112 research outputs found
Impact of dietary protein on lipid metabolism-related gene expression in porcine adipose tissue
<p>Abstract</p> <p>Background</p> <p>High dietary protein can reduce fat deposition in animal subcutaneous adipose tissue, but little is known about the mechanism.</p> <p>Methods</p> <p>Sixty Wujin pigs of about 15 kg weight were fed either high protein (HP: 18%) or low protein (LP: 14%) diets, and slaughtered at body weights of 30, 60 or 100 kg. Bloods were collected to measure serum parameters. Subcutaneous adipose tissues were sampled for determination of adipocyte size, protein content, lipid metabolism-related gene expression, and enzyme activities.</p> <p>Results</p> <p>HP significantly reduced adipocyte size, fat meat percentage and backfat thickness, but significantly increased daily gain, lean meat percentage and loin eye area at 60 and 100 kg. Serum free fatty acid and triglyceride concentrations in the HP group were significantly higher than in the LP group. Serum glucose and insulin concentrations were not significantly affected by dietary protein at any body weight. HP significantly reduced gene expression of acetyl CoA carboxylase (ACC), fatty acid synthase (FAS) and sterol regulatory element binding protein 1c (SREBP-1c) at 60 kg and 100 kg; however, the mRNA level and enzyme activity of FAS were increased at 30 kg. HP promoted gene and protein expression and enzyme activities of lipoprotein lipase (LPL), carmitine palmtoyltransferase-1B (CPT-1B), peroxisome proliferator-activated receptor <it>γ </it>(PPAR<it>γ</it>) and adipocyte-fatty acid binding proteins (A-FABP) at 60 kg, but reduced their expression at 100 kg.</p> <p>Gene expression and enzyme activity of hormone sensitive lipase (HSL) was reduced markedly at 60 kg but increased at 100 kg by the high dietary protein. Levels of mRNA, enzyme activities and protein expression of ACC, FAS, SREBP-1c and PPAR<it>γ </it>in both LP and HP groups increased with increasing body weight. However, gene and protein expression levels/enzyme activities of LPL, CPT-1B, A-FABP and HSL in both groups were higher at 60 kg than at 30 and 100 kg.</p> <p>Conclusion</p> <p>Fat deposition in Wujin pigs fed high dietary protein for 25 weeks was reduced mainly by depression of lipogenic gene expression. The mechanism of lipid transport, lipolysis and oxidation in adipose tissue regulated by dietary protein appeared to be different at 60 kg and 100 kg body weights.</p
Light absorption enhancement of black carbon in urban Beijing in summer
The light absorption enhancement (E-abs) of black carbon (BC) caused by non-BC materials is an important source of uncertainty in radiative forcing estimate, yet remains poorly understood in relatively polluted environment such as the megacity Beijing. Here BC absorption enhancement at 630 nm was in-situ measured using a ther-modenuder coupled with a soot particle aerosol mass spectrometer and a single scattering albedo monitor in Beijing in summer. The project average (+/- 1 sigma) E-abs was 1.59 ( +/- 0.26), suggesting a significant amplification of BC absorption due to coating materials. E-abs presented a clear daytime increase due to enhanced photochemical processing, and a strong dependence on the mass ratios of non-BC coatings to BC (R-BC). Our results showed that the increase in E(abs )as a function of R-BC was mainly caused by the increased contributions of secondary aerosol. Further analysis showed that the BC absorption enhancement in summer in Beijing was mainly associated with secondary formation of nitrate, sulfate and highly oxidized secondary organic aerosol (SOA), while the formation of freshly and less oxidized SOA appeared not to play an important role.Peer reviewe
A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning
IntroductionThe coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians.MethodsThree COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity.ResultsPatients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively.ConclusionOverall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics
Analysis of the role of BrRPP1 gene in Chinese cabbage infected by Plasmodiophora brassicae
IntroductionThe clubroot disease caused by Plasmodiophora brassicae (P. brassicae) poses a serious threat to the economic value of cruciferous crops, which is a serious problem to be solved worldwide. Some resistance genes to clubroot disease in Brassica rapa L. ssp pekinensis cause by P. brassicae have been located on different chromosomes. Among them, Rcr1 and Rcr2 were mapped to the common candidate gene Bra019410, but its resistance mechanism is not clear yet.MethodsIn this experiment, the differences of BrRPP1 between the resistant and susceptible material of Chinese cabbage were analyzed by gene cloning and qRT-PCR. The gene function was verified by Arabidopsis homologous mutants. The expression site of BrRPP1 gene in cells was analyzed by subcellular localization. Finally, the candidate interaction protein of BrRPP1 was screened by yeast two-hybrid library.ResultsThe results showed that the cDNA sequence, upstream promoter sequence and expression level of BrRPP1 were quite different between the resistant and susceptible material. The resistance investigation found that the Arabidopsis mutant rpp1 was more susceptible to clubroot disease than the wild type, which suggested that the deletion of rpp1 reduces resistance of plant to clubroot disease. Subcellular location analysis confirmed that BrRPP1 was located in the nucleus. The interaction proteins of BrRPP1 screened from cDNA Yeast Library by yeast two-hybrid are mainly related to photosynthesis, cell wall modification, jasmonic acid signal transduction and programmed cell death.DiscussionBrRPP1 gene contains TIR-NBS-LRR domain and belongs to R gene. The cDNA and promoter sequence of BrRPP1 in resistant varieties was different from that in susceptible varieties led to the significant difference of the gene expression of BrRPP1 between the resistant varieties and the susceptible varieties. The high expression of BrRPP1 gene in resistant varieties enhanced the resistance of Chinese cabbage to P. brassicae, and the interaction proteins of BrRPP1 are mainly related to photosynthesis, cell wall modification, jasmonic acid signal transduction and programmed cell death. These results provide important clues for understanding the mechanism of BrRPP1 in the resistance of B. rapa to P. brassicae
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An unexpected catalyst dominates formation and radiative forcing of regional haze
Although regional haze adversely affects human health and possibly counteracts global warming from increasing levels of greenhouse gases, the formation and radiative forcing of regional haze on climate remain uncertain. By combining field measurements, laboratory experiments, and model simulations, we show a remarkable role of black carbon (BC) particles in driving the formation and trend of regional haze. Our analysis of long-term measurements in China indicates declined frequency of heavy haze events along with significantly reduced SO₂, but negligibly alleviated haze severity. Also, no improving trend exists for moderate haze events. Our complementary laboratory experiments demonstrate that SO₂ oxidation is efficiently catalyzed on BC particles in the presence of NO₂ and NH₃, even at low SO₂ and intermediate relative humidity levels. Inclusion of the BC reaction accounts for about 90–100% and 30–50% of the sulfate production during moderate and heavy haze events, respectively. Calculations using a radiative transfer model and accounting for the sulfate formation on BC yield an invariant radiative forcing of nearly zero W m⁻² on the top of the atmosphere throughout haze development, indicating small net climatic cooling/warming but large surface cooling, atmospheric heating, and air stagnation. This BC catalytic chemistry facilitates haze development and explains the observed trends of regional haze in China. Our results imply that reduction of SO₂ alone is insufficient in mitigating haze occurrence and highlight the necessity of accurate representation of the BC chemical and radiative properties in predicting the formation and assessing the impacts of regional haze
Modeling biogenic and anthropogenic secondary organic aerosol in China
A revised Community Multi-scale Air Quality (CMAQ) model with updated
secondary organic aerosol (SOA) yields and a more detailed description of SOA
formation from isoprene oxidation was applied to study the spatial and
temporal distribution of SOA in China in the entire year of 2013. Predicted
organic carbon (OC), elemental carbon and volatile organic compounds agreed
favorably with observations at several urban areas, although the high OC
concentrations in wintertime in Beijing were under-predicted. Predicted
summer SOA was generally higher (10–15 µg m<sup>−3</sup>) due to large
contributions of isoprene (country average, 61 %), although the relative
importance varies in different regions. Winter SOA was slightly lower and was
mostly due to emissions of alkane and aromatic compounds (51 %).
