Infrared spectroscopy of NaCl(CH3OH)n complexes in helium nanodroplets

Infrared (IR) spectra of complexes between NaCl and methanol have been recorded for the first time. These complexes were formed in liquid helium nanodroplets by consecutive pick-up of NaCl and CH3OH molecules. For the smallest NaCl(CH3OH)n complexes where n = 1-3, the IR data suggest that the lowest energy isomer is the primary product in each case. The predominant contribution to the binding comes from ionic hydrogen bonds between the OH in each methanol molecule and the chloride ion in the NaCl, as established by the large red-shift of the OH stretching bands compared with the isolated CH3OH molecule. For n ≥ 4 there is a dramatic shift from discrete vibrational bands to very broad absorption envelopes, suggesting a profound change in the structural landscape and, in particular, access to multiple low-energy isomers

Infrared Laser Spectroscopy of Salt-Solvent Complexes using Helium Nanodroplets

Infrared (IR) spectra of complexes consisting of an alkali halide salt (MX) molecule and one or more protic solvent molecules have been recorded for the first time in this thesis. NaCl and LiI are the principal salts investigated and have been combined with the solvents water and methanol to form complexes of type MX(solvent)n (n = 1-7) in liquid helium nanodroplets. IR spectra were recorded using a depletion technique. For small complexes (n = 1 – 3) the spectra are consistent with formation of contact ion-pair structures in which each solvent molecule forms a single ionic hydrogen bond (IHB) to an intact M+X- ion-pair. For n ≥ 4, the IR spectra suggest that multiple isomers of MX(solvent)n are present in helium nanodroplets. Ab initio calculations were used to support the results by predicting possible structures and their corresponding IR spectra. A mass spectrometric study of a variety of alkali halide salts with a variety of protic and aprotic solvents in helium nanodroplets was also performed. The aim here was to survey the mass spectrometric behaviour of species within the helium nanodroplets in preparation for future IR spectroscopic studies. The salts chosen for this study were NaCl, NaBr, NaF, NaI, LiI, LiCl, CsI and KF, while the solvents chosen were water, methanol, acetone and acetonitrile, i.e. two protic and two aprotic solvents. The ions observed in the mass spectra have been described and assigned to be derived from the neutral species in helium nanodroplets environment

<it>Walterinnesia aegyptia </it>venom combined with silica nanoparticles enhances the functioning of normal lymphocytes through PI3K/AKT, NFκB and ERK signaling

Abstract Background The toxicity of snake venom varies over time in some species. The venom of newborn and small juvenile snakes appears to be more potent than adults of the same species, and a bite from a snake that has not fed recently, such as one that has just emerged from hibernation, is more dangerous than one that has recently fed due to the larger volume of venom injected. Therefore, the potency of a snake's venom is typically determined using the LD50 or IC50 tests. In the present study, we evaluated the anti-tumor potential of snake venom from Walterinnesia aegyptia (WEV) on the human breast carcinoma cell line MDA-MB-231, as well as its effect on the normal mice peripheral blood mononuclear cells (PBMCs). Results This venom was used alone (WEV) or in combination with silica nanoparticles (WEV+NP). The IC50 values of WEV alone and WEV+NP in the MDA-MB-231 cells were determined to be 50 ng/ml and 20 ng/ml, respectively. Interestingly, at these concentrations, the venom did not affect the viability of normal human PBMCs. To investigate the in vivo effects of this venom further, three groups of mice were used (15 mice in each group): Group I was the control, Group II was subcutaneously injected with WEV, and Group III was injected with WEV+NP. Using flow cytometry and western blot analysis, we found that the blood lymphocytes of WEV-injected mice exhibited a significant increase in actin polymerization and cytoskeletal rearrangement in response to CXCL12 through the activation of AKT, NF-κB and ERK. These lymphocytes also showed a significant increase in their proliferative capacity in response to mitogen stimulation compared with those isolated from the control mice (P Conclusion Our data reveal the unique biological effects of WEV, and we demonstrated that its combination with nanoparticles strongly enhanced these biological effects.</p

[In Press] Knowledge graph for recommendation system : enhanced relation reliability and prediction probability (ERRaPP)

With the current explosion of information, the end-users find it challenging to filter this information. Recommendation systems present solutions to filter and prioritize the information to overcome the problem of information overloading. However, one of the main challenges associated with RS is accuracy. A knowledge graph (KG) is one solution to improve the recommendation system’s performance. The existing solutions do not consider the side information and semantic relationship from the knowledge graph, which results in the problem of accuracy of the recommendation and the processing time. Our proposed solution aims to increase the accuracy and decrease the processing time by exploring semantic relations between entities and considering the importance of relationships. The proposed system consists of a collaborative knowledge graph (GCN) with Enhanced Relation Reliability and Prediction Probability (ERRaPP) algorithm to enhance the recommendation accuracy and minimize the processing time. This algorithm includes the importance of relation specialized in an entity to get more reliable paths. It also has an attention mechanism with a sigmoid function to replace the inner product between entities embedding to improve the prediction. The results are obtained for different model stages (training, evaluation, test) for 4 other datasets (Book-Crossing, MovieLens-20 M, MovieLens-1 M and Last.FM). The results show that the proposed solution achieves better recommendation accuracy with less processing time for all three stages and 4 datasets. The proposed solution provides the recommendation accuracy of 0.705 against the current accuracy of 0.665 on average for the Book-Crossing dataset and a processing time of 7.884 seconds against the current processing time of 12 seconds on average for the testing stage. The proposed solution focuses on enhancing the overall accuracy and reducing the processing time of the knowledge graph-based recommendation system by using the ERRaPP algorithm. Finally, the solution with enhanced relation reliability and score prediction improves the recommendation accuracy by considering semantic relations between entities

Cellular and Molecular Mechanisms Underlie the Anti-Tumor Activities Exerted by <em>Walterinnesia aegyptia</em> Venom Combined with Silica Nanoparticles against Multiple Myeloma Cancer Cell Types

<div><p>Multiple myeloma (MM) is a clonal disease of plasma cells that remains incurable despite the advent of several novel therapeutics. In this study, we aimed to delineate the impact of snake venom extracted from <em>Walterinnesia aegyptia</em> (WEV) alone or in combination with silica nanoparticles (WEV+NP) on primary MM cells isolated from patients diagnosed with MM as well as on two MM cell lines, U266 and RPMI 8226. The IC₅₀ values of WEV and WEV+NP that significantly decreased MM cell viability without affecting the viability of normal peripheral mononuclear cells (PBMCs) were determined to be 25 ng/ml and 10 ng/ml, respectively. Although both WEV (25 ng/ml) and WEV+NP (10 ng/ml) decreased the CD54 surface expression without affecting the expression of CXCR4 (CXCL12 receptor) on MM cells, they significantly reduced the ability of CXC chemokine ligand 12 (CXCL12) to induce actin cytoskeleton rearrangement and the subsequent reduction in chemotaxis. It has been established that the binding of CXCL12 to its receptor CXCR4 activates multiple intracellular signal transduction pathways that regulate MM cell chemotaxis, adhesion, and proliferation. We found that WEV and WEV+NP clearly decreased the CXCL12/CXCR4-mediated activation of AKT, ERK, NFκB and Rho-A using western blot analysis; abrogated the CXCL12-mediated proliferation of MM cells using the CFSE assay; and induced apoptosis in MM cell as determined by PI/annexin V double staining followed by flow cytometry analysis. Monitoring the expression of B-cell CCL/Lymphoma 2 (Bcl-2) family members and their role in apoptosis induction after treatment with WEV or WEV+NP revealed that the combination of WEV with NP robustly decreased the expression of the anti-apoptotic effectors Bcl-2, Bcl_XL and Mcl-1; conversely increased the expression of the pro-apoptotic effectors Bak, Bax and Bim; and altered the mitochondrial membrane potential in MM cells. Taken together, our data reveal the biological effects of WEV and WEV+NP and the underlying mechanisms against myeloma cancer cells.</p> </div

