Objectives: Pollution exposure is associated with several dermatological conditions including acne, atopic dermatitis, and psoriasis. Antimicrobial peptides (AMPs) are key effectors of innate defense, and some AMPs are involved in inflammatory skin conditions. In this study, we aimed to characterize expression changes of human AMPs under different in-vitro pollution exposures. Methods: RNA-seq profiling was conducted on normal human primary epidermal keratinocytes (NHEK) treated with either a vehicle control, or benzo[a]pyrene (BaP) and on pigmented living skin equivalent models (pLSE) treated with either a vehicle control, ozone, or vehicle exhaust. Differential expressed genes (DEGs) were identified with R scripts. DEGs of PM2.5 were obtained from the literature and the GEO database. Also, 180 human AMP genes were obtained from a UDAMP database. UpSetPlot was used to plot DEGs overlaps. MetaVolcano was used to identify frequently changed AMPs. Results: We used in-house and published transcriptome profiles to identify AMP genes that displayed altered expression under in-vitro pollution exposure. Of the 180 AMP genes under investigation, 37 showed significant changes in expression in at least 1 of the 5 experiments. Using MetaVolcano, 13 AMP genes were identified to be frequently and consistently changed. Several AMPs associated with inflammation and skin diseases were frequently upregulated, including S100A8, S100A9, LCN2, HBD3, RNASE7, and CXCL1. Only 3 frequently downregulated AMP genes were identified, including CXCL14, which is reported to be a noninflammatory AMP that is highly expressed in healthy skin and is downregulated in skin diseases. Conclusions: The data sets suggest that expression of both proinflammatory and homeostatic AMPs can be perturbed by pollution. These findings provide new clues to explain how pollution affects skin innate defense, host–microbe interactions and contributes to abnormal skin conditions. Normalizing aberrant AMP expression may be a potential approach to treat pollution associated skin disorders in the future.

Objectives: Cohort and epidemiology studies have previously revealed potential associations between air pollution exposure and acne vulgaris. However, the molecular mechanisms that drive these associations are not currently well understood. In this study, we compared the molecular signatures of acne and PM2.5-exposed skin to infer whether common underlying biological mechanisms exist. Methods: Acne microarray data sets were downloaded from GEO. RMAExpress was used for microarray normalization, and TMeV was used to identify differential expressed genes (DEGs). A random-effects model in MetaVolcanoR was used to determine fold changes and P values. DEGs of PM2.5-exposed skin-cell models were obtained from the literature. DEGs were compared using GeneOverlap and a custom R script. Analyses of pathways, upstream regulators, and causal networks were conducted using ingenuity pathway analysis (IPA). Results: The molecular signatures of acne skin and the effect of PM2.5 on skin in vitro were compared at 3 levels: (1) gene expression, (2) pathway activity, and (3) upstream regulators. Significant concordant overlaps of both upregulated (P < 3e-23) and downregulated DEGs (P< .005) were observed in acne skin and PM2.5-exposed keratinocytes. However, for the PM2.5-exposed 3D skin model, significant overlap with acne skin was only observed for upregulated DEGs (P < 8e-14). Fold changes of DEGs in both acne and PM2.5-exposed data sets showed significant correlation (Pearson correlation coefficient > 0.6; P < .001). An IPA analysis identified 13 pathways commonly enriched in acne and PM2.5 data sets, including IL17, IL6, Toll receptor PPAR, LXR–RXR, and acute-phase response pathways. Common upstream regulators were further identified including TNFα, NFκB, CAMP, AhR, and IL17A. Finally, causal network analysis revealed several potential hub regulators shared in acne pathogenesis and PM2.5-exposed skin, including HIF1α, TNF, IL1α, and CCL5. Conclusions: Our analysis revealed significant concordant molecular signatures between acne and PM2.5-exposed skin. Biological insights from this study offer clues that build the causal links between air pollution and acne pathogenesis.

The use of molecular markers is one of the most sensitive, powerful technologies for genetic purity assessment of seed lots. In this study, we aimed to develop a set of insertion and deletion (InDel) markers, through bioinformatics approaches, that may effectively distinguish three representative japonica rice (Oryza sativa L.) varieties, Nipponbare, Taichung 65 and Zhonghua11. The published whole-genome sequences of these varieties were aligned using BWA-MEM, followed by manual inspection for InDels of more than ten base pairs in size with the tview function of SAMtools. A set of ten InDel markers were thus identified and then validated by PCR in the three japonica rice varieties and their intercross F1 hybrids. Results showed that the InDel markers developed in this study could reliably distinguish these three japonica rice varieties. These molecular markers together with the detection method developed here can be applied to DNA-based genetic purity evaluation in rice breeding.

