Enantioselective CuH-Catalyzed Anti-Markovnikov Hydroamination of 1,1-Disubstituted Alkenes

Enantioselective synthesis of β-chiral amines has been achieved via copper-catalyzed hydroamination of 1,1-disubstituted alkenes with hydroxylamine esters in the presence of a hydrosilane. This mild process affords a range of structurally diverse β-chiral amines, including β-deuterated amines, in excellent yields with high enantioselectivities. Furthermore, catalyst loading as low as 0.4 mol% could be employed to deliver product in undiminished yield and selectivity, demonstrating the practicality of this method for large-scale synthesis.National Institutes of Health (U.S.) (Award GM58160

Enantioselective Synthesis of α-Aminosilanes by Copper-Catalyzed Hydroamination of Vinylsilanes

The synthesis of α-aminosilanes by a highly enantio- and regioselective copper-catalyzed hydroamination of vinylsilanes is reported. The system employs Cu-DTBM-SEGPHOS as the catalyst, diethoxymethylsilane as the stoichiometric reductant, and O-benzoylhydroxylamines as the electrophilic nitrogen source. This hydroamination reaction is compatible with differentially substituted vinylsilanes, thus providing access to amino acid mimics and other valuable chiral organosilicon compounds.National Institutes of Health (U.S.) (Award GM58160

A direct approach to amines with remote stereocentres by enantioselective CuH-catalysed reductive relay hydroamination

Amines with remote stereocentres (stereocentres that are three or more bonds away from the C–N bond) are important structural elements in many pharmaceutical agents and natural products. However, previously reported methods to prepare these compounds in an enantioselective manner are indirect and require multistep synthesis. Here, we report a copper-hydride-catalysed, enantioselective synthesis of γ- or δ-chiral amines from readily available allylic alcohols, esters and ethers using a reductive relay hydroamination strategy (a net reductive process in which an amino group is installed at a site remote from the original carbon–carbon double bond). The protocol was suitable for substrates containing a wide range of functional groups and provided remote chiral amine products with high levels of regio- and enantioselectivity. Sequential amination of substrates containing several carbon–carbon double bonds could be achieved, demonstrating the high chemoselectivity of this process.National Institutes of Health (U.S.) (Award GM58160

Towards a Deep Understanding of Multilingual End-to-End Speech Translation

In this paper, we employ Singular Value Canonical Correlation Analysis (SVCCA) to analyze representations learnt in a multilingual end-to-end speech translation model trained over 22 languages. SVCCA enables us to estimate representational similarity across languages and layers, enhancing our understanding of the functionality of multilingual speech translation and its potential connection to multilingual neural machine translation. The multilingual speech translation model is trained on the CoVoST 2 dataset in all possible directions, and we utilize LASER to extract parallel bitext data for SVCCA analysis. We derive three major findings from our analysis: (I) Linguistic similarity loses its efficacy in multilingual speech translation when the training data for a specific language is limited. (II) Enhanced encoder representations and well-aligned audio-text data significantly improve translation quality, surpassing the bilingual counterparts when the training data is not compromised. (III) The encoder representations of multilingual speech translation demonstrate superior performance in predicting phonetic features in linguistic typology prediction. With these findings, we propose that releasing the constraint of limited data for low-resource languages and subsequently combining them with linguistically related high-resource languages could offer a more effective approach for multilingual end-to-end speech translation.Comment: Accepted to Findings of EMNLP 202

Going the Extra Mile in Face Image Quality Assessment:A Novel Database and Model

An accurate computational model for image quality assessment (IQA) benefits many vision applications, such as image filtering, image processing, and image generation. Although the study of face images is an important subfield in computer vision research, the lack of face IQA data and models limits the precision of current IQA metrics on face image processing tasks such as face superresolution, face enhancement, and face editing. To narrow this gap, in this paper, we first introduce the largest annotated IQA database developed to date, which contains 20,000 human faces -- an order of magnitude larger than all existing rated datasets of faces -- of diverse individuals in highly varied circumstances. Based on the database, we further propose a novel deep learning model to accurately predict face image quality, which, for the first time, explores the use of generative priors for IQA. By taking advantage of rich statistics encoded in well pretrained off-the-shelf generative models, we obtain generative prior information and use it as latent references to facilitate blind IQA. The experimental results demonstrate both the value of the proposed dataset for face IQA and the superior performance of the proposed model.Comment: Appearing in IEEE TM

The role of calpains in ventilator-induced diaphragm atrophy

Contains fulltext : 178017.pdf (publisher's version ) (Open Access)BACKGROUND: Controlled mechanical ventilation (CMV) is associated with diaphragm dysfunction. Dysfunction results from muscle atrophy and injury of diaphragm muscle fibers. Enhanced proteolysis and reduced protein synthesis play an important role in the development of atrophy. The current study is to evaluate the effects of the calpains inhibitor calpeptin on the development of diaphragm atrophy and activation of key enzymes of the ubiquitin-proteasome pathway in rats under CMV. METHODS: Three groups of rats were studied: control animals (CON, n = 8), rats subjected to 24 h of MV (CMV, n = 8), and rats subjected to 24 h of MV after administration of the calpain inhibitor calpeptin (CMVC, n = 8). The diaphragm was analyzed for calpain activity, myosin heavy chain (MHC) content, and cross-sectional area (CSA) of diaphragmatic muscle fibers as a marker for muscle atrophy. In addition, key enzymes of the ubiquitin-proteasome pathway (MAFbx and MuRF1) were also studied. RESULTS: CMV resulted in loss of both MHCfast and MHCslow. Furthermore, the CSA of diaphragmatic muscle fibers was significantly decreased after 24 h of CMV. However, calpain inhibitor calpeptin prevented loss of MHC and CSA after CMV. In addition, calpeptin prevented the increase in protein expression of calpain1 and calpain2 and reduced calpain activity as indicated by reduced generation of the calpain cleavage product alphaII-spectrin in the diaphragm. CMV-induced upregulation of both MAFbx and MuRF1 protein levels was attenuated by treatment with calpeptin. CONCLUSIONS: The calpain inhibitor calpeptin prevents MV-induced muscle atrophy. In addition, calpeptin attenuated the expression of key proteolytic enzymes known to be involved in ventilator-induced diaphragm atrophy, including MAFbx and MuRF1

An Observed Correlation Between Thermal and Non-Thermal Emission in Gamma-Ray Bursts

Recent observations by the $Fermi$ Gamma-ray Space Telescope have confirmed the existence of thermal and non-thermal components in the prompt photon spectra of some Gamma-ray bursts (GRBs). Through an analysis of six bright Fermi GRBs, we have discovered a correlation between the observed photospheric and non-thermal $\gamma$-ray emission components of several GRBs using a physical model that has previously been shown to be a good fit to the Fermi data. From the spectral parameters of these fits we find that the characteristic energies, $E_{\rm p}$ and $kT$, of these two components are correlated via the relation $E_{\rm p} \propto T^{\alpha}$ which varies from GRB to GRB. We present an interpretation in which the value of index $\alpha$ indicates whether the jet is dominated by kinetic or magnetic energy. To date, this jet composition parameter has been assumed in the modeling of GRB outflows rather than derived from the data