Kurdish handwritten character recognition using deep learning techniques

Handwriting recognition is regarded as a dynamic and inspiring topic in the exploration of pattern recognition and image processing. It has many applications including a blind reading aid, computerized reading, and processing for paper documents, making any handwritten document searchable and converting it into structural text form. High accuracy rates have been achieved by this technology when recognizing handwriting recognition systems for English, Chinese Arabic, Persian, and many other languages. However, there is not such a system for recognizing Kurdish handwriting. In this paper, an attempt is made to design and develop a model that can recognize handwritten characters for Kurdish alphabets using deep learning techniques. Kurdish (Sorani) contains 34 characters and mainly employs an Arabic/Persian based script with modified alphabets. In this work, a Deep Convolutional Neural Network model is employed that has shown exemplary performance in handwriting recognition systems. Then, a comprehensive database has been created for handwritten Kurdish characters which contain more than 40 thousand images. The created database has been used for training the Deep Convolutional Neural Network model for classification and recognition tasks. In the proposed system the experimental results show an acceptable recognition level. The testing results reported an 83% accuracy rate, and training accuracy reported a 96% accuracy rate. From the experimental results, it is clear that the proposed deep learning model is performing well and comparable to the similar to other languages handwriting recognition systems

Effect of WEV and WEV+NP on CXCL12-mediated signaling.

<p>U266 (A) and RPMI 8226 (B) cells were untreated (0) or treated with 25 ng/ml of NP, 25 ng/ml of WEV or 10 ng/ml of WEV+NP for 12 hours. Cells were then treated for 2 min with medium or 250 ng/ml CXCL12 prior to being lysed. Proteins in the cell lysates were resolved on a 7% acrylamide gel. The phosphorylation levels of AKT (p-AKT), ERK1/2 (p-ERK1/2), IκBα (p- IκBα) and PLCβ3 (p-PLCβ3) and the activation level of Rho-A (Rho-A_GTP) were corrected for the level of total β-actin on stripped blots. One representative blot for each downstream effector from 10 independent experiments is shown. Accumulated results are expressed as the mean values of normalized specific phosphorylation ± SEM from 10 separate experiments for U266 (<b>C</b>) and RPMI 8226 (<b>D</b>) cells. *P<0.05, WEV-treated vs. control; #P<0.05, WEV+NP-treated vs. control; +P<0.05, WEV+NP-treated vs. WEV-treated.</p

WEV alone or combined with NP induced apoptosis in MM cancer cells.

<p>The potential of WEV and WEV+NP to induce the apoptosis or necrosis of MM cancer cells was determined by flow cytometry based on their PI/Annexin V staining patterns. (<b>A</b>) One representative data set from 12 independent experiments is shown. (<b>B</b>) Accumulated data from 12 experiments are expressed as the mean percentage of apoptotic cells ± SEM for untreated cancer cells (0) (dotted bars), NP-treated cells (hatched bars), WEV-treated cells (closed gray bars) and WEV+NP-treated cells (closed black bars). ^*P<0.05, WEV-treated vs. NP; ^#P<0.05, WEV+NP-treated vs. NP; ⁺P<0.05, WEV+NP-treated vs. WEV-treated cells.</p

Time- and dose-dependent effect of WEV and WEV+NP treatment on cell viability.

<p>Electron microscope images of double mesoporous core-shell silica nanospheres (DMCSSs) before (<b>A</b>) and after (<b>B</b>) the venom loading. Cell viability was assessed using the MTT assay. RPMI 8226 cells (<b>C</b>), U266 cells (<b>D</b>) and normal PBMCs (<b>E</b>) were treated overnight with different concentrations (0, 1, 5, 10, 25, 50, 100 and 1000 ng/ml) of NP (open circles), WEV (gray triangles) or WEV+NP (closed black squares). RPMI 8226 cells (<b>F</b>), U266 cells (<b>G</b>) and normal PBMCs (<b>H</b>) were treated with 25 ng/ml of NP (open circles), 25 ng/ml of WEV (gray triangles) or 10 ng/ml of WEV+NP (closed black squares) for different incubation times (0, 1, 2, 6, 12, 24, 36 and 48 h). The data collected from independent experiments (n = 5) are shown, and the results are expressed as the mean percentage of viable cells ± SEM.</p