Search Results (10,013)

Myostatin (Mstn), a well-characterized member of the transforming growth factor-β (TGF-β) superfamily, serves as a key negative regulator of skeletal muscle mass. Its overactivation is closely associated with the pathogenesis of various musculoskeletal and metabolic disorders. Over the past decades, inhibiting Mstn has emerged as a promising therapeutic strategy to promote muscle growth. A range of Mstn-targeted inhibitors has been developed, yielding encouraging preclinical and clinical outcomes. These include small molecules, monoclonal antibodies, peptibodies, and gene therapy-based approaches. This review summarizes the biological structure and function of Mstn, provides a comprehensive overview of recent advances in Mstn-targeted therapeutics, and offers critical insights into future directions for drug development and clinical translation. Full article

Background/Objectives: KRAS G12C mutations define a clinically actionable subset of solid tumors, particularly non–small cell lung cancer. Clinical responses to approved covalent inhibitors remain limited by intrinsic and acquired resistance, highlighting the need for structurally distinct inhibitor scaffolds to expand therapeutic options. The objective of this study was to identify novel covalent binders targeting the KRAS G12C switch-II pocket through large-scale in silico screening and experimental validation. Methods: More than 1.9 million small molecules from diverse commercial libraries were screened using covalent docking, followed by multi-stage refinement incorporating molecular dynamics simulations, MM/GBSA free-energy estimation, and cancer-focused QSAR modeling. Results: This integrated workflow yielded 50 prioritized compounds spanning several chemically distinct scaffold classes. These candidates displayed favorable predicted binding energetics, stable ligand-protein interactions over extended simulation timescales, and low structural similarity to clinically approved KRAS G12C inhibitors sotorasib and adagrasib. Benchmarking against these clinical agents, using identical computational parameters, yielded comparable predicted binding energies for several candidate molecules. In cellular NanoBRET target-engagement assays, selected scaffolds, including K788-7251 and AN-989/14669131, exhibited sub-micromolar engagement of KRAS G12C with minimal endothelial cytotoxicity. Conclusions: Collectively, these findings identify structurally distinct, KRAS G12C inhibitor chemotypes and provide tractable starting points for the development of next-generation targeted therapies. Full article

Binding affinity prediction in computational drug discovery is confounded by trivial correlations between molecular size and measured potency. We introduce cellular sheaf Laplacians as descriptors of ligand molecular geometry that quantify geometric frustration independent of system size. Sheaves are constructed over molecular graphs by assigning three-dimensional coordinate spaces to atoms and projection operators encoding ideal bonding geometry to edges; eigendecomposition of the resulting Laplacian yields spectral features measuring inconsistencies between local geometric constraints and global topology. Applied to 14,050 protein-ligand complexes from the PDBbind v2020 refined set, MW-residualized Sheaf features capture a statistically significant geometric signal ($r_{\mathrm{partial}} = 0.171$, $p<{10}^{-70}$) that is orthogonal to the Wiener index ($r=0.013$) and persists after controlling for both molecular weight and classical graph-theoretic descriptors ($r_{\mathrm{partial}} = 0.390$, $p<{10}^{-9}$). Sheaf spectral features alone achieve predictive performance ($R^2=0.403$) approaching that of fourteen classical cheminformatics descriptors ($R^2=0.446$), and their combination yields consistent improvements across the binding affinity spectrum (RMSE $=1.43$$p{K}_d$). Permutation importance analysis confirms the Sheaf Frobenius norm as the second most influential descriptor after molecular weight. We introduce Topological Binding Efficiency as a size-normalized quality metric identifying ligands that achieve potent binding through geometric complementarity rather than molecular bulk. Gaussian mixture analysis of the maximum eigenvalue distribution among strong binders reveals two distinct spectral modes corresponding to planar aromatic and three-dimensional sp3-rich scaffolds, confirmed by significant differences in fraction of sp3 carbons and aromatic ring counts ($p<{10}^{-8}$). As an intentionally ligand-centric framework, our approach complements rather than replaces protein-aware co-modelling architectures. This work establishes cellular sheaf theory as a principled framework for encoding molecular topology with statistically significant associations with binding affinity, providing interpretable geometric insights that are inaccessible to conventional molecular descriptors. Full article

