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Several amino acids can stimulate milk synthesis in mammary epithelial cells (MECs), however, the regulatory role of isoleucine (Ile) and underlying molecular mechanism remain poorly understood. In this study, we aimed to evaluate the regulatory effects of Ile on milk protein and fat synthesis in MECs and reveal the mediation mechanism of Brahma-related gene 1 (BRG1) on this regulation. Ile dose-dependently affected milk protein and fat synthesis, mTOR phosphorylation, SREBP-1c expression and maturation, and BRG1 protein expression in bovine MECs. PI3K inhibition by LY294002 treatment blocked the stimulation of Ile on BRG1 expression. BRG1 knockdown and gene activation experiments showed that it mediated the stimulation of Ile on milk protein and fat synthesis, mTOR phosphorylation, and SREBP-1c expression and maturation in MECs. ChIP-PCR analysis detected that BRG1 bound to the promoters of mTOR and SREBP-1c, and ChIP-qPCR further detected that these binding were increased by Ile stimulation. In addition, BRG1 positively regulated the binding of H3K27ac to these two promoters, while it negatively affected the binding of H3K27me3 to these promoters. BRG1 knockdown blocked the stimulation of Ile on these two gene expression. The expression of BRG1 was higher in mouse mammary gland in the lactating period, compared with that in the puberty or dry period. Taken together, these experimental data reveal that Ile stimulates milk protein and fat synthesis in MECs via the PI3K-BRG1-mTOR/SREBP-1c pathway.
Many waterflooding oil fields, injecting water into an oil-bearing reservoir for pressure maintenance, are in their middle to late stages of development. To explore the geological conditions and improve oilfield recovery of the most important well group of the Hu 136 block, located on the border areas of three provinces (Henan, Shandong, and Hebei), Zhongyuan Oilfield, Sinopec, central China, a 14C cross-well tracer monitoring technology was developed and applied in monitoring the development status and recognize the heterogeneity of oil reservoirs. The tracer response in the production well was tracked, and the water drive speed, swept volume of the injection fluid were obtained. Finally, the reservoir heterogeneity characteristics, such as the dilution coefficient, porosity, permeability, and average pore-throat radius, were fitted according to the mathematical model of the heterogeneous multi-layer inter-well theory. The 14C-AMS technique developed in this work is expected to be a potential analytical method for evaluating underground reservoir characteristics and providing crucial scientific guidance for the mid to late oil field recovery process.
Estimation of the initial state of turbulent channel flow from spatially and temporally resolved wall data is performed using adjoint-variational data assimilation. The estimated flow fields satisfy the Navier–Stokes equations and minimize a cost function defined as the difference between model predictions and the available observations. The accuracy of the predicted flow deteriorates with distance from the wall, most precipitously across the buffer layer beyond which only large-scale structures are reconstructed. To explain this trend, we examine the domain of dependence of the observations and the Hessian matrix of the state-estimation cost function, both of which are efficiently evaluated using adjoint fields initiated from impulses at wall sensors. Eigenanalysis of the Hessian is performed, and the eigenvalues are related to the capacity to reconstruct flow structures represented by the eigenvectors. Most of the eigenmodes decay beyond the buffer layer, thus demonstrating weak sensitivity of wall observations to the turbulence in the bulk. However, when the measurement time $t_m^{+} \gtrsim 20$, some streamwise-elongated Hessian eigenfunctions remain finite in the outer flow, and correspond to the sensitivity of wall observations to outer large-scale motions. At much longer observation times, the adjoint field becomes chaotic as it amplifies exponentially, which is indicative of extreme gradients of the cost function and an ill-conditioned Hessian matrix, and both exacerbate the difficulty of estimating turbulence from wall observations.
It is generally accepted that high-oleic crops have at least 70% oleate. As compared to their normal-oleic counterparts, oil and food products made from high-oleic peanut have better keeping quality and are much healthier. Therefore, high-oleic peanut is well recognized by processors and consumers. However, owing to the limited availability of high-oleic donors, most present-day high-oleic peanut varietal releases merely have F435 type FAD2 mutations. Through screening of a mutagenized peanut population of 15L46, a high-yielding peanut line with desirable elliptical oblong large seeds, using near infrared model for predicting oleate content in individual single seeds, high-oleic peanut mutants were identified. Sequencing FAD2A and FAD2B of the mutants along with the wild type revealed that these mutants possessed G448A FAD2A (F435 type FAD2A mutation) and G558A FAD2B (non-F435 type FAD2B mutation). Expression of the wild and mutated type FAD2B in yeast verified that the functional mutation contributed to the high-oleic phenotype in these mutants. The mutants provided additional high-oleic donors to peanut quality improvement.
Developmental signals and environmental stresses regulate carbon distribution in the vegetative and reproductive organs of plants and affect seed yield. Cleistogenes songorica is a xerophytic grass with great potential application value in ecological restoration. However, how carbohydrate transport and distribution during grain filling affect the seed yield of C. songorica under water stress is not clear. The present study showed that the soluble sugar and starch contents of cleistogamous (CL) spikes and chasmogamous (CH) spikes were significantly higher at the milk stage, which was attributed to a significantly higher seed number and seed yield per spike under water stress conditions than under well-watered conditions (P < 0.01). RNA-seq data revealed a total of 54,525 differentially expressed genes (DEGs) under water stress conditions, but only 3744 DEGs were shared among all comparison groups. Weighted gene co-expression network analysis showed that the transport and distribution of carbohydrates were regulated by ABA-responsive genes (CsABA8OX1_1, CsABA8OX1_2, CsABA8OX2_1, CsABA8OX2_2, CsNCED3, CsNCED1_1, CsNCED1_2 and CsNCED4_1) and sugar transport and starch synthesis genes (CsSUS1, CsSUS2, CsSUS3, CsAGP1, CsAGP4, CsAGP5, CsSSS1 and CsSBE5) under water stress conditions. These genes jointly regulated carbohydrate remobilization in sources (stems, leaves and sheaths) to promote grain filling and improve seed yield. The present study helped to clarify the phenotypic, metabolic and transcriptional response mechanisms of vegetative organs, such as stems and leaves, and reproductive organs, such as CL spikes and CH spikes, to promote carbohydrate redistribution under water stress, and it provides theoretical guidance for improving seed yields.
The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.
Thyroid cancer (TC) incidence has increased greatly during the past decades with a few established risk factors, while no study is available that has assessed the association of the Chinese Health Dietary Index (CHDI) with TC. We conducted a 1:1 matched case–control study in two hospitals in Shanghai, China. Diet-quality scores were calculated according to CHDI using a validated and reliable FFQ. Conditional logistic regression analysis and restricted cubic spline analysis were used to reveal potential associations between CHDI score and TC risk. A total of 414 pairs of historically confirmed TC patients and healthy controls were recruited from November 2012 to December 2015. The total score of cases and controls were 67·5 and 72·8, respectively (P < 0·001). The median score of total vegetables, fruit, diary products, dark green and orange vegetables, fish, shellfish and mollusk, soyabean, whole grains, dry bean and tuber in cases was significantly lower than those in controls. Compared with the reference group (≤60 points), the average (60–80 points) and high (≥80 points) levels of the CHDI score were associated with a reduced risk of TC (OR: 0·40, 95 % CI 0·26, 0·63 for 60–80 points; OR: 0·22, 95 % CI 0·12, 0·38 for ≥80 points). In age-stratified analyses, the favourable association remained significant among participants who are younger than 50 years old. Our data suggested that high diet quality as determined by CHDI was associated with lower risk of TC.
