Although statins are effective for treating hypercholesterolemia, they can have various side effects, including rhabdomyolysis, a potentially fatal condition. This review evaluated the incidence and underlying molecular mechanism of statin-induced rhabdomyolysis and analyzed its risk factors, prevention, and management. We focused on the clinical and randomized clinical trials of statin monotherapies and combinations with other drugs. The primary mechanism of statin therapy-induced rhabdomyolysis is believed to be a decrease in ubiquinone (coenzyme Q) produced by the HMG-CoA pathway. Additionally, different types of lipophilic and hydrophilic statins play a role in causing rhabdomyolysis. Although statin-induced rhabdomyolysis has a low incidence, there is no guarantee that patients will be free of this side effect. Rhabdomyolysis can be prevented by reducing the risk factors, such as using CYP3A4 inhibitors, using high-dose statins, and strenuous physical activities.

The emergence of multidrug-resistant Mycobacterium tuberculosis (MTB) has become a major problem in treating tuberculosis (TB) and shows the need to develop new and efficient drugs for better TB control. This study aimed to use in silico techniques to discover potential inhibitors to the Enoyl-[acyl-carrier-protein] reductase (InhA), which controls mycobacterial cell wall construction. Initially, 391 quercetin analogs present in the KNApSAck_3D database were selected, filters were sequentially applied by docking-based virtual screening. After recategorizing the variables (bond energy prediction and molecular interaction, including hydrogen bond and hydrophobic bond), compounds C00013874, C00006532, and C00013887 were selected as hit ligands. These compounds showed great hydrophobic contributions, and for each hit ligand, 100 ns of molecular dynamic simulations were performed, and the binding free energy was calculated. C00013874 demonstrated the greatest capacity for the InhA enzyme inhibition with ΔGbind = −148.651 kcal/mol compare to NAD (native ligand) presented a ΔGbind = −87.570 kcal/mol. These data are preliminary studies and might be a suitable candidate for further experimental analysis.

Background: Asymptomatic and high-risk COVID-19 patients are advised to self-isolate at home. However, patients may not realize that the condition is deteriorating until too late. Objective: This study aims to review various artificial intelligence-based telemedicine research during the COVID-19 outbreak and proposes a framework for developing telemedicine powered by artificial intelligence to monitor progression in COVID-19 patients during isolation at home. It also aims to map challenges using artificial intelligence-based telemedicine in the community. Methods: A systematic review was performed for the related articles published in 2019–2021 and conducted in the PubMed and ScienceDirect database using the keywords “telemedicine,” “artificial intelligence,” and “COVID-19”. The inclusion criteria were full-text articles and original research written in the English language. Results: Thirteen articles were included in this review to describe the current application of artificial intelligence-based telemedicine during the COVID-19 pandemic. Various current applications have been implemented, such as for early diagnosis and tracing of contact for the users, to monitor symptoms and decision-making treatment, clinical management, and virtual and remote treatment. We also proposed the framework of telemedicine powered by artificial intelligence for support the self-isolation of COVID-19 patients based on the recent update in technology. However, we identified some challenges for using digital health technologies because of the ethical and practical use, the policy and regulation, and device use both for healthcare workers and patients. Conclusion: Artificial intelligence promises to improve the practice of medicine in various ways. However, practical applications still need to be explored, and medical professionals also need to adapt to these advances for better healthcare delivery to the public.

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, pharmacists have been on the front lines of health care, offering vital services. Consequently, the need for pharmacists to support an effective antibiotic stewardship (AMS) program during the COVID-19 outbreak has become increasingly evident. This scoping review was performed to examine related articles in 2020– 2022 published in the Scopus, SAGE, and Cochrane databases with the keywords “Pharmacist” and “Antibiotic Stewardship” and “COVID-19”. The inclusion criteria were full-text articles written in English. A total of 15 articles were included in this review to describe the role of pharmacists in AMS during the COVID-19 outbreak. In general, pharmacists are responsible for identifying and treating patients during pandemics, ensuring the continued supply and accessibility of medications, promoting health policies, and monitoring antibiotic use for COVID-19 cases and co-infections. At the hospital, as the most significant element for pharmacists on the AMS team, the apparent change is demonstrated in educating patients on telehealth services, clarifying misconceptions about treatments and antibiotic consumption, as well as taking a leadership position to establish local guidelines for the COVID-19 treatment protocol. Pharmacists have an important role in the AMS program, and the COVID-19 pandemic was perceived as a highlight their importance. Therefore, their work with the AMS program needs to be improved as they learn to extend their role in telehealth services, educate and clarify the misconceptions about COVID-19 treatments and other antibiotic consumption in the community, inventory control the COVID-19 drug, antibiotics, and vaccine, as well as take the lead in establishing local guidelines on antibiotic consumption during the pandemic outbreak. Graphical Abstract:

Background: A prophylactic and immunotherapeutic vaccine for Mycobacterium tuberculosis (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection. Methods: The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike glycoprotein of SARS-CoV-2 for B and T cells. The antigenicity, allergenicity, and several physiochemical properties of the developed multi-epitope vaccination were then evaluated. Additionally, molecular docking and normal mode analysis (NMA) were utilized in evaluating the vaccine’s immunogenicity and complex stability. Results: Selected proteins and predicted epitopes suggest that the vaccine prediction can be helpful in the protection against both SARS-CoV-2 and MTB coinfection. Through docking molecular and NMA, the vaccine-TLR4 protein interaction was predicted to be efficient with a high level of IgG, T-helper cells, T-cytotoxic cells, andIFN-γ. Conclusion: This epitope-based vaccine is a potentially attractive tool for SARS-CoV-2 and MTB coinfection vaccine development. Graphical Abstract: