Surface sterilization method for reducing microbial contamination of field grown strawberry explants intended for in vitro culture

An effective disinfection method for strawberry (Fragaria x ananassa Duch.) cv. Senga Sengana micropropagation using runner tips and nodal segments as explants was developed. The explants were surface sterilized with different sterilants for different durations. The present studies on the effect of different regimes of sterilization revealed that maximum aseptic cultures were obtained from both explants runner tips and nodal segments when treated with 1.5% sodium hypochlorite for 20 min plus ethyl alcohol 70% for 30 s, but the surviving percentage was less because this treatment resulted in necrosis and tissue injury of explants. However, mercuric chloride (0.1%) for 4 min resulted in less percentage of aseptic cultures but gave highest percentage of surviving explants as most of researchers have found that a single sterilant is more effective than the combination. Surface sterilization with mercuric chloride (0.1%) for 4 min was the optimum duration which resulted in highest percentage of explant survival.Keywords: In vitro, senga sengana, strawberry, sterilizationAfrican Journal of Biotechnology Vol. 12(39), pp. 5749-575

Ca2+-Dependent Interaction between FKBP12 and Calcineurin Regulates Activity of the Ca2+ Release Channel in Skeletal Muscle

AbstractCalcineurin is a Ca2+ and calmodulin-dependent protein phosphatase with diverse cellular functions. Here we examined the physical and functional interactions between calcineurin and ryanodine receptor (RyR) in a C2C12 cell line derived from mouse skeletal muscle. Coimmunoprecipitation experiments revealed that the association between RyR and calcineurin exhibits a strong Ca2+ dependence. This association involves a Ca2+ dependent interaction between calcineurin and FK506-binding protein (FKBP12), an accessory subunit of RyR. Pretreatment with cyclosporin A, an inhibitor of calcineurin, enhanced the caffeine-induced Ca2+ release (CICR) in C2C12 cells. This effect was similar to those of FK506 and rapamycin, two drugs known to cause dissociation of FKBP12 from RyR. Overexpression of a constitutively active form of calcineurin in C2C12 cells, ΔCnA(391–521) (deletion of the last 131 amino acids from calcineurin), resulted in a decrease in CICR. This decrease in CICR activity was partially recovered by pretreatment with cyclosporin A. Furthermore, overexpression of an endogenous calcineurin inhibitor (cain) or an inactive form of calcineurin (ΔCnA(H101Q)) in C2C12 cells resulted in up-regulation of CICR. Taken together, our data suggest that a trimeric-interaction among calcineurin, FKBP12, and RyR is important for the regulation of the RyR channel activity and may play an important role in the Ca2+ signaling of muscle contraction and relaxation

A negatively charged region of the skeletal muscle ryanodine receptor is involved in Ca2+-dependent regulation of the Ca2+ release channel

AbstractThe ryanodine receptor/Ca2+ release channels from skeletal (RyR1) and cardiac (RyR2) muscle cells exhibit different inactivation profiles by cytosolic Ca2+. D3 is one of the divergent regions between RyR1 (amino acids (aa) 1872–1923) and RyR2 (aa 1852–1890) and may contain putative binding site(s) for Ca2+-dependent inactivation of RyR. To test this possibility, we have deleted the D3 region from RyR1 (ΔD3-RyR1), residues 1038–3355 from RyR2 (Δ(1038–3355)-RyR2) and inserted the skeletal D3 into Δ(1038–3355)-RyR2 to generate sD3-RyR2. The channels formed by ΔD3-RyR1 and Δ(1038–3355)-RyR2 are resistant to inactivation by mM [Ca2+], whereas the chimeric sD3-RyR2 channel exhibits significant inactivation at mM [Ca2+]. The ΔD3-RyR1 channel retains its sensitivity to activation by caffeine, but is resistant to inactivation by Mg2+. The data suggest that the skeletal D3 region is involved in the Ca2+-dependent regulation of the RyR1 channel

Comparative study of the functional properties of lupin, green pea, fava bean, hemp, and buckwheat flours as affected by pH

Acknowledgments This work is part of the Strategic Research 2011–2016 and is funded by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS).Peer reviewedPublisher PD

Identification of Motive Forces on the Whole Body System during Walking

Motive forces by muscles are applied to different parts of the human body in a periodic fashion when walking at a uniform rate. In this study, the whole human body is modeled as a multidegree of freedom (MDOF) system with seven degrees of freedom. In view of the changing contact conditions with the ground due to alternating feet movements, the system under study is considered piecewise time invariant for each half-period when one foot is in contact with the ground. Forces transmitted from the body to the ground while walking at a normal pace are experimentally measured and numerically simulated. Fourth-order Runge-Kutta method is employed to numerically simulate the forces acting on different masses of the body. An optimization problem is formulated with the squared difference between the measured and simulated forces transmitted to the ground as the objective function, and the motive forces on the body masses as the design variables to solve

Deep Learning to Predict the Hydration and Performance of Fly Ash-Containing Cementitious Binders

Fly ash (FA) – an industrial byproduct – is used to partially substitute Portland cement (PC) in concrete to mitigate concrete\u27s environmental impact. Chemical composition and structure of FAs significantly impact hydration kinetics and compressive strength of concrete. Due to the substantial diversity in these physicochemical attributes of FAs, it has been challenging to develop a generic theoretical framework – and, therefore, theory-based analytical models – that could produce reliable, a priori predictions of properties of [PC + FA] binders. In recent years, machine learning (ML) – which is purely data-driven, as opposed to being derived from theorical underpinnings – has emerged as a promising tool to predict and optimize properties of complex, heterogenous materials, including the aforesaid binders. That said, there are two issues that stand in the way of widespread use of ML models: (1) ML models require thousands of data-records to learn input-output correlations and developing such a large, yet consistent database is impractical; and (2) ML models – while good at producing predictions – are unable to reveal the underlying correlation between composition/structure of material and its properties. This study employs a deep forest (DF) model to predict composition- and time-dependent hydration kinetics and compressive strength of [PC + FA] binders. Data dimensionality-reduction and segmentation techniques – premised on theoretical understanding of composition-structure correlations in FAs, and hydration mechanism of PC – are used to boost the DF model\u27s prediction performance. And, finally, through inference of the intermediate and final outputs of the DF model, a simple, closed-form analytical model is developed to predict compressive strength, and reveal the correlations between mixture design and compressive strength of [PC + FA] binders

Spectral hardness evolution characteristics of tracking Gamma-ray Burst pulses

Employing a sample presented by Kaneko et al. (2006) and Kocevski et al. (2003), we select 42 individual tracking pulses (here we defined tracking as the cases in which the hardness follows the same pattern as the flux or count rate time profile) within 36 Gamma-ray Bursts (GRBs) containing 527 time-resolved spectra and investigate the spectral hardness, $E_{peak}$ (where $E_{peak}$ is the maximum of the $\nu F_{\nu}$ spectrum), evolutionary characteristics. The evolution of these pulses follow soft-to-hard-to-soft (the phase of soft-to-hard and hard-to-soft are denoted by rise phase and decay phase, respectively) with time. It is found that the overall characteristics of $E_{peak}$ of our selected sample are: 1) the $E_{peak}$ evolution in the rise phase always start on the high state (the values of $E_{peak}$ are always higher than 50 keV); 2) the spectra of rise phase clearly start at higher energy (the median of $E_{peak}$ are about 300 keV), whereas the spectra of decay phase end at much lower energy (the median of $E_{peak}$ are about 200 keV); 3) the spectra of rise phase are harder than that of the decay phase and the duration of rise phase are much shorter than that of decay phase as well. In other words, for a complete pulse the initial $E_{peak}$ is higher than the final $E_{peak}$ and the duration of initial phase (rise phase) are much shorter than the final phase (decay phase). This results are in good agreement with the predictions of Lu et al. (2007) and current popular view on the production of GRBs. We argue that the spectral evolution of tracking pulses may be relate to both of kinematic and dynamic process even if we currently can not provide further evidences to distinguish which one is dominant. Moreover, our statistical results give some witnesses to constrain the current GRB model.Comment: 32 pages, 26 figures, 3 tables, accepted for publication in New Astronom

Pharmacoinformatics-based identification of transmembrane protease serine-2 inhibitors from Morus Alba as SARS-CoV-2 cell entry inhibitors

Transmembrane protease serine-2 (TMPRSS2) is a cell-surface protein expressed by epithelial cells of specific tissues including those in the aerodigestive tract. It helps the entry of novel coronavirus (n-CoV) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the host cell. Successful inhibition of the TMPRSS2 can be one of the crucial strategies to stop the SARS-CoV-2 infection. In the present study, a set of bioactive molecules from Morus alba Linn. were screened against the TMPRSS2 through two widely used molecular docking engines such as Autodock vina and Glide. Molecules having a higher binding affinity toward the TMPRSS2 compared to Camostat and Ambroxol were considered for in-silico pharmacokinetic analyses. Based on acceptable pharmacokinetic parameters and drug-likeness, finally, five molecules were found to be important for the TMPRSS2 inhibition. A number of bonding interactions in terms of hydrogen bond and hydrophobic interactions were observed between the proposed molecules and ligand-interacting amino acids of the TMPRSS2. The dynamic behavior and stability of best-docked complex between TRMPRSS2 and proposed molecules were assessed through molecular dynamics (MD) simulation. Several parameters from MD simulation have suggested the stability between the protein and ligands. Binding free energy of each molecule calculated through MM-GBSA approach from the MD simulation trajectory suggested strong affection toward the TMPRSS2. Hence, proposed molecules might be crucial chemical components for the TMPRSS2 inhibition