To explore whether embryo culture with melatonin (MT) can improve the embryonic development and clinical outcome of patients with repeated cycles after in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) failure, immature oocytes from controlled ovarian superovulation cycles were collected for in vitro maturation (IVM) and ICSI. The obtained embryos were cultured in 0, 10–11, 10–9, 10–7 and 10–5 M MT medium respectively, and 10–9 M was screened out as the optimal concentration. Subsequently, 140 patients who underwent failed IVF/ICSI cycles received 140 cycles of embryo culture in vitro with a medium containing 10–9 M MT, these 140 MT culture cycles were designated as the experimental group (10–9 M group), and the control group was the previous failed cycles of patients (0 M group). The results showed that the fertilization, cleavage, high-quality embryo, blastocyst, and high-quality blastocyst rates of the 10–9 M group were significantly higher than those of the 0 M group (P < 0.01; P < 0.01; P < 0.0001; P < 0.0001; P < 0.0001). To date, in total, 50 vitrified-warmed cycle transfers have been performed in the 10–9 M group and the implantation rate, biochemical pregnancy rate and clinical pregnancy rate were significantly higher than those in the 0 M group (all P < 0.0001). Two healthy infants were delivered successfully and the other 18 women who achieved clinical pregnancy also had good examination indexes. Therefore the application of 10–9 M MT to embryo cultures in vitro improved embryonic development in patients with repeated cycles after failed IVF/ICSI cycles and had good clinical outcomes.
Temperature strongly impacts the rates of physiological and biochemical processes, which in turn can determine the survival and population size of insects. At low temperatures performance is limited, however, cold tolerance and performance at low temperature can be improved after short- or long-term acclimation in many insect species. To understand mechanisms underlying acclimation, we sequenced and compared the transcriptome of the blowfly Chrysomya megacephala under rapid cold hardening (RCH) and long-term cold acclimation (LCA) conditions. The RCH response was dominated by genes related to immune response, spliceosome, and protein processing in endoplasmic reticulum with up-regulation during recovery from RCH. In contrast, LCA was associated with genes related to carbohydrate metabolism and cytoskeleton branching and stabilizing. Meanwhile, mRNA levels of genes related to glycerophospholipid metabolism, and some heat shock proteins (Hsps) were collectively up-regulated by both RCH and LCA. There were more genes and pathway adjustments associated with LCA than RCH. Overall, the transcriptome data provide basic information of molecular mechanisms underpinning the RCH and LCA response. The partly independent molecular responses to RCH and LCA suggest that several avenues for manipulating cold performance exist and RCH might be more effective as it only triggers fewer genes and affects the general metabolisms less. These observations provide some appropriate methods to improve cold tolerance of C. megacephala, and hold promise for developing an extended use of mass-reared C. megacephala with better cold performance as a pollinator of crops at low temperatures.
Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.
Methods
Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.
Results
We observed 51 common diet–gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10−4, Pdepression status = 5.86 × 10−4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet–gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10−3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10−4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).
Conclusions
Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits–gut microbiome interactions with depression and anxiety.
The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.
Taurine (Tau) has many profound physiological functions, but its role and molecular mechanism in muscle cells are still not fully understood. In this study, we investigated the role and underlying molecular mechanism of Tau on protein synthesis and proliferation of C2C12 myoblast cells. Cells were treated with Tau (0, 60, 120, 180 and 240 μM) for 24 h. Tau dose-dependently promoted protein synthesis, cell proliferation, mechanistic target of rapamycin protein (mTOR) phosphorylation and also AT-rich interaction domain 4B (ARID4B) expression, with the best stimulatory effects at 120 μM. LY 294002 treatment showed that Tau promoted ARID4B expression in a phosphoinositide 3-kinase (PI3K)-dependent manner. ARID4B knockdown (by small interfering RNA transfection for 24 h) prevented Tau from stimulating protein synthesis and cell proliferation, whereas ARID4B gene activation (using the CRISPR/dCas9 technology) had stimulatory effects. ARID4B knockdown abolished Tau signalling to mRNA expression and protein phosphorylation of mTOR, whereas ARID4B gene activation had stimulatory effects. Chromatin immunoprecipitation (ChIP)-PCR identified that all of ARID4B, H3K27ac and H3K27me3 bound to the −4368 to –4591 bp site in the mTOR promoter, and ChIP-quantitative PCR (qPCR) further detected that Tau stimulated ARID4B binding to this site. ARID4B knockdown or gene activation did not affect H3K27me3 binding to the mTOR promoter but decreased or increased H3K27ac binding, respectively. Furthermore, ARID4B knockdown abolished the stimulation of Tau on H3K27ac binding to the mTOR promoter. In summary, these data uncover that Tau promotes protein synthesis and proliferation of C2C12 myoblast cells through the PI3K-ARID4B-mTOR pathway, providing a deep understanding of how Tau regulates anabolism in muscle cells.
