Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients

Exploiting Host Kinases to Combat Dengue Virus Infection and Disease

The burden of dengue on human health has dramatically increased in recent years, underscoring the urgent need for effective therapeutic interventions. Despite decades of research since the discovery of the dengue virus, no specific antiviral treatments are available and strategies to reliably prevent severe disease remain limited. Direct-acting antivirals against dengue are under active investigation but have shown limited efficacy to date. An underappreciated Achille's heal of the virus is its dependence on host factors for infection and pathogenesis, each of which presents a potential avenue for therapeutic intervention. We and others have demonstrated that dengue virus relies on multiple host kinases, some of which are already targeted by clinically approved inhibitors. These offer drug repurposing opportunities for host-directed dengue treatment. Here, we summarize findings on the role of kinases in dengue infection and disease and highlight potential kinase targets for the development of innovative host-directed therapeutics.

Safety of baricitinib in vaccinated patients with severe and critical COVID-19 sub study of the randomised Bari-SolidAct trial

BACKGROUND

The Bari-SolidAct randomized controlled trial compared baricitinib with placebo in patients with severe COVID-19. A post hoc analysis revealed a higher incidence of serious adverse events (SAEs) among SARS-CoV-2-vaccinated participants who had received baricitinib. This sub-study aimed to investigate whether vaccination influences the safety profile of baricitinib in patients with severe COVID-19.

METHODS

Biobanked samples from 146 participants (55 vaccinated vs. 91 unvaccinated) were analysed longitudinally for inflammation markers, humoral responses, tissue viral loads, and plasma viral antigens on days 1, 3, and 8. High-dimensional analyses, including RNA sequencing and flow cytometry, were performed on available samples. Mediation analyses were used to assess relationships between SAEs, baseline-adjusted biomarkers, and treatment-vaccination status.

FINDINGS

Vaccinated participants were older, more frequently hospitalized, had more comorbidities, and exhibited higher nasopharyngeal viral loads. Baricitinib treatment did not affect antibody responses or viral clearance, but reduced markers of T-cell and monocyte activation compared to placebo (sCD25, sCD14, sCD163, sTIM-3). Age, baseline levels of plasma viral antigen, and several inflammatory markers, as well as IL-2, IL-6, Neopterin, CXCL16, sCD14, and suPAR on day 8 were associated with the occurrence of SAEs. However, mediation analyses of markers linked to SAEs, baricitinib treatment, or vaccination status did not reveal statistically significant interactions between vaccination status and SAEs.

INTERPRETATION

This sub-study did not identify any virus- or host-related biomarkers significantly associated with the interaction between SARS-CoV-2 vaccination status and the safety of baricitinib. However, caution should be exercised due to the moderate sample size.

FUNDING

EU Horizon 2020 (grant number 101015736).

Designing and optimizing clinical trials for long COVID

Long COVID is a debilitating, multisystemic illness following a SARS-CoV-2 infection whose duration may be indefinite. Over four years into the pandemic, little knowledge has been generated from clinical trials. We analyzed the information available on ClinicalTrials.gov, and found that the rigor and focus of trials vary widely, and that the majority test non-pharmacological interventions with insufficient evidence. We highlight promising trials underway, and encourage the proliferation of clinical trials for treating Long COVID and other infection-associated chronic conditions and illnesses (IACCIs). We recommend several guidelines for Long COVID trials: First, pharmaceutical trials with potentially curative, primary interventions should be prioritized, and both drug repurposing and new drug development should be pursued. Second, study designs should be both rigorous and accessible, e.g., triple-blinded randomized trials that can be conducted remotely, without participants needing to leave their homes. Third, studies should have multiple illness comparator cohorts for IACCIs such as myalgic encephalomyelitis (ME/CFS) and dysautonomia, and screen for the full spectrum of symptomatology and pathologies of these illnesses. Fourth, studies should consider inclusion/exclusion criteria with an eye towards equity and breadth of representation, including participants of all races, ethnicities, and genders most impacted by COVID-19, and including all levels of illness severity. Fifth, involving patient-researchers in all aspects of studies brings immensely valuable perspectives that will increase the impact of trials. We also encourage the development of efficient clinical trial designs including methods to study several therapies in parallel.

Discovery of a novel inhibitor of macropinocytosis with antiviral activity

Several viruses hijack various forms of endocytosis in order to infect host cells. Here, we report the discovery of a molecule with antiviral properties that we named virapinib, which limits viral entry by macropinocytosis. The identification of virapinib derives from a chemical screen using high-throughput microscopy, where we identified chemical entities capable of preventing infection with a pseudotype virus expressing the spike (S) protein from SARS-CoV-2. Subsequent experiments confirmed the capacity of virapinib to inhibit infection by SARS-CoV-2, as well as by additional viruses, such as mpox virus and TBEV. Mechanistic analyses revealed that the compound inhibited macropinocytosis, limiting this entry route for the viruses. Importantly, virapinib has no significant toxicity to host cells. In summary, we present the discovery of a molecule that inhibits macropinocytosis, thereby limiting the infectivity of viruses that use this entry route such as SARS-CoV2.

The AI Future of Emergency Medicine

In the coming years, artificial intelligence (AI) and machine learning will likely give rise to profound changes in the field of emergency medicine, and medicine more broadly. This article discusses these anticipated changes in terms of 3 overlapping yet distinct stages of AI development. It reviews some fundamental concepts in AI and explores their relation to clinical practice, with a focus on emergency medicine. In addition, it describes some of the applications of AI in disease diagnosis, prognosis, and treatment, as well as some of the practical issues that they raise, the barriers to their implementation, and some of the legal and regulatory challenges they create.

Significance of Artificial Intelligence in the Study of Virus-Host Cell Interactions

A highly critical event in a virus's life cycle is successfully entering a given host. This process begins when a viral glycoprotein interacts with a target cell receptor, which provides the molecular basis for target virus-host cell interactions for novel drug discovery. Over the years, extensive research has been carried out in the field of virus-host cell interaction, generating a massive number of genetic and molecular data sources. These datasets are an asset for predicting virus-host interactions at the molecular level using machine learning (ML), a subset of artificial intelligence (AI). In this direction, ML tools are now being applied to recognize patterns in these massive datasets to predict critical interactions between virus and host cells at the protein-protein and protein-sugar levels, as well as to perform transcriptional and translational analysis. On the other end, deep learning (DL) algorithms-a subfield of ML-can extract high-level features from very large datasets to recognize the hidden patterns within genomic sequences and images to develop models for rapid drug discovery predictions that address pathogenic viruses displaying heightened affinity for receptor docking and enhanced cell entry. ML and DL are pivotal forces, driving innovation with their ability to perform analysis of enormous datasets in a highly efficient, cost-effective, accurate, and high-throughput manner. This review focuses on the complexity of virus-host cell interactions at the molecular level in light of the current advances of ML and AI in viral pathogenesis to improve new treatments and prevention strategies.

