Current pharmaceutical biotechnology最新文献

Introduction: Generalized anxiety disorder (GAD) is a prevalent and intricate mental disorder that significantly impairs the quality of life of patients. Currently, the exact etiology of GAD remains incompletely understood. Consequently, the discovery of novel drug targets for GAD is highly important.

Methods: We obtained cis-eQTL data of druggable genes from the eQTLGen Consortium as the exposure data and GWAS data of GAD from the FinnGen Database as the outcome. The impact of druggable genes on GAD was simulated through Mendelian randomization analysis. Subsequently, a colocalization analysis was conducted to calculate the probability of shared pathogenic variants between the cis-eQTLs of druggable genes and GAD. To further validate our findings, a summary data-based Mendelian randomization (SMR) analysis was carried out.

Results: Mendelian randomization (MR) analysis identified 24 druggable genes with potential causal relationships, among which genetically predicted increased KDM5A levels were associated with a higher risk of GAD (OR=1.0991, 95% CI: 1.0021-1.2056, P=0.0451), suggesting a potential role of KDM5A gene expression in the pathogenesis of GAD. The GAD and KDM5A genes might share a causal variant. The SMR further verified the accuracy of the KDM5A gene.

Discussion: MR analysis identified KDM5A as a promising therapeutic target for GAD, with additional potential from genes, like MERTK and PPT1. However, the effectiveness of the relevant drug targets requires further validation.

Conclusion: This study suggested that the KDM5A gene might be a potential therapeutic target for treating GAD, providing a direction for future drug development in GAD patients.

Introduction: Ganoderma lucidum is considered a medicinal mushroom, as it primarily improves gut health by modulating the gut microbiota. As an abundant source of bioactive metabolites, antioxidants, and industrial enzymes, mushrooms make significant contributions to functional foods, nutrition, and pharmaceuticals. Polysaccharides derived from G. lucidum exhibit prebiotic potential, promoting the growth and activity of beneficial gut microorganisms.

Methods: This review examines the impact of white rot basidiomycetes metabolites on colorectal cancer treatment. We have compiled and analyzed data from PubMed, Google Scholar, and ResearchGate, presenting a comprehensive report with a table for clear understanding.

Results: Evidence from in vivo and in vitro studies demonstrates that G. lucidum has potential as a gastrointestinal cancer inhibitor by inducing pro-apoptosis, autophagy, G0/G1 cell cycle arrest, and immunomodulation.

Discussion: Bioactive metabolites and polysaccharides have prebiotic potential, enhancing the growth and activity of beneficial gut microorganisms that may lower the risk of gastrointestinal cancers by modifying gut bacteria. The prebiotic properties may boost immunity, reduce inflammation, and strengthen intestinal barrier integrity.

Conclusion: The current review explores the therapeutic potential of G. lucidum and other medicinal mushrooms as dietary supplements, focusing on their impact on the gut microbiome and gastrointestinal cancer.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a global health concern. In recent years, the gut microbiota, often referred to as the body's "second genome," has been recognized as playing a crucial role in the pathogenesis of MASLD. PubMed was searched for articles published in the last decade using keywords like "MASLD," "NAFLD," "gut microbiota," "FXR," and "Trace elements." The progress of the latest NAFLD clinical trial was also reviewed from the Chinese Clinical Trial Registry, organized by clinical phase. In the development of MASLD, the gut microbiota not only participates in regulating host gene expression but also exerts a core influence on immune function and affects the liver's reparative capabilities. Furthermore, the metabolic products of the gut microbiota are involved in the occurrence and development of liver diseases through the gut-liver axis. A diet high in fat can trigger metabolic inflammation, changes in gut microbiota, and abnormalities in metabolic products, all of which may initiate inflammatory responses. The emerging strategies for treating MASLD are surprising. Clinical trial information for chemical drugs was obtained from the Chinese platform for registration and disclosure of drug clinical trials, and it was found that in the current drug development, some drugs have advanced to Phase III clinical trials. The diversity of gut bacteria among individuals and the impact of microbial composition beyond bacteria should not be overlooked. Whether drug therapy combined with dietary patterns is more effective than monotherapy remains to be seen.

Introduction: This study aimed to develop a local drug delivery system using pterostilbene (PTS) flexible nanoliposomes (FNL) to overcome its limitations, such as poor water solubility and instability under light and oxygen. The research focused on optimizing deformability and transdermal delivery using dipotassium glycyrrhizinate and a single-chain surfactant as membrane softeners.

Methods: The encapsulation process and formulation of PTS FNL were systematically optimized through single-factor and orthogonal experiments. The physicochemical properties, stability, and transdermal performance of the optimized FNL were evaluated using dynamic light scattering, transmission electron microscopy (TEM), Turbiscan stability analysis, and in vitro/in vivo permeation studies.

