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Infant colic is a condition of unknown cause which can result in carer distress and attachment difficulties. Recent studies have implicated the gut microbiota in infant colic, and certain probiotics have demonstrated possible efficacy. We aim to investigate whether the intestinal microbiota composition in infants with colic is associated with cry/fuss time at baseline, persistence of cry/fuss at 4-week follow-up, or child behavior at 2 years of age. Fecal samples from infants with colic (n = 118, 53% male) were analyzed using 16S rRNA sequencing. After examining the alpha and beta diversity of the clinical samples, we performed a differential abundance analysis of the 16S data to look for taxa that associate with baseline and future behavior, while adjusting for potential confounding variables. In addition, we used random forest classifiers to evaluate how well baseline gut microbiota can predict future crying time. Alpha diversity of the fecal microbiota was strongly influenced by birth mode, feed type, and child gender, but did not significantly associate with crying or behavioral outcomes. Several taxa within the microbiota (including Bifidobacterium, Clostridium, Lactobacillus, and Klebsiella) associate with colic severity, and the baseline microbiota composition can predict further crying at 4 weeks with up to 65% accuracy. The combination of machine learning findings with associative relationships demonstrates the potential prognostic utility of the infant fecal microbiota in predicting subsequent infant crying problems.
In engineering design, surrogate models are often used instead of costly computer simulations. Typically, a single surrogate model is selected based on the previous experience. We observe, based on an analysis of the published literature, that fitting an ensemble of surrogates (EoS) based on cross-validation errors is more accurate but requires more computational time. In this paper, we propose a method to build an EoS that is both accurate and less computationally expensive. In the proposed method, the EoS is a weighted average surrogate of response surface models, kriging, and radial basis functions based on overall cross-validation error. We demonstrate that created EoS is accurate than individual surrogates even when fewer data points are used, so computationally efficient with relatively insensitive predictions. We demonstrate the use of an EoS using hot rod rolling as an example. Finally, we include a rule-based template which can be used for other problems with similar requirements, for example, the computational time, required accuracy, and the size of the data.
Imprinted genes uniquely drive and support fetoplacental growth by controlling the allocation of maternal resources to the fetus and affecting the newborn’s growth. We previously showed that alterations of the placental imprinted gene expression are associated with suboptimal perinatal growth and respond to environmental stimuli including socio-economic determinants. At the same time, maternal psychosocial stress during pregnancy (MPSP) has been shown to affect fetal growth. Here, we set out to test the hypothesis that placental imprinted gene expression mediates the effects of MPSP on fetal growth in a well-characterized birth cohort, the Stress in Pregnancy (SIP) Study. We observed that mothers experiencing high MPSP deliver infants with lower birthweight (P=0.047). Among the 109 imprinted genes tested, we detected panels of placental imprinted gene expression of 23 imprinted genes associated with MPSP and 26 with birthweight. Among these genes, five imprinted genes (CPXM2, glucosidase alpha acid (GAA), GPR1, SH3 and multiple ankyrin repeat domains 2 (SHANK2) and THSD7A) were common to the two panels. In multivariate analyses, controlling for maternal age and education and gestational age at birth and infant gender, two genes, GAA and SHANK2, each showed a 22% mediation of MPSP on fetal growth. These data provide new insights into the role that imprinted genes play in translating the maternal stress message into a fetoplacental growth pattern.
The magnetometer measurements taken by Cassini have confirmed the unusual character of Saturn’s internal magnetic field known from previous flybys and have revealed additional properties that suggest a rather unique dynamo in this planet. Within measurement uncertainty, the internal magnetic field is completely symmetric with respect to Saturn’s spin axis. The upper limit on the tilt of the magnetic dipole could be reduced from 1 to 0.06 degree. Moreover, only axisymmetric quadrupole and octupole moments are needed to fit the data. The lack of non-axisymmetric field components prevents a reliable determination of the bulk rotation rate of Saturn’s deep interior. Using data from Cassini’s closest approach to Saturn during orbit insertion, the magnetic moments of degrees four and five have been determined. The spatial power spectrum shows a zig-zag pattern with high power in odd spherical harmonic degrees and low power in even degrees. Compared to a simple dipole field, this corresponds to a concentration of magnetic flux towards the rotation poles. The flux concentration becomes progressively more pronounced when the field is continued into the interior. Comparison of the Cassini field model with that based on the Pioneer 11 and Voyager 1 and 2 measurements taken roughly 30 years earlier suggests that the secular variation of Saturn’s field is at least one order of magnitude slower than that of the Earth. A viable explanation for most of the unusual field properties is that a stably stratified and electrically conducting layer, formed by a partial demixing of helium from metallic hydrogen, exists on top of a “standard” dynamo in Saturn’s deep interior. This dynamo, driven by thermal and compositional convection, generates a magnetic field that is moderately asymmetric and time dependent. Rapid time variations and non-axisymmetric field components are filtered out in the stable layer by a skin effect. This model also implies that the top of the active dynamo may be located rather deep in Saturn’s interior and the geometric drop-off of the dipole strength with the radius cubed could explain the unexpectedly low field strength at Saturn’s surface. The stable layer model does not provide an explanation for the magnetic flux concentration towards the poles. Strong differential rotation in the dynamo region can have this effect, but a physical mechanism for such a flow state remains to be explored. From magnetic measurements to be taken during the very close approaches in the Grand Finale of the Cassini mission, we can expect to characterize Saturn’s magnetic field up to at least spherical harmonic degree nine and possibly to detect weak non-axisymmetric field components, which would enable an accurate determination of Saturn’s rotation period.
Coherent cuboidal B2 nanoprecipitation in body-centered cubic (BCC)-based high-entropy alloys (HEAs) is important for the improvement of mechanical strength. The present work primarily investigated the effect of Ti substitution for Al on the cuboidal B2 nanoprecipitates in BCC Al0.7NiCoFeCr2 HEAs. A series of (Al,Ti)0.7NiCoFeCr2 HEAs with different Al/Ti ratios were prepared by suction-cast processing, and their microstructures and mechanical properties were then characterized comprehensively. It was found that the substitution of Ti for Al can change the phase structures of ordered precipitation, from the B2-AlNi to a highly ordered L21-Ni2AlTi phase. Especially, a small amount addition of Ti (≤4.2 at.%, Al/Ti ratio ≥2/1) renders the HEAs with cuboidal L21 nanoparticles coherently precipitated into the BCC matrix, which is attributed to the moderate lattice misfit (ε = 0.5–0.6%) between BCC and L21 phases. HEAs with such coherent microstructures exhibit high compressive yield strength of about 1700–1800 MPa. When the Ti content reaches up to 6.25 at.%, the matrix of the alloy will be turned into the σ phase, rather than BCC, leading to a heavy brittleness.
In September 2016, the annual meeting of the International Union for Quaternary Research’s Loess and Pedostratigraphy Focus Group, traditionally referred to as a LoessFest, met in Eau Claire, Wisconsin, USA. The 2016 LoessFest focused on “thin” loess deposits and loess transportation surfaces. This LoessFest included 75 registered participants from 10 countries. Almost half of the participants were from outside the United States, and 18 of the participants were students. This review is the introduction to the special issue for Quaternary Research that originated from presentations and discussions at the 2016 LoessFest. This introduction highlights current understanding and ongoing work on loess in various regions of the world and provides brief summaries of some of the current approaches/strategies used to study loess deposits.
With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order to derive the features of interest in the observations. A number of automated detection methods and algorithms have been developed for solar activities, based on the image processing and machine learning techniques. In this paper, after briefly reviewing some automated detection methods, we describe our efficient and versatile automated detection method for solar filaments. It is able not only to recognize filaments, determine the features such as the position, area, spine, and other relevant parameters, but also to trace the daily evolution of the filaments. It is applied to process the full disk Hα data observed in nearly three solar cycles, and some statistic results are presented.
Previous studies show inconsistent associations between α-linolenic acid (ALA) and risk of CHD. We aimed to examine an aggregate association between ALA intake and risk of CHD, and assess for any dose–response relationship. We searched the PubMed, EMBASE and Web of Science databases for prospective cohort studies examining associations between ALA intake and CHD, including composite CHD and fatal CHD. Data were pooled using random-effects meta-analysis models, comparing the highest category of ALA intake with the lowest across studies. Subgroup analysis was conducted based on study design, geographic region, age and sex. For dose–response analyses, we used two-stage random-effects dose–response models. In all, fourteen studies of thirteen cohorts were identified and included in the meta-analysis. The pooled results showed that higher ALA intake was associated with modest reduced risk of composite CHD (risk ratios (RR)=0·91; 95 % CI 0·85, 0·97) and fatal CHD (RR=0·85; 95 % CI 0·75, 0·96). The analysis showed a J-shaped relationship between ALA intake and relative risk of composite CHD (χ2=21·95, P<0·001). Compared with people without ALA intake, only people with ALA intake <1·4 g/d showed reduced risk of composite CHD. ALA intake was linearly associated with fatal CHD – every 1 g/d increase in ALA intake was associated with a 12 % decrease in fatal CHD risk (95 % CI −0·21, −0·04). Though a higher dietary ALA intake was associated with reduced risk of composite and fatal CHD, the excess composite CHD risk at higher ALA intakes warrants further investigation, especially through randomised controlled trials.
Bipolar disorder is a highly heritable polygenic disorder. Recent
enrichment analyses suggest that there may be true risk variants for
bipolar disorder in the expression quantitative trait loci (eQTL) in the
We sought to assess the impact of eQTL variants on bipolar disorder risk
by combining data from both bipolar disorder genome-wide association
studies (GWAS) and brain eQTL.
To detect single nucleotide polymorphisms (SNPs) that influence
expression levels of genes associated with bipolar disorder, we jointly
analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls)
and a genome-wide brain (cortical) eQTL (193 healthy controls) using a
Bayesian statistical method, with independent follow-up replications. The
identified risk SNP was then further tested for association with
hippocampal volume (n = 5775) and cognitive performance
(n = 342) among healthy individuals.