From bench to bedside: potential of translational research in COVID-19 and beyond

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) have been around for more than 3 years now. However, due to constant viral evolution, novel variants are emerging, leaving old treatment protocols redundant. As treatment options dwindle, infection rates continue to rise and seasonal infection surges become progressively common across the world, rapid solutions are required. With genomic and proteomic methods generating enormous amounts of data to expand our understanding of SARS-CoV-2 biology, there is an urgent requirement for the development of novel therapeutic methods that can allow translational research to flourish. In this review, we highlight the current state of COVID-19 in the world and the effects of post-infection sequelae. We present the contribution of translational research in COVID-19, with various current and novel therapeutic approaches, including antivirals, monoclonal antibodies and vaccines, as well as alternate treatment methods such as immunomodulators, currently being studied and reiterate the importance of translational research in the development of various strategies to contain COVID-19.

Drug repurposing for respiratory infections

Respiratory infections such as Coronavirus disease 2019 are a substantial worldwide health challenge, frequently resulting in severe sickness and death, especially in susceptible groups. Conventional drug development for respiratory infections faces obstacles such as extended timescales, substantial expenses, and the rise of resistance to current treatments. Drug repurposing is a potential method that has evolved to quickly find and reuse existing medications for treating respiratory infections. Drug repurposing utilizes medications previously approved for different purposes, providing a cost-effective and time-efficient method to tackle pressing medical needs. This chapter summarizes current progress and obstacles in repurposing medications for respiratory infections, focusing on notable examples of repurposed pharmaceuticals and their probable modes of action. The text also explores the significance of computational approaches, high-throughput screening, and preclinical investigations in identifying potential candidates for repurposing. The text delves into the significance of regulatory factors, clinical trial structure, and actual data in confirming the effectiveness and safety of repurposed medications for respiratory infections. Drug repurposing is a valuable technique for quickly increasing the range of treatments for respiratory infections, leading to better patient outcomes and decreasing the worldwide disease burden.

Combination therapy of high-dose intravenous anakinra and baricitinib in patients with critical COVID-19: Promising results from retrospective observational study

INTRODUCTION

In this study, we aimed to evaluate the safety and efficacy of combination treatment of high-dose intravenous anakinra and baricitinib in patients with critically ill COVID-19.

MATERIAL AND METHODS

This retrospective observational study was conducted in a tertiary center with diagnosis of COVID-19 patients.Study population consisted of patients with positive polymerase chain reaction and computer tomography findings compatible with COVID-19 as well as critical illness.

RESULTS

Data of 15 patients in combination group and 43 patients in control group were evaluated and included into the study. Overall mortality was 46.7 % (n = 7) in combination arm and 69.8 % (n = 30) in control group although it was not statistically significant (p = 0.1). Similarly, need of intubation was also lower in combination arm (46.7 %) compared to control group (69.8 %), it was not significantly different (p = 0.1). ICU admission was significantly lower in combination (46.7 %, n = 7) arm than control group (76.7 %, n = 33) (p = 0.03, Odds ratio [OR]:4.7). Development of severe infection (20 %, n = 3 vs 25 %, n = 9/36), pulmonary embolism (6.7 %, n = 1 vs 0), myocardial infarction (6.7 %, n = 1 vs 2.6 %, n = 1/38) and pneumothorax (13.3 %, n = 2 vs 2.6 %, n = 1/38) were not different between two groups (p = 0.7, p = 0.3, p = 0.5 and p = 0.2). In multivariable analysis only cHIS score was associated with high mortality (p = 0.018, OR:2.8, [95 % confidence interval: 1.2-6.6]). In survival analysis, mortality rate was significantly lower in combination arm than control group (Log-Rank:p = 0.04).

CONCLUSION

Combination therapy of high-dose anakinra and baricitinib may be an adequate treatment option in patients with COVID-19 who had critical disease and has acceptable safety profile.

Identification of antiviral phytochemicals from cranberry as potential inhibitors of SARS-CoV-2 main protease (Mpro)

Cranberry phytochemicals are known to possess antiviral activities. In the current study, we explored the therapeutic potential of cranberry against SARS-CoV-2 by targeting its main protease (Mpro) enzyme. Firstly, phytochemicals of cranberry origin were identified from three independent databases. Subsequently, virtual screening, using molecular docking and molecular dynamics simulation approaches, led to the identification of three lead phytochemicals namely, cyanidin 3-O-galactoside, β-carotene and epicatechin. Furthermore, in vitro enzymatic assays revealed that cyanidin 3-O-galactoside had the highest inhibitory potential with IC50 of 9.98 μM compared to the other two phytochemicals. Cyanidin 3-O-galactoside belongs to the class of anthocyanins. Anthocyanins extracted from frozen cranberry also exhibited the highest inhibitory potential with IC50 of 23.58 μg/ml compared to the extracts of carotenoids and flavanols, the class for β-carotene and epicatechin, respectively. Finally, we confirm the presence of the phytochemicals in the cranberry extracts using targeted LC-MS/MS analysis. Our results, therefore, indicate that the identified cranberry-derived bioactive compounds as well as cranberry could be used for therapeutic interventions against SARS-CoV-2.

A Risk Profile Using Simple Hematologic Parameters to Assess Benefits From Baricitinib in Patients Hospitalized With COVID-19: A Post Hoc Analysis of the Adaptive COVID-19 Treatment Trial-2

BACKGROUND

The ACTT risk profile, which was developed from ACTT-1 (Adaptive COVID-19 Treatment Trial-1), demonstrated that hospitalized patients with COVID-19 in the high-risk quartile (characterized by low absolute lymphocyte count [ALC], high absolute neutrophil count [ANC], and low platelet count at baseline) benefited most from treatment with the antiviral remdesivir. It is unknown which patient characteristics are associated with benefit from treatment with the immunomodulator baricitinib.

OBJECTIVE

To apply the ACTT risk profile to the ACTT-2 cohort to investigate potential baricitinib-related treatment effects by risk quartile.

DESIGN

Post hoc analysis of ACTT-2, a randomized, double-blind, placebo-controlled trial. (ClinicalTrials.gov: NCT04401579).

SETTING

Sixty-seven trial sites in 8 countries.

PARTICIPANTS

Adults hospitalized with COVID-19 (n = 999; 85% U.S. participants).

INTERVENTION

Baricitinib+remdesivir versus placebo+remdesivir.

MEASUREMENTS

Mortality, progression to invasive mechanical ventilation (IMV) or death, and recovery, all within 28 days; ALC, ANC, and platelet count trajectories.

RESULTS

In the high-risk quartile, baricitinib+remdesivir was associated with reduced risk for death (hazard ratio [HR], 0.38 [95% CI, 0.16 to 0.86]; P = 0.020), decreased progression to IMV or death (HR, 0.57 [CI, 0.35 to 0.93]; P = 0.024), and improved recovery rate (HR, 1.53 [CI, 1.16 to 2.02]; P = 0.002) compared with placebo+remdesivir. After 5 days, participants receiving baricitinib+remdesivir had significantly larger increases in ALC and significantly larger decreases in ANC compared with control participants, with the largest effects observed in the high-risk quartile.

LIMITATION

Secondary analysis of data collected before circulation of current SARS-CoV-2 variants.

CONCLUSION

The ACTT risk profile identifies a subgroup of hospitalized patients who benefit most from baricitinib treatment and captures a patient phenotype of treatment response to an immunomodulator and an antiviral. Changes in ALC and ANC trajectory suggest a mechanism whereby an immunomodulator limits severe COVID-19.

PRIMARY FUNDING SOURCE

National Institute of Allergy and Infectious Diseases.

Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects

The impact of the coronavirus disease 2019 (COVID-19) pandemic on the everyday livelihood of people has been monumental and unparalleled. Although the pandemic has vastly affected the global healthcare system, it has also been a platform to promote and develop pioneering applications based on autonomic artificial intelligence (AI) technology with therapeutic significance in combating the pandemic. Artificial intelligence has successfully demonstrated that it can reduce the probability of human-to-human infectivity of the virus through evaluation, analysis, and triangulation of existing data on the infectivity and spread of the virus. This review talks about the applications and significance of modern robotic and automated systems that may assist in spreading a pandemic. In addition, this study discusses intelligent wearable devices and how they could be helpful throughout the COVID-19 pandemic.

Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI's role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.

In-silico evaluation of natural alkaloids against the main protease and spike glycoprotein as potential therapeutic agents for SARS-CoV-2

Severe Acute Respiratory Syndrome Corona Virus (SARS-CoV-2) is the causative agent of COVID-19 pandemic, which has resulted in global fatalities since late December 2019. Alkaloids play a significant role in drug design for various antiviral diseases, which makes them viable candidates for treating COVID-19. To identify potential antiviral agents, 102 known alkaloids were subjected to docking studies against the two key targets of SARS-CoV-2, namely the spike glycoprotein and main protease. The spike glycoprotein is vital for mediating viral entry into host cells, and main protease plays a crucial role in viral replication; therefore, they serve as compelling targets for therapeutic intervention in combating the disease. From the selection of alkaloids, the top 6 dual inhibitory compounds, namely liensinine, neferine, isoliensinine, fangchinoline, emetine, and acrimarine F, emerged as lead compounds with favorable docked scores. Interestingly, most of them shared the bisbenzylisoquinoline alkaloid framework and belong to Nelumbo nucifera, commonly known as the lotus plant. Docking analysis was conducted by considering the key active site residues of the selected proteins. The stability of the top three ligands with the receptor proteins was further validated through dynamic simulation analysis. The leads underwent ADMET profiling, bioactivity score analysis, and evaluation of drug-likeness and physicochemical properties. Neferine demonstrated a particularly strong affinity for binding, with a docking score of -7.5025 kcal/mol for main protease and -10.0245 kcal/mol for spike glycoprotein, and therefore a strong interaction with both target proteins. Of the lead alkaloids, emetine and fangchinoline demonstrated the lowest toxicity and high LD50 values. These top alkaloids, may support the body's defense and reduce the symptoms by their numerous biological potentials, even though some properties naturally point to their direct antiviral nature. These findings demonstrate the promising anti-COVID-19 properties of the six selected alkaloids, making them potential candidates for drug design. This study will be beneficial in effective drug discovery and design against COVID-19 with negligible side effects.

Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics

Over the period of the preceding decade, artificial intelligence (AI) has proved an outstanding performance in entire dimensions of science including pharmaceutical sciences. AI uses the concept of machine learning (ML), deep learning (DL), and neural networks (NNs) approaches for novel algorithm and hypothesis development by training the machines in multiple ways. AI-based drug development from molecule identification to clinical approval tremendously reduces the cost of development and the time over conventional methods. The COVID-19 vaccine development and approval by regulatory agencies within 1-2 years is the finest example of drug development. Hence, AI is fast becoming a boon for scientific researchers to streamline their advanced discoveries. AI-based FDA-approved nanomedicines perform well as target selective, synergistic therapies, recolonize the theragnostic pharmaceutical stream, and significantly improve drug research outcomes. This comprehensive review delves into the fundamental aspects of AI along with its applications in the realm of pharmaceutical life sciences. It explores AI's role in crucial areas such as drug designing, drug discovery and development, traditional Chinese medicine, integration of multi-omics data, as well as investigations into drug repurposing and polypharmacology studies.

Recent progress in discovery of novel AAK1 inhibitors: from pain therapy to potential anti-viral agents

Adaptor associated kinase 1 (AAK1), a member of the Ark1/Prk1 family of Ser/Thr kinases, is a specific key kinase regulating Thr156 phosphorylation at the μ2 subunit of the adapter complex-2 (AP-2) protein. Due to their important biological functions, AAK1 systems have been validated in clinics for neuropathic pain therapy, and are being explored as potential therapeutic targets for diseases caused by various viruses such as Hepatitis C (HCV), Dengue, Ebola, and COVID-19 viruses and for amyotrophic lateral sclerosis (ALS). Centreing on the advances of drug discovery programs in this field up to 2023, AAK1 inhibitors are discussed from the aspects of the structure-based rational molecular design, pharmacology, toxicology and synthetic routes for the compounds of interest in this review. The aim is to provide the medicinal chemistry community with up-to-date information and to accelerate the drug discovery programs in the field of AAK1 small molecule inhibitors.

Mapping the Lipid Signatures in COVID-19 Infection: Diagnostic and Therapeutic Solutions

The COVID-19 pandemic ignited research centered around the identification of robust biomarkers and therapeutic targets. SARS-CoV-2, the virus responsible, hijacks the metabolic machinery of the host cells. It relies on lipids and lipoproteins of host cells for entry, trafficking, immune evasion, viral replication, and exocytosis. The infection causes host cell lipid metabolic remodelling. Targeting lipid-based processes is thus a promising strategy for countering COVID-19. Here, we review the role of lipids in the different steps of the SARS-CoV-2 pathogenesis and identify lipid-centric targetable avenues. We discuss lipidome changes in infected patients and their relevance as potential clinical diagnostic or prognostic biomarkers. We summarize the emerging direct and indirect therapeutic approaches for targeting COVID-19 using lipid-inspired approaches. Given that viral protein-targeted therapies may become less effective due to mutations in emerging SARS-CoV-2 variants, lipid-inspired interventions may provide additional and perhaps better means of combating this and future pandemics.