Previous studies have demonstrated structural and functional changes of the hippocampus in patients with major depressive disorder (MDD). However, no studies have analyzed the dynamic functional connectivity (dFC) of hippocampal subregions in melancholic MDD. We aimed to reveal the patterns for dFC variability in hippocampus subregions – including the bilateral rostral and caudal areas and its associations with cognitive impairment in melancholic MDD.
Methods
Forty-two treatment-naive MDD patients with melancholic features and 55 demographically matched healthy controls were included. The sliding-window analysis was used to evaluate whole-brain dFC for each hippocampal subregions seed. We assessed between-group differences in the dFC variability values of each hippocampal subregion in the whole brain and cognitive performance on the MATRICS Consensus Cognitive Battery (MCCB). Finally, association analysis was conducted to investigate their relationships.
Results
Patients with melancholic MDD showed decreased dFC variability between the left rostral hippocampus and left anterior lobe of cerebellum compared with healthy controls (voxel p < 0.005, cluster p < 0.0125, GRF corrected), and poorer cognitive scores in working memory, verbal learning, visual learning, and social cognition (all p < 0.05). Association analysis showed that working memory was positively correlated with the dFC variability values of the left rostral hippocampus-left anterior lobe of the cerebellum (r = 0.338, p = 0.029) in melancholic MDD.
Conclusions
These findings confirmed the distinct dynamic functional pathway of hippocampal subregions in patients with melancholic MDD, and suggested that the dysfunction of hippocampus-cerebellum connectivity may be underlying the neural substrate of working memory impairment in melancholic MDD.
Kinetic energy flux (KEF) is an important physical quantity that characterizes cascades of kinetic energy in turbulent flows. In large-eddy simulation (LES), it is crucial for the subgrid-scale (SGS) model to accurately predict the KEF in turbulence. In this paper, we propose a new eddy-viscosity SGS model constrained by the properly modelled KEF for LES of compressible wall-bounded turbulence. The new methodology has the advantages of both accurate prediction of the KEF and strong numerical stability in LES. We can obtain an approximate KEF by the tensor-diffusivity model, which has a high correlation with the real value. Then, using the artificial neural network method, the local ratios between the real KEF and the approximate KEF are accurately modelled. Consequently, the SGS model can be improved by the product of that ratio and the approximate KEF. In LES of compressible turbulent channel flow, the new model can accurately predict mean velocity profile, turbulence intensities, Reynolds stress, temperature–velocity correlation, etc. Additionally, for the case of a compressible flat-plate boundary layer, the new model can accurately predict some key quantities, including the onset of transitions and transition peaks, the skin-friction coefficient, the mean velocity in the turbulence region, etc., and it can also predict the energy backscatters in turbulence. Furthermore, the proposed model also shows more advantages for coarser grids.
Laser–plasma accelerators (LPAs) have great potential to realize a compact X-ray free-electron laser (FEL), which is limited by the beam properties currently. Two-color high-intensity X-ray FEL provides a powerful tool for probing ultrafast dynamic systems. In this paper, we present a simple and feasible method to generate a two-color X-ray FEL pulse based on an LPA beam. In this scheme, time-dependent mismatch along the bunch is generated and manipulated by the designed lattice system, enabling FEL lasing at different wavelength within two undulator sections. The time separation between the two pulses can be precisely adjusted by varying the time-delay chicane. Numerical simulations show that two-color soft X-ray FELs with gigawatt-level peak power and femtosecond duration can be generated, which confirm the validity and feasibility of the scheme.
