Research on the use of biodegradable polymers for drug delivery has been ongoing since they were first used as bioresorbable surgical devices in the 1980s. For tissue engineering and drug delivery, biodegradable polymer poly-lactic-co-glycolic acid (PLGA) has shown enormous promise among all biomaterials. PLGA are a family of FDA-approved biodegradable polymers that are physically strong and highly biocompatible and have been extensively studied as delivery vehicles of drugs, proteins, and macromolecules such as DNA and RNA. PLGA has a wide range of erosion times and mechanical properties that can be modified. Many innovative platforms have been widely studied and created for the development of methods for the controlled delivery of PLGA. In this paper, the various manufacturing processes and characteristics that impact their breakdown and drug release are explored in depth. Besides different PLGA-based nanoparticles, preclinical and clinical applications for different diseases and the PLGA platform types and their scale-up issues will be discussed.

Cardiovascular diseases (CVDs) are a common cause of heart failure globally. The need to explore possible ways to tackle the disease necessitated this study. The study designed a machine learning model for cardiovascular disease risk prediction in accordance with a dataset that contains 11 features which may be used to forecast the disease. The dataset from Kaggle on cardiovascular disease includes approximately 70,000 patient records that were used to determine the outcome. Compared to the UCI dataset, the Kaggle dataset has many more training and validation records. Models created using neural networks, random forests, Bayesian networks, C5.0, and QUEST were compared for this dataset. On training and testing data sets, the results acquired a high accuracy (99.1 percent), which is significantly superior to previous methods. Ahead‐of‐time detection and diagnosis of cardiac disease, as well as better treatment outcomes, are strong possibilities for the suggested prediction model. Additionally, it may help patients better manage their illness or life forms in order to increase their chances of recovery/survival. The result showed greater accuracy and promising signs that machine‐learning algorithms can indeed assist in early identification of the disease and improvement of the treatment outcome.

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory disease, i.e., breast cancer, non-small cell lung cancer, gout, rheumatoid arthritis, and liver cirrhosis. Therefore, NEK7 is a promising target for drug development against various cancer malignancies. The combination of drug repurposing and structure-based virtual screening of large libraries of compounds has dramatically improved the development of anticancer drugs. The current study focused on the virtual screening of 1200 benzene sulphonamide derivatives retrieved from the PubChem database by selecting and docking validation of the crystal structure of NEK7 protein (PDB ID: 2WQN). The compounds library was subjected to virtual screening using Auto Dock Vina. The binding energies of screened compounds were compared to standard Dabrafenib. In particular, compound 762 exhibited excellent binding energy of −42.67 kJ/mol, better than Dabrafenib (−33.89 kJ/mol). Selected drug candidates showed a reactive profile that was comparable to standard Dabrafenib. To characterize the stability of protein–ligand complexes, molecular dynamic simulations were performed, providing insight into the molecular interactions. The NEK7–Dabrafenib complex showed stability throughout the simulated trajectory. In addition, binding affinities, pIC50, and ADMET profiles of drug candidates were predicted using deep learning models. Deep learning models predicted the binding affinity of compound 762 best among all derivatives, which supports the findings of virtual screening. These findings suggest that top hits can serve as potential inhibitors of NEK7. Moreover, it is recommended to explore the inhibitory potential of identified hits compounds through in-vitro and in-vivo approaches.

