51 research outputs found

    Synthesis and Characterization of a Novel Mycophenolic Acid–Quinic Acid Conjugate Serving as Immunosuppressant with Decreased Toxicity

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    Mycophenolic acid (MPA) is one of the most commonly used immunosuppressive drugs for improving the outcome of cell and organ transplantations. However, an undesired adverse effect of MPA impedes its application in the clinics for post-transplant patients. By conjugating MPA to quinic acid (QA) via amide bonds, we synthesized a novel immunosuppressant, <i>N</i>-[2-[[(4<i>E</i>)-6-(1,3-dihydro-4-hydroxy-6-methoxy-7-methyl-3-oxo-5-isobenzofuranyl)-4-methyl-1-oxo-4-hexen-1-yl]­amino]­ethyl]-(1α,3R,4α,5R)-1,3,4,5-tetrakis­(acetyloxy)­cyclohexanecarboxamide (abbreviated as MQ4), which exhibits improved stability demonstrated by its incubation in vitro with human plasma, suggesting its better resistance to hydrolytic degradation induced by plasma enzyme. While the immunosuppressive effect of MQ4 on human lymphocyte proliferation was partially compromised as shown by flow cytometry, significant decrease in cytotoxicity of MQ4 to insulin producing ÎČ cells could compensate this drawback to some degree. There was a decreased level of apoptotic mediator caspase-3, which may contribute to the decreased toxicity of MQ4 to INS-1E cells. MQ4 could further improve insulin stimulation index and downregulate NFÎșB expression compared to physical mixing of QA to MPA. Taken together, MQ4 is a promising immunosuppressive agent for preventing and minimizing post-transplanted immune rejection

    Additional file 1 of Characterization and analysis of multi-organ full-length transcriptomes in Sphaeropteris brunoniana and Alsophila latebrosa highlight secondary metabolism and chloroplast RNA editing pattern of tree ferns

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    Additional file 1: Fig S1. Statistics of Nr annotations of S. brunoniana (top ten). (a)Root. (b)Rachis. (C)Pinna. Fig S2. Structural prediction of three-organ full-length transcriptomes of A. latebrosa. (a) The quantity of lncRNAs in three organs. (b) Transcription factor family distribution (top ten). (c) Distribution of SSR motifs. The X axis represents the SSR motif units, i.e., the number of repeating bases. The Y axis represents the number of repetitions of the bases, where the specific repetition count corresponds to the colors mentioned in the legend. The Z axis represents the number of SSRs. Fig S3. Enrichment results of KEGG expression up-regulated genes in S. brunoniana pinna (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment. Fig S4. Enrichment results of KEGG expression up-regulated genes in S. brunoniana root (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment. Fig S5. Enrichment results of KEGG expression up-regulated genes in S. brunoniana rachis (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment. Fig S6. Enrichment results of KEGG expression up-regulated genes in A. latebrosa pinna (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment. Fig S7. Enrichment results of KEGG expression up-regulated genes in A. latebrosa root (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment. Fig S8. Enrichment results of KEGG expression up-regulated genes in A. latebrosa rachis (compared with root and rachis) (top twenty). The significantly enriched pathways with corrected p-value (q value) < 0.05 were shown. Number indicates the size of the dot, describing the number of unigenes enriched in the pathway. The color bar represents the q value and indicates significance of the enrichment

    Exploring a Proximity-Coupled Co Chain on Pb(110) as a Possible Majorana Platform

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    Linear chains of magnetic atoms proximity coupled to an <i>s</i>-wave superconductor are predicted to host Majorana zero modes at the chain ends in the presence of strong spin–orbit coupling. Specifically, iron (Fe) chains on Pb(110) have been explored as a possible system to exhibit topological superconductivity and host Majorana zero modes [Nadj-Perge, S. et al., Science 2014, 346, 602−607]. Here, we study chains of the transition metal cobalt (Co) on Pb(110) and check for topological signatures. Using spin-polarized scanning tunneling spectroscopy, we resolve ferromagnetic order in the <i>d</i> bands of the chains. Interestingly, also the subgap Yu–Shiba–Rusinov (YSR) bands carry a spin polarization as was predicted decades ago. Superconducting tips allow us to resolve further details of the YSR bands and in particular resonances at zero energy. We map the spatial distribution of the zero-energy signal and find it delocalized along the chain. Hence, despite the ferromagnetic coupling within the chains and the strong spin-orbit coupling in the superconductor, we do not find clear evidence of Majorana modes. Simple tight-binding calculations suggest that the spin–orbit–split bands may cross the Fermi level four times which suppresses the zero-energy modes

