SAGE Datasets Research Articles

Evaluation of Global Historical Cropland Datasets with Regional Historical Evidence and Remotely Sensed Satellite Data from the Xinjiang Area of China

Global land use/cover change (LUCC) datasets are essential for quantitatively assessing the impacts of LUCC on global change, but many uncertainties in existing global datasets seriously hamper climate modeling. Evaluating the reliability of existing global LUCC datasets is a precondition for improved data quality. In this study, based on the regional historical document-based reconstructions, satellite-based data, and historical reclamation evidence for the Xinjiang area of China, the accuracy and rationality of cropland data for this area in the HYDE 3.2 and SAGE datasets were evaluated by utilizing comparative analysis regarding three aspects, namely the change tendency of the cropland area, the area of cropland, and the differences in spatial pattern. This study concluded that the amount of cropland in the Xinjiang area in the global and regional datasets shows both disparate trends and large differences in absolute values. Spatially, historical reclamation evidence indicated that agricultural cultivation in the Xinjiang area underwent expansion from south to north and from east to west over the past 300 years; however, the global datasets revealed that the cropland spatial patterns in the Xinjiang area in the historical period are similar to those in the current period. These differences are attributable to the uncertainties of the basic assumptions, per capita cropland area estimates, and reconstruction methods in the global datasets. The findings of the study highlight the necessity of regional studies on historical LUCC in the Xinjiang area.

Mood Homeostasis, Low Mood, and History of Depression in 2 Large Population Samples

Existing therapeutic options are insufficient to tackle the disease burden of depression, and new treatments are sorely needed. Defining new psychotherapeutic targets is challenging given the paucity of coherent mechanistic explanations for depression. To assess whether mood homeostasis (ie, the stabilization of one's mood by engaging in mood-modifying activities) is a possible new therapeutic target by testing the hypothesis that people with low (vs high) mean mood and people with (vs without) a history of depression have impaired mood homeostasis. The quantitative association between mood and daily activities was computed in 2 large case-control studies based on the 58sec data set (collected from December 1, 2012, to May 31, 2014, and analyzed from April 1 to 30, 2019), and the World Health Organization Study on Global Aging and Adult Health (WHO SAGE) data set (collected from January 1, 2007, to December 31, 2010, and analyzed from June 1 to 30, 2019). The 58sec data set consists of self-enrolled participants from high-income countries. The WHO SAGE data set consists of nationally representative participants in low- and middle-income countries recruited via cluster sampling. The main outcome (defined before data analysis) was the difference in mood homeostasis between people with high vs low mean mood (58sec data) and between people with vs without a history of depression (WHO SAGE data). A total of 28 212 participants from the 58sec data set (65.8% female; mean [SD] age, 28.1 [9.0] years) and 30 116 from the WHO SAGE data set (57.0% female; mean [SD] age, 57.8 [14.7] years) were included, for an overall study population of 58 328 participants. Mood homeostasis was significantly lower in people with low (vs high) mean mood (0.63 [95% CI, 0.45 to 0.79] vs 0.96 [95% CI, 0.96 to 0.98]; P < .001) and in people with (vs without) a history of depression (0.03 [95% CI, -0.26 to 0.24] vs 0.68 [95% CI, 0.55 to 0.75]; P < .001). In dynamic simulations, lower mood homeostasis led to more depressive episodes (11.8% vs 3.8% yearly risk; P < .001) that lasted longer (4.19 vs 2.90 weeks; P = .006). In this study, mood homeostasis appeared to have been impaired in people with low mood and in those with a history of depression. Mood homeostasis may therefore provide new insights to guide the development of treatments for depression.

Evaluating the accuracy of Chinese pasture data in global historical land use datasets

Global historical land use datasets are widely used in global environmental change studies; however, uncertainties in the included pasture data have not been evaluated. In this study, using trend, relative difference ratio (RDR), and spatial comparisons, we evaluated the accuracy of China pasture data in the HYDE (versions 3.1 and 3.2), SAGE, and PJ datasets using historical document-based reconstructions, including the land use datasets for China covering 1935–1997 (hereafter Ge-dataset) and Northeast China covering the 1700s–2000 (hereafter Ye-dataset), and the satellite-based China’s Land-Use/cover Datasets (CLUDs) for 1980–2015. Four important results were obtained. (1) China pasture area in the HYDE, SAGE, and PJ datasets and grassland area in the Ge-dataset, Ye-dataset, and CLUDs show both disparate trends and large differences in absolute values. (2) Spatially, 50.9%, 52.8%, and 63.0% pasture/grassland grids in 2000 had RDRs greater than 60% between HYDE3.1, HYDE3.2, and SAGE datasets, and CLUDs, respectively. The percentage of grids with RDRs less than 20% were 24.9%, 26.7%, and 16.0%, respectively. (3) Based on HYDE3.2, the spatial distribution of pasture in Northeast China over the last 300 year has expanded, which is in contrast to the results from the Ye-dataset, which shows the spatial distribution of grassland shrinking because of human reclamation activities. (4) The large contrasts between the global datasets and Chinese native datasets are due to differences in pasture/grassland definitions, land use practices, and spatial reconstruction methods.

The lncRNA H19 positively affects the tumorigenic properties of glioblastoma cells and contributes to NKD1 repression through the recruitment of EZH2 on its promoter.

The still largely obscure molecular events in the glioblastoma oncogenesis, a primary brain tumor characterized by an inevitably dismal prognosis, impel for investigation. The importance of Long noncoding RNAs as regulators of gene expression has recently become evident. Among them, H19 has a recognized oncogenic role in several types of human tumors and was shown to correlate to some oncogenic aspects of glioblastoma cells. Here we, hypothesyze that in glioblastoma H19 exerts its function through the interaction with the catalytic subunit of the PRC2 complex, EZH2. By employing a factor analysis on a SAGE dataset of 12 glioblastoma samples, we show that H19 expression in glioblastoma tissues correlates with that of several genes involved in glioblastoma growth and progression. H19 knock-down reduces viability, migration and invasiveness of two distinct human glioblastoma cell lines. Most importantly, we provide a mechanistic perspective about the role of H19 in glioblastoma cells, by showing that its expression is inversely linked to that of NKD1, a negative regulator of Wnt pathway, suggesting that H19 might regulate NKD1 transcription via EZH2-induced H3K27 trimethylation of its promoter. Indeed, we showed that H19 binds EZH2 in glioblastoma cells, and that EZH2 binding to NKD1 and other promoters is impaired by H19 silencing.In this work we describe H19 as part of an epigenetic modulation program executed by EZH2, that results in the repression of Nkd1. We believe that our results can provide a new piece to the complex puzzle of H19 function in glioblastoma.

A comparable yardstick: adjusting for education bias in South African health system responsiveness ratings.

Health-system responsiveness (HSR) measures the experience of health-system users in terms of the non-clinical aspects of the health system. This has been operationalized as a measurable construct in multiple surveys and studies. According to the literature, reporting behaviour may vary systematically across socio-demographic characteristics. In this study we explore the association between education levels and reporting behaviour in terms of HSR in South Africa using data from the World Health Organization Study on Global Ageing and Adult Health for South Africa (WHO SAGE) conducted in 2007 and 2008. We consider the reporting behaviour of 1499 adults aged 50 and older in terms of the reported HSR for their most recent outpatient provider visit during the preceding 12 months. More specifically, we explore whether there are systematic biases in reporting behaviour by education levels and other socio-economic covariates through the use of data from anchoring vignettes. These are questions depicting hypothetical HSR scenarios which provide a fixed benchmark for comparing individuals' own HSR ratings and identifying potential reporting biases. Using a hierarchical-ordered probit model in regression analysis, we found large differences in HSR ratings between the lowest and highest education groups after adjusting for reporting bias using the anchoring vignettes. This finding holds across all seven HSR domains captured in the WHO SAGE dataset. In the most extreme case, individuals with no education are likely to underreport poor HSR by between 2.6 and 9.4% percentage points compared with individuals with secondary schooling or higher. Policy-makers need to take cognizance of potential reporting biases in HSR ratings and make the necessary adjustments to obtain data that are as true and accurate as possible. The need for this is especially acute in a country such as South Africa with large socio-economic inequalities and disparities in access to healthcare.

Reconstructing spatial distribution of historical cropland in China's traditional cultivated region: Methods and case study

As an important part of land use/cover change (LUCC), historical LUCC in long time series attracts much more attention from scholars. Currently, based on the view of combining the overall control of cropland area and 'top-down' decision-making behaviors, here are two global historical land-use datasets, generally referred as the Sustainability and the Global Environment datasets (SAGE datasets) and History Database of the Global Environment datasets (HYDE datasets). However, at the regional level, these global datasets have coarse resolutions and inevitable errors. Considering various factors that influenced cropland distribution, including cropland connectivity and the limitation of natural and human factors, this study developed a reconstruction model of historical cropland based on constrained Cellular Automaton (CA) of 'bottom-up'. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. Applied the reconstruction model to Shandong Province, we reconstructed its spatial distribution of cropland during 8 periods. The reconstructed results show that: 1) it is properly suitable for constrained CA to simulate and reconstruct the spatial distribution of cropland in traditional cultivated region of China; 2) compared with 'SAGE datasets' and 'HYDE datasets', this study have formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format.

