FDMine: a graph mining approach to predict and evaluate food-drug interactions

Food-drug interactions (FDIs) arise when nutritional dietary consumption regulates biochemical mechanisms involved in drug metabolism. Towards characterizing the nature of food’s influence on pharmacological treatment, it is essential to detect all possible FDIs. In this study, we propose FDMine, a novel systematic framework that models the FDI problem as a homogenous graph. In this graph, all nodes representing drug, food and food composition are referenced as chemical structures. This homogenous representation enables us to take advantage of reported drug-drug interactions for accuracy evaluation, especially when accessible ground truth for FDIs is lacking. Our dataset consists of 788 unique approved small molecule drugs with metabolism-related drug-drug interactions (DDIs) and 320 unique food items, composed of 563 unique compounds with 179 health effects. The potential number of interactions is 87,192 and 92,143 when two different versions of the graph referred to as disjoint and joint graphs are considered, respectively. We defined several similarity subnetworks comprising food-drug similarity (FDS), drug-drug similarity (DDS), and food-food similarity (FFS) networks, based on similarity profiles. A unique part of the graph is the encoding of the food composition as a set of nodes and calculating a content contribution score to re-weight the similarity links. To predict new FDI links, we applied the path category-based (path length 2 and 3) and neighborhood-based similarity-based link prediction algorithms. We calculated the precision@top (top 1%, 2%, and 5%) of the newly predicted links, the area under the receiver operating characteristic curve, and precision-recall curve. We have performed three types of evaluations to benchmark results using different types of interactions. The shortest path-based method has achieved a precision 84%, 60% and 40% for the top 1%, 2% and 5% of FDIs identified, respectively. We validated the top FDIs predicted using FDMine to demonstrate its applicability and we relate therapeutic anti-inflammatory effects of food items informed by FDIs. We hypothesize that the proposed framework can be used to gain new insights on FDIs. FDMine is publicly available to support clinicians and researchers.

Are Drug-Free School Zones Effective? Evidence From Matching Schools and School-like Entities

Using a combination of spatial and statistical analysis, this paper focuses on analyzing the effectiveness of drug-free school zones (DFSZ) around K-12 schools in Los Angeles County. A propensity score matching model is employed to match schools and school-like entities to compare the amount of drug crimes in two distinct 1000-foot buffers surrounding them. The model is then compared to a coarsened exact matching model. The average treatment effects (ATE) and average treatment effects on the treated (ATT) are estimated. Our results indicate that there are 2.7 and 1.7 fewer drug crimes and non–marijuana-related drug crimes respectively near schools, as a result of the policy. The total effect of the policy is estimated to reduce drug crime near schools by between 1065 to 1643 fewer incidences per year. Furthermore, we find no significant differences in gang-related drug crimes, gang-related violent crimes, or property crimes as a result of the policy.

Ultra Flexible Nanocarrier for Enhanced the Ocular Delivery of Quercetin in Management of Macular Edema

Quercetin (Que) and its derivatives are naturally taking place phytochemicals with promising bioactive belongings. The antidiabetic, anti-inflammatory, antioxidant, antimicrobial, anti-Alzheimer’s, antiarthritic, cardiovascular, and wound-healing possessions of Que have been extensively investigated, as well as its anticancer commotion against different cancer cell lines has been newly reported. Que and its derivatives are found predominantly in the Western starve yourself, and people might benefit from their defensive effect just by taking them via diets or as a food enhancement. Bioavailability-related drug-delivery systems of Que have also been markedly exploited, and Que nanoparticles become visible as a promising proposal to enhance their bioavailability. The present review aims to make available a brief overview of the therapeutic things, new insights, and forthcoming perspectives of Que. Plants and plant parts are used for its aroma, flavor, or therapeutic properties. There are a number of recompense associated with using plants and plant phytoconstituents as contrasting to pharmaceutical merchandise.

Reversible Cerebral vasoconstriction syndrome associated with the use of sibutramine

The reversible cerebral vasoconstriction syndrome, also known as Call-Fleming syndrome, was initially described in 1988, and is characterized by a clinical syndrome of headaches episodes, generally the “thunderclap” pattern, due to a deregulation of the vascular tonus, leading to segmentary cerebral vasoconstriction and secondary neurological deficits, including those by ischemic or hemorrhagic stroke. In this paper, we present two illustrative cases of this syndrome due to the use of sibutramine. To our knowledge, this situation hasn’t been described as related drug before.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

An atlas of protein turnover rates in mouse tissues

Protein turnover is critical to cellular physiology as well as to the growth and maintenance of tissues. The unique synthesis and degradation rates of each protein help to define tissue phenotype, and knowledge of tissue- and protein-specific half-lives is directly relevant to protein-related drug development as well as the administration of medical therapies. Using stable isotope labeling and mass spectrometry, we determine the in vivo turnover rates of thousands of proteins—including those of the extracellular matrix—in a set of biologically important mouse tissues. We additionally develop a data visualization platform, named ApplE Turnover, that enables facile searching for any protein of interest in a tissue of interest and then displays its half-life, confidence interval, and supporting measurements. This extensive dataset and the corresponding visualization software provide a reference to guide future studies of mammalian protein turnover in response to physiologic perturbation, disease, or therapeutic intervention.

