cancerous liver. Further, isolation of LCSCs from common HCC cell lines using FACScan and microbeads showed no consistent marker expression pattern. We also show that LCSCs have unique subtypes. Immunohistochemistry of HCC tissues showed that different HCCs express unique combinations of LCSC markers. Quantitative real-time polymerase chain reaction analysis showed that LCSCs isolated using different markers in the same HCC phenotype had different expression profiles. Likewise, LCSCs isolated from different HCC phenotypes with the same marker also had unique expression profiles and displayed varying resistance profiles to Sorafenib. Thus, using a range of commonly used CSC markers in HCCs and cell lines, we demonstrate that currently available markers are not specific for LCSCs. LCSCs have unique subtypes that express distinctive combinations of LCSC markers and altered drug resistance profiles, making their identification problematic

Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction, and medical education, and investigate whether LLMs possess the transformative power to revolutionize these tasks or whether the distinct complexities of biomedical domain presents unique challenges. Following an extensive literature survey, we find that significant advances have been made in the field of text generation tasks, surpassing the previous state-of-the-art methods. For other applications, the advances have been modest. Overall, LLMs have not yet revolutionized the biomedicine, but recent rapid progress indicates that such methods hold great potential to provide valuable means for accelerating discovery and improving health. We also find that the use of LLMs, like ChatGPT, in the fields of biomedicine and health entails various risks and challenges, including fabricated information in its generated responses, as well as legal and privacy concerns associated with sensitive patient data. We believe this first-of-its-kind survey can provide a comprehensive overview to biomedical researchers and healthcare practitioners on the opportunities and challenges associated with using ChatGPT and other LLMs for transforming biomedicine and health