ResearchPad - editorial https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Ten simple rules for designing learning experiences that involve enhancing computational biology Wikipedia articles]]> https://www.researchpad.co/article/elastic_article_14536 <![CDATA[Adipose Stem Cells (ASCs) and Stromal Vascular Fraction (SVF) as a Potential Therapy in Combating (COVID-19)-Disease]]> https://www.researchpad.co/article/elastic_article_14529 A recent and interesting study reported improved respiratory activity after intravenous administration of mesenchymal stem cells (MSCs) into patients affected by coronavirus disease 2019 (COVID-19). These outcomes displayed that intravenous infiltration of MSCs is a safe and efficacy treatment for COVID-19 pneumonia, a severe acute respiratory illness caused by the coronavirus 2 (SARS-CoV-2). Only 7 patients were treated, but with extraordinary results, opening a new strategy in COVID-19 therapy. Currently, no specific therapies against SARS-CoV-2 are available. The MSCs therapy outcomes reported, are striking, as these cells inhibit the over-activation of the immune system, promoting endogenous repair, by improving the lung microenvironment after the SARS-CoV-2 infection. The MSCs could represent an effective, autologous and safe therapy, and therefore, sharing these published results, here is reported the potential use possibilities in COVID-19 of the most common MSCs represented by Adipose Stem Cells (ASCs).

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<![CDATA[Guide to Immunopharmacology: a database to boost immunology education, research and therapy]]> https://www.researchpad.co/article/elastic_article_14427 In the era of big data, the establishment of a free database, containing all the immune drug targets and associated cell types, is of great value. To this aim, the Guide to Immunopharmacology has been created in a joint effort between the International Union of Basic and Clinical Pharmacology (IUPHAR) and the International Union of Immunological Societies (IUIS). Here we highlight the structure and content of the database, which includes up‐to‐date quantitative information on the fundamental science underlying each immune target. A set of practical examples and tools for data mining are summarized to support immune research into drug discovery and therapeutics.

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<![CDATA[COVID-19 and Ophthalmology: A New Chapter in an Old Story]]> https://www.researchpad.co/article/elastic_article_8342 <![CDATA[Taking a Responsibility for Future Progression of Clinical Psychopharmacology and Neuroscience]]> https://www.researchpad.co/article/elastic_article_14173 <![CDATA[Psoriasis, biologic therapy, and the pandemic of the 21st century]]> https://www.researchpad.co/article/elastic_article_14148 The pandemic known as coronavirus disease-19 (COVID-19) has quickly spread worldwide, with a significant impact on lives all over the world. The complexity related to the new coronavirus and the clinical syndrome it causes is not yet fully understood. The impact of COVID-19 on patients with psoriasis under biologic agents is continuously being observed in this rapidly changing pandemic. A case-by-case evaluation must be made by dermatologists, and the final decision should be discussed and decided by both the patient and the specialist. Observations reveal that immunosuppressive therapy may have a role in the treatment of this virus, placing emphasis on the scenario of safety through maintenance of therapy with biologic agents, especially when there are no signs or symptoms related to the infection or contact with an infected patient.

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<![CDATA[Measuring what matters – information systems for management of chronic disease in primary healthcare settings in low and middle-income countries: challenges and opportunities]]> https://www.researchpad.co/article/elastic_article_14108 Effective health information systems are essential to the delivery of high-quality community-based care for chronic disease which will be needed to address the changing healthcare needs of populations in low and middle-income country settings. Health management information systems (health service data collected at facility level) and electronic health records (data organised by individual patients) may support the measurement-based, collaborative approach that is central to the chronic care model, which has been adopted as the basis for task-shared models of care for mental health and non-communicable disease. We used the performance of routine information systems management to guide our commentary on the evidence-base about information systems to support chronic care. We found that, despite an appetite for using the information to support decision-making around service planning, this rarely happens in practice, reasons include that data is not perceived to be of good quality or fit for purpose. There is often a mismatch between technology design and the availability of specialised knowledge and infrastructure. However, when data collection is designed in collaboration with local stakeholders, there is some evidence of success, demonstrated by completion and accuracy of data forms. Whilst there are global targets for the development of health information systems and progress on these is undoubtedly being made, indicators for chronic disease are seldom prioritised by national governments and there is insufficient decentralisation to facilitate local data-driven decision-making. Our recommendations for future research and development, therefore, focus upon the need to integrate context into the design of information systems: through building strong multisectoral partnerships, ensuring newly developed indicators are well aligned to service models and using technology that is a good fit with local infrastructure. This approach will be necessary if information systems are to deliver on their potential to drive improvements in care for chronic disease.

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<![CDATA[Microbial metabolite mimicry: one step closer to drug discovery]]> https://www.researchpad.co/article/elastic_article_14104 <![CDATA[Multiple Viewpoints on Physician Home Visits]]> https://www.researchpad.co/article/elastic_article_14065 <![CDATA[Editorial: Advances in Biological Understanding of Tumor Radiation Resistance]]> https://www.researchpad.co/article/elastic_article_14024 <![CDATA[Editorial progress of the Colombia Medica Journal]]> https://www.researchpad.co/article/elastic_article_13928 <![CDATA[Editor’s Farewell]]> https://www.researchpad.co/article/elastic_article_13903 <![CDATA[One oral and maxillofacial surgeon’s attitude toward the COVID-19 pandemic]]> https://www.researchpad.co/article/elastic_article_13889 <![CDATA[Hematopoietic stem cell transplantation dilemma during the COVID-19 era]]> https://www.researchpad.co/article/elastic_article_13732 <![CDATA[Artificial intelligence and COVID-19: A multidisciplinary approach]]> https://www.researchpad.co/article/elastic_article_13703 The COVID-19 pandemic is taking a colossal toll in human suffering and lives. A significant amount of new scientific research and data sharing is underway due to the pandemic which is still rapidly spreading. There is now a growing amount of coronavirus related datasets as well as published papers that must be leveraged along with artificial intelligence (AI) to fight this pandemic by driving news approaches to drug discovery, vaccine development, and public awareness. AI can be used to mine this avalanche of new data and papers to extract new insights by cross-referencing papers and searching for patterns that AI algorithms could help discover new possible treatments or help in vaccine development. Drug discovery is not a trivial task and AI technologies like deep learning can help accelerate this process by helping predict which existing drugs, or brand-new drug-like molecules could treat COVID-19. AI techniques can also help disseminate vital information across the globe and reduce the spread of false information about COVID-19. The positive power and potential of AI must be harnessed in the fight to slow the spread of COVID-19 in order to save lives and limit the economic havoc due to this horrific disease.

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<![CDATA[Reviving the US CDC]]> https://www.researchpad.co/article/elastic_article_13695 <![CDATA[Eliminating HCV: a marathon, not a sprint]]> https://www.researchpad.co/article/elastic_article_13631 <![CDATA[COVID-19: Es el momento de estar más unidos que nunca<sup><a href="#d33e204">☆</a></sup>]]> https://www.researchpad.co/article/elastic_article_13619 <![CDATA[Medicina Nuclear en la pandemia por COVID-19<sup><a href="#d34e227">☆</a></sup>]]> https://www.researchpad.co/article/elastic_article_13567 <![CDATA[La mascarilla (que tanto necesitamos es la que hubiéramos necesitado)<sup><a href="#d33e187">☆</a></sup>]]> https://www.researchpad.co/article/elastic_article_13559