Current Drug Targets - Volume 25, Issue 6, 2024

Gallbladder cancer (GBC) is an uncommon condition in which malignant (cancer) cells are detected in gallbladder tissue. Cancer is often triggered when normal cells turn malignant and begin to spread. Cancer can also be caused by genetic anomalies that result in uncontrolled cell proliferation and tumor development. MicroRNAs (also known as miRNAs or miRs) are a group of small, endogenous, non-coding RNAs of 19-23 nucleotides in length, which play a key role in post-transcriptional gene regulation. These miRNAs serve as negative gene regulators by supervising target genes and regulating biological processes, including cell proliferation, migration, invasion, and apoptosis. Cancer development and progression relate to aberrant miRNA expression. This review demonstrated the implication of various genetic factors and microRNAs in developing and regulating GBC. This suggests the potential of genes and RNAs as the diagnostic, prognostic, and therapeutic targets in gallbladder cancer.

Obesity is a growing global health problem, leading to various chronic diseases. Despite standard treatment options, the prevalence of obesity continues to rise, emphasizing the need for new drugs. in vitro methods of drug discovery research provide a time and cost-saving platform to identify new antiobesity drugs. The review covers various aspects of obesity and drug discovery research using in vitro models. Besides discussing causes, diagnosis, prevention, and treatment, the review focuses on the advantages and limitations of in vitro studies and exhaustively covers models based on enzymes and cell lines from different animal species and humans. In contrast to conventional in vivo animal investigations, in vitro preclinical tests using enzyme- and cell line-based assays provide several advantages in development of antiobesity drugs. These methods are quick, affordable, and provide high-throughput screening. They can also yield insightful information about drug-target interactions, modes of action, and toxicity profiles. By shedding light on the factors that lead to obesity, in vitro tests can also present a chance for personalized therapy. Technology will continue to evolve, leading to the creation of more precise and trustworthy in vitro assays, which will become more and more crucial in the search for novel antiobesity medications.

Epidermolysis bullosa (EB) is an inherited skin disease representing a spectrum of rare genetic disorders. These conditions share the common trait that causes fragile skin, resulting in the development of blisters and erosions. The inheritance follows an autosomal pattern, and the array of clinical presentations leads to significant physical suffering, considerable morbidity, and mortality. Despite EB having no cure, effectively managing EB remains an exceptional challenge due to its rarity and complexity, occasionally casting a profound impact on the lives of affected individuals. Considering that EB management requires a multidisciplinary approach, this sometimes worsens the condition of patients with EB due to inappropriate handling. Thus, more appropriate and precise treatment management of EB is essentially needed. Advanced technology in medicine and health comes into the bioinformatics era. Including treatment for skin diseases, omics-based approaches aim to evaluate and handle better disease management and treatment. In this work, we review several approaches regarding the implementation of omics-based technology, including genetics, pathogenic mutation, skin microbiomics, and metagenomics analysis for EB. In addition, we highlight recent updates on the potential of metagenomics analysis in precision medicine for EB.

Background: Tablet formulation could be revolutionized by the integration of modern technology and established pharmaceutical sciences. The pharmaceutical sector can develop tablet formulations that are not only more efficient and stable but also patient-friendly by utilizing artificial intelligence (AI), machine learning (ML), and materials science. Objectives: The primary objective of this review is to explore the advancements in tablet technology, focusing on the integration of modern technologies like artificial intelligence (AI), machine learning (ML), and materials science to enhance the efficiency, cost-effectiveness, and quality of tablet formulation processes. Methods: This review delves into the utilization of AI and ML techniques within pharmaceutical research and development. The review also discusses various ML methodologies employed, including artificial neural networks, an ensemble of regression trees, support vector machines, and multivariate data analysis techniques. Results: Recent studies showcased in this review demonstrate the feasibility and effectiveness of ML approaches in pharmaceutical research. The application of AI and ML in pharmaceutical research has shown promising results, offering a potential avenue for significant improvements in the product development process. Conclusion: The integration of nanotechnology, AI, ML, and materials science with traditional pharmaceutical sciences presents a remarkable opportunity for enhancing tablet formulation processes. This review collectively underscores the transformative role that AI and ML can play in advancing pharmaceutical research and development, ultimately leading to more efficient, reliable and patient-centric tablet formulations.

Background: Hedyotis diffusa Willd. (HDW) is a common anticancer herbal medicine in China, and its therapeutic effectiveness has been demonstrated in a range of cancer patients. There is no consensus about the therapeutic targets and molecular mechanisms of HDW, which contains many active ingredients. Aim: To clarify the mechanism of HDW for esophageal adenocarcinoma (EAC), we utilized network pharmacology and weighted gene co-expression network analysis methods (WGCNA). Methods: The gene modules that were linked with the clinical features of EAC were obtained through the WGCNA method. Then, the potential target genes were retrieved through the network pharmacology method in order to determine the targets of the active components. After enrichment analysis, a variety of signaling pathways with significant ratios of target genes were found, including regulation of trans-synaptic signaling, neuroactive ligand-receptor interaction and modulation of chemical synaptic transmission. By means of protein-protein interaction (PPI) network analysis, we have successfully identified the hub genes, which were AR, CNR1, GRIK1, MAPK10, MAPT, PGR and PIK3R1. Result: Our study employed molecular docking simulations to evaluate the binding affinity of the active components with the hub gene. The identified active anticancer constituents in HDW are scopoletol, quercetin, ferulic acid, coumarin, and trans-4-methoxycinnamyl alcohol. Conclusion: Our findings shed light on the molecular underpinnings of HDW in the treatment of EAC and hold great promise for the identification of potential HDW compounds and biomarkers for EAC therapy.