Publications

The Bin/amphiphysin/Rvs (BAR) superfamily proteins have a crescent binding domain and bend biomembranes along the domain axis. However, their anisotropic bending rigidities and spontaneous curvatures have not been experimentally determined. Here, we estimated these values from the bound protein densities on tethered vesicles using a mean-field theory of anisotropic bending energy and orientation-dependent excluded volume. The dependence curves of the protein density on the membrane curvature are fitted to the experimental data for the I-BAR and N-BAR domains reported by C. Prevost et al. Nat. Commun., 2015, 6, 8529 and F.-C. Tsai et al. Soft Matter, 2021, 17, 4254-4265, respectively. For the I-BAR domain, all three density curves of different chemical potentials exhibit excellent fits with a single parameter set of anisotropic bending energy. When the classical isotropic bending energy is used instead, one of the curves can be fitted well, but the others exhibit large deviations. In contrast, for the N-BAR domain, two curves are not well fitted simultaneously the anisotropic model, although it is significantly improved compared to the isotropic model. This deviation likely suggests a cluster formation of the N-BAR domains.

JTD Keywords: Membrane-mediated interactions,elastic properties,bar,shape,mechanisms,inclusions,generation,polymers,driven,bod

Tumor secreted extracellular vesicles (EVs) are potent intercellular signaling platforms. They are responsible for the accommodation of the premetastatic niche (PMN) to support cancer cell engraftment and metastatic growth. However, complex cancer cell composition within the tumor increases also the heterogeneity among cancer secreted EVs subsets, a functional diversity that has been poorly explored. This phenomenon is particularly relevant in highly plastic and heterogenous triple-negative breast cancer (TNBC), in which a significant representation of malignant cancer stem cells (CSCs) is displayed. Herein, we selectively isolated and characterized EVs from CSC or differentiated cancer cells (DCC; EVsCSC and EVsDCC , respectively) from the MDA-MB-231 TNBC cell line. Our results showed that EVsCSC and EVsDCC contain distinct bioactive cargos and therefore elicit a differential effect on stromal cells in the TME. Specifically, EVsDCC activated secretory cancer associated fibroblasts (CAFs), triggering IL-6/IL-8 signaling and sustaining CSC phenotype maintenance. Complementarily, EVsCSC promoted the activation of α-SMA+ myofibroblastic CAFs subpopulations and increased the endothelial remodeling, enhancing the invasive potential of TNBC cells in vitro and in vivo. In addition, solely the EVsCSC mediated signaling prompted the transformation of healthy lungs into receptive niches able to support metastatic growth of breast cancer cells.© 2023 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

JTD Keywords: chemoresistance, dormancy, drives, extracellular vesicles, invasion, plasticity, premetastatic niche, triple-negative breast cancer, tumor microenvironment, Cancer cell plasticity, Extracellular vesicles, Fibroblasts, Premetastatic niche, Triple-negative breast cancer, Tumor microenvironment

Individual biohybrid microrobots have the potential to perform biomedical in vivo tasks such as remote-controlled drug and cell delivery and minimally invasive surgery. This work demonstrates the formation of biohybrid sperm-templated clusters under the influence of an external magnetic field and essential functionalities for wireless actuation and drug delivery. Ferromagnetic nanoparticles are electrostatically assembled around dead sperm cells, and the resulting nanoparticle-coated cells are magnetically assembled into three-dimensional biohybrid clusters. The aim of this clustering is threefold: First, to enable rolling locomotion on a nearby solid boundary using a rotating magnetic field; second, to allow for noninvasive localization; third, to load the cells inside the cluster with drugs for targeted therapy. A magneto-hydrodynamic model captures the rotational response of the clusters in a viscous fluid, and predicts an upper bound for their step-out frequency, which is independent of their volume or aspect ratio. Below the step-out frequency, the rolling velocity of the clusters increases nonlinearly with their perimeter and actuation frequency. During rolling locomotion, the clusters are localized using ultrasound images at a relatively large distance, which makes these biohybrid clusters promising for deep-tissue applications. Finally, we show that the estimated drug load scales with the number of cells in the cluster and can be retained for more than 10 h. The aggregation of microrobots enables them to collectively roll in a predictable way in response to an external rotating magnetic field, and enhances ultrasound detectability and drug loading capacity compared to the individual microrobots. The favorable features of biohybrid microrobot clusters place emphasis on the importance of the investigation and development of collective microrobots and their potential for in vivo applications.

