MicroRNAs and Chinese Medicinal Herbs: New Possibilities in Cancer Therapy

In recent decades Chinese medicine has been used worldwide as a complementary and alternative medicine to treat cancer. Plenty of studies have shown that microRNAs (miRNAs) play fundamental roles in many pathological processes, including cancer, while the anti-cancer mechanisms of Chinese medicinal herbs targeting miRNAs also have been extensively explored. Our previous studies and those of others on Chinese medicinal herbs and miRNAs in various cancer models have provided a possibility of new cancer therapies, for example, up-regulating the expression of miR-23a may activate the positive regulatory network of p53 and miR-23a involved in the mechanism underlying the anti-tumor effect of berberine in hepatocellular carcinoma (HCC). In this review, we survey the role of Chinese medicinal herbal products in regulating miRNAs in cancer and the use of mediating miRNAs for cancer treatment. In addition, the controversial roles of herb-derived exogenous miRNAs in cancer treatment are also discussed. It is expected that targeting miRNAs would provide a novel therapeutic approach in cancer therapy by improving overall response and survival outcomes in cancer treatment, especially when combined with conventional therapeutics and Chinese medicinal herbal products. © 2015 by the authors; licensee MDPI, Basel, Switzerland.published_or_final_versio

Suppression of Vascular Endothelial Growth Factor via Inactivation of Eukaryotic Elongation Factor 2 by Alkaloids in Coptidis rhizoma in Hepatocellular Carcinoma

Aim of study: To investigate the inhibitory effect of Coptidis rhizome aqueous extract (CRAE) on vascular endothelial growth factor (VEGF) expression and tumor angiogenesis in hepatocellular carcinoma (HCC). Methods: Quality control of CRAE was determined. Secretion of VEGF protein and expression of its mRNA in MHCC97L and Hep G2 cells were measured with enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction. Synthesis of nascent protein was determined by AHA-protein-labeling technologies. The in vivo antiangiogenic effect of CRAE was evaluated with a xenograft model. Results: Absence of organochlorine pesticides in CRAE was found, and phytochemical analysis showed that its components were in proportion of magnoflorine 2.2%, jatrorrhizine 1.68%, palmatine 4.4%, and berberine 13.8%. CRAE exhibited significant inhibition on VEGF secretion from MHCC97L and HepG2 cells at nontoxic doses. The mRNA transcripts of VEGF could not be inhibited by CRAE; however, synthesis of VEGF nascent protein was potently blocked by CRAE. CRAE intervention increased the phosphorylation of eukaryotic elongation factor 2 (eEF2) in HCC cells, which blocked eEF2 activity for proceeding nascent protein synthesis. The activity of eEF2 was restored in CRAE-treated HCC cells in the presence of A484594, leading to the recovery of VEGF expression. Berberine was found to be the major active component in CRAE; however, CRAE is more effective in inhibiting eEF2 activity compared to berberine treatment alone, suggesting the additive effect of other components present. Reduction of tumor size and neovascularization were observed in mice xenograft model. Conclusion: Our study postulates the antiangiogenic effect of CRAE on hepatocellular carcinoma via an eEF2-driven pathway.postprin

IRE1α inhibition by natural compound genipin on tumour associated macrophages reduces growth of hepatocellular carcinoma

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Autophagy-induced RelB/p52 activation mediates tumour-associated macrophage repolarisation and suppression of hepatocellular carcinoma by natural compound baicalin

Open Access JournalThe plasticity of tumour-associated macrophages (TAMs) has implicated an influential role in hepatocellular carcinoma (HCC). Repolarisation of TAM towards M1 phenotype characterises an immune-competent microenvironment that favours tumour regression. To investigate the role and mechanism of TAM repolarisation in suppression of HCC by a natural compound baicalin, Orthotopic HCC implantation model was used to investigate the effect of baicalin on HCC; liposome-clodronate was introduced to suppress macrophage populations in mice; bone marrow-derived monocytes (BMDMs) were induced to unpolarised, M1-like, M2-like macrophages and TAM using different conditioned medium. We observed that oral administration of baicalin (50 mg/kg) completely blocked orthotopic growth of implanted HCC. Suppression of HCC by baicalin was diminished when mice macrophage was removed by clodronate treatment. Baicalin induced repolarisation of TAM to M1-like phenotype without specific toxicity to either phenotype of macrophages. Baicalin initiated TAM reprogramming to M1-like macrophage, and promoted pro-inflammatory cytokines production. Co-culturing of HCC cells with baicalin-treated TAMs resulted in reduced proliferation and motility in HCC. Baicalin had minimal effect on derivation of macrophage polarisation factors by HCC cells, while directly induced repolarisation of TAM and M2-like macrophage. This effect was associated with elevated autophagy, and transcriptional activation of RelB/p52 pathway. Suppression of autophagy or RelB abolished skewing of baicalin-treated TAM. Autophagic degradation of TRAF2 in baicalin-treated TAM might be responsible for RelB/p52 activation. Our findings unveil the essential role of TAM repolarisation in suppressive effect of baicalin on HCC, which requires autophagy-associated activation of RelB/p52.published_or_final_versio

Current Status of Herbal Medicines in Chronic Liver Disease Therapy: The Biological Effects, Molecular Targets and Future Prospects

Chronic liver dysfunction or injury is a serious health problem worldwide. Chronic liver disease involves a wide range of liver pathologies that include fatty liver, hepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. The efficiency of current synthetic agents in treating chronic liver disease is not satisfactory and they have undesirable side effects. Thereby, numerous medicinal herbs and phytochemicals have been investigated as complementary and alternative treatments for chronic liver diseases. Since some herbal products have already been used for the management of liver diseases in some countries or regions, a systematic review on these herbal medicines for chronic liver disease is urgently needed. Herein, we conducted a review describing the potential role, pharmacological studies and molecular mechanisms of several commonly used medicinal herbs and phytochemicals for chronic liver diseases treatment. Their potential toxicity and side effects were also discussed. Several herbal formulae and their biological effects in chronic liver disease treatment as well as the underlying molecular mechanisms are also summarized in this paper. This review article is a comprehensive and systematic analysis of our current knowledge of the conventional medicinal herbs and phytochemicals in treating chronic liver diseases and on the potential pitfalls which need to be addressed in future study. © 2015 by the authors; licensee MDPI, Basel, Switzerland.published_or_final_versio

Berberine Suppresses Cyclin D1 Expression through Proteasomal Degradation in Human Hepatoma Cells

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Generative adversarial networks in ophthalmology: what are these and how can they be used?

PURPOSE OF REVIEW: The development of deep learning (DL) systems requires a large amount of data, which may be limited by costs, protection of patient information and low prevalence of some conditions. Recent developments in artificial intelligence techniques have provided an innovative alternative to this challenge via the synthesis of biomedical images within a DL framework known as generative adversarial networks (GANs). This paper aims to introduce how GANs can be deployed for image synthesis in ophthalmology and to discuss the potential applications of GANs-produced images. RECENT FINDINGS: Image synthesis is the most relevant function of GANs to the medical field, and it has been widely used for generating 'new' medical images of various modalities. In ophthalmology, GANs have mainly been utilized for augmenting classification and predictive tasks, by synthesizing fundus images and optical coherence tomography images with and without pathologies such as age-related macular degeneration and diabetic retinopathy. Despite their ability to generate high-resolution images, the development of GANs remains data intensive, and there is a lack of consensus on how best to evaluate the outputs produced by GANs. SUMMARY: Although the problem of artificial biomedical data generation is of great interest, image synthesis by GANs represents an innovation with yet unclear relevance for ophthalmology

Artificial intelligence and deep learning in ophthalmology

Artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest in recent years. DL has been widely adopted in image recognition, speech recognition and natural language processing, but is only beginning to impact on healthcare. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography and visual fields, achieving robust classification performance in the detection of diabetic retinopathy and retinopathy of prematurity, the glaucoma-like disc, macular oedema and age-related macular degeneration. DL in ocular imaging may be used in conjunction with telemedicine as a possible solution to screen, diagnose and monitor major eye diseases for patients in primary care and community settings. Nonetheless, there are also potential challenges with DL application in ophthalmology, including clinical and technical challenges, explainability of the algorithm results, medicolegal issues, and physician and patient acceptance of the AI 'black-box' algorithms. DL could potentially revolutionise how ophthalmology is practised in the future. This review provides a summary of the state-of-the-art DL systems described for ophthalmic applications, potential challenges in clinical deployment and the path forward

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology

Incidence of bleeding in patients with left ventricular thrombi post-myocardial infarction on triple antithrombotic therapy with a lowered International Normalised Ratio (INR) range: a case series

Journal of Thrombosis and Thrombolysis39410 - 42