Vol 30, No 34 (2024)
- Year: 2024
- Articles: 6
- URL: https://vestnikugrasu.org/1381-6128/issue/view/10186
Immunology, Inflammation & Allergy
Dental Caries: Unveiling the State-of-the-art Insights and Crafting Hypotheses for Oral Health
Abstract
:The pathophysiological understanding of dental caries explains that the primary factor responsible is linked to an imbalance in microbial composition within the oral cavity, stemming from both artificial and natural sources. Streptococcus mutans (S. mutans) is the most accountable and prevalent pathogen for caries development among the diverse pool. S. mutans, an acidogenic bacterium, lowers oral pH through the metabolic conversion of dietary sugar into organic acids, leading to enamel demineralization and dental caries. Numerous antibacterial interventions have been employed in the past to address this issue. However, adopting such an approach poses the risk of exacerbating concerns related to Antimicrobial Resistance (AMR) and long-term oral cytotoxicity. In response to this, a sustainable strategy is suggested, involving the utilization of L-Arginine (L-Arg) as a probiotic nutrient supplement for non-pathogenic microbes. It will help in creating a natural competitive environment against the pathogenic microbes responsible for initiating dental caries. The hypothesis involves utilizing a combination of a nutrient supplement and the repurposed drug Piceatannol, specifically for its anti-biofilm properties. This combination synergistically improves the effectiveness of the therapy by converting the complex microbial biofilm into a planktonic state.
2667-2670
Prescription Precision: A Comprehensive Review of Intelligent Prescription Systems
Abstract
:Intelligent Prescription Systems (IPS) represent a promising frontier in healthcare, offering the potential to optimize medication selection, dosing, and monitoring tailored to individual patient needs. This comprehensive review explores the current landscape of IPS, encompassing various technological approaches, applications, benefits, and challenges. IPS leverages advanced computational algorithms, machine learning techniques, and big data analytics to analyze patient-specific factors, such as medical history, genetic makeup, biomarkers, and lifestyle variables. By integrating this information with evidence-based guidelines, clinical decision support systems, and real-time patient data, IPS generates personalized treatment recommendations that enhance therapeutic outcomes while minimizing adverse effects and drug interactions. Key components of IPS include predictive modeling, drug-drug interaction detection, adverse event prediction, dose optimization, and medication adherence monitoring. These systems offer clinicians invaluable decision-support tools to navigate the complexities of medication management, particularly in the context of polypharmacy and chronic disease management. While IPS holds immense promise for improving patient care and reducing healthcare costs, several challenges must be addressed. These include data privacy and security concerns, interoperability issues, integration with existing electronic health record systems, and clinician adoption barriers. Additionally, the regulatory landscape surrounding IPS requires clarification to ensure compliance with evolving healthcare regulations. Despite these challenges, the rapid advancements in artificial intelligence, data analytics, and digital health technologies are driving the continued evolution and adoption of IPS. As precision medicine gains momentum, IPS is poised to play a central role in revolutionizing medication management, ultimately leading to more effective, personalized, and patient-centric healthcare delivery.
2671-2684
Recent Research Trends against Skin Carcinoma - An Overview
Abstract
2685-2700
Huangqi Guizhi Wuwu Decoction Improves Inflammatory Factor Levels in Chemotherapy-induced Peripheral Neuropathy by Regulating the Arachidonic Acid Metabolic Pathway
Abstract
Background:Chemotherapy-induced Peripheral Neuropathy (CIPN) is a common complication that arises from the use of anticancer drugs. Huangqi Guizhi Wuwu Decoction (HGWWD) is an effective classic prescription for treating CIPN; however, the mechanism of the activity is not entirely understood.
Objective:This study aimed to investigate the remedial effects and mechanisms of HGWWD on CIPN.
Methods:Changes in behavioral, biochemical, histopathological, and biomarker indices were used to evaluate the efficacy of HGWWD treatment. Ultra-high-performance liquid chromatography/mass spectrometry combined with the pattern recognition method was used to screen biomarkers and metabolic pathways related to CIPN. The results of pathway analyses were verified by protein blotting experiments.
Results:A total of 29 potential biomarkers were identified and 13 metabolic pathways were found to be involved in CIPN. In addition HGWWD reversed the levels of 19 biomarkers. Prostaglandin H2 and 17α,21-dihydroxypregnenolone were targeted as core biomarkers.
Conclusion:This study provides scientific evidence to support the finding that HGWWD mainly inhibits the inflammatory response during CIPN by regulating arachidonic acid metabolism.
2701-2717
Lycium barbarum Ameliorates Oral Mucositis via HIF and TNF Pathways: A Network Pharmacology Approach
Abstract
Background:Oral mucositis is the most common and troublesome complication for cancer patients receiving radiotherapy or chemotherapy. Recent research has shown that Lycium barbarum, an important economic crop widely grown in China, has epithelial protective effects in several other organs. However, it is unknown whether or not Lycium barbarum can exert a beneficial effect on oral mucositis. Network pharmacology has been suggested to be applied in "multi-component-multi-target" functional food studies. The purpose of this study is to evaluate the effect of Lycium barbarum on oral mucositis through network pharmacology, molecular docking and experimental validation.
Aims:To explore the biological effects and molecular mechanisms of Lycium barbarum in the treatment of oral mucositis through network pharmacology and molecular docking combined with experimental validation.
Methods:Based on network pharmacology methods, we collected the active components and related targets of Lycium barbarum from public databases, as well as the targets related to oral mucositis. We mapped protein- protein interaction (PPI) networks, performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, and constructed a 'components-disease-targets' network and 'components- pathways-targets' network using Cytoscape to further analyse the intrinsic molecular mechanisms of Lycium barbarum against oral mucositis. The affinity and stability predictions were performed using molecular docking strategies, and experiments were conducted to demonstrate the biological effects and possible mechanisms of Lycium barbarum against oral mucositis.
Results:A network was established between 49 components and 61 OM targets. The main active compounds were quercetin, beta-carotene, palmatine, and cyanin. The predicted core targets were IL-6, RELA, TP53, TNF, IL10, CTNNB1, AKT1, CDKN1A, HIF1A and MYC. The enrichment analysis predicted that the therapeutic effect was mainly through the regulation of inflammation, apoptosis, and hypoxia response with the involvement of TNF and HIF pathways. Molecular docking results showed that key components bind well to the core targets. In both chemically and radiation-induced OM models, Lycium barbarum significantly promoted healing and reduced inflammation. The experimental verification showed Lycium barbarum targeted the key genes (IL-6, RELA, TP53, TNF, IL10, CTNNB1, AKT1, CDKN1A, HIF1A, and MYC) through regulating the HIF and TNF signaling pathways, which were validated using the RT-qPCR, immunofluorescence staining and western blotting assays.
Conclusion:In conclusion, the present study systematically demonstrated the possible therapeutic effects and mechanisms of Lycium barbarum on oral mucositis through network pharmacology analysis and experimental validation. The results showed that Lycium barbarum could promote healing and reduce the inflammatory response through TNF and HIF signaling pathways.
2718-2735
Weight, CYP3A5 Genotype, and Voriconazole Co-administration Influence Tacrolimus Initial Dosage in Pediatric Lung Transplantation Recipients with Low Hematocrit based on a Simulation Model
Abstract
Objective:The method of administering the initial doses of tacrolimus in recipients of pediatric lung transplantation, especially in patients with low hematocrit, is not clear. The present study aims to explore whether weight, CYP3A5 genotype, and voriconazole co-administration influence tacrolimus initial dosage in recipients of pediatric lung transplantation with low hematocrit based on safety and efficacy using a simulation model.
Methods:The present study utilized the tacrolimus population pharmacokinetic model, which was employed in lung transplantation recipients with low hematocrit.
Results:For pediatric lung transplantation recipients not carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-13, 13-19, 19-22, 22-35, 35-38, and 38-40 kg are 0.03, 0.04, 0.05, 0.06, 0.07, and 0.08 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and without voriconazole, the recommended tacrolimus doses for weights of 10-18, 18-30, and 30-40 kg are 0.06, 0.08, 0.11 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients not carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20 and 20-40 kg are 0.02 and 0.03 mg/kg/day, which are split into two doses, respectively. For pediatric lung transplantation recipients carrying CYP3A5*1 and with voriconazole, the recommended tacrolimus doses for weights of 10-20, 20-33, and 33-40 kg are 0.03, 0.04, and 0.05 mg/kg/day, which are split into two doses, respectively.
Conclusion:The present study is the first to recommend the initial dosages of tacrolimus in recipients of pediatric lung transplantation with low hematocrit using a simulation model.
2736-2748