Search Results (491)

This review explores the therapeutic promise of natural compounds in modulating 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), a key enzyme in cholesterol synthesis. HMGCR dysregulation is implicated in dyslipidemia, cardiovascular disease, and cancer, conditions linked to oxidative stress. While statins inhibit HMGCR, their side effects necessitate exploring alternatives. The review highlights various natural compounds—flavonoids, phenolic acids, stilbenes, and herbal formulations—with HMGCR-modulating and antioxidant capabilities. In vitro and in vivo studies suggest these compounds offer a promising avenue for treating HMGCR-related conditions. Synergistic effects are observed when combining natural products with statins, hinting at combination therapies that could lower statin dosages and reduce adverse effects. Natural HMGCR modulators hold therapeutic promise but face hurdles like limited in vivo data, regulatory issues, variability in composition, potential drug interactions, and safety concerns. Future research must prioritize comprehensive mechanistic studies, standardized preparations, and well-designed clinical trials. Overcoming these challenges through rigorous science is essential for integrating natural HMGCR modulators into clinical practice and improving patient outcomes in a safe and effective manner. Specifically, clinical trials should consider combination therapies and comparison with standard treatments like statins. More research is also needed on optimal dosages and treatment regimens. Full article

Background/Objectives: Pain is a growing public health concern worldwide, and the use of combinations of drugs can improve their analgesic effects while minimizing their adverse effects. Drugs such as metformin (antidiabetic) and melatonin (sleep regulator) have analgesic potential in combination. In this study, we evaluated the pharmacological interaction between metformin and melatonin when orally administered in a rat model, using the formalin test. Methods: Female Wistar rats (220–350 g) were injected with 50 µL of 1% formalin in the dorsal surface of the right hind paw. Formalin produces pain-related flinching behavior, and antinociception was evaluated as the reduction in this response. The percentage of the antinociceptive effect was determined after the oral administration of metformin (30–1000 mg/kg), melatonin (10–150 mg/kg), and their combination (MMC). To establish the nature of the interaction, isobolographic analysis was performed in a fixed-dose ratio (0.5:0.5), based on the effective dose 50 (ED₅₀) values for each drug: metformin (947.46 ± 242.60 mg/kg) and melatonin (126.86 ± 37.98 mg/kg). To evaluate the mechanism of action, the receptor antagonist for metformin compound C (dorsomorphin) for AMPK inhibition, MT1 and MT2 melatonin receptor antagonists (4-P-PDOT, luzindole), and an opioid antagonist (naloxone) were employed. The rotarod test was used to evaluate the safety profile of the combination. Results: The metformin–melatonin combination significantly reduced the number of flinches in the second phase of the formalin test. The theoretical ED₅₀ for the combination (ED₅₀ T) was 537.15 ± 122.76 mg/kg. Experimentally, the ED₅₀ (ED₅₀ E) was significantly lower (360.83 ± 23.36 mg/kg), indicating a synergistic interaction for the combination involving opioidergic pathways, MT2 receptors, and AMPK activation. Conclusions: Oral metformin–melatonin coadministration could provide a therapeutic alternative for inflammatory pain. Full article

Continuing our search for bioactive compounds in species from the Juncaceae family, we investigated Juncus tenuis. The structures of five previously undescribed phenanthrenes—tenuins A–E (1–5)—and 14 known phenanthrenes (6–19), along with other components, were isolated and characterized using nuclear magnetic resonance and high-resolution mass spectrometry measurements. The antiproliferative activity of all of the isolated phenanthrenes was evaluated against the human colorectal adenocarcinoma cell lines COLO 205 (doxorubicin-sensitive) and COLO 320 (doxorubicin-resistant), as well as a non-tumorigenic human fibroblast cell line (CCD-19Lu), using the MTT viability assay. Diphenanthrenes 4, 5, and 19 showed the most potent antiproliferative effects, with IC₅₀ values ranging from 7.60 to 17.32 μM; however, these compounds lacked selectivity toward cancer cells. To explore potential chemosensitizing properties, the synergistic effects of the phenanthrenes with the anticancer drug doxorubicin were also examined in the COLO 320 cells. Notably, compound 2 exhibited very strong synergism (CI = 0.021), indicating a highly potent interaction. These findings highlight J. tenuis as a valuable source of phenanthrenes and demonstrate the synergistic anticancer potential of natural phenanthrenes with doxorubicin, offering promising prospects for overcoming multidrug resistance in colorectal cancer therapy. Full article

