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Background: The variation in the pathogen type as well as the spatial heterogeneity of predictors make the generality of any associations with pathogen discovery debatable. Our previous work confirmed that the association of a group of predictors differed across different types of RNA viruses, yet there have been no previous comparisons of the specific predictors for RNA virus discovery in different regions. The aim of the current study was to close the gap by investigating whether predictors of discovery rates within three regions—the United States, China, and Africa—differ from one another and from those at the global level. Methods: Based on a comprehensive list of human-infective RNA viruses, we collated published data on first discovery of each species in each region. We used a Poisson boosted regression tree (BRT) model to examine the relationship between virus discovery and 33 predictors representing climate, socio-economics, land use, and biodiversity across each region separately. The discovery probability in three regions in 2010–2019 was mapped using the fitted models and historical predictors. Results: The numbers of human-infective virus species discovered in the United States, China, and Africa up to 2019 were 95, 80, and 107 respectively, with China lagging behind the other two regions. In each region, discoveries were clustered in hotspots. BRT modelling suggested that in all three regions RNA virus discovery was better predicted by land use and socio-economic variables than climatic variables and biodiversity, although the relative importance of these predictors varied by region. Map of virus discovery probability in 2010–2019 indicated several new hotspots outside historical high-risk areas. Most new virus species since 2010 in each region (6/6 in the United States, 19/19 in China, 12/19 in Africa) were discovered in high-risk areas as predicted by our model. Conclusions: The drivers of spatiotemporal variation in virus discovery rates vary in different regions of the world. Within regions virus discovery is driven mainly by land-use and socio-economic variables; climate and biodiversity variables are consistently less important predictors than at a global scale. Potential new discovery hotspots in 2010–2019 are identified. Results from the study could guide active surveillance for new human-infective viruses in local high-risk areas. Funding: FFZ is funded by the Darwin Trust of Edinburgh (https://darwintrust.bio.ed.ac.uk/). MEJW has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 874735 (VEO) (https://www.veo-europe.eu/).

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Background: E. coli O157 is a bacterial pathogen that is shed by cattle and can cause severe disease in humans. Phage type (PT) 21/28 is a subtype of E. coli O157 that is found across Scotland and is associated with particularly severe human morbidity. Methods: A cross-sectional survey of Scottish cattle farms was conducted in the period Feb 2002-Feb 2004 to determine the prevalence of E. coli O157 in cattle herds. Data from 88 farms on which E. coli O157 was present were analysed using generalised linear mixed models to identify risk factors for the presence of PT 21/28 specifically. Results: The analysis identified private water supply, and northerly farm location as risk factors for PT 21/28 presence. There was a significant association between the presence of PT 21/28 and an increased number of E. coli O157 positive pat samples from a farm, and PT 21/28 was significantly associated with larger E. coli O157 counts than non-PT 21/28 E. coli O157. Conclusion: PT 21/28 has significant risk factors that distinguish it from other phage types of E. coli O157. This finding has implications for the control of E. coli O157 as a whole and suggests that control could be tailored to target the locally dominant PT. [ABSTRACT FROM AUTHOR]

We report here our experience in achieving remission in a 20-year-old man with pulmonary capillary hemangiomatosis (PCH) with atypical endotheliomatosis following therapy with doxycycline. PCH is a rare disorder characterized by proliferating capillaries that invade the pulmonary interstitium and alveolar septae, and occlude the pulmonary vasculature. The patient's symptoms, lung function, and radiographic findings had worsened despite treatment with both prednisone and alpha-interferon. He was considered to be a candidate for transplantation. Given the elevated levels of basic fibroblast growth factor (bFGF) in urine and the capillary proliferation noted on biopsy specimens, we elected to treat the patient with doxycycline, a matrix metalloproteinase and angiogenesis inhibitor. Following several weeks of therapy, a gradual resolution of symptoms was noted, with normalization of pulmonary function test results and urine bFGF levels. After 18 months of therapy, the patient remains in complete remission. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common cancer in women worldwide. Elucidation of underlying biology and molecular pathways is necessary for improving therapeutic options and clinical outcomes. CLN3 protein (CLN3p), deficient in neurodegenerative CLN3 disease is anti-apoptotic, and defects in the CLN3 gene cause accelerated apoptosis of neurons in CLN3 disease and upregulation of ceramide. Dysregulated apoptotic pathways are often implicated in the development of the oncogenic phenotype. Predictably, CLN3 mRNA expression and CLN3 protein were upregulated in a number of human and murine breast cancer cell lines. Here, we determine CLN3 expression in non-tumor vs. tumor samples from fresh and formalin-fixed/paraffin-embedded (FFPE) breast tissue and analyze the association between CLN3 overexpression and different clinicopathological characteristics of breast cancer patients. Additionally, gene expression of 28 enzymes involved in sphingolipid metabolism was determined. CLN3 mRNA is overexpressed in tumor vs. non-tumor breast tissue from FFPE and fresh samples, as well as in mouse MCF7 breast cancer compared to MCF10A normal cells. Of the clinicopathological characteristics of tumor grade, age, menopause status, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), only absence of HER2 expression correlated with CLN3 overexpression. Sphingolipid genes for ceramide synthases 2 and 6 (CerS2; CerS6), delta(4)-desaturase sphingolipid 2 (DEGS2) and acidic sphingomyelinase (SMPD1) displayed higher expression levels in breast cancer vs. control tissue, whereas, ceramide galactosyltransferase (UGT8) was underexpressed in breast cancer samples. CLN3 may be a novel molecular target for cancer drug discovery with the goal of modulation of ceramide pathways.

