Nanotechnology-based Approaches and Investigational Therapeutics against
COVID-19

Rahman, Md. Mominur; Ahmed, Mohiuddin; Islam, Mohammad Touhidul; Khan, Rasel Ahmed; Sultana, Sharifa; Maeesa, Saila Kabir; Hasan, S. Shakir; Hossain, Mohammed Abed; Ferdous, Kazi Sayma; Mathew, Bijo; Rauf, Abdur; Uddin, Sahab

doi:10.2174/1381612827666210701150315

Cited by 13 publications

(8 citation statements)

References 248 publications

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“…Several investigations have suggested that amyloid protein buildup triggers astrogliosis; nevertheless, activated astrocytes produce an A42-immunopositive substance that changes in concentration across the cerebral cortex in AD brains depending on the severity of the disease. Although the precise method by which A42 material collects inside active astrocytes is unknown, it is thought to be owing to either phagocytosis or endocytosis [194][195][196][197][198][199] (Figures 5 and 6).…”

Section: The Interaction Of Neurons and Glia In Alzheimer'smentioning

confidence: 99%

Emerging Role of Neuron-Glia in Neurological Disorders: At a Glance

Rahman

Islam

Yamin

et al. 2022

Oxidative Medicine and Cellular Longevity

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Based on the diverse physiological influence, the impact of glial cells has become much more evident on neurological illnesses, resulting in the origins of many diseases appearing to be more convoluted than previously happened. Since neurological disorders are often random and unknown, hence the construction of animal models is difficult to build, representing a small fraction of people with a gene mutation. As a result, an immediate necessity is grown to work within in vitro techniques for examining these illnesses. As the scientific community recognizes cell-autonomous contributions to a variety of central nervous system illnesses, therapeutic techniques involving stem cells for treating neurological diseases are gaining traction. The use of stem cells derived from a variety of sources is increasingly being used to replace both neuronal and glial tissue. The brain’s energy demands necessitate the reliance of neurons on glial cells in order for it to function properly. Furthermore, glial cells have diverse functions in terms of regulating their own metabolic activities, as well as collaborating with neurons via secreted signaling or guidance molecules, forming a complex network of neuron-glial connections in health and sickness. Emerging data reveals that metabolic changes in glial cells can cause morphological and functional changes in conjunction with neuronal dysfunction under disease situations, highlighting the importance of neuron-glia interactions in the pathophysiology of neurological illnesses. In this context, it is required to improve our understanding of disease mechanisms and create potential novel therapeutics. According to research, synaptic malfunction is one of the features of various mental diseases, and glial cells are acting as key ingredients not only in synapse formation, growth, and plasticity but also in neuroinflammation and synaptic homeostasis which creates critical physiological capacity in the focused sensory system. The goal of this review article is to elaborate state-of-the-art information on a few glial cell types situated in the central nervous system (CNS) and highlight their role in the onset and progression of neurological disorders.

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Section: The Interaction Of Neurons and Glia In Alzheimer'smentioning

confidence: 99%

Emerging Role of Neuron-Glia in Neurological Disorders: At a Glance

Rahman

Islam

Yamin

et al. 2022

Oxidative Medicine and Cellular Longevity

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“…Sildenafil (Viagra), for example, is currently used to treat erectile dysfunction in men but was primarily designed for the treatment of angina [ 40 ]. Several medicines, including anticancer drugs, are yet to be discovered, as their associated target proteins (both primary and non-target) are unknown [ 7 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ]. Furthermore, several therapeutic cancer targets remain “unchecked” by pharmaceutical establishments.…”

Section: Anticancer Drug Target Predictionmentioning

confidence: 99%

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

et al. 2022

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Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

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“…e methodological quality of eligible RCTs was evaluated independently through the Cochrane Handbook for Systematic Reviews of Interventions. Specifically, it includes (1) Selection bias: which describes in detail the method for generating randomly assigned sequences; (2) e implementation of bias: concealment of allocation; (3) Measurement bias: blinding of participants, personnel, and outcome assessors; (4) Follow-up of bias: incomplete data on outcome; (5) Reporting bias: selectively reporting favorable results and hiding unfavorable ones; (6) Other biases: conflict of interest, insufficient sample size, unbalanced baseline. Each entry was assessed as "low risk," "unclear risk," or "high risk" regarding this statement.…”

