生物分析与生物医学杂志

Precision genome editing holds immense promise for the treatment of genetic disorders, but efficient in vivo delivery of CRISPR-Cas9 components remains a formidable challenge. This article explores the development and application of targeted nanoparticles as a delivery platform for the CRISPR-Cas9 system. We discuss the design, optimization, and in vivo testing of nanoparticles tailored to specific cell types and tissues. The integration of nanotechnology and genome editing not only enhances the precision and efficiency of genome modifications but also paves the way for potential therapeutic breakthroughs.

The study of single-cell heterogeneity is a fundamental aspect of understanding complex biological systems. This article explores the transformative capabilities of quantitative Imaging Flow Cytometry (qIFC) in unraveling the intricacies of single-cell analysis. We discuss the principles, instrumentation, and data analysis techniques associated with qIFC, emphasizing its capacity to provide quantitative and spatial information at the single-cell level. This technology enables comprehensive investigations into cell populations, revealing hidden phenotypic diversity, dynamic responses, and subcellular features. The integration of qIFC is poised to advance our knowledge of cellular biology, immunology, and disease mechanisms.

The human gut microbiota plays a pivotal role in drug metabolism, impacting drug efficacy and safety. This article delves into the burgeoning field of gut microbiota-mediated drug metabolism and its implications for personalized medicine. We explore the mechanisms underlying microbiotamediated transformations of pharmaceuticals, their influence on drug bioavailability, and their potential to modulate individual drug responses. By elucidating the interplay between gut microbes and drugs, we uncover new avenues for tailoring drug therapies to individual patients, ultimately enhancing treatment outcomes.

High-throughput proteomic profiling has become a pivotal tool in identifying potential biomarkers for various diseases. This article reviews recent advancements in proteomic technologies and their application in biomarker discovery. We discuss the challenges associated with data analysis and integration and explore strategies to enhance the sensitivity and specificity of biomarker identification. By harnessing the power of mass spectrometry, machine learning, and bioinformatics, researchers are making significant strides towards revolutionizing disease diagnosis and personalized treatment strategies.

Beta thalassemia is a disorder in which the body is unable to synthesise haemoglobin beta subunit due to deleterious mutations in the β-globin gene that results in underproduction of Adult Haemoglobin (HbA). Fetal Haemoglobin (HbF), which is composed of two α and two γ subunits, has been identified as a potential substitute for HbA with great clinical significance in β-thalassaemic patients. However, in the developmental stages, the expression of HbF is gradually minimized and overtaken by HbA. Our research found that the investigation of blood expression and its relationship to DEGs may aid in elucidating the role of these DEGs in beta thalassemia progression, and an RNA sequencing study indicated that the β globin gene is down regulated. There are 200 genes that are differently expressed in β thalassemia patients compared to healthy controls, as well as two key genes. KLF1 and MDM2 are two potential target genes for beta thalassemia patients that could be employed as diagnostic indicators. The differentially expressed genes include genes involved in heme biosynthesis, heme binding, erythrocyte homeostasis, iron ion binding, erythrocyte differentiation, gas transport and response to oxygen species metabolic processes, and other cellular processes. However, functional studies are needed to confirm their proposed relevance in beta thalassemia.