Hoppealbrechtsen2648

Carbon sequestration is a key soil function, and an increase in soil organic carbon (SOC) is an indicator of ecosystem recovery because it underpins other ecosystem services by acting as a substrate for the soil microbial community. The soil microbial community constitutes the active pool of SOC, and its necromass (microbial residue carbon, MRC) contributes strongly to the stable SOC pool. Therefore, we propose that the potential for restoration of degraded karst ecosystems lies in the abundance of soil microbial community and the persistence of its necromass, and may be measured by changes in its contribution to the active and stable SOC pools during recovery. We investigated changes in SOC stocks using an established space-for-time chronosequence along a perturbation gradient in the subtropical karst ecosystem sloping cropland less then abandoned cropland less then shrubland less then secondary forest less then primary forest. Microbial biomarkers were extracted from soil profiles from surface to beubstantially to building SOC stocks after abandonment of agriculture in degraded karst landscapes.Environmental factors are well known to affect spatio-temporal patterns of infectious disease outbreaks, but whether the rapid spread of COVID-19 across the globe is related to local environmental conditions is highly debated. We assessed the impact of environmental factors (temperature, humidity and air pollution) on the global patterns of COVID-19 early outbreak dynamics during January-May 2020, controlling for several key socio-economic factors and airport connections. We showed that during the earliest phase of the global outbreak (January-March), COVID-19 growth rates were non-linearly related to climate, with fastest spread in regions with a mean temperature of ca. 5 °C, and in the most polluted regions. However, environmental effects faded almost completely when considering later outbreaks, in keeping with the progressive enforcement of containment actions. Accordingly, COVID-19 growth rates consistently decreased with stringent containment actions during both early and late outbreaks. Our findings indicate that environmental drivers may have played a role in explaining the early variation among regions in disease spread. With limited policy interventions, seasonal patterns of disease spread might emerge, with temperate regions of both hemispheres being most at risk of severe outbreaks during colder months. Nevertheless, containment measures play a much stronger role and overwhelm impacts of environmental variation, highlighting the key role for policy interventions in curbing COVID-19 diffusion within a given region. If the disease will become seasonal in the next years, information on environmental drivers of COVID-19 can be integrated with epidemiological models to inform forecasting of future outbreak risks and improve management plans.Methods for metric scoring and health status classification in development of index of biotic integrity (IBI) vary considerably across published studies. The difference between ecosystem health assessment results from these alternative methods for scoring and classification has rarely been studied systematically. Poyang Lake in China has experienced severe degradation over recent decades. Here, we aimed to develop a benthic macroinvertebrate-based index of biotic integrity (B-IBI) to assess the wetland health of Poyang Lake, and to evaluate the difference in assessment results using different methods of scoring and classification. Data on benthic macroinvertebrate assemblages, water quality and human-induced disturbances were collected at 30 sampling sites. Forty-nine attributes of macroinvertebrate assemblages were tested, and only the attributes that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites were selected as the B-IBI hed is therefore important for the wetland conservation.Aggressive B-cell lymphomas are currently classified based in part upon the presence or absence of translocations involving BCL2, BCL6, and MYC. Most clinical laboratories employ fluorescence in situ hybridization (FISH) analysis for the detection of these rearrangements. The potential role of RNA-based sequencing approaches in the evaluation of malignant lymphoma is currently unclear. In this study, we performed RNA sequencing (RNAseq) in 37 cases of aggressive B-cell lymphomas using a commercially available next generation sequencing assay and compared results to previously performed FISH studies. RNAseq detected 1/7 MYC (14%), 3/8 BCL2 (38%) and 4/8 BCL6 (50%) translocations identified by FISH. RNAseq also detected 1 MYC/IGH fusion in a case not initially tested by FISH due to low MYC protein expression and 2 BCL6 translocations that were not detected by FISH. RNAseq identified the partner gene in each detected rearrangement, including a novel EIF4G1-BCL6 rearrangement. In summary, RNAseq complements FISH for the detection of rearrangements of BCL2, BCL6 and MYC in the evaluation and classification of aggressive B-cell lymphomas by detecting rearrangements that may be cryptic by FISH methods and by identifying the rearrangement partner genes. UNC0638 purchase Detection of these clinically important translocations may be optimized by combined use of FISH and RNAseq.Transport stress (TS) in animals lead to change in blood composition, brain structure, and the endocrine system as well as behavior. γ-aminobutyric acid (GABA), a major inhibitory neurotransmitter in the mammalian central nervous system (CNS), influences many physiological functions and plays a significant role in coping with stress. This study aimed to explore the effect of stress on behavior, HPA axis, GABA transmitters and the distribution of GABAergic interneurons in the prefrontal cortex (PFC) and striatum of the brain by a rat model of simulated transport stress (STS). Thirty-six male Sprague Dawley rats were randomly divided into a control group (n = 12, no stress), a TS1d group (n = 12, 2 h stress for 1 d) and a TS7d group (n = 12, 2 h stress each day for 7 d). After STS, the rats were subjected to open-field testing (OFT) followed by serologic analysis, colorimetry, Western blot and immunohistochemistry. The total score of the OFT showed the similar profile with serum concentrations of corticosterone (CORT) and norepinephrine (NE), which in the TS7d group were all higher than the TS1d group but lower than the control group. STS also reduced GABA, glutamate decarboxylase 67 (GAD67) and GABA transporter 1 (GAT1) expression in the TS1d and these markers were increased in the TS7d, suggesting that GABA was related to hypothalamic-pituitary-adrenal (HPA) axis activation under stress. The number of parvalbumin (PV)-, somatostatin (SOM)-, and calretinin (CR)- positive cells were decreased with stress increase. Our findings revealed that STS affected the behavior of rats, synthesis and release of GABA by altering the HPA axis.The most recent developments on Pickering emulsions deal with the design of responsive emulsions able to undergo fast destabilization under the effect of an external stimulus. In this scenario, soft colloidal particles like microgels are considered novel class suitable emulsifiers. Microgels particles self-assemblies are highly deformable at interfaces covering higher surfaces than hard particles and their interfacial behavior strongly depends on external-stimuli. Microgels are very diverse owing to the large variety of them from the point of view of possible combinations of stimuli-responsiveness and different microstructures (crosslinking density and distribution). Herein, we illustrate the use of different types of responsive microgels not only from a structural point of view but also even from physical one. For that, the effect of different microgels parameters such as internal structure and charge density on mechanical properties of the interface will be discussed.