Section: Risk Of Bias Assessment According To the Cochranementioning

confidence: 99%

“…e remaining 3 studies lacked any description of the allocation hiding method, which was considered to have an unclear bias risk [26,28,36]. e following methods respectively concealed the 10 studies: (1) Randomized block design treatment assignment [24]; (2) the study personnel received a sealed opaque envelope with an assignment to intervention or control group [25]; (3) Use SAS software and interactive randomization tools in REDCap (Research Electronic Data Capture) [27,34]; (4) Random assignment was unstratified and done by local clinical or research staff using a web-based interface with allocation concealment [29]; (5) Treatment assignments were generated using randomly permuted blocks [30,31,33]; (6) e individual recruiting the patient (senior physician responsible for therapeutic intervention) contacted the center by phone after the patient is enrolled.…”

Section: Risk Of Bias Within Studiesmentioning

confidence: 99%

“…When faced with this scenario, we must act swiftly to present therapeutic choices. Despite advances in vaccination and drug research, including nanotechnology-based drug [6]and natural bioactive molecules [7,8], unfortunately, due to the genetic diversity and rapid evolution of this novel coronavirus, there is still no special effective treatment has been found to contain the disease [9][10][11]. General supportive care for novel coronavirus pneumonia is currently the only choice [12].…”

Section: Introductionmentioning

confidence: 99%

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Efficacy and Safety of Convalescence Plasma Therapy in COVID-19 Patients: A Systematic Review and Meta-Analysis

Dai

Tang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Background. The coronavirus disease 2019 (COVID-19) has outbroken into a global pandemic. The death rate for hospital patients varied between 11% and 15%. Although COVID-19 is extremely contagious and has a high fatality rate, the amount of knowledge available in the published literature and public sources is rapidly growing. The efficacy of convalescent plasma (CP) therapy for COVID-19 is controversial. Objective. This meta-analysis was designed to assess the efficacy of CP therapy for COVID-19 through a literature survey. Methods. Until August 30, 2021, a literature search was undertaken in Pubmed, Embase, Web of Science, Cochrane Central Register of Controlling Trials (Central), and China National Knowledge Infrastructure databases. The Risk Ratio (RR) and 95% confidence intervals (CIs) were pooled using a fixed or random effect model in dichotomous data. Mean difference (MD) and 95% confidence intervals (CIs) were pooled using a fixed or random effect model in continuous data. Studies with missing or unsuitable data were presented descriptively in the outcomes. Results. In total, thirteen randomized controlled trials (RCTs) were selected for the present meta-analysis, which included a total of 13232 participants. Our results revealed that the CP group has lower mortality compared to the control group, and there was a statistically significant difference (RR: 0.70, 95% CI: 0.55, 0.89, Z = 2.92, P = 0.004 < 0.01 ); other secondary outcomes such as the shortness of breath symptom improved significantly in CP group (RR:1.48, 95% CI: 1.13, 1.93, Z = 2.85, P = 0.004 < 0.01 ), as well as Interleukin-6 (IL-6) (MD: −4.46, 95% CI: −8.28, −0.63, Z = 2.28, P = 0.02 < 0.05 ) and Ferritin (MD: −447.68, 95% CI: −501.75, −393.6, Z = 16.23, P < 0.00001 ) are reduced significantly in CP group. However, there was no statistically significant change in the ventilator withdrawal rate, imaging results improvement, or days to hospital discharge. There was also no substantial difference in viral nucleic acid negative conversion rate and neutralizing antibody-positive conversion rate, as well as the incidence of adverse reactions. Conclusions. The safety and potential efficacy of convalescent plasma therapy offer a promising treatment strategy for COVID-19. CP therapy can reduce mortality and improve breath and inflammatory cytokines IL-6 and Ferritin in COVID-19 with no significant increase in adverse reactions. However, it does not affect improving virology indicators. In summary, more high-quality clinical trials are needed to verify the conclusion of the present study.

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Nanotechnology-based Approaches and Investigational Therapeutics against COVID-19

Cited by 13 publications

References 248 publications

Emerging Role of Neuron-Glia in Neurological Disorders: At a Glance

Emerging Role of Neuron-Glia in Neurological Disorders: At a Glance

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Efficacy and Safety of Convalescence Plasma Therapy in COVID-19 Patients: A Systematic Review and Meta-Analysis

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