[2]Catenane Synthesis via Covalent Templating

After earlier unsuccessful attempts, this work reports the application of covalent templating for the synthesis of mechanically interlocked molecules (MiMs) bearing no supramolecular recognition sites. Two linear strands were covalently connected in a perpendicular fashion by a central ketal linkage. After subsequent attachment of the first strand to a template via temporary benzylic linkages, the second was linked to the template in a backfolding macrocyclization. The resulting pseudo[1]rotaxane structure was successfully converted to a [2]catenane via a second macrocyclization and cleavage of the ketal and temporary linkages.     

The coarse moduli space of a flat analytic groupoid

Annali di Matematica Pura ed Applicata (1923 -) - Let $$\mathcal X $$ be a flat analytic groupoid $$R_X\stackrel{s}{\underset{t}{\rightrightarrows }}X$$ such that the holomorphic map...     

Folding of Synthetic Homogeneous Glycoproteins in the Presence of a Glycoprotein Folding Sensor Enzyme

UDP‐glucose:glycoprotein glucosyltransferase (UGGT) plays a key role in recognizing folded and misfolded glycoproteins in the glycoprotein quality control system of the endoplasmic reticulum. UGGT detects misfolded glycoproteins and re‐glucosylates them as a tag for misfolded glycoproteins. A flexible model to reproduce in vitro folding of a glycoprotein in the presence of UGGT in a mixture containing correctly folded, folding intermediates, and misfolded glycoproteins is described. The data demonstrates that UGGT can re‐glucosylate all intermediates in the in vitro folding experiments, thus indicating that UGGT inspects not only final folded products, but also the glycoprotein folding intermediates.     

Inherently Chiral Macrocyclic Oligothiophenes: Easily Accessible Electrosensitive Cavities with Outstanding Enantioselection Performances

Linear conjugated oligothiophenes of variable length and different substitution pattern are ubiquitous in technologically advanced optoelectronic devices, though limitations in application derive from insolubility, scarce processability and chain‐end effects. This study describes an easy access to chiral cyclic oligothiophenes constituted by 12 and 18 fully conjugated thiophene units. Chemical oxidation of an “inherently chiral” sexithiophene monomer, synthesized in two steps from commercially available materials, induces the formation of an elliptical dimer and a triangular trimer endowed with electrosensitive cavities of different tunable sizes. Combination of chirality with electroactivity makes these molecules unique in the current oligothiophenes literature. These macrocycles, which are stable and soluble in most organic solvents, show outstanding chiroptical properties, high circularly polarized luminescence effects and an exceptional enantiorecognition ability.     

Enzyme Design from the Bottom Up: An Active Nickel Electrocatalyst with a Structured Peptide Outer Coordination Sphere

Catalytic, peptide‐containing metal complexes with a well‐defined peptide structure have the potential to enhance molecular catalysts through an enzyme‐like outer coordination sphere. Here, we report the synthesis and characterization of an active, peptide‐based metal complex built upon the well‐characterized hydrogen production catalyst [Ni(P^Ph₂N^Ph)₂]²⁺ (P^Ph₂N^Ph=1,3,6‐triphenyl‐1‐aza‐3,6‐diphosphacycloheptane). The incorporated peptide maintains its β‐hairpin structure when appended to the metal core, and the electrocatalytic activity of the peptide‐based metal complex (≈100,000 s^?1) is enhanced compared to the parent complex ([Ni(P^Ph₂N^APPA)₂]²⁺; ≈50,500 s^‐1). The combination of an active molecular catalyst with a structured peptide provides a scaffold that permits the incorporation of features of an enzyme‐like outer‐coordination sphere necessary to create molecular electrocatalysts with enhanced functionality.     

Insights into the Decomposition of Olefin Metathesis Precatalysts

The decomposition of a series of benzylidene, methylidene, and 3‐phenylindenylidene complexes has been probed in alcohol solution in the presence of base. Tricyclohexylphosphane‐containing precatalysts are shown to yield [RuCl(H)(H₂)(PCy₃)₂] in isopropyl alcohol solutions, while 3‐phenylindenylidene complexes lead to η⁵‐(3‐phenyl)indenyl products. The potential‐energy surfaces for the formation of the latter species have been probed using density functional theory studies.     

Tetracyanoquinodimethane Reduction by Complexed Guanidinyl‐Functionalized Aromatic Compounds

In this work, we report on the reduction of tetracyanoquinodimethane (TCNQ) with dicationic complexes of guanidinyl‐functionalized aromatic (GFA) electron donors. In contrast to reduction with free GFAs, milder reduction conditions were achieved, and this led to semiconducting materials with extended TCNQ π stacking. The charge on the TCNQ units was estimated from the structural data obtained by single‐crystal X‐ray diffraction analysis and from IR spectroscopic data. The electrical conductivity was studied and the activation energy of the semiconducting materials was estimated from the temperature dependence of the conductivity.     

Novel betulin derivatives inhibit IFN-γ and modulates COX-2 expression

Abstract

Betulin (BE) is a pentacyclic triterpenes, obtained from natural sources and with several biological activities described, such as anti-tumoral and anti-inflammatory activities. The BE esterification at hydroxyl group (C-3 and C-28) resulted in five new ester derivatives with different numbers of carbons or halogens (chlorine and fluorine). Among these BE derivatives, two (2a e 2c) were able to significantly decrease IFN-g (*p?=?0.0391; **p?=?0.0156) and 2c modulated the expression of COX-2 better than Dexamethasone (DEXA). Regarding to cytotoxic assay, the best results were obtained for BE without modifications, with emphasis on tumoral cell lines Raji and MCF-7. The derivatives 2a and 2c showed immunomodulation activity (for the cytokines IFN-g). The presence of chorine in BE seems to be important for the ability of modulate COX-2 expression, since the ester chloride derivative 2c at 100?μM is more powerful inhibitor of COX-2 than DEXA.     

Sensing the Anti-Epileptic Drug Perampanel with Paper-Based Spinning SERS Substrates

The applications of SERS in therapeutic drug monitoring, or other fields of analytical chemistry, require the availability of sensitive sensors and experimental approaches that can be implemented in affordable ways. In this contribution, we show the production of cost-effective SERS sensors obtained by depositing Lee-Meisel Ag colloids on filter paper either by natural sedimentation or centrifugation. We have characterized the morphological and plasmonic features of the sensors by optical microscopy, SEM, and UV-Vis spectroscopy. Such sensors can be used to quantify by SERS the anti-epileptic drug Perampanel (in the concentration range 1 × 10⁻⁴–5 × 10⁻⁶ M) by spinning them during the micro-Raman measurements on the top of a custom device obtained from spare part hard disk drives. This approach minimizes laser-induced heating effects and allows averaging over the spatial non-uniformity of the sensor.     

A Probabilistic Re-Intepretation of Confidence Scores in Multi-Exit Models

In this paper, we propose a new approach to train a deep neural network with multiple intermediate auxiliary classifiers, branching from it. These ‘multi-exits’ models can be used to reduce the inference time by performing early exit on the intermediate branches, if the confidence of the prediction is higher than a threshold. They rely on the assumption that not all the samples require the same amount of processing to yield a good prediction. In this paper, we propose a way to train jointly all the branches of a multi-exit model without hyper-parameters, by weighting the predictions from each branch with a trained confidence score. Each confidence score is an approximation of the real one produced by the branch, and it is calculated and regularized while training the rest of the model. We evaluate our proposal on a set of image classification benchmarks, using different neural models and early-exit stopping criteria.