ABSTRACT
BACKGROUND Erythema nodosum leprosum (ENL) is an acute and systemic inflammatory reaction of leprosy characterised by painful nodules and involvement of various organs. Thalidomide is an immunomodulatory and anti-inflammatory drug currently used to treat this condition. Cereblon (CRBN) protein is the primary target of thalidomide, and it has been pointed out as necessary for the efficacy of this drug in others therapeutics settings. OBJECTIVES In this study, we aimed to evaluate the influence of CRBN gene variants on the dose of thalidomide as well as its adverse effects during treatment of ENL. METHODS A total of 103 ENL patients in treatment with thalidomide were included in this study. DNA samples were obtained from saliva and molecular analysis of CRBN gene were performed to investigate the variants rs1620675, rs1672770 and rs4183. Different genotypes of CRBN variants were evaluated in relation to their influence on the dose of thalidomide and on the occurrence of adverse effects. FINDINGS No association was found between CRBN variants and thalidomide dose variation. However, the genotypes of rs1672770 showed association with gastrointestinal effects (p = 0.040). Moreover, the haplotype DEL/C/T (rs4183/rs1672770/rs1620675) was also associated with gastrointestinal adverse effects (p = 0.015). MAIN CONCLUSIONS Our results show that CRBN variants affect the treatment of ENH with thalidomide, especially on the adverse effects related to the drug.
ABSTRACT
@#Myocardial infarction (MI) in the young adults are more common among the Asians compared to the Caucasians. It is of great interest to investigate the genetic risks that increase the susceptibility of MI in young patients with no family history. We conducted a genetic analysis on a young adult diagnosed with acute MI. The coronary angiogram showed acute complete occlusion of the left anterior descending artery with 40% left ventricular ejection fraction (LVEF). Patient’s DNA was subjected to genotyping using Infinium Asian Screening Array. The genotypes were annotated and associated with risks of cardiovascular diseases catalogued in GWAS database. Ninety-four genetic variants were detected. Patient has more than half of the genetic variants being homozygous risk genotypes for coronary artery and coronary heart diseases. Identifying the potential genetic modifiers associated with MI in young patients is of great interest to help the clinician make informed decisions to implement preventive and personalised medicine for this patient.
ABSTRACT
The aim of this study is to prepare acetaminophen sustained-release tablets by hot melt extrusion 3D printing technology based on the concept of "Quality by Design" (QbD). Firstly, the failure mode and effect analysis (FMEA) was used to determine the critical process parameters (CPPs), then full-factor experimental design was used to analyze the critical quality attributes (CQAs) and to establish the design space. The results showed that the content of plasticizer, the path spacing and the shell numbers are independent variable for the experimental design. The design space was concluded to be plasticizer content: 9%, and the shell number: 3-5, the path spacing: 1.05-1.2 mm. In this study, 3D printing technology was used to prepare acetaminophen sustained-release tablets in accordance with the concept of QbD, which improved the durability of the process and ensured the uniform and controllable quality of the preparation and also provided experimental basis for personalised medicine.
ABSTRACT
Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine.