Electrochemical energy storage technology is of critical importance for portable electronics, transportation and large‐scale energy storage systems. There is a growing demand for energy storage ...devices with high energy and high power densities, long‐term stability, safety and low cost. To achieve these requirements, novel design structures and high performance electrode materials are needed. Porous 1D nanomaterials which combine the advantages of 1D nanoarchitectures and porous structures have had a significant impact in the field of electrochemical energy storage. This review presents an overview of porous 1D nanostructure research, from the synthesis by bottom‐up and top‐down approaches with rational and controllable structures, to several important electrochemical energy storage applications including lithium‐ion batteries, sodium‐ion batteries, lithium‐sulfur batteries, lithium‐oxygen batteries and supercapacitors. Highlights of porous 1D nanostructures are described throughout the review and directions for future research in the field are discussed at the end.
Porous 1D nanomaterials utilize the advantages of both 1D nanoarchitecture and porous morphology to further enhance the performance of materials for energy‐storage applications. The current status of porous 1D nanostructures, from methodologies for rational and controllable synthesis, to their successful application in lithium‐ion batteries, sodium‐ion batteries, lithium–sulfur batteries, lithium–oxygen batteries and supercapacitors is presented.
Summary
Guidelines for doctors managing osteoporosis in the Asia-Pacific region vary widely. We compared 18 guidelines for similarities and differences in five key areas. We then used a structured ...consensus process to develop clinical standards of care for the diagnosis and management of osteoporosis and for improving the quality of care.
Purpose
Minimum clinical standards for assessment and management of osteoporosis are needed in the Asia-Pacific (AP) region to inform clinical practice guidelines (CPGs) and to improve osteoporosis care. We present the framework of these clinical standards and describe its development.
Methods
We conducted a structured comparative analysis of existing CPGs in the AP region using a “5IQ” model (identification, investigation, information, intervention, integration, and quality). One-hundred data elements were extracted from each guideline. We then employed a four-round Delphi consensus process to structure the framework, identify key components of guidance, and develop clinical care standards.
Results
Eighteen guidelines were included. The 5IQ analysis demonstrated marked heterogeneity, notably in guidance on risk factors, the use of biochemical markers, self-care information for patients, indications for osteoporosis treatment, use of fracture risk assessment tools, and protocols for monitoring treatment. There was minimal guidance on long-term management plans or on strategies and systems for clinical quality improvement. Twenty-nine APCO members participated in the Delphi process, resulting in consensus on 16 clinical standards, with levels of attainment defined for those on identification and investigation of fragility fractures, vertebral fracture assessment, and inclusion of quality metrics in guidelines.
Conclusion
The 5IQ analysis confirmed previous anecdotal observations of marked heterogeneity of osteoporosis clinical guidelines in the AP region. The Framework provides practical, clear, and feasible recommendations for osteoporosis care and can be adapted for use in other such vastly diverse regions. Implementation of the standards is expected to significantly lessen the global burden of osteoporosis.
Aims/hypothesis
As microRNA-21 (miR-21) plays a pathological role in fibrosis, we hypothesised that it may be a therapeutic target for diabetic nephropathy.
Methods
Abundance of miR-21 was examined ...in diabetic kidneys from
db/db
mice. The therapeutic potential of miR-21 in diabetic kidney injury was examined in
db/db
mice by an ultrasound-microbubble-mediated miR-21 small hairpin RNA transfer. In addition, the role and mechanisms of miR-21 in diabetic renal injury were examined in vitro under diabetic conditions in rat mesangial and tubular epithelial cell lines by overexpressing or downregulating miR-21.
Results
In
db/db
mice, a mouse model of type 2 diabetes, renal miR-21 at age 20 weeks was increased twofold compared with
db/m
+
mice at the same age, and this increase was associated with the development of microalbuminuria and renal fibrosis and inflammation. More importantly, gene transfer of miR-21 knockdown plasmids into the diabetic kidneys of
db/db
mice at age 10 weeks significantly ameliorated microalbuminuria and renal fibrosis and inflammation at age 20 weeks, revealing a therapeutic potential for diabetic nephropathy by targeting miR-21. Overexpression of miR-21 in kidney cells enhanced, but knockdown of miR-21 suppressed, high-glucose-induced production of fibrotic and inflammatory markers. Targeting
Smad7
may be a mechanism by which miR-21 regulates renal injury because knockdown of renal miR-21 restored Smad7 levels and suppressed activation of the TGF-β and NF-κB signalling pathways.
Conclusions/interpretation
Inhibition of miR-21 might be an effective therapy for diabetic nephropathy.
Background and Objective: Short‐chain fatty acids, such as butyric acid and propionic acid, are metabolic by‐products generated by periodontal microflora such as Porphyromonas gingivalis, and ...contribute to the pathogenesis of periodontitis. However, the effects of butyrate on the biological activities of gingival fibroblasts (GFs) are not well elucidated.
Material and Methods: Human GFs were exposed to various concentrations of butyrate (0.5–16 mm) for 24 h. Viable cells that excluded trypan blue were counted. Cell cycle distribution of GFs was analyzed by propidium iodide‐staining flow cytometry. Cellular reactive oxygen species (ROS) production was measured by flow cytometry using 2’,7’‐dichlorofluorescein (DCF). Total RNA and protein lysates were isolated and subjected to RT‐PCR using specific primers or to western blotting using specific antibodies, respectively.
Results: Butyrate inhibited the growth of GFs, as indicated by a decrease in the number of viable cells. This event was associated with an induction of G0/G1 and G2/M cell cycle arrest by butyrate (4–16 mm) in GFs. However, no marked apoptosis of GFs was noted in this experimental condition. Butyrate (> 2 mm) inhibited the expression of cdc2, cdc25C and cyclinB1 mRNAs and reduced the levels of Cdc2, Cdc25C and cyclinB1 proteins in GFs, as determined using RT‐PCR and western blotting, respectively. This toxic effect of butyrate was associated with the production of ROS.
Conclusion: These results suggest that butyrate generated by periodontal pathogens may be involved in the pathogenesis of periodontal diseases via the induction of ROS production and the impairment of cell growth, cell cycle progression and expression of cell cycle‐related genes in GFs. These events are important in the initiation and prolongation of inflammatory processes in periodontal diseases.
Lipopolysaccharide (LPS) of Gram-negative bacteria can elicit a strong immune response. Although extracellular LPS is sensed by TLR4 at the cell surface and triggers a transcriptional response, ...cytosolic LPS binds and activates non-canonical inflammasome caspases, resulting in pyroptotic cell death, as well as canonical NLRP3 inflammasome-dependent cytokine release. Contrary to the highly regulated multiprotein platform required for caspase-1 activation in the canonical inflammasomes, the non-canonical mouse caspase-11 and the orthologous human caspase-4 function simultaneously as innate sensors and effectors, and their regulation is unclear. Here we show that the oxidized phospholipid 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphorylcholine (oxPAPC) inhibits the non-canonical inflammasome in macrophages, but not in dendritic cells. Aside from a TLR4 antagonistic role, oxPAPC binds directly to caspase-4 and caspase-11, competes with LPS binding, and consequently inhibits LPS-induced pyroptosis, IL-1β release and septic shock. Therefore, oxPAPC and its derivatives might provide a basis for therapies that target non-canonical inflammasomes during Gram-negative bacterial sepsis.
Over the last 20 years, substantial amounts of grassland have been converted to other land uses in the Northern Great Plains. Most of land cover/land use (LCLU) assessments in this region have been ...based on the U.S. Department of Agriculture - Cropland Data Layer (USDA - CDL), which may be inconsistent. Here, we demonstrate an approach to map land cover utilizing multi-temporal Earth Observation data from Landsat and MODIS. We first built an annual time series of accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperatures. Using the Enhanced Vegetation Index (EVI) derived from Landsat Collection 1's surface reflectance, we then fit at each pixel a downward convex quadratic model to each year's progression of AGDD (i.e., EVI = α + β × AGDD − γ × AGDD2). Phenological metrics derived from fitted model and the goodness of fit then are submitted to a random forest classifier (RFC) to characterize LCLU for four sample counties in South Dakota in three years (2006, 2012, 2014) when reference point datasets are available for training and validation. To examine the sensitivity of the RFC to sample size and design, we performed classifications under different sample selection scenarios. The results indicate that our proposed method accurately mapped major crops in the study area but showed limited accuracy for non-vegetated land covers. Although all RFC models exhibit high accuracy, estimated land cover areas from alternative models could vary widely, suggesting the need for a careful examination of model stability in any future land cover supervised classification study. Among all sampling designs, the “same distribution” models (proportional distribution of the sample is like proportional distribution of the population) tend to yield best land cover prediction. RFC used only the most eight important variables (e.g., three fitted parameter coefficients α, β, and γ; maximum modeled EVI; AGDD at maximum modeled EVI; the number of observations used to fit CxQ model; and the number of valid observations) have slightly higher accuracy compared to those using all variables. By summarizing annual image time series through land surface phenology modeling, LCLU classification can embrace both seasonality and interannual variability, thereby increasing the accuracy of LCLU change detection.
•Land surface phenology (LSP) modeled using Landsat EVI and MODIS LST•Land cover from random forest classification (RFC) using only phenometrics as input•Combinations of reference data augmented by CDL used for training/validation•LSP-RFC accurately identified major crops compared to the Cropland Data Layer (CDL).•Caveat: alternative RFC training designs yielded widely varying area estimates.
Many studies have shown that high elevation environments are among very sensitive to climatic changes and where impacts are exacerbated. Across Central Asia, which is especially vulnerable to climate ...change due to aridity, the ability of global climate projections to capture the complex dynamics of mountainous environments is particularly limited. Over montane Central Asia, agropastoralism constitutes a major portion of the rural economy. Extensive herbaceous vegetation forms the basis of rural economies in Kyrgyzstan. Here we focus on snow cover seasonality and the effects of terrain on phenology in highland pastures using remote sensing data for 2001–2017. First, we describe the thermal regime of growing season using MODerate Resolution Imaging Spectrometer (MODIS) land surface temperature (LST) data, analyzing the modulation by elevation, slope, and aspect. We then characterized the phenology in highland pastures with metrics derived from modeling the land surface phenology using Landsat normalized difference vegetation index (NDVI) time series together with MODIS LST data. Using rank correlations, we then analyzed the influence of four metrics of snow cover seasonality calculated from MODIS snow cover composites—first date of snow, late date of snow, duration of snow season, and the number of snow-covered dates (SCD)—on two key metrics of land surface phenology in the subsequent growing season, specifically, peak height (PH; the maximum modeled NDVI) and thermal time to peak (TTP; the amount of growing degree-days accumulated during modeled green-up phase). We evaluated the role of terrain features in shaping the relationships between snow cover metrics and land surface phenology metrics using exact multinomial tests of equivalence. Key findings include (1) a positive relationship between SCD and PH occurred in over 1664 km2 at p < 0.01 and 5793 km2 at p < 0.05, which account for >8% of 68,881 km2 of the pasturelands analyzed in Kyrgyzstan; (2) more negative than positive correlations were found between snow cover onset and PH, and more positive correlations were observed between snowmelt timing and PH, indicating that a longer snow season can positively influence PH; (3) significant negative correlations between TTP and SCD appeared in 1840 km2 at p < 0.01 and 6208 km2 at p < 0.05, and a comparable but smaller area showed negative correlations between TTP and last date of snow (1538 km2 at p < 0.01 and 5188 km2 at p < 0.05), indicating that under changing climatic conditions toward earlier spring warming, decreased duration of snow cover may lead to lower pasture productivity, thereby threatening the sustainability of montane agropastoralism; and (4) terrain had a stronger influence on the timing of last date of snow cover than on the number of snow-covered dates, with slope being more important than aspect, and the strongest effect appearing from the interaction of aspect and steeper slopes. In this study, we characterized the snow-phenology interactions in highland pastures and revealed strong dependencies of pasture phenology on timing of snowmelt and the number of snow-covered dates.
•Modeled LSP in pastures at 30 m using 17 years of Landsat and MODIS data•Prevalent trend of increasing peak NDVI in highland pastures 2001–2017•Later snowmelt date and more snow covered dates increased peak NDVI•Slope was more important than aspect on linkages between snow cover & LSP.
To explore the characteristics of Helicobacter pylori resistance in China and the association between antibiotic resistance and several clinical factors.
H. pylori strains were collected from ...patients in 13 provinces or cities in China between 2010 and 2016. Demographic data including type of disease, geographic area, age, gender and isolation year were collected to analyse their association with antibiotic resistance. Antibiotic resistance was detected using the Etest test and the Kirby-Bauer disc diffusion method.
H. pylori were successfully cultured from 1117 patients. The prevalence of metronidazole, clarithromycin (CLA), azithromycin, levofloxacin (LEV), moxifloxacin, amoxicillin (AMO), tetracycline and rifampicin resistance was 78.2, 22.1, 23.3, 19.2, 17.2, 3.4, 1.9 and 1.5%, respectively. No resistance to furazolidone was observed. The resistance rates to LEV and moxifloxacin were higher in strains isolated from patients with gastritis compared to those with duodenal ulcer and among women. Compared to patients ≥40 years old, younger patients exhibited lower resistance rates to CLA, azithromycin, LEV and moxifloxacin. The resistance rates to CLA and AMO were higher in strains isolated more recently, and we also found that the prevalence of resistance to metronidazole, CLA, azithromycin and AMO were significantly different among different regions of China.
The resistance rates to metronidazole, CLA and LEV were high in China. Patient age, gender, disease and location were associated with the resistance of H. pylori to some antibiotics. Furazolidone, AMO and tetracycline are better choices for H. pylori treatment in China.
Remote sensing imagery has been a key data source for precision agriculture. However, high-resolution and/or hyperspectral imagery have typically been favored for their greater information content. ...This study aims to demonstrate the capability of medium-resolution imagery in precision agriculture by developing an example of canola yield mapping using Sentinel-2 data in central Alberta. Two simple empirical models for mapping precision canola yield are tested: one using random forest regression and a second using functional linear regression. Both take as input freely-available Sentinel-2 time series images and use these to predict precision yield gathered by a yield monitor. The models were able to predict crop yield to within 12–16% accuracy of the reference yield. These results also demonstrate that a time series of medium-resolution multispectral imagery can capture small-scale variation in crop yields. The proposed methods can be applied to other areas or cropping systems to improve understanding of crop growth at both the field-level and regional-level.
PDF
