Chemical characterization of hydrocarbons and transcriptome profiling to elucidate pathway(s) of hydrocarbon biosynthesis in maize, pea, Botryococcus braunii and Emiliania huxleyi

The goal of my research is to provide metabolic profiling and transcriptome profiling data from which the hydrocarbon biosynthesis pathway can be dissected via the isolation and characterization of genes involved in hydrocarbon biosynthesis in four organisms. Conditions for the hyper- and hypo-accumulation of hydrocarbons in four organisms were established. The physiological conditions that induce the hyper- and hypo-accumulation of hydrocarbons conditions were used to simultaneously collect RNA for transcriptome sequencing analysis. Simultaneously, the hydrocarbons were analyzed in the four biological systems, specifically to identify the positions of double bonds in alkenes, which provide biochemical evidence about how hydrocarbons are biosynthesized. The comparative transcriptome profiling of cells that hyper- and hypo-accumulate hydrocarbon in all four biological systems is being used to identify genes that are differentially expressed between these two conditions. My research has finished the entire pipeline for maize. Maize silk with differential hydrocarbon accumulation at different developmental stages were utilized and transcriptomes of these silks for candidate genes involved in hydrocarbon biosynthesis were mined. This comparative transcriptome profiling approach is also being applied to pea epidermis, and the two algae, B. braunii and E. huxleyi. These accomplishments have set the stage for comparative transcriptome profiling to identify candidate genes involved in the hydrocarbon biosynthetic pathway(s) in these four biological systems. In addition, sequence similarity networks can be built from these four biological systems by pairwise blast. The within system networks can then be clustered to identify highly inter-connected modules using the Markov Chain Clustering method. Then, modules without any genes increasing their expression in the direction of hydrocarbon accumulation and genes without increasing expression in the direction of hydrocarbon accumulation will be filtered out. By this cross-system analysis, the candidate genes involved in hydrocarbon biosynthetic pathway(s) shared by maize silk, pea epidermis, B. braunii and E. huxleyi can be discovered. In addition, the systems that have been set up and characterized in this body of work can also be used to identify the hydrocarbon biosynthetic pathways specific to each of the individual biological systems. Addressing these research goals will add to the current understanding of how hydrocarbons are biosynthesized in different biological systems. This fundamental understanding has the potential of impacting the development alternative advanced biofuels that can be used in place of petroleum-sourced fuels. It is widely recognized that the current use of fossil-carbon as an energy source is unsustainable because of depleting supplies and the accumulation of carbon dioxide in the environment. Because biologically-sourced hydrocarbons have chemical structures that are nearly identical to petroleum, they ultimately could have an application in the development of advanced biofuels

Combination of Dendrobium Mixture and Metformin Curbs the Development and Progression of Diabetic Cardiomyopathy by Targeting the lncRNA NEAT1

OBJECTIVES: This study aimed to explore the efficacy of combination treatment with dendrobium mixture and metformin (Met) in diabetic cardiomyopathy (DCM) and its effects on NEAT1 and the Nrf2 signaling pathway. METHODS: H9c2 cells were maintained in medium supplemented with either low (5.5 mmol/L) or high (50 mmol/L) glucose. Male Sprague-Dawley rats were fed a high-glucose diet and administered a single, low dose of streptozotocin (35 mg/kg) via intraperitoneal injection to induce the development of DM. After induction of DM, the rats were treated with dendrobium mixture (10 g/kg) and Met (0.18 g/kg) daily for 4 weeks. Next, quantitative reverse transcription (qRT)-PCR and western blotting were performed to evaluate the expression levels of target genes and proteins. Flow cytometry was performed to assess apoptosis, and hematoxylin and eosin staining was performed to evaluate the morphological changes in rat cardiac tissue. RESULTS: In patients with diabetes mellitus (DM) and myocardial cells and heart tissues from rats with high glucose-induced DM, NEAT1 was downregulated, and the expression levels of Nrf2 were decreased (p<0.01, p<0.001). The combination of dendrobium mixture and Met upregulated the expression of NEAT1 which upregulated Nrf2 by targeting miR-23a-3p, resulting in reduced apoptosis and improved cardiac tissue morphology (p<0.01, p<0.001). CONCLUSION: Dendrobium mixture and Met upregulated the expression of NEAT1 in DCM, thereby inhibiting apoptosis of myocardial cells

Quantum Algorithm for Unsupervised Anomaly Detection

Anomaly detection, an important branch of machine learning, plays a critical role in fraud detection, health care, intrusion detection, military surveillance, etc. As one of the most commonly used unsupervised anomaly detection algorithms, the Local Outlier Factor algorithm (LOF algorithm) has been extensively studied. This algorithm contains three steps, i.e., determining the k-distance neighborhood for each data point x, computing the local reachability density of x, and calculating the local outlier factor of x to judge whether x is abnormal. The LOF algorithm is computationally expensive when processing big data sets. Here we present a quantum LOF algorithm consisting of three parts corresponding to the classical algorithm. Specifically, the k-distance neighborhood of x is determined by amplitude estimation and minimum search; the local reachability density of each data point is calculated in parallel based on the quantum multiply-adder; the local outlier factor of each data point is obtained in parallel using amplitude estimation. It is shown that our quantum algorithm achieves exponential speedup on the dimension of the data points and polynomial speedup on the number of data points compared to its classical counterpart. This work demonstrates the advantage of quantum computing in unsupervised anomaly detection

Genetic and environmental variation impact the cuticular hydrocarbon metabolome on the stigmatic surfaces of maize

Background: Simple non-isoprenoid hydrocarbons accumulate in discrete regions of the biosphere, including within bacteria and algae as a carbon and/or energy store, and the cuticles of plants and insects, where they may protect against environmental stresses. The extracellular cuticular surfaces of the stigmatic silks of maize are rich in linear hydrocarbons and therefore provide a convenient system to study the biological origins and functions of these unique metabolites. Results: To test the hypotheses that genetics and environment influence the accumulation of surface hydrocarbons on silks and to examine the breadth of metabolome compositions across diverse germplasm, cuticular hydrocarbons were analyzed on husk-encased silks and silks that emerged from the husk leaves from 32 genetically diverse maize inbred lines, most of which are commonly utilized in genetics experiments. Total hydrocarbon accumulation varied ~ 10-fold among inbred lines, and up to 5-fold between emerged and husk-encased silks. Alkenes accounted for 5-60% of the total hydrocarbon metabolome, and the majority of alkenes were monoenes with a double bond at either the 7th or 9th carbon atom of the alkyl chain. Total hydrocarbon accumulation was impacted to similar degrees by genotype and husk encasement status, whereas genotype predominantly impacted alkene composition. Only minor differences in the metabolome were observed on silks that were emerged into the external environment for 3- versus 6-days. The environmental influence on the metabolome was further investigated by growing inbred lines in 2 years, one of which was warmer and wetter. Inbred lines grown in the drier year accumulated up to 2-fold more hydrocarbons and up to a 22% higher relative abundance of alkenes. In summary, the surface hydrocarbon metabolome of silks is primarily governed by genotype and husk encasement status, with smaller impacts of environment and genotype-by-environment interactions. Conclusions: This study reveals that the composition of the cuticular hydrocarbon metabolome on silks is affected significantly by genetic factors, and is therefore amenable to dissection using quantitative genetic approaches. Such studies will clarify the genetic mechanisms responsible for the accumulation of these metabolites, enabling detailed functional investigations of the diverse and complex protective roles of silk surface lipids against environmental stresses

AEROsol generic classification using a novel Satellite remote sensing Approach (AEROSA)

Numerous studies (hereafter GA: general approach studies) have been made to classify aerosols into desert dust (DD), biomass-burning (BB), clean continental (CC), and clean maritime (CM) types using only aerosol optical depth (AOD) and Ångström exponent (AE). However, AOD represents the amount of aerosol suspended in the atmospheric column while the AE is a qualitative indicator of the size distribution of the aerosol estimated using AOD measurements at different wavelengths. Therefore, these two parameters do not provide sufficient information to unambiguously classify aerosols into these four types. Evaluation of the performance of GA classification applied to AErosol Robotic NETwork (AERONET) data, at sites for situations with known aerosol types, provides many examples where the GA method does not provide correct results. For example, a thin layer of haze was classified as BB and DD outside the crop burning and dusty seasons respectively, a thick layer of haze was classified as BB, and aerosols from known crop residue burning events were classified as DD, CC, and CM by the GA method. The results also show that the classification varies with the season, for example, the same range of AOD and AE were observed during a dust event in the spring (20th March 2012) and a smog event in the autumn (2nd November 2017). The results suggest that only AOD and AE cannot precisely classify the exact nature (i.e., DD, BB, CC, and CM) of aerosol types without incorporating more optical and physical properties. An alternative approach, AEROsol generic classification using a novel Satellite remote sensing Approach (AEROSA), is proposed to provide aerosol amount and size information using AOD and AE, respectively, from the Terra-MODIS (MODerate resolution Imaging Spectroradiometer) Collection 6.1 Level 2 combined Dark Target and Deep Blue (DTB) product and AERONET Version 3 Level 2.0 data. Although AEROSA is also based on AOD and AE, it does not claim the nature of aerosol types, instead providing information on aerosol amount and size. The purpose is to introduce AEROSA for those researchers who are interested in the generic classification of aerosols based on AOD and AE, without claiming the exact aerosol types such as DD, BB, CC, and CM. AEROSA not only provides 9 generic aerosol classes for all observations but can also accommodate variations in location and season, which GA aerosol types do not.</jats:p

