Role of Silymarin in Cancer Treatment: Facts, Hypotheses, and Questions

The flavonoid silymarin extracted from the seeds of Sylibum marianum is a mixture of 6 flavolignan isomers. The 3 more important isomers are silybin (or silibinin), silydianin, and silychristin. Silybin is functionally the most active of these compounds. This group of flavonoids has been extensively studied and they have been used as hepato-protective substances for the mushroom Amanita phalloides intoxication and mainly chronic liver diseases such as alcoholic cirrhosis and nonalcoholic fatty liver. Hepatitis C progression is not, or slightly, modified by silymarin. Recently, it has also been proposed for SARS COVID-19 infection therapy. The biochemical and molecular mechanisms of action of these substances in cancer are subjects of ongoing research. Paradoxically, many of its identified actions such as antioxidant, promoter of ribosomal synthesis, and mitochondrial membrane stabilization, may seem protumoral at first sight, however, silymarin compounds have clear anticancer effects. Some of them are: decreasing migration through multiple targeting, decreasing hypoxia inducible factor-1α expression, inducing apoptosis in some malignant cells, and inhibiting promitotic signaling among others. Interestingly, the antitumoral activity of silymarin compounds is limited to malignant cells while the nonmalignant cells seem not to be affected. Furthermore, there is a long history of silymarin use in human diseases without toxicity after prolonged administration. The ample distribution and easy accessibility to milk thistle—the source of silymarin compounds, its over the counter availability, the fact that it is a weed, some controversial issues regarding bioavailability, and being a nutraceutical rather than a drug, has somehow led medical professionals to view its anticancer effects with skepticism. This is a fundamental reason why it never achieved bedside status in cancer treatment. However, in spite of all the antitumoral effects, silymarin actually has dual effects and in some cases such as pancreatic cancer it can promote stemness. This review deals with recent investigations to elucidate the molecular actions of this flavonoid in cancer, and to consider the possibility of repurposing it. Particular attention is dedicated to silymarin's dual role in cancer and to some controversies of its real effectiveness.

Research on Hydrogen Consumption and Driving Range of Hydrogen Fuel Cell Vehicle under the CLTC-P Condition

Hydrogen consumption and mileage are important economic indicators of fuel cell vehicles. Hydrogen consumption is the fundamental reason that restricts mileage. Since there are few quantitative studies on hydrogen consumption during actual vehicle operation, the high cost of hydrogen consumption in outdoor testing makes it impossible to guarantee the accuracy of the test. Therefore, this study puts forward a test method based on the hydrogen consumption of fuel cell vehicles under CLTC-P operating conditions to test the hydrogen consumption of fuel cell vehicles per 100 km. Finally, the experiment shows that the mileage calculated by hydrogen consumption has a higher consistency with the actual mileage. Based on this hydrogen consumption test method, the hydrogen consumption can be accurately measured, and the test time and cost can be effectively reduced.

Common Fallacies about Multivalued Circuits

For more than 60 years, many ternary or quaternary circuits have been proposed based on similar assumptions. We successively examine four of these assumptions and demonstrate that they are wrong. The fundamental reason for which m-valued combinational circuits are more complicated than the corresponding binary ones is explained. M-valued flash memories are used in USB devices because access times in not critical and a trade-off is possible between access time and chip area. If m-valued circuits are reduced to a very small niche in the binary world with semi-conductor technologies, there is a significant exception: quantum devices and computers are a true breakthrough as qbits are intrinsically multivalued. Successful m-valued circuits need m-valued devices as qbits.

Powerful and Novel Tumour Detection in Brain MRI Images Employing Hybrid Computational Techniques

Brain tumour detection is an evergreen topic to attract attention in the examination field of Information Technology innovation with biomedical designing, in view of the gigantic need of proficient and viable strategy for assessment of enormous measure of information. Image segmentation is considered as one of the most vital systems for visualizing tissues in an individual. To robotize image segmentation, we have proposed a calculation to get global optimal thresholding esteem for a specific brain MRI image, utilizing OTSU+Sauvola binarization strategy. The fundamental reason for feature collection is to diminish the quantity of structures utilized in classification while keeping up satisfactory classification exactness. One of the most extra-customary procedures applied for feature extraction is Discrete Wavelet Transform (DWT). Adequately it anticipates the estimation space on a plane to such an extent that the fluctuation of the information is ideally protected. We propose a justifiable model for brain tumours discovery and classification i.e., to classify whether the tumour is benign or malignant, utilizing SVM classification. SVM utilized here deals with basic hazard minimization to group the images for the tumour extraction, and a Graphical User Interface is created for the tumour classification operation, using the MATLAB platform.

Toward the Development of Key Competencies: A Conceptual Framework for the STEM Curriculum Design and a Case Study

National attention has been given to science, technology, engineering, and mathematics (STEM) education, which is well recognized as an effective way to cultivate the key competencies of 21st-century talents. However, current STEM education falls short of the desired results. The fundamental reason is that there has not been a clearly and structurally explained systematic construction and effective implementation of STEM curricula. Accordingly, this article systematically expounds on the construction of the STEM curricula system from four aspects. Specifically, we first proposed the components of the STEM competencies as the goal of STEM education to provide a guiding direction for other parts of the design of the STEM curricula. Then, we elaborated on how to cultivate the STEM competencies from two aspects: the design principles of the STEM curricula content and the implementation strategies of STEM teaching. Finally, we explained how to effectively evaluate to monitor and improve the implementation of the STEM curriculum. In addition to the above mentioned, we then presented a case study of STEM courses constructed under the guidance of “think-based instruction theory” (TBIT) to help readers further understand the nature of the STEM curricula.

