Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Next Issue
Volume 2, June
Previous Issue
Volume 1, December

Biophysica, Volume 2, Issue 1 (March 2022) – 8 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Select all
Export citation of selected articles as:
Article
Cholesterol Significantly Affects the Interactions between Pirfenidone and DPPC Liposomes: Spectroscopic Studies
Biophysica 2022, 2(1), 79-88; https://doi.org/10.3390/biophysica2010008 - 16 Feb 2022
Viewed by 718
Abstract
In this work, we studied the effect of as on the interaction of membrane DPPC with the key antifibrotic drug pirfenidone. Liposomal forms of pirfenidone were obtained using passive loading. The addition of cholesterol reduces the loading efficiency of pirfenidone by 10%. The [...] Read more.
In this work, we studied the effect of as on the interaction of membrane DPPC with the key antifibrotic drug pirfenidone. Liposomal forms of pirfenidone were obtained using passive loading. The addition of cholesterol reduces the loading efficiency of pirfenidone by 10%. The main binding site of pirfenidone in DPPC liposomes is the carbonyl group: the interaction with PF significantly increases the proportion of low-hydrated carbonyl groups as revealed by ATR-FTIR spectroscopy. The phosphate group acts as an additional binding site; however, due to shielding by the choline group, this interaction is weak. The hydrophobic part of the bilayer is not involved in PF binding at room temperature. Cholesterol changes the way of interaction between carbonyl groups and pirfenidone probably because of the formation of two subpopulations of DPPC and causes a dramatic redistribution of carbonyl groups onto the degrees of hydration. The proportion of moderately hydrated carbonyl groups increases, apparently due to the deepening of pirfenidone into the circumpolar region of the bilayer. For the first time, a change in the microenvironment of pirfenidone upon binding to liposomes was shown: aromatic moiety interacts with the bilayer. Full article
(This article belongs to the Collection Feature Papers in Biophysics)
Show Figures

Figure 1

Article
Bioluminescence Resonance Energy Transfer (BRET) Allows Monitoring the Barnase-Barstar Complex In Vivo
Biophysica 2022, 2(1), 72-78; https://doi.org/10.3390/biophysica2010007 - 07 Feb 2022
Cited by 1 | Viewed by 771
Abstract
Bioluminescence resonance energy transfer (BRET) seems to be a promising biophysical technique to study protein–protein interactions within living cells due to a very specific reaction of bioluminescence that essentially decreases the background of other cellular components and light-induced destruction of biomacromolecules. An important [...] Read more.
Bioluminescence resonance energy transfer (BRET) seems to be a promising biophysical technique to study protein–protein interactions within living cells due to a very specific reaction of bioluminescence that essentially decreases the background of other cellular components and light-induced destruction of biomacromolecules. An important direction of the development of this technique is the study of known strong protein–protein complexes in vivo and the estimation of an average distance between chromophores of the donor and acceptor. Here, we demonstrate an in vivo interaction between barnase fused with luciferase (from Renilla reniformis, RLuc) and barstar fused with EGFP (enhanced green fluorescent protein of Aequorea victoria) monitored by BRET. The distance between the luciferase and EGFP chromophores within the complex has been evaluated as equal to (56 ± 2) Å. Full article
(This article belongs to the Special Issue Protein Engineering: The Present and the Future)
Show Figures

Figure 1

Editorial
Acknowledgment to Reviewers of Biophysica in 2021
Biophysica 2022, 2(1), 70-71; https://doi.org/10.3390/biophysica2010006 - 27 Jan 2022
Cited by 1 | Viewed by 582
Abstract
Rigorous peer-reviews are the basis of high-quality academic publishing [...] Full article
Article
Fractal Dimension Analysis to Detect the Progress of Cancer Using Transmission Optical Microscopy
Biophysica 2022, 2(1), 59-69; https://doi.org/10.3390/biophysica2010005 - 07 Jan 2022
Viewed by 864
Abstract
Fractal dimension, a measure of self-similarity in a structure, is a powerful physical parameter for the characterization of structural property of many partially filled disordered materials. Biological tissues are fractal in nature and reports show a change in self-similarity associated with the progress [...] Read more.
Fractal dimension, a measure of self-similarity in a structure, is a powerful physical parameter for the characterization of structural property of many partially filled disordered materials. Biological tissues are fractal in nature and reports show a change in self-similarity associated with the progress of cancer, resulting in changes in their fractal dimensions. Here, we report that fractal dimension measurement is a potential technique for the detection of different stages of cancer using transmission optical microscopy. Transmission optical microscopy of a thin tissue sample produces intensity distribution patterns proportional to its refractive index pattern, representing its mass density distribution. We measure fractal dimension detection of different cancer stages and find its universal feature. Many deadly cancers are difficult to detect in their early to different stages due to the hard-to-reach location of the organ and/or lack of symptoms until very late stages. To study these deadly cancers, tissue microarray (TMA) samples containing different stages of cancers are analyzed for pancreatic, breast, colon, and prostate cancers. The fractal dimension method correctly differentiates cancer stages in progressive cancer, raising possibilities for a physics-based accurate diagnosis method for cancer detection. Full article
(This article belongs to the Collection Feature Papers in Biophysics)
Show Figures

Figure 1

Article
Nascent Adhesion Clustering: Integrin-Integrin and Integrin-Substrate Interactions
Biophysica 2022, 2(1), 34-58; https://doi.org/10.3390/biophysica2010004 - 07 Jan 2022
Viewed by 854
Abstract
Nascent adhesions (NAs) are a general precursor to the formation of focal adhesions (FAs) that provide a fundamental mechanism for cell adhesion that is, in turn, involved in cell proliferation, migration, and mechanotransduction. Nascent adhesions form when cells come into contact with substrates [...] Read more.
Nascent adhesions (NAs) are a general precursor to the formation of focal adhesions (FAs) that provide a fundamental mechanism for cell adhesion that is, in turn, involved in cell proliferation, migration, and mechanotransduction. Nascent adhesions form when cells come into contact with substrates at all rigidities and generally involve the clustering of ligated integrins that may recruit un-ligated integrins. Nascent adhesions tend to take on characteristic sizes in the range of O(100nm150nm) in diameter and tend to contain integrin numbers of O(2060). The flexible, adaptable model we present provides and clear explanation of how these conserved cluster features come about. Our model is based on the interaction among ligated and un-ligated integrins that arise due to deformations that are induced in the cell membrane-cell glycocalyx and substrate system due to integrin activation and ligation. This model produces a clearly based interaction potential, and from it an explicit interaction force among integrins, that our stochastic diffusion-interaction simulations then show will produce nascent clusters with experimentally observed characteristics. Our simulations reveal effects of various key parameters related to integrin activation and ligation as well as some unexpected and previously unappreciated effects of parameters including integrin mobility and substrate rigidity. Moreover, the model’s structure is such that refinements are readily incorporated and specific suggestions are made as to what is required for further progress in understanding nascent clustering and the development of mature focal adhesions in a truly predictive manner. Full article
(This article belongs to the Collection Feature Papers in Biophysics)
Show Figures

Figure 1

Article
Autologous Gradient Formation under Differential Interstitial Fluid Flow Environments
Biophysica 2022, 2(1), 16-33; https://doi.org/10.3390/biophysica2010003 - 04 Jan 2022
Viewed by 853
Abstract
Fluid flow and chemokine gradients play a large part in not only regulating homeostatic processes in the brain, but also in pathologic conditions by directing cell migration. Tumor cells in particular are superior at invading into the brain resulting in tumor recurrence. One [...] Read more.
Fluid flow and chemokine gradients play a large part in not only regulating homeostatic processes in the brain, but also in pathologic conditions by directing cell migration. Tumor cells in particular are superior at invading into the brain resulting in tumor recurrence. One mechanism that governs cellular invasion is autologous chemotaxis, whereby pericellular chemokine gradients form due to interstitial fluid flow (IFF) leading cells to migrate up the gradient. Glioma cells have been shown to specifically use CXCL12 to increase their invasion under heightened interstitial flow. Computational modeling of this gradient offers better insight into the extent of its development around single cells, yet very few conditions have been modelled. In this paper, a computational model is developed to investigate how a CXCL12 gradient may form around a tumor cell and what conditions are necessary to affect its formation. Through finite element analysis using COMSOL and coupled convection-diffusion/mass transport equations, we show that velocity (IFF magnitude) has the largest parametric effect on gradient formation, multidirectional fluid flow causes gradient formation in the direction of the resultant which is governed by IFF magnitude, common treatments and flow patterns have a spatiotemporal effect on pericellular gradients, exogenous background concentrations can abrogate the autologous effect depending on how close the cell is to the source, that there is a minimum distance away from the tumor border required for a single cell to establish an autologous gradient, and finally that the development of a gradient formation is highly dependent on specific cell morphology. Full article
(This article belongs to the Special Issue Role of Water in Biological Systems)
Show Figures

