Search Results (16,475)

The digestive system is one of the most complex systems in the body, integrating multiple functions, closely linked to and influenced by chemosensory mechanisms, as well as by the presence, composition, and dynamics of the microbiome. Increasing attention has been directed toward plant-derived foods and medicines, which interact with gut microbiota and modulate host physiological responses through microbial metabolism, leading to the formation of bioactive metabolites that influence host signaling pathways and therapeutic response. The review, based on relevant articles from major international databases using specific terms with a focus on microbiome-mediated interactions and molecular mechanisms, highlights the role of microbiome and diagnostic methods through the analysis of specific composition and changes in microbiota, as well as the importance of microbiomes in relation to the treatment of chronic diseases, given their complex influence on drug metabolism. The microbiome influences the response to medications and resistance to therapy, being also involved in the metabolism of plant-derived foods and medicines through complex microbial interactions, while the importance of modern diagnostic approaches supports the use of microbiome analysis to improve diagnosis, monitoring, and personalized medical strategies. Full article

Background: Adipose tissue is increasingly recognized as a highly dynamic endocrine and immunometabolic organ with marked functional heterogeneity. It serves as a reservoir for the active form of vitamin D₃, 1α,25-dihydroxyvitamin D₃ or calcitriol (1α,25-D₃), since it expresses enzymes responsible for its activation and inactivation and contains the vitamin D receptor (VDR). Through both classical and non-classical mechanisms, calcitriol modulates adipocyte proliferation and differentiation, protein expression and energy metabolism. This review aims to explore the signal transduction mechanisms of calcitriol in adipocytes, detailing the classical pathways mediated by the nuclear VDR (VDRn), as well as non-classical pathways involving membrane-associated VDR (VDRm), microRNAs, AMP-activated protein kinase (AMPK), and sirtuin 1 (SIRT1). Methods: A literature search was conducted using PubMed, ScienceDirect, and MDPI-indexed journals, prioritizing studies published within the last 10 years to ensure the inclusion of up-to-date evidence. Results: This review summarizes current knowledge on both classical and non-classical signaling pathways that are activated by calcitriol and highlights key molecular targets with potential relevance for drug development and therapeutic intervention. Through VDRn, calcitriol regulates the expression of proteins involved in inflammation and energy metabolism. Additionally, it modulates cellular processes such as energy production and secretion via the AMPK/SIRT1 axis and microRNA-mediated pathways, contributing to mitochondrial function and metabolic homeostasis. Conclusions: Calcitriol plays a central role in adipocyte biology by integrating multiple signaling pathways that regulate metabolic and inflammatory responses. These mechanisms highlight its potential as a therapeutic target and biomarker in metabolic diseases. Moreover, microRNAs emerge as critical posttranscriptional regulators in these processes, reinforcing their relevance as both biomarkers and targets for future interventions. Full article