JTD Keywords: drug delivery, magnetic actuation, microrobot aggregation, sperm, Driven, Drug delivery, Magnetic actuation, Magnetotactic bacteria, Microrobot aggregation, Microrobots, Motion, Movement, Propulsion, Sperm, Sphere, Ultrasound, Wall

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice. Author

JTD Keywords: biomedical measurement, chronic obstructive pulmonary disease, couplings, diaphragm, disease severity, efficiency, electromyography, exacerbations, healthy volunteers, inspiratory muscles, loading, mechanomyography, obstructive pulmonary-disease, pressure measurement, protocols, respiratory mechanics, respiratory muscles, responsiveness, spirometry, stimulation, volume measurement, At rests, Biomedical measurement, Biomedical measurements, Chronic obstructive pulmonary disease, Couplings, Disease severity, Efficiency ratio, Electromyography, Healthy subjects, Healthy volunteers, Loading, Mechanical efficiency, Mechanomyogram, Muscle, Muscles, Neural respiratory drive, Noninvasive medical procedures, Pressure measurement, Protocols, Pulmonary diseases, Surface electromyogram, Volume measurement

We studied how anisotropic proteins are orientationally ordered and change the radius of membrane tubes using mean-field theory with an orientation-dependent excluded volume interaction.

JTD Keywords: bar, density, driven, generation, inclusions, invagination, mechanisms, monte-carlo, tubulation, Mediated aggregation

Background: Opioid-related deaths are increasing globally. Respiratory complications of opioid use and underlying respiratory disease in people with Opioid Use Disorder (OUD) are potential contributory factors. Individual variation in susceptibility to overdose is, however, incompletely understood. This study investigated the prevalence of respiratory depression (RD) in OUD treatment and compared this to patients with chronic obstructive pulmonary disease (COPD) of equivalent severity. We also explored the contribution of opioid agonist treatment (OAT) dosage, and type, to the prevalence of RD. Methods: There were four groups of participants: 1) OUD plus COPD (‘OUD-COPD’, n = 13); 2) OUD without COPD (‘OUD’, n = 7); 3) opioid-naïve COPD patients (‘COPD'n = 13); 4) healthy controls (‘HC'n = 7). Physiological indices, including pulse oximetry (SpO2%), end-tidal CO2 (ETCO2), transcutaneous CO2 (TcCO2), respiratory airflow and second intercostal space parasternal muscle electromyography (EMGpara), were recorded continuously over 40 min whilst awake at rest. Significant RD was defined as: SpO2%< 90% for > 10 s, ETCO2 per breath > 6.6 kPa, TcCO2 overall mean > 6 kPa, respiratory pauses > 10 s Results: At least one indicator was observed in every participant with OUD (n = 20). This compared to RD episode occurrence in only 2/7 HC and 2/13 COPD participants (p < 0.05,Fisher's exact test). The occurrence of RD was similar in OUD participants prescribed methadone (n = 6) compared to those prescribed buprenorphine (n = 12). Conclusions: Undetected RD is common in OUD cohorts receiving OAT and is significantly more severe than in opioid-naïve controls. RD can be assessed using simple objective measures. Further studies are required to determine the association between RD and overdose risk. © 2022 Elsevier B.V.

JTD Keywords: buprenorphine, comorbidity, deaths, drive, heroin, lung disease, opioid substitution treatment, opioids, overdose, pulse oximetry, respiratory depression, risk, Acute exacerbations, Comorbidity, Lung disease, Opioid substitution treatment, Opioids, Overdose, Respiratory depression

[Figure: see text].

JTD Keywords: activation, cell extrusion, contraction, drives, homeostasis, interface, junctions, kinase, tension, Adhesion, Article, Cell membranes, Chemical activation, Cytology, E-cadherin, Epithelial monolayers, Epithelium, Homoeostasis, Human, Mechanical instabilities, Monolayers, Morphological transformations, Morphology, Normal tissue, Oncogenics, Soft substrates, Substrates, Tissue, Tissue mechanics, Tissue morphology, Tumor development

Mapping the biochemical composition of eukaryotic cells without the use of exogenous labels is a long-sought objective in cell biology. Recently, it has been shown that composition maps on dry single bacterial cells with nanoscale spatial resolution can be inferred from quantitative nanoscale dielectric constant maps obtained with the scanning dielectric microscope. Here, it is shown that this approach can also be applied to the much more challenging case of fixed and dry eukaryotic cells, which are highly heterogeneous and show micrometric topographic variations. More importantly, it is demonstrated that the main bottleneck of the technique (the long computation times required to extract the nanoscale dielectric constant maps) can be shortcut by using supervised neural networks, decreasing them from weeks to seconds in a wokstation computer. This easy-to-use data-driven approach opens the door for in situ and on-the-fly label free nanoscale composition mapping of eukaryotic cells with scanning dielectric microscopy. © 2021 The Authors. Small Methods published by Wiley-VCH GmbH