Since their initial discovery in 2003, carbon quantum dots (CDs) have attracted significant attention due to their unique optical properties and potential biomedical applications. This review critically examines the past 20 years of research on CDs, with a particular focus on cytotoxicity studies from the last decade. CDs, typically less than 10 nm in size, have been synthesized from various organic and inorganic precursors using multiple methods, including hydrothermal, microwave, and chemical reduction techniques. Their properties can be finely tuned by modifying synthesis parameters and incorporating dopants. The preliminary studies on the biological effects of CDs were published in 2013, highlighting their antibacterial properties and low toxicity in certain contexts. Subsequent research has explored their bioactivity, including their application in drug delivery, bioimaging, and photothermal therapy. However, the cytotoxicity of CDs remains a critical area of investigation. Further studies have demonstrated that surface functional groups, charge, concentration, and size significantly influence their interaction with biological systems. For instance, CDs with positive surface charges exhibit higher cellular uptake and greater cytotoxicity compared to their negatively charged counterparts. In vivo studies utilizing animal models such as zebrafish, mice, and planarians have provided valuable insights into the potential toxicological impacts of CDs. The results indicate that while CDs generally exhibit low toxicity at certain concentrations, high doses can lead to adverse effects, including oxidative stress, organ damage, and disrupted cellular functions. Notably, the route of administration (oral, intravenous, or intraperitoneal) also affects the observed toxicity profiles. The goal of this review is to integrate the results of various studies to provide a balanced perspective on the potential risks and benefits of CDs, guiding future research and applications in nanomedicine. This review underscores the necessity for standardized and comprehensive toxicological evaluations of CDs to fully understand their safety and efficacy for biomedical applications. Full article

The taxane family of compounds, including paclitaxel, docetaxel (Taxotere), and cabazitaxel (Jevtana), are common drugs used in chemotherapy for the frontline treatment of most major types of cancer. Alopecia, the dramatic loss of hair, is a common side effect that became a symbol of the suffering of many cancer patients. Concerted efforts have been made to understand the mechanism of taxane toxicity to hair follicles and, thus, prevention methods. Taxanes act by stabilizing cellular microtubules, which consequently cause mitotic arrest and then failure, as microtubules play critical functions in chromosome segregation. Hair follicle matrix cells are highly proliferative and thus are exceedingly sensitive to taxanes. We review the cellular mechanism-based strategies under investigation to counter taxane-induced hair follicle damage. These include the application of cyclin kinase inhibitors to block mitotic entry, the practical method using scalp cooling to reduce exposure of scalp hair follicles to drugs during infusion, the requirement of p53 action for hair follicle damage, and the recently discovered method of using low-intensity ultrasound to break taxane-stabilized microtubules and thus reverse taxane toxicity in hair follicle matrix cells. The concept of low-intensity ultrasound as an antidote to taxanes may have the potential to provide a practical and compelling strategy to counter alopecia in cancer treatment using taxanes. Tweet: Taxanes (paclitaxel/docetaxel) are powerful microtubule-stabilizing cancer drugs, but they also cause adverse effects, including alopecia. New research discoveries of temporary microtubule disruption by low-intensity ultrasound may counteract taxane toxicity and prevent alopecia during cancer chemotherapy. “Mechanistic-based strategies for the prevention of taxane-induced hair follicle damage in cancer chemotherapy” OUTLINE: 1. Taxane/paclitaxel mechanism of action in cancer therapy. 2. Taxane side effects: Alopecia (hair loss). 3. p53 dependence of taxane-induced hair follicle damage. 4. Research efforts to counter taxane -induced alopecia by CDK4/6i. 5. Prevention of taxane chemotherapy side effects using scalp cooling. 6. Discovery of low-intensity ultrasound as an antidote for taxane cytotoxicity, and potential prevention of alopecia in chemotherapy using taxanes. 7. Summary and prospective. Full article