College students are at high risk of problematic internet use (PIU). A great amount of research has focused on the PIU among college students. However, little is known about the change pattern of PIU across the college years. Moreover, how peer internet overuse behavior and peer attitude toward internet overuse work together to shape college students' PIU trajectory, and whether such peer contagion effects are equal for all students remain unclear. The present study used latent growth curve model to examine these issues.

A total of 2572 Chinese college students (M

=18.37, SD=0.85; 65% girls) participated in the study. They completed questionnaires regarding demographics, peer internet overuse behavior, peer attitude toward internet overuse, and friendship satisfaction at Wave 1, and PIU at Waves 1-4.

After controlling for covariates, the findings revealed that (a) PIU slightly increased before the second year of college and then declined rapidly; (b) both peer internet overuse behavior and peer attitude toward internet overuse were related to the PIU at baseline; however, only peer internet overuse behavior was associated with the change of PIU; and (c) the effect of peer internet overuse behavior on PIU change was moderated by friendship satisfaction and gender.

These findings emphasized the dynamic and context-sensitive nature of PIU and clarified how peer contagion unfolded with peer internet overuse behavior and peer attitude toward internet overuse. Theoretical implications and application of these findings are discussed.

These findings emphasized the dynamic and context-sensitive nature of PIU and clarified how peer contagion unfolded with peer internet overuse behavior and peer attitude toward internet overuse. Theoretical implications and application of these findings are discussed.

Goblet cell carcinoma (GCC), formerly known as goblet cell carcinoid, of the appendix constitutes less than 14% of all primary appendiceal neoplasms. Surgical resection is the main treatment and the role of adjuvant chemotherapy (AC) is not established. This study aims to evaluate the impact of AC in stage II-III appendiceal GCC.

Patients with pathological stage II and III GCC who underwent surgical resection between 2006 and 2015 were identified from the National Cancer Database (NCDB) using ICD-O-3 morphology and topography codes 8243/3 (goblet cell carcinoid) and C18.1. Patients treated with neoadjuvant systemic and/or radiation therapy and adjuvant radiation were excluded. Univariate and multivariable analyses were conducted, and Kaplan-Meier Curves were used to compare overall survival (OS) based on treatment received with Log-rank test.

A total of 619 patients were identified. 54.4% males and 89.0% Caucasian; median age 56 (range, 23-90) years. Distribution across pathological stages II-III was 82but not with pathological stage II.

Cervical cancer is the second most common female cancer globally, and it is vital to detect cervical cancer with low cost at an early stage using automated screening methods of high accuracy, especially in areas with insufficient medical resources. Automatic detection of cervical intraepithelial neoplasia (CIN) can effectively prevent cervical cancer.

Due to the deficiency of standard and accessible colposcopy image datasets, we present a dataset containing 4753 colposcopy images acquired from 679 patients in three states (acetic acid reaction, green filter, and iodine test) for detection of cervical intraepithelial neoplasia. Based on this dataset, a new computer-aided method for cervical cancer screening was proposed.

We employed a wide range of methods to comprehensively evaluate our proposed dataset. Hand-crafted feature extraction methods and deep learning methods were used for the performance verification of the multistate colposcopy image (MSCI) dataset. Importantly, we propose a gated recurrent convolutional neural network (C-GCNN) for colposcopy image analysis that considers time series and combined multistate cervical images for CIN grading.