Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

We developed a quality assurance (QA) tool, namely microarray outlier filter (MOF), and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR) dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Gene Expression Profiling of Bone Marrow Stromal Cells from Juvenile, Adult, Aged and Osteoporotic Rats: With an Emphasis on Osteoporosis

PURPOSE: Osteoporosis is a multi-factorial, age-related disease with a complex etiology and mode of regulation involving a large numbers of genes. To better understand the possible relationships among genes, we fingerprinted genes in a rat model induced by ovariectomy to determine differences among osteoporotic, non-osteoporotic, aged and juvenile rats. METHODS: We applied genome wide cDNA microarray technology to analyze genes expressed in bone marrow mesenchymal stromal cells (BMSC) and compared non-osteoporotic adult vs osteoporotic, non-osteoporotic adult vs aged, and non-osteoporotic adult vs juvenile. Rigorous statistical analysis of functional annotation (EASE program) identified over-represented biological and molecular functions with significant group wide changes (p≤0.05). Some of the expressed genes were further confirmed by quantitative RT-PCR (reverse transcription-polymerase chain reaction) RESULTS: Differences in gene expression were observed by identifying transcripts selected by t-test that were consistently changed by a minimum of two-fold. There were 195 transcripts that showed an increased expression and 109 transcripts that showed decreased expression relative to the osteoporotic condition. Of these, 75% transcripts were unknown gene products or ESTs (expressed sequence tag). A number of genes found in the aged and juvenile groups were not present in the osteoporotic rats. Functional clustering of the genes using the EASE bioinformatics program revealed that transcripts in osteoporosis were associated with signal transduction, lipid metabolism, protein metabolism, ionic and protein transport, neuropeptide and G-protein signaling pathways. Although some of the genes have previously been shown to play a key role in osteoporosis, several genes were uniquely identified in this study and likely play a role in developing aged related osteoporosis that could have compelling implications in the development of new diagnostic strategies and therapeutics for osteoporosis. CONCLUSIONS: These data suggest that osteoporosis is associated with changes of multiple novel gene expression and that numerous pathways could play important roles in osteoporosis pathogenesis

Genetic control of adenylate kinase and fructokinase in hexaploid wheat and other Triticeae species

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references.Not availabl

Relationship between Hyperuricemia and Lipid Profiles in US Adults

Background. Although the link between hyperuricemia and metabolic syndrome had been recognized, the association of the dyslipidemia among individuals with hyperuricemia remains not comprehensively assessed. Methods. Using NHANES III study, we examined the relation between serum lipid profiles and different serum uric acid levels, including serum total cholesterol, LDL cholesterol, triglycerides, HDL cholesterol, apolipoprotein-B, lipoprotein (a), apolipoprotein AI, ratio of triglycerides to HDL cholesterol, and ratio of apolipoprotein-B to AI. Results. After adjusting for potential confounders, average differences (95% confidence interval) comparing the top to the bottom (reference) serum uric acid were 0.29 (0.19, 0.39) mmol/L for total cholesterol, 0.33 (0.26, 0.41) mmol/L for triglycerides, 0.14 (0.01, 0.27) mmol/L for LDL cholesterol, −0.08 (−0.11, −0.05) mmol/L for HDL, and 0.09 (0.05, 0.12) g/L for serum apolipoprotein-B. Notably, ratios of triglycerides to HDL cholesterol and apolipoprotein-B to AI were also linearly associated with uric acid levels (P for trend < 0.001). Conclusions. This study suggested that serum LDL cholesterol, triglycerides, total cholesterol, apolipoprotein-B levels, ratio of triglycerides to HDL cholesterol, and ratio of apolipoprotein-B to AI are strongly associated with serum uric acid levels, whereas serum HDL cholesterol levels are significantly inversely associated. In the clinical practice, the more comprehensive strategic management to deal with dyslipidemia and hyperuricemia deserves further investigation

Anti-inflammatory effects of Cynanchum taiwanianum rhizome aqueous extract in IL-1 beta beta-induced NRK-52E cells

Objective: In the present study, we investigated the anti-inflammatory effect of C. taiwanianum T. Yamaza rhizome aqueous extract (CTAE). Materials and methods: The present study investigated the anti-inflammatory effect of CTAE using IL-1 beta beta-induced NRK-52E cells. Production of NO and PGE(2) by ELISA, the mRNA and protein expression of iNOS and COX-2, phosphorylation of I kappa kappa B alpha alpha, and activation of NF-kappa kappa B by RT-PCR and western blotting were determined

Damaging Effect of Hot Metal Atoms on Organic Semiconducting Films during Top Contact Formation

The formation of a high quality interface between metallic and organic semiconducting thin films is critically important in achieving high-performance organic electronics devices. In this regard, the importance of understanding the multifaceted issue of structure damage incurred to organic films by the evaporated metal atoms cannot be overstated. In the present study, we have investigated the change of a structurally ordered, organic semiconducting (o.s.) thin film of 5,11-bis­(triethylsilylethynyl)­anthradithiophene (TESADT) effected by gold atoms by means of synchrotron-based soft X-ray spectroscopies including ultraviolet photoemission spectroscopy (UPS) and X-ray photoemission spectroscopies (XPS) with imaging capability, near edge X-ray absorption fine structure (NEXAFS) spectroscopy, and atomic force microscopy (AFM). This work shows that gold atoms readily diffuse into the organic films and nucleate into nanometer-size clusters, damage chemical structure, destroy structural ordering of the organic films, and shift relevant core level binding energy in accord with the expected interfacial band bending. Additionally, the patterned deposition performed via shadow mask is not reliable in confining Au deposit to the designated region due to the rapid diffusion of Au atoms. As a result, the real Au contacts should be treated as morphologically complicated gold films residing on top of structurally disordered organic film interspersed with Au clusters