Hybrid Erythrocyte Liposomes: Functionalized Red Blood Cell Membranes for Molecule Encapsulation

The modification of erythrocyte membrane properties provides a new tool towards improved drug delivery and biomedical applications. The fabrication of hybrid erythrocyte liposomes is presented by doping red blood cell membranes with synthetic lipid molecules of different classes (PC, PS, PG) and different degrees of saturation (14:0, 16:0-18:1). The respective solubility limits are determined, and material properties of the hybrid liposomes are studied by a combination of X-ray diffraction, epi-fluorescent microscopy, dynamic light scattering (DLS), Zeta potential, UV-vis spectroscopy, and Molecular Dynamics (MD) simulations. Membrane thickness and lipid orientation can be tuned through the addition of phosphatidylcholine lipids. The hybrid membranes can be fluorescently labelled by incorporating Texas-red DHPE, and their charge modified by incorporating phosphatidylserine and phosphatidylglycerol. By using fluorescein labeled dextran as an example, it is demonstrated that small molecules can be encapsulated into these hybrid liposomes

Membrane-Accelerated Amyloid-β Aggregation and Formation of Cross-β Sheets

Amyloid- β aggregates play a causative role in Alzheimer’s disease. These aggregates are a product of the physical environment provided by the basic neuronal membrane, composed of a lipid bilayer. The intrinsic properties of the lipid bilayer allow amyloid- β peptides to nucleate and form well-ordered cross- β sheets within the membrane. Here, we correlate the aggregation of the hydrophobic fragment of the amyloid- β protein, A β 25 - 35 , with the hydrophobicity, fluidity, and charge density of a lipid bilayer. We summarize recent biophysical studies of model membranes and relate these to the process of aggregation in physiological systems

Membrane-Accelerated Amyloid-β Aggregation and Formation of Cross-β Sheets

Amyloid- β aggregates play a causative role in Alzheimer’s disease. These aggregates are a product of the physical environment provided by the basic neuronal membrane, composed of a lipid bilayer. The intrinsic properties of the lipid bilayer allow amyloid- β peptides to nucleate and form well-ordered cross- β sheets within the membrane. Here, we correlate the aggregation of the hydrophobic fragment of the amyloid- β protein, A β 25 - 35 , with the hydrophobicity, fluidity, and charge density of a lipid bilayer. We summarize recent biophysical studies of model membranes and relate these to the process of aggregation in physiological systems

Glucose Can Protect Membranes against Dehydration Damage by Inducing a Glassy Membrane State at Low Hydrations

The physical effects of small sugars on membranes have been studied for decades, primarily because of their membrane stabilization in cold or dehydrated environments. We studied the effects of up to 20 mol% glucose in bilayers made of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) at low hydration by combining X-ray diffraction and Molecular Dynamics (MD) simulations. In agreement with previous studies, we observe membrane thinning at low and membrane thickening at high sugar concentrations. Glucose was found to preferentially localize to the outer head region of phospholipid bilayers at all concentrations, and partitioning of sugar in the membranes was found to monotonically increase with increasing sugar concentration. While the number of gauche defects in the lipid acyl tails and the lipid packing in the presence of sugar resembled values of a fluid lipid bilayer, tail dynamics, as assessed by autocorrelation of the carbon atoms in the phospholipid tails, were slowed down significantly with increasing glucose content. Thus, our findings suggest that sugar leads to a a disordered, glassy state of the hydrophobic membrane core. The non-monotonic effect of glucose on membrane thickness was found to be an effect of fluidification at low concentrations and decreased interdigitation in the higher sugar concentration regime

Predicting non-muscle invasive bladder cancer outcomes using artificial intelligence: a systematic review using APPRAISE-AI

Abstract Accurate prediction of recurrence and progression in non-muscle invasive bladder cancer (NMIBC) is essential to inform management and eligibility for clinical trials. Despite substantial interest in developing artificial intelligence (AI) applications in NMIBC, their clinical readiness remains unclear. This systematic review aimed to critically appraise AI studies predicting NMIBC outcomes, and to identify common methodological and reporting pitfalls. MEDLINE, EMBASE, Web of Science, and Scopus were searched from inception to February 5th, 2024 for AI studies predicting NMIBC recurrence or progression. APPRAISE-AI was used to assess methodological and reporting quality of these studies. Performance between AI and non-AI approaches included within these studies were compared. A total of 15 studies (five on recurrence, four on progression, and six on both) were included. All studies were retrospective, with a median follow-up of 71 months (IQR 32−93) and median cohort size of 125 (IQR 93−309). Most studies were low quality, with only one classified as high quality. While AI models generally outperformed non-AI approaches with respect to accuracy, c-index, sensitivity, and specificity, this margin of benefit varied with study quality (median absolute performance difference was 10 for low, 22 for moderate, and 4 for high quality studies). Common pitfalls included dataset limitations, heterogeneous outcome definitions, methodological flaws, suboptimal model evaluation, and reproducibility issues. Recommendations to address these challenges are proposed. These findings emphasise the need for collaborative efforts between urological and AI communities paired with rigorous methodologies to develop higher quality models, enabling AI to reach its potential in enhancing NMIBC care