In a two dimensional electron system (2DES), coherent spin precession of a ballistic spin polarized current, controlled by the Rashba spin orbit interaction, is a remarkable phenomenon that’s been observed only recently. Datta and Das predicted this precession would manifest as an oscillation in the source-drain conductance of the channel in a spin-injected field effect transistor (Spin FET). The indium arsenide single quantum well materials system has proven to be ideal for experimental confirmation. The 2DES carriers have high mobility, low sheet resistance, and high spin orbit interaction. Techniques for electrical injection and detection of spin polarized carriers were developed over the last two decades. Adapting the proposed Spin FET to the Johnson-Silsbee nonlocal geometry was a key to the first experimental demonstration of gate voltage controlled coherent spin precession. More recently, a new technique measured the oscillation as a function of channel length. This article gives an overview of the experimental phenomenology of the spin injection technique. We then review details of the application of the technique to InAs single quantum well (SQW) devices. The effective magnetic field associated with Rashba spin-orbit coupling is described, and a heuristic model of coherent spin precession is presented. The two successful empirical demonstrations of the Datta Das conductance oscillation are then described and discussed.

We discuss recent progress in the development of cognitive ontologies and summarize three challenges in the coordinated development and application of these resources. Challenge 1 is to adopt a standardized definition for cognitive processes. We describe three possibilities and recommend one that is consistent with the standard view in cognitive and biomedical sciences. Challenge 2 is harmonization. Gaps and conflicts in representation must be resolved so that these resources can be combined for mark-up and interpretation of multi-modal data. Finally, Challenge 3 is to test the utility of these resources for large-scale annotation of data, search and query, and knowledge discovery and integration. As term definitions are tested and revised, harmonization should enable coordinated updates across ontologies. However, the true test of these definitions will be in their community-wide adoption which will test whether they support valid inferences about psychological and neuroscientific data.

Store-operated calcium (Ca2+) entry (SOCE) can be mediated by two novel proteins, STIM/Orai. We have previously demonstrated that members of the TRPC family, putative basal and store operated calcium entry channels, are present in human myometrium and regulated by labor associated stimuli IL-1β and mechanical stretch. Although STIM and Orai isoforms (1-3) have been reported in other smooth muscle cell types, there is little known about the expression or gestational regulation of STIM and Orai expression in human myometrium. Total RNA was isolated from lower segment human myometrial biopsies obtained at caesarean section from women at the time of preterm no labor (PTNL), preterm labor (PTL), term non-labor (TNL) and term with labor (TL); primary cultured human uterine smooth muscle cells, and a human myometrial cell line (hTERT-HM). STIM1-2, and Orai1-3 mRNA expression was assessed by quantitative real-time PCR. All five genes were expressed in myometrial tissue and cultured cells. Orai2 was the most abundant Orai isoform in human myometrium. Expression of STIM1-2/Orai1-3 did not alter with the onset of labor. Orai1 mRNA expression in cultured cells was enhanced by IL-1β treatment. This novel report of STIM1-2 and Orai1-3 mRNA expression in pregnant human myometrium and Orai1 regulation by IL-1β indicates a potential role for these proteins in calcium signaling in human myometrium during pregnancy.

The brainstem is directly involved in controlling blood pressure, respiration, sleep/wake cycles, pain modulation, motor and cardiac output. As such it is of significant basic science and clinical interest. However, the brainstem’s location close to major arteries and adjacent pulsatile cerebrospinal fluid filled spaces, means that it is difficult to reliably record functional magnetic resonance imaging (fMRI) data from. These physiological sources of noise generate time varying signals in fMRI data, which if left uncorrected can obscure signals of interest. In this Methods Article we will provide a practical introduction to the techniques used to correct for the presence of physiological noise in time series fMRI data. Techniques based on independent measurement of the cardiac and respiratory cycles, such as retrospective image correction (RETROICOR, Glover et al., 2000), will be described and their application and limitations discussed. The impact of a physiological noise model, implemented in the framework of the general linear model, on resting fMRI data acquired at 3T and 7T is presented. Data driven approaches based such as independent component analysis (ICA) are described. MR acquisition strategies that attempt to either minimise the influence of physiological fluctuations on recorded fMRI data, or provide additional information to correct for their presence, will be mentioned. General advice on modelling noise sources, and its effect on statistical inference via loss of degrees of freedom, and non-orthogonality of regressors, is given. Lastly, different strategies for assessing the benefit of different approaches to physiological noise modelling are presented.

The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy adults. It will serve as a key resource for the neuroscience research community, enabling discoveries of how the brain is wired and how it functions in different individuals. To fulfill its potential, the HCP consortium is developing an informatics platform that will handle: 1) storage of primary and processed data, 2) systematic processing and analysis of the data, 3) open access data sharing, and 4) mining and exploration of the data. This informatics platform will include two primary components. ConnectomeDB will provide database services for storing and distributing the data, as well as data analysis pipelines. Connectome Workbench will provide visualization and exploration capabilities. The platform will be based on standard data formats and provide an open set of application programming interfaces (APIs) that will facilitate broad utilization of the data and integration of HCP services into a variety of external applications. Primary and processed data generated by the HCP will be openly shared with the scientific community, and the informatics platform will be available under an open source license. This paper describes the HCP informatics platform as currently envisioned and places it into the context of the overall HCP vision and agenda.