Search Results (56)

Antimicrobial peptides (AMPs) are a primary defense against pathogens. Here, we examined the interaction of two BP100 analogs, R²R⁵-BP100 (where Arg substitutes Lys 2 and 5) and R²R⁵-BP100-A-NH-C₁₆ (where an Ala and a C₁₆ hydrocarbon chain are added to the R²R⁵-BP100 C-terminus), with membrane models. Large unilamellar vesicles (LUVs) and giant unilamellar vesicles (GUVs) were prepared with the major lipids in Gram-positive (GP) and Gram-negative (GN) bacteria, as well as red blood cells (RBCs). Fluorescence data, dynamic light scattering (DLS), and zeta potential measurements revealed that upon achieving electroneutrality through peptide binding, vesicle aggregation occurred. Circular dichroism (CD) spectra corroborated these observations, and upon vesicle binding, the peptides acquired α-helical conformation. The peptide concentration, producing a 50% release of carboxyfluorescein (C₅₀) from LUVs, was similar for GP-LUVs. With GN and RBC-LUVs, C₅₀ decreased in the following order: BP100 > R²R⁵-BP100 > R²R⁵BP100-A-NH-C₁₆. Optical microscopy of GP-, GN-, and RBC-GUVs revealed the rupture or bursting of the two former membranes, consistent with a carpet mechanism of action. Using GUVs, we confirmed RBC aggregation by BP100 and R²R⁵-BP100. We determined the minimal inhibitory concentrations (MICs) of peptides for a GN bacterium (Escherichia coli (E. coli)) and two GP bacteria (two strains of Staphylococcus aureus (S. aureus) and one strain of Bacillus subtilis (B. subtilis)). The MICs for S. aureus were strain-dependent. These results demonstrate that Lys/Arg replacement can improve the parent peptide’s antimicrobial activity while increasing hydrophobicity renders the peptide less effective and more hemolytic. Full article

Peptides designed to interfere with specific steps of viral infection mechanisms have shown promising antiviral potential. In this study, we investigated the ability of a synthetic peptide (peptide 303), derived from the fusion protein sequence of the Infectious Salmon Anemia Virus (ISAV), to inhibit membrane fusion mediated by the ISAV fusion peptide (ISAV-FP1). To assess this, we employed a model membrane system consisting of large unilamellar vesicles (LUVs) composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), dipalmitoylphosphatidylcholine (DPPC), and cholesterol. Membrane fusion kinetics were monitored via R18 fluorescence dequenching. Additionally, the interaction of peptide 303 with lipid membranes was evaluated using fluorescence anisotropy measurements. The potential direct interaction between peptide 303 and ISAV-FP1 was further examined through Förster Resonance Energy Transfer (FRET) assays. Our results demonstrate that peptide 303 effectively inhibits ISAV-FP1-mediated membrane fusion. Furthermore, peptide 303 was shown to interact with lipid bilayers and with ISAV-FP1 itself. These findings suggest a dual inhibitory mechanism in which peptide 303 both prevents ISAV-FP1 binding to the membrane and directly interacts with the fusion peptide, thereby disrupting its fusogenic activity. Full article

Background: Huntington’s Disease (HD) is a neurodegenerative disorder caused by an abnormal extension of a CAG repeat stretch located in the exon 1 of the HTT (IT15) gene, leading to production of a mutated and misfolded Huntingtin protein (muHTT) with an abnormally elongated polyglutamine (polyQ) region. This mutation causes muHTT to oligomerize and aggregate in the brain, particularly in the striatum and cortex, causing alterations in intracellular trafficking, caspase activation, and ganglioside metabolism, ultimately leading to neuronal damage and death and causing signs and symptoms such as chorea and cognitive dysfunction. Currently, there is no available cure for HD patients; hence, there is a strong need to look for effective therapies. Methods: This study aims to investigate the efficacy of siRNA-containing nano-engineered lipopolymers in selectively silencing the HTT expression in a neuronal model expressing a chimeric protein formed by the human mutated exon 1 of the HTT gene, tagged with GFP. Toxicity of lipopolymers was assessed using MTT assay, while efficacy of silencing was monitored using qRT-PCR, as well as Western blotting/flow cytometry. Changes in muHTT-GFP aggregation were observed using fluorescence microscopy and image analyses. Results: Here, we show that engineered lipopolymers can be used as delivery vehicles for specific siRNAs, decreasing the transcription of the mutated gene, as well as the muHTT protein production and aggregation, with Leu-Fect C being the most effective candidate amongst the assessed lipopolymers. Conclusions: Our findings have profound implications for genetic disorder therapies, highlighting the potential of nano-engineered materials for silencing mutant genes and facilitating molecular transfection across cellular barriers. This successful in vitro study paves the way for future in vivo investigations with preclinical models, offering hope for previously considered incurable diseases such as HD. Full article