JTD Keywords: eukaryotic cells, label-free mapping, machine learning, nanoscale, scanning dielectric microscopy, Biochemical composition, Cells, Constant, Cytology, Data-driven approach, Dielectric forces, Dielectric materials, Eukaryotic cells, Label-free mapping, Machine learning, Mapping, Nanoscale, Nanoscale composition, Nanoscale spatial resolution, Nanotechnology, Scanning, Scanning dielectric microscopy, Supervised neural networks

We examine a mechanism of locomotion of active particles whose surface is uniformly coated with mobile enzymes. The enzymes catalyze a reaction that drives phoretic flows but their homogeneous distribution forbids locomotion by symmetry. We find that the ability of the enzymes to migrate over the surface combined with self-phoresis can lead to a spontaneous symmetry-breaking instability whereby the homogeneous distribution of enzymes polarizes and the particle propels. The instability is driven by the advection of enzymes by the phoretic flows and occurs above a critical Péclet number. The transition to polarized motile states occurs via a supercritical or subcritical pitchfork bifurcations, the latter of which enables hysteresis and coexistence of uniform and polarized states.

JTD Keywords: Biomimetic & bio-inspired materials, Locomotion, Surface-driven phase separation

This study evaluates the onset and offset of neural inspiratory time estimated from surface diaphragm electromyographic (EMGdi) recordings. EMGdi and airflow signals were recorded in ten healthy subjects according to two respiratory protocols based on respiratory rate (RR) increments, from 15 to 40 breaths per minute (bpm), and fractional inspiratory time (Ti/Ttot) decrements, from 0.54 to 0.18. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). The EMGdi amplitude was estimated using the fixed sample entropy computed over a 250 ms moving window of the EMGdi signal (EMGdifse). The neural onset was detected through a dynamic threshold over the EMGdifse using the kernel density estimation method, while neural offset was detected by finding when the EMGdifse had decreased to 70 % of the peak value reached during inspiration. The Bland-Altman analysis between airflow and neural onsets showed a global bias of 46 ms in the RR protocol and 22 ms in the Ti/Ttot protocol. The Bland-Altman analysis between airflow and neural offsets reveals a global bias of 11 ms in the RR protocol and -2 ms in the Ti/Ttot protocol. The relationship between pairs of RR values (Pearson’s correlation coefficient of 0.99, Bland- Altman limits of -2.39 to 2.41 bpm, and mean bias of 0.01 bpm) and between pairs of Ti/Ttot values (Pearson’s correlation coefficient of 0.86, Bland-Altman limits of -0.11 to 0.10, and mean bias of -0.01) showed a good agreement. In conclusion, we propose a method for determining neural onset and neural offset based on non-invasive recordings of the electrical activity of the diaphragm that requires no filtering of cardiac muscle interference.

JTD Keywords: Kernel density estimation (KDE),, Surface diaphragm electromyographic,, (EMGdi) signal,, Inspiratory time,, Neural respiratory drive (NRD),, Neural inspiratory time,, Fixed sample entropy (fSampEn)

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this work, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson’s correlation values between inspiratory mouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38???0.12, 0.27???0.11 and 0.11???0.13, respectively. Whereas at 33 cmH2O (maximum inspiratory load) were 0.83???0.02, 0.76???0.07 and 0.61???0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.

JTD Keywords: Electromyography, diaphragm muscle, neural respiratory drive

The poor rehabilitation success rate, including the cases of ineffective and detrimental adaptations, make stroke a leading cause of disability. Thus, it is essential to recognize the mechanisms driving healthy motor recovery to improve such rate. Stroke alters the Synergy Architecture (SA), the modular muscle control system. So SA analysis may constitute a powerful tool to design and assess rehabilitation procedures. However, current impairment scales do not consider the patient's neuromuscular state. To gain insights into this hypothesis, we recorded multiple myoelectric signals from upper-limb muscles, in healthy subjects, while executing a set of common rehabilitation exercises. We found that SA reveals optimized motor control strategies and the positive effects of the use of visual feedback (VF) on motor control. Furthermore we demonstrate that the right and left arm's SA share the basic structure within the same subject, so we propose using the unaffected limb's SA as a reference motion pattern to be reached through rehabilitation.

JTD Keywords: Bars, Electromyography, Motor drives, Neuromuscular, Vectors, Visualization