Comparisons of cropland area from multiple datasets over the past 300 years in the traditional cultivated region of China

Land use/cover change is an important parameter in the climate and ecological simulations. Although they had been widely used in the community, SAGE dataset and HYDE dataset, the two representative global historical land use datasets, were little assessed about their accuracies in regional scale. Here, we carried out some assessments for the traditional cultivated region of China (TCRC) over last 300 years, by comparing SAGE2010 and HYDE (v3.1) with Chinese Historical Cropland Dataset (CHCD). The comparisons were performed at three spatial scales: entire study area, provincial area and 60 km by 60 km grid cell. The results show that (1) the cropland area from SAGE2010 was much more than that from CHCD; moreover, the growth at a rate of 0.51% from 1700 to 1950 and −0.34% after 1950 were also inconsistent with that from CHCD. (2) HYDE dataset (v3.1) was closer to CHCD dataset than SAGE dataset on entire study area. However, the large biases could be detected at provincial scale and 60 km by 60 km grid cell scale. The percent of grid cells having biases greater than 70% ( 70%) and 90% ( 90%) accounted for 56%–63% and 40%–45% of the total grid cells respectively while those having biases range from −10% to 10% and from −30% to 30% account for only 5%–6% and 17% of the total grid cells respectively. (3) Using local historical archives to reconstruct historical dataset with high accuracy would be a valuable way to improve the accuracy of climate and ecological simulation.

Aberrant Expression of Long Noncoding RNAs in Cervical Intraepithelial Neoplasia

Long noncoding RNAs (lncRNAs) are a unique class of messenger RNA-like transcripts of at least 200 nucleotides in length with no significant protein-coding capacity. Aberrant lncRNA expression is emerging as a major component of the cancer transcriptome. Here, we sought to determine if differential lncRNA expression is a feature of the human cervical intraepithelial neoplasia (CIN) transcriptome. Sequence data were derived from 16 long serial analyses of gene expression (L-SAGE) libraries constructed from cervical specimens representing mild (CIN1), moderate (CIN2), and severe (CIN3) histopathologic grades of CIN. A novel lncRNA discovery pipeline was developed to query the expression of lncRNAs within the SAGE data sets. A total of 2,230,370 sequence tags were delineated from the 16 SAGE libraries, representing the expression of 367,482 unique tags at varying abundance. Using a novel stepwise filtering strategy, we analyzed the cervical SAGE libraries and identified the expression profiles of 1056 lncRNAs in the human cervix. We present the first lncRNA expression profile derived from nonneoplastic cervical tissue and establish that changes in lncRNA expression do occur in cervical intraepithelial lesions. Our analysis also shows statistically significant aberrant expression of lncRNAs in the 3 CIN grades, suggesting that these unique noncoding RNA transcripts may contribute to the development and progression of precursor lesions. Through the analysis of L-SAGE libraries constructed from cervical specimens, we provide the first lncRNA expression profile of the cervix and demonstrate aberrant expression in early-stage neoplasia.

TACR1 Genotypes Predict fMRI Response to Alcohol Cues and Level of Alcohol Dependence

The tachykinin receptor 1 (TACR1) gene is a promising candidate gene in the search for the genetic basis of alcohol dependence (AD); TACR1 antagonists improve symptomology not only in preclinical models of AD but also in a clinical sample of detoxified alcoholics (George et al., Science 319:1536, 2008). The purpose of the current study was to determine whether TACR1 single nucleotide polymorphisms (SNPs) were associated with (i) blood oxygen level dependent (BOLD) activation in response to gustatory alcohol cues in a sample of heavy drinkers and (ii) Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) AD symptom count in a large, publicly available data set-the Study of Addictions: Genetics and Environment Genome Wide Association study (SAGE GWAS) (Bierut et al., 2010). First, we examined relationships between TACR1 genotypes and neural responses during a craving task in 326 individuals with alcohol use disorders. Next, correlational analyses between 69 TACR1 SNPs and DSM-IV-TR AD symptoms were performed on the SAGE data set. rs3771863, rs3755459, and rs1106855 predicted BOLD activation in response to alcohol cues in those same reward and reinforcement brain areas, especially in the medial prefrontal cortex, striatum, and insula. rs3771863 also predicted AD symptom count in the SAGE data set and BOLD activation in the mesocorticolimbic pathway response to alcohol cues. Each of the 5 SNPs in the TACR1 gene that was significantly related to AD severity in the SAGE data set and/or the BOLD response to the craving task is near the 3' or 5' areas of the gene and may therefore be near mutations with potential functional significance. In particular, the potential functional significance of rs1106855 should be explored because of its location within a stop codon.