A set of procedures was developed for the simple synthesis of phytyl phenolipids, which resulted in high yields (70–95%) of phytyl esters of caffeic, protocatechuic, homoprotocatechuic, and dihydrocaffeic acids. Initial characterization revealed that these new compounds exhibited similar radical scavenging activity and liposolubility to α-tocopherol, a key antioxidant present in membranes. Cyclic voltammetry analysis indicated that the phytyl derivatives had lower anodic peak potentials compared to the original phenolic acids, with electron transfer following an adsorption-controlled mechanism. In phosphatidylcholine large unilamellar vesicles (LUVs), phytyl esters demonstrated remarkable efficiency in preventing liposome autoxidation when compared to α-tocopherol. Despite their strong radical scavenging capacity and membrane penetration ability, the antioxidant effectiveness of the phytyl esters in liposomes was influenced by the structure of their polyphenolic moiety. These new compounds are considered promising candidates for future pharmacological applications against oxidative stress in lipoproteins and cells, warranting further evaluation of their antioxidant and anti-inflammatory effects in cellular models and in vivo. Full article

Background: The use of antimicrobial peptides (AMPs) as biotechnological tools is an area of growing interest in the research that seeks to improve crop defense. SmAP_α1–21 and SmAP_γ27–44 were previously reported to inhibit Fusarium graminearum, permeabilize the plasma membrane and induce cytoplasmic disorganization. To exert its activity, SmAP_α1–21 initially enters through the basal and apical cells of F. graminearum conidia and then displays a general but non-homogeneous distribution in the cytoplasm of all conidial cells, in contrast. Methods: We analyzed, focusing on membrane interaction, the mode of action of SmAP_γ27–44, a peptide based on the γ-core of defensins DefSm2-D and DefSm3, and SmAP_α1–21, based on the α-core of DefSm2-D. Additionally, we compared the behavior of SmAP_α1–21 with that of SmAP3_α1–21 based on DefSm3 but with no activity against F. graminearum. Results: In this study, we showed that SmAP_γ27–44 enters the cells with discrete intracellular localization. Furthermore, both peptides disrupted the plasma membrane, but with different modes of action. When large unilamellar liposomes (LUVs) containing phosphatidic acid and ergosterol were used as a filamentous fungal plasma membrane model, SmAP_γ27–44 strongly induced aggregation concomitantly with the solubilization of the liposomes and showed the maximal insertion of its tryptophan moiety into the membrane’s hydrophobic interior. In comparison, SmAP_α1–21 showed a high effect on the ζ potential of anionic vesicles, vesicle aggregation capacity after reaching a concentration threshold, and moderate transfer of tryptophan to the membrane. SmAP3_α1–21, on the other hand, showed poor superficial adsorption to liposomes. Conclusions: In view of our results, a cell penetration peptide-like effect was pictured for the γ-core defensin-derived peptide and a classical AMP action was observed for the α-core defensin-derived one. Full article

In the last decades, numerous dendrimers with a variety of potential biomedical applications have been developed and investigated. The aim of the present study was to evaluate the molecular mechanisms of interaction between two dendrimers with proven antibacterial activity (4-N,N-dimethylamino-1,8-naphthalimide (Dab) and 3-bromo-Dab (Dab-Br)) and POPC (1-palmitoyl-2-oleoylphosphatidylcholine) model membranes (monolayers and liposomes). The pressure-area isotherms and the compressional modulus of the monolayers revealed that Dab is likely to penetrate the hydrophobic region of POPC, whereas Dab-Br inserts mainly into the lipid headgroup area. This assumption was confirmed by FTIR-ATR of POPC liposomes containing Dab and Dab-Br dendrimers. In addition, Dab induced a higher lipid order in POPC large unilamellar vesicles (LUVs) compared to Dab-Br. Moreover, both dendrimers changed the negative zeta potential of POPC vesicles to positive values, with slightly higher effect of Dab-Br, indicating electrostatic interactions between the lipid headgroups and dendrimers. Furthermore, Dab was able to reduce the average POPC LUVs’ size, unlike Dab-Br. The visualization of giant unilamellar vesicles revealed that the increasing dendrimer concentration induced model membrane shrinking and complete disintegration, which was more prominent for Dab. Based on the experimental results, new fundamental knowledge about the destabilizing effect of dendrimers on model lipid membranes will be acquired with a focus on their application in pharmacology and clinical practice. Full article