Learning from COVID-19: How drug hunters can prepare for the next pandemic

Over 3 years, the SARS-CoV-2 pandemic killed nearly 7 million people and infected more than 767 million globally. During this time, our very small company was able to contribute to antiviral drug discovery efforts through global collaborations with other researchers, which enabled the identification and repurposing of multiple molecules with activity against SARS-CoV-2 including pyronaridine tetraphosphate, tilorone, quinacrine, vandetanib, lumefantrine, cetylpyridinium chloride, raloxifene, carvedilol, olmutinib, dacomitinib, crizotinib, and bosutinib. We highlight some of the key findings from this experience of using different computational and experimental strategies, and detail some of the challenges and strategies for how we might better prepare for the next pandemic so that potential antiviral treatments are available for future outbreaks.

A narrative review on tofacitinib: The properties, function, and usefulness to treat coronavirus disease 2019

In coronavirus disease 2019 (COVID-19), the formation of cytokine storm may have a role in worsening of the disease. By attaching the cytokines like interleukin-6 to the cytokine receptors on a cell surface, Janus kinase (JAK)-signal transducers and activators of transcription (STAT) pathway will be activated in the cytoplasm lead to hyperinflammatory conditions and acute respiratory distress syndrome. Inhibition of JAK/STAT pathway may be useful to prevent the formation of cytokine storm. Tofacitinib is a pan inhibitor of JAKs. In this review, the main characteristics of tofacitinib and its usefulness against COVID-19 pneumonia were reviewed. Tofacitinib may be a hopeful therapeutic candidate against COVID-19 respiratory injury since it inhibits a range of inflammatory pathways. Hence, the agent may be considered a potential therapeutic against the post-COVID-19 respiratory damage. Compared to other JAK inhibitors (JAKi), the administration of tofacitinib in COVID-19 patients may be safer and more effective. Other JAKi such as baricitinib are related to severe adverse events such as thrombotic events compared to more common side effects of tofacitinib.

Advances in treatment strategies for COVID-19: Insights from other coronavirus diseases and prospects

The coronavirus disease 2019 (COVID-19) pandemic is the third human disease outbreak caused by an emerging coronavirus in the 21st century. Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the COVID-19 pandemic has been the most devastating, with millions of deaths. Medical countermeasures are needed to limit the number of infections and fatalities. Here, we discuss advances in clinical and research-based treatment methods for SARS-CoV-2 that were initially derived from treatments for other coronaviruses. Recent advances in SARS-CoV-2 treatments, from traditional drugs and immunotherapies to artificial intelligence to predict potential future treatment methods, are summarized and discussed.

An Overview on Anti-COVID-19 Drug Achievements and Challenges Ahead

The appearance of several coronavirus pandemics/epidemics during the last two decades (SARS-CoV-1 in 2002, MERS-CoV in 2012, and SARS-CoV-2 in 2019) indicates that humanity will face increasing challenges from coronaviruses in the future. The emergence of new strains with similar transmission characteristics as SARS-CoV-2 and mortality rates similar to SARS-CoV-1 (∼10% mortality) or MERS-CoV (∼35% mortality) in the future is a terrifying possibility. Therefore, getting enough preparations to face such risks is an inevitable necessity. The present study aims to review the drug achievements and challenges in the fight against SARS-CoV-2 with a combined perspective derived from pharmacology, pharmacotherapy, and medicinal chemistry insights. Appreciating all the efforts made during the past few years, there is strong evidence that the desired results have not yet been achieved and research in this area should still be pursued seriously. By expressing some pessimistic possibilities and concluding that the drug discovery and pharmacotherapy of COVID-19 have not been successful so far, this short essay tries to draw the attention of responsible authorities to be more prepared against future coronavirus epidemics/pandemics.

Baricitinib Versus Tocilizumab for the Treatment of Moderate to Severe COVID-19

BACKGROUND

To date, minimal data directly compare tocilizumab with baricitinib for treatment in moderate to severe COVID-19.

OBJECTIVE

To compare the rates of in-hospital mortality with progression to mechanical ventilation in patients with COVID-19 who received either tocilizumab or baricitinib.

METHODS

The authors conducted a single-centered, institutional review board-approved, retrospective cohort study. Patients who were 18 years or older who were hospitalized with COVID-19 and who received tocilizumab or baricitinib were included. The primary end point is a composite outcome of progression to mechanical ventilation or in-hospital mortality. Secondary end points include components of the composite outcome and progression to higher level of care, duration of mechanical ventilation, and hospital and intensive care length of stay. Safety end points include the incidence of infections and thrombosis.

RESULTS

A total of 176 patients were included, of whom 61 (34.7%) received tocilizumab and 115 (65.3%) received baricitinib. In the primary outcome, there was no difference between the groups (52.5% tocilizumab vs 44.3% baricitinib, P = 0.305). For safety outcomes, there was a higher instance of thrombosis (11.5% tocilizumab vs 3.5% baricitinib, P = 0.042) and rates of antibiotic use after initiation of therapy (55.7% tocilizumab vs 38.3% baricitinib, P = 0.026) in the tocilizumab group.

CONCLUSION AND RELEVANCE

There was no significant difference in the composite outcome in patients who received tocilizumab or baricitinib for the treatment of COVID-19. However, there was an increase in rates of thrombosis in those receiving tocilizumab compared with baricitinib. These results need to be confirmed in larger prospective, randomized trials.

AI in drug discovery and its clinical relevance

The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in the drug discovery pipeline. We present applications of AI at various stages of drug discovery pipelines, including the inherently computational approaches of de novo design and prediction of a drug's likely properties. Open-source databases and AI-based software tools that facilitate drug design are discussed along with their associated problems of molecule representation, data collection, complexity, labeling, and disparities among labels. How contemporary AI methods, such as graph neural networks, reinforcement learning, and generated models, along with structure-based methods, (i.e., molecular dynamics simulations and molecular docking) can contribute to drug discovery applications and analysis of drug responses is also explored. Finally, recent developments and investments in AI-based start-up companies for biotechnology, drug design and their current progress, hopes and promotions are discussed in this article.

Clinically Evaluated COVID-19 Drugs with Therapeutic Potential for Biological Warfare Agents

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak resulted in hundreds of millions of coronavirus cases, as well as millions of deaths worldwide. Coronavirus Disease 2019 (COVID-19), the disease resulting from exposure to this pathogen, is characterized, among other features, by a pulmonary pathology, which can progress to "cytokine storm", acute respiratory distress syndrome (ARDS), respiratory failure and death. Vaccines are the unsurpassed strategy for prevention and protection against the SARS-CoV-2 infection. However, there is still an extremely high number of severely ill people from at-risk populations. This may be attributed to waning immune response, variant-induced breakthrough infections, unvaccinated population, etc. It is therefore of high importance to utilize pharmacological-based treatments, despite the progression of the global vaccination campaign. Until the approval of Paxlovid, an efficient and highly selective anti-SARS-CoV-2 drug, and the broad-spectrum antiviral agent Lagevrio, many pharmacological-based countermeasures were, and still are, being evaluated in clinical trials. Some of these are host-directed therapies (HDTs), which modulate the endogenic response against the virus, and therefore may confer efficient protection against a wide array of pathogens. These could potentially include Biological Warfare Agents (BWAs), exposure to which may lead to mass casualties due to disease severity and a possible lack of efficient treatment. In this review, we assessed the recent literature on drugs under advanced clinical evaluation for COVID-19 with broad spectrum activity, including antiviral agents and HDTs, which may be relevant for future coping with BWAs, as well as with other agents, in particular respiratory infections.

Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review

Artificial intelligence (AI) plays a more and more important role in our everyday life due to the advantages that it brings when used, such as 24/7 availability, a very low percentage of errors, ability to provide real time insights, or performing a fast analysis. AI is increasingly being used in clinical medical and dental healthcare analyses, with valuable applications, which include disease diagnosis, risk assessment, treatment planning, and drug discovery. This paper presents a narrative literature review of AI use in healthcare from a multi-disciplinary perspective, specifically in the cardiology, allergology, endocrinology, and dental fields. The paper highlights data from recent research and development efforts in AI for healthcare, as well as challenges and limitations associated with AI implementation, such as data privacy and security considerations, along with ethical and legal concerns. The regulation of responsible design, development, and use of AI in healthcare is still in early stages due to the rapid evolution of the field. However, it is our duty to carefully consider the ethical implications of implementing AI and to respond appropriately. With the potential to reshape healthcare delivery and enhance patient outcomes, AI systems continue to reveal their capabilities.

Discovery of pyrrolo[2,1-f][1,2,4]triazine-based inhibitors of adaptor protein 2-associated kinase 1 for the treatment of pain

Adaptor protein 2-associated kinase 1 (AAK1) is a member of the Ark1/Prk1 family of serine/threonine kinases and plays a role in modulating receptor endocytosis. AAK1 was identified as a potential therapeutic target for the treatment of neuropathic pain when it was shown that AAK1 knock out (KO) mice had a normal response to the acute pain phase of the mouse formalin model, but a reduced response to the persistent pain phase. Herein we report our early work investigating a series of pyrrolo[2,1-f][1,2,4]triazines as part of our efforts to recapitulate this KO phenotype with a potent, small molecule inhibitor of AAK1. The synthesis, structure-activity relationships (SAR), and in vivo evaluation of these AAK1 inhibitors is described.

Graphical Abstract

Development of the non-receptor tyrosine kinase FER-targeting PROTACs as a potential strategy for antagonizing ovarian cancer cell motility and invasiveness

Aberrant overexpression of non-receptor tyrosine kinase FER has been reported in various ovarian carcinoma-derived tumor cells and is a poor prognosis factor for patient survival. It plays an essential role in tumor cell migration and invasion, acting concurrently in both kinase-dependent and -independent manners, which is not easily suppressed by conventional enzymatic inhibitors. Nevertheless, the proteolysis-targeting chimeras (PROTACs) technology offers superior efficacy over traditional activity-based inhibitors by simultaneously targeting enzymatic and scaffold functions. Hence in this study, we report the development of two PROTAC compounds that promote robust FER degradation in a cereblon-dependent manner. Both PROTAC degraders outperform an FDA-approved drug, Brigatinib, in ovarian cancer cell motility suppression. Importantly, these PROTAC compounds also degrade multiple oncogenic FER fusion proteins identified in human tumor samples. These results lay an experimental foundation to apply the PROTAC strategy to antagonize cell motility and invasiveness in ovarian and other types of cancers with aberrant expression of FER kinase and highlight PROTACs as a superior strategy for targeting proteins with multiple tumor-promoting functions.

Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment

Recently, a wide spectrum of artificial intelligence (AI)-based applications in the broader categories of digital pathology, biomarker development, and treatment have been explored. In the domain of digital pathology, these have included novel analytical strategies for realizing new information derived from standard histology to guide treatment selection and biomarker development to predict treatment selection and response. In therapeutics, these have included AI-driven drug target discovery, drug design and repurposing, combination regimen optimization, modulated dosing, and beyond. Given the continued advances that are emerging, it is important to develop workflows that seamlessly combine the various segments of AI innovation to comprehensively augment the diagnostic and interventional arsenal of the clinical oncology community. To overcome challenges that remain with regard to the ideation, validation, and deployment of AI in clinical oncology, recommendations toward bringing this workflow to fruition are also provided from clinical, engineering, implementation, and health care economics considerations. Ultimately, this work proposes frameworks that can potentially integrate these domains toward the sustainable adoption of practice-changing AI by the clinical oncology community to drive improved patient outcomes.

Baricitinib Treatment of Coronavirus Disease 2019 Is Associated With a Reduction in Secondary Infections

We performed a secondary analysis of the National Institutes of Health-sponsored Adaptive COVID-19 Treatment Trial (ACTT-2) randomized controlled trial and found that baricitinib was associated with a 50% reduction in secondary infections after controlling for baseline and postrandomization patient characteristics. This finding provides a novel mechanism of benefit for baricitinib and supports the safety profile of this immunomodulator for the treatment of coronavirus disease 2019.

Bibliometric analysis of the use of artificial intelligence in COVID-19 based on scientific studies

Background and Aims

One such strategy is citation analysis used by researchers for research planning an article referred to by another article receives a "citation." By using bibliometric analysis, the development of research areas and authors' influence can be investigated. The current study aimed to identify and analyze the characteristics of 100 highly cited articles on the use of artificial intelligence concerning COVID-19.

Methods

On July 27, 2022, this database was searched using the keywords "artificial intelligence" and "COVID-19" in the topic. After extensive searching, all retrieved articles were sorted by the number of citations, and 100 highly cited articles were included based on the number of citations. The following data were extracted: year of publication, type of study, name of journal, country, number of citations, language, and keywords.

Results

The average number of citations for 100 highly cited articles was 138.54. The top three cited articles with 745, 596, and 549 citations. The top 100 articles were all in English and were published in 2020 and 2021. China was the most prolific country with 19 articles, followed by the United States with 15 articles and India with 10 articles.

Conclusion

The current bibliometric analysis demonstrated the significant growth of the use of artificial intelligence for COVID-19. Using these results, research priorities are more clearly defined, and researchers can focus on hot topics.