Acute myocardial infarction (AMI) causes high mortality, with cardiomyocyte apoptosis playing a critical role. Although circular RNAs modulate cardiac disorders, related mechanisms remain unclear. Here, we identify circRERE as a previously unrecognized pro-apoptotic regulator under ischemic stress. circRERE is markedly upregulated in ischemic myocardium and promotes apoptosis by sponging miR-27a-3p to elevate Caspase9. Using epigallocatechin gallate-primed exosomes (EGCG-primed exosomes, Exo^EGCG) as a tool to modulate circRERE, we found that Exo^EGCG significantly reduced circRERE levels, restored miR-27a-3p activity, and suppressed Caspase9. Gain- and loss-of-function tests confirmed that circRERE mediates Exo^EGCG-derived protection. Collectively, circRERE represents a novel and actionable target for AMI, with Exo^EGCG serving as an effective delivery platform. Full article

Diabetic kidney disease (DKD) affects approximately 40% of patients with diabetes mellitus and remains a leading cause of end-stage renal disease worldwide. Early diagnosis and identification of therapeutic targets are critical for improving patient outcomes, yet reliable biomarkers are lacking. This study integrated transcriptomic data from the Gene Expression Omnibus (GEO) database (GSE96804, GSE30528, and GSE142025) with machine learning algorithms and Mendelian randomization (MR) to identify diagnostic biomarkers for DKD. Differentially expressed genes (DEGs) were identified and intersected with key modules from weighted gene co-expression network analysis (WGCNA). Four machine learning methods—least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine-recursive feature elimination (SVM-RFE), and extreme gradient boosting (XGBoost)—were applied for feature selection. Five hub genes (SPP1, CD44, VCAM1, C3, and TIMP1) were identified at the intersection of these approaches. Two-sample MR analysis using eQTL data from the eQTLGen Consortium and kidney function GWAS from the CKDGen Consortium provided evidence supporting potential causal associations between SPP1, C3, and TIMP1 expression and estimated glomerular filtration rate decline. Immune infiltration analysis via CIBERSORT estimated elevated proportions of M1 macrophages and activated CD4${}^{+}$ memory T cells in DKD samples, with all five hub genes showing correlations with macrophage infiltration. A diagnostic model based on these five genes achieved a cross-validated area under the receiver operating characteristic curve (CV-AUC) of 0.938 in the discovery dataset and AUC values of 0.917 and 0.889 in two independent external validation cohorts. Drug–gene interaction analysis identified 10 candidate compounds targeting the hub genes. These findings provide a computational framework for identifying candidate diagnostic biomarkers and generating hypotheses regarding potential therapeutic targets for DKD; however, all results are derived from in silico analyses and require experimental validation—including qPCR, immunohistochemistry, and prospective clinical cohort studies—before clinical applicability can be established. Full article

Bilirubin, historically recognized solely as a waste product of heme catabolism, has recently gained attention for its potential protective role in the cardiovascular system. Experimental and clinical studies suggest that bilirubin exhibits potent antioxidant, anti-inflammatory, anti-apoptotic, and cytoprotective properties that may protect the heart against oxidative stress, ischemia–reperfusion injury, and the progression of cardiovascular diseases, such as heart failure. As an endogenous hormone, bilirubin activates peroxisome proliferator-activated receptor-α (PPARα), a nuclear receptor that controls energy balance and lipid metabolism. Moderately elevated circulating bilirubin levels have been associated with a reduced risk of coronary artery disease, heart failure, and myocardial infarction; however, the mechanisms underlying bilirubin’s protective effects remain incompletely understood. Conversely, the gut microbiota’s metabolism of bilirubin to urobilin is detrimental, given urobilin’s association with cardiometabolic dysfunction. The therapeutic potential of bilirubin in the management of cardiovascular disease is becoming increasingly apparent, supported by preclinical research and emerging technologies that enhance bilirubin delivery via nanoparticles and methods to elevate plasma bilirubin levels. Collectively, these scientific advancements position bilirubin as a promising, biologically plausible endogenous therapeutic for the prevention and treatment of heart disease. Full article

