Schisandra chinensis in Liver Disease: Exploring the Mechanisms and Therapeutic Promise of an Ancient Chinese Botanical

Archives of Pharmacology and Therapeutics, Journal Year: 2024, Volume and Issue: 6(1), P. 27 - 33

Published: Jan. 1, 2024

Background: Schisandra chinensis is a traditional Chinese herbal medicine that has been used for centuries liver health. The active lignans in Schisandra, including schisandrin and gomisins, have exhibited anti-inflammatory, antioxidant, hepatoprotective properties preliminary studies. With rising rates of chronic diseases globally, there interest the potential therapeutic role Schisandra. Purpose: To comprehensively review current evidence treating injury disease synthesize implications future human research. Main body: extracts decreased inflammatory cytokines oxidative stress markers increased endogenous antioxidant activity animal models, suggesting utility mitigating inflammation damage. Additional preclinical studies demonstrated attenuated enzyme levels, necrosis, fibrosis progression chemical-induced hepatotoxicity with treatment. Enhanced cytochrome P450 activity, glutathione production, glycogen synthesis were also observed, improving detoxification regeneration capacity. Small trials hepatitis nonalcoholic fatty showed improved enzymes symptoms supplementation but limited quality sample size. Conclusion: biologically relevant mechanisms warrant further research on its as phytotherapy. Well-designed, large-scale clinical are needed to establish efficacy safety applications.

Language: Английский

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Transforming Screening, Risk Stratification, and Treatment Optimization in Chronic Liver Disease Through Data Science and translational Innovation

The Indonesian Journal of Gastroenterology Hepatology and Digestive Endoscopy, Journal Year: 2024, Volume and Issue: 25(1), P. 53 - 62

Published: May 16, 2024

Background: Chronic liver diseases continue to face challenges in prognosis, treatment selection, disease mechanisms, screening, and therapeutic optimization. Promising innovations could address these gaps through data integration novel analytic approaches.Main Body: MAPS-CRAFITY integrating clinical variables, AFP, CT/MRI findings, transformer modeling of RFA improve HCC outcome prediction guide management. Analyses revealing IL21R as a PBC susceptibility gene implicating dysfunctional VWF processing portal hypertension deliver mechanistic insights. Quantifying childhood MAFLD informs screening needs, while supporting use G6PD deficient donors enables transplantation access expansion risk stratification. Updating Baveno criteria enhances an prognostic score identifies optimal candidates maximize efficacy.Conclusion: Recent research leverages diverse types, genetics, imaging, machine learning develop integrated predictive systems that allow more personalized therapy selection. Elucidating molecular pathways provides targets biomarkers. Evidence-based models facilitate delivering tailored interventions. Optimization current modalities validation patient selection improves real-world effectiveness. Multifaceted modern approaches promise unmet needs transform hepatology care.

Language: Английский

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Type 1 diabetes mellitus: retrospect and prospect

Bulletin of the National Research Centre/Bulletin of the National Research Center, Journal Year: 2024, Volume and Issue: 48(1)

Published: April 19, 2024

Abstract Background Type 1 diabetes (T1D) is an autoimmune disease leading to destruction of insulin-producing pancreatic beta cells. Both genetic and environmental factors contribute pathogenesis. The incidence T1D increasing worldwide, with significant geographic ethnic variations. Patients present symptoms hyperglycemia complications. Main body In T1D, autoreactive T cells autoantibodies destroy cells, causing insulin deficiency. Exogenous therapy essential but cannot replicate normal physiology. Management requires intensive lifestyle education on diet, exercise, glucose monitoring avoiding complications, in addition insulin. Novel therapies like immunotherapy, cell transplantation, artificial pancreas devices AI algorithms aim improve care. Strategies for reversing involve combination immunotherapies block autoimmunity regenerate via stem or xenotransplantation. Conclusion While type remains challenging, ongoing research provides hope. Elucidating individualized mechanisms translating findings into precision prevention treatment approaches are critical improving long-term outcomes. Innovative multi-targeted may fundamentally change the trajectory T1D.

Language: Английский

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Realizing the Promise of Artificial Intelligence in Hepatocellular Carcinoma through Opportunities and Recommendations for Responsible Translation

Jurnal Online Informatika, Journal Year: 2024, Volume and Issue: 9(1), P. 70 - 79

Published: April 26, 2024

This study aims to provide an overview of the current state-of-the-art applications artificial intelligence (AI) and machine learning in management hepatocellular carcinoma (HCC), explore future directions for continued progress this emerging field. is a comprehensive literature review that synthesizes recent findings advancements application AI techniques across various aspects HCC care, including screening early detection, diagnosis staging, prognostic modeling, treatment planning, interventional guidance, monitoring response. The draws upon wide range published research studies, focusing on integration with diverse data sources, such as medical imaging, clinical data, genomics, other multimodal information. results demonstrate AI-based systems have shown promise improving accuracy efficiency screening, diagnosis, tumor characterization compared traditional methods. Machine models integrating clinical, genomic outperformed conventional staging predicting survival recurrence risk. recommendation potential optimize personalized therapy selection, while augmented reality can guide procedures real-time. Moreover, longitudinal may enhance assessment response monitoring. Despite these promising findings, highlights need rigorous multicenter prospective validation standardized datasets, thoughtful consideration ethical implications before widespread implementation technologies management.

