Relationships between Landscape Patterns and Hydrological Processes in the Subtropical Monsoon Climate Zone of Southeastern China

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p &lt; 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon’s diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts.</p

Analysis of Vegetation Vulnerability Dynamics and Driving Forces to Multiple Drought Stresses in a Changing Environment

Quantifying changes in the vulnerability of vegetation to various drought stresses in different seasons is important for rational and effective ecological conservation and restoration. However, the vulnerability of vegetation and its dynamics in a changing environment are still unknown, and quantitative attribution analysis of vulnerability changes has been rarely studied. To this end, this study explored the changes of vegetation vulnerability characteristics under various drought stresses in Xinjiang and conducted quantitative attribution analysis using the random forest method. In addition, the effects of ecological water transport and increased irrigation areas on vegetation vulnerability dynamics were examined. The standardized precipitation index (SPI), standardized precipitation-evapotranspiration index (SPEI), and standardized soil moisture index (SSMI) represent atmospheric water supply stress, water and heat supply stress, and soil water supply stress, respectively. The results showed that: (1) different vegetation types responded differently to water stress, with grasslands being more sensitive than forests and croplands in summer; (2) increased vegetation vulnerability under drought stresses dominated in Xinjiang after 2003, with vegetation growth and near-surface temperature being the main drivers, while increased soil moisture in the root zone was the main driver of decreased vegetation vulnerability; (3) vulnerability of cropland to SPI/SPEI/SSMI-related water stress increased due to the rapid expansion of irrigation areas, which led to increasing water demand in autumn that was difficult to meet; and (4) after ecological water transport of the Tarim River Basin, the vulnerability of its downstream vegetation to drought was reduced

Structural water as an essential comonomer in supramolecular polymerization

Water is an essential comonomer in a supramolecular polymer that is used as a recyclable, water-activated glue.</jats:p

A solution-processable and ultra-permeable conjugated microporous thermoset for selective hydrogen separation.

The synthesis of a polymer that combines the processability of plastics with the extreme rigidity of cross-linked organic networks is highly attractive for molecular sieving applications. However, cross-linked networks are typically insoluble or infusible, preventing them from being processed as plastics. Here, we report a solution-processable conjugated microporous thermoset with permanent pores of ~0.4 nm, prepared by a simple heating process. When employed as a two-dimensional molecular sieving membrane for hydrogen separation, the membrane exhibits ultrahigh permeability with good selectivity for H2 over CO2, O2, N2, CH4, C3H6 and C3H8. The combined processability, structural rigidity and easy feasibility make this polymeric membrane promising for large-scale hydrogen separations of commercial and environmental relevance

Enhanced sensitivity of neutralizing antibody detection for different AAV serotypes using HeLa cells with overexpressed AAVR

A cell-based transduction inhibition assay (TI) is widely used in clinical trials to detect neutralizing antibody (NAb) titers against recombinant adeno-associated virus (rAAV), one of the most important criteria to exclude patients in gene therapy. Different cell lines are used in cell-based TI because the rAAV transduction efficiencies vary largely among serotypes. A cell line suitable for TI for most serotypes is highly desirable, especially for those with very low transduction efficiencies in vitro such as rAAV8 and rAAV9. Herein, we report an AAVR-HeLa, a stable cell line with overexpressed AAVR, a newly identified receptor for rAAVs, was established for cell-based TIs. The AAVR expression level in AAVR-HeLa cells was approximately 10-fold higher than in HeLa cells, and was stably transfected after twenty three passages. For all AAV serotypes (AAV1-10), except for AAV4, the transduction efficiencies increased significantly in AAVR-HeLa cells. It was demonstrated that the AAVR enhancement of transduction efficiency was only for rAAV and not for lentiviral and adenoviral vectors. According to the minimal multiplicity of infection (MOIs) for the assay, the NAb detection sensitivity increased at least 10 and 20 fold for AAV8 and AAV9, respectively. The seroprevalence of NAbs were investigated at the 1:30 level as a cutoff value using AAVR-HeLa cells. It was shown that the seropositive rate for AAV2 was 87% in serum samples from 99 adults, followed by lower seropositive rates for AAV5 (7%), AAV8 (7%) and AAV9 (1%). Venn diagram analysis showed the presence of cross-reactivity of NAbs to two or three serotypes in 13 samples (13.1%). However, no patient was found to possess NAbs for all the four serotypes. These results demonstrated that the AAVR-HeLa cell line may be utilized to detect the NAbs through cell-based TI assays for most of AAV serotypes

Inactivating hepatic follistatin alleviates hyperglycemia

Unsuppressed hepatic glucose production (HGP) contributes substantially to glucose intolerance and diabetes, which can be modeled by the genetic inactivation of hepatic insulin receptor substrate 1 (Irs1) and Irs2 (LDKO mice). We previously showed that glucose intolerance in LDKO mice is resolved by hepatic inactivation of the transcription factor FoxO1 (that is, LTKO mice)-even though the liver remains insensitive to insulin. Here, we report that insulin sensitivity in the white adipose tissue of LDKO mice is also impaired but is restored in LTKO mice in conjunction with normal suppression of HGP by insulin. To establish the mechanism by which white adipose tissue insulin signaling and HGP was regulated by hepatic FoxO1, we identified putative hepatokines-including excess follistatin (Fst)-that were dysregulated in LDKO mice but normalized in LTKO mice. Knockdown of hepatic Fst in the LDKO mouse liver restored glucose tolerance, white adipose tissue insulin signaling and the suppression of HGP by insulin; however, the expression of Fst in the liver of healthy LTKO mice had the opposite effect. Of potential clinical significance, knockdown of Fst also improved glucose tolerance in high-fat-fed obese mice, and the level of serum Fst was reduced in parallel with glycated hemoglobin in obese individuals with diabetes who underwent therapeutic gastric bypass surgery. We conclude that Fst is a pathological hepatokine that might be targeted for diabetes therapy during hepatic insulin resistance

Early Identification of High-Risk TIA or Minor Stroke Using Artificial Neural Network

Background and Purpose: The risk of recurrent stroke following a transient ischemic attack (TIA) or minor stroke is high, despite of a significant reduction in the past decade. In this study, we investigated the feasibility of using artificial neural network (ANN) for risk stratification of TIA or minor stroke patients.Methods: Consecutive patients with acute TIA or minor ischemic stroke presenting at a tertiary hospital during a 2-year period were recruited. We collected demographics, clinical and imaging data at baseline. The primary outcome was recurrent ischemic stroke within 1 year. We developed ANN models to predict the primary outcome. We randomly down-sampled patients without a primary outcome to 1:1 match with those with a primary outcome to mitigate data imbalance. We used a 5-fold cross-validation approach to train and test the ANN models to avoid overfitting. We employed 19 independent variables at baseline as the input neurons in the ANN models, using a learning algorithm based on backpropagation to minimize the loss function. We obtained the sensitivity, specificity, accuracy and the c statistic of each ANN model from the 5 rounds of cross-validation and compared that of support vector machine (SVM) and Naïve Bayes classifier in risk stratification of the patients.Results: A total of 451 acute TIA or minor stroke patients were enrolled. Forty (8.9%) patients had a recurrent ischemic stroke within 1 year. Another 40 patients were randomly selected from those with no recurrent stroke, so that data from 80 patients in total were used for 5 rounds of training and testing of ANN models. The median sensitivity, specificity, accuracy and c statistic of the ANN models to predict recurrent stroke at 1 year was 75%, 75%, 75%, and 0.77, respectively. ANN model outperformed SVM and Naïve Bayes classifier in our dataset for predicting relapse after TIA or minor stroke.Conclusion: This pilot study indicated that ANN may yield a novel and effective method in risk stratification of TIA and minor stroke. Further studies are warranted for verification and improvement of the current ANN model