Objective: Glutamic acid decarboxylase 65 (GAD65) antibody-associated epilepsy often presents as chronic focal epilepsy, usually with temporal lobe predominance, marked drug resistance, and inconsistent response to first-line immunotherapy. We assembled a large, harmonized, and literature-derived patient-level cohort to examine whether immunotherapy timing and regimen composition were associated with seizure outcome and to identify clinically meaningful prognostic signals. Methods: We performed a literature-derived patient-level analysis of 375 unique published cases linked to 132 contributory source publications from an audited full-text register of 166 reviewed studies. Descriptive analyses used the whole cohort. Treatment-response analyses assessed seizure outcome at the first evaluable post-immunotherapy assessment and at the last follow-up. Good seizure outcome was defined as seizure freedom and/or ≥50% seizure reduction. The primary timing comparison contrasted early treatment, defined as immunotherapy within 6 months of symptom onset, with late treatment, defined as immunotherapy after more than 12 months; four cases treated in the intermediate >6 to ≤12 month window were retained for descriptive timing summaries but excluded from the primary comparison. Statistical testing used the Fisher exact, Chi-square, Mann–Whitney U, and prespecified clustered logistic sensitivity analyses where appropriate. Results: The pooled phenotype was predominantly female, usually temporal-lobe-based, and frequently drug-resistant, with common autoimmune comorbidity and heterogeneous MRI abnormalities. Among timing-evaluable treated cases, earlier immunotherapy showed a class-specific, exploratory signal rather than a uniform regimen-independent effect. In rituximab/CD20-directed regimens, early treatment was associated with a higher rate of good seizure outcome than late treatment at both the first post-immunotherapy assessment and last follow-up (93.8% vs. 50.0%; risk difference [RD]: 43.8 percentage points; 95% CI: 7.7 to 72.7). A similar pattern was observed in the broader escalation group (94.4% vs. 55.6%; RD: 38.9 percentage points; 95% CI: 6.3 to 68.1). By contrast, steroid-containing regimens showed no clear early-versus-late advantage (84.6% vs. 88.2%; RD: −3.6 percentage points; 95% CI: −18.4 to 20.1). Shorter epilepsy duration before immunotherapy and absence of established drug resistance were the most clinically meaningful favorable baseline features. Significance: In GAD65 antibody-associated epilepsy, the therapeutic window may be most relevant for escalation strategies rather than for steroid-containing first-line regimens. However, these class-specific findings are exploratory and hypothesis-generating. They derive from non-randomized, literature-derived data and may reflect treatment intensity, center practice, publication era, and confounding by indication rather than isolated regimen superiority. Prospective collaborative registries with standardized longitudinal seizure outcome measures are needed to validate these observations. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis, biological heterogeneity, and persistent challenges in staging and treatment selection. This narrative review summarizes current and emerging applications of AI across lung cancer screening and early detection, imaging-based staging and prognostication, tissue and liquid biopsy-based tumor characterization, treatment planning, surgical and intraoperative guidance, and drug discovery. In imaging, deep learning models have demonstrated high performance in pulmonary nodule detection, risk stratification, and prediction of molecular alterations, while also showing promise in improving screening efficiency and reducing interpretive variability. In pathology and liquid biopsy domains, AI enables prediction of driver mutations, immunotherapy response, and survival outcomes directly from histopathology slides, circulating tumor DNA, and other blood-based biomarkers, facilitating minimally invasive precision oncology approaches. In treatment planning and delivery, AI systems are being developed to support clinical decision-making, surgical planning (through advanced image segmentation and delineation of operative anatomy), and intraoperative navigation through robotic and computer vision-enabled platforms. Despite these advances, significant barriers remain, including limited real-world validation, algorithmic biases, workflow integration issues, and unresolved ethical and legal concerns. Future progress will depend on the development of transparent, clinically validated, and generalizable AI systems that augment rather than replace the expertise of clinical providers and healthcare teams. Active engagement from pulmonologists, oncologists, radiologists, and thoracic surgeons will be essential in guiding safe implementation and ensuring that AI-driven innovations translate into meaningful improvements in patient outcomes. Full article

Immunotherapy has transformed cancer treatment; however, clinical benefit remains limited to a subset of patients, underscoring the need for robust biomarkers that capture tumor-immune interactions across cancer types. In this study, we performed a comprehensive pan-cancer, multi-omics characterization of the immune checkpoint–related molecules CD70, CD80, and TIGIT to evaluate their diagnostic, prognostic, and immunological relevance. Using integrative analyses of transcriptomic, epigenomic, genomic, pharmacogenomic, and single-cell RNA-sequencing data from The Cancer Genome Atlas and complementary resources, we assessed expression patterns, DNA methylation, somatic mutations, copy number alterations, immune infiltration, tumor stemness, and drug sensitivity. CD70, CD80, and TIGIT were broadly dysregulated across multiple malignancies, with coordinated overexpression particularly evident in kidney renal clear-cell carcinoma. Elevated expression of these immune checkpoints was associated with advanced tumor stage, aggressive molecular subtypes, and unfavorable survival outcomes in selected cancers, including uveal melanoma and renal malignancies. Functional analyses revealed significant associations between checkpoint expression and key oncogenic pathways, including epithelial–mesenchymal transition, apoptosis, and hormone receptor signaling, suggesting links with tumor progression and immune activation states. Immune deconvolution analyses indicated that TIGIT expression is associated with a T-cell–inflamed microenvironment and reduced neutrophil infiltration, while CD80 exhibited methylation-dependent associations with immune cell composition. Genomic and epigenetic alterations were found to correlate with checkpoint expression patterns and immune phenotypes across tumor types. Pharmacogenomic profiling identified associations between checkpoint expression and sensitivity to multiple anticancer agents; however, these findings are based on cell line datasets and should be considered predictive. Single-cell transcriptomic analyses further resolved cell-type–specific expression patterns, distinguishing tumor-intrinsic from immune-restricted expression profiles. Collectively, our findings establish CD70, CD80, and TIGIT as integrative biomarkers of tumor progression, immune contexture, and therapeutic response, providing a rationale for their clinical exploitation in precision immuno-oncology. Full article