Decision Models and Technology Can Help Psychiatry Develop Biomarkers

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation. This, we argue, is a fundamental reason why psychiatry is unable to define clinically useful biomarkers: because psychiatry does not currently quantify clinical data, decision models cannot be operationalized and, in the absence of an operationalized decision model, it is impossible to define how a biomarker might be of use. Here, psychiatry might benefit from digital technologies that have recently emerged specifically to quantify clinically relevant facets of human behavior. We propose that digital tools might help psychiatry in two ways: first, by quantifying data already present in the standard clinical interaction and by allowing decision models to be operationalized and evaluated; second, by testing whether new forms of data might have value within an operationalized decision model. We reference successes from other medical specialties to illustrate how quantitative data and operationalized decision models improve patient care.

AN EXPLORATORY STUDY ON THE RESEARCH TENDENCY OF SCHOOL COUNSELORS IN SOUTH KOREA

This study aimed to examine a research tendency through Master's and Doctoral dissertation in South Korea related to school counselors. In this study, school counselors were used in terms that included full-time and contractual counselors. School counselors are teachers who specialize in understanding students' daily psychological counseling, problem behavior and maladaptive counseling and establishing a prevention support system of fundamental reason of problem behavior for students. This is because their tasks required in school are similar. They were deployed to unit schools after Wee Project implemented in 2007 to ensure that students and all students experiencing poor learning and school maladaptation for having a happy school life. This study aimed to lay the foundation for improving and developing policies for improving the welfare and professionalism of school counselors, focusing on the subject of the degree thesis related to school counselors. This study conducted an exploratory study based on the year of publication and topics of the dissertation based on key words extracted from the data. The dissertations were published from 2010 to 2021 and were collected through Riss, a domestic database website in South Korea. This study focused on the frequency of emergence and Word Cloud which shows research tendency based on the year of publication analyzed by the frequency of emergency, title of the dissertation, and key words in abstract of the dissertation extracted from a file in MS Excel from the domestic database homepage. The analysis results of this study are as follows. First, the role and awareness of professional counseling teachers and Wee classes are required. Second, research was conducted to develop the capabilities of school counselors teachers working in the Wee class.it will serve as a foundation for improving professionalism, leading to the protection of ethics as a counselor working in the Wee class and ensuring the rights and welfare of counselors. In order to improve counseling capabilities, supervision and a certain amount of counseling practice are required in the process of training school counselors.

Impact of the Coronavirus Pandemic on Sino-US Relations

This article focuses on the impact of the pandemic coronavirus (COVID-19) on Sino-US relations. It describes Sino-US relations before and after the outbreak of the coronavirus pandemic. Particular attention is paid to the ongoing trade war between the PRC and the US, as well as the development of the information war caused by the politicization of the epidemic. The reasons for the deterioration of Sino-US relations under the influence of the coronavirus are considered. The author highlighted the following factors: US fears about the transition of world economic and political leadership from Washington to Beijing; the disagreement between China and the United States over the anti-epidemic in the framework of multilateral cooperation; problems caused by objectively accelerated changes in the world order. It is concluded that the epidemic plays a limited role in the deterioration of economic and political relations between China and the US. The fundamental reason remains the discrepancy between the unilateralism advocated by the US and multilateralism called for by China.

An Analysis on Object Recognition Using Convolutional Neural Networks

The global development and progress in scientific paraphernalia and technology is the fundamental reason for the rapid increasein the data volume. Several significant techniques have been introducedfor image processing and object detection owing to this advancement. The promising features and transfer learning of ConvolutionalNeural Network (CNN) havegained much attention around the globe by researchers as well as computer vision society, as a result of which, several remarkable breakthroughs were achieved. This paper comprehensively reviews the data classification, history as well as architecture of CNN and well-known techniques bytheir boons and absurdities. Finally, a discussion for implementation of CNN over object detection for effectual results based on their critical analysis and performances is presented

In the Wilderness

The chapter analyses the reasons for Venizelos's confrontation with the prince, from their respective points of view. A reason for Venizelos was his restless desire for progress towards union with Greece, through a more genuine autonomy. There was also a personal element. He was not someone to sit down meekly in face of the sharp attacks of the prince's advisers who set out to stop his mouth. The fundamental reason was dispute over union, reflecting two different political philosophies, popular sovereignty for Venizelos, the interests of the Glücksburg dynasty for prince George. The clash pushed the prince into more arbitrary measures, the closure of Venizelos's newspaper, and his short imprisonment. His rallies and island-wide visits before the assembly elections of March 1903 showed that he was still a popular figure. But though Venizelos was cold shouldered when he visited Athens to explain his position, it would be wrong to see him as isolated. Politically aware Cretans were taking sides, the prince's arbitrary behavior was alienating members of the professional classes.