RESUMEN
Respiratory diseases like chronic obstructive pulmonary disease (COPD), chronic bronchitis, asthma, lung cancer, tuberculosis (TB), pneumonia, and, currently, respiratory infection due to novel Coronavirus (2019-nCoV) have been the major cause of concern these days and pose a serious challenge before the medical practitioners. Various types of dosage forms, surgeries, and radiotherapies are available as the major treatment options;however, these approaches are of limited use in the successful management of the above disorders and some seem very expensive. Conventional dosage form-based therapies have many disadvantages, including poor bioavailability, safety issues, poor site specificity, and drug resistance. In recent years, with the recent advancement in research and develop- ment, different novel drug delivery approaches have been aimed for comprehen- sive management of various types of respiratory diseases. Cyclodextrins (CDs) based formulations played a significant role in improving the treatment of respi- ratory diseases. It is utilized to improve the drug's physicochemical properties, however, some of its derivatives offer direct therapeutic efficacy. In this chapter, the derivates of CD, provided with their sources and physicochemical properties, are discussed with their applications in treating major lung diseases like COPD, chronic bronchitis, asthma, lung cancer, pulmonary fibrosis, pneumonia, etc. We have also aimed to showcase, based on the ongoing clinical trials, the recent translational potential of CD-based drug delivery systems used in the respiratory disease therapy. © The Author (s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
RESUMEN
COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, based on 5434 records of COVID cases collected from a popular data science community and using Rapid Miner Studio software, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Employing the same clinical dataset, a linear regression model is also proposed having a moderately high coefficient of determination of 0.739 in accurately predicting the occurrence of COVID-19. A decision support system can also be developed using the association rules to ease out and automate early detection of other diseases. © 2023 by the authors.
RESUMEN
We present the publication trends in the literature on venture capital financing during crises and highlight the top publishing source with the most contributing authors in their affiliated countries using bibliometric and content analysis of 115 documents retrieved from the Scopus database. This study provides insight into the theme with the help of co-occurrence, co-citation, and bibliographic coupling analysis. The authors' keyword co-occurrence analysis shows the spatial links among the articles based on venture capital during the financial crisis and the COVID-19 pandemic. The top productive and influential source is the journal Venture Capital, followed by Small Business Economics and the Journal of Business Venturing. The Journal of Business Venturing is the top journal in terms of citations per document. The United States is the most contributing affiliated country having strong links with several nations. The publications on crisis-led venture capital increased significantly after the financial crisis of 2008.