Figure 1

Technical Note
Triglyceride Saturation in Patients at Risk of NASH and NAFLD: A Cross-Sectional Study
Biophysica 2022, 2(1), 8-15; https://doi.org/10.3390/biophysica2010002 - 30 Dec 2021
Viewed by 757
Abstract
Chemical shift magnetic resonance imaging (MRI) is commonly used to estimate the amount of fat in tissues, namely the proton density fat fraction (PDFF). In addition to PDFF, the type of fat can be inferred and characterized in terms of the number of [...] Read more.
Chemical shift magnetic resonance imaging (MRI) is commonly used to estimate the amount of fat in tissues, namely the proton density fat fraction (PDFF). In addition to PDFF, the type of fat can be inferred and characterized in terms of the number of double bonds (NDB), number of methylene-interrupted double bonds (NMIDB) and the chain length (CL) of the fatty acid chains. The saturation index is potentially a marker for metabolic disorders. This study assesses the feasibility of estimating these parameters independently or in a constrained manner. Correlations with spectroscopy were measured in 109 subjects’ subcutaneous and visceral fat depots (p = 2 × 10−28), and with the NAFLD Activity Score (NAS) from histological evaluation of biopsies. The findings indicate that imaging estimates are comparable to spectroscopy (p = 0.0002), but there is no significant association of NDB with NAS (p = 0.1). Full article
Show Figures

Figure 1

Communication
Old Enzyme, New Role: The β-Glucosidase BglC of Streptomyces scabiei Interferes with the Plant Defense Mechanism by Hydrolyzing Scopolin
Biophysica 2022, 2(1), 1-7; https://doi.org/10.3390/biophysica2010001 - 22 Dec 2021
Cited by 1 | Viewed by 1081
Abstract
The beta-glucosidase BglC fulfills multiple functions in both primary metabolism and induction of pathogenicity of Streptomyces scabiei, the causative agent of common scab in root and tuber crops. Indeed, this enzyme hydrolyzes cellobiose and cellotriose to feed glycolysis with glucose directly and [...] Read more.
The beta-glucosidase BglC fulfills multiple functions in both primary metabolism and induction of pathogenicity of Streptomyces scabiei, the causative agent of common scab in root and tuber crops. Indeed, this enzyme hydrolyzes cellobiose and cellotriose to feed glycolysis with glucose directly and modifies the intracellular concentration of these cello-oligosaccharides, which are the virulence elicitors. The inactivation of bglC led to unexpected phenotypes such as the constitutive overproduction of thaxtomin A, the main virulence determinant of S. scabiei. In this work, we reveal a new target substrate of BglC, the phytoalexin scopolin. Removal of the glucose moiety of scopolin generates scopoletin, a potent inhibitor of thaxtomin A production. The hydrolysis of scopolin by BglC displayed substrate inhibition kinetics, which contrasts with the typical Michaelis–Menten saturation curve previously observed for the degradation of its natural substrate cellobiose. Our work, therefore, reveals that BglC targets both cello-oligosaccharide elicitors emanating from the hosts of S. scabiei, and the scopolin phytoalexin generated by the host defense mechanisms, thereby occupying a key position to fine-tune the production of the main virulence determinant thaxtomin A. Full article
(This article belongs to the Special Issue Protein Engineering: The Present and the Future)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop