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To remedy these gaps, researchers must continue to further elucidate the needs, preferences, and gaps regarding access to early care and education opportunities for Latino children. For those studying trauma and ACEs among low-income children, greater attention to how preventative interventions or treatments that are embedded in ECE settings serve Latino populations is warranted, as this has the tremendous potential to mitigate the long-term impact of ACEs on Latino children. The paper concludes with a set of early childhood practice and policy recommendations for enhancing protective experiences for low-income Latino children.In the context of rising disasters worldwide and the challenges of the COVID-19 pandemic, this commentary considers the implications of findings in resilience science on children and youth for disaster preparation and response. The multisystem challenges posed by disasters are illustrated by the COVID-19 pandemic. We discuss the significance of disasters in the history of resilience science and the emergence of a unifying systems definition of resilience. Principles of a multisystem perspective on resilience and major findings on what matters for young people in disasters are delineated with reference to the pandemic. Striking parallels are noted in the psychosocial resilience factors identified at the level of individual children, families, schools, and communities. These parallels suggest that adaptive capacities associated with resilience in these interacting systems reflect interconnected networks and processes that co-evolved and may operate in concert. As resilience science moves toward integrated theory, knowledge, and applications in practice, particularly in disaster risk reduction and resilience promotion, more focus will be needed on multisystem and multidisciplinary research, communication, training, and planning.Inequalities are prevalent across the spectrum of cancer research and patient care, with destructive repercussions for people and society. We cannot ignore them and must act against the social injustices that perpetuate them.The risks posed to patients with cancer by the current COVID-19 pandemic demand rapid structural changes in healthcare delivery, with many positive changes likely to continue long term. An immediate critical reassessment of trial methodology based on clinical and scientific priorities is essential to ensure the resilience of clinical cancer research and optimize patient-centered care.The COVID-19 pandemic has disrupted the spectrum of cancer care, including delaying diagnoses and treatment and halting clinical trials. In response, healthcare systems are rapidly reorganizing cancer services to ensure that patients continue to receive essential care while minimizing exposure to SARS-CoV-2 infection.Angiotensin converting enzyme 2 (ACE2) and main protease (MPro) are significant target proteins, mainly involved in the attachment of viral genome to host cells and aid in replication of severe acute respiratory syndrome-coronaviruses or SARS-CoV genome. In the present study, we identified 11 potent bioactive compounds from ethanolic leaf extract of Ipomoea obscura (L.) by using GC-MS analysis. These potential bioactive compounds were considered for molecular docking studies against ACE2 and MPro target proteins to determine the antiviral effects against SARS-COV. Results exhibits that among 11 compounds from I. obscura (L.), urso-deoxycholic acid, demeclocycline, tetracycline, chlorotetracycline, and ethyl iso-allocholate had potential viral inhibitory activity. Hence, the present findings suggested that chemical constitution present in I. obscura (L.) will address inhibition of corona viral replication in host cells.The COVID-19 crisis has brought about new clinical questions, new workflows, and accelerated distributed healthcare needs. Although artificial intelligence (AI)-based clinical decision support seemed to have matured, the application of AI-based tools for COVID-19 has been limited to date. In this perspective piece, the opportunities and requirements for AI-based clinical decision support systems are identified and challenges that impact “AI readiness” for rapidly emergent healthcare challenges are highlighted.The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that led to the COVID-19 (Coronavirus Disease 2019) pandemic, has resulted in substantial overburdening of healthcare systems as well as an economic crisis on a global scale. This has in turn resulted in widespread efforts to identify suitable therapies to address this aggressive pathogen. Therapeutic antibody and vaccine development are being actively explored, and a phase I clinical trial of mRNA-1273 which is developed in collaboration between the National Institute of Allergy and Infectious Diseases and Moderna, Inc. is currently underway. Timelines for the broad deployment of a vaccine and antibody therapies have been estimated to be 12-18 months or longer. These are promising approaches that may lead to sustained efficacy in treating COVID-19. However, its emergence has also led to a large number of clinical trials evaluating drug combinations composed of repurposed therapies. As study results of these combinations continue to be evaluated, there is a need to move beyond traditional drug screening and repurposing by harnessing artificial intelligence (AI) to optimize combination therapy design. This may lead to the rapid identification of regimens that mediate unexpected and markedly enhanced treatment outcomes.This work describes the design and implementation of an automated device for catalytic materials testing by direct modifications to a gas chromatograph (GC). The setup can be operated as a plug-flow isothermal reactor and enables the control of relevant parameters such as reaction temperature and reactant partial pressures directly from the GC. selleck products High-quality kinetic data (including reaction rates, product distributions, and activation barriers) can be obtained at almost one-tenth of the fabrication cost of analogous commercial setups. With these key benefits including automation, low cost, and limited experimental equipment instrumentation, this implementation is intended as a high-throughput catalyst screening reactor that can be readily utilized by materials synthesis researchers to assess the catalytic properties of their synthesized structures in vapor-phase chemistries.