    Systematic Investigation of Isoindigo-Based Polymeric Field-Effect Transistors: Design Strategy and Impact of Polymer Symmetry and Backbone Curvature

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    Ten isoindigo-based polymers were synthesized, and their photophysical and electrochemical properties and device performances were systematically investigated. The HOMO levels of the polymers were tuned by introducing different donor units, yet all polymers exhibited <i>p</i>-type semiconducting properties. The hole mobilities of these polymers with centrosymmetric donor units exceeded 0.3 cm<sup>2</sup> V<sup>–1</sup> s<sup>–1</sup>, and the maximum reached 1.06 cm<sup>2</sup> V<sup>–1</sup> s<sup>–1</sup>. Because of their low-lying HOMO levels, these copolymers also showed good stability upon moisture. AFM and GIXD analyses revealed that polymers with different symmetry and backbone curvature were distinct in lamellar packing and crystallinity. DFT calculations were employed to help us propose the possible packing model. Based on these results, we propose a design strategy, called “molecular docking”, to understand the interpolymer π–π stacking. We also found that polymer symmetry and backbone curvature affect interchain “molecular docking” of isoindigo-based polymers in film, ultimately leading to different device performance. Finally, our design strategy maybe applicable to other reported systems, thus representing a new concept to design conjugated polymers for field-effect transistors

    miR-338 promotes an epithelial phenotype in gastric cancer.

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    <p>(A) Right panel: NRP1 expression was detected by western blot in AGS cells after treatment with 3 independent siRNA sequences (siNRP1) or a control (siC). Left panel: Relative expression of NRP1 was shown in the histogram. (B) Right panel: An immunoblot analysis of N-cadherin, vimentin, fibronectin, E-cadherin and SNAIL in AGS cells transfected with siNRP1 or siC. Left panel: Relative expression of proteins was shown in the histogram. (C) An immunoblot analysis of N-cadherin, vimentin, fibronectin, E-cadherin and SNAIL in AGS cells infected with LV-hsa-mir-338 or cont-miR, with or without NRP1 restoration. The protein expression levels were normalized to GAPDH. The data represent the means±s.d.; * p<0.01.</p

    DataSheet_1_Construction and validation of a prognostic nutritional index-based nomogram for predicting pathological complete response in breast cancer: a two-center study of 1,170 patients.pdf

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    BackgroundPathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is associated with favorable outcomes in breast cancer patients. Identifying reliable predictors for pCR can assist in selecting patients who will derive the most benefit from NAC. The prognostic nutritional index (PNI) serves as an indicator of nutritional status and systemic immune competence. It has emerged as a prognostic biomarker in several malignancies; however, its predictive value for pCR in breast cancer remains uncertain. The objective of this study is to assess the predictive value of pretreatment PNI for pCR in breast cancer patients.MethodsA total of 1170 patients who received NAC in two centers were retrospectively analyzed. The patients were divided into three cohorts: a training cohort (n=545), an internal validation cohort (n=233), and an external validation cohort (n=392). Univariate and multivariate analyses were performed to assess the predictive value of PNI and other clinicopathological factors. A stepwise logistic regression model for pCR based on the smallest Akaike information criterion was utilized to develop a nomogram. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model.ResultsPatients with a high PNI (≄53) had a significantly increased pCR rate (OR 2.217, 95% CI 1.215-4.043, p=0.009). Tumor size, clinical nodal status, histological grade, ER, Ki67 and PNI were identified as independent predictors and included in the final model. A nomogram was developed as a graphical representation of the model, which incorporated the PNI and five other factors (AIC=356.13). The nomogram demonstrated satisfactory calibration and discrimination in the training cohort (C-index: 0.816, 95% CI 0.765-0.866), the internal validation cohort (C-index: 0.780, 95% CI 0.697-0.864) and external validation cohort (C-index: 0.714, 95% CI 0.660-0.769). Furthermore, DCA indicated a clinical net benefit from the nomogram.ConclusionThe pretreatment PNI is a reliable predictor for pCR in breast cancer patients. The PNI-based nomogram is a low-cost, noninvasive tool with favorable predictive accuracy for pCR, which can assist in determining individualized treatment strategies for breast cancer patients.</p
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