New insight into strategies used to develop long-acting G-CSF biologics for neutropenia therapy

Over the last 20 years, granulocyte colony-stimulating factors (G-CSFs) have become the major therapeutic option for the treatment of patients with neutropenia. Most of the current G-CSFs require daily injections, which are inconvenient and expensive for patients. Increased understanding of G-CSFs’ structure, expression, and mechanism of clearance has been very instrumental in the development of new generations of long-acting G-CSFs with improved efficacy. Several approaches to reducing G-CSF clearance via conjugation techniques have been investigated. PEGylation, glycosylation, polysialylation, or conjugation with immunoglobulins or albumins have successfully increased G-CSFs’ half-lives. Pegfilgrastim (Neulasta) has been successfully approved and marketed for the treatment of patients with neutropenia. The rapidly expanding market for G-CSFs has increased demand for G-CSF biosimilars. Therefore, the importance of this review is to highlight the principle, elimination’s route, half-life, clearance, safety, benefits, and limitations of different strategies and techniques used to increase the half-life of biotherapeutic G-CSFs. Understanding these strategies will allow for a new treatment with more competitive manufacturing and lower unit costs compared with that of Neulasta

Melatonin downregulates the increased hepatic alpha-fetoprotein expression and restores pancreatic beta cells in a streptozotocin-induced diabetic rat model: a clinical, biochemical, immunohistochemical, and descriptive histopathological study

BackgroundDiabetes mellitus (DM) is a chronic metabolic disorder. Hepatopathy is one of the serious effects of DM Melatonin (MT) is a potent endogenous antioxidant that can control insulin output. However, little information is available about the potential association between melatonin and hepatic alpha-fetoprotein expression in diabetes.ObjectiveThis study was conducted to assess the influence of MT on diabetes-related hepatic injuries and to determine how β-cells of the pancreas in diabetic rats respond to MT administration.Materials and methodsForty rats were assigned to four groups at random (ten animals per group). Group I served as a normal control group. Group II was induced with DM, and a single dose of freshly prepared streptozotocin (45 mg/kg body weight) was intraperitoneally injected. In Group III, rats received 10 mg/kg/day of intraperitoneal melatonin (IP MT) intraperitoneally over a period of 4 weeks. In Group IV (DM + MT), following the induction of diabetes, rats received MT (the same as in Group III). Fasting blood sugar, glycosylated hemoglobin (HbA1c), and serum insulin levels were assessed at the end of the experimental period. Serum liver function tests were performed. The pancreas and liver were examined histopathologically and immunohistochemically for insulin and alpha-fetoprotein (AFP) antibodies, respectively.ResultsMT was found to significantly modulate the raised blood glucose, HbA1c, and insulin levels induced by diabetes, as well as the decreased alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Furthermore, MT attenuated diabetic degenerative changes in the pancreas and the hepatic histological structure, increased the β-cell percentage area, and decreased AFP expression in the liver tissue. It attenuated diabetes-induced hepatic injury by restoring pancreatic β-cells; its antioxidant effect also reduced hepatocyte injury.ConclusionCollectively, the present study confirmed the potential benefits of MT in downregulating the increased hepatic alpha-fetoprotein expression and in restoring pancreatic β-cells in a streptozotocin-induced diabetic rat model, suggesting its promising role in the treatment of diabetes

Therapeutic Role of Carotenoids in Blood Cancer: Mechanistic Insights and Therapeutic Potential