Integrative analysis revealed a significant association between a brain
eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes
factor = 5.48; bipolar disorder P =
5.85×10–5). Follow-up studies across multiple independent
samples confirmed the association of the risk SNP (rs6088662) with gene
expression and bipolar disorder susceptibility (P =
3.54×10–8). Further exploratory analysis revealed that
rs6088662 is also associated with hippocampal volume and cognitive
performance in healthy individuals.
Our findings suggest that 20q11.22 is likely a risk region for bipolar
disorder; they also highlight the informative value of integrating
functional annotation of genetic variants for gene expression in
advancing our understanding of the biological basis underlying complex
disorders, such as bipolar disorder.
Rumination is an important cognitive risk factor for onset and relapse of depression. However, no studies have employed a dimensional approach in investigating the neural correlates of rumination and the relationship with depression.
Non-clinical healthy subjects (n = 306), who completed the classical rumination and depression scales, were studied using voxel-based morphometry and regional homogeneity (ReHo). Subsequently, mediation analysis was conducted to examine the influence of rumination on the relationship between brain structure and depression. Moreover, depressive patients (n = 60) and a control group (n = 63) of comparable age and education were studied with regions of interest that were identified in the healthy individuals.
For healthy individuals, regional grey-matter volume (rGMV) of dorsolateral prefrontal cortex (DLPFC) and parahippocampal gyrus (PHG) were positively correlated with rumination. In addition, rumination had a mediating effect on the relationship between the DLPFC and PHG and depression. Moreover, ReHo analysis showed that rumination had a significantly negative correlation with functional homogeneity of DLPFC. However, compared to the control group, depressed patients showed significant decrease of rGMV in the DLPFC and PHG and there was a significant negative correlation between DLPFC volume and depressive rumination.
Increased DLPFC volume (decreased ReHo) in healthy individuals while decreased in depression indicated the trend of DLPFC from inefficient inhibition (‘overload state’) to impaired regulatory mechanism (‘paralysis state’). This finding might elucidate when and why healthy individuals would develop sustained negative mood and depression eventually.
The goal of this research is to synthesize novel linear and hyperbranched polythiophene derivatives containing diketopyrrolopyrrole (DPP) as linking groups, and to investigate thermal, optical, electrochemical, and photovoltaic properties of those derivatives. Polymers with high regioregularity were synthesized via the Universal Grignard metathesis polymerization. Those linear or hyperbranched polythiophenes containing DPP bridging moieties showed higher molecular weights and better thermal stability compared with normal P3HT. The UV-vis absorption spectra of the DPP-containing polymers are similar to that of P3HT in film state, while they show distinct attenuation in fluorescent emission. Finally, all polymers were blended with PC61BM and used as active layers for fabrication of inverted solar devices. The devices based on those DPP-containing polythiophenes revealed the open-circuit voltage (VOC) of 0.55–0.58 V, the short-circuit current (JSC) of 8.62–16.21 mA/cm2, the fill factor (FF) of 36–41%, and the power conversion efficiency (PCE) of 1.73–3.74%.
The advancement of computational tools for material property predictions enables broad search of novel materials for various energy-related applications. However, challenges still exist in accurately predicting the mean free paths (MFPs) of electrons and phonons in a high-throughput frame for thermoelectric property predictions, which largely hinders the computation-driven search for novel materials. In this work, this need is eliminated under the small-grain-size limit, in which these MFPs are restricted by the grain sizes within a bulk material. A new criterion for ZT evaluation is proposed for general nanograined bulk materials and is demonstrated with representative oxides.
Triple supermassive black holes (SMBH) can form during the hierarchical mergers of massive galaxies with an existing binary. Perturbations by a third black hole may accelerate the merging process of an inner binary, for example through the Kozai mechanism. We analyze the evolution of simulated hierarchical triple SMBHs in galactic centers, and find resonances in the evolution of the semi-major axis, the eccentricity and the inclination, for both the inner and the outer orbits of the triple system, which are not only Kozai like. Through resonant oscillations, SMBH can trigger a significant increase of the inner SMBH binary eccentricity shortening the merger timescale expected from gravitational wave (GW) emission. As hierarchical triple SMBHs may be frequent in massive galaxies, the influence of orbital resonances is of great importance to our understanding of black hole coalescence and gravitational wave detection. Although Kozai mechanism is believed to play an important role in this process, detailed studies on the pattern of these resonances is necessary.
For structural investigation, highly (112) oriented tetragonal Cu2ZnSnS4 (CZTS) thin films on hexagonal sapphire (0001) single crystal substrates were obtained by radio frequency (RF) magnetron sputtering. The influences of the deposition parameters, such as substrate temperature (Tsub) and working Ar pressure (PAr) on the chemical composition and structural properties of as deposited CZTS films were investigated. The film sputtered at 500°C has the only orientation of (112), also, it bears the best structural quality with pure CZTS phase and an estimated band gap of 1.51eV.