Treatment options for patients with severe COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has affected the world for over 3 years. Treatment options have improved substantially during this period, including antiviral drugs, antibody drugs, immune-based agents, and vaccination. While these improvements have reduced mortality rates in patients with COVID-19, some patients still develop severe illness. In this review, we aimed to provide an overview of treatments for patients with severe COVID-19 from study reports and clinical experience. We discussed the treatments from two perspectives: respiratory care and drug treatments. In the respiratory care section, we discussed the usefulness of high-flow nasal cannula therapy and non-invasive ventilation as an alternative to invasive ventilation. In the drug treatments section, we focused on three classes for severe COVID-19 treatment: antiviral drugs, immune-based agents, and anticoagulation therapy. We did not discuss antibody drugs and vaccination, as they are not used for severe COVID-19 treatment.

Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease

Acute respiratory distress syndrome (ARDS) is intricately linked with SARS-CoV-2-associated disease severity and mortality, especially in patients with co-morbidities. Lung tissue injury caused as a consequence of ARDS leads to fluid build-up in the alveolar sacs, which in turn affects oxygen supply from the capillaries. ARDS is a result of a hyperinflammatory, non-specific local immune response (cytokine storm), which is aggravated as the virus evades and meddles with protective anti-viral innate immune responses. Treatment and management of ARDS remain a major challenge, first, because the condition develops as the virus keeps replicating and, therefore, immunomodulatory drugs are required to be used with caution. Second, the hyperinflammatory responses observed during ARDS are quite heterogeneous and dependent on the stage of the disease and the clinical history of the patients. In this review, we present different anti-rheumatic drugs, natural compounds, monoclonal antibodies, and RNA therapeutics and discuss their application in the management of ARDS. We also discuss on the suitability of each of these drug classes at different stages of the disease. In the last section, we discuss the potential applications of advanced computational approaches in identifying reliable drug targets and in screening out credible lead compounds against ARDS.

COVID-19 Therapeutics: An Update on Effective Treatments Against Infection With SARS-CoV-2 Variants

The coronavirus disease 2019 (COVID-19) pandemic is one of the most consequential global health crises in over a century. Since its discovery in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to mutate into different variants and sublineages, rendering previously potent treatments and vaccines ineffective. With significant strides in clinical and pharmaceutical research, different therapeutic strategies continue to be developed. The currently available treatments can be broadly classified based on their potential targets and molecular mechanisms. Antiviral agents function by disrupting different stages of SARS-CoV-2 infection, while immune-based treatments mainly act on the human inflammatory response responsible for disease severity. In this review, we discuss some of the current treatments for COVID-19, their mode of actions, and their efficacy against variants of concern. This review highlights the need to constantly evaluate COVID-19 treatment strategies to protect high risk populations and fill in the gaps left by vaccination.

Review: A Roadmap to Use Nonstructured Data to Discover Multitarget Cancer Therapies

Therapy resistance to single agents has led to the realization that combination therapies could become the cornerstone of cancer treatment. To operationalize the selection of effective and safe multitarget therapies, we propose to integrate chemical and preclinical therapeutic information with clinical efficacy and toxicity data, allowing a new perspective on the drug target landscape. To assess the feasibility of this approach, we evaluated the publicly available chemical, preclinical, and clinical therapeutic data, and we addressed some potential limitations while integrating the data. First, by mapping available structured data from the main biomedical resources, we noticed that there is only a 1.7% overlap between drugs in chemical, preclinical, or clinical databases. Especially, the limited amount of structured data in the clinical domain hinders linking drugs to clinical aspects such as efficacy and side effects. Second, to overcome the abovementioned knowledge gap between the chemical, preclinical, and clinical domain, we suggest information extraction from scientific literature and other unstructured resources through natural language processing models, where BioBERT and PubMedBERT are the current state-of-the-art approaches. Finally, we propose that knowledge graphs can be used to link structured data, scientific literature, and electronic health records, to come to meaningful interpretations. Together, we expect this richer knowledge will lower barriers toward clinical application of personalized combination therapies with high efficacy and limited adverse events.

Outpatient medications associated with protection from COVID-19 hospitalization

The COVID-19 pandemic remains the pre-eminent global health problem, and yet after more than three years there is still no prophylactic agent against the disease aside from vaccines. The objective of this study was to evaluate whether pre-existing, outpatient medications approved by the US Food and Drug Administration (FDA) reduce the risk of hospitalization due to COVID-19. This was a retrospective cohort study of patients from across the United States infected with COVID-19 in the year 2020. The main outcome was adjusted odds of hospitalization for COVID-19 amongst those positive for the infection. Outcomes were adjusted for known risk factors for severe disease. 3,974,272 patients aged 18 or older with a diagnosis of COVID-19 in 2020 met our inclusion criteria and were included in the analysis. Mean age was 50.7 (SD 18). Of this group, 290,348 patients (7.3%) were hospitalized due to COVID-19, similar to the CDC's reported estimate (7.5%). Four drugs showed protective effects against COVID-19 hospitalization: rosuvastatin (aOR 0.91, p = 0.00000024), empagliflozin-metformin (aOR 0.69, p = 0.003), metformin (aOR 0.97, p = 0.017), and enoxaparin (aOR 0.88, p = 0.0048). Several pre-existing medications for outpatient use may reduce severity of disease and protect against COVID-19 hospitalization. Well-designed clinical trials are needed to assess the efficacy of these agents in a therapeutic or prophylactic setting.

Molecular recognition of SARS-CoV-2 spike protein with three essential partners: exploring possible immune escape mechanisms of viral mutants

OBJECTIVE

The COVID-19 epidemic is raging around the world, with the emergence of viral mutant strains such as Delta and Omicron, posing severe challenges to people's health and quality of life. A full understanding life cycle of the virus in host cells helps to reveal inactivation mechanism of antibody and provide inspiration for the development of a new-generation vaccines.

METHODS

In this work, molecular recognitions and conformational changes of SARS-CoV-2 spike protein mutants (i.e., Delta, Mu, and Omicron) and three essential partners (i.e., membrane receptor hACE2, protease TMPRSS2, and antibody C121) both were compared and analyzed using molecular simulations.

RESULTS

Water basin and binding free energy calculations both show that the three mutants possess higher affinity for hACE2 than WT, exhibiting stronger virus transmission. The descending order of cleavage ability by TMPRSS2 is Mu, Delta, Omicron, and WT, which is related to the new S1/S2 cutting site induced by transposition effect. The inefficient utilization of TMPRSS2 by Omicron is consistent with its primary entry into cells via the endosomal pathway. In addition, RBD-directed antibody C121 showed obvious resistance to Omicron, which may have originated from high fluctuation of approaching angles, high flexibility of I472-F490 loop, and reduced binding ability.

CONCLUSIONS

According to the overall characteristics of the three mutants, high infectivity, high immune escape, and low virulence may be the future evolutionary selection of SARS-CoV-2. In a word, this work not only proposes the possible resistance mechanism of SARS-CoV-2 mutants, but also provides theoretical guidance for the subsequent drug design against COVID-19 based on S protein structure.

Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data

With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same.

Design, synthesis, and biological evaluation of novel ruxolitinib and baricitinib analogues for potential use against COVID-19

The coronavirus pandemic known as COVID-19 caused by severe acute respiratory syndrome coronavirus 2, threatens public health worldwide. Approval of COVID-19 vaccines and antiviral drugs have greatly reduced the severe cases and mortality rate. However, the continuous mutations of viruses are challenging the efficacies of vaccines and antiviral drugs. A drug repurposing campaign has identified two JAK1/2 inhibitors ruxolitinib and baricitinib as potential antiviral drugs. Ruxolitinib and baricitinib exert dual antiviral effect by modulation of inflammatory response via JAK1/2 and inhibition of viral entry via AAK1 and GAK. Inspired by this, in an effort to diversify chemical space, three analogues ((R)-8, (S)-8, and 9) of ruxolitinib and baricitinb were made using a scaffold hopping strategy. Compound 9 displayed potent and comparable potencies against AAK1, JAK1, and JAK2 compared to baricitinib. Notably, compound 9 showed better selectivity for AAK1, JAK1, and JAK2 over GAK. Besides, compound 9 displayed good druglikeness according to Lipinski's and Veber's rule. We thereby identified a potential lead compound 9, which might be used for the further development of anti-coronaviral therapy.

A Clinical Insight on New Discovered Molecules and Repurposed Drugs for the Treatment of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began churning out incredulous terror in December 2019. Within several months from its first detection in Wuhan, SARS-CoV-2 spread to the rest of the world through droplet infection, making it a pandemic situation and a healthcare emergency across the globe. The available treatment of COVID-19 was only symptomatic as the disease was new and no approved drug or vaccine was available. Another challenge with COVID-19 was the continuous mutation of the SARS-CoV-2 virus. Some repurposed drugs, such as hydroxychloroquine, chloroquine, and remdesivir, received emergency use authorization in various countries, but their clinical use is compromised with either severe and fatal adverse effects or nonavailability of sufficient clinical data. Molnupiravir was the first molecule approved for the treatment of COVID-19, followed by Paxlovid™, monoclonal antibodies (MAbs), and others. New molecules have variable therapeutic efficacy against different variants or strains of SARS-CoV-2, which require further investigations. The aim of this review is to provide in-depth information on new molecules and repurposed drugs with emphasis on their general description, mechanism of action (MOA), correlates of protection, dose and dosage form, route of administration, clinical trials, regulatory approval, and marketing authorizations.

A review of Janus kinase inhibitors for the treatment of Covid-19 pneumonia

BACKGROUND

In inflamed tissue, immune cells are accumulated, and various intercellular signals are involved in the pathogenesis. Janus kinases (JAKs) are typical tyrosine kinases involved in mediating the signaling of multiple cytokines and growth factors and induce the transcription of molecules related to inflammation or immunity via the transcription factor signal transducers and activators of transcription (STAT). Hence, they have garnered significant interest as a therapeutic target. JAK inhibitors have been evaluated as a major drug for remission induction in the treatment of autoimmune diseases such as rheumatoid arthritis. BODY: Covid-19 infection due to SARS-CoV-2 has caused a pandemic, with approximately 660 million infections and 6.7 million deaths worldwide (January, 2023). The prognosis is poor and the major causes of death are respiratory failure attributed to rapid pneumonia, thromboembolism due to a cytokine storm, and multi-organ failure. As a treatment modality, molecular targeted therapy, such as cytokine-targeting therapy, is attracting attention, in addition to antiviral drugs. Baricitinib, a JAK inhibitor, is used for the treatment of severe pneumonia, in addition to antiviral drugs and glucocorticoids. The mechanism of action of baricitinib includes inhibition of viral receptor-mediated endocytosis, which involves the NF-κB activating kinase (NAK) family, and mediating the anti-cytokine effects via JAK 1/2 inhibition. It improves severe pneumonia and reduces mortality.

CONCLUSION

Thus, the development of molecular targeted drugs with elucidated pathological mechanisms may aid in controlling Covid-19 infection.

Model exploration for discovering COVID-19 targeted traditional Chinese medicine

In terms of treatment, a particularly targeted drug is needed to combat the COVID-19 pandemic. Although there are currently no specific drugs for COVID-19, traditional Chinese medicine(TCM) is clearly effective. It is recommended that through data analysis and mining of TCM cases (expert experience) and population evidence (RCT and cohort studies), core prescriptions for various efficacy can be obtained. Starting from a multidimensional model of regulating immunity, improving inflammation, and protecting multiple organs, this paper constructs a multidimensional model of targeted drug discovery, integrating molecular, cellular, and animal efficacy evaluation. Through functional activity testing, biophysical detection of compound binding to target proteins, multidimensional pharmacodynamic evaluation systems of cells (Vero E6, Vero, Vero81, Huh7, and caca2) and animals (mice infected with the new coronavirus, rhesus macaques, and hamsters), the effectiveness of effective preparations was evaluated, and various efficacy effects including lung moisturizing, dehumidification and detoxification were obtained. Using modern technology, it is now possible to understand how the immune system is controlled, how inflammation is reduced, and how various organs are protected. Complete early drug characterization and finally obtain effective targeted TCM. This article provides a demonstration resource for the development of new drugs specifically for TCM.

Paving New Roads Using Allium sativum as a Repurposed Drug and Analyzing its Antiviral Action Using Artificial Intelligence Technology

CONTEXT

The whole universe is facing a coronavirus catastrophe, and prompt treatment for the health crisis is primarily significant. The primary way to improve health conditions in this battle is to boost our immunity and alter our diet patterns. A common bulb veggie used to flavor cuisine is garlic. Compounds in the plant that are physiologically active are present, contributing to its pharmacological characteristics. Among several food items with nutritional value and immunity improvement, garlic stood predominant and more resourceful natural antibiotic with a broad spectrum of antiviral potency against diverse viruses. However, earlier reports have depicted its efficacy in the treatment of a variety of viral illnesses. Nonetheless, there is no information on its antiviral activities and underlying molecular mechanisms.

OBJECTIVES

The bioactive compounds in garlic include organosulfur (allicin and alliin) and flavonoid (quercetin) compounds. These compounds have shown immunomodulatory effects and inhibited attachment of coronavirus to the angiotensin-converting enzyme 2 (ACE2) receptor and the Mpro of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Further, we have discussed the contradictory impacts of garlic used as a preventive measure against the novel coronavirus.

METHOD

The GC/MS analysis revealed 18 active chemicals, including 17 organosulfur compounds in garlic. Using the molecular docking technique, we report for the first time the inhibitory effect of the under-consideration compounds on the host receptor ACE2 protein in the human body, providing a crucial foundation for understanding individual compound coronavirus resistance on the main protease protein of SARS-CoV-2. Allyl disulfide and allyl trisulfide, which make up the majority of the compounds in garlic, exhibit the most potent activity.

