The Development of New Methods to Streamline Heterocycle Synthesis

A series of new methods of C-N bond formation using azide or nitro group as nitrogen atom source were developed. The synthetic utility of these methods were demonstrated. Control experiments were performed for mechanistic study. Synthesis and characterization of new N-heteroheptacenes for solution-based organic field effect transistor were accomplished. A new and efficient synthetic route to FTY-720 phosphonate analogues was established

Efficient Synthesis of 3<i>H</i>‑Indoles Enabled by the Lead-Mediated α‑Arylation of β‑Ketoesters or γ‑Lactams Using Aryl Azides

The development of a lead-mediated α-arylation reaction between aryl azides and β-ketoesters or γ-lactams that facilitates the formation of 3<i>H</i>-indoles is disclosed. Twenty-five examples are included which demonstrate the generality of this reaction to access aryl azides bearing tetrasubstituted <i>o</i>-alkyl substituents. When paired with a Staudinger reduction, this reaction streamlines the synthesis of functionalized 3<i>H</i>-indoles

Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons-4

<p><b>Copyright information:</b></p><p>Taken from "Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons"</p><p></p><p>The Plant Journal 2007;52(5):961-972.</p><p>Published online Jan 2007</p><p>PMCID:PMC2230500.</p><p>© 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd</p

Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons-1

<p><b>Copyright information:</b></p><p>Taken from "Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons"</p><p></p><p>The Plant Journal 2007;52(5):961-972.</p><p>Published online Jan 2007</p><p>PMCID:PMC2230500.</p><p>© 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd</p

Ab Initio Study of the Charge-Storage Mechanisms in RuO₂-Based Electrochemical Ultracapacitors

The charge-storage mechanisms in ruthenium dioxide are investigated with first-principles density-functional theory (DFT) calculations. Both proton-intercalated bulk and proton-adsorbed RuO₂(110) surfaces have been studied to obtain insight into the energetics of discharging processes in RuO₂-based aqueous supercapacitors. We predict the existence of a stable ruthenium oxyhydroxide (RuOOH) and demonstrate that the RuO₂(110) surface as well as a significant fraction of the available subsurface sites remain completely protonated during cyclic voltammetry measurements in aqueous electrolytes. DFT calculations also show that the bulk proton insertion not only is kinetically inhibited by a high energy barrier of proton diffusion in bulk RuO₂ (1.62 eV), but also is thermodynamically inactive under the experimental operating conditions due to a low intercalation voltage (0.08 V in the dilute limit). These results exclude simple bulk or surface protonation as the reason for excellent electrochemical performance of hydrous nanocrystalline RuO₂ supercapacitors and point to the importance of subsurface and grain boundary effects

Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons-3

<p><b>Copyright information:</b></p><p>Taken from "Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons"</p><p></p><p>The Plant Journal 2007;52(5):961-972.</p><p>Published online Jan 2007</p><p>PMCID:PMC2230500.</p><p>© 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd</p

Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons-0

<p><b>Copyright information:</b></p><p>Taken from "Identification of a plastid intercistronic expression element (IEE) facilitating the expression of stable translatable monocistronic mRNAs from operons"</p><p></p><p>The Plant Journal 2007;52(5):961-972.</p><p>Published online Jan 2007</p><p>PMCID:PMC2230500.</p><p>© 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd</p

DataSheet1_A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies.PDF

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.</p

Table1_A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies.XLSX

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.</p

Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model

We propose score dynamics (SD), a general framework for learning accelerated evolution operators with large timesteps from molecular dynamics (MD) simulations. SD is centered around scores or derivatives of the transition log-probability with respect to the dynamical degrees of freedom. The latter play the same role as force fields in MD but are used in denoising diffusion probability models to generate discrete transitions of the dynamical variables in an SD time step, which can be orders of magnitude larger than a typical MD time step. In this work, we construct graph neural network-based SD models of realistic molecular systems that are evolved with 10 ps timesteps. We demonstrate the efficacy of SD with case studies of the alanine dipeptide and short alkanes in aqueous solution. Both equilibrium predictions derived from the stationary distributions of the conditional probability and kinetic predictions for the transition rates and transition paths are in good agreement with MD. Our current SD implementation is about 2 orders of magnitude faster than the MD counterpart for the systems studied in this work. Open challenges and possible future remedies to improve SD are also discussed