Current lung cancer screening guidelines in the United States fail to identify many individuals at risk of developing the disease. Additionally, existing healthcare infrastructure has been leveraged to establish IPN clinics, a promising approach to addressing the limitations of current screening guidelines. Early-stage lung cancer is frequently diagnosed because of the incidental detection of pulmonary nodules on clinically indicated chest CT scans, particularly in the absence of formal screening programs. While artificial intelligence (AI) systems for lung cancer detection have demonstrated significant advancements in medicine, their clinical validation in screening settings remains limited. This review will discuss the pivotal trials underpinning the United States Preventive Services Task Force (USPSTF) recommendations for lung cancer screening, which have shaped the current guidelines for at-risk populations. We will explore recent studies investigating the role of AI in enhancing lung cancer screening efforts, highlighting how AI has the potential to improve early detection, streamline workflows, and reduce false positives and negatives in screening processes. This review will present the lung cancer screening rates at our institution, with a specific focus on the validation and integration of AI-driven technologies into our established screening programs. Using AI algorithms, we have validated enhanced detection capabilities through retrospective analysis of historical patient data, demonstrating significant improvements in identifying high-risk individuals and early-stage malignancies. These AI models, validated through rigorous cross-validation methods and clinical trials, have proven to outperform traditional screening approaches in sensitivity and specificity. The integration of these AI technologies within the lung cancer screening framework not only optimizes existing programs but also expands access to screening, improving early detection rates and ultimately leading to better patient outcomes. Through continuous validation and refinement, we aim to solidify AI’s role in transforming lung cancer detection and patient care. Through ongoing validation and implementation, AI can play a crucial role in transforming lung cancer screening practices, ultimately contributing to earlier diagnosis and improved patient survival. Full article

Microfluidics is a technology that manipulates liquids on the scales ranging from microliters to femtoliters. Such low volumes require precise control over pressures that drive their flow into the microfluidic chips. This article describes a custom-built pressure controller for driving microfluidic chips. The pressure controller features piezoelectrically controlled pressure regulation valves. As an open-source system, it offers high customizability and allows users to modify almost every aspect. The cost is roughly a third of what similar, alternative, commercially available piezoelectrically controlled pressure regulators could be purchased for. The measured output pressure values of the device vary less than 0.7% from the device’s reported pressure values when the requested pressure is between −380 and 380 mbar. Importantly, the output pressure the device creates fluctuates only ±0.2 mbar when the pressure is cycled between 10 and 500 mbar. The pressure reading accuracy and stability validation suggest that the device is highly feasible for many advanced (low-pressure) microfluidic applications. Here, we compare the main features of our device to commercially and non-commercially available alternatives and further demonstrate the device’s performance and accessibility in successful microfluidic hydrodynamic focusing (MHF)-based synthesis of large unilamellar vesicles (LUVs). Full article

The properties of the large unilamellar vesicles (LUVs) from 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine (DMPC), modified by lipopolysaccharides (LPS) from Salmonella enterica sv. Enteritidis, which mimics Gram-negative bacteria, were studied by various physical methods. LPS, in the range of 0/20/50 % w/w relative to the lipid, had a regulatory role in the structure of the LUVs toward the lower size, low polydispersity, and over-a-month size stability due to the lower negative zeta potential. The addition of LPS resulted in increased density, which determined the ultrasound velocity and the specific adiabatic compressibility. In a 0.5/1/2 mg/mL concentration range, the total lipid content did not significantly affect the size of LUVs and influenced the density-related attributes similarly to the LPS content. A positive correlation was found between temperature and vesicle size, and a negative correlation was found between temperature and density and compressibility—except for the anomaly behavior at 25 °C, around the melting point of DMPC. Full article

Drug delivery systems play a pivotal role in targeted pharmaceutical transport and controlled release at specific sites. Liposomes, commonly used as drug carriers, constitute a fundamental part of these systems. Moreover, the drug–liposome model serves as a robust platform for investigating interaction processes at both cellular and molecular levels. To advance our understanding of drug carrier uptake mechanisms, we employed fluorescence lifetime imaging microscopy (FLIM) and fluorescence correlation spectroscopy (FCS), leveraging the unique benefits of two-photon (2P) excitation. Our approach utilized giant unilamellar vesicles (GUVs) as a simplified model system for cell membranes, labelled with the amphiphilic fluorescent dye 3,3′-dioctadecyloxa-carbocyanine (DiOC₁₈(3)). Additionally, large unilamellar vesicles (LUVs) functioned as a drug carrier system, incorporating the spectrally distinct fluorescent sulforhodamine 101 (SRh101) as a surrogate drug. The investigation emphasized the diverse interactions between GUVs and LUVs based on the charged lipids employed. We examined the exchange kinetics and structural alterations of liposome carriers during the uptake process. Our study underscores the significance of employing 2P excitation in conjunction with FLIM and FCS. This powerful combination offers a valuable methodological approach for studying liposome interactions, positioning them as an exceptionally versatile model system with a distinct technical advantage. Full article

