Current pharmaceutical biotechnology最新文献

Tumor microenvironment (TME) plays a particularly important role in the pathogenesis and drug resistance of lung cancer. This article provides a framework that allows us to view lung cancer through the lens of cancer stem cells (CSCs) and angiogenesis, with the aim of enhancing both clinical and laboratory insights. It critically examines the bidirectional interactions between CSCs and other components of the TME, highlighting their combined contributions to tumor aggressiveness and angiogenic processes. We discuss the mechanisms by which CSCs influence angiogenesis, including the release of growth factors and cytokines, while also emphasizing how angiogenic factors, in turn, modulate CSC behavior and help maintain a microenvironment that supports tumor growth. Potential biomarkers and therapeutic targets- such as CD133, ALDH1, and VEGF-are explored as valuable not only for disease management but also for the development of targeted therapies for lung cancer. This article ultimately provides a foundation for researchers to further investigate these interconnected processes and for clinicians to consider therapeutic strategies when managing patients with lung cancer. Given the multifaceted nature of lung cancer biology and the numerous molecules involved, we advocate for a panel-centered approach in both research and clinical management, while underscoring the importance of carefully considering toxicity risks and variability in molecular expression.

Diabetes mellitus (DM) is a group of metabolic disorders characterised by insufficient insulin secretion and reduced insulin sensitivity in target tissues, leading to a range of metabolic abnormalities. DM has a profound global impact and exerts detrimental effects on patients' health. Traditional Chinese Medicines (TCMs), characterised by dialectical treatment principles and a holistic therapeutic philosophy, have been shown to play an important role in the management and alleviation of DM. In this review, we provide a concise overview of recent applications of TCMs in DM, summarise the underlying mechanisms, and discuss both the limitations of current practices and future prospects in this field. Numerous non-clinical and clinical studies have demonstrated the significant therapeutic advantages of TCMs in improving and alleviating DM. However, limitations persist, including variability among TCM formulations, the scarcity of high-quality randomised clinical trials, potential adverse effects and drug interactions, and challenges in standardisation. Establishing rigorous and scientifically sound quality standards, conducting larger-scale multicentre randomised controlled trials, and further elucidating the underlying mechanisms may offer effective solutions to these challenges and support the broader application of TCMs in DM management.

Acute-on-chronic liver failure (ACLF) is a life-threatening syndrome characterized by the sudden deterioration of liver function in patients with chronic liver disease, frequently progressing to multi-organ failure. Despite advances in supportive therapies, the underlying pathogenesis remains poorly understood, and effective pharmacological treatments are still lacking. Bile acids (BAs) and the intestinal microbiota interact dynamically, and disruptions in their homeostasis are closely linked to the progression of ACLF. This review summarizes current understanding of bile acid metabolism and gut microbiota dysbiosis in ACLF, explores the reciprocal regulatory mechanisms between them, and discusses emerging therapeutic strategies targeting this axis. The goal is to identify novel approaches that may improve clinical outcomes for patients with ACLF.

This 2024 year-in-review article provides a comprehensive overview of the most cited articles published in Current Pharmaceutical Biotechnology (CPB) during the year across six key thematic areas: cancer, nanotechnology, antimicrobial agents, drug delivery, neurodegenerative diseases, and herbal and natural products. A total of twenty-nine high-impact studies have been selected and examined, each contributing meaningful advancements to the respective fields. The review highlights the application of phytochemicals in oncology, the versatility of nanomaterials in targeted therapies, innovations in antimicrobial strategies against resistant pathogens, intelligent drug delivery platforms, novel therapeutic approaches for neurodegenerative disorders, and the evolving role of botanicals in modern biopharmaceuticals. Through a narrative synthesis, the review illustrates how CPB has served as a vital platform for translational research, bridging molecular science and clinical innovation.

Background: STIM- and Orai-mediated store operated calcium entry (SOCE) is a ubiquitous Ca2+ signaling process, crucial for the proper function of immune, muscle and neuronal systems. To treat SOCE-related disorder or diseases of these systems, and to mechanistically dissect activation and function of SOCE, specific SOCE inhibitors are needed. However, strategies for developing new SOCE modifiers are still limited.