RESULTS

Conventional medicine has proven its efficiency from ancient times. Currently, our article's prime spotlight was on the activity of Allium sativum on the relegation of viral load and further highlighted artificial intelligence technology to study the attachment of the allicin compound to the SARS-CoV-2 receptor to reveal its efficacy.

CONCLUSIONS

The COVID-19 pandemic has triggered interest among researchers to conduct future research on molecular docking with clinical trials before releasing salutary remedies against the deadly malady.

Oral Janus kinase inhibitors for treating hospitalized patients with COVID-19: An updated systematic review and meta-analysis of randomized controlled trials

OBJECTIVES

This study investigated the clinical efficacy and safety of oral Janus kinase inhibitors (JAKis) in the treatment of hospitalized patients with COVID-19.

METHODS

The PubMed, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases were searched for relevant articles written before January 29, 2022. Only randomized controlled trials (RCTs) that assessed the clinical efficacy and safety of oral JAKis in patients with COVID-19 were included.

RESULTS

In the pooled analysis of the 7 RCTs, the all-cause 28-day mortality rate in the study group receiving JAKis was significantly lower than that in the control group (9.4% [183/1941] vs. 10.9% [184/1687], risk ratio [RR] = 0.69, 95% confidence interval [CI], 0.58-0.81, I² = 0%). In addition, the risk of 14-day mortality was in the study group was lower than that in the control group (RR = 0.65, 95% CI, 0.46-0.92, I² = 0%). Finally, the study group and the control group exhibited similar risks of any adverse events (RR = 0.96, 95% CI, 0.89-1.04, I² = 0%).

CONCLUSIONS

Oral JAKis can significantly reduce the risk of death among patients with COVID-19. In addition, JAKis are tolerable for hospitalized patients with COVID-19.

Pharmacological therapies and drug development targeting SARS-CoV-2 infection

The development of therapies for SARS-CoV-2 infection, based on virus biology and pathology, and of large- and small-scale randomized controlled trials, have brought forward several antiviral and immunomodulatory drugs targeting the disease severity. Casirivimab/Imdevimab monoclonal antibodies and convalescent plasma to prevent virus entry, Remdesivir, Molnupiravir, and Paxlovid nucleotide analogs to prevent viral replication, a variety of repurposed JAK-STAT signaling pathway inhibitors, corticosteroids, and recombinant agonists/antagonists of cytokine and interferons have been found to provide clinical benefits in terms of mortality and hospitalization. However, current treatment options face multiple clinical needs, and therefore, in this review, we provide an update on the challenges of the existing therapeutics and highlight drug development strategies for COVID-19 therapy, based on ongoing clinical trials, meta-analyses, and clinical case reports.

Profiles of host immune impairment in Plasmodium and SARS-CoV-2 infections

Over the past two decades, many countries have reported a steady decline in reported cases of malaria, and a few countries, like China, have been declared malaria-free by the World Health Organization. In 2020 the number of deaths from malaria has declined since 2000. The COVID-19 pandemic has adversely affected overall public health efforts and thus it is feasible that there might be a resurgence of malaria. COVID-19 and malaria share some similarities in the immune responses of the patient and these two diseases also share overlapping early symptoms such as fever, headache, nausea, and muscle pain/fatigue. In the absence of early diagnostics, there can be a misdiagnosis of the infection(s) that can pose additional challenges due to delayed treatment. In both SARS-CoV-2 and Plasmodium infections, there is a rapid release of cytokines/chemokines that play a key role in disease pathophysiology. In this review, we have discussed the cytokine/chemokine storm observed during COVID-19 and malaria. We observed that: (1) the severity in malaria and COVID-19 is likely a consequence primarily of an uncontrolled 'cytokine storm'; (2) five pro-inflammatory cytokines (IL-6, IL-10, TNF-α, type I IFN, and IFN-γ) are significantly increased in severe/critically ill patients in both diseases; (3) Plasmodium and SARS-CoV-2 share some similar clinical manifestations and thus may result in fatal consequences if misdiagnosed during onset.

Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

Innate and adaptive immune response in SARS-CoV-2 infection-Current perspectives

Coronavirus disease 2019 (COVID-19) has been a global pandemic, caused by a novel coronavirus strain with strong infectivity, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the in-depth research, the close relationship between COVID-19 and immune system has been dug out. During the infection, macrophages, dendritic cells, natural killer cells, CD8⁺ T cells, Th1, Th17, Tfh cells and effector B cells are all involved in the anti-SARS-CoV-2 responses, however, the dysfunctional immune responses will ultimately lead to the excessive inflammation, acute lung injury, even other organ failure. Thus, a detailed understanding of pertinent immune response during COVID-19 will provide insights in predicting disease outcomes and developing appropriate therapeutic approaches. In this review, we mainly clarify the role of immune cells in COVID-19 and the target-vaccine development and treatment.

Thrombotic storm in coronavirus disease 2019: from underlying mechanisms to its management

Introduction. Coronavirus disease 2019 (COVID-19) identified in December 2019 in Wuhan, China, is associated with high mortality rates worldwide.Hypothesis/Gap Statement. Thrombotic problems, such as coagulopathy, are common in COVID-19 patients. Despite anticoagulation, thrombosis is more common in patients in the intensive care unit and patients with more severe disease. Although the exact mechanisms of coagulopathy in COVID-19 patients are still unclear, studies showed that overactivation of the renin-angiotensin system (RAS), cytokine storm, endothelial damage, formation of neutrophil extracellular traps (NETs), and also extracellular vesicles (EVs) in response to COVID-19 induced inflammation can lead to systemic coagulation and thrombosis.Aim. The management of COVID-19 patients requires the use of basic and readily available laboratory markers, both on admission and during hospitalization. Because it is critical to understand the pathophysiology of COVID-19 induced coagulopathy and treatment strategies, in this review we attempt to explain the underlying mechanism of COVID-19 coagulopathy, its diagnosis, and the associated successful treatment strategies.Conclusion. The exact mechanisms behind COVID-19-related coagulopathy are still unclear, but several studies revealed some mechanisms. More research is needed to determine the best anticoagulant regimen and to study other therapeutic options.

Care of the Seriously Ill Patient with SARS-CoV-2

In late 2019, SARS-CoV-2 caused the greatest global health crisis in a century, impacting all aspects of society. As the COVID-19 pandemic evolved throughout 2020 and 2021, multiple variants emerged, contributing to multiple surges in cases of COVID-19 worldwide. In 2021, highly effective vaccines became available, although the pandemic continues into 2022. There has been tremendous expansion of basic, translational, and clinical knowledge about SARS-CoV-2 and COVID-19 since the pandemic's onset. Treatment options have been rapidly explored, attempting to repurpose preexisting medications in tandem with development and evaluation of novel agents. Care of the seriously ill patient is examined.