Mesenchymal stem cells (MSCs) have been extensively investigated for the treatment of various diseases. The therapeutic potential of MSCs is attributed to complex cellular and molecular mechanisms of ...action including differentiation into multiple cell lineages and regulation of immune responses via immunomodulation. The plasticity of MSCs in immunomodulation allow these cells to exert different immune effects depending on different diseases. Understanding the biology of MSCs and their role in treatment is critical to determine their potential for various therapeutic applications and for the development of MSC-based regenerative medicine. This review summarizes the recent progress of particular mechanisms underlying the tissue regenerative properties and immunomodulatory effects of MSCs. We focused on discussing the functional roles of paracrine activities, direct cell–cell contact, mitochondrial transfer, and extracellular vesicles related to MSC-mediated effects on immune cell responses, cell survival, and regeneration. This will provide an overview of the current research on the rapid development of MSC-based therapies.
Conspectus The trifluoromethyl group is widely prevalent in many pharmaceuticals and agrochemicals because its incorporation into drug candidates could enhance chemical and metabolic stability, ...improve lipophilicity and bioavailability, and increase the protein bind affinity. Consequently, extensive attention has been devoted toward the development of efficient and versatile methods for introducing the CF3 group into various organic molecules. Direct trifluoromethylation reaction has become one of the most efficient and important approaches for constructing carbon–CF3 bonds. Traditionally, the nucleophilic trifluoromethylation reaction involves an electrophile and the CF3 anion, while the electrophilic trifluoromethylation reaction involves a nucleophile and the CF3 cation. In 2010, we proposed the concept of oxidative trifluoromethylation: the reaction of nucleophilic substrates and nucleophilic trifluoromethylation reagents in the presence of oxidants. In this Account, we describe our recent studies of oxidative trifluoromethylation reactions of various nucleophiles with CF3SiMe3 in the presence of oxidants. We have focused most of our efforts on constructing carbon–CF3 bonds via direct trifluoromethylation of various C–H bonds. We have demonstrated copper-mediated or -catalyzed or metal-free oxidative C–H trifluoromethylation of terminal alkynes, tertiary amines, arenes and heteroarenes, and terminal alkenes. Besides various C–H bonds, aryl boronic acids proved to be viable nucleophilic coupling partners for copper-mediated or -catalyzed cross-coupling reactions with CF3SiMe3. To further expand the reaction scope, we also applied H-phosphonates to the oxidative trifluoromethylation system to construct P–CF3 bonds. Most recently, we developed silver-catalyzed hydrotrifluoromethylation of unactivated olefins. These studies explore boronic acids, C–H bonds, and P–H bonds as novel nucleophiles in transition-metal-mediated or -catalyzed cross-coupling reactions with CF3SiMe3, opening new viewpoints for future trifluoromethylation reactions. Furthermore, we also achieved the oxidative trifluoromethylthiolation reactions of aryl boronic acids and terminal alkynes to construct carbon–SCF3 bonds by using CF3SiMe3 and elemental sulfur as the nucleophilic trifluoromethylthiolating reagent. These oxidative trifluoromethylation and trifluoromethylthiolation reactions tolerate a wide range of functional groups, affording a diverse array of CF3- and CF3S-containing compounds with high efficiencies, and provide elegant and complementary alternatives to classical trifluoromethylation and trifluoromethylthiolation reactions. Because of the importance of the CF3 and SCF3 moieties in pharmaceuticals and agrochemicals, these reactions would have potential applications in the life science fields.
A silver‐mediated oxidative difluoromethylation of styrenes and vinyl trifluoroborates with TMSCF2H is reported for the first time. This method enables direct and facile access to CF2H‐alkenes from ...abundant alkenes with excellent functional‐group compatibility. Moreover, this Ag/TMSCF2H protocol could further enable a series of radical difluoromethylation reactions of a wide array of substrates, offering a generic and complementary platform for the construction of diversified C−CF2H bonds.
A silver‐mediated oxidative difluoromethylation of styrenes and vinyltrifluoroborates with TMSCF2H to construct vinyl−CF2H bonds has been achieved for the first time. This protocol also provides a generic platform for radical difluoromethylation of a broad array of substrates including diverse alkenes, carboxylic acids, heteroarenes, and isonitriles, enabling expedient construction of diversified C−CF2H bonds.
Network Newton Distributed Optimization Methods Mokhtari, Aryan; Qing Ling; Ribeiro, Alejandro
IEEE transactions on signal processing,
2017-Jan.1,-1, 2017-1-1, Letnik:
65, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We study the problem of minimizing a sum of convex objective functions, where the components of the objective are available at different nodes of a network and nodes are allowed to only communicate ...with their neighbors. The use of distributed gradient methods is a common approach to solve this problem. Their popularity notwithstanding, these methods exhibit slow convergence and a consequent large number of communications between nodes to approach the optimal argument because they rely on first-order information only. This paper proposes the network Newton (NN) method as a distributed algorithm that incorporates second-order information. This is done via distributed implementation of approximations of a suitably chosen Newton step. The approximations are obtained by truncation of the Newton step's Taylor expansion. This leads to a family of methods defined by the number K of Taylor series terms kept in the approximation. When keeping K terms of the Taylor series, the method is called NN-K and can be implemented through the aggregation of information in K-hop neighborhoods. Convergence to a point close to the optimal argument at a rate that is at least linear is proven and the existence of a tradeoff between convergence time and the distance to the optimal argument is shown. The numerical experiments corroborate reductions in the number of iterations and the communication cost that are necessary to achieve convergence relative to first-order alternatives.
