Antioxidant activity of <i>Vaccinium axillare</i> Nakai fruits during oxidative stress <i>in vivo</i>

Intensity of free radical oxidation processes in vivo (model of induced oxidative stress) was studied after the probe introduction of Vaccinium axillare Nakai fruit extract. Material and methods. Four groups (n = 40) of white male CBA mice weighing 20–25 g were included in the experiment: 1 – intact control; 2–0.9 % sodium chloride solution was administered per os for 10 days in a dose of 10 ml/kg/day; 3 – group “cisplatin” (animals received 0.9 % sodium chloride solution similarly to group 2, on the fifth day of the experiment cisplatin was administered once by intraperitoneal injection at a dose of 7.5 mg/kg); 4 – group “cisplatin + blueberries” (mice received per os extract of Blueberry axillary fruits at a dose of 10 ml/kg/day for 10 days, on the fifth day of the experiment cisplatin was administered once by intraperitoneal injection at a dose of 7.5 mg/kg). Antioxidant activity of Blueberry axillary was studied by chemiluminescence. Results and discussion. Analysis of kinetic parameters of mouse kidney homogenate chemiluminescence showed that oxidative stress develops in animals after a single intraperitoneal injection of cisplatin, the extract of Blueberry axillary fruit decreases its severity. Conclusions. Bilberry fruit extract (Vaccinium axillare Nakai) has pronounced antioxidant properties and may be important in the treatment and prevention of diseases associated with oxidative stress

Effects of glyprolines on free-radical oxidation in the brain neocortex of white rats in mild traumatic brain injury

The aim of the study was to compare the effect of glyproline peptides RGRGP (Arg-Gly-Arg-Gly-Pro), RGP (Arg-GlyPro), PRPGP (Pro-Arg-Pro-Gly-Pro) and PGPL (Pro-Gly-Pro-Leu) peptide substances at various concentrations on the free radical oxidation intensity of the brain tissues of Wistar males after intraperitoneal administration of peptide solutions after traumatic brain injury.Material and methods. The brain tissue of Wistar males aged 2–3 months (n = 126) were used in the experiment. RGRGP, RGP, PRPGP, and PGPL peptides were provided by Academician N.F. Myasoyedov. Traumatic brain injury (TBI) was modeled by free fall of a load. From the second to the fifth day of the experiment, the animals were injected intraperitoneally with peptides. On the sixth day, the animals were taken out of the experiment. The activity of free radical oxidation was determined in freshly prepared homogenates of sections of the cerebral cortex by chemiluminescence (CL).Results. TBI significantly enhance free-radical oxidation intensity of the neocortex in brain tissue of Wistar rats, and the studied peptides affect it in different ways - from a decrease in CL intensity (the minimum value in TBI + RGP 0.1 group) to its increase (the maximum value in TBI + RGPGP 0.1 group). The effect depends on the dose of glyproline.Conclusions. The results obtained, based on the analysis of the free radical oxidation intensity of tissues, mainly indicate a different degree of correction of tissue homeostasis indicators. It can be assumed that Arg-Pro-Gly peptide can be the basis for the development of new drugs for post-stress rehabilitation after injuries of various levels and genesis

Crossover from the chiral to the standard universality classes in the conductance of a quantum wire with random hopping only

The conductance of a quantum wire with off-diagonal disorder that preserves a sublattice symmetry (the random hopping problem with chiral symmetry) is considered. Transport at the band center is anomalous relative to the standard problem of Anderson localization both in the diffusive and localized regimes. In the diffusive regime, there is no weak-localization correction to the conductance and universal conductance fluctuations are twice as large as in the standard cases. Exponential localization occurs only for an even number of transmission channels in which case the localization length does not depend on whether time-reversal and spin rotation symmetry are present or not. For an odd number of channels the conductance decays algebraically. Upon moving away from the band center transport characteristics undergo a crossover to those of the standard universality classes of Anderson localization. This crossover is calculated in the diffusive regime.Comment: 22 pages, 9 figure

Using least median of squares for structural superposition of flexible proteins

<p>Abstract</p> <p>Background</p> <p>The conventional superposition methods use an ordinary least squares (LS) fit for structural comparison of two different conformations of the same protein. The main problem of the LS fit that it is sensitive to outliers, i.e. large displacements of the original structures superimposed.</p> <p>Results</p> <p>To overcome this problem, we present a new algorithm to overlap two protein conformations by their atomic coordinates using a robust statistics technique: least median of squares (LMS). In order to effectively approximate the LMS optimization, the forward search technique is utilized. Our algorithm can automatically detect and superimpose the rigid core regions of two conformations with small or large displacements. In contrast, most existing superposition techniques strongly depend on the initial LS estimating for the entire atom sets of proteins. They may fail on structural superposition of two conformations with large displacements. The presented LMS fit can be considered as an alternative and complementary tool for structural superposition.</p> <p>Conclusion</p> <p>The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. Furthermore, we show that the LMS fit can be extended to multiple level superposition between two conformations with several rigid domains. Our fit tool has produced successful superpositions when applied to proteins for which two conformations are known. The binary executable program for Windows platform, tested examples, and database are available from <url>https://engineering.purdue.edu/PRECISE/LMSfit</url>.</p

Statistical learning leads to persistent memory: evidence for one-year consolidation

Statistical learning is a robust mechanism of the brain that enables the extraction of environmental patterns, which is crucial in perceptual and cognitive domains. However, the dynamical change of processes underlying long-term statistical memory formation has not been tested in an appropriately controlled design. Here we show that a memory trace acquired by statistical learning is resistant to inference as well as to forgetting after one year. Participants performed a statistical learning task and were retested one year later without further practice. The acquired statistical knowledge was resistant to interference, since after one year, participants showed similar memory performance on the previously practiced statistical structure after being tested with a new statistical structure. These results could be key to understand the stability of long-term statistical knowledge

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes