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Biophysica

Biophysica is an international, peer-reviewed, open access journal on applying the methods of physics, chemistry, and math to study biological systems, published bimonthly online by MDPI.

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All Articles (256)

Lipid-based delivery systems (LDS), including lipid nanoparticles (LNPs) and liposomes, have become indispensable tools in modern biomedicine owing to their biocompatibility, capacity to encapsulate diverse therapeutic agents, and potential for targeted delivery. Despite their clinical success, conventional batch-based manufacturing methods are hindered by variability, limited scalability, and complex processing steps, slowing their broader translation. Microfluidic technologies offer a transformative solution by enabling precise fluid handling, rapid mixing, and reproducible production of LDS with tunable physicochemical attributes such as particle size, lamellarity, and drug-loading efficiency. This review highlights advances in microfluidic design strategies, including hydrodynamic flow focusing, staggered herringbone mixers, and toroidal micromixers, and evaluates how critical parameters such as flow rate, solvent composition, and lipid concentration influence LDS performance. Furthermore, we discuss the application of microfluidics in drug delivery, nucleic acid therapeutics, and vaccine platforms, underscoring its role in improving scalability, quality control, and clinical translation. Finally, we examine current challenges, including throughput limitations and solvent handling, while outlining future directions for integrating emerging materials and additive manufacturing to optimize LDS fabrication. Collectively, microfluidic platforms provide a promising pathway for next-generation lipid nanomedicines with enhanced precision, reproducibility, and therapeutic efficacy.

10 March 2026

Various types of microfluidic mixers: (A) T-junction mixing. (B) V-junction mixing. (C) Baffle micromixer. (D) Staggered herringbone micromixer. (E) Bifurcation toroidal micromixer. Figure created using BioRender.

Biophysical Characterization and In Vitro Evaluation of Doxycycline-Loaded Egg Yolk Phospholipid Liposomes

  • Baatarmanlai Dorjgochoo,
  • Delgernaran Gomboragchaa and
  • Enkhtaivan Erdene
  • + 5 authors

Antimicrobial resistance represents not only a biological challenge but also a physicochemical limitation associated with antibiotic transport, membrane interaction, and local availability. In this preliminary study, a liposome-encapsulated doxycycline delivery system was developed using egg yolk-derived phospholipids, and its biophysical properties and release behavior were investigated. Phospholipids were isolated from egg yolk and used to prepare doxycycline-loaded liposomes via a thin-film hydration method combined with freeze–thaw processing. Liposome morphology was characterized by atomic force microscopy (AFM), while encapsulation efficiency was quantified by reversed-phase high-performance liquid chromatography (RP-HPLC). In vitro release kinetics were evaluated using a dialysis diffusion method, and antibacterial activity was assessed as a functional indicator of drug availability using minimum inhibitory concentration (MIC) assays against Staphylococcus aureus and methicillin-resistant S. aureus (MRSA). The prepared liposomes exhibited morphology with diameters of approximately 153 nm (PDI = 0.223). The encapsulation efficiency of doxycycline hyclate was 8.41%, and complete drug release was achieved within 48 h. Liposome-encapsulated doxycycline demonstrated a two-fold reduction in MIC values compared with free doxycycline. These findings offer preliminary insight to support further optimization and expanded investigation of liposome-encapsulated antibiotic delivery systems.

28 February 2026

AFM characterization of liposomes. (A) Liposome structure, (B) 3D topography, (C) spatial distribution, and (D) height and diameter measurements.

Chemical Characterization and Antiproliferative Evaluation of Compounds Isolated from White Shrimp (Penaeus vannamei) By-Products

  • Héctor Enrique Trujillo-Ruiz,
  • Dania Guadalupe Leal-Rodríguez and
  • Carmen María López-Saiz
  • + 6 authors

Cancer is the second leading cause of death worldwide, requiring more effective treatments. By-products from the white shrimp (Penaeus vannamei) are a promising source of bioactive compounds. Compounds with antiproliferative activity were isolated and identified in exoskeleton and cephalothorax extracts. The hexane extract of the exoskeleton reduced the viability of Human Prostate Carcinoma cell line (22Rv1) to 40.6% without toxicity in Adult Retinal Pigment Epithelium-19 (ARPE-19). Among the 19 fractions obtained, H3 reduced cell viability to 20.78%. Spectroscopic analysis identified bis(2-ethylhexyl) terephthalate, neoxanthin, and violaxanthin. Fluorescence microscopy showed morphological alterations. These findings demonstrate in vitro antiproliferative activity of compounds derived from shrimp by-products and support further studies to elucidate their mechanisms of action and evaluate their potential relevance in cancer prevention or therapeutic research.

25 February 2026

22Rv1 viability exposed to exoskeleton hexane and acetone extracts at different concentrations (25–200 μg/mL). Different letters above the bars indicate significant differences (p ≤ 0.05).

Traditional drug design methods based on trial and error are costly and inefficient. The computational approach ToSS-MoDE (Topological Substructural Molecular Design) offers an alternative by linking molecular descriptors to biological activity. To develop a QSAR model to predict the anti-inflammatory activity of synthetic and natural compounds using weighted spectral moments. Spectral moments (µk) were calculated from the adjacency matrix between bonds for 410 compounds (180 active and 230 inactive). MODESLAB software (MICROSOFT OFFICE 365) was used to generate descriptors, and Linear Discriminant Analysis (LDA) was applied to classify activity. The model was validated with an external series of 62 compounds. Results. The model showed an overall classification of 91.59% in the training series and 90.2% in validation. The spectral moments µ0, µ3, µ4, and µ5 were the most significant. Diosgenin, a natural metabolite, showed potential anti-inflammatory activity (classification probability: 81%). The model showed strong training performance (91.7% accuracy) and promising external performance for confidently classified compounds. All datasets, descriptor-generation settings, coefficients, and posterior probabilities are fully described in the main text to ensure full reproducibility.

24 February 2026

Representation of the isocontribution zones of a molecule.

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Biophysica - ISSN 2673-4125