Methodology: In this study, we identified a novel SOCE inhibitor named 2PHDO from a small pool of Chinese herbal extracts used for treating psoriasis. It could block SOCE and SOCEmediated NFAT translocation in multiple types of cells with a half inhibitory concentration around 1 μM. At this concentration, 2PHDO was specific for SOCE. Mechanistically, 2PHDO didn’t affect the activation of STIM1 or its physical coupling with Orai1. Rather, 2PHDO inhibited SOCE via its actions on Orai1.

Results: 2PHDO may serve as a good template for developing new medicines aiming to treat SOCE related diseases.

Conclusion: Overall, we proved the feasibility of screening and identification of novel SOCE inhibitors from active monomers of Chinese herbal medicine.

Introduction: Diabetes is a chronic metabolic disease that affects individuals of all ages. Therefore, there is an urgent need to develop novel therapeutic agents from natural sources. In this context, Hibiscus cannabinus was selected for the present investigation. The study aimed to evaluate the hypoglycemic, hypolipidemic, and antioxidant activities of Hibiscus cannabinus extract in a streptozotocin-induced diabetic model in Wistar rats.

Methods: An in vivo study was planned to evaluate the hypoglycaemic, hypolipidemic, and antioxidant effects activities of HCE. Thirty-six male Wistar rats were randomly divided into six groups, and diabetes was induced by a single acute intraperitoneal injection of STZ. Animals were treated orally with HCE at doses of 100, 200, and 400 mg/kg b.wt., or with Glibenclamide (5 mg/kg b.wt.), along with a normal control group. The rats were monitored for body weight, feed intake, blood glucose and insulin levels, lipid profile, and markers of lipid peroxidation and antioxidant activity.

Results: HCE showed a significant reduction in blood glucose levels, improved lipid profile, enhanced antioxidant enzyme activity, and decreased lipid peroxidation in diabetic rats in a dosedependent manner compared with the control group. Notably, the 400 mg/kg b.wt. HCE group exhibited efficacy comparable to that of the Glibenclamide treatment group.

Discussion: HCE showed activity in streptozotocin-induced diabetic rats, indicating its potential as a natural therapeutic agent. Further investigation into its mechanisms and clinical applicability for managing diabetes-related complications is needed to support its pharmaceutical use.

Conclusion: HCE extract exhibited strong antidiabetic, lipid-lowering, and antioxidant activities in STZ-induced diabetic rats.

Colorectal cancer is among the most prevalent and lethal malignancies worldwide. Its initially asymptomatic nature contributes to a high incidence of metastatic cases. Although predominantly diagnosed in older adults, the incidence among younger populations is rising at an alarming rate. Historically, treatment has relied on antineoplastic agents such as 5-fluorouracil, irinotecan, and oxaliplatin. While these agents remain in use, their effectiveness is limited, particularly in metastatic disease, with modest improvements in overall survival and progressionfree survival. Moreover, their low target specificity results in significant systemic toxicity. This underscores the urgent need formore selective and less toxic therapeutic strategies, such as monoclonal antibodies. Monoclonal antibodies targeting Vascular Endothelial Growth Factor (VEGF), Epidermal Growth Factor Receptor (EGFR), and immune checkpoints have become integral to the management of metastatic colorectal cancer. Notable examples include bevacizumab (anti-VEGF), cetuximab and panitumumab (anti-EGFR), and the immune checkpoint inhibitors pembrolizumab, nivolumab, and ipilimumab. Their clinical success especially when guided by molecular tumour profiling highlights their contribution to improved patient outcomes. In addition, other targeted therapies distinct from monoclonal antibodies are currently under investigation.

Introduction: The rise of Multidrug-Resistant (MDR) bacterial infections and the limited efficacy of conventional antibiotics have underscored the urgent need for innovative antimicrobial therapies. Antimicrobial Peptides (AMPs) represent a promising class of agents due to their broad-spectrum activity; however, their clinical application is often hindered by cytotoxicity and poor stability. This study aimed to develop and evaluate a novel ultrashort AMP-antibiotic conjugate, UP5-C-Levo, with improved antimicrobial efficacy and safety.

Methods: UP5-C-Levo was synthesized by covalently linking the ultrashort peptide UP5 to the antibiotic levofloxacin. The antimicrobial activity of the conjugate was assessed against MDR Gram-positive and Gram-negative bacteria using Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) assays. Antibiofilm efficacy was tested on Staphylococcus aureus biofilms. Cytotoxicity was evaluated via hemolysis of human erythrocytes and MTT assays on MDCK cells. Scanning Electron Microscopy (SEM) was employed to investigate bacterial membrane disruption.