Linezolid represents a critical last-resort treatment for severe multidrug-resistant (MDR) Gram-positive bacterial infections. Rising linezolid resistance in Enterococcus isolates threatens its efficacy; this study characterized the molecular features and transfer potential of plasmid-encoded linezolid resistance genes optrA and poxtA in a linezolid-resistant Enterococcus asini isolate from chickens. An E. asini strain was isolated during a surveillance program focusing on drug-resistant Gram-positive bacteria in poultry. PCR screened linezolid resistance genes, conjugation and plasmid stability assays evaluated gene transferability and stability, and whole-genome sequencing (WGS) was performed using both the Illumina and Nanopore platforms. We present the first detection of optrA and poxtA genes in E. asini recovered from chicken feces in China. Sequence analysis of the complete genome showed that poxtA and optrA were situated on two distinct plasmids. The poxtA positive plasmid, pHNGXN23C145Ea-1, also carried multiple resistance genes, including tet(S), fexB, erm(B), ant(6)-Ia, aph(3′)-III. Furthermore, the poxtA gene was flanked by IS1216E mobile elements. The optrA bearing plasmid, pHNGXN23C145Ea-2, harbours a common genetic array of ‘IS1216E fexA-optrA-erm(A)-IS1216E’. Conjugation experiments indicated that neither the poxtA- nor the optrA-bearing plasmid was transferred to recipient strains, which was consistent with sequence analysis showing that both plasmids lacked intact conjugative transfer regions. Stability assays confirmed that poxtA and optrA remained highly stable in the absence of selective pressure. Notably, this discovery was made in a livestock sample, despite the non-use of linezolid in food animals, suggesting that such niches may act as silent reservoirs for resistance genes, which could persist and potentially transfer to clinically relevant MDR pathogens. Full article

Propolis is a bee product with a complex chemical composition that exhibits remarkable antifungal activity against C. albicans and can inhibit resistant biofilms thanks to its content of compounds such as flavonoids and phenolic acids. Its efficacy varies depending on its geographic origin: European propolis inhibits the initial formation of biofilms, while Brazilian propolis is superior at inhibiting mature biofilms. This product also possesses fungicidal and fungistatic properties comparable in efficacy to conventional drugs, such as nystatin, fluconazole, and chlorhexidine. The use of nanotechnology, such as nanoparticles or nanorods, has overcome the low solubility of propolis compounds, improving their bioavailability and reducing cell adhesion and hyphal formation. Moreover, the integration of propolis into dental materials demonstrate its versatility for preventing recurrent infections. The study of isolated compounds such as pinocembrin, galangin, and chrysin has facilitated the identification of specific mechanisms of action, and the application of molecules such as guttiferone E in photodynamic therapies and the discovery of quorum-sensing inhibitors, such as kaempferol, using in silico models have opened new avenues for blocking yeast communication and virulence. These findings position propolis as a multifaceted and promising therapeutic alternative, although there is a need to optimize formulations to ensure clinical safety and biocompatibility. In this review, we analyze research published around the world over the last 15 years on the effects of propolis against C. albicans biofilms. Full article

Multiple studies have demonstrated that the conjugation of various metal cores to a modified tamoxifen vector amplifies its antitumor activity, rendering such engineered structures effective even in triple-negative breast cancer (TNBC), a tumor subtype traditionally considered irrelevant for endocrine therapy. With a focus on TNBC cell line, this study shows that hybrids with Pd- and Cu- in comparison to Pt-based counterparts exerted an advanced cytotoxic profile in terms of sustained cytotoxicity throughout all tested periods, well synchronized with an intensive and prolonged oxidative burst measured by 4-amino-5-methylamino-2′,7′-difluorofluorescein diacetate (DAF-FM), dihydroethidium (DHE), and dihydrorhodamine 123 (DHR-123) in the background. Translation to the orthotopic syngeneic mouse in vivo model confirmed their superiority toward Pt-based conjugates, as well as tamoxifen alone, with a more profound tumor-reducing potential of Cu-tamoxifen, which was finally restricted by its toxicity. Surprisingly, the tamoxifen vector per se, with an approx. 2-fold lower cytotoxic potential than Pt- and Cu-hybrids in vitro, showed exceptional tumor-reducing potential in vivo, profiled in the last days of the treatment period. Intensive infiltration of immune cells, preferentially lymphocytes, was observed in tumor samples from animals exposed to the tamoxifen vector, underscoring the ligand’s immune potential and again suggesting that cytotoxicity is not a measure of successful treatment. Full article