Language: Английский

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Optical Insights into Fibrotic Livers: Applications of Near-Infrared Spectroscopy and Machine Learning

Archives of Gastroenterology Research, Journal Year: 2024, Volume and Issue: 5(1), P. 1 - 10

Published: Jan. 1, 2024

Background: Liver fibrosis staging is critical for patient selection and management prior to transplantation, but biopsy invasive serum biomarkers lack accuracy. Near-infrared spectroscopy (NIRS) an emerging non-invasive technology that can detect liver via changes in tissue composition. Machine learning (ML) enables analysis of NIRS data diagnostic modeling. Purpose: To review the potential NIRS-ML approaches rapid, point-of-care detection, including technological principles, promising applications, current limitations, future directions. Main body abstract: leverages unique near-infrared absorbance patterns reflecting collagen accumulation, lipid reduction, other chemical alterations fibrotic liver. Handheld/hyperspectral systems acquire spectroscopic minutes. Multiple human studies correlate with histological scores. ML techniques like partial least squares regression, neural networks, support vector machines, random forests analyze spectra develop optimized algorithms. Initial models differentiate mild versus advanced stage cirrhosis high accuracy, outperforming traditional biomarkers. Recent advances include smartphone-based scanning, cloud computing, integrated user-friendly platforms. However, further large validation trials, standardization, assessment confounding factors, improved methodology, cost-effectiveness are required before widespread clinical implementation. Conclusion: With ongoing research address remaining barriers, hold great disruptive quantification fibrosis, optimizing transplant surgery planning management.

Language: Английский

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Integrated Metabolomics and Lipidomics Analysis Reveals the Mechanism Behind the Action of Chiglitazar on the Protection Against Sepsis-Induced Acute Lung Injury

Metabolites, Journal Year: 2025, Volume and Issue: 15(5), P. 290 - 290

Published: April 25, 2025

Background: Sepsis-induced acute lung injury (SALI) is a critical clinical challenge with high mortality. Metabolic dysregulation drives SALI pathogenesis, disrupting function and energy metabolism. Despite proven benefits, metabolic restoration underused in sepsis. This study explores chiglitazar’s role balancing metabolism to protect against SALI. Methods: The protective effects of chiglitazar CLP rats were demonstrated by the survival curve, histological analysis, immunohistochemical analysis tissue. Metabolomic lipidomic analyses tissue samples using gas chromatography–mass spectrometry (GC-MS) liquid (LC-MS) performed evaluate shifts induced surgery pretreatment. mRNA protein levels underlying targets directing nicotinamide adenine dinucleotide (NAD+) triglyceride synthesis analyzed qPCR Western blotting. To validate mechanism which protected SALI, SIRT1 inhibitor EX-527 was applied human normal epithelial (BEAS-2B) cells another batch observe its reverse effect action. Results: Chiglitazar pretreatment significantly restored NAD+ improved dysregulated lipid enhancing triglycerides (TGs) suppressing accumulated fatty acids (FAs). modulation mediated associated upregulations SIRT1/PGC-1α/PPARα/GPAT3 axis. Co-treatment LPS-stimulated BEAS-2B inhibited on aforementioned signaling pathways worsened injury, respectively. Conclusions: alleviates restoring TG synthesis, highlighting as promising therapeutic strategy management

Language: Английский

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Bending the Curve Through Innovations to Overcome Persistent Obstacles in HIV Prevention and Treatment

Journal of AIDS and HIV Treatment, Journal Year: 2024, Volume and Issue: 6(1), P. 44 - 53

Published: Jan. 1, 2024

Background: HIV/AIDS remains a major global public health challenge despite significant progress in treatment. New infections and HIV-related deaths persist, fueled by disparities prevention care access. Purpose: This review synthesizes recent advances across key domains - from vaccine development to novel treatments omics approaches – that collectively hold promise for ending the pandemic. Main body: Multiple innovative HIV platforms are now early-phase trials, including mRNA vaccines as well conserved epitope mosaic constructs broader immunogenicity. Long-acting injectable antiretrovirals represent milestone treatment, while gene editing techniques offer future curative potential. Leveraging multi-omics data through genomics, transcriptomics, proteomics, metabolomics provides systems-level insights into viral persistence new therapeutic opportunities. The gut microbiome is increasingly recognized mediator of progression, spurring research probiotic/prebiotic supplementation fecal transplantation. Across these domains, integration artificial intelligence machine learning will likely accelerate discovery. Conclusion: Despite past setbacks, cure effort has renewed momentum. Translating emerging tools like long-acting profiling clinical application could bend pandemic’s trajectory. Innovation must be paired with ensuring equitable access maximize impact.

Language: Английский

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