Background: Drug–drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women’s healthcare. Methods: A DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein–protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. Results: This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25%, respectively). Some were expected to improve current therapies (n = 23), while others would cause harmful effects (n = 11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Conclusions: These results show the importance of DDI studies aimed at identifying those that might compromise or improve their efficacy, which could lead to personalizing female reproductive therapies. Full article

Colchicine is a potent alkaloid with well-established anti-inflammatory properties. It shows significant promise in treating classic immune-mediated inflammatory diseases, as well as associated cardiovascular diseases, including atherosclerosis. However, its clinical use is limited by a narrow therapeutic window, dose-limiting systemic toxicity, variable bioavailability, and clinically significant drug–drug interactions, partly mediated by modulation of P-glycoprotein and cytochrome P450 3A4 metabolism. This review explores advanced delivery strategies designed to overcome these limitations. We critically evaluate lipid-based systems, such as solid lipid nanoparticles, liposomes, transferosomes, ethosomes, and cubosomes; polymer-based nanoparticles; microneedles; and implants, including drug-eluting stents. These systems ensure targeted delivery, improve pharmacokinetics, and reduce toxicity. Additionally, we discuss chemical derivatization approaches, such as prodrugs, codrugs, and strategic ring modifications (A-, B-, and C-rings), aimed at optimizing both the efficacy and safety profile of colchicine. Combinatorial nanoformulations that enable the co-delivery of colchicine with synergistic agents, such as glucocorticoids and statins, as well as theranostic platforms that integrate therapeutic and diagnostic functions, are also considered. These innovative delivery systems and derivatives have the potential to transform colchicine therapy by broadening its clinical applications while minimizing adverse effects. Future challenges include scalable manufacturing, long-term safety validation, and the translation of research into clinical practice. Full article

In clinical decision support systems (CDSSs), where accurate classification of drug–drug interactions (DDIs) can directly affect treatment safety and outcomes, identifying drug interactions is a major challenge, introducing a scalable approach for classifying DDIs utilizing a finely-tuned biomedical language model. The method shown here uses BiomedBERT, a domain-specific version of bidirectional encoder representations from transformers (BERT) that was pre-trained on biomedical literature, to reduce the number of resources needed during fine-tuning. Low-rank adaptation (LoRA) was used to fine-tune the model on the DrugBank dataset. The objective was to classify DDIs into two clinically distinct categories, that is, synergistic and antagonistic interactions. A pseudo-labeling strategy was created to deal with the problem of not having enough labeled data. A curated ground-truth dataset was constructed using polarity-labeled interaction entries from DrugComb and verified DrugBank antagonism pairs. The fine-tuned model is used to figure out what kinds of interactions there are in the rest of the unlabeled data. A checkpointing system saves predictions and confidence scores in small pieces, which means that the process can be continued and is not affected by system crashes. The framework is designed to log every prediction it makes, allowing results to be refined later, either manually or through automated updates, without discarding low-confidence cases, as traditional threshold-based methods often do. The method keeps a record of every output it generates, making it easier to revisit earlier predictions, either by experts or with improved tools, without depending on preset confidence cutoffs. It was built with efficiency in mind, so it can handle large amounts of biomedical text without heavy computational demands. Rather than focusing on model novelty, this research demonstrates how existing biomedical transformers can be adapted to polarity-aware DDI classification with minimal computational overhead, emphasizing deployment feasibility and clinical relevance. Full article

Diabetes mellitus (DM) is one of the leading causes of death and disability worldwide and its prevalence continues to rise. Chronic hyperglycemia exposes patients to severe complications. Among these, diabetic vascular lesions are the most destructive. Their primary driver is the synergistic interaction between hyperglycemia-induced oxidative stress and chronic inflammation. This review systematically elucidates how multiple pathological pathways—namely, metabolic dysregulation, mitochondrial dysfunction, endoplasmic reticulum stress, and epigenetic reprogramming—cooperate to drive oxidative stress and inflammatory cascades. Confronting this complex pathological network, natural products, unlike conventional single-target synthetic drugs, exert multi-target synergistic effects, simultaneously modulating several key pathogenic networks. This enables the restoration of redox homeostasis and the suppression of inflammatory responses, thereby improving vascular function and delaying both microvascular and macrovascular disease progression. However, the clinical translation of natural products still faces multiple challenges and requires comprehensive mechanistic studies and rigorous validation to fully realize their therapeutic potential. Full article