Acute mountain sickness (AMS) arises from hypobaric hypoxia at high altitude and still lacks effective pharmacological treatments. Although hypoxic preconditioning via gradual ascent prevents AMS, the underlying molecular adaptations have not yielded therapeutics. Here, inspired by metabolic reprogramming during stepwise altitude adaptation, we screened for anti-hypoxia compounds and identified H0802 (N-(pyridin-2-yl) pyridine-2-carbothioamide) as the most promising candidate. H0802 markedly enhances hypoxic tolerance in mice, prolongs survival under acute hypoxia, improves survival during simulated high-altitude exposure, and attenuates hypoxia-induced lung injury, accompanied by combined anti-inflammatory and antioxidant effects. Transcriptomic profiling shows that H0802 elicits a gene expression signature resembling hypoxia, including key hypoxia-related genes (Edn1, Angptl4, Mt1, Gdf15, Slc7a5, and Hif-3α) involved in glucose and oxygen metabolism. Mechanistically, H0802 stabilizes endogenous hypoxia-inducible factor (HIF) proteins under normoxia by preventing ubiquitin-dependent degradation, thereby activating hypoxia-responsive genes. In vivo, H0802 pretreatment lowers circulating glucose and hepatic glycogen while increasing brain glucose uptake, suggesting a metabolic shift that preserves cerebral energy during acute hypoxic stress; it also modulates whole-body oxygen consumption. H0802 represents a candidate for anti-AMS therapy, and phenotypic optimization of H0802 provides a potential route for drug discovery. Full article

Cancer has become a major global health threat due to its high incidence and mortality. However, the development of anti-cancer drugs is limited by high costs, long cycles, and low success rates, slowing the progress of new treatments. As a method that simulates human cognitive functions, artificial intelligence (AI) has greatly improved the efficiency of drug development. Machine learning is a core part of AI and supports applications such as natural language processing and computer vision. This paper reviews recent advances in AI for optimizing anti-cancer drug discovery, development, and medication therapy management. First, we highlight the applications of AI in target identification, druggability assessment, drug screening, and repurposing. Second, we detail how AI optimizes drug combination therapy and clinical trial design. Finally, we describe the role of AI in treatment management, including nanoparticle delivery systems, personalized dosing, and adaptive therapy. AI greatly streamlines anti-cancer drug development and provides new directions for precision cancer therapy. Full article

Reproducible morphological profiling, particularly for drug discovery, has become an important tool for compound evaluation. Established workflows such as CellProfiler provide a widely adopted foundation for Cell Painting analysis. However, conventional pipelines often require substantial manual configuration and technical expertise, which can limit scalability and accessibility. In this study, a fully automated deep learning-based workflow is presented for segmentation-driven morphological profiling from raw microscopy data. Using a curated subset of the JUMP Cell Painting pilot dataset, ground-truth masks were generated and used to train a U-net–based segmentation model in the IKOSA platform. Post-processing strategies were introduced to improve instance separation and reduce segmentation artifacts. The final model achieved strong segmentation performance (precision/recall/AP up to 0.98/0.94/0.92 for nuclei), with an average runtime of 2.2 s per 1080 × 1080 image. Segmentation outputs enabled large-scale feature extraction, yielding 3664 morphological descriptors that showed high correlation with CellProfiler-derived measurements (normalized MAE: 0.0298). Feature prioritization further reduced redundancy to 1145 informative descriptors. These results demonstrate that automated deep learning pipelines can complement established Cell Painting workflows by reducing configuration overhead while maintaining compatibility with validated morphological profiling standards. The proposed workflow may help improve resource efficiency in drug discovery and personalized medicine. Full article