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Biological soil crusts (BSCs) consist of a diverse and highly integrated community of organisms that effectively colonize and collectively stabilize soil surfaces. BSCs vary in terms of soil chemistry and texture as well as the environmental parameters that combine to support unique combinations of organisms—including cyanobacteria dominated, lichen-dominated, and bryophyte-dominated crusts. The list of organismal groups that make up BSC communities in various and unique combinations include—free living, lichenized, and mycorrhizal fungi, chemoheterotrophic bacteria, cyanobacteria, diazotrophic bacteria and archaea, eukaryotic algae, and bryophytes. The various BSC organismal groups demonstrate several common characteristics including—desiccation and extreme temperature tolerance, production of various soil binding chemistries, a near exclusive dependency on asexual reproduction, a pattern of aerial dispersal over impressive distances, and a universal vulnerability to a wide range of human-related perturbations. With this publication, we provide literature-based insights as to how each organismal group contributes to the formation and maintenance of the structural and functional attributes of BSCs, how they reproduce, and how they are dispersed. We also emphasize the importance of effective application of molecular and microenvironment sampling and assessment tools in order to provide cogent and essential answers that will allow scientists and land managers to better understand and manage the biodiversity and functional relationships of soil crust communities.

There are at present ${ \mathcal O }(100)$ gravitational-wave candidates from compact binary mergers reported in the astronomical literature. As detector sensitivities are improved, the catalog will swell in size: first to ${ \mathcal O }(1000)$ events in the A+ era and then to ${ \mathcal O }({10}^{6})$ events in the era of third-generation observatories like Cosmic Explorer and the Einstein Telescope. Each event is analyzed using Bayesian inference to determine properties of the source including component masses, spins, tidal parameters, and the distance to the source. These inference products are the fodder for some of the most exciting gravitational-wave science, enabling us to measure the expansion of the universe with standard sirens, to characterize the neutron-star equation of state, and to unveil how and where gravitational-wave sources are assembled. In order to maximize the science from the coming deluge of detections, we introduce GW Cloud , a searchable repository for the creation and curation of gravitational-wave inference products. It is designed with five pillars in mind: uniformity of results, reproducibility of results, stability of results, access to the astronomical community, and efficient use of computing resources. We describe how to use GW Cloud with examples, which readers can replicate using the companion code to this paper. We describe our long-term vision for GW Cloud .

Objective: To explore relationships between PET/CT characteristics of cold-activated brown adipose tissue (BAT), measures of adiposity and metabolic markers. Methods: We conducted a post-hoc analysis of a study which utilized PET/CT to characterize BAT. 25 men ages 18–24 (BMI 19.4 to 35.9 kg/m2) were studied. Fasting blood samples were collected. Body composition was measured using DXA. An individualized cooling protocol was utilized to activate BAT prior to imaging with PET/CT. Results: There was an inverse relationship between fasting serum glucose and BAT volume (r = −0.40, p = 0.048). A marginally significant inverse relationship was also noted between fasting glucose and total BAT activity (r = −0.40, p = 0.05). In addition, a positive correlation was observed between serum FGF21 and SUVmax (r = 0.51, p = 0.01). No significant correlations were noted for measures of BAT activity or volume and other indicators of adiposity or glucose metabolism. Conclusions: The presence of active BAT may be associated with lower fasting glucose in young men. BAT activity may also be correlated with levels of FGF21, suggesting that BAT may lower glucose levels via an FGF21 dependent pathway. Further studies are needed to clarify mechanisms by which BAT may impact glucose metabolism.

Despite the demand and interest for the blockchain technology, there are still major challenges for blockchain application initiatives (projects and ventures) to be sustainable and reliable. While starting a non-blockchain initiative already comes with itsown sets of challenges and has around 50% failure rate, starting a blockchain initiative rises the rate to 90% due to additional variables and confusion on top of this. Such a situation deters innovators and eventually dampens innovation, requiring priority for actions. This paper attempts to contribute by compiling and outlining the various key variables to be considered, as a set of parameters for blockchain initiators. Through secondary data collection: literature reviews, report studies and primary data collection: interventional and observational case study, interviews with blockchain researchers, businesses and entrepreneurs, this paper categorises variables into blockchain-related and business-related categories, outlining consideration points for each of the variables. By summarizing and integrating the variables and referring to theories of innovation and adoption, it is concluded that concept validation entailing both initiative feasibility and user-demand, is of key importance for blockchain innovations.

Nitrogen (N) fertilizer is routinely applied by farmers to increase crop yields. At present, farmers often over-apply N fertilizer in some locations or at certain times because they do not have high-resolution crop N status data. N-use efficiency can be low, with the remaining N lost to the environment, resulting in higher production costs and environmental pollution. Accurate and timely estimation of N status in crops is crucial to improving cropping systems’ economic and environmental sustainability. Destructive approaches based on plant tissue analysis are time consuming and impractical over large fields. Recent advances in remote sensing and deep learning have shown promise in addressing the aforementioned challenges in a non-destructive way. In this work, we propose a novel deep learning framework: a self-supervised spectral–spatial attention-based vision transformer (SSVT). The proposed SSVT introduces a Spectral Attention Block (SAB) and a Spatial Interaction Block (SIB), which allows for simultaneous learning of both spatial and spectral features from UAV digital aerial imagery, for accurate N status prediction in wheat fields. Moreover, the proposed framework introduces local-to-global self-supervised learning to help train the model from unlabelled data. The proposed SSVT has been compared with five state-of-the-art models including: ResNet, RegNet, EfficientNet, EfficientNetV2, and the original vision transformer on both testing and independent datasets. The proposed approach achieved high accuracy (0.96) with good generalizability and reproducibility for wheat N status estimation.

We present the purpose, long-term development vision, basic design, detection algorithm and preliminary results obtained with the Cosmic Ray Extremely Distributed Observatory (CREDO) Detector mobile application. The CREDO Detector app and related infrastructure are unique in terms of their scale, targeting many form-factors and open-access philosophy. This philosophy translates to the open-source code of the app, open-access in terms of both data inflow as well as data consumption and above all, the citizen science philosophy that means that the infrastructure is open to all who wish to participate in the project. The CREDO infrastructure and CREDO Detector app are designed for the large-scale study of various radiation forms that continuously reach the Earth from space, but with the sensitivity to local radioactivity as well. Such study has great significance both scientifically and educationally as cosmic radiation has an impact on diverse research areas from life on Earth to the functioning of modern electronic devices. The CREDO Detector app is now working worldwide across phones, tablets, laptops, PCs and cheap dedicated registration stations. These diverse measurements contribute to the broader search for large-scale cosmic ray correlations, as well as the CREDO-specific proposed extensive air showers and incoherent secondary cosmic rays.

Frizzled homolog 3 receptor was up-regulated in several gastrointestinal cancers such as esophageal and gastric cancers. Moreover, frizzled homolog 3 has recently reported to be expressed in colorectal adenoma specimens. In the present study, we investigated the clinical significance of frizzled homolog 3 protein in colorectal cancer patients. Using immunocytochemical staining, frizzled homolog 3 expression was examined in 186 colorectal cancer specimens, 79 colorectal adenoma specimens, 133 colorectal polyp specimens, 127 colorectal cancer specimens with lymph node and/or distant metastasis, 310 specimens of various non-colorectal cancer metastatic carcinomas and 40 specimens with simultaneous occurrence of colorectal cancer, colorectal adenoma and colorectal polyp. Statistical analysis was used to correlate frizzled homolog 3 protein expression to the clinicohistopathological factors, recurrence/metastasis and survival after follow-up for 42 months in colorectal cancer patients. Frizzled homolog 3 protein was expressed in 100% colorectal cancer specimens, 89% colorectal adenoma specimens, 75% colorectal polyp specimens and 69% normal colorectal epithelial tissues. Moreover, frizzled homolog 3 immunocytochemical scores were highly correlated with colorectal cancer progression. Furthermore, frizzled homolog 3 was expressed in a comparatively lower percentage of metastatic hepatocellular carcinoma and metastatic renal clear cell carcinoma with focal and very weak staining than other metastatic tumor types. On the other hand, the frizzled homolog 3 immunocytochemical scores of colorectal adenomas with synchronous colorectal carcinomas were significantly higher than those of pure colorectal adenomas. Statistical analysis showed that frizzled homolog 3 immunocytochemical scores were associated with Dukes stage and lymph node status. Finally, stratified groups of colorectal cancer patients had significant differences in their recurrence/metastasis and survival. In conclusion, the present large-scale study has clearly showed that frizzled homolog 3 protein can generate clinically important information for colorectal cancer patients.

Abstract Background Alcohol use disorders (AUDs) lead to alterations in central nervous system (CNS) architecture along with impaired learning and memory. Previous work from our group and that of others suggests that one mechanism underlying these changes is alteration of cell proliferation, apoptosis, and DNA-repair in neural stem cells (NSCs) produced as a consequence of ethanol-induced effects on the expression of genes related to p53-signaling. This study tests the hypothesis that changes in the expression of p53-signaling genes represent biomarkers of ethanol abuse which can be identified in the peripheral blood of rat drinking models and human AUD subjects and posits that specific changes may be correlated with differences in neuropsychological measures and CNS structure. Results Remarkably, microarray analysis of 350 genes related to p53-signaling in peripheral blood leukocytes (PBLs) of binge-drinking rats revealed 190 genes that were significantly altered after correcting for multiple testing. Moreover, 40 of these genes overlapped with those that we had previously observed to be changed in ethanol-exposed mouse NSCs. Expression changes in nine of these genes were tested for independent confirmation by a custom QuantiGene Plex (QGP) assay for a subset of p53-signaling genes, where a consistent trend for decreased expression of mitosis-related genes was observed. One mitosis-related gene (Pttg1) was also changed in human lymphoblasts cultured with ethanol. In PBLs of human AUD subjects seven p53-signaling genes were changed compared with non-drinking controls. Correlation and principal components analysis were then used to identify significant relationships between the expression of these seven genes and a set of medical, demographic, neuropsychological and neuroimaging measures that distinguished AUD and control subjects. Two genes (Ercc1 and Mcm5) showed a highly significant correlation with AUD-induced decreases in the volume of the left parietal supramarginal gyrus and neuropsychological measures. Conclusions These results demonstrate that alcohol-induced changes in genes related to proliferation, apoptosis, and DNA-repair are observable in the peripheral blood and may serve as a useful biomarker for CNS structural damage and functional performance deficits in human AUD subjects.