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Antibiotic resistance is a global public health threat, and urgent actions should be undertaken for developing alternative antimicrobial strategies and approaches. Notably, bismuth drugs exhibit potent antimicrobial effects on various pathogens and promising efficacy in tackling SARS-CoV-2 and related infections. As such, bismuth-based materials could precisely combat pathogenic bacteria and effectively treat the resultant infections and inflammatory diseases through a controlled release of Bi ions for targeted drug delivery. Currently, it is a great challenge to rapidly and massively manufacture bismuth-based particles, and yet there are no reports on effectively constructing such porous antimicrobial-loaded particles. Herein, we have developed two rapid approaches (

Characterizing soil moisture variation has critical implications for various ecosystem processes and the hydrological cycle. In this study, we identified the hot moments (times with high temporal variation rates) and hot spots (areas with high temporal variation rates) of the soil moisture variation and investigated their controlling factors on a tea garden hillslope in Taihu Lake Basin, China. Daily soil moisture data were calculated for 39 sites, and then, daily soil moisture maps were generated from March 1, 2014 to February 28, 2015. The soil moisture temporal variation rates (VR) at different locations and during different time periods were calculated based on these maps. We found that because soil water content at the subsurface was more spatially varied than that at the surface on this hillslope, spatial heterogeneity of VR was also greater at 0.3-m depth than that at 0.1-m depth. Elevation, sand content and rock fragment content were positively correlated (p

Thin film nanocomposite (TFN) membranes, which incorporate nanomaterials in a crosslinked polyamide matrix, often show enhanced separation properties thanks to the additional pores or channels offered by these materials. In this study, we deliberately created nanovoids in the dense polyamide rejection layer by acid-etching copper nanoparticles (CuNPs) contained in a TFN membrane. Systematic membrane characterization confirmed the complete removal of CuNPs using 1% HNO3, which formed nanovoids of approximately 10 nm in size. The water flux of the etched membrane TFC-Cu50X was nearly quadrupled compared to that of the CuNPs loaded membrane TFC-Cu50. This significantly improved water flux can be ascribed to the enhanced water transport through these nano-sized voids. The nanovoids-enhanced approach provides new possibilities for synthesizing high performance membranes.

Although the frequency and intensity of seasonal drought and wetness are increasing under climate change background, their effects on soil nitrate nitrogen (NO3--N) leaching have remained unclear. In this study, validated by the field data on a typical tea garden hillslope in Taihu basin, China, the Decomposition-Denitrification (DNDC) model was used to investigate these effects. The decennial drought, decennial wetness, and normal conditions of different seasons were combined to construct 31 scenarios. Results showed that seasonal drought decreased annual NO3--N leaching, with a reduction of 6.52%−18.70% (one-season drought), 18.62%−29.68% (two-season drought), 36.64%−43.99% (three-season drought) and 51.44% (all-season drought) relative to the normal scenario. Except the spring drought, drought in other seasons had legacy effects that increased NO3--N leaching in their succession seasons. The legacy effect of summer drought even continued till the summer of next year. Seasonal wetness increased annual NO3--N leaching, with an increase of 2.58%−11.39% (one-season wetness), 10.04%−22.31% (two-season wetness), 19.50%−29.39% (three-season wetness), and 29.66% (all-season wetness) relative to the normal scenario. Autumn and winter wetness decreased the NO3--N leaching in their succession seasons, while spring and summer wetness had no such effect. Soil NO3--N leaching had positive correlations with precipitation (drought scenarios: r = 0.74; wetness scenarios: r = 0.54) and soil water seepage (drought scenarios: r = 0.62; wetness scenarios: r = 0.56). Weak correlation coefficients between soil NO3--N content and NO3--N leaching were also observed especially under spring drought (r = 0.17) and summer drought (r = 0.14). However, NO3--N leaching was not limited by soil NO3--N content after the application of basal fertilizer. Fertilization plus drought or wetness increased the risk of soil NO3--N leaching. These findings will be benefit for controlling the non-point N loss of tea plantation under the background of climate change.

Whether the spatial variation and influence of rock fragment contents (RFCs) on soil hydraulic parameters (SHPs) should be jointly considered in the soil water simulation have been less investigated in previous studies. In this study, we tested whether considering these factors were necessary in the soil water simulation on a representative stony-soil hillslope located in Taihu Lake Basin, China. Five schemes of SHPs in HYDRUS-3D model were established. They were (i) MultiRFHet: spatially varied SHPs extracted from Durner’s multimodal retention function based on the observed soil water retention data; (ii) RosHom: spatially uniformed SHPs derived from ROSETTA; (iii) RosHet: spatially varied SHPs derived from ROSETTA; (iv) RosRFCHom: spatially uniformed SHPs derived from ROSETTA and adjusted by RFCs; (v) RosRFCHet: spatially varied SHPs derived from ROSETTA and adjusted by RFCs. Results indicated when the spatial variation and influence of RFCs on SHPs were both considered (MultiRFHet and RosRFCHet), acceptable accuracies (Nash-Sutcliffe efficiency or NSE ≥ 0.58 for MultiRFHet and > 0.17 for RosRFCHet) were achieved in simulating the soil water storage (SWS) variation. Since the MultiRFHet required the calibration by the observed soil water retention data, RosRFCHet was a good alternative in the simulation. On the contrary, the SHPs acquired without considering neither the RFCs nor the spatial variation yielded unacceptable simulation results (NSE general

Many approaches have been proposed to identify the representative sampling sites for estimating the spatial mean soil water contents. However, comparisons on these approaches have seldom been conducted to simultaneously predict the surface and subsurface mean soil water contents. In this study, five approaches were evaluated in identifying representative sites to estimate the surface and subsurface mean soil water contents on a typical hillslope in Taihu Lake Basin, China. They were temporal stability analysis (TSA), k-means clustering with environmental factors as inputs (EFs), combinations of TSA and EFs (EFs + TSA), k-means clustering with surface soil water contents as inputs (Theta), and combinations of TSA and Theta (Theta+TSA). The correlation coefficient (r) and root mean squared error (RMSE) between estimated and measured mean soil water contents were used to evaluate the accuracies during the calibration period (the first 25 dates) and validation period (the last 18 dates). Results showed the optimal number of representative sites on this hillslope was six. When >6 representative sites were selected, the TSA had the lowest accuracies for estimating both surface and subsurface mean soil water contents during validation period (mean RMSE ≥ 0.011 m3 m−3). The Theta and Theta + TSA had better accuracies in estimating surface mean soil water contents during both calibration and validation periods (mean RMSE

CO2 electrolysis using solid oxide electrolysis cells (SOECs) is a promising technology for sustainable conversion of CO2 to chemicals and the intermittent renewable electricity storage. However, the lack of highly active and stable cathode inhibits the development of CO2 electrolysis in SOECs for practical applications. Herein, La0.5Sr0.5Fe1-xVxO3-δ/Ce0.8Gd0.2O2-δ (LSFVx/GDC, x = 0, 0.05, 0.10, 0.15) composite with high catalytic activity and operating stability is exploited as cathode material of SOEC for CO2 electrolysis. The introduction of vanadium promotes the formation of oxygen deficiencies in LSFVx/GDC, and alters the electronic structure of Fe, thus greatly enhances the adsorption and dissociation of CO2. Compared with the LSF/GDC cathode, the LSFV0.05/GDC cathode achieves ca. 51.2% increase in current density at 1.6 V and 800 °C.

Rock fragments (RFs, mineral particles with diameter > 2 mm) can substantially influence soil carbon (C) and nitrogen (N) cycles through different physical mechanisms. These physical mechanisms include changing soil hydraulic parameters (vSH) by reducing fine earth bulk density (vSHBD) and volume (vSHVo), and affecting soil C and N stocks (vCN) by reducing fine earth bulk density (vCNBD) and volume (vCNVo), and increasing fine earth C and N concentrations (vCNCo). In this study, based on soil and climate data in a typical hilly area of China, we construct scenarios by considering these physical mechanisms to investigate the responses of key soil C and N outputs (carbon dioxide or CO2, and nitrous oxide or N2O emissions, and N leaching) to RF content (RFC) in DNDC and DayCent models. Results showed that when considering vSH and vCN, parabolic relationships were observed between these soil C and N outputs and RFC, with maximum in RFC = 0.3–0.6 g g−1. The vCN dominated the responses of soil CO2 emission to RFC, while vSH exerted comparative contributions to the responses of soil N2O emission and N leaching. When only considering vSH, opposite contributions of vSHBD and vSHVo were observed in DNDC model, and contributions of vSHBD overwhelmed those of vSHVo. However, vSHVo dominated these responses in DayCent model. When only considering vCN, the vCNCo dominated these responses, though considerable superimposed influences of vCNBD and vCNVo appeared under high RFC. The discrepancies between these responses to RFC in DNDC and DayCent models might be due to the different model complexities in simulating soil hydrology, biogeochemistry, and the role of bulk density in these models. Relatively, more distinct responses were achieved in DNDC model. These findings can extend our understandings of RFs and soil C and N cycles.

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

Soil moisture variations in space and time are critical in ecological, hydrological, pedological and environmental studies. This study used fractal analysis to detect the spatio-temporal variability of soil moisture on two contrasting land use hillslopes in the hilly area of Taihu Lake Basin of China. Surface (0–20 cm) soil moisture data from January 2013 to September 2015 (a total of 37 sampling days) were analyzed at 39 and 38 sites on the tea garden and forest hillslopes, respectively, with a spatial resolution of about 8 m. Results showed that the forest hillslope was significantly ( P 2 = 0.753 for tea garden ( P 2 = 0.459 for forest ( P

The ROSETTA model has routinely been applied to predict the soil hydraulic properties for simulating the water flow at the hillslope scale. However, the uncertainties in water flow simulations are substantial due to the soil heterogeneity and ROSETTA model structure. In order to reduce these uncertainties, this study used the HYDRUS-2D and ensemble mean to simulate soil moisture based on the outputs of all candidate models. In addition, the bias correction techniques (including linear bias correction (LBC) and cumulative distribution function (CDF) matching) were also applied to improve the prediction of soil moisture. A total of 320 days of observed soil moisture data at two depths (10 and 30 cm) in the upper and lower slope positions were adopted to evaluate the performances of different bias correction methods results showed that the uncertainty in hillslope-scale soil moisture simulation due to the ROSETTA model structure was more important than that due to the soil heterogeneity. The CDF matching-based nonlinear bias correction approach was generally better than the LBC in reducing the uncertainty in soil moisture simulation. Combining the ensemble mean and CDF matching was a viable approach to improve the accuracy of the numerical model for simulating the hillslope-scale soil moisture variations.

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0–20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m−3) than that based on the smallest SDRD (RMSE = 0.034 m3 m−3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE

The electromagnetic induction (EMI) technique has been widely used to survey soil properties at intermediate spatial scales. However, EMI data interpretation remains a challenge for more accurate and robust mapping. Residual analysis is an alternative approach that can be used to improve the EMI data mining. On a tea garden (TG) hillslope and a bamboo forest (BF) hillslope, terrain indices were used to regress the apparent electrical conductivity (ECa) in ten repeated EMI surveys using stepwise multiple linear regressions (SMLR). Residuals of ECa in these regressions, which had terrain influence removed, were then calculated. The classification and regression tree (CART) model was adopted to quantify the relative contributions of terrain indices (elevation, slope, plane curvature–PLC, profile curvature–PRC, and topographic wetness index–TWI), static soil properties (rock fragment content–RFC, depth to bedrock–DB, contents of clay, silt and sand), and dynamic soil property (volumetric soil moisture–θ) to ECa and their residuals. Results show that contributions of terrain indices to ECa are around 50%. However, contributions of terrain indices to ECa residuals are

Spatio-temporal variability of soil moisture (θ) is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time θ monitoring methods. This restricted the comprehensive and intensive examination of θ dynamics. In this study, we integrated the manual and real-time monitored data to depict the hillslope θ dynamics with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear (support vector machines-SVM) models were used to predict θ at 39 manual sites (collected 1–2 times per month) with θ collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each depth and manual site, an optimal prediction model was then determined at this depth of this site. Results showed that θ at the 39 manual sites can be reliably predicted (root mean square errors 3 m −3 ) using both SMLR and SVM. The linear or non-linear relationship between θ at each manual site and at the three real-time monitoring sites was the main reason for choosing SMLR or SVM as the optimal prediction model. The subsurface flow dynamics was an important factor that determined whether the relationship was linear or non-linear. Depth to bedrock, elevation, topographic wetness index, profile curvature, and θ temporal stability influenced the selection of prediction model since they were related to the subsurface soil water distribution and movement. Using this approach, hillslope θ spatial distributions at un-sampled times and dates can be predicted. Missing information of hillslope θ dynamics can be acquired successfully.

Pedotransfer functions were often applied to predict the soil water contents at field capacity (FC) and permanent wilting point (PWP), which are the key parameters used in the soil nitrogen (N) biogeochemical models for simulating the nitrate ( N O 3 - - N ) leaching. However, the PTF prediction uncertainty was often ignored. In addition, the uncertainty of the N model structure (soil N cycling is described with a set of equations) can also be substantial. Based on the 12 classic pedotransfer functions (PTFs) (namely Baumer, Brakensiek/Rawls, British Soil Survey Topsoil, British Soil Survey Subsoil, EPIC, Hutson, Manrique, Rawls, Campbell, Mayr/Jarvis, Rawls/Brakensiek, and Vereecken) and 2 biogeochemical models (DayCent and DeNitrification-DeComposition (DNDC)), this study evaluated the PTF prediction and model structural uncertainty in soil NO3−-N leaching modelling on a tea garden hillslope in Taihu Lake Basin, China. The ensemble mean was then applied to combine the 12 outputs of each model and the 24 outputs of both models. Finally, the linear bias-correction combined with the ensemble mean, i.e., the ensemble bias-correction (EBC), was also applied for the prediction of the leachate NO3−-N concentrations. Data on basic soil properties were used to derive the FC and PWP by using the 12 PTFs. Results showed that both the PTF prediction and model structural uncertainty were equally important in soil N O 3 - - N leaching modelling at four slope positions. The coefficients of variation of the N O 3 - - N concentration forecasts obtained by different PTFs, representing the PTF prediction uncertainty, were positively related to the climate factors, especially when PTFs were used in DayCent. Ensemble mean was found to produce a very large bias in the prediction of the leachate N O 3 - - N concentrations, which is due to the prediction bias of PTFs. The EBC can substantially improve the prediction of the soil N O 3 - - N leaching, especially when the 24 outputs of both models were combined.

Pd single site-anchored La0.5Sr0.5FeO3-δ-Ce0.8Sm0.2O2-x (Pd-LSF(SDC)) cathode is constructed for CO2 electrolysis in solid oxide electrolysis cells. The decoration of Pd species on LSF greatly improves CO2 electrolysis performance with 65.7% enhancement in current density at 1.6 V compared with the LSF counterpart. Electrochemical and density functional theory calculation results suggest that the Pd species are atomically anchored on the LSF phase. The coordinatively unsaturated Pd with oxygen vacancies facilitates the CO2 dissociative adsorption, electron transfer and mass transport, thus greatly decreases the polarization resistance of the cathode and promotes the CO2 electrolysis performance. This work provides an effective strategy to design the supported single site catalyst for high-temperature CO2 electrolysis.

Due to the economic benefits, land use change (e.g. deforest to tea or fruit plantation) has been widely occurred in the south-eastern hilly area of China. This may stimulate serious soil nitrogen (N) losses due to large fertilizer inputs (about 1–2 times of that in regular rice-wheat rotation). Therefore, we investigated the soil N2O fluxes and leachate NO3–-N concentrations and their responses to multiple factors on a tea garden (TG) hillslope and an adjacent bamboo forest (BF) hillslope. Soil N2O fluxes and leachate NO3–-N concentrations on the TG hillslope were 3.28 and 4.24 times of those on the BF hillslope, respectively. Soil N2O fluxes measured in spring were the greatest while those measured in winter were the lowest. However, the measured leachate NO3–-N concentrations were the greatest in winter but the lowest in summer. On both hillslopes, soil temperature (ST) and precipitation during the previous seven days (API7) were positively related to soil N2O fluxes but negatively related to leachate NO3–-N concentrations, while the ground water table depth was opposite. Soil water content (SWC) and the ratio of SWC/field capacity (SWC/FC) negatively influenced leachate NO3–-N concentrations on both hillslopes. Positive influences of SWC and SWC/FC on soil N2O fluxes were observed on the TG hillslope, while quadratic relationships were observed on the BF hillslope. Thresholds of ST and API7 were existed in the controlling the spatial variations of soil N2O fluxes and leachate NO3–-N concentrations on both hillslopes. When ST was > 9.5 °C, spatial variations in soil N2O fluxes were controlled by topography, soil properties and soil hydrological parameters on both hillslopes. Similarly, when API7 were

Spatial patterns of land use types (mixed forest: MF, tea garden: TG, bamboo forest: BF) in a mountainous area with rapid agricultural land development were optimized to reduce NO3−-N leaching and N2O emission in this study. Firstly, a process-oriented biogeochemical model (Denitrification Decomposition, DNDC) was calibrated and validated on representative MF, TG and BF hillslopes. To upscale the simulations, hydropedological function (HPF) units were generated by overlapping maps of land use, soil organic carbon, rock fragment content and slope, which were recognized as critical factors affecting soil N cycle. The calibrated DNDC models were then adopted to simulate the soil N cycles in different HPF units and assess temporal and spatial variations of NO3−-N leaching and N2O emission risks. Lastly, spatial allocations of TG were determined respectively for minimizing NO3−-N leaching (MLN_LU) and N2O emission (MEN_LU), and balancing the reductions of both (BRN_LU). Results showed that the DNDC model had acceptable accuracies on these representative hillslopes (R2 > 0.50, NSE > 0.30). Land use of TG had the greatest N loss risks, the mean annual NO3−-N leaching and N2O flux in TG HPF units (72.11- and 3.63- kg N ha−1, respectively) were respectively 2.61 and 2.50 times of those of the entire study area. Temporal variations of NO3−-N leaching and N2O flux were both controlled by the timing of precipitation, and their spatial patterns were both primarily controlled by land use and then respectively by soil hydraulic properties (NO3−-N leaching) and soil carbon and N concentrations (N2O flux). Due to the relatively small spatial variations of soil and terrain properties and rational land use spatial patterns in this study area, the MLN_LU only reduced 7.6% of NO3−-N leaching, the MEN_LU only reduced 6.0% of N2O flux, and the BRN_LU reduced both by 3.3% and 4.1%, respectively. This study emphasized the role of land use pattern optimization in reducing the non-point N losses in mountainous area, and could provide scientific guidelines for future agricultural land developments.

Potentilla discolor is used as an ethnomedicine in treatments of diabetes mellitus in China for years. In the present study, the anti-hyperglycemic effects of a clinical active extract (decoction) from P. discolor were investigated in Ob-db mice. Four week's treatment of P. discolor decoction ameliorated the development of hyperlipidemia, lipid peroxidation and hyperglycemia associated with hyperphagia and polydypsia in Ob-db mice. P. discolor significantly attenuated the increase of blood glucose and cholesterol levels in Ob-db mice. These findings clearly provided evidences regarding the anti-hyperglycemic potentials of P. discolor decoction. High-resolution liquid chromatography-mass spectrometry/mass spectrometry (HR-LC-MS/MS) was used to analyze the phytochemicals in P. discolor decoction. In an comprehensive analysis of phytochemicals in P. discolor, thirty-five components were identified or characterized in P. discolor decoction and only sixteen of them have been reported in P. discolor previously. There are five major components identified in P. discolor decoction. One of the major components is a flavonoid sulfate, and this is the first evidence for the presences of sulfated flavonoid in P. discolor. Sulfated flavonoids have been reported to improve the complications of diabetes mellitus by inhibition of the aldose reductase in both experimental animals and clinical trials. Therefore, the sulfated flavonoid in P. discolor decoction may in part contribute to the anti-hyperglycemic effect of P. discolor.

The aim of this study was to compare two-dimensional (2D) and three-dimensional (3D) methods for computing left ventricular (LV) rotation.A two-axis linear/rotary system was designed using rotary motors controlled through a digital interface, and 10 freshly harvested pig hearts were studied. Each heart was mounted on the rotary actuator with the base being rotated at different known degrees of rotation (10°, 15°, 20°, and 25°) and was passively driven by a pump with calibrated stoke volume (50 mL) at a constant rate (60 beats/min) simultaneously. Cardiac motion was scanned to acquire 2D short-axis views using a GE Vivid 7 system for assessing rotation, and 3D apical full-volume loops were acquired using a Toshiba Applio Artida ultrasound system. Full-volume 3D image loops were analyzed online with Toshiba Wall Motion Tracking software, and short-axis 2D images were analyzed offline for LV rotation in GE EchoPAC PC at corresponding LV levels.At each state, both 2D and 3D echocardiography detected the changes in LV rotation but overestimated the rotation degrees. The biases for overestimation from 3D imaging were smaller compared with 2D imaging at each LV level. Both methods, when compared with each other, showed a linear correlation (r = 0.84, P.0001). Bland-Altman comparison showed 99% of data points within range, with a constant bias between both methods (adjusted values of 3D = 1.892 + 0.964 × 3D).Although 3D echocardiography showed smaller bias, the results between 2D and 3D echocardiography were comparable.

Fasudil hydrochloride (FH), a Rho kinase inhibitor, is used to treat neurological diseases. This study aims to elucidate the anti-dementia role of FH in Alzheimer's disease. Twenty-four Sprague-Dawley rats were randomly divided into four groups: (1) sham-operated group (control), (2) sham-operated followed by FH administration group (sham+FH), (3) streptozotocin (STZ)-treated group (STZ), and (4) STZ treatment followed by FH administration group (STZ+FH). Rats in the STZ and STZ+FH groups received two divided doses of STZ (1.5 mg/kg) intracerebroventricularly on days 1 and 3, whereas control and sham+FH group rats were given citric acid/sodium citrate buffer. Rats in the sham+FH and STZ+FH groups were then treated intraperitoneally with FH (10 mg/kg) for 4 weeks, and rats in the STZ and control groups were treated with saline. Learning and memory were measured using the Morris water maze test. The synaptic ultrastructure in the CA1 region of the hippocampus was observed using electronic microscopy. The expression of synaptophysin (SYP) was measured using real-time polymerase chain reaction and western blot analyses; the expression of p-LIMK2 and p-cofilin were also detected using western blot analysis. The results indicate that STZ induced deficit in learning/memory, decrease in SYP expression, degeneration in synaptic structures, and increase in the expressions of p-LIMK2 and p-cofilin. These changes were reversed by the administration of FH, suggesting that FH has anti-dementia properties that protect synaptic structure and function. FH induced dephosphorylation (inactivation) of LIMK2 and subsequent dephosphorylation (activation) of cofilin, which may be responsible for the amelioration of neuronal synaptic structure and function.

National Basic Research Program of China [2012CB933503]; National Natural Science Foundation of China [61036003, 61176092, 60837001]; Fundamental Research Funds for the Central Universities [2010121056]; State Key Laboratory of Functional Materials for Informatics

We report on normal incidence p-i-n heterojunction photodiodes operating in the near-infrared region and realized in pure germanium on planar silicon substrate. The diodes were fabricated by ultrahigh vacuum chemical vapor deposition at 600 degrees C without thermal annealing and allowing the integration with standard silicon processes. Due to the 0.14% residual tensile strain generated by the thermal expansion mismatch between Ge and Si, an efficiency enhancement of nearly 3-fold at 1.55 mu m and the absorption edge shifting to longer wavelength of about 40 nm are achieved in the epitaxial Ge films. The diode with a responsivity of 0.23 A/W at 1.55 mu m wavelength and a bulk dark current density of 10 mA/cm(2) is demonstrated. These diodes with high performances and full compatibility with the CMOS processes enable monolithically integrating microphotonics and microelectronics on the same chip.

The thermal stability of SiGe films on an ultra thin Ge buffer layer on Si fabricated at low temperature has been studied. The microstructure and morphology of the samples were investigated by high-resolution X-ray diffraction, Raman spectra and atomic force microscopy, and using a diluted Secco etchant to reveal dislocation content. After thermal annealing processing, it is observed that undulated surface, threading dislocations (TDs) and stacking faults (SFs) appeared at the strained SiGe layer, which developed from the propagation of a misfit dislocation (MD) during thermal annealing, and no SFs but only TDs formed in strain-relaxed sample. And it is found that the SiGe films on the Ge layer grown at 300 °C has crosshatch-free surface and is more stable than others, with a root mean square surface roughness of less than 2 nm and the threading dislocation densities as low as ∼105 cm−2. The results show that the thermal stability of the SiGe films is associated with the Ge buffer layer, the relaxation extent and morphology of the SiGe layer.

National Natural Science Foundation of China [60676027, 50672079]; Key Projects of Fujian Science and Technology [2006H0036]; National Basic Research Program of China (973 Program) [2007CB613404]; New Century Excellent Talents in University

High-quality Ge epilayer on Si(1 0 0) substrate with an inserted low-temperature Ge seed layer and a thin Si0.77Ge0.23 layer was grown by ultrahigh vacuum chemical vapor deposition. The epitaxial Ge layer with surface root-mean-square roughness of 0.7 nm and threading dislocation density of 5 x 10(5) cm(-2) was obtained. The influence of low temperature Ge seed layer on the quality of Ge epilayer was investigated. We demonstrated that the relatively higher temperature (350 degrees C) for the growth of Ge seed layer significantly improved the crystal quality and the Hall hole mobility of the Ge epilayer. (C) 2008 Elsevier B.V. All rights reserved.