This paper develops the application of the alternating direction method of multipliers (ADMM) to optimize a dynamic objective function in a decentralized multi-agent system. At each time slot, agents ...in the network observe local functions and cooperate to track the optimal time-varying argument of the sum objective. This cooperation is based on maintaining local primal variables that estimate the value of the optimal argument and auxiliary dual variables that encourage proximity with neighboring estimates. Primal and dual variables are updated by an ADMM iteration that can be implemented in a distributed manner whereby local updates require access to local variables and the most recent primal variables from adjacent agents. For objective functions that are strongly convex and have Lipschitz continuous gradients, the distances between the primal and dual iterates to their corresponding time-varying optimal values are shown to converge to a steady state gap. This gap is explicitly characterized in terms of the condition number of the objective function, the condition number of the network that is defined as the ratio between the largest and smallest nonzero Laplacian eigenvalues, and a bound on the drifts of the optimal primal variables and the optimal gradients. Numerical experiments corroborate theoretical findings and show that the results also hold for non-differentiable and non-strongly convex primal objectives.
It is highly desirable, although very challenging, to develop self‐healable materials exhibiting both high efficiency in self‐healing and excellent mechanical properties at ambient conditions. ...Herein, a novel Cu(II)–dimethylglyoxime–urethane‐complex‐based polyurethane elastomer (Cu–DOU–CPU) with synergetic triple dynamic bonds is developed. Cu–DOU–CPU demonstrates the highest reported mechanical performance for self‐healing elastomers at room temperature, with a tensile strength and toughness up to 14.8 MPa and 87.0 MJ m−3, respectively. Meanwhile, the Cu–DOU–CPU spontaneously self‐heals at room temperature with an instant recovered tensile strength of 1.84 MPa and a continuously increased strength up to 13.8 MPa, surpassing the original strength of all other counterparts. Density functional theory calculations reveal that the coordination of Cu(II) plays a critical role in accelerating the reversible dissociation of dimethylglyoxime–urethane, which is important to the excellent performance of the self‐healing elastomer. Application of this technology is demonstrated by a self‐healable and stretchable circuit constructed from Cu–DOU–CPU.
A dimethylglyoxime–urethane (DOU)‐based polyurethane elastomer self‐heals immediately at room temperature and shows world‐record strength and toughness. Cu(II)DOU coordination bonds greatly strengthen the materials while enhancing the dynamics of the DOU bonds to facilitate self‐healing. This material design reconciles the contradictory properties of mechanical robustness and self‐healing efficiency, providing a powerful new strategy to create high‐performance self‐healing materials.
The development of catalytic carboacylation of simple olefins, which would enable the rapid construction of ketones with high levels of complexity and diversity, is very challenging. To date, the ...vast majority of alkene carboacylation reactions are typically restricted to single- and two-component methodologies. Here we describe a three-component carboacylation of alkenes via the merger of radical chemistry with nickel catalysis. This reaction manifold utilizes a radical relay strategy involving radical addition to an alkene followed by alkyl radical capture by an acyl-nickel complex to forge two vicinal C-C bonds under mild conditions. Excellent chemoselectivity and regioselectivity have been achieved by utilizing a pendant weakly chelating group. This versatile protocol allows for facile access to a wide range of important β-fluoroalkyl ketones from simple starting materials.
In recent years, green, low carbon and sustainable development has become a common topic of concern. Aiming at solving the drawback of low accuracy of PM2.5 concentration prediction, this paper ...proposes a method based on deep learning to predict PM2.5 concentration. Firstly, we comprehensively consider various meteorological elements such as temperature, relative humidity, precipitation, wind, visibility, etc., and comprehensively analyze the correlation between meteorological elements and PM2.5 concentration. Secondly, the time series data of PM2.5 concentration monitoring stations are used as the reference sequence and comparison sequence in the gray correlation analysis algorithm to construct the spatial weight matrix, and the spatial relationship of the original data is extracted by using the spatial weight matrix. Finally, we combine the forgetting and input threshold to synthesize the updated threshold, merge the unit state and the hidden state, and use the Gate Recurrent Unit (GRU) as the core network structure of the recurrent neural network. Compared with the traditional LSTM model, the GRU model is simpler. In terms of convergence time and required epoch, GRU is better than the traditional LSTM model. On the basis of ensuring the accuracy of the model, the training time of the model is further reduced. The experimental results show that the root mean square error and the average absolute error of this method can reach 18.32 ug⋅m−3 and 13.54 ug⋅m−3 in the range of 0–80 h, respectively. Therefore, this method can better characterize the time series characteristics of air pollutant changes, so as to make a more accurate prediction of PM2.5 concentration.
A large number of reagents have been developed for the synthesis of trifluoromethylated compounds. However, an ongoing challenge in trifluoromethylation reaction is the use of less expensive and ...practical trifluoromethyl sources. We report herein the unprecedented direct trifluoromethylation of (hetero)arenes using trifluoromethanesulfonic anhydride as a radical trifluoromethylation reagent by merging photoredox catalysis and pyridine activation. Furthermore, introduction of both the CF3 and OTf groups of the trifluoromethanesulfonic anhydride into internal alkynes to access tetrasubstituted trifluoromethylated alkenes was achieved. Since trifluoromethanesulfonic anhydride is a low‐cost and abundant chemical, this method provides a cost‐efficient and practical route to trifluoromethylated compounds.
The light FFFantastic: An unprecedented application of trifluoromethanesulfonic anhydride as a radical trifluoromethylation reagent was developed by merging photoredox catalysis and pyridine activation. The synthetic utility of this method is exemplified by the C−H trifluoromethylation of (hetero)arenes and trifluoromethyltriflation of alkynes.
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