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An efficient approach to allylic boronates via iron-catalyzed boration of allylic esters is described. The reactions of allylic esters and bis(pinacolato)diboron (B2pin2) proceed smoothly catalyzed by FeCl2/PPh3. Thus, a wide range of allylic boronates with broad functional-group compatibility are obtained.

There are many lines of evidence indicating that mechanical stress regulates bone metabolism and promotes bone growth. BMP, Wnt, ERK1/2, and OPG/RANKL are the main molecules thought to regulate the effects of mechanical loading on bone formation. Recently, microRNAs were found to be involved in bone cell proliferation and differentiation, regulating the balance of bone formation and bone resorption. Emerging evidence indicates that microRNAs also participate in mechanical stress-mediated bone metabolism, and is associated with disuse induced osteoporosis or osteopenia. Mechanical stress is able to induce expression of microRNAs that modulate the expression of osteogenic and bone resorption factors, leading to the positive impact of mechanical stress on bone. This review discusses the emerging evidence implicating an important role for microRNAs in the mechanical stress response in bone cells, as well as the challenges of translating microRNA research into potential treatment. J. Cell. Physiol. 232: 1239-1245, 2017. © 2016 Wiley Periodicals, Inc.

The high computation and memory storage of large deep neural networks (DNNs) models pose intensive challenges to the conventional Von-Neumann architecture, incurring sub-stantial data movements in the memory hierarchy. The memristor crossbar array has emerged as a promising solution to mitigate the challenges and enable low-power acceleration of DNNs. Memristor-based weight pruning and weight quantization have been seperately investigated and proven effectiveness in reducing area and power consumption compared to the original DNN model. However, there has been no systematic investigation of memristor-based neuromorphic computing (NC) systems considering both weight pruning and weight quantization. In this paper, we propose an unified and systematic memristor-based framework considering both structured weight pruning and weight quantization by incorporating alternating direction method of multipliers (ADMM) into DNNs training. We consider hardware constraints such as crossbar blocks pruning, conductance range, and mismatch between weight value and real devices, to achieve high accuracy and low power and small area footprint. Our framework is mainly integrated by three steps, i.e., memristor-based ADMM regularized optimization, masked mapping and retraining. Experimental results show that our proposed framework achieves 29.81× (20.88×) weight compression ratio, with 98.38% (96.96%) and 98.29% (97.47%) power and area reduction on VGG-16 (ResNet-18) network where only have 0.5% (0.76%) accuracy loss, compared to the original DNN models. We share our models at anonymous link http://bit.ly/2Jp5LHJ.

We present the quadratic soliton-like combs in a half-harmonic generation regime by optical parametric oscillator configurations with a continuous pump.

Objective: This study aimed to investigate whether there exist the limits of finger tapping frequency in the peripheral nerve injury detection in upper limb, and the effects of rehabilitation treatment on upper limb with peripheral nerve injury through finger tapping.Methods: Here, 54 patients with peripheral nerve injury in upper limb were selected. We conducted finger tapping frequency test and Lind-mark hand function assessment score on the 54 subjects, and recorded the data 2-week before and after rehabilitation treatment.Results: Finger tapping frequency and Lind-mark hand function assessment score have a high positive correlation regardless of the side of upper limb with peripheral nerve injury before and after the rehabilitation treatment. Finger tapping frequency of the right affected hand after treatment is significantly higher than that of before treatment (male: P < 0.05; female: P < 0.01), while finger tapping frequency of the left affected hand after treatment shows no significant difference compared to before treatment. Meanwhile, finger tapping frequency of the female subjects' unaffected hand after treatment is significantly higher than before treatment (left: P < 0.01; right: P < 0.05), however, this was not observed in male subjects. Based on data analysis, there is a high-correlation between finger tapping frequency and Lind-mark score of the patients' affected hand with brachial plexus nerve injury. A trend of the patients' affected hand with radial nerve injury is similar with brachial plexus nerve injury.Conclusion: Compared with Lind-mark score, finger tapping frequency outperformed in the aspect of speed of neural impulse conduction in patients with peripheral nerve damage.

Processing-in-memory (PIM) architectures have demonstrated great potential in accelerating numerous deep learning tasks. Particularly, resistive random-access memory (RRAM) devices provide a promising hardware substrate to build PIM accelerators due to their abilities to realize efficient in-situ vector-matrix multiplications (VMMs). However, existing PIM accelerators suffer from frequent and energy-intensive analog-to-digital (A/D) conversions, severely limiting their performance. This paper presents a new PIM architecture to efficiently accelerate deep learning tasks by minimizing the required A/D conversions with analog accumulation and neural approximated peripheral circuits. We first characterize the different dataflows employed by existing PIM accelerators, based on which a new dataflow is proposed to remarkably reduce the required A/D conversions for VMMs by extending shift and add (S+A) operations into the analog domain before the final quantizations. We then leverage a neural approximation method to design both analog accumulation circuits (S+A) and quantization circuits (ADCs) with RRAM crossbar arrays in a highly-efficient manner. Finally, we apply them to build an RRAM-based PIM accelerator (i.e., \textbf{Neural-PIM}) upon the proposed analog dataflow and evaluate its system-level performance. Evaluations on different benchmarks demonstrate that Neural-PIM can improve energy efficiency by 5.36x (1.73x) and speed up throughput by 3.43x (1.59x) without losing accuracy, compared to the state-of-the-art RRAM-based PIM accelerators, i.e., ISAAC (CASCADE)., 14 pages, 13 figures, Published in IEEE Transactions on Computers

Nitrous acid (HONO) plays a significant role in tropospheric chemistry. The emission sources of HONO, however, are poorly characterized, which constraints the predictive capabilities of HONO and the associated environmental influences in models. This study measured the emission factors of HONO (EFHONO) from the agricultural residue (including wheat, rice, corn and soybean straws) open burning, the largest biomass combustion source in China. Based on this, a high-resolution (0.25 ° × 0.25 °) emission inventory of HONO from 2011 to 2015 was established using the city-level activity data compiled through statistical yearbook review in combination with machine learning algorithms, including linear regression (LR), back-propagation neural network (BPNN), general regression neural network (GRNN) and random forest (RF). Results showed that the averaged EFHONO from open burning of wheat, rice, corn and soybean straws were 0.10, 0.25, 0.98 and 0.97 g kg−1, respectively. Total annual emissions of HONO were estimated to be 101347.3, 100232.1, 104278.3, 98383.0 and 107783.9 tons, respectively, for 2011–2015. Regions with high HONO emission intensities were mainly concentrated in North China Plain and Northeast China, whereas low intensities were mainly allocated to western regions. The temporal distribution of average provincial emissions showed the peaks in March, April, June and October, respectively. Results shown herein should be useful for improving the accuracy of HONO budgets and air quality simulations in China.

An efficient method for the synthesis of (Z)-selective α-trifluoromethyl alkenyl triflates is described. As an important fluorinated building block, it is utilized successfully for the synthesis of various trifluoromethyl derivatives such as diarylethylenes, enynes, alkynes, and benzofurans.

Considering the Rashba and Zeeman effects, the effective Hamiltonian for electrons in AlGaN/GaN quantum wells (QWs) with the magnetic field is obtained, and the effective transverse and longitudinal g -factor ( g ⊥ , / / ) are derived. The small anisotropy of the g factor in bulk wurtzite materials is clearly shown, while the anisotropy in QWs induced by the quantum confined effect is evident. Moreover, the average g factor ( g *) depends greatly on the position of the origin along the growth axis ( c axis). With increasing well thickness, both g ⊥ and g / / increase, and the g -factor anisotropy first decreases and then increases slowly. Results show the g -factor and its anisotropy in III-nitride QWs can be modulated by the well thickness, and they are greatly affected by the internal electric field and the quantum confined effect.

The study of atmospheric chemical compositions in remote areas is of great significance for understanding the biogeochemical impact of atmospheric dry deposition on ecosystems. In this study, a total of 50 p.m.2.5 samples were collected at a high alpine forest of Mt. Gongga, Eastern Tibetan Plateau from May 2015 to May 2016 to investigate the characteristics of PM2.5 mass concentration and its major compositions including elemental carbon (EC), organic carbon (OC), and 24 trace elements. The average PM2.5 mass concentration was 17.19 ± 8.81 μg/m3, which was at an intermediate level compared with other areas of Tibetan Plateau. The yearly average concentrations of OC and EC were 2.98 ± 1.95 and 0.43 ± 0.33 μg/m3, accounting for 19.49% and 2.51% of PM2.5 mass, respectively, and the sums of the total concentrations of the 24 analyzed trace elements were 3.70 ± 0.80 μg/m3, accounting 27% of PM2.5 mass concentration. PM2.5, EC and OC showed the higher concentrations and larger fluctuation in the dry season (October 2015 to May 2016) compared with those in the wet season (June 2015 to September 2015), which was attributed to the multiple factors including the increases of biomass burning and fossil fuel emissions, the relatively shallow boundary layer height and lower temperature, and the less precipitation. Two distinct seasonal patterns were observed for the 24 analyzed trace elements in PM2.5: the crustal-derived trace elements like Fe, Al, Mn and Sr showed the higher concentrations in the wet season, while anthropogenic-derived elements such as Cd, Pb, Ni and Zn exhibited the higher level during the dry season. Six sources were identified for PM2.5 at Mt. Gongga with the application of the positive matrix factorization (PMF). Biomass burning (27.06%) and crustal source (26.93%) were the two main sources, followed by secondary formation (16.41%), traffic-related source (12.89%), coal burning (10.57%) and industrial metallurgical process (6.15%). Finally, it was proposed that the atmospheric acidic processing could not only promote the dissolution of Fe, but also enhance the solubility of the other trace elements in the atmosphere during the transport. Accordingly, this would increase the bioavailability and/or toxicity to the biotic and plants.

Ambient SO2 pollution poses a great threat on air quality, human health, and ecosystem safety. The ground-level SO2 monitoring sites over China have been established during the past years, while the long-term SO2 data was still missing before 2014, which cannot reveal the evolution trend of SO2 pollution and assess its response to the anthropogenic activity. In this work, we developed a high-quality random forest (RF) model to simulate the long-term SO2 concentration across the entire China from 1973 to 2014, based on substantial explanatory variables (e.g., meteorological factors, SO2 emission intensity, land use types). The 10-fold cross-validation R2 value and root mean square error (RMSE) over China reached 0.64 and 17.06 μg/m3, respectively, both of which were significantly higher than those of other models such as back propagation neural network (BPNN) and generalized regression neutral network (GRNN). Among all of the predictors, T displayed the highest relative importance value, followed by WS, Prec, SO2 emission intensity, RH, DOY, elevation, and the lower one for land use types and P. The estimated mean SO2 concentration during 1973–2014 displayed the remarkably spatial variation with the higher value in North China Plain (NCP) and Middle part of Inner Mongolia. This historical SO2 level estimation suggested that air pollution was not a new environmental issue that could be dated back to 1973. Overall, the annually mean SO2 level for each grid increased from 29.46 ± 9.79 to 31.44 ± 8.77 μg/m3 from 1973 to 2014. The annually mean SO2 concentration in NCP showed rapid increase from 34.32 ± 3.05 to 36.97 ± 3.18 μg/m3 during 1973–2002, whereas they decreased significantly after 2003 (from 37.46 ± 3.20 to 36.13 ± 3.48 μg/m3 during 2003–2014). The gradual decrease since 2003 was benefitted from the adjustment of the energy consumption structure and the adoption of emission control technologies. However, the SO2 levels in some western regions showed the violent increases since 2003 due to the proposal of “development of the western region”. The estimated daily SO2 concentration across the entire China could provide the essential data for epidemiological research and air pollution prevention.

Z-scheme-type photocatalysts with two photochemical systems of graphic-C3N4 (g-C3N4) and anatase TiO2 (A-TiO2) nanocrystals combined with Au nanoparticles (NPs) [(Au/A-TiO2)@g-C3N4] were successfully fabricated. The surface heterojunction between coexposed {001} and {101} facets in A-TiO2 nanocrystals improves separation efficiency of photoelectrons and holes. Supported Au NPs gather and transfer the stimulated electrons originated from A-TiO2 to g-C3N4. Wrapped g-C3N4 nanosheets can not only trap the photoelectrons, but also its surface π bond can improve adsorption capabilities for CO2. (Au/A-TiO2)@g-C3N4 catalysts with enriched surface photoelectrons and CO2 exhibit high photocatalytic activity for visible-light-driven conversion of CO2, i.e., the formation rates of CH4 and CO over (Au/A-TiO2)@C3N4-5 catalyst are 37.4 and 21.7 μmol g−1 h−1, respectively. The selectivity for CO2 reduction is higher than 99%, and the selectivity of CH4 product increases from 1.4% to 63.3%. The innovation of Z-scheme-type photocatalysts is expected to provide new inspiration for artificial simulation photosynthesis.

Ambient ozone (O3) poses great damage to human health, biodiversity, and climate change. Although the health risk due to O3 pollution has been widely evaluated, the spatiotemporal variation of O3 level and its potential health impact in a remote tropical island was less concerned. In the present study, we firstly employed an efficient machine learning model named random forest (RF) to fill the missing O3 column amount over Hainan Island of China based on the meteorological factors and other geographical covariates. The result suggested that the RF model achieved the best performance (R2 = 0.87, RMSE = 6.36 DU) among all of the filling methods. We further used an extreme gradient boosting (XGBoost) algorithm to estimate the surface O3 level around Hainan Island on the basis of the full-coverage O3 column amount and other predictors. The XGBoost method showed the better predictive performance (R2 = 0.59, RMSE = 24.14 μg/m3) compared with other estimation models. The predicted O3 concentration exhibited remarkably spatial difference with the highest value observed in Dongfang (77.61 ± 5.25 μg/m3), followed by that in Changjiang (72.51 ± 5.22 μg/m3), and the lowest one in Lingshui (64.16 ± 2.71 μg/m3). Based on the estimated O3 level, we found that the annually mean nonattainment days in Dongfang reached 29.26 ± 35.20 days and about one third of days in the winter fell into the severe O3 pollution over Hainan Island. Besides, the mean all-cause mortalities owing to severe O3 pollution over Hainan Island were calculated to be 391 (95%CI: (212–570)) cases each year, accounting for 0.004% of all the population in Hainan Island. The statistical simulation of O3 level at a remote island updated the traditional knowledge and aroused the public concern on island air pollution.

A new design idea is put forward to adapt the design requirement of wide-speed range vehicle in the paper. The novel points are that the design Mach number and shock flowfield are variable continuously in the design methodology. The design process is introduced about the wide-speed waverider and the repeatability function is achieved systematically by means of the parameterized modeling. In order to validate the advantages of the new approach during the wide-speed range, the flowfield characteristics are investigated numerically in the paper. The numerical method is validated by comparing the simulation results with wind tunnel experiment data. The obtained results show that the wide-speed range waverider could be obtained easily by the parameterized modeling. For the variable Mach number waverider, the pressure drag accounts for the main part of total drag, about 60∼70%. The percentage of viscous drag increases and that of the rear drag decreases with the increase of flow velocity. The viscous L / D of Case 5 does not change obviously during the wide-speed range. The variable Mach number waverider holds the steady aerodynamic performance during the wide-speed range. This shows that the new design method is very useful for the integrated design of wide-speed hypersonic vehicles.

Size-segregated aerosol samples were collected in the land-sea boundary zone of East China, the offshore area of East China Sea (ECS), to determine the concentrations of water-soluble inorganic nitrogen (WSIN), water-soluble organic nitrogen (WSON), urea, and free amino acids (FAAs), to quantify their sources, and to estimate their dry deposition fluxes. The results indicated that the mean concentrations of WSIN, WSON, urea, and FAAs in total suspended particle (TSP) were 547.14 nmol/m3, 258.64 nmol/m3, 12.69 nmol/m3, and 2589.03 pmol/m3, respectively. The WSIN, WSON, and urea concentrations in TSP showed remarkably spatial variation with the higher one during the shipping line (SL) 1 and SL4, while they exhibited the lower ones during SL3 and SL5. The biomass burning and fertilizer application in the continent provided important precursors for WSIN, WSON, and urea in the offshore areas. Besides, O3-related photochemical process also promoted the secondary formation of these species. In contrast, these anthropogenic sources played the minor roles on the relatively remote marine region (SL5). It was interesting to note that the total FAAs during SL5 did not show the lowest concentration, which might be contributed by the bubble bursting on the sea surface and the release of bacteria. The Positive Matrix Factorization (PMF) method identified fertilizer application and secondary formation were important sources for WSIN (35.54% and 27.53%) and WSON (43.07% and 40.46%), respectively. However, fertilizer application and combustion sources played the crucial important roles on urea (65.93% and 19.13%) and FAAs (51.35% and 16.35%). The mean dry deposition fluxes of WSIN, WSON, urea, and FAAs in the ECS offshore area were 206763.57 nmol m−2 d−1, 103763.07 nmol m−2 d−1, 4746.20 nmol m−2 d−1, and 1047.08 nmol m−2 d−1, respectively. The present study revealed that the ambient N-bearing particles in the land-sea boundary zone suffered from the combined effects of continental transport and the release of marine organisms.

The various interfering signals present in the space result in the inability to obtain a clean and clear solar radio dynamic spectrum, which affects the effective observation of solar radio burst events. At the data processing level, we propose a method for predicting and processing radio interference signals in solar radio burst events using recurrent neural network in deep learning. Firstly, the radio signal that satisfies the condition is selected by the amount of solar radio flux of all frequency channels at some moment, and then the position of the initial time of the burst event is located by using the variation curve of the solar radio flux with time under the single frequency channel. After that, the constructed recurrent neural network is used to predict the signal value of the radio in the burst area. Finally, according to the linear additivity of the signal, the value of the clean pure burst event is obtained by subtracting the predicted radio value from the original value of the burst area. The experimental results show that the proposed method can effectively remove the interference in the solar radio dynamic spectrum and preserve the effective information of the burst event to the greatest extent. This provides a new idea and research direction for deep learning in the anti-interference processing of astronomical big data.

The wet S deposition was treated as a key issue because it played the negative on the soil acidification, biodiversity loss, and global climate change. However, the limited ground-level monitoring sites make it difficult to fully clarify the spatiotemporal variations of wet S deposition over China. Therefore, an ensemble model of improved machine learning and geostatistical method named fruit fly optimization algorithm-random forest-spatiotemporal Kriging (FOA-RF-STK) model was developed to estimate the nationwide S deposition based on the emission inventory, meteorological factors, and other geographical covariates. The ensemble model can capture the relationship between predictors and S deposition flux with the better performance (R2 = 0.68, root mean square error (RMSE) = 7.51 kg ha−1 yr−1) compared with the original RF model (R2 = 0.52, RMSE = 8.99 kg ha−1 yr−1). Based on the improved model, it predicted that the highest and lowest S deposition flux were mainly concentrated on the Southeast China (69.57 kg S ha−1 yr−1) and Inner Mongolia (42.37 kg S ha−1 yr−1), respectively. The estimated wet S deposition flux displayed the remarkably seasonal variation with the highest value in summer (22.22 kg S ha−1 sea−1), follwed by ones in autumn (18.30 kg S ha−1 sea−1), spring (16.27 kg S ha−1 sea−1), and the lowest one in winter (14.71 kg S ha−1 sea−1), which was closely associated with the rainfall amounts. The study provides a novel approach for the S deposition estimation at a national scale.

Background: Mild cognitive impairment (MCI) is a brain disease with both anatomical and functional alterations. There is clear evidence that individuals that are diagnosed with MCI have a high risk to develop dementia in the next 2–5 years compared to an age-matched population with a non-MCI diagnosis. The present study aimed to investigate whether the finger tapping frequency of patients with MCI was different from that of healthy individuals without MCI, and whether Tai Chi, a traditional Chinese movement discipline, could improve the finger tapping frequency of MCI patients.Methods: The study population consisted of subjects of ≥50 years of age. Group one included 40 subjects without exercise habits from communities of Yangpu District in Shanghai, and group two included 60 subjects from a Tai Chi class in Shanghai Elderly University of Huangpu District. The Montreal Cognitive Assessment (MoCA) and a finger tapping test were conducted to assess the finger tapping frequency of all subjects.Results: The MoCA score of MCI subjects was significantly lower compared to subjects without MCI (P < 0.01), and was not influenced by age, weight, or height. The finger tapping frequency of MCI subjects’ left hands was significantly lower compared to that of healthy subjects without MCI (P < 0.01), and a similar trend was observed for the subjects’ right hand. The MoCA score of MCI subjects in the Tai Chi class was significantly lower than that of healthy subjects without MCI (P < 0.01), which was not influenced by age, weight or height. The finger tapping frequency of MCI subjects’ right hands was lower compared to that of healthy subjects in the Tai Chi class without MCI (P < 0.05), but no significant difference regarding the finger tapping frequency of the left hand was observed.Conclusion: These findings suggested that finger tapping frequency of MCI subjects was significantly lower compared to normal subjects without MCI, and long-term Tai Chi exercise could reduce this significant difference. Moreover, there was no significant difference between groups for the subjects’ non-dominant (left) hand.

A base-controlled regiodivergent azidation of trifluoromethyl alkenyl triflates providing either (E)-3-azido-1-aryl-4,4,4-trifluorobut-1-ene (CF

A method for the synthesis of allylboronates by iron-catalyzed boration of allylic alcohols with H3BO3 as an additive is developed. The introduction of H3BO3 promotes the cleavage of C‒O bond in allylic alcohols obviously. Functional groups, such as fluoro, chloro, bromo, alkyl, and alkoxy, are tolerated well. Thus, various allylboronates are obtained in acceptable yield.

In this paper, the viscous effects of shock reflection hysteresis in steady supersonic flow is studied analytically, experimentally and numerically, taking the boundary layer developed over the reflecting surface into consideration. Based on a hypothesis that the interaction origin keep invariable during the shock–boundary layer interaction, the separation region is replaced by a virtual wedge with a fixed angle. Combined the free-interaction theory with the shock reflection hysteresis theory, a detailed analysis describing the viscous flow structures of shock reflection configurations is proposed. It is illustrated by mean of further analysis that a shock reflection hysteresis which is similar to the one that exists in the reflection of symmetric shock waves is found theoretically. Experimental results verify the analytical interaction model as well as the existence of two shock reflection patterns, although the hysteresis is not conformed by experiments. This paper also presents results of simulations for the hysteresis process which results from keeping the wedge angle constant and changing the free-stream Mach number, for confirming the hysteresis phenomenon.

As an important part of the basic research on shock wave, shock reflection phenomena which appear in many practical situations, ranging from supersonic aircraft wings to hypersonic vehicles and engines, always receive a great deal of attention. Generally speaking, the slipstream which is an important part of shock reflection structures has a significant effect on the flow property. On the one hand, better understanding of the slipstream is beneficial to flow control which aims to reduce the stagnation pressure loss. On the other hand, it also provides a reasonable way in mixing enhancement. In view of these structures, the schlieren method and the shadow method are widely applied for flow visualization so far. However, the photographs which are obtained by the above methods merely reflect the flow field that is through temporal and spatial integration, rather than high-spatiotemporal resolution images. Also, the evolution of the slipstream cannot be fully investigated by means of the traditional methods of flow visualization. Garrison and Settles (1992) trace the evolution of the slipstream which emanates from the triple point of the k-shock system using the Planar Laser Scattering (PIS) technique. Afterwards, to describe the steady Mach reflection configuration approximately, Azevedo and Liu (1993) and Li and Ben-Dor (1997) investigate shape of the slipstream ignoring the viscous effect respectively. Then, Rikanati et al. (2006) indicate that the slipstream thickening of the pseudo-steady Mach reflection is caused by small-scale growth of the Kelvin–Helmholtz shear flow instability using the interferometry technique. Afterwards, Rubidge et al. (2013a, b; Rubidge and Skews 2014) point out that Kelvin–Helmholtz instability do form on the pseudo-steady Mach reflection slipstream, and describe the Kelvin–Helmholtz instability evolution using the schlieren images. However, little work has been conducted on the development of the slipstream in steady shock reflection. Hence, a series of experiments are performed to observe the fine structures of the steady shock reflection and investigate the evolution of the slipstream in this paper, using Nano-tracer Planar Laser Scattering (NPLS) technique.

A Pd-catalyzed hydrogenation of (Z)-trifluoromethyl alkenyl triflate providing either (Z)- or (E)-3,3,3-trifluoropropenyl derivatives with excellent divergent geometric control in good yield is described. Catalyzed by Pd(OAc)2/PPh3, the reduction of (Z)-trifluoromethyl alkenyl triflates with HSiEt3 gave (E)-3,3,3-trifluoropropenyl derivatives, and while using HCOOH/Et3N as the reducing agent, the (Z)-isomers were obtained through an elimination/hydrogenation tandem pathway. Both transformations showed excellent geometrical selectivity.

The first ferrous chloride catalyzed boration/β-fluorine elimination of trifluoromethyl alkenes is described. Thus, a full range of gem-difluoroallylboronates were obtained in high yield under mild conditions. As an important fluorinated building block, gem-difluoroallylboronate can be readily converted into diverse difluoro-substituted species.