Accuracy assessment of global historical cropland datasets based on regional reconstructed historical data—A case study in Northeast China

Historical cropland datasets are fundamental for quantifying the effects of human land use activities on climatic change and the carbon cycle. Two representative global land-use datasets, the Global Land Use Database (termed SAGE dataset) and the Historical Database of the Global Environment (termed HYDE dataset) have been established and used widely. Despite improvement of data quality and methodologies for extracting historical land use information, certain dataset limitations exist that need to be quantified and communicated to users so that they can make informed decisions on whether and how these land-use products should be used. The Cropland data of Northeast China (CNEC) is based on calibrated historical data and a multi-sourced data conversion model, and reconstructs cropland cover change in Northeast China over the last 300 years. Using the CNEC as a reference, we evaluated the accuracy of cropland cover for SAGE and HYDE in Northeast China at spatial scales ranging from the entire Northeast China to provinces and even individual raster grid cells. Neither SAGE nor HYDE reflects real historical land reclamation. Cropland areas in SAGE are overestimated by 20.98 times in 1700 to 1.6 times in 1990. Although HYDE is better, there are significant disagreements in cropland area and distribution between HYDE and CNEC, especially in the 18th and 19th centuries. The proportion of total grid cells whose relative error was greater than 100% was 63.55% in 1700 and 53.27% in 1780. Global cropland dataset errors over Northeast China originate mainly from both the reverse calculation method for historical cropland data based on modern spatial patterns, and modern land-use outputs from satellite data.

TESTING MASS LOSS IN LARGE MAGELLANIC CLOUD CEPHEIDS USING INFRARED AND OPTICAL OBSERVATIONS. II. PREDICTIONS AND TESTS OF THE OGLE-III FUNDAMENTAL-MODE CEPHEIDS

In this article, we test the hypothesis that Cepheids have infrared excesses due to mass loss. We fit a model using the mass-loss rate and the stellar radius as free parameters to optical observations from the OGLE-III survey and infrared observations from the 2MASS and SAGE data sets. The sample of Cepheids have predicted minimum mass-loss rates ranging from zero to $10^{-8}M_\odot$ $yr^{-1}$, where the rates depend on the chosen dust properties. We use the predicted radii to compute the Period-Radius relation for LMC Cepheids, and to estimate the uncertainty caused by the presence of infrared excess for determining angular diameters with the infrared surface brightness technique. Finally, we calculate the linear and non-linear Period-Luminosity (P-L) relations for the LMC Cepheids at VIJHK + IRAC wavelengths and we find that the P-L relations are consistent with being non-linear at infrared wavelengths, contrary to previous results.

A comprehensive in silico expression analysis of RNA binding proteins in normal and tumor tissue; identification of potential players in tumor formation

RNA binding proteins (RBPs) are involved in several post-transcriptional stages of gene expression and dictate the quality and quantity of the cellular proteome. When aberrantly expressed, they can lead to disease states as well as cancers. A basic requirement to understand their role in normal tissue development and cancer is the build of comprehensive gene expression maps. In this direction, we generated a list with 383 human RBPs based on the NCBI and EMSEMBL databases. SAGE and MPSS were then used to verify their levels of expression in normal tissues while SAGE and microarray datasets were used to perform comparisons between normal and tumor tissues. As main outcomes of our studies, we identified clusters of co-expressed or co-regulated genes that could act together in the development and maintenance of specific tissues; we also obtained a high confidence list of RBPs aberrantly expressed in several tumor types. This later list contains potential candidates to be explored as diagnostic and prognostic markers as well as putative targets for cancer therapy approaches.

PERIOD-LUMINOSITY RELATIONS DERIVED FROM THE OGLE-III FUNDAMENTAL MODE CEPHEIDS

In this paper, we have derived Cepheid period–luminosity (P–L) relations for the Large Magellanic Cloud (LMC) fundamental mode Cepheids, based on the data released from OGLE-III. We have applied an extinction map to correct for the extinction of these Cepheids. In addition to the VIW-band P–L relations, we also include JHK and four Spitzer IRAC-band P–L relations, derived by matching the OGLE-III Cepheids to the Two Micron All Sky Survey and SAGE data sets, respectively. We also test the nonlinearity of the Cepheid P–L relations based on extinction-corrected data. Our results (again) show that the LMC P–L relations are nonlinear in VIJH bands and linear in KW and the four IRAC bands, respectively.

Differential gene expression in normal esophagus and Barrett’s esophagus

AACR Annual Meeting-- Apr 12-16, 2008; San Diego, CA 3137 As the premalignant lesion of esophageal adenocarcinoma (EAC), Barrett’s esophagus (BE) is characterized by intestinal metaplasia in the normal esophagus (NE). In order to explore potential molecular mechanism of human BE, we analyzed three microarray datasets (two cDNA arrays and one oligo array) and one SAGE dataset with bioinformatics tools. SAM and SAGE(Poisson) were used to identify differentially expressed individual genes. GSEA was used to identify a priori defined sets of genes differentially expressed. These gene sets are either grouped according to certain signaling pathway (GSEA curated), or the presence of consensus binding sequences of known transcription factors (GSEA motif). Both SAM and SAGE(Poisson) identified 68 differentially expressed genes (55 BE genes and 13 NE genes) with a cutoff ratio (>4 fold). With immunohistochemical staining (IHC) on pairs of NE and BE tissues from 6 patients, these genes were grouped into 4 categories: Category I (25 genes only expressed in BE), Category II (5 genes only expressed in NE), Category III (11 genes expressed more in BE than in NE), and Category IV (2 genes expressed more in NE than in BE). Differential expression of the remaining genes was not confirmed by IHC either due to false pickup by microarray and SAGE, or lack of proper antibodies. Further analysis of the genes of Category I and Category II showed that, (1) these genes perfectly clustered NE from BE samples separately; (2) expression patterns of these genes in BE were similar to those in stomach, small intestine, colon and lung, suggesting that BE may be a multi-directional differentiation type of epithelium; (3) 14 genes of Category I and 8 of Category III were down-regulated in EAC, suggesting that dedifferentiation took place during carcinogenesis. TGFβ pathway and several transcription factors (Cdx2, HNF1, HNF4) were activated in BE as determined by GSEA motif analysis. Consistent with ectopic expression of Cdx2 in BE, with IHC 12 known Cdx2 target genes were also found to be expressed only in BE, and 10 known Cdx2 target genes were expressed more in BE than in NE. Four genes (Fabp1, Heph, Lyz, Tff3) belong to Category I and 2 genes (Agr2, Cdh17) Category III. Our data strongly support an important role of Cdx2 in the development of BE.

Defining the gene expression signature of rhabdomyosarcoma by meta-analysis

BackgroundRhabdomyosarcoma is a highly malignant soft tissue sarcoma in childhood and arises as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of RMS gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets have opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated.ResultsIn this work we performed a meta-analysis on four microarray and two SAGE datasets of gene expression data on RMS in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Regulatory pathways and biological processes significantly enriched has been investigated and a list of differentially meta-profiles have been identified as possible candidate of aggressiveness of RMS.ConclusionOur results point to a general down regulation of the energy production pathways, suggesting a hypoxic physiology for RMS cells. This result agrees with the high malignancy of RMS and with its resistance to most of the therapeutic treatments. In this context, different isoforms of the ANT gene have been consistently identified for the first time as differentially expressed in RMS. This gene is involved in anti-apoptotic processes when cells grow in low oxygen conditions. These new insights in the biological processes responsible of RMS growth and development demonstrate the effective advantage of the use of integrated analysis of gene expression studies.

Mass exchange between stratosphere and trotosphere over the Tibetan Plateau and its surroundings

Using NCEP dataset we calculate the exchange of mass across the thermal tropopause by the Wei’s method from 1978 to 1997 over the Tibetan Plateau and its surroundings. We also calculate the annual variation of aerosol and ozone of 100 hPa level with the monthly SAGE dataset from July 1988 to December 1993. Results indicate that (i) the mass from troposphere to stratosphere is magistral station in summer over the Tibetan Plateau and its surroundings. The air transport reaches the summit in midsummer with two large value centers, which lie in the north of Bengal Bay and southeastern Tibetan Plateau, respectively. A large value center, which lies over the Tibetan Plateau, is smaller than that aforementioned. In winter, the mass transport is from stratosphere to troposphere, and reaches the minimum in January. (ii) As far as the 19-year mean cross-tropopause mass exchange from June to September is concerned, the net mass transport is 14.84×1018 kg from troposphere to stratosphere. So the area from the Tibetan Plateau to the Bengal Bay is a channel through which the mass of lower atmosphere layer gets into upper troposphere and lower stratosphere. (iii) The cross-tropopause mass may take the lower level aerosol to the tropopause. Then, the concentration of aerosol near the tropopause becomes larger, which may cause the content of ozone to reduce.