A new approach to separate hydrogen from carbon dioxide using graphdiyne-like membrane

In order to separate a mixture of hydrogen ($H_2$) and carbon dioxide ($CO_2$) gases, we have proposed a new approach employing the graphdiyne-like membrane (GDY-H) using density functional theory (DFT) calculations and molecular dynamics (MD) simulations. GDY-H is constructed by removing one-third diacetylenic ($-$C$\equiv$C$-$C$\equiv$C$-$) bonds linkages and replacing with hydrogen atoms in graphdiyne structure. Our DFT calculations exhibit poor selectivity and good permeances for $H_2$/$CO_2$ gases passing through this membrane. To improve the performance of the GDY-H membrane for $H_2$/$CO_2$ separation, we have placed two layers of GDY-H adjacent to each other which the distance between them is 2 nm. Then, we have inserted 1,3,5-triaminobenzene between two layers. In this approach, the selectivity of $H_2$/$CO_2$ is increased from 5.65 to completely purified $H_2$ gas. Furthermore, GDY-H membrane represents excellent permeance, about $10^8$ gas permeation unit (GPU), for $H_2$ molecule at temperatures above 20 K. The $H_2$ permeance is much higher than the value of the usual industrial limits. Moreover, our proposed approach shows a good balance between the selectivity and permeance parameters for the gas separation which is an essential factor for $H_2$ purification and $CO_2$ capture processes in the industry

Genetic analysis of partial resistance to basal stem rot (Sclerotinia sclerotiorum) in sunflower

Basal stem rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is one of the major diseases of sunflower (Helianthus annuus L.) in the world. Quantitative trait loci (QTLs) implicated in partial resistance to basal stem rot disease were identified using 99 recombinant inbred lines (RILs) from the cross between sunflower parental lines PAC2 and RHA266. The study was undertaken in a completely randomized design with three replications under controlled conditions. The RILs and their parental lines were inoculated with a moderately aggressive isolate of S. sclerotiorum (SSKH41). Resistance to disease was evaluated by measuring the percentage of necrosis area three days after inoculation. QTLs were mapped using an updated high-density SSR and SNP linkage map. ANOVA showed significant differences among sunflower lines for resistance to basal stem rot (P <= 0.05). The frequency distribution of lines for susceptibility to disease showed a continuous pattern. Composite interval mapping analysis revealed 5 QTLs for percentage of necrotic area, localized on linkage groups 1, 3, 8, 10 and 17. The sign of additive effect was positive in 5 QTLs, suggesting that the additive allele for partial resistance to basal stem rot came from the paternal line (RHA266). The phenotypic variance explained by QTLs (R 2) ranged from 0.5 to 3.16%. Identified genes (HUCL02246_1, GST and POD), and SSR markers (ORS338, and SSL3) encompassing the QTLs for partial resistance to basal stem rot could be good candidates for marker assisted selection

Radiomics predictive modeling from dual-time-point FDG PET Ki parametric maps : application to chemotherapy response in lymphoma

Background: To investigate the use of dynamic radiomics features derived from dual-time-point (DTP-feature) [18F]FDG PET metabolic uptake rate Ki parametric maps to develop a predictive model for response to chemotherapy in lymphoma patients. Methods We analyzed 126 lesions from 45 lymphoma patients (responding n = 75 and non-responding n = 51) treated with chemotherapy from two different centers. Static and DTP radiomics features were extracted from baseline static PET images and DTP Ki parametric maps. Spearman’s rank correlations were calculated between static and DTP features to identify features with potential additional information. We first employed univariate analysis to determine correlations between individual features, and subsequently utilized multivariate analysis to derive predictive models utilizing DTP and static radiomics features before and after ComBat harmonization. For multivariate modeling, we utilized both the minimum redundancy maximum relevance feature selection technique and the XGBoost classifier. To evaluate our model, we partitioned the patient datasets into training/validation and testing sets using an 80/20% split. Different metrics for classification including area under the curve (AUC), sensitivity (SEN), specificity (SPE), and accuracy (ACC) were reported in test sets. Results Via Spearman’s rank correlations, there was negligible to moderate correlation between 32 out of 65 DTP features and some static features (ρ < 0.7); all the other 33 features showed high correlations (ρ ≥ 0.7). In univariate modeling, no significant difference between AUC of DTP and static features was observed. GLRLM_RLNU from static features demonstrated a strong correlation (AUC = 0.75, p value = 0.0001, q value = 0.0007) with therapy response. The most predictive DTP features were GLCM_Energy, GLCM_Entropy, and Uniformity, each with AUC = 0.73, p value = 0.0001, and q value < 0.0005. In multivariate analysis, the mean ranges of AUCs increased following harmonization. Use of harmonization plus combining DTP and static features was shown to provide significantly improved predictions (AUC = 0.97 ± 0.02, accuracy = 0.89 ± 0.05, sensitivity = 0.92 ± 0.09, and specificity = 0.88 ± 0.05). All models depicted significant performance in terms of AUC, ACC, SEN, and SPE (p < 0.05, Mann–Whitney test). Conclusions Our results demonstrate significant value in harmonization of radiomics features as well as combining DTP and static radiomics models for predicting response to chemotherapy in lymphoma patients.Medicine, Faculty ofScience, Faculty ofNon UBCPhysics and Astronomy, Department ofRadiology, Department ofReviewedFacultyResearche

Dynamic Motions of Ligands around the Metal Centers Afford a Fidget Spinner-Type AIE Luminogen

A new type of aggregation-induced emission (AIE) luminogen containing a dimeric metal fragment and two or three phthalazine ligands is described, which shows dynamic motions of ligands around the metal centers in solution. Based on the variable-temperature and EXSY NMR spectroscopy data, X-ray crystallography structures, and computational results, three different pathways (i.e., reversible exchange with haptotropic shifts, circulation of ligands around the dimeric metal fragment, and walking on the spot of ligands on the metal centers) were considered for this dynamic behavior. Restriction of these dynamic processes in the aggregate forms of the compounds (in H2O/CH3CN solvent mixtures) contributes to their AIE. DFT calculations and NMR analysis showed that bright excited states for these molecules are not localized on isolated molecules, and the emission of them stemmed from π-dimers or π-oligomers. The morphologies and the mode of associations in the solvent mixtures were determined by using transmission electron microscopy (TEM) and concentration-dependent NMR spectroscopy. The computational results showed the presence of a conical intersection (CI) between the S0 and S1 excited state, which provides an accessible pathway for nonradiative decay in these systems

Stimuli-responsive (nano)architectures for phytochemical delivery in cancer therapy

The use of phytochemicals for purpose of cancer therapy has been accelerated due to resistance of tumor cells to conventional chemotherapy drugs and therefore, monotherapy does not cause significant improvement in the prognosis and survival of patients. Therefore, administration of natural products alone or in combination with chemotherapy drugs due to various mechanisms of action has been suggested. However, cancer therapy using phytochemicals requires more attention because of poor bioavailability of compounds and lack of specific accumulation at tumor site. Hence, nanocarriers for specific delivery of phytochemicals in tumor therapy has been suggested. The pharmacokinetic profile of natural products and their therapeutic indices can be improved. The nanocarriers can improve potential of natural products in crossing over BBB and also, promote internalization in cancer cells through endocytosis. Moreover, (nano)platforms can deliver both natural and synthetic anti-cancer drugs in combination cancer therapy. The surface functionalization of nanostructures with ligands improves ability in internalization in tumor cells and improving cytotoxicity of natural compounds. Interestingly, stimuli-responsive nanostructures that respond to endogenous and exogenous stimuli have been employed for delivery of natural compounds in cancer therapy. The decrease in pH in tumor microenvironment causes degradation of bonds in nanostructures to release cargo and when changes in GSH levels occur, it also mediates drug release from nanocarriers. Moreover, enzymes in the tumor microenvironment such as MMP-2 can mediate drug release from nanocarriers and more progresses in targeted drug delivery obtained by application of nanoparticles that are responsive to exogenous stimulus including light

Nanostructures for site-specific delivery of oxaliplatin cancer therapy: Versatile nanoplatforms in synergistic cancer therapy

As a clinically approved treatment strategy, chemotherapy-mediated tumor suppression has been compromised, and in spite of introducing various kinds of anticancer drugs, cancer eradication with chemotherapy is still impossible. Chemotherapy drugs have been beneficial in improving the prognosis of cancer patients, but after resistance emerged, their potential disappeared. Oxaliplatin (OXA) efficacy in tumor suppression has been compromised by resistance. Due to the dysregulation of pathways and mechanisms in OXA resistance, it is suggested to develop novel strategies for overcoming drug resistance. The targeted delivery of OXA by nanostructures is described here. The targeted delivery of OXA in cancer can be mediated by polymeric, metal, lipid and carbon nanostructures. The advantageous of these nanocarriers is that they enhance the accumulation of OXA in tumor and promote its cytotoxicity. Moreover, (nano)platforms mediate the co-delivery of OXA with drugs and genes in synergistic cancer therapy, overcoming OXA resistance and improving insights in cancer patient treatment in the future. Moreover, smart nanostructures, including pH-, redox-, light-, and thermo-sensitive nanostructures, have been designed for OXA delivery and cancer therapy. The application of nanoparticle-mediated phototherapy can increase OXA's potential in cancer suppression. All of these subjects and their clinical implications are discussed in the current review