Viral myocarditis (VMC), predominantly driven by Coxsackievirus B3 (CVB3) infection and the resultant excessive immune response, lacks effective treatments and specific antiviral drugs in clinical practice. Chlorogenic acid (CGA) has been proven to have significant antiviral and anti-inflammatory properties. This study evaluated the potential and mechanism of action of CGA against CVB3-induced viral myocarditis. Our research results showed that CGA significantly alleviated myocardial tissue damage in vivo. This protective effect was accompanied by effective inhibition of myocardial inflammatory responses and viral replication. Further in vitro experiments confirmed that CGA significantly inhibited the replication of CVB3 in a dose-dependent manner, and its inhibitory effect mainly targeted the replication stage of the viral life cycle. Mechanistically, CGA treatment correlates with reduced ZBP1 expression and accelerated ZBP1 degradation involving the ubiquitin–proteasome pathway, accompanied by suppressed activation of PANoptosis markers. These findings suggest that CGA alleviates CVB3-induced myocarditis through concerted antiviral and anti-inflammatory effects, with ZBP1-mediated PANoptosis as a potential contributing mechanism. Full article

Xylazole is a sedative and analgesic agent widely used in Chinese veterinary practice, valued for its convenient administration and effectiveness. This study aimed to clarify its mechanism of action by investigating the effects on cAMP and monoamine neurotransmitters using both in vitro and in vivo rat models. In rat cortical neurons, Xylazole increased cAMP levels in a concentration- and time-dependent manner, transiently increased extracellular DA levels, which subsequently declined, consistently reduced extracellular NE levels, and enhanced extracellular 5-HT along with its metabolite 5-HIAA. In contrast, in vivo administration in adult rats reduced cAMP, DA, and NE levels across multiple brain regions, including the cerebrum, hippocampus, and brainstem, while increasing 5-HT and 5-HIAA. Notably, in the cerebellum group, cAMP was elevated after drug washout, a pattern not observed in the other brain regions. These findings reveal a striking divergence: in P7 cortical neurons, Xylazole triggers an α₂-adrenoceptor-dependent cAMP elevation, whereas in adult brain regions, a high concentration of locally delivered Xylazole leads to predominantly inhibitory cAMP changes, with a notable delayed increase in the cerebellum. Because of the non-physiological concentration used in reverse microdialysis, the in vivo neurochemical patterns should be regarded as exploratory regional responses, not as evidence of specific receptor-mediated mechanisms. Full article

Additive manufacturing has emerged as a transformative technology for fabricating complex drug-eluting medical devices, offering unprecedented design freedom and functional integration capabilities. This comprehensive review systematically analyzes 3D printing technologies applied to pharmaceutical device manufacturing, focusing on drug-eluting vascular stents as a representative application. This review covers six primary additive manufacturing techniques, ranging from high-resolution vat photopolymerization (25 μm resolution) to direct energy deposition, with a focus on their capabilities for produce pharmaceutical devices with controlled drug release properties. Novel 4D/5D/6D printing technologies introduce stimuli-responsive behaviors enabling programmable drug release profiles and adaptive device functionality. Manufacturing process optimization reveals superior design flexibility compared to conventional methods, with 85–95% reduction in design iteration time and elimination of tooling costs for complex geometries. The material landscape encompasses traditional metals (316L stainless steel, cobalt–chromium), biodegradable polymers (polylactic acid, PLA; polycaprolactone, PCL; poly(lactic-co-glycolic acid), PLGA), shape-memory materials (i.e., polymers and alloys capable of recovering a pre-programmed shape upon exposure to a specific stimulus such as body temperature, moisture, or light), and advanced nanocomposites, each offering distinct drug-loading capacities (100–500 μg/cm²) and release kinetics. Critical challenges include standardization requirements (International Organization for Standardization (ISO) 5840 and American Society for Testing and Materials (ASTM) F2606), pharmaceutical-grade manufacturing protocols, and regulatory pathways for novel drug-device combinations. This review identifies key research priorities including development of biocompatible printing materials, accelerated drug release testing protocols, and scalable manufacturing processes suitable for medical device production. This analysis demonstrates that 3D printing enables integration of multiple pharmaceutical functions within single devices, controlled spatiotemporal drug delivery, and elimination of secondary manufacturing steps for drug coating processes, advancing the development of next-generation therapeutic medical devices. Full article

Ovarian cancer is a gynecological cancer, which, if metastasized and not detected early, can cause death among women. Therefore, accurate prediction of drug responses to ovarian cancer is needed. A gynecological pathologist inspects abnormality in tissues and provides a report for patients; however, this diagnostic process (1) is difficult to undertake; (2) requires experience; and (3) is time-consuming. Moreover, existing tools are imperfect. Hence, we present a computational pipeline to improve predictions of drug response pertaining to ovarian cancer. First, we downloaded digital pathology images pertaining to ovarian responses to bevacizumab from the Cancer Imaging Archive Repository. We employed a histogram of oriented gradients for images, constructed feature vectors, and used Fisher’s linear discriminant analysis to alter data representations through dimensionality reduction. This reduced-dimensionality data was used for regression analysis, employing support vector regression coupled with various kernels and calculating the area under the ROC curve (AUC). Experimental results were validated using transformer-based models (ViT and Swin) and other deep learning (DL) models (VGG16, ResNet50, InceptionV3, MobileNetV2, and EfficientNetB6). Our approach using a radial kernel (named SVRD + R) improved AUC performance by 17% compared to the best-performing transformer-based model (ViT). Likewise, AUC performance improved by 14.9% when compared against the best DL-based model (MobileNetV2). These results demonstrate feasibility, showing that induced models via the presented AI-based pipeline can lead to superior performance when investigating prediction problems pertaining to gynecologic cancer studies. Full article

Background/Objectives: Metastatic triple-negative breast cancer (mTNBC) carries a poor prognosis and limited treatment options. Sacituzumab govitecan (SG), an anti-Trop-2 antibody–drug conjugate, has shown activity in this setting, but a quantitative synthesis integrating randomized and real-world evidence—particularly in underrepresented subgroups—was lacking. We aimed to summarize the comparative benefit of SG, which derives from a single randomized trial, and to assess whether trial-level efficacy is consistent with the activity observed in routine practice. Methods: Following PRISMA 2020, we searched PubMed/MEDLINE and Web of Science (January 2017–April 2026) for trials and observational cohorts of SG monotherapy in mTNBC. Comparative effects were taken from randomized data; single-arm efficacy (objective response rate [ORR], clinical benefit rate [CBR], median progression-free [PFS], and overall survival [OS]) was pooled using random-effects models. Risk of bias was assessed with RoB 2 and ROBINS-I. The review was registered in the Open Science Framework. Results: Nine studies (1242 patients; 980 SG-treated) were included: one randomized trial (ASCENT), two single-arm trials, and six real-world cohorts. In ASCENT, SG improved PFS (hazard ratio [HR] 0.41, 95% CI 0.33–0.63) and OS (HR 0.51, 0.42–0.64). Pooled ORR was 31.1% (28.0–34.4), and CBR was 42.2% (37.7–46.8), with the median PFS being 4.8 months (4.4–5.3) and OS being 11.0 months (9.3–13.0); trial-derived and real-world estimates were concordant. The benefit persisted in older patients (HR 0.25) and Black women (HR 0.44) but not in those with brain metastases (HR 0.68, 0.38–1.23). Conclusions: SG shows clinically meaningful activity in mTNBC that is broadly consistent between controlled trials and routine practice. Comparative superiority over chemotherapy rests on a single randomized trial (ASCENT); the pooled single-arm estimates describe activity and its consistency rather than a comparative effect. Full article

Pharmacogenomics AI offers significant potential for individualized drug therapy; however, its clinical benefits remain unevenly distributed. Models trained predominantly on European-ancestry data consistently underperform in non-European populations, with polygenic risk scores (PRS) showing an estimated 39–73% reduction in predictive accuracy in African-ancestry cohorts across complex traits. These disparities have driven increased interest in moving beyond single-layer genomic approaches. Multi-omics frameworks integrating genomic, transcriptomic, proteomic, and metabolomic data have emerged as a promising strategy to improve prediction across heterogeneous clinical populations, as each molecular layer provides distinct and complementary biological information. Among these layers, metabolomics may represent a particularly transferable component across populations. Metabolite profiles capture the downstream functional output of biological systems influenced by genetic, environmental, dietary, and microbiome-related factors, and may therefore be less reliant on ancestry-stratified allele frequency structures that underlie performance disparities in genomic models. This review synthesizes evidence regarding the mechanistic basis of genomic bias in pharmacogenomics AI, the emerging role of multi-omics integration, especially metabolomics, in improving predictive performance, and the current landscape of computational strategies for bias mitigation, including federated learning, transfer learning, domain adaptation, and synthetic data generation. Collectively, current evidence supports metabolomics-inclusive multi-omics frameworks as a biologically plausible, hypothesis-generating strategy to reduce reliance on ancestry-linked genomic features. However, direct evidence that such frameworks reduce ancestry-related bias in clinical AI outputs remains limited, underscoring the need for globally diverse datasets and prospective multi-population validation. Full article

The rapid emergence of antimicrobial resistance has intensified the need for advanced therapeutic platforms capable of improving the efficacy, stability, and targeted delivery of antimicrobial agents. Electrospun nanofibers have emerged as highly promising materials for biomedical applications due to their large surface area, high porosity, tunable morphology, and ability to incorporate a broad range of bioactive compounds. This review provides a comprehensive overview of the design, fabrication, and biomedical applications of electrospun bioactive nanofibers functionalized with antimicrobial drugs. It presents the main nanofiber fabrication techniques, with particular emphasis on electrospinning and the influence of solution, process, and environmental parameters on fiber morphology and drug-loading efficiency. Natural, synthetic, and hybrid polymer systems commonly employed in electrospun antimicrobial nanofibers are analyzed in relation to their physicochemical properties, biocompatibility, and therapeutic performance. In addition, the review highlights different drug incorporation strategies, including encapsulation, immobilization, and surface coating, as well as the mechanisms of action of antimicrobial agents. Recent advances in nanotechnology-based antimicrobial systems and their role in overcoming analytical, biopharmaceutical, and drug-delivery limitations are also examined. Furthermore, the review addresses current challenges related to scalability, reproducibility, stability, and clinical translation of electrospun nanofibers. Finally, future perspectives focusing on multifunctional, stimuli-responsive, and personalized antimicrobial nanofiber systems are discussed as promising directions for combating bacterial infections and reducing the global burden of antimicrobial resistance. Full article

