Tissue-specific transcriptome analysis reveals candidate genes for terpenoid and phenylpropanoid metabolism in the medicinal plant ferula assafoetida

© 2019 ABRF. Methionine oxidation plays a critical role in many processes of biologic and biomedical importance, including cellular redox responses and stability of protein pharmaceuticals. Bottom-up methods for analysis of methionine oxidation can suffer from incomplete sequence coverage, as well as an inability to readily detect correlated oxidation between 2 or more methionines. However, the methodology for quantifying protein oxidation in top-down analyses is lacking. Previous work has shown that electron transfer dissociation (ETD)–based tandem mass spectrometry (MS/MS) fragmentation offers accurate and precise quantification of amino acid oxidation in peptides, even in complex samples. However, the ability of ETD-based MS/MS fragmentation to accurately quantify amino acid oxidation of proteins in a top-down manner has not been reported. Using apomyoglobin and calmodulin as model proteins, we partially converted methionines into methionine sulfoxide by incubation in H2O2. Using top-down ETD-based fragmentation, we quantified the amount of oxidation of various ETD product ions and compared the quantified values with those from traditional bottom-up analysis. We find that overall quantification of methionine oxidation by top-down MS/MS ranges from good agreement with traditional bottom-up methods to vast differences between the 2 techniques, including missing oxidized product ions and large differences in measured oxidation quantities. Care must be taken in transitioning ETD-based quantitation of oxidation from the peptide level to the intact protein level

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

An Efficient Detection Technique for Synchronous CDMA Communication Systems Based on the Expectation Maximization Algorithm

Journal PaperMaximum likelihood detection of superimposed signals in code-division multiple access (CDMA) communication systems has a computational complexity that is exponential in the number of users, and its implementation is practically prohibitive even for a moderate number of users. Applying the expectation maximization algorithm to this problem, we decompose the multiuser detection problem into a series of single-user problems, and thus present an iterative computationally efficient algorithm for detection of superimposed signals in synchronous direct-sequence CDMA communication systems. The resulting structure includes the well-known multistage detector as one of its special cases. With a proper choice of its parameters, the new detector can achieve the advantages of both the multistage and conventional detector and have good performance for both strong and weak users

Evaluation of biochemical, physiological traits and percentage of essential oil of sickleweed (Falcaria vulgaris) population in different geographical and climatic regions

Sickleweed (Falcaria vulgaris) is the name of a species of annual, and perennial herbaceous plants of the genus Falcaria. Climate change could negatively influnces the performance of various plant species in plant kingdom. In this study, 15 different sickleweed populations from seven provinces of the country were collected based on an unbalanced nest design with 10 replications and the percentage of essential oil, types of chlorophyll, phenol, proline, protein, and carotenoids were measured on them. The results showed that there was a significant difference between populations at the level of one percent for the studied traits. The results of the mean comparison showed that populations Ard-Shaban and Qaz-Ilan in terms of the evaluated traits and especially the percentage of essential oil were at the upper of the studied samples and selected as suitable populations. In addition, populations Gilan-Deylaman and Kur-Gerger-e Sofla were also identified as superior populations in terms of studied traits by cluster analysis and principle component analysis (PCA). Since the high level of proline and biochemical and physiological traits in plants can play a role in plants’ tolerance to stresses, therefore, populations with high values of these traits can be used in stress tolerance breeding programs. Therefore, in this study, populations Gilan-Deylaman and Kur-Gerger-e Sofla can be suitable populations for this purpose. In addition, the essential oil of this plant is used in the treatment of diseases, and therefore populations Ard-Shaban and Qaz-Ilan, which showed a high percentage of essential oil, can be used in breeding programs to increase the performance of this trait

Comparative study of adsorptive role of carbonaceous materials in removal of UV-active impurities of paclitaxel extracts

Graphite oxide (GO) and reduced graphene oxide (rGO) nanosheets were synthesized with a low-cost manufacturing method. The morphology and structures of the synthesized samples were studied using X-ray diffraction (XRD), atomic force microscopy (AFM), Fourier-transform infrared (FTIR) and Raman spectroscopy. The efficiencies of GO and rGO as novel candidate adsorbents in the pre-purification of paclitaxel were compared and contrasted with those of commercial graphite (Gt), graphene (G) and multi-wall carbon nanotube (MWCNT). According to UV–vis and HPLC analyses, rGO was evaluated as the best absorbent for the removal of impurities in pre-purification of paclitaxel from plant cell cultures. In contrast, the GO had the poorest proficiency for paclitaxel pre-purification in comparison with the other carbonaceous adsorbents. This is attributed to the existence of many localized defects in the π-structure of GO that is related to weakness of π–π stacking interactions between crude extract impurities and GO

The mean comparison of physiological and biochemical studied traits for sickleweed populations using Duncan’s method.

The mean comparison of physiological and biochemical studied traits for sickleweed populations using Duncan’s method.</p

Estimation of the variance components of the sources of variation in the unbalanced nest design of the studied physiological and biochemical traits.

Estimation of the variance components of the sources of variation in the unbalanced nest design of the studied physiological and biochemical traits.</p

Characteristics of the collection areas of Sickleweed plant samples.

Characteristics of the collection areas of Sickleweed plant samples.</p

Unbalanced nest variance analysis of physiological and biochemical traits in sickleweed populations.

Unbalanced nest variance analysis of physiological and biochemical traits in sickleweed populations.</p