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Chemical characterization of hydrocarbons and transcriptome profiling to elucidate pathway(s) of hydrocarbon biosynthesis in maize, pea, Botryococcus braunii and Emiliania huxleyi

The goal of my research is to provide metabolic profiling and transcriptome profiling data from which the hydrocarbon biosynthesis pathway can be dissected via the isolation and characterization of genes involved in hydrocarbon biosynthesis in four organisms. Conditions for the hyper- and hypo-accumulation of hydrocarbons in four organisms were established. The physiological conditions that induce the hyper- and hypo-accumulation of hydrocarbons conditions were used to simultaneously collect RNA for transcriptome sequencing analysis. Simultaneously, the hydrocarbons were analyzed in the four biological systems, specifically to identify the positions of double bonds in alkenes, which provide biochemical evidence about how hydrocarbons are biosynthesized. The comparative transcriptome profiling of cells that hyper- and hypo-accumulate hydrocarbon in all four biological systems is being used to identify genes that are differentially expressed between these two conditions. My research has finished the entire pipeline for maize. Maize silk with differential hydrocarbon accumulation at different developmental stages were utilized and transcriptomes of these silks for candidate genes involved in hydrocarbon biosynthesis were mined. This comparative transcriptome profiling approach is also being applied to pea epidermis, and the two algae, B. braunii and E. huxleyi. These accomplishments have set the stage for comparative transcriptome profiling to identify candidate genes involved in the hydrocarbon biosynthetic pathway(s) in these four biological systems. In addition, sequence similarity networks can be built from these four biological systems by pairwise blast. The within system networks can then be clustered to identify highly inter-connected modules using the Markov Chain Clustering method. Then, modules without any genes increasing their expression in the direction of hydrocarbon accumulation and genes without increasing expression in the direction of hydrocarbon accumulation will be filtered out. By this cross-system analysis, the candidate genes involved in hydrocarbon biosynthetic pathway(s) shared by maize silk, pea epidermis, B. braunii and E. huxleyi can be discovered. In addition, the systems that have been set up and characterized in this body of work can also be used to identify the hydrocarbon biosynthetic pathways specific to each of the individual biological systems. Addressing these research goals will add to the current understanding of how hydrocarbons are biosynthesized in different biological systems. This fundamental understanding has the potential of impacting the development alternative advanced biofuels that can be used in place of petroleum-sourced fuels. It is widely recognized that the current use of fossil-carbon as an energy source is unsustainable because of depleting supplies and the accumulation of carbon dioxide in the environment. Because biologically-sourced hydrocarbons have chemical structures that are nearly identical to petroleum, they ultimately could have an application in the development of advanced biofuels.</p

Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980–2017

Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country&rsquo;s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. In this study, 38-years (1980&ndash;2017) of spatial and temporal variations of AOD in China were analyzed using AOD records derived from MODIS atmosphere products and the MERRA-2 dataset. The results showed that the annual mean AOD values throughout China have gone through an increasing, but fluctuating, trend, especially in 1982 and in 1992 due to two volcano eruptions; the AOD values experienced a dramatically increasing period during 2000&ndash;2007 with the rapid economic development and &ldquo;population explosions&rdquo; in China/after 2008, the AOD values gradually decreased from 0.297 (2008) to 0.257 (2017). The AOD values in China were generally higher in spring than that in other seasons. The Sichuan Basin has always been an area with high AOD values owing to the strong human activity and the basin topography (hindering aerosol diffusions in the air). In contrast, the Qinghai Tibet Plateau has always been an area with low AOD values due to low aerosol emissions and clear sky conditions there. The trend analysis of AOD values during 1980&ndash;2017 in China indicated that the significant increasing trend was mainly observed in Southeastern China. By contrast, the AOD values in the northernmost of China showed a significant decreasing trend. Then, the contributions (AODP) of the AOD for black carbon aerosol (BCAOD), dust aerosol (DUAOD), organic carbon aerosol (OCAOD), sea salt aerosol (SSAOD), and SO4 aerosol (SO4AOD) to the total AOD values were calculated. The results showed that DUAOD (25.43%) and SO4AOD (49.51%) were found to be the main driving factors for the spatial and temporal variations of AOD values. Finally, the effects of anthropogenic aerosol emissions, socioeconomic factors, and land-use and land coverage changes on AOD were analyzed. The GDP, population density, and passenger traffic volume were found to be the main socioeconomic drivers for AOD distributions. Relatively larger AOD values were mainly found in urban land and land covered by water, while lower AOD values were found in grassland and permanent glacier areas