Results: The optimized PTS FNL exhibited high encapsulation efficiency (96.49 ± 0.7%), a particle size of (60.11 ± 0.54 nm), PDI (0.237), a zeta potential of (-10.16 ± 0.54 mV), and good stability at 4°C and 25°C for three months. TEM confirmed spherical morphology, while in vitro studies demonstrated superior skin retention and prolonged permeation compared to PTS nanoliposomes (NL) and GTCC solutions. In vivo tests on human volunteers revealed that 0.4% PTS FNL cream significantly improved skin elasticity and chromaticity over 28 days without adverse effects.

Discussion: The enhanced deformability of PTS FNL contributed to its improved transdermal delivery, making it a promising candidate for cosmetic applications. The study highlights the effectiveness of membrane softeners in optimizing liposomal formulations, though long-term stability under varied conditions warrants further investigation.

Conclusion: The developed PTS FNL system significantly enhances skin permeation and stability, demonstrating great potential for cosmetic use in anti-aging and skin-brightening formulations. This approach provides a viable strategy for improving the delivery of poorly soluble active ingredients.

Introduction: The current pharmaceutical industry has increasingly adopted artificial intelligence (AI), integrating it across the entire industrial chain. While AI improves efficiency and reduces costs, it also faces challenges. This study explores both the technological evolution and contemporary innovation hotspots of AI in pharmacy.

Methods: Methods: This study adopts a fusion analysis of multi-source data, constructing a bidimensional analytical framework based on patented inventions (1990-2024) and research articles (2020-2024) as research objects. The study applies the Latent Dirichlet Allocation (LDA) topic model to analyze the evolution of patent topics and employs CiteSpace to construct keyword knowledge graphs from research articles. By integrating patent and article data to define technical labels, the study identifies research hotspots from the perspective of the pharmaceutical life cycle, enabling cross-validation from both scientific and technical dimensions.

Results: The number of AI-related patents in the pharmaceutical field has grown rapidly over the past five years. Technological topics exhibit a distinct evolutionary trend. Research hotspots span the entire pharmaceutical life cycle, from drug development to clinical delivery. Additionally, potential directions for future technological development have been identified.

Discussion: Research hotspots in the application of AI in pharmaceuticals include target identification, virtual screening, drug delivery, clinical trials, and pharmacovigilance. Precision medicine and explainable AI (XAI)-driven pharmacy modeling are expected to emerge as key directions for future technological development.

Conclusion: AI has already reshaped the pharmaceutical industry through applications across all stages of the pharmaceutical life cycle. It is poised to attract growing research attention and drive innovative applications in the years ahead.

The rising prevalence of Multidrug-Resistant (MDR) Acinetobacter baumannii, particularly in hospital environments, has become a global health concern due to its capacity to cause severe infections and its resistance to conventional antibiotics. This article reviews the detection methods for the resistant genes, focusing on carbapenem-resistant A. baumannii (CRAB), where various phenotypic, molecular, and advanced diagnostic technologies, with particular attention to Fluorescence Resonance Energy Transfer (FRET) assays based on Quantum Dots (QDs) and Graphene Oxide (GO), are reviewed. These nanoparticle-based FRET assays show promising potential for rapid, sensitive, and multiplex detection of antibiotic resistance genes, offering significant improvements over traditional methods. In particular, integrating QDs and GO as donor-acceptor pairs in FRET allows real-time detection and high specificity of a key determinant of carbapenem resistance in A. baumannii. Adopting these advanced diagnostic tools could revolutionise infection control and management, providing timely and accurate diagnostics that are crucial in clinical settings.

Introduction: FLRCC is a rare renal carcinoma subtype caused by FH mutations, categorized into hereditary (germline mutations) and sporadic (somatic mutations) forms. These forms are clinically and pathologically similar, complicating differentiation without genetic testing. The aim of this study is to investigate the clinicopathological and molecular genetic differences between hereditary and sporadic fumarate hydratase (FH)-deficient leiomyomatosis and renal cell carcinoma (FLRCC) to improve diagnostic accuracy and clinical management.

Method: A retrospective analysis of 14 FLRCC patients was conducted(May 2020-August 2023). Immunohistochemistry (FH, 2SC, p16), HE staining, and next-generation sequencing (NGS) of tumor tissues and blood leukocytes were performed.

Results: The 14 patients with FH-deficient leiomyoma were 25-54 years old, with a mean age of 36.21 ± 8.16. 78.5% (11/14) had clinical symptoms and multiple, large-sized fibroids (median maximum volume was 75 mm). Patients with leiomyoma and FH deficiency were divided into hereditary and sporadic FLRCC based on FH gene sequencing. Patients with HLRCC had an earlier onset, and the serum tumor marker CA125 was more significant. Moreover, tumor tissues from patients with hereditary and sporadic FH-deficient LRCC differed in immunohistochemical and HE staining characteristics, including more positive p16 and greater susceptibility to invasion and metastasis in patients with HLRCC, as well as malignant proliferation in patients with sporadic FH-deficient LRCC.

Discussion: Although limited by sample size, our preliminary findings indicated subtle differences in the age of onset, as well as immunohistochemical and histopathological features of hereditary and sporadic FH-deficient LRCC, facilitating the understanding and clinical diagnosis of FLRCC.

Conclusion: In clinical diagnosis, all information should be fully integrated, and a comprehensive judgment should be made to make a correct pathological diagnosis and provide targeted treatment for patients with an FH gene mutation.

Introduction: Breast cancer and depression are both serious diseases that significantly impact women's physical health. The molecular mechanisms underlying their comorbidity remain elusive. This study aims to identify key genes and the molecular mechanisms associated with the comorbidity of breast cancer and depression using bioinformatics analysis methods.

Methods: Data files for breast cancer and depression were obtained from the TCGA database and the NCBI GEO public database, respectively. The random survival forest algorithm was utilized to identify key genes co-expressed in both breast cancer and depression. Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) were employed to predict biological functions and signaling pathway differences influenced by these key genes in both diseases. The R package "RcisTarget" was utilized to predict molecular transcriptional regulatory relationships of the key genes. The CIBERSORT algorithm was applied for immune function correlation analysis of comorbid key genes. The differential expression of key genes was validated in breast cancer tissue and depression blood by qPCR.

Results: The TCGA database provided original mRNA expression data for breast cancer, while the NCBI GEO public database offered the dataset GSE58430 related to depression. Through functional enrichment and random survival forest analysis, CCNB1, MLPH, PSME1, and RACGAP1 were identified as four key genes. The specific signaling pathways、strong correlation with immune cells, and the potential molecular mechanisms of these four key genes were analyzed in breast cancer and depression. Their expression levels were verified in blood and tissue samples.

Discussion: This study discovered the comorbidity genes of breast cancer and depression, providing a certain direction for the prevention and treatment of these two diseases. At present, breast cancer and depression are serious diseases that affect women's physical and mental health. The connection between the two is not very clear. This study proposes that these two diseases have comorbidity genes. The risk population of the disease can be detected early through testing, so as to intervene early and improve prognosis. However, the sample size of the database analyzed in this study was relatively small, and the sample size and methods for clinical validation were insufficient. Further in-depth research will be conducted in the future.

Conclusion: This study identified CCNB1, MLPH, PSME1, and RACGAP1 as key genes associated with the comorbidity of breast cancer and depression.

A defining characteristic of tumor cells is their preferential reliance on aerobic glycolysis for lactate production, even under oxygen-sufficient conditions - the well-known Warburg effect. Recent advances have revealed lactate to be far more than a metabolic waste product, establishing its role as a versatile signaling molecule with multiple functions in cancer progression. Acting simultaneously as a pro-inflammatory mediator, hypoxia surrogate, tumor burden indicator, and metastasis predictor, lactate exerts profound and wide-ranging effects on immune cell function within the tumor microenvironment (TME). The immunomodulatory properties of lactate create a profoundly immunosuppressive milieu that facilitates tumor immune evasion. It achieves this through coordinated suppression of antitumor immune effectors, including natural killer cells, dendritic cells, and cytotoxic T lymphocytes, while simultaneously enhancing the immunosuppressive functions of regulatory T cells, tumorassociated macrophages, and endothelial cells. This dual mechanism of action promotes tumor progression and metastasis through multiple pathways. The groundbreaking discovery of lysine lactylation (Kla) has further expanded our understanding of lactate's biological roles, revealing a direct molecular connection between tumor metabolism and epigenetic regulation. This review provides a comprehensive synthesis of current knowledge regarding lactate-mediated immune modulation in the TME, examines recent advances in our understanding of lactate-dependent tumor biology, and evaluates emerging therapeutic strategies that target lactate metabolism. By integrating these perspectives, we aim to offer both fundamental insights and practical guidance for the development of novel anticancer therapies that target metabolic-epigenetic crosstalk.

Medicinal herbs and herbal formulations have garnered increasing attention in skincare and anti-aging due to their versatility, safety, and potential effectiveness. Korean medicinal herbs and herbal formulations have a rich history in traditional Asian medicine, and they are increasingly gaining recognition as anti-aging and skincare treatments. Korean herbal medicine, known as Hanbang, draws from various natural ingredients, like ginseng, green tea, and licorice, to create herbal formulations passed down for centuries. These formulations are recognized for their potential to promote healthy, youthful skin. Ingredients such as ginseng and green tea possess antioxidant properties that combat free radicals and reduce oxidative stress on the skin, preventing premature aging. Korean skincare treatments often incorporate these herbal formulations, emphasizing natural ingredients and techniques such as herbal masks, teas, and acupuncture to enhance skin vitality and combat aging signs. Understanding the role of major bioactive compounds in Korean herbal medicine is essential for bridging traditional practices with modern dermatological science. Because of the increasing global demand for natural, effective, and safe skincare products, it is increasingly important for natural agents' mechanisms, efficacy, and commercial value to be systematically evaluated and documented. This review aims at fulfilling this knowledge gap as well as providing directions for future research and product development. Considering all the beneficial effects of Korean medicinal herbs, the current review discusses major bioactive compounds present in these herbs and formulations used in anti-aging and skincare treatments, along with their extraction procedure, commercialization, and patents. The review highlights the potential benefits of Korean herbal medicine in promoting youthful, radiant skin through natural and time-honored practices.