The article aims to estimate and forecast the transmissibility of shigellosis and explore the association of meteorological factors with shigellosis. The mathematical model named Susceptible–Exposed–Symptomatic/Asymptomatic–Recovered–Water/Food (SEIARW) was used to explore the feature of shigellosis transmission based on the data of Wuhan City, China, from 2005 to 2017. The study applied effective reproduction number (Reff) to estimate the transmissibility. Daily meteorological data from 2008 to 2017 were used to determine Spearman's correlation with reported new cases and Reff. The SEIARW model fit the data well (χ2 = 0.00046, p > 0.999). The simulation results showed that the reservoir-to-person transmission of the shigellosis route has been interrupted. The Reff would be reduced to a transmission threshold of 1.00 (95% confidence interval (CI) 0.82–1.19) in 2035. Reducing the infectious period to 11.25 days would also decrease the value of Reff to 0.99. There was a significant correlation between new cases of shigellosis and atmospheric pressure, temperature, wind speed and sun hours per day. The correlation coefficients, although statistically significant, were very low (<0.3). In Wuhan, China, the main transmission pattern of shigellosis is person-to-person. Meteorological factors, especially daily atmospheric pressure and temperature, may influence the epidemic of shigellosis.
I propose a triangular theory of self to characterise the sense of selfhood in the era of social media. According to the theory, the self in the social media era comprises the represented self that is located in the private mind of the person, the registered self that is presented on social media platforms, and the inferred self that is constructed by the virtual audience. The three components of the self interact in dynamic ways to constitute a sense of selfhood and identity specific to the social media era. Autobiographical memory plays a critical role in the development and maintenance of these components. The triangular theory of self introduces new ways to understand and study memory and self in a digitally mediated world.
The Democratic Republic of the Congo (DRC) has one of the highest levels of child undernutrition globally; however, little information exists on the underlying socio-economic inequalities resulting in undernutrition. This study aims to examine the differences in the nutritional statuses of children across different wealth quintiles and explores the association between malnutrition in children and related factors.
Design:
We utilised the 2018 Multiple Indicator Cluster Survey data. We estimated the prevalence of malnutrition across all twenty-six provinces. The study used the WHO 2006 child growth standards to measure stunting, underweight and wasting. We employed a mixed-effect linear model to analyse the association between nutritional status and healthcare accessibility, domestic sanitation, and socio-demographic factors.
Setting:
Twenty-six provinces in the DRC.
Participants:
21 477 children under 5 years of age and 21 828 women of childbearing age in the DRC.
Results:
The national prevalence of underweight, stunting and wasting was found to be 23·33 %, 42·05 % and 5·66 %, respectively. Household wealth and mother’s education level were significantly positively associated with the nutritional statuses of children. Among households in the lowest wealth quintile, residence in urban areas was a protective factor against undernutrition.
Conclusion:
The findings of this study indicate considerable socio-economic inequalities in the nutritional statuses of children under 5 years of age in the DRC, highlighting the need for nutrition promotion as part of maternal and child healthcare. Interventions and policies should include improving nutrition education for less-educated mothers, in particular, in the central provinces of the DRC.
The rice water weevil, Lissorhoptrus oryzophilus Kuschel (Coleoptera: Curculionidae), is a destructive pest that causes damage to rice crops worldwide. The olfactory system is critical for host or mate location by weevils, but only limited information about the molecular mechanism of olfaction-related behaviour has been reported in this insect. In this study, we conducted SMRT-seq transcriptome analysis and obtained 54,378 transcripts, 38,706 of which were annotated. Based on these annotations, we identified 40 candidate chemosensory genes, including 31 odorant-binding proteins (OBPs), six chemosensory proteins (CSPs) and three sensory neuron membrane proteins (SNMPs). Phylogenetic analysis showed that LoryOBPs, LoryCSPs and LorySNMPs were distributed in various clades. The results of tissue expression patterns indicated that LoryOBPs were highly abundant in the antennae, whereas LoryCSPs were highly abundant not only in the antennae but also in the abdomen, head and wings. Our findings substantially expand the gene database of L. oryzophilus and may serve as a basis for identifying novel targets to disrupt key olfactory genes, potentially providing an eco-friendly strategy to control this pest in the future.