An abnormal alanine aminotransferase (ALT) level is predictive of disease and all-cause mortality and may indicate liver injury. Using twin modeling, the genetic and environmental factors that affect human serum ALT levels have been well studied for the populations in the different countries, and the results showed moderate-to-high heritability. However, the heritability of ALT level has not been explored in Chinese population. Thus, we recruited 369 pairs of twins (233 monozygotic and 136 dizygotic) from the Qingdao Twin Registry in China with a median age of 50 years (40−80 years). Correlation analysis and a structural equation model (SEM) were conducted to evaluate the heritability of ALT level. The data for age, gender, body mass index and alcohol consumption were set as covariates. Intrapair correlation in monozygotic twins was 0.64 (95%CI [.56, .71]) and 0.42 (95% CI [.28, .55]) in dizygotic twins. The SEM analysis indicated that 65% (95% CI [57%, 71%]) of the variation in ALT levels can be explained by additive genetics and 35% (95% CI [29%, 44%]) of the variation is attributed to unique environmental factors or residuals. Shared environmental influences were not significant. In conclusion, serum ALT variations exhibited strong genetic effects. The variation could also be explained by unique environmental factors. However, shared environmental factors have a minor impact on the serum ALT level.

This study compared late bilinguals’ pitch feedback control in L1 and L2 production using a frequency-altered feedback paradigm in which participants read target words while presented with unexpected pitch-shift in their voice feedback. Variables of language (L1 or L2) and perturbation magnitudes (0, 100, 200, or 400 cents) were manipulated. Behaviorally, participants produced larger magnitudes but longer latencies of vocal compensation in L2 than in L1 production, suggesting that L2 pitch feedback control has greater importance but lower efficiency. Event-related potential findings demonstrated that 400-cent shifts elicited greater N1 amplitudes than those in the 0-cent baseline condition in L1 production. This difference was non-significant in L2 production, implying different neural processing of unaltered feedback and externally-generated feedback in L1 and L2 production. Participants’ vocal compensation and P2 amplitudes were similarly modulated by pitch-shift in L1 and L2 production, implying a similar gating mechanism to correct internal and external errors.

As optical parametric chirped pulse amplification has been widely adopted for the generation of extreme intensity laser sources, nonlinear crystals of large aperture are demanded for high-energy amplifiers. Yttrium calcium oxyborate (YCa4O(BO3)3, YCOB) is capable of being grown with apertures exceeding 100 mm, which makes it possible for application in systems of petawatt scale. In this paper, we experimentally demonstrated for the first time to our knowledge, an ultra-broadband non-collinear optical parametric amplifier with YCOB for petawatt-scale compressed pulse generation at 800 nm. Based on the SG-II 5 PW facility, amplified signal energy of approximately 40 J was achieved and pump-to-signal conversion efficiency was up to 42.3%. A gain bandwidth of 87 nm was realized and supported a compressed pulse duration of 22.3 fs. The near-field and wavefront aberration represented excellent characteristics, which were comparable with those achieved in lithium triborate-based amplifiers. These results verified the great potential for YCOB utilization in the future.

Plasma vertical displacement control is essential for the stable operation of tokamak devices. The traditional plasma vertical displacement calculation method is not suitable for balancing speed and accuracy simultaneously, which is necessary for real-time feedback control. In this study, neural networks are used to rapidly detect vertical displacement recognition. Based on a fully connected neural network, the vertical displacement calculation model is trained and tested using magnetic data of approximately 2000 shots. To compare the effects of different inputs on vertical displacement calculation, different magnetic measurement diagnostic signals are used to train and test the model. Compared with a full magnetic measurement dataset, 39 magnetic measurement signals (38 magnetic probes and plasma current) show better accuracy with mean square error <0.0005. The model is tested using historical experimental data, and it demonstrates accurate vertical displacement calculation even in the case of a vertical displacement event. In general, neural network algorithm has great application potential in vertical displacement calculation.

Electron resonant interactions with electromagnetic whistler-mode waves play an important role in electron flux dynamics in various space plasma systems: planetary radiation belts, bow shocks, solar wind and magnetic reconnection regions. Two key wave characteristics determining the regime of wave–particle interactions are the wave intensity and the wave coherency. The classical quasi-linear diffusion approach describes well electron diffusion by incoherent and low-amplitude waves, whereas the nonlinear resonant models describe electron phase bunching and trapping by highly coherent intense waves. This study is devoted to the investigation of the regime of electron resonant interactions with incoherent but intense waves. Although this regime is characterized by electron diffusion, we show that diffusion rates scale linearly with the wave amplitude, $D\propto B_w$, in contrast to the quasi-linear diffusion scaling $D_{QL}\propto B_w^2$. Using observed wave amplitude distributions, we demonstrate that the quasi-linear diffusion model significantly overestimates electron scattering by incoherent, but intense whistler-mode waves. We discuss the results obtained in the context of simulations of long-term electron flux dynamics in space plasma systems.

One challenge facing humans (and nonhuman animal) is that some options that appear attractive locally may not turn out best in the long run. To analyse this human learning problem, we explore human performance in a dynamic decision-making task that places local and global rewards in conflict. We found that experiences that included previous choices and rewards are not easily incorporated into people’s strategy to enhance their performance. Our results suggest that humans are easily driven by concerns about recent feedback, and that choice of a suboptimal behaviour option may be overcome by providing informative cues that indicate a clear immediate outcome for a better option.

An initially perturbed interface between two fluids of different densities is usually unstable when driven by an acceleration or a shock wave; it is known as a Rayleigh–Taylor instability or a Richtmyer–Meshkov instability. One of the most significant issues in these instabilities is the spatiotemporal development of fingers generated at the interface, which plays an important role in both scientific research (e.g. supernova explosion) and engineering applications (e.g. inertial confinement fusion). Accurate theoretical solution of these interfacial fingers remains as an unsolved and challenging problem since Taylor's seminal work more than seven decades ago. This paper reports a unified theory established for such phenomena by combining the classical potential-flow theory and a dual-source model to address the long-standing difficulty highlighted by the initial-value sensitivity and strong nonlinearity. It is the first time for a theory to accurately predict the long-time developments in both growth rate and shape curvature of interfacial fingers at all density ratios in two and three dimensions. Moreover, the new theory clearly reveals the nonlinear coupling mechanism for interfacial evolution, and especially explains the origin of overshot in the growth rate curve.

This work elucidated the performance and mechanisms of Pb2+ adsorption by kaolinite, montmorillonite, goethite and ferrihydrite using batch experiments. The contributions of various adsorption mechanisms were quantified using a stepwise extraction method. Several characterizations (scanning electron microscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, point of zero charge analysis and X-ray fluorescence) were utilized to analyse the physicochemical properties and the potential adsorption mechanisms. The results indicated that the adsorption processes of montmorillonite and goethite approached equilibrium within 20 min, while 60 min were required for the adsorption processes of kaolinite and ferrihydrite. The adsorption processes of Pb2+ by the four minerals best fit the pseudo-second order model. The adsorption capacities of the four minerals for Pb2+ followed the order: montmorillonite > goethite > ferrihydrite > kaolinite, and the maximum adsorption capacities were 69.20, 46.95, 34.32 and 18.62 mg g–1, respectively. The stepwise extraction test showed that the adsorption mechanism of Pb2+ was dominated by ion exchange for montmorillonite, precipitation and complexation for goethite and complexation for kaolinite and ferrihydrite.

High-power continuous-wave ultraviolet lasers are useful for many applications. As ultraviolet laser sources, the wavelength switching capability and compact structure are very important to extend the applicability and improve the flexibility in practical applications. In this work, we present two simple and relatively compact schemes by laser diode pumping to obtain a watt-level single-wavelength 348.7-nm laser and discrete wavelength tunable ultraviolet lasers around 349 nm (from 334.7 to 364.5 nm) by intracavity frequency doubling based on Pr3+:YLF and $\unicode{x3b2}$ -BBO crystals. The maximum output power of the single-wavelength 348.7-nm laser is 1.033 W. The output powers of the discrete wavelength tunable lasers are at the level of tens of milliwatts, except for two peaks at 348.7 and 360.3 nm with output powers of approximately 500 mW. In addition, simulations are carried out to explain the experimental results and clarify the tuning mechanisms.

Using data from three automatic weather stations (LGB69, Eagle and Dome A) from distinctly different climatological zones along the CHINARE (Chinese National Antarctic Research Expedition) traverse route from Zhongshan Station to Dome A, we investigated the characteristics of meteorological conditions and subsurface heat conduction. Spatial analysis indicated decreasing trends in air temperature, relative humidity and wind speed from the coastal katabatic wind zone to the inland plateau region, and air temperatures clearly showed a strong daily variability in winter, suggesting the effect from the fluctuation in the Antarctic atmospheric system. We also analyzed the optimal response time of the 1 and 3 m depth snow temperatures to the 0.1 m depth snow temperature for each site under clear/overcast and day/night situations. This showed an important enhancement to the heat transfer from shortwave radiation penetration. Using an iterative optimization method, we estimated the subsurface heat conduction variations along the transect. This was ~3–5 W m–2. Multiple maxima in daily mean subsurface fluxes were found in winter, with a typical value above 2 W m–2, while a single minimum value under –2 W m–2 was found in summer. On an annual scale, a larger mean loss of subsurface heat conduction was observed in the inland plateau compared to in the coastal katabatic area. Finally, we discussed the possible influences of turbulent and radiant transport on the vertical heat response and confirmed the wind enhancement on the growth of thermal conductivity. This preliminary study provides a brief perspective and an important reference for studying subsurface heat conduction in inland areas of Antarctica.

Meristems in land plants share conserved functions but develop highly variable structures. Meristems in seed-free plants, including ferns, usually contain one or a few pyramid-/wedge-shaped apical cells (ACs) as initials, which are lacking in seed plants. It remained unclear how ACs promote cell proliferation in fern gametophytes and whether any persistent AC exists to sustain fern gametophyte development continuously. Here, we uncovered previously undefined ACs maintained even at late developmental stages in fern gametophytes. Through quantitative live-imaging, we determined division patterns and growth dynamics that maintain the persistent AC in Sphenomeris chinensis, a representative fern. The AC and its immediate progenies form a conserved cell packet, driving cell proliferation and prothallus expansion. At the apical centre of gametophytes, the AC and its adjacent progenies display small dimensions resulting from active cell division instead of reduced cell expansion. These findings provide insight into diversified meristem development in land plants.

In this study, we investigate the differences between two transient, three-dimensional, thermomechanically coupled ice-sheet models, namely, a first-order approximation model (FOM) and a ‘full’ Stokes ice-sheet model (FSM) under the same numerical framework. For all numerical experiments, we take the FSM outputs as the reference values and calculate the mean relative errors in the velocity and temperature fields for the FOM over 100 years. Four different boundary conditions (ice slope, geothermal heat flux, basal topography and basal sliding) are tested, and by changing these parameters, we verify the thermomechanical behavior of the FOM and discover that the velocity and temperature biases of the FOM generally increase with increases in the ice slope, geothermal heat flux, undulation amplitude of the ice base, and with the existence of basal sliding. In addition, the model difference between the FOM and FSM may accumulate over time, and the spatial distribution patterns of the relative velocity and temperature errors are in good agreement.

In this work, we propose using an ensemble Kalman method to learn a nonlinear eddy viscosity model, represented as a tensor basis neural network, from velocity data. Data-driven turbulence models have emerged as a promising alternative to traditional models for providing closure mapping from the mean velocities to Reynolds stresses. Most data-driven models in this category need full-field Reynolds stress data for training, which not only places stringent demand on the data generation but also makes the trained model ill-conditioned and lacks robustness. This difficulty can be alleviated by incorporating the Reynolds-averaged Navier–Stokes (RANS) solver in the training process. However, this would necessitate developing adjoint solvers of the RANS model, which requires extra effort in code development and maintenance. Given this difficulty, we present an ensemble Kalman method with an adaptive step size to train a neural-network-based turbulence model by using indirect observation data. To our knowledge, this is the first such attempt in turbulence modelling. The ensemble method is first verified on the flow in a square duct, where it correctly learns the underlying turbulence models from velocity data. Then the generalizability of the learned model is evaluated on a family of separated flows over periodic hills. It is demonstrated that the turbulence model learned in one flow can predict flows in similar configurations with varying slopes.

Our research question was to evaluate the chromosome concordance of trophectoderm (TE) biopsy with noninvasive chromosome screening (NICS) using embryo culture medium renewed twice on Day 3 (D3) and Day 4 (D4). In this study, we evaluated 64 cycles with 223 biopsied blastocysts. These were categorized into two groups based on replacing embryo culture medium on D3 (control group) or on D3 and D4 (experimental group). The fundamental characteristics and main outcomes were compared. The concordance rates of NICS results with TE biopsy were determined according to next generation sequencing results. In total, 103 experimental and 120 control embryo cultures were collected, and the euploid status was analyzed using NICS technology. The overall concordance rates with TE biopsy of the experimental and control groups were 0.86 and 0.75, respectively. Statistically significant difference was found between the two groups. An additional medium renewal of the D4 embryo culture can improve the concordance of NICS with TE biopsy.