Allium sativum L., also known as garlic, is a perennial plant widely used as a spice and also considered a medicinal herb since antiquity. The aim of this study was to determine by gas chromatography–mass spectrometry (GC–MS) the chemical profile fingerprint of the essential oil (EO) of one accession of Peruvian A. sativum (garlic), to evaluate its antioxidant activity and an in- silico study on NADPH oxidase activity of the volatile phytoconstituents. The antioxidant activity was tested using DPPH and β-carotene assays. An in-silico study was carried out on NADPH oxidase (PDB ID: 2CDU), as was ADMET prediction. The results indicated that diallyl trisulfide (44.21%) is the major component of the EO, followed by diallyl disulfide (22.08%), allyl methyl trisulfide (9.72%), 2-vinyl-4H-1,3-dithiine (4.78%), and α-bisabolol (3.32%). Furthermore, the EO showed antioxidant activity against DPPH radical (IC₅₀ = 124.60 ± 2.3 µg/mL) and β-carotene bleaching (IC₅₀ = 328.51 ± 2.0). The best docking score on NADPH oxidase corresponds to α-bisabolol (ΔG = −10.62 kcal/mol), followed by 5-methyl-1,2,3,4-tetrathiane (ΔG = −9.33 kcal/mol). Additionally, the volatile components could be linked to the observed antioxidant activity, leading to potential inhibitors of NADPH oxidase.

Coronavirus disease 2019 (COVID-19) is a global infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Approximately 15% of severe cases require an intensive care unit (ICU) admission and mechanical ventilation due to development of acute respiratory distress syndrome (ARDS). Tetracyclines (TCs) are a group of bacteriostatic antibiotics, like tetracycline, minocycline, and doxycycline, effective against aerobic and anaerobic bacteria as well as Gram-positive and Gram-negative bacteria. Based on available evidences, TCs may be effective against coronaviruses and thus useful to treat COVID-19. Thus, this review aims to provide a brief overview on the uses of TCs for COVID-19 management. SARS-CoV-2 and other coronaviruses depend mainly on the matrix metalloproteinases (MMPs) for their proliferation, cell adhesion, and infiltration. The anti-inflammatory mechanisms of TCs are linked to different pathways. Briefly, TCs inhibit mitochondrial cytochrome c and caspase pathway with improvement of lymphopenia in early COVID-19. Specifically, minocycline is effective in reducing COVID-19–related complications, through attenuation of cytokine storm as apparent by reduction of interleukin (IL)-6, IL-1, and tumor necrosis factor (TNF)-α. Different clinical trials recommend the replacement of azithromycin by minocycline in the management of COVID-19 patients at high risk due to two main reasons: 1) minocycline does not prolong the QT interval and even inhibits ischemia-induced arrhythmia; 2) minocycline displays synergistic effect with chloroquine against SARS-CoV-2. Taken together, the data presented here show that TCs, mainly doxycycline or minocycline, may be potential partners in COVID-19 management, derived pneumonia, and related complications, such as acute lung injury (ALI) and ARDS.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by severe cytokine storm syndrome following inflammation. SARS-CoV-2 directly interacts with angiotensin-converting enzyme 2 (ACE-2) receptors in the human body. Complementary therapies that impact on expression of IgE and IgG antibodies, including administration of bee venom (BV), have efficacy in the management of arthritis, and Parkinson's disease. A recent epidemiological study in China showed that local beekeepers have a level of immunity against SARS-CoV-2 with and without previous exposure to virus. BV anti-inflammatory properties are associated with melittin and phospholipase A2 (PLA2), both of which show activity against enveloped and non-enveloped viruses, including H1N1 and HIV, with activity mediated through antagonist activity against interleukin-6 (IL-6), IL-8, interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α). Melittin is associated with the underexpression of proinflammatory cytokines, including nuclear factor-kappa B (NF-κB), extracellular signal-regulated kinases (ERK1/2), and protein kinase Akt. BV therapy also involves group III secretory phospholipase A₂in the management of respiratory and neurological diseases. BV activation of the cellular and humoral immune systems should be explored for the application of complementary medicine for the management of SARS-CoV-2 infections. BV “vaccination” is used to immunize against cytomegalovirus and can suppress metastases through the PLA2 and phosphatidylinositol-(3,4)-bisphosphate pathways. That BV shows efficacy for HIV and H1NI offers opportunity as a candidate for complementary therapy for protection against SARS-CoV-2.