The increasing demand for compact and energy-efficient heat exchangers has accelerated the development of passive heat transfer enhancement techniques and intelligent predictive tools for improved thermal system design. In the present study, an experimental and machine learning-based investigation was conducted to evaluate the thermo-hydraulic performance of a counter-flow double-pipe heat exchanger equipped with helical wire coil (WC) inserts under turbulent flow conditions. The novelty of this work lies in the systematic assessment of fifteen insert configurations by combining three wire diameters (1.0, 1.5, and 2.0 mm) with five pitch ratios (P/Dc = 0.625, 1.25, 1.875, 2.5, and 3.125). Experiments were performed over a Reynolds number range of 5500-15000, and the experimental setup was validated against established Nusselt number and friction factor correlations. The thermo-hydraulic performance was evaluated using the heat transfer coefficient, Nusselt number, friction factor, pressure drop, and thermal performance factor. The results showed that the wire coil inserts generated strong swirl flow and secondary vortices, which enhanced fluid mixing and suppressed thermal boundary layer development, resulting in a maximum Nusselt number enhancement of 126.7% compared with the plain tube. The highest Nusselt number (180.24) was achieved using a 2 mm wire diameter with a P/Dc of 0.625. Although the friction factor increased by 156.5-410.8% due to greater flow resistance, the thermal performance factor remained above unity (1.01-1.35) for all configurations, confirming the overall thermo-hydraulic effectiveness of the inserts. Furthermore, Linear Regression, Ridge Regression, Random Forest, and Gradient Boosting models were developed to predict the heat transfer and flow characteristics. Among them, the Gradient Boosting model demonstrated the highest prediction accuracy, achieving R2 values of 0.9984 and 0.9971 for the Nusselt number and friction factor, respectively, highlighting the potential of machine learning for the rapid design and optimization of advanced heat exchanger systems.
This comprehensive review presents a thorough examination of recent advances in nanoemulsion (NE) green technology, focusing on biomass-assisted synthesis, characterization, and the diverse biomedical implications of these nanoscale emulsions. NEs, characterized by their minute droplet sizes and kinetic stability, have garnered considerable attention due to their potential applications across various biomedical fields. This review presents a comprehensive analysis of state-of-the-art synthesis methods, including mini-emulsion polymerization, NE–solvent evaporation, spontaneous emulsification, sol–gel techniques, and innovative strategies for producing complex multicomponent materials. Emphasis is placed on the evolution of synthetic approaches, offering insights into the current landscape of NE production. In exploring the biomedical applications, the study categorizes nanocarriers formed within NEs, distinguishing between polymeric, inorganic, and hybrid nanocarriers based on their chemical composition. Noteworthy advancements in synthetic strategies are outlined for each category, showcasing the dynamic nature of NEs technology. A key highlight is the discussion of emerging trends in biomedical applications, spanning medicine, food, agriculture, cosmetics, and environmental science. Specific attention is given to the role of NEs in nanofiltration, elucidating their effectiveness in removing diverse pharmaceuticals through polyamide nano-filters. Moreover, the manuscript delves into the pivotal role of NEs in bioremediation, addressing hazardous substances such as PFASs through adsorption, photo-degradation/defluorination, and other innovative mechanisms. This review aims to provide a contemporary overview of green NE technologies, offering valuable insights for researchers, scientists, and practitioners in nanotechnology, pharmaceuticals, and biomedical sciences.
Noninvasive biomedical analysis remains a central objective in modern diagnostics, where early detection significantly improves therapeutic outcomes. Tissue fluorescence has emerged as a powerful optical strategy owing to its molecular specificity, rapid acquisition, and practically no sample preparation. Originating from endogenous fluorophores, such as Nicotinamide Adenine Dinucleotide in its reduced form (NADH), Flavin Adenine Dinucleotide (FAD), collagen, elastin, keratin, and porphyrins, fluorescence encodes information on metabolic activity, extracellular matrix organization, oxidative stress, glycation, and other physio-pathological processes. Advances in excitation sources, fiber-optic probes, MultiSpectral Imaging (MSI), HyperSpectral Imaging (HSI), and Fluorescence Lifetime Imaging Microscopy (FLIM) have expanded clinical applicability, while computational tools including multivariate analysis and machine learning now enable automated interpretation of complex optical signatures. Current evidence demonstrates strong diagnostic potential across cancer screening, diabetes, systemic lupus erythematosus, osteoporosis, dermatological disorders, and other metabolic or degenerative diseases. Despite these advances, challenges persist, including limited penetration depth, inter-individual variability, spectral overlap, and lack of standardized acquisition protocols. Future progress will rely on harmonized clinical validation, multimodal optical platforms, curated spectral databases, and artificial intelligence-assisted decision support. Collectively, tissue fluorescence represents a promising foundation for next-generation, portable, real-time, and patient-centered precision diagnostics.
Thrombosis is built, not merely catalyzed. Across arterial and venous disease, thrombus formation depends on a succession of protein–protein interactions (PPIs) that coordinate platelet capture and activation, thromboinflammatory amplification, and assembly of membrane-bound coagulation complexes. Although active-site inhibitors and receptor antagonists have transformed antithrombotic therapy, clinical benefit is often constrained by bleeding because many targets are indispensable for everyday hemostasis when inhibited systemically. This review advances a “thrombus assembly” framework that reframes drug discovery around disrupting interfaces that organize pathologic clot growth in a context-dependent manner shaped by shear, surfaces, local cofactors, and transient complex formation. We highlight translational proof that interface blockade works in humans, focusing on VWF A1–GPIbα inhibition and GPVI-directed strategies as exemplars of lesion- and shear-dependent antiplatelet therapy. We then survey platelet adhesion and activation PPIs (VWF–GPIb, collagen–GPVI, and αIIbβ3–ligand interactions), thromboinflammatory interfaces (including P-selectin–PSGL-1 and CLEC-2–podoplanin), and opportunities to target coagulation complex assembly and thrombin exosites without directly inhibiting catalytic active sites. A modality-focused section links interface class to therapeutic format—antibodies/nanobodies, aptamers with antidotes, peptides and macrocycles, and small-molecule PPI inhibitors—and summarizes trade-offs in reversibility, half-life, manufacturability, and immunogenicity. Finally, we discuss assays that preserve interface biology (whole-blood flow systems, microfluidics, thrombin generation, and clot mechanics) and propose clinical positioning and trial endpoints for context-gated mechanisms. By targeting the contacts that assemble and stabilize thrombi, PPI disruption offers a pragmatic route toward more selective, potentially bleeding-sparing antithrombotic therapy and a roadmap for next-generation pipeline development.
Core-binding factor (CBF) leukemias, including inv(16) AML, involve RUNX1/CBFβ chromosomal rearrangements that generate oncogenic fusion proteins. In inv(16) AML, the CBFβ–SMMHC fusion (CBFB–MYH11) dominantly perturbs RUNX1 by sequestering it in aberrant, high-affinity complexes. Structural studies reveal that CBFβ–SMMHC binds the RUNX1 Runt domain with higher affinity than wild-type CBFβ, aided by a second RUNX1-binding site in its SMMHC tail. This altered interface underlies the fusion’s dominant-negative disruption of RUNX1 target-gene regulation. Chemical probes have been developed to disrupt this interface; notably, the bivalent inhibitor AI-10-49 selectively binds CBFβ–SMMHC, displacing RUNX1 and restoring RUNX1 transcriptional function. AI-10-49 delays leukemia progression in murine inv(16) models and induces apoptosis in human inv(16) AML cells. Mechanistically, uncoupling RUNX1 from CBFβ–SMMHC liberates RUNX1 to repress oncogenic programs: for example, RUNX1 rebinds distal MYC enhancers and recruits polycomb factors (RING1B) in place of SWI/SNF (BRG1) to silence MYC, triggering leukemia cell apoptosis. These chromatin and transcriptional consequences underscore how CBFβ–SMMHC sustains leukemic transcriptional programs. Importantly, combining CBFβ–SMMHC inhibitors with BET bromodomain inhibitors synergistically eradicates inv(16) leukemia in preclinical models. Together, these insights into the structural basis and functional role of the CBFβ–SMMHC–RUNX1 interface highlight protein–protein interaction disruption as a promising translational strategy in core-binding factor leukemia therapy.