Giant unilamellar vesicles (GUVs) are membrane models used to study membrane properties. Electroformation is one of the methods used to produce GUVs. During electroformation protocol, dry lipid film is formed. The drying of the lipid film induces the cholesterol (Chol) demixing artifact, in which Chol forms anhydrous crystals which do not participate in the formation of vesicles. This leads to a lower Chol concentration in the vesicle bilayers compared to the Chol concentration in the initial lipid solution. To address this problem, we propose a novel electroformation protocol that includes rapid solvent exchange (RSE), plasma cleaning, and spin-coating methods to produce GUVs. We tested the protocol, focusing on vesicles with a high Chol content using different spin-coating durations and vesicle type deposition. Additionally, we compared the novel protocol using completely dry lipid film. The optimal spin-coating duration for vesicles created from the phosphatidylcholine/Chol mixture was 30 s. Multilamellar vesicles (MLVs), large unilamellar vesicles (LUVs) obtained by the extrusion of MLVs through 100 nm membrane pores and LUVs obtained by extrusion of previously obtained LUVs through 50 nm membrane pores, were deposited on an electrode for 1.5/1 Chol/phosphatidylcholine (POPC) lipid mixture, and the results were compared. Electroformation using all three deposited vesicle types resulted in a high GUV yield, but the deposition of LUVs obtained by the extrusion of MLVs through 100 nm membrane pores provided the most reproducible results. Using the deposition of these LUVs, we produced high yield GUVs for six different Chol concentrations (from 0% to 71.4%). Using a protocol that included dry lipid film GUVs resulted in lower yields and induced the Chol demixing artifact, proving that the lipid film should never be subjected to drying when the Chol content is high. Full article

The linear undecapeptide KKLFKKILKYL-NH₂ (BP100) highlights for its antibacterial activity against Gram-negative bacteria and its low toxicity. These excellent biological properties prompted the investigation of its mechanism of action, which were undertaken using spectroscopic techniques, biophysical analysis, microscopy, and molecular dynamic simulations. Studies were conducted in different membrane environments, such as anionic, zwitterionic, and mixed membranes, as well as in vesicles (LUVs and GUVs) and bacteria. The findings suggest that BP100 exhibits a preference for anionic membranes, and its mechanism of action involves charge neutralization and membrane permeabilization. In these membranes, BP100 transitions from an unstructured state in water to an α-helix with the axis parallel to the surface. MD simulations suggest that after electrostatic interaction with the membrane, BP100 flips, facilitating the insertion of its hydrophobic face into the membrane bilayer. Thus, BP100 adopts an almost vertical transmembrane orientation with lysine side chains snorkelling on both sides of the membrane. As a result of the rotation, BP100 induces membrane thinning and slow lipid diffusion and promotes water penetration, particularly in anionic lipid membranes. These investigations pointed towards a carpet-like mechanism and are aligned with the biological activity profile described for BP100. This review covers all the studies carried out on the mechanism of action of BP100 published between 2009 and 2023. Full article

Over the last decade, treatment paradigms for breast cancer have undergone a renaissance, particularly in hormone-receptor-positive/HER2-negative breast cancer. These revolutionary therapies are based on the selective targeting of aberrancies within the cell cycle. This shift towards targeted therapies has also changed the landscape of disease monitoring. In this article, we will review the fundamentals of cell cycle progression in the context of the new cyclin-dependent kinase inhibitors. In addition to discussing the currently approved cyclin-dependent kinase inhibitors for breast cancer, we will explore the ongoing development and search for predictive biomarkers and modalities to monitor treatment. Full article

This research proposes a deep learning method for classifying student behavior in classrooms that follow the professional learning community teaching approach. We collected data on five student activities: hand-raising, interacting, sitting, turning around, and writing. We used the sum of absolute differences (SAD) in the LUV color space to detect scene changes. The K-means algorithm was then applied to select keyframes using the computed SAD. Next, we extracted features using multiple pretrained deep learning models from the convolutional neural network family. The pretrained models considered were InceptionV3, ResNet50V2, VGG16, and EfficientNetB7. We leveraged feature fusion, incorporating optical flow features and data augmentation techniques, to increase the necessary spatial features of selected keyframes. Finally, we classified the students’ behavior using a deep sequence model based on the bidirectional long short-term memory network with an attention mechanism (BiLSTM-AT). The proposed method with the BiLSTM-AT model can recognize behaviors from our dataset with high accuracy, precision, recall, and F1-scores of 0.97, 0.97, and 0.97, respectively. The overall accuracy was 96.67%. This high efficiency demonstrates the potential of the proposed method for classifying student behavior in classrooms. Full article