Brain organoid technology has revolutionized in vitro modeling of human neurodevelopment and disease, providing unprecedented insights into cortical patterning, neural circuit assembly, and pathogenic mechanisms of neurological disorders. Critically, human brain organoids uniquely recapitulate human-specific developmental processes—such as the expansion of outer radial glia and neuromelanin—that are absent in rodent models, making them indispensable for studying human brain evolution and dysfunction. However, a major bottleneck persists: Extended culture periods (≥6 months) are empirically required to achieve late-stage maturation markers like synaptic refinement, functional network plasticity, and gliogenesis. Yet prolonged conventional 3D culture exacerbates metabolic stress, hypoxia-induced necrosis, and microenvironmental instability, leading to asynchronous tissue maturation—electrophysiologically active superficial layers juxtaposed with degenerating cores. This immaturity/heterogeneity severely limits their utility in modeling adult-onset disorders (e.g., Alzheimer’s disease) and high-fidelity drug screening, as organoids fail to recapitulate postnatal transcriptional signatures or neurovascular interactions without bioengineering interventions. We summarize emerging strategies to decouple maturation milestones from rigid temporal frameworks, emphasizing the synergistic integration of chronological optimization (e.g., vascularized co-cultures) and active bioengineering accelerators (e.g., electrical stimulation and microfluidics). By bridging biological timelines with scalable engineering, this review charts a roadmap to generate translationally relevant, functionally mature brain organoids. Full article

Background/Objectives: Limited robust data support the use of antibiotic combinations in the treatment of orthopedic infections. However, in certain situations, the combination of antibiotics seems to be beneficial. This review aims to outline the circumstances under which a combination of antibiotics may be utilized in the treatment of orthopedic infections. Methods: We reviewed the existing guidelines on orthopedic infections and focused on situations where antibiotic combinations are recommended or proposed optionally. We chose vitro and animal studies that provide evidence for the effectiveness of several widely recommended combinations. Results: The combinations serve multiple purposes: they provide empirical coverage while awaiting microbiological results, offer targeted treatment for difficult-to-treat infections, and facilitate oral treatment primarily for staphylococcal infections. The objectives include enhancing bacterial coverage against Gram-positive and Gram-negative bacteria, achieving synergistic effects with bactericidal agents, and reducing the risk of antibiotic resistance. The review outlines specific combinations for fracture-related infections, periprosthetic joint infections, spinal infections, and anterior cruciate ligament reconstruction infections, emphasizing the importance of tailoring antibiotic choices based on local epidemiology and patient history. The review also addresses potential drawbacks of combination therapy, such as toxicity, higher costs, and drug interactions, underscoring the complexity of managing orthopedic infections effectively. Conclusions: According to the guidelines, several different proposals are made, depending in part on the countries’ epidemiology. In a well-defined situation, various authors propose either monotherapy or a combination of antibiotics. When a combination is suggested, the choice of antibiotics is based on the expected effect: broadening the spectrum, enhancing bactericidal activity, achieving a synergistic effect, or reinforcing biofilm activity to optimize the treatment. Full article

Cancer presents significant challenges owing to its complex molecular pathways and resistance to therapy. Natural metabolites have significant medicinal potential by regulating the sensing and signaling pathways associated with cancer development. Recognizing their interactions within the tumor microenvironment may unveil innovative techniques for inhibiting malignant activities and improve therapy success. This article highlights studies regarding ovarian cancer metabolism, signaling mechanisms, and therapeutic natural substances. This study summarizes clinical and experimental results to emphasise the synergistic effects of alkaloids, flavonoids, and terpenoids in improving therapeutic effectiveness and alleviating drug resistance. Bioactive compounds are essential in regulating ovarian cancer metabolism and signaling pathways, affecting glycolysis, lipid metabolism, and the survival of tumor cells. This review examines metabolic programming and essential pathways, including glycolysis, TCA cycle, lipid metabolism, PI3K/AKT/mTOR, AMPK, and MAPK, emphasizing their therapeutic significance. The integration of metabolic treatments with medicines based on natural compounds has significant potential for enhancing treatment effectiveness and mitigating therapeutic resistance. Ovarian cancer needs an integrated strategy that includes metabolic reprogramming, signaling modulation, and drugs derived from natural products. Natural chemicals provide intriguing approaches to address chemotherapy resistance and improve treatment efficacy. Further research is required to enhance these methodologies and evaluate their practical applicability for improved patient outcomes. Full article