Blood cancers are characterized by pathological disorders causing uncontrolled hematological cell division. Various strategies were previously explored for the treatment of blood cancers, including chemotherapy, Car-T therapy, targeting chimeric antigen receptors, and platelets therapy. However, all these therapies pose serious challenges that limit their use in blood cancer therapy, such as poor metabolism. Furthermore, the solubility and stability of anticancer drugs limit efficacy and bio-distribution and cause toxicity. The isolation and purification of natural killer cells during Car-T cell therapy is a major challenge. To cope with these challenges, treatment strategies from phyto-medicine scaffolds have been evaluated for blood cancer treatments. Carotenoids represent a versatile class of phytochemical that offer therapeutic efficacy in the treatment of cancer, and specifically blood cancer. Carotenoids, through various signaling pathways and mechanisms, such as the activation of AMPK, expression of autophagy biochemical markers (p62/LC3-II), activation of Keap1-Nrf2/EpRE/ARE signaaling pathway, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), increased level of reactive oxygen species, cleaved poly (ADP-ribose) polymerase (c-PARP), c-caspase-3, -7, decreased level of Bcl-xL, cycle arrest at the G0/G1 phase, and decreasing STAT3 expression results in apoptosis induction and inhibition of cancer cell proliferation. This review article focuses the therapeutic potential of carotenoids in blood cancers, addressing various mechanisms and signaling pathways that mediate their therapeutic efficacy

Target-Specific Machine Learning Scoring Function Improved Structure-Based Virtual Screening Performance for SARS-CoV-2 Drugs Development

Leveraging machine learning has been shown to improve the accuracy of structure-based virtual screening. Furthermore, a tremendous amount of empirical data is publicly available, which further enhances the performance of the machine learning approach. In this proof-of-concept study, the 3CLpro enzyme of SARS-CoV-2 was used. Structure-based virtual screening relies heavily on scoring functions. It is widely accepted that target-specific scoring functions may perform more effectively than universal scoring functions in real-world drug research and development processes. It would be beneficial to drug discovery to develop a method that can effectively build target-specific scoring functions. In the current study, the bindingDB database was used to retrieve experimental data. Smina was utilized to generate protein-ligand complexes for the extraction of InteractionFingerPrint (IFP) and SimpleInteractionFingerPrint SIFP fingerprints via the open drug discovery tool (oddt). The present study found that randomforestClassifier and randomforestRegressor performed well when used with the above fingerprints along the Molecular ACCess System (MACCS), Extended Connectivity Fingerprint (ECFP4), and ECFP6. It was found that the area under the precision-recall curve was 0.80, which is considered a satisfactory level of accuracy. In addition, our enrichment factor analysis indicated that our trained scoring function ranked molecules correctly compared to smina’s generic scoring function. Further molecular dynamics simulations indicated that the top-ranked molecules identified by our developed scoring function were highly stable in the active site, supporting the validity of our developed process. This research may provide a template for developing target-specific scoring functions against specific enzyme targets

Assessment of RACGAP1 as a Prognostic and Immunological Biomarker in Multiple Human Tumors: A Multiomics Analysis

Several recent studies have pointed out that arc GTPase activating protein 1 (RACGAP1) is a putative oncogene in many human tumors. However, to date, no pan-cancer analysis has been performed to study the different aspects of this gene expression and behavior in tumor tissues. Here, we applied several bioinformatics tools to perform a comprehensive analysis for RACGAP1. First, we assessed the expression of RACGAP1 in several types of human tumors and tried to correlate that with the stage of the tumors analyzed. We then performed a survival analysis to study the correlation between RACGAP1 upregulation in tumors and the clinical outcome. Additionally, we investigated the mutation forms, the correlation with several immune cell infiltration, the phosphorylation status of the interested protein in normal and tumor tissues, and the potential molecular mechanisms of RACGAP1 in cancerous tissue. The results demonstrated that RACGAP1, a highly expressed gene across several types of tumors, correlated with a poor prognosis in several types of human cancers. Moreover, it was found that RACGAP1 affects the tumor immune microenvironment by influencing the infiltration level of several immune cells. Collectively, the current study provides a comprehensive overview of the oncogenic roles of RACGAP1, where our results nominate it as a potential prognostic biomarker and a target for antitumor therapy development

Correlates of memory loss and depression among myocardial infarction patients in Al-Qassim, Saudi Arabia

Background: After myocardial infarction (MI), patients have an elevated risk for depression, which has a negative impact on morbidity and mortality for patients. As depression and memory function are associated, we examined them in the context of one another. Our objectives were to determine the proportion of patients with either depression only, memory loss only, or both depression and memory loss and to examine the correlates with each outcome. Methods: This study was a cohort of 264 patients who had myocardial infarction. Data sources included medical records and phone interviews. Results: The participants’ mean age was 62 ± 12.2 years and mean body mass index was 28.4 ± 5.8 kg/m2. Of the participants, 6.4% had memory loss alone, 23.17% had depression alone, and 6.1% had combined memory loss and depression. Activity level and poor health were significantly associated with depression only (p < 0.05). Poor health was significantly associated with combined memory loss and depression (p < 0.05). Conclusion: Activity level and poor health were identified as correlates of depression as well as combined memory loss and depression. Future studies should aim to improve screening for depression among post-MI patients and develop appropriate interventions to raise the level of activity. Keywords: Depression, Memory loss, Cardiovascular disease, Myocardial infarction, Patient

Electrospun Nanofiber Composites for Drug Delivery: A Review on Current Progresses

A medication&rsquo;s approximate release profile should be sustained in order to generate the desired therapeutic effect. The drug&rsquo;s release site, duration, and rate must all be adjusted to the drug&rsquo;s therapeutic aim. However, when designing drug delivery systems, this may be a considerable hurdle. Electrospinning is a promising method of creating a nanofibrous membrane since it enables drugs to be placed in the nanofiber composite and released over time. Nanofiber composites designed through electrospinning for drug release purposes are commonly constructed of simple structures. This nanofiber composite produces matrices with nanoscale fiber structure, large surface area to volume ratio, and a high porosity with small pore size. The nanofiber composite&rsquo;s large surface area to volume ratio can aid with cell binding and multiplication, drug loading, and mass transfer processes. The nanofiber composite acts as a container for drugs that can be customized to a wide range of drug release kinetics. Drugs may be electrospun after being dissolved or dispersed in the polymer solution, or they can be physically or chemically bound to the nanofiber surface. The composition and internal structure of the nanofibers are crucial for medicine release patterns

Data_Sheet_1_Recognizing novel drugs against Keap1 in Alzheimer’s disease using machine learning grounded computational studies.xlsx

Alzheimer’s disease (AD) is the most common neurodegenerative disorder in the world, affecting an estimated 50 million individuals. The nerve cells become impaired and die due to the formation of amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs). Dementia is one of the most common symptoms seen in people with AD. Genes, lifestyle, mitochondrial dysfunction, oxidative stress, obesity, infections, and head injuries are some of the factors that can contribute to the development and progression of AD. There are just a few FDA-approved treatments without side effects in the market, and their efficacy is restricted due to their narrow target in the etiology of AD. Therefore, our aim is to identify a safe and potent treatment for Alzheimer’s disease. We chose the ursolic acid (UA) and its similar compounds as a compounds’ library. And the ChEMBL database was adopted to obtain the active and inactive chemicals against Keap1. The best Quantitative structure-activity relationship (QSAR) model was created by evaluating standard machine learning techniques, and the best model has the lowest RMSE and greatest R2 (Random Forest Regressor). We chose pIC50 of 6.5 as threshold, where the top five potent medicines (DB06841, DB04310, DB11784, DB12730, and DB12677) with the highest predicted pIC50 (7.091184, 6.900866, 6.800155, 6.768965, and 6.756439) based on QSAR analysis. Furthermore, the top five medicines utilize as ligand molecules were docked in Keap1’s binding region. The structural stability of the nominated medications was then evaluated using molecular dynamics simulations, RMSD, RMSF, Rg, and hydrogen bonding. All models are stable at 20 ns during simulation, with no major fluctuations observed. Finally, the top five medications are shown as prospective inhibitors of Keap1 and are the most promising to battle AD.</p