Chronic rhinosinusitis (CRS) constitutes a multicausal inflammatory disease of the nose and paranasal sinuses, often associated with olfactory dysfunction (OD), a symptom that significantly impacts patients’ quality of life. OD in CRS was traditionally thought to be related to mechanical obstruction of the olfactory cleft, but is now considered to be multifactorial, involving conductive, inflammatory, and sensorineural mechanisms as well. Type-2 inflammatory response (high interleukins IL-4, IL-5, IL-13), eosinophilia, and increased IgE are involved in epithelial damage, impaired neurogenesis, and persistent olfactory loss, especially in chronic rhinosinusitis with nasal polyps (CRSwNP). In addition, peripheral chronic inflammation may also play a role in central neural remodeling, which may potentially affect olfactory function. Objective psychophysical testing is necessary to accurately assess olfactory function because self-reports may lack reliability. Management strategies aim at reducing inflammation and restoring sinonasal ventilation. First-line therapy with intranasal corticosteroids and short courses of systemic corticosteroids may be useful for symptomatic relief. Biologic agents directed against type-2 inflammation have demonstrated significant benefits in selected cases. Functional Endoscopic Sinus Surgery (FESS) plays an important role in the treatment of refractory CRS to restore the airflow and to improve the delivery of topical drugs. Olfactory outcomes following surgery, however, are variable and often incomplete, reflecting underlying inflammation and neuroepithelial damage. Disease recurrence, especially in type-2–driven CRS, affects long-term outcomes, underscoring the necessity to incorporate surgery in an individualized, endotype-informed treatment strategy. Full article

Polymer coatings are integral to nearly every modern cardiovascular and endovascular device, including drug-eluting stents (DESs) and drug-coated balloons (DCBs), bioabsorbable vascular scaffolds (BVSs), occluders, grafts, and catheter and guidewire hydrophilic surfaces. Persistent complications, including late stent thrombosis, delayed endothelialization, hypersensitivity, and restenosis, show that coatings actively shape biological responses rather than acting as inert drug carriers. Their surface chemistry, drug release kinetics, and degradation behavior are upstream determinants of blood– and tissue–material responses that govern healing and failure. This review frames coating selection as a structure–property–biological response problem. It surveys the major classes of synthetic polymer coatings and the defining surface and bulk properties. This review also examines how composition and architecture control drug release, and traces the interfacial cascade of protein adsorption, coagulation and complement activation, platelet and leukocyte responses, and neutrophil extracellular trap (NET) formation. These mechanisms are linked to contemporary design strategies that improve hemocompatibility, limit thrombosis, promote endothelial recovery, and tune degradation, and to the standardization and translation gaps that remain. The central message is that polymer coatings are not biologically equivalent. Their surface chemistries and degradation profiles determine the thrombo-inflammatory outcomes. Therefore, coating design should be guided by intended biological response, not drug release alone. Full article

Growth hormone-releasing hormone (GHRH) antagonists have displayed anti-neoplastic activity against a multitude of cancers in vitro, as well as in vivo, via xenografted tumors in nude mice. Following a successful demonstration of GHRH antagonists treating non-Hodgkin’s lymphoma and the discovery of GHRH mRNA and peptide products in immune cells, GHRH antagonism was explored in acute myeloid leukemia (AML), a disease characterized by a malignant expansion of immature myeloid progenitors, and poor 5-year survival. Targeted therapies have yielded breakthroughs in treatment response and overall survival, such as all-trans retinoic acid/arsenic trioxide (ATRA/ATO) for acute promyelocytic leukemia (APL), or FLT3 inhibitors, IDH inhibitors, and menin inhibitors for AML harboring actionable genetic lesions. However, therapeutic resistance remains a major barrier to durable remission. GHRH receptor (GHRH-R) has been reported in several experimental models of AML, including drug-resistant sublines. Significant time- and dose-dependent reduction in leukemic growth was observed in vitro and in vivo following MIA-602 treatment. FLT3 inhibitor resistance has been associated with activation of PI3K/AKT, ERK/MAPK, inflammatory, stromal, and apoptotic escape pathways. The documented effects of GHRH-R antagonism raise the possibility that it could influence signaling networks relevant to therapeutic resistance in AML. This hypothesis remains speculative; to date no studies have stratified AML by FLT3 status in the context of GHRH-R expression or GHRH antagonism, and there is currently no evidence that MIA-602 directly alters FLT3 receptor signaling or inhibitor sensitivity. Full article