A highly selective and atom efficient ‘trifluoroacetic ester/ketone metathesis’ has been sincerely witnessed. Enolizable alkyl (at least two non-hydrogen atoms) aryl ketones were found to react readily with ethyl trifluoroacetate under the promotion of NaH to afford trifluoroacetic ester/ketone exchange products, trifluoromethyl ketones (TFMKs), and aromatic acid esters, which were quite different from the general Claisen condensation products, 1,3-diketones. The outcome of the reaction between ketone and ethyl trifluoroacetate is strongly related to the structures of substrates, the steric congestion caused by alkyl group is in favor of the C–C bond cleavage. DFT investigation further disclosed that the metathesis reaction was a kinetically favored pathway. Using only a slight excess of cheap trifluoromethylation reagent, simple operation and mild conditions make it a practical method for preparation of TFMKs on large scale, as well as a new choice of converting aryl alkyl ketones to aromatic acid esters.

Reversible photoswitched triplet-triplet annihilation upconversion (TTA UC) was demonstrated with dithienylethene (DTE) derivatives as the photochromic units, 2,6-diiodoBodipy as the triplet photosensitizer, and perylene as the triplet acceptor/emitter. The TTA UC is undisturbed by the open-form DTE but can be switched OFF upon photoirradiation of the mixture of the three components at 254 nm, i.e., by the closed-form DTE. Subsequent visible light irradiation restores the TTA UC. By studying the competitive triplet-state energy-transfer processes with nanosecond time-resolved transient difference absorption and fluorescence spectroscopy, we confirmed that the quenching of the perylene triplet excited state by closed-form DTE is dominant among the four possible quenching processes.

There are many lines of evidence indicating that mechanical stress regulates bone metabolism and promotes bone growth. BMP, Wnt, ERK1/2, and OPG/RANKL are the main molecules thought to regulate the effects of mechanical loading on bone formation. Recently, microRNAs were found to be involved in bone cell proliferation and differentiation, regulating the balance of bone formation and bone resorption. Emerging evidence indicates that microRNAs also participate in mechanical stress-mediated bone metabolism, and is associated with disuse induced osteoporosis or osteopenia. Mechanical stress is able to induce expression of microRNAs that modulate the expression of osteogenic and bone resorption factors, leading to the positive impact of mechanical stress on bone. This review discusses the emerging evidence implicating an important role for microRNAs in the mechanical stress response in bone cells, as well as the challenges of translating microRNA research into potential treatment. J. Cell. Physiol. 232: 1239-1245, 2017. © 2016 Wiley Periodicals, Inc.

An efficient method for the synthesis of (Z)-selective α-trifluoromethyl alkenyl triflates is described. As an important fluorinated building block, it is utilized successfully for the synthesis of various trifluoromethyl derivatives such as diarylethylenes, enynes, alkynes, and benzofurans.

Combined orthognathic-orthodontic treatment can be lengthy and expensive. It is therefore important to evaluate the effectiveness of proposed treatment and the likely outcomes.To determine the demographic and surgical details of patients who received orthognathic-orthodontic treatment at Christchurch Hospital, New Zealand, and to assess treatment using the Severity and Outcome Index (SOI).An observational and retrospective study was conducted of patients who received surgical orthodontic treatment between 2005 and 2012 at Christchurch Hospital. Pre- and post-treatment lateral cephalometric radiographs of 93 patients were evaluated. Seven cephalometric parameters were assessed using the Severity and Outcome Index. A severity score ranged from 0 for the most severe to 7 for the least severe, while the outcome score ranged from 0 for the worst to 7 for the best outcome.Class II patients had a severity score of 3.4 and the best outcome score of 6.2. Class III patients had a severity score of 3.3 and an outcome score of 6.1. Patients with an anterior open bite (AOB) had the worst severity score of 3.0, and the worst outcome score of 5.9. The overall treatment outcome scores for all groups were statistically significantly greater than the severity scores, which increased from 3.4 to 6.1 (p0.05).Favourable outcomes were achieved for a group of patients with a high need for treatment. Christchurch Hospital appeared to be treating cases of increased severity and gained better treatment outcomes when compared with a United Kingdom (UK) national audit.

Enolizable alkyl aryl ketones react with ester (II) to produce the 2 types of title compounds.

Summary Metastatic disease is the primary cause of death for most cancer patients. Angiogenesis is the formation of a new capillary network from pre-existing vessels and required for tumor vasculature. Heparanase, a β-endoglucuronidase, assistants tumor invasion, metastasis and angiogenesis. Chitooligosaccharides (COS) is obtained by hydrolysis of chitosan. COS has been proved to be anti-angiogenesis activity. The mechanism of COS inhibits angiogenesis is not very clear, COS is hypothesized by author to be an inhibitor of heparanase.