Results: UP5-C-Levo exhibited potent antimicrobial activity, with MIC values ranging from 12.5 to 25 μM across all tested MDR strains. It significantly reduced biofilm biomass, achieving nearcomplete eradication of S. aureus biofilms. Hemolysis and cytotoxicity assays indicated minimal toxicity to human cells. SEM imaging revealed extensive bacterial membrane disruption, suggesting a dual mechanism of action.

Discussion: The conjugation of UP5 with levofloxacin resulted in a synergistic antimicrobial agent with enhanced efficacy and low cytotoxicity. The ability of UP5-C-Levo to disrupt bacterial membranes and eradicate biofilms addresses two major challenges in infection treatment. These findings align with current strategies aimed at overcoming antibiotic resistance through AMPbased drug design.

Conclusion: UP5-C-Levo is a promising therapeutic candidate for the treatment of MDR and biofilm-associated infections. Its strong antibacterial and antibiofilm activity, combined with a favorable safety profile, supports further preclinical development and potential clinical translation.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that has a distinct histopathological profile, heterogeneity, and poor prognosis, with a limited number of available therapies. Artificial intelligence (AI), machine learning (ML), deep learning (DL), and radiomics have fundamentally improved the accuracy of diagnosis, prognosis, and therapy in TNBC. Recent AI advances in TNBC include transformer-graph convolution models like NACNet (90% accuracy, 96% sensitivity, AUC 0.82) for NAC response prediction, and longitudinal deep learning radiomics models achieving AUCs of 0.924 (training) and 0.875 (testing) by integrating ultrasound and clinical data. Hybrid CNN-Bi-LSTM-EfficientNet mammography models have reached 99.2% accuracy, while ConvNeXtBase ultrasound models achieved 89% accuracy and F1-scores of 0.81 for TNBC subtype classification. AI is also being paired with nanotechnology to create intelligent drug-delivery systems, reduce toxicity, predict drug resistance, and integrate tumor microenvironment, immune biomarkers, and radiomics for personalized therapy. AI-based imaging models have shown excellent accuracy in terms of diagnostics and subtyping of TNBC, with AUC values reaching up to 0.97. In the same context, DL-based models based on whole-slide histopathology images and radiomics predicted response to neoadjuvant therapy with AUC values as high as 0.96. AI-derived immune infiltrating cell (IIC) signatures, radiomics-derived omics models, and spatial tumor microenvironment (sTME) traits have been demonstrated to be prognostics for disease-free survival (DFS) and overall survival (OS) as well. Various AI-based prognostic models, including the AI-based TLS-TB index nomogram, clinic-radiomics signatures, and Digi-sTILs scores, have C-index values from 0.65 to 0.76, supporting moderate to strong prognostic classification. Incorporating AI-derived immune signatures, tumor microenvironment, and radiomics with clinical parameters facilitates personalized planning for risk stratification, prognostic prediction, and selection of treatment options for management of TNBC compared to the traditional TNM staging alone. However, the generalizability of AI-derived models continued to be tested due to variations in training datasets and the biological heterogeneity of TNBC, which challenged their implementation and clinical applicability. Therefore, multi-center validation and prospective clinical trials will be the need of the hour to fully integrate AI as a tool in the standard practice of precision oncology and personalized management of TNBC.

Invasive Fungal Infections (IFIs) are a growing global health concern, particularly among immunocompromised individuals and critically ill patients. Diagnosis remains challenging due to nonspecific symptoms, low sensitivity of conventional methods, and the emergence of antifungal resistance. This review outlines the diagnostic limitations of microscopy, culture, and serological assays while exploring the potential of molecular tools. Emphasis is placed on integrated diagnostic pathways, resistance gene detection, point-of-care assays, and Artificial Intelligence (AI) enhanced imaging for fungal infections. Diagnostic challenges in special populations are also addressed. The role of diagnostics in antifungal stewardship and infection control is discussed with forward-looking perspectives. By integrating conventional approaches with emerging technologies, this review highlights the need for a more precise and responsive diagnostic era in IFIs. Timely and accurate diagnosis of IFIs is vital for improving outcomes. The integration of traditional and emerging diagnostic tools, including pan-fungal platforms and resistance profiling, is key to advancing fungal disease management globally, particularly in resource- limited settings.