Traditional Chinese medicine (TCM), a holistic medical system rooted in dialectical theories and natural product-based therapies, has served as a cornerstone of healthcare systems for millennia. While its empirical efficacy is widely recognized, the polypharmacological mechanisms stemming from its multi-component nature remain poorly characterized. The conventional trial-and-error approaches for bioactive compound screening from herbs raise sustainability concerns, including excessive resource consumption and suboptimal temporal efficiency. The integration of artificial intelligence (AI) and multi-omics technologies with network pharmacology (NP) has emerged as a transformative methodology aligned with TCM’s inherent “multi-component, multi-target, multi-pathway” therapeutic characteristics. This convergent review provides a computational framework to decode complex bioactive compound–target–pathway networks through two synergistic strategies, (i) NP-driven dynamics interaction network modeling and (ii) AI-enhanced multi-omics data mining, thereby accelerating drug discovery and reducing experimental costs. Our analysis of 7288 publications systematically maps NP-AI–omics integration workflows for natural product screening. The proposed framework enables sustainable drug discovery through data-driven compound prioritization, systematic repurposing of herbal formulations via mechanism-based validation, and the development of evidence-based novel TCM prescriptions. This paradigm bridges empirical TCM knowledge with mechanism-driven precision medicine, offering a theoretical basis for reconciling traditional medicine with modern pharmaceutical innovation. Full article

Regulatory T cells (Tregs) have multiple roles in the tumor microenvironment (TME), which maintain a balance between autoimmunity and immunosuppression. This research aimed to investigate the interaction between cancer stemness and Regulatory T cells (Tregs) in the breast cancer tumor immune microenvironment. Breast cancer stemness was calculated using one-class logistic regression. Twelve main cell clusters were identified, and the subsequent three subsets of Regulatory T cells with different differentiation states were identified as being closely related to immune regulation and metabolic pathways. A prognostic risk model including MEA1, MTFP1, PASK, PSENEN, PSME2, RCC2, and SH2D2A was generated through the intersection between Regulatory T cell differentiation-related genes and stemness-related genes using LASSO and univariate Cox regression. The patient’s total survival times were predicted and validated with AUC of 0.96 and 0.831 in both training and validation sets, respectively; the immunotherapeutic predication efficacy of prognostic signature was confirmed in four ICI RNA-Seq cohorts. Seven drugs, including Ethinyl Estradiol, Epigallocatechin gallate, Cyclosporine, Gentamicin, Doxorubicin, Ivermectin, and Dronabinol for prognostic signature, were screened through molecular docking and found a synergistic effect among drugs with deep learning. Our prognostic signature potentially paves the way for overcoming immune resistance, and blocking the interaction between cancer stemness and Tregs may be a new approach in the treatment of breast cancer. Full article

Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, driven by chronic inflammation, gut microbiota dysbiosis, and complex tumor microenvironment interactions. Current therapies are limited by systemic toxicity and poor tumor accumulation. This study aimed to develop a ROS/enzyme dual-responsive oral drug delivery system, KGM-CUR/PSM microspheres, to achieve precise drug release in CRC and enhance tumor-specific drug accumulation, which leverages high ROS levels in CRC and the β-mannanase overexpression in colorectal tissues. Methods: In this study, we synthesized a ROS-responsive prodrug polymer (PSM) by conjugating polyethylene glycol monomethyl ether (mPEG) and mesalazine (MSL) via a thioether bond. CUR was then encapsulated into PSM using thin-film hydration to form tumor microenvironment-responsive micelles (CUR/PSM). Subsequently, konjac glucomannan (KGM) was employed to fabricate KGM-CUR/PSM microspheres, enabling targeted delivery for colorectal cancer therapy. The ROS/enzyme dual-response properties were confirmed through in vitro drug release studies. Cytotoxicity, cellular uptake, and cell migration were assessed in SW480 cells. In vivo efficacy was evaluated in AOM/DSS-induced CRC mice, monitoring tumor growth, inflammatory markers (TNF-α, IL-1β, IL-6, MPO), and gut microbiota composition. Results: In vitro drug release studies demonstrated that KGM-CUR/PSM microspheres exhibited ROS/enzyme-responsive release profiles. CUR/PSM micelles demonstrated significant anti-CRC efficacy in cytotoxicity assays, cellular uptake studies, and cell migration assays. In AOM/DSS-induced CRC mice, KGM-CUR/PSM microspheres significantly improved survival and inhibited CRC tumor growth, and effectively reduced the expression of inflammatory cytokines (TNF-α, IL-1β, IL-6) and myeloperoxidase (MPO). Histopathological and microbiological analyses revealed near-normal colon architecture and microbial diversity in the KGM-CUR/PSM group, confirming the system’s ability to disrupt the “inflammation-microbiota-tumor” axis. Conclusions: The KGM-CUR/PSM microspheres demonstrated a synergistic enhancement of anti-tumor efficacy by inducing apoptosis, alleviating inflammation, and modulating the intestinal microbiota, which offers a promising stimuli-responsive drug delivery system for future clinical treatment of CRC. Full article

Background/Objectives: Combination therapies using traditional Chinese medicine and Western drugs have gained attention for their enhanced therapeutic effects and reduced side effects. Toujie Quwen Granules (TQG), known for its antiviral properties, particularly against respiratory viruses, could offer new treatment strategies when combined with antiviral drugs like arbidol, especially for diseases such as Coronavirus disease. This study investigates the synergistic mechanisms between arbidol and components from TQG against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (M^pro). Methods: We identified compounds from TQG via existing data. Multi-ligand molecular docking, pharmacokinetic/toxicity screening, and preliminary simulations were performed to assess potential synergistic compounds with arbidol. UPLC-Q-Exactive Orbitrap-MS verified the presence of these compounds. Extended simulations and in vitro assays, including Luciferase and surface plasmon resonance, validated the findings. Results: Five compounds interacted with arbidol in synergy based on docking and preliminary dynamics simulation results. Only Baicalein (HQA004) could be identified in the herbal remedy by untargeted metabolomics, with ideal pharmacokinetic properties, and as a non-toxic compound. Extended simulations revealed that HQA004 enhanced arbidol’s antiviral activity via a “Far” Addition Mechanism #2, with an optimal 2:1 arbidol:HQA004 ratio. The movements of arbidol (diffusion and intramolecular conformational shifts) in the system were significantly reduced by HQA004, which may be the main reason for the synergism that occurred. In vitro experiments confirmed an increased inhibition of M^pro by the combination. Conclusions: HQA004 demonstrated synergistic potential with arbidol in inhibiting M^pro. The development of combination therapies integrating Western and herbal medicine is supported by these findings for effective antiviral treatments. Full article

Objectives: Drug-drug cocrystals with improved properties can be used to facilitate the development of synergistic therapeutic combinations. The goal of the present study is to obtain novel drug-drug cocrystals involving two anti-glioma agents, temozolomide (TMZ) and myricetin (MYR). Methods: The novel TMZ-MYR cocrystal was prepared via slurry and solvent evaporation techniques and characterized by X-ray diffraction, thermal analysis, infrared spectroscopy, and dynamic vapor sorption measurements. The stability, compaction, and dissolution properties were also evaluated. Results: Crystal structure analysis revealed that the cocrystal lattice contains two TMZ molecules, one MYR molecule, and four water molecules, which are linked by hydrogen bonding interactions to produce a three-dimensional network. The cocrystal hydrate exhibited favorable stability and tabletability compared to pure TMZ. A dissolution study showed that the maximum solubility of MYR in the cocrystal (176.4 μg/mL) was approximately 6.6 times higher than that of pure MYR·H₂O (26.9 μg/mL), while the solubility of TMZ from the cocrystal (786.7 µg/mL) was remarkably lower than that of pure TMZ (7519.8 µg/mL). The solubility difference between MYR and TMZ was diminished from ~280-fold to ~4.5-fold. Conclusions: Overall, the TMZ-MYR cocrystal optimizes the stability and tabletability of TMZ and the dissolution behavior of both drugs, offering a promising approach for synergistic anti-glioma therapy with improved clinical potential. Full article