Navigating the US “Green Rush”: anti-money laundering and de-risking implications for banking cannabis-related businesses in Jamaica

Purpose This paper aims to illuminate the diverging approaches to marijuana-related drug enforcement at the federal and state levels in the USA, which have facilitated a boom in the US medical cannabis industry (i.e. the “Green Rush”). It further sheds light on how the USA’ aggressive extraterritorial approach to anti-money laundering (AML) enforcement might simultaneously suppress the banking of cannabis-related businesses in Jamaica due to the lingering fear of de-risking. Design/methodology/approach An international and comparative legal and policy analysis was conducted of the nexus among shifting drug enforcement policies, AML laws and the banking of cannabis-related businesses. Findings This study found that the constitutional relationship between the US federal government and states has created a de facto comparative advantage for the US medical cannabis-related businesses that benefit from limited access to financial services. This was found to pose far-reaching implications for the banking and development of the Jamaican cannabis sector due to the dependence of the country’s financial institutions on correspondent banking relationships with the US banks that are regulated by federal AML statutes. Originality/value To the best of the author’s knowledge, this paper is the first of its kind to examine the extraterritorial regulatory risks to the banking of cannabis-related businesses in Jamaica.

Hypertension-Related Drug Activity Identification Based on Novel Ensemble Method

Hypertension is a chronic disease and major risk factor for cardiovascular and cerebrovascular diseases that often leads to damage to target organs. The prevention and treatment of hypertension is crucially important for human health. In this paper, a novel ensemble method based on a flexible neural tree (FNT) is proposed to identify hypertension-related active compounds. In the ensemble method, the base classifiers are Multi-Grained Cascade Forest (gcForest), support vector machines (SVM), random forest (RF), AdaBoost, decision tree (DT), Gradient Boosting Decision Tree (GBDT), KNN, logical regression, and naïve Bayes (NB). The classification results of nine classifiers are utilized as the input vector of FNT, which is utilized as a nonlinear ensemble method to identify hypertension-related drug compounds. The experiment data are extracted from hypertension-unrelated and hypertension-related compounds collected from the up-to-date literature. The results reveal that our proposed ensemble method performs better than other single classifiers in terms of ROC curve, AUC, TPR, FRP, Precision, Specificity, and F1. Our proposed method is also compared with the averaged and voting ensemble methods. The results reveal that our method could identify hypertension-related compounds more accurately than two classical ensemble methods.

miRNAs as modulators of cholesterol in breast cancer stem cells: an approach to overcome drug resistance in cancer

: It has been postulated that a small number of cancer stem cells (CSCs) buried in tumour mass drive cancer growth and impart cancer drug resistance. However, their eradication has not been achieved so far as the mechanistic understanding around CSCs’ role in cancer development and growth is limited. The cholesterol accumulation and efflux processes have been shown to play an important role in maintaining cell’s integrity and its sensitivity towards drugs, as altered cholesterol pathways contribute to cancer drug resistance. Emerging evidences have indicated miRNAs as regulators of CSCs, and also as regulators of cholesterol pathways in cancer cells, but a link between the two has not been fully established so far. In this review, we have collated key signalling pathways, and published evidences emphasising the involvement of miRNAs and cholesterol in CSCs related drug resistance. Additionally, we have used bioinformatics analysis to identify miRNAs that may modulate cholesterol pathways in CSCs at molecular level to contribute to cancer drug resistance. Our results that two miRNAs (hsa-miR-34a-5p and hsa-miR-373-3p) interact, and bind to two known Breast CSC markers (CD44 and CD24), and mediate expression of several cholesterol-related genes (INSIG2, APOL2, CYP51A1, HDLB, and DHCR7). Furthermore, survival analysis of the breast cancer patients’ gene expression data revealed that higher expression of these genes is associated with poor disease free survival. We therefore propose that targeting these two miRNAs could possibly provide a way to alter cell’s response to drugs via modulating cholesterol pathway in CSCs.