Contributions of monoterpene SOA was relatively constant (8–10 %).
Overall, biogenic SOA accounted for approximately 75 % of total SOA in
summer, 50–60 % in autumn and spring, and 24 % in winter. The
Sichuan Basin had the highest predicted SOA concentrations in the country in
all seasons, with hourly concentrations up to 50 µg m<sup>−3</sup>.
Approximately half of the SOA in all seasons was due to the traditional
equilibrium partitioning of semivolatile components followed by
oligomerization, while the remaining SOA was mainly due to reactive surface
uptake of isoprene epoxide (5–14 %), glyoxal (14–25 %) and
methylglyoxal (23–28 %). Sensitivity analyses showed that formation of
SOA from biogenic emissions was significantly enhanced due to anthropogenic
emissions. Removing all anthropogenic emissions while keeping the biogenic
emissions unchanged led to total SOA concentrations of less than
1 µg m<sup>−3</sup>, which suggests that manmade emissions facilitated
biogenic SOA formation and controlling anthropogenic emissions would result
in reduction of both anthropogenic and biogenic SOA
C1-C2 alkyl aminiums in urban aerosols: Insights from ambient and fuel combustion emission measurements in the Yangtze River Delta region of China
We measured low molar-mass alkyl aminiums (methylaminium, dimethylaminium, ethylaminium and diethylaminium) in urban aerosols in the Yangtze River Delta region of eastern China in August 2014 and from November 2015 to May 2016. After examining artifact formation on sample filters, methylaminium, dimethylaminium and ethylaminium concentrations were quantified. The three C1-C2 aminiums exhibited a unimodal size distribution that maximized between 0.56 and 1.0 μm. Their concentrations in PM2.5 were 5.7 ± 3.2 ng m−3, 7.9 ± 5.4 ng m−3 and 20.3 ± 16.6 ng m−3, respectively, with higher concentrations during the daytime and in warm seasons. On new particle growth days, amine uptake to particles larger than 56 nm was barely enhanced. The molar ratios of individual aminium/NH4+ in PM2.5 were on the order of 10−4 and 10−3. Aminiums were thus far less to out-compete ammonium (NH4+) in neutralizing acidic species in particle sizes down to 56 nm. Abundant nitrate (NO3−/SO42− molar ratio = ∼3) and its correlation to methylaminium and ethylaminium implied that nitrate might be more important aminium salt than sulfate in urban aerosols of this area. Direct measurement of particle-phase amine emission from coal and biomass burning showed that coal burning is an important atmospheric amine source, considering coal burning is top-ranked particulate matter source in China
Characterisation of black carbon (BC) mixing state and flux in Beijing using single particle measurements
BC is generated by the incomplete combustion of carbonaceous fuels and it is an important component of fine
PM2:5. In the atmosphere BC particles have a complex structure and its mixing state has crucial impact on optical
properties. Quantifying the sources and emissions of black carbon in urban environments is important and presently
uncertain, particularly in megacities undergoing rapid growth and change in emissions. During the winter of 2016
(10th Nov-10th Dec) the BC was characterised as part of a large joint UK-China field experiment in Beijing.
This paper focuses on understanding the mixing state of BC as well as identification and quantification of BC
sources. We used a combination of a Centrifugal Particle Mass Analyser (CPMA) and a Single Particle Soot
Photometer (SP2) to uniquely quantify the morphology independent mass of single refractory BC particles and their
coating content. The CPMA allows us to select pre-charged aerosol particles according to their mass to charge ratio
and the SP2 provides information on the mass of refractory BC through a laser-induced incandescence method.
Furthermore, another SP2 was used to measure the BC flux at 100m height using the Eddy Covariance method.
We have successfully gathered 4 weeks of continuous measurements which include several severe pollution events
in Beijing. Here we present preliminary results, characterising the distribution of coating mass on BC particles in
Beijing and linking this to the main sources of BC in the city. We will provide initial estimates of the BC flux
over a several kilometre footprint. Such analysis will provide important information for the further investigation of
source distribution, emission